Unevenly distributed rainfall leads to reduced potato water productivity (WP) under rainfed production. Understanding practices that can increase WP is vital. Objectives were to (i) understand seasonal variables that influence WP under rainfed conditions and (ii) the effect of the integration of cultivar, locality, mulch on potato WP. The study was under two agroecological zones Appelsbosch (Mbalenhle locality), and Swayimane (Stezi, and Mbhava locality), under smallholder. A split plot, in a randomized complete block design experiment, consists of mulching (mulch and not mulch), and selected cultivars. Soil water content (SWC), yield, and climatic conditions were collected, water use (ET) and WP were calculated. Rainfall, ET, and SWC had a significant influence on seasonal WP. Cultivar x mulch x locality had an insignificant effect on WP, however, locality x cultivars significantly altered potato WP. Localities that had lower vapor pressure deficit (VPD), low relative humidity, and sandy soil had higher potato WP of 14.53 kg m-3. The findings suggest that localities that have less atmospheric dryness and cultivars that show stability of yield across seasons can be an easy-to-apply practice for increasing potato WP under a resource-limited environment. Mulch is important when the distribution of intra-annual rainfall does not match crop water requirements.

Extreme Ultraviolet (EUV) photolithography process, is a cornerstone of semiconductor manufacturing and operates under demanding precision standards realized via nanometer-level overlay (OVL) error modeling. This procedure allows the machine to anticipate and correct OVL errors before impacting the wafer, thereby facilitating near-optimal image exposure while simultaneously minimizing the overall OVL error. Such models are usually high dimensional and exhibit rigorous statistical phenomena such as collinearities that play a crucial role in the process of tuning their parameters. Ordinary Least Squares (OLS) is the most widely used method for parameters tuning of Overlay models but in most cases it fails to compensate for such phenomena. In this paper we propose the usage of Ridge Regression, a widely known Machine Learning (ML) algorithm especially suitable for datasets that exhibit high multicollinearity. The proposed method has been applied in perturbed data from a 300 mm wafer fab and the results show reduced residuals when ridge regression is applied instead of OLS.

This research centres on advancing the utilisation of a novel Deep Ensemble model called RicEns-Net for predicting crop yields through sophisticated multi-modal data engineering. Initially, data for the study were acquired from Ernst \& Young (EY), a prominent global technology and management consulting firm, as part of their annual data science challenge (EY Open Science Challenge 2023). The predictive models leverage multi-modal data by integrating radar and optical-type remote sensing data alongside meteorological data to create supplementary features essential for predicting crop yield. The primary data features are derived from spectral indices extracted from Sentinel 2 satellites, while more advanced features are generated through combinations and interactions of these fundamental features. Furthermore, data from Sentinel 1 and 3, along with meteorological measurements such as surface temperature and rainfall, account for the intricate natural factors influencing crop yield, creating a comprehensive set of data features based on existing research. To tackle the complexity introduced by numerous data features, extensive data engineering was conducted to identify the most predictive features among 100+ and mitigate the "curse of dimensionality," resulting in 15 features from 5 different modalities. The proposed RicEns-Net comprises multiple machine learning algorithms in a deep ensemble approach to leverage the best features of each of these techniques, achieving optimal performance. The proposed model achieves an MAE value of 341 kg/Ha for prediction, surpassing the performance of the EY Open Science Challenge 2023 winner models and state-of-the-art deep/machine learning approaches.

Understanding the relationship between sugar yield and related traits is crucial for successfully breeding this important industrial crop. Thirteen sugar beet monogram cultivars were evaluated during 2018-2019. The study used a split-factorial design with two planting dates as the main plot, while cultivars and harvesting dates were laid out as CRBD as subplots. Significant differences were observed among the cultivars for all measured traits. The genetic correlation coefficients showed the highest positive and significant correlations between sugar yield and white sugar yield (WSY) (0.88**), sugar content (SC) (0.71**), and white sugar content (0.65**). Conversely, the highest negative and significant correlations were found between sugar yield and molasses sugar content (-0.62**), alkalinity coefficient (-0.58**), and root potassium content (-0.52**). In the stepwise multiple regression analysis, white sugar content (WSC), sugar content (SC), root α-amino nitrogen content, and root yield were included in the regression model, explaining 84% of the total variance in the sugar yield. Path analysis revealed that sugar content (1.12) and root yield (1.03) had the highest direct effects on sugar yield. These traits can be used as key criteria for developing superior hybrids with high economic productivity, thereby accelerating the selection process in various breeding programs.

Accordingly, a lot of dry direct seeding rice would be dense planted, that the initial seedling quantity could approach or even exceed the targeted effective panicle number. While limit information is available to evaluate the effects of involved novel nitrogen application methods, that total nitrogen once applied at a determined leaf age stage, on the yield formation traits of such dense planted dry direct seeding rice. The two-year experiments with total 180 kg ha-1 nitrogen once applied time treatments at sixth (L6), seventh (L7), eighth (L8), ninth (L9) and tenth (L10) leaf age stages were carried out. Results showed that the above-ground dry matter weight at maturity and grain yield of L8 was 2.1% ~ 11.8% and 4.0% ~ 9.9% higher than those of other treatments. Compared to other treatments, the higher above-ground dry matter weight after heading stage, bigger mean leaf area index with higher leaf area index at heading stage, increased leaf area duration, crop growth rate and net assimilation rate from jointing to heading period were important traits of higher grain yield formation of L8. In addition, the L8 had relative higher grain-leaf ratio traits than other treatments. Overall, a total 180 kg ha-1 nitrogen with mixed urea and compound fertilizer once applied at eighth leaf age stage would be suggest a useful high yield cultivation method for dense planted dry direct seeding rice in rice-wheat rotation system.

This study aimed to explore the genetic information about the yield traits in perennial Chinese rice "Shendao3^#" and provide a series of theoretical bases for the innovative utilization of perennial Chinese rice germplasm. The F₂ population derived from the cross between perennial Chinese rice "Shendao3^#" and one annual rice "XiqingzaoB" was developed to identify QTLs’ underlying yield-related traits. Fifteen yield traits including plant height, panicle plant^-1, and thousand-grain weight were measured for the QTL mapping. The software packages Excel 2010, GraphpadPrism 5.0, and QTLIciMapping 4.10 were used to perform the phenotypic data analysis, construction of molecular map, and QTL mapping, respectively. Results indicated 15 yield-related traits displaying normal distribution and belonging to quantitative trait inheritance. A total of 25 QTLs associated with the yield-related traits and 26 epistatic QTLs were detected on the whole genome except for the 6th and 12th chromosomes. This finding explained phenotypic variance with ranging from 4.21% to 27.30% and 1.15% to 19.30%, respectively. Six pleiotropic QTL (chromosomal regions) underlying two or more yield-related traits were detected on the 1st , 4th, 7th, 8th, and 11th chromosomes, respectively. Among 25 QTLs underlying a single yield-related trait, 11 were primarily identified in the perennial Chinese rice "Shendao3^#". All QTLs underlying 15 yield-related traits followed the genetic model of additive, dominant, and digenic epistatic of additive by additive, additive by dominant, dominant by additive, and dominant by dominant. This work can serve as a good foundation for yield-related gene mining and its utilization in breeding the perennial Chinese rice "Shendao3^#".

The decline in global pollinator populations has raised serious concerns about the sustainability of ecosystems and agricultural productivity. Urban environments, often characterized by habitat loss and environmental stressors, are considered challenging habitats for pollinators. However, urban green spaces, including street and ornamental trees, can play a crucial role in supporting pollinators by providing essential food resources. This study aimed to evaluate the sugar and amino acid production of eight urban tree species to determine their potential contributions to pollinator nutrition. Our findings revealed significant variability among species regarding nectar volume, sugar content, and amino acid composition, emphasizing the importance of considering multiple factors when assessing the utility of floral resources. Consequently, Tilia amurensis, Heptacodium miconioides, Aesculus turbinata, and Wisteria floribunda demonstrated superior potential in supporting urban pollinator communities. Contrastingly, Sorbus commixta, Styrax japonicus, and Cornus kousa, often favored for their aesthetic appeal, showed less potential. This study underscores the need for urban tree selection that prioritizes species that provide diverse and abundant nutritional resources for pollinators while balancing aesthetic and ecological values. Our results offer a foundation for better-informed urban biodiversity management and contribute to creating pollinator-friendly urban environments.

We conclude that Hbr not only favored growth, but also colonization with R. intraradices and consequently biomass production, and N and P content in plant tissue. The growth response and nutrient exchange suggest interdependence between brassinosteroids and the endomycorrhizal fungus.

Apple-tree (Malus × domestica Borkh.) belongs to the genus Rosaceae. Due to its adaptability and tolerance to different soil and climatic conditions, it is cultivated worldwide for fresh consump-tion. Therefore, the priorities of apple growers are the high-quality of fruits and stable yield for high production. In total about 90 to 95 percent of fruits should fall or be eliminated from apple trees to avoid overcropping and poor-quality fruits. Several technologies such as handwork, me-chanically or chemical substances are used for fruit and bud elimination. The most profitable in commercial orchards is the use of chemicals for elimination, but due to the European Green Deal more environmentally sustainable solutions are required. Elimination of fruitlets is influenced by several factors. Additionally, the apple trees have the self-elimination mechanism. This is de-termined by apple genotype, physiological futures and genetics. This review focuses on the bio-logical factors and genetics mechanisms in apple yield self-regulation for better understanding the regulatory mechanism of fruitlets abscission for future breeding programs targeted on self-regulating yield apple varieties

The study investigates the economic feasibility and farmer acceptance of utilizing treated wastewater (TWW) for agricultural irrigation, particularly in the Northern Jordan Valley. Despite its potential to mitigate water scarcity, concerns persist regarding its impact on soil health, crop yield, and land utilization, hindering widespread adoption. The research aims to measure farm profitability and farmers' willingness to embrace TWW through various blending scenarios with traditional surface water sources. The yield response function to salinity was incorporated into profit function to simulate crop profitability and water values. Results indicate that the introduction of TWW negatively affects salt-sensitive crops like citrus but positively impacts others such as date palm, olives, tomatoes, and peppers due to increased fertilizer content in irrigation water. Economic performance indicators reveal a gradual decrease in water net productivity for citrus with increasing blending ratios of TWW, with the water value decreasing accordingly. Higher percentages of treated water do not consistently lead to increased productivity, profitability, or net value added, emphasizing the need for careful consideration and understanding of economic risks associated with specific crops and water quality. To mitigate the impact of water salinity on citrus production, growers are advised to improve soil quality, periodically flush the soil with low-salinity water, and use salt-tolerant rootstocks. Regular monitoring of soil and water salinity levels is crucial for informed decision-making. While using TWW, water may offer cost savings.

A multi-environment evaluation of sorghum genotypes was conducted across six environments in the 2021 main growing season in a randomized complete block design with three replications. The objectives of the study were to estimate the magnitude of genotypes by environment interaction (GEI) and grain yield stability of drought-tolerant sorghum genotypes across different environments. Data were subjected to analysis of variance, Additive Main Effects and Multiplicative Interaction (AMMI), and GGE biplot analysis. Combined analysis of variance revealed significant variations among genotypes, environments, and GEI for yield and yield-related traits, indicating that these factors significantly affected grain yield. The maximum mean grain yield value of genotypes due to the mean effect of the environment was obtained from G1 (5119.93kg ha-1), followed by G14 (4834.57 kg ha-1), and G18 (4801.20 ha-1), while the least mean grain yield was obtained from G3 (3314.50 kg ha-1). The multiplicative variance of the treatment sum of squares due to GEI was partitioned into four principal component axes (PCA). Sum squares of the first and second interaction principal component axis (IPCA) explained 71.07% and 17.50% of the GEI variation, respectively. The IPCA1&2 mean squares were highly significant (P≤0.01), indicating the adequacy of the AMMI model with the first two IPCAs for cross-validation of grain yield variation. The magnitude of the GEI sum squares was 3.9 times that of the genotype sum squares for grain yield, indicating the presence of substantial differences in genotypic responses across environments. The results of cultivar superiority measure (Pi), yield stability index (YSI), AMMI stability value (ASV), regression coefficient (bi), and deviation from regression (S2di) depicted that genotypes G18, G22, G31, and 32 were the most stable genotypes for grain yield and biomass yield, respectively. AMMI2 biplot showed Jinka, Alduba, and Kako were the most discriminating environments as indicated by the long distance from the origin; whereas testing locations Meioso and Gato with short vector length indicated that these locations had less discriminating power on the genotypes' performance. The study has provided precious information on the yield stability status of the sorghum genotypes and the best environments for future improvement programs in Ethiopia.

Tamil Nadu, a state in southern India, is bereft of any native milch or dual-purpose cattle breed and the state depends chiefly on crossbred cattle for milk production. As most (90 percent) of the milk production in the state was contributed by Jersey crossbred cattle, the genetic evaluation study was intended to assess the milk production traits viz., test-day milk yields (TDMYs), total milk yield (TMY) and 305-day milk yield (305MY) in these crossbred cattle reared under farmers’ rearing environment. Data on monthly TDMYs (TDMY1 to TDMY10) of Jersey crossbred cows (n=81,653) reared by the farmers over 24 years (1999-2022) were collected for evaluation. The influence of non-genetic factors viz., location (agroclimatic zones), period and season of calving, and parity on TDMYs, TMY, and 305MY were assessed, and the variance and covariance components for genetic parameters (heritability and genetic correlation) of the traits were estimated by the method of restricted maximum likelihood (REML) under multivariate animal model and by random regression model (RRM). The overall means of various TDMYs ranged from 4.98 (TDMY10) to 9.95 kg (TDMY2) and, for TMY and 305MY the means were 2480.33 and 2393.71 kg respectively. The heritabilities estimated by animal model for TDMYs were high and ranged from 0.39 ± 0.01 to 0.47 ± 0.01 and were fairly less variable throughout the lactation while the estimates obtained by RRM were medium to high and ranged between 0.28 ± 0.01 and 0.65 ± 0.02 for different days in milk (DIMs). The heritability estimated for TMY and 305MY were 0.48 ± 0.01 and 0.49 ± 0.01 respectively. The estimates of heritability in mid-lactation yields were comparatively little less than those at the beginning and the end of lactation. The high estimates of heritabilities for TDMYs, TMY, and 305MY obtained in the present study offered an ample scope for improving milk production through selective breeding. Genetic correlations between TDMYs estimated by animal model were positive and moderate to high, with a range between 0.47 ± 0.01 and 0.99 ± 0.00. Considerably higher estimates (0.97-0.99) were observed between adjacent TDMYs showing strong genetic associations. By RRM, genetic correlations estimated between DIMs were positive, except for a few estimates and the magnitude of genetic correlation decreased with an increase in the interval between the DIMs. The high genetic correlation observed between the TDMYs in early and mid stages of lactation with TMY and 305MY suggested that these test day yields could be used favorably for the early selection of cows for milk production which facilitates reduction in the generation interval and consequently increase the annual genetic gain for the milk production traits.

Non-destructive, accurate, and timely approach for crop yield prediction at field scale is vital for precision agriculture. This study aimed to investigate the appropriate wavelengths and their combinations to explore the new SIs derived from UAV hyperspectral images in predicting yield during the growing season of spring maize. The best wavelengths and new SIs, including the difference spectral index, ratio spectral index, and normalized difference spectral index forms, were obtained by the contour maps constructed by the coefficient of determination (R2) from the linear regression models between the yield and all possible SIs screening out from the 450-950 nm wavelengths. The results showed that the most sensitive wavelengths were 640-714 nm at WJQ, 450-650 nm and 750-950 nm at SKS, and 450-700 nm and 750-950 nm at FJJ. The new SIs established here were different across the three experimental fields, and their performance on maize yield prediction were generally better than that of the published SIs. In addition, the new SIs presented different response to various N fertilization levels. This study demonstrated the potential of exploring new spectral characteristics from remote sensing technology for predicting field-scale crop yield in spring maize cropping systems before harvest.

This study investigates by hybrid approach of classical calculations and numerical explicit FEM simulation the strain rate sensitive hardening of Polypropylene Sabic 83MF10 under dynamic tension loads. The Cowper-Symonds model is employed to characterize the non-linear increase in yield strength with strain rate, within the range of 0,01 to 1 [1⁄s]. For lower strain rates, a drastic decrease in yield strength is observed, suggesting the significant influence of creep and relaxation phenomena. The study proposes further research incorporating viscoelastic properties for a more comprehensive material model. Additionally, the study observes a disproportionate increase in yield strength for samples with smaller radius, indicating a dependency on triaxiality which suggests further research on the Drucker-Prager model for this material. The study concludes by recommending a broader range of input parameters for future studies, including the Johnson-Cook model and comparison of tensile test results with compression test results.

The viticulture sector, spanning over 7.3 million hectares worldwide, plays a crucial economic role but faces challenges such as labor shortages, rising production costs, market competition, and climate change stresses. Addressing these issues requires monitoring the spatial and temporal variability in vineyard productivity. Traditional ground-based observations, though accurate, are time-consuming and limited in scope. Precision viticulture, leveraging technologies like GPS, remote sensing, and artificial intelligence, offers efficient, non-destructive monitoring tools. This study aims to develop and test a technological workflow using the mobile app Digivit, integrated with the AgroSat platform, to estimate yield variability in vineyards. The workflow was performed during the 2023 growing season in a series of vineyards near Siena (Italy) and involved two main steps: spatial variability characterization using AgroSat and yield estimation using the mobile Digivit app. AgroSat processed Sentinel-2 NDVI data to identify homogeneous zones, while Digivit used smartphone images of grape clusters to estimate yields. The field campaign, performed three weeks before harvest, involved monitoring representative vines within identified zones and uploading georeferenced images for cluster segmentation analysis. Yield estimates were validated against measured weights, showing a strong linear correlation (R²=0.85, RMSE=43.74g). Excluding one outlier improved correlation to R²=0.95, RMSE=14.58g. Vineyard-level yield predictions were compared with harvest data, achieving an overall error of approximately 7%, in agreement with other methods in the literature. The study demonstrates that the Digivit app provides accurate, timely yield prediction, supporting farmers in harvest planning and winemaking management. The user-friendly mobile app approach facilitates a broader adoption of precision viticulture technologies among farmers, overcoming barriers related to technical expertise.

Durum wheat (DW) is one of the major crops grown in the Mediterranean area, a climate-vulnerable region where the increase in day/night (d/n) temperature are severely threatening DW yield stability. In order to improve DW heat tolerance, the introgression of chromosomal segments derived from the wild gene pool is a promising strategy. Here, four DW-Thinopyrum spp. near-isogenic recombinant lines (NIRLs) were assessed for their physiological response and productive performance after an intense heat stress (IH, 37/27°C d/n) applied for 3 days at anthesis. The NIRLs included two primary types (R5, R112), carriers (+) of a differently sized Th. ponticum 7el1L segment on DW 7AL arm, and two corresponding secondary types (R69-9/R5, R69-9/R112), possessing a Th. elongatum 7EL segment distally inserted into the 7el1L ones. Their response to the IH stress was compared to that of corresponding non-carrier sib lines (−) and of the heat tolerant cv. Margherita. Overall, the R112+, R69-9/R5+ and R69-9/R112+ NIRLs exhibited a tolerant behaviour towards the applied stress, standing out for maintenance of leaf relative water content, but also for accumulation of proline and soluble sugars in flag leaf and for preservation of photosynthetic efficiency. As a result, all the above three NIRLs (R112+ > R69-9/R5+ > R69-9/R112+) displayed good yield stability under the IH, also in comparison with cv. Margherita, R112+ particularly relying on strength of spike fertility/grain number traits, R69-9/R5+ on efficient compensation by grain weight increase. This work largely confirmed and further substantiated the value of exploiting the wild germplasm of Thinopyrum species as useful source for the improvement of DW tolerance to even extreme abiotic stress conditions, such as the severe heat treatment throughout day- and night-time applied here.

Sesame seeds and their edible oil are highly nutritious and rich in mono- and polyunsaturated fatty acids. Bioactive compounds such as sterols, tocopherols, and sesamol provide significant medicinal benefits. The high oil content (50%) and favorable mono-and polyunsaturated fatty acids balance, as well as sesame's resilience to water stress makes, make it a promising candidate for global agricultural expansion. However, sesame production faces challenges such as low yields, poor response to agricultural inputs, and losses due to capsule dehiscence. To enhance yield, traits like determinate growth, dwarfism, high harvest index, non-shattering capsules, and photoperiod sensitivity are needed. These traits can be achieved through variation or induced mutation breeding. Traditional breeding methods often result in unwanted genetic changes. The CRISPR/Cas9 technology has the potential to suppress detrimental alleles and improve the fatty acid profile by inhibiting polyunsaturated fatty acid biosynthesis. Even though sesame is an orphan crop, it has entered the genomic era, with available sequences assisting molecular breeding efforts. This progress aids in associating single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs) with key economic traits, as well as identifying genes related to adaptability, oil production, fatty acid synthesis, and photosynthesis. Additionally, transcriptomic studies can reveal genes involved in abiotic stress responses and adaptation to diverse climates. Quantitative trait loci (QTL) mapping can identify loci linked to crucial traits such as capsule size, seed count per capsule, and capsule number per plant. This paper reviews recent advances in sesame breeding, discusses ongoing challenges, and explores potential strategies for future improvement. Hence, integrating advanced genomic tools and breeding strategies provides promising ways to enhance sesame production to meet global demands.

Within the European Union (EU), new plant varieties, to be included at the Common catalog of a member state, has to be registered at the national list, after plant variety testing processes to establish whether the candidate variety is distinguishable, uniform and stable (DUS) and meets the requirement of the cultivation or use value requirement (VCU). Technical development, climate change and changing consumer needs, including the detection of GMOs, necessitate the innovation of plant variety testing methods. Within the EU-funded "InnoVar" project, it has been sent out questionnaires to several countries, which were aimed at analyzing strengths, weaknesses, opportunities and threats (SWOT) of the current methods and with their help it is possible to have look for a new direction, opportunity and strategy, which can incorporate together with the innovation results into the development of the new methods. Our study confirmed that the SWOT analysis could be used to achieve the set goals; according to the answers to the questionnaires, it became necessary to introduce new characters (e.g. cold tolerance) and new test methods (molecular markers, precision techniques, organic farming) into the variety testing procedures. The development of high-yielding, disease and/or pest-resistant plant varieties with good adaptability and the accurate evaluation of genotypes play a crucial role in ensuring that farmers can access high-performing plant varieties and contribute to sustainable food production.

To enhance pomegranate production on marginal gravelly lands, standardized planting techniques were evaluated in an 8-year-old orchard. Trenching, wider pit excavation, pit digging, and auger digs with dimensions of 1 and 2 m were employed. Utilizing native soil from barren land, with or without spent wash, and mixing it with black soil up to 1 m deep, growth parameters, leaf nutrients, fruit production, and fruit quality were assessed. The trench and wider pit methods outperformed others, yielding greater above-ground biomass (>70.3 kg tree⁻¹), root biomass (>24.5 kg, tree⁻¹), and cross-sectional area (>3.30 m² tree⁻¹). These methods also produced longer roots (>4.0 m tree⁻¹) and higher leaf phosphorus (>0.28%) and potassium (>1.81%) levels, fruit juice content (>48.50%), and total soluble solids (>16.05°) compared to other planting methods. This resulted in higher and more sustainable fruit yield production under the trench and wider pit planting methods (>7.21 t ha⁻¹). Similarly, the native and black soil mixture produced healthy fruit trees, improved fruit quality, and sustainably higher fruit yield over the native soil alone. In summary, the trench and wider pit methods (2–3 m³), combined with a soil mixture, are recommended for sustainable, high-quality fruit production in shallow gravelly terrains, thereby improving food security and the livelihoods of farmers in arid regions.

Understanding the interrelationships between land use, climate change, and regional water yield is critical for effective water resource management and ecosystem protection. However, comprehensive insights into how water yield evolves under different land use scenarios and climate change remain elusive. This study employs the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models, Patch-generating Land Use Simulation (PLUS) model, and Geodetector within a unified framework to evaluate the dynamics of land use, water yield, and their relationships with various factors (meteorological, social, economic, etc.). To forecast the Land Use/Cover Change (LUCC) pattern of the Yellow River Basin by 2030, three scenarios were considered: economic development priority (Scenario1), ecological development priority(Scenario2), and cropland development priority(Scenario3). Climate change scenarios were constructed using CMIP6 data, representing low stress (SSP119), medium stress (SSP245), and high stress (SSP585) conditions. The results show the following: (1) From 2000 to 2020, cropland was predominant in the Yellow River Basin, Henan Province, with significant land conversion to impervious land (construction land) and forest land; (2) Water yield changes during this period were primarily influenced by meteorological factors, with land use changes having negligible impact; (3) By 2030, the water yield of Scenario1 is highest among different land use scenarios, marginally surpassing ecological development priority by 0.5%; (4) Climate scenarios reveal significant disparities, with SSP126 yielding 67% higher water production than SSP245, driven predominantly by precipitation; (5) Geodetector analysis identifies precipitation as the most influential single factor, with significant interactions among meteorological and socio-economic factors. These findings offer valuable insights for policymakers and researchers in formulating land use and water resource management strategies.

Crop rotation diversification using legumes has been advocated as one of the solutions to improve the resilience of the crop system to various environmental stresses and the use of nitrogen resources. However, when forage legumes or grass-legumes are ploughed, there is a high risk of nitrate leaching, especially in sandy soils. The aim of the study was to determine the effect strip tillage intercropping management on soil mineral nitrogen (SMN), water-extractable organic carbon (WEOC) content and winter wheat (WW, Triticum aestivum L.) grain yield compared to forage legume and WW monocropping with conventional tillage. In intercropping was used winter wheat - black medick (Medicago lupulina L.) WW+BM, winter wheat - white clover (Trifolium repens L.) WW+WC, and winter wheat - Egyptian clover (Trifolium alexandrinum L.) WW+EC. Research was repeated in two experiments. The results showed that after strip tillage and WW sowing less or similar SMN content cud be detected, as in conventional tillage and WW + forage legumes intercropping. WW grain yield in intercrops decreased, compared to the grasses monocultures that were ploughed before WW sowing. The highest amount of WEOC was in intercropping soil growing WW+WC or in all fields (except WW+EC) after applying strip tillage. During the research period, the amounts of mobile humic substances (HSs) and mobile humic acids (HAs) changed analogously. Their content increased substantially in fields with WC and EC, regardless of whether the grasses were ploughed or grown with WW.

The metabolites secreted by probiotics or released after their lysis are called postbiotics. They provide physiological benefits to the host, preventing the colonisation of pathogens by improving the intestinal environment for beneficial commensal bacteria, which reduces the incidence of digestive disorders and improve the immune system. The aim of this work was to evaluate the addition of postbiotics to dairy cow rations during the transition period on nutrient digestibility, composition, and milk yield. The effects of two postbiotics were evaluated in twelve Friesian cows from 30 days before calving to two months of lactation. The animals were randomly allocated to the treatments control (CT) and supplemented with postbiotics (PC and PR). Feeding was ad libitum with 60/40 of forage/concentrate ratio. Daily feed intake and milk production were recorded individually throughout the study. Two digestibility balances were performed, one before parturition and one after parturition. Colostrum was sampled at first milking and milk was sampled weekly. Data were analysed using a mixed mode in R software. The results suggest that postbiotic supplementation in late gestation and early lactation increase the voluntary intake of dry matter, especially in the PR treatment, with higher apparent total tract digestibility of dry matter, organic matter and neutral detergent fiber. Both treatments including postbiotics induced an increase in colostral immunoglobulin concentration. Milk production of cows receiving the PC treatment was the highest, with high fat and protein yields and a higher persistence of the production curve throughout the lactation.

Enhancing soil fertility and maize productivity is crucial for sustainable agriculture. This study aimed to evaluate the effects of tillage practices, nitrogen management strategies, and acidified hydrochar on soil fertility and maize productivity. The experiment used a randomized complete block design with split-split plot arrangement and four replications. Main plots received shallow tillage and deep tillage. Sub-plots were treated with nitrogen (120 kg ha⁻¹) from farmyard manure and urea, including control, 33% FYM + 67% urea (MU), and 80% FYM + 20% urea (MF). Acidified hydrochar treatments H0 (no hydrochar) and H1 (with hydrochar, 2 t ha⁻¹) were applied to sub-sub plots. Deep tillage significantly increased plant height, biological yield, grain yield, ear length, grains ear-1, thousand grain weight, and nitrogen content compared to shallow tillage. MU and MF improved growth parameters and yield over the control. Hydrochar effects varied; H1 enhanced certain yield components but reduced plant height and soil properties compared to H0. Canonical discriminant analysis linked deep tillage and MU/MF nitrogen management with improved yield and soil characteristics. In conclusion, deep tillage combined with integrated nitrogen manage-ment enhances maize productivity and soil health. However, hydrochar application requires op-timization. These findings highlight the importance of selecting appropriate tillage and nitrogen strategies for sustainable maize production. These insights guide policymakers, agronomists, and agricultural extension services in adopting evidence-based strategies for sustainable agriculture, enhancing food production, and mitigating environmental impacts. Future research should in-vestigate long-term impacts across diverse environments to validate these results.

Background: Pleurotus ostreutus is one of the world’s most commonly consumed mushrooms. Cultivation of mushrooms using wood resources usually results in environmental issues of deforestation. Juncao grass Pennisetum sp, Arundo Donax, and Methodology: Miscanthus are the culture mediums used in this research which offered a composting system most particularly for a simple formulation, cheap and feasible for small farms in cultivating oyster mushrooms. Results: The present study assessed the different junco grass as a substrate for growing Pleurotus ostreatus given the enzyme activities, growth, and yields. In addition, on the other hand, Lignin peroxidase (LiP) was the most active enzyme in each culture material among the other enzyme activities expressed differently between substrate and growing stages. Fruiting bodies harvested on giant grass,Arundo donax,and miscanthus,substrate weighed 159.2g/bag,132g/bag, and 65.1g/bag on average respectively. The biological efficiency of pleurotus cultivated in three different substrates was 75.2%, 63.4%, and 28.7%, respectively. Lignin peroxidase (LiP) was the most active enzyme followed by Laccase in each substrate. At the same time, other enzyme activities were differently expressed between substrate and different developmental stages. Nutrient analysis revealed significant variations, with differences in polysaccharides, proteins, and amino acids among substrates as well as the presence of heavy metals as arsenic, lead, mercury, and cadmium content in all samples was within safe limits. Conclusion: Findings from this study will serve as a solid foundation for future studies aimed at characterizing different substrate responses on enzyme activity. This research provides a sustainable footprint for subsequent research promoting eco-friendly mushroom production. The obtained results indicate that Arundo donax should be a good substrate in place of giant grass, using miscanthus is not productive based on the results obtained in this research the juncao grasses offer a sustainable approach that reduces reliance on wood-based substrates and enhances environmental sustainability.

Increasing nitrogen use efficiency (NUE) by improving agricultural practices, soil knowledge and implementing precision agriculture, is essential to reduce the overuse of fertilisers and increase nutrient retention. This study aimed to optimise N management in agriculture by establishing a critical N dilution curve (CNDC) and analysing variations in NUE and N nutrition index (NNI) among different crops under various treatments. Using a Bayesian model, the CNDC was determined as %Nc = 3.63 * PDM-0.71. The results presented that plant dry matter (PDM) and plant N content (PNC) varied significantly with crop type and sampling moments. Strong positive correlations are presented by PDM with N uptake (NUp) (0.89) and NNI (0.88), along with an inverse correlation with critical N concentration (-0.95). The study found that crops under irrigation conditions had higher NUp and higher NNI. This study provides valuable insights into the influence of key management decisions on the N nutritional status of annual ryegrass-based forage crops. The results highlight the critical role of accurate and conscious decision-making in improving NUE and crop yields, emphasising the complex interactions between biomass production and N dynamics in crops. The conclusions allow significant benefits to be realised, contributing to the sustainability of agricultural systems.

Exploring the growth and physiological response mechanisms of rice under continuous drought stress circumstances can provide a significant scientific foundation and technological assistance for meeting drought difficulties, improving drought resistance and rice (Oryza sativa L.) output, and ensuring food security. In this study, a rice field experiment was conducted under a rain shelter with five different treatments set up: P1 (drought stress from tillering stage), P2 (drought stress from jointing-booting stage), P3 (drought stress from heading-flowering stage), P4 (drought stress from grain filling stage), and CK (adequate water management throughout the growth stage). Continuous drought stress from different growth stages with four levels (mild, medium, serious, and extreme). The results showed that the effects of different drought stress treatments on rice growth varied significantly. Compared with the CK treatment, plant height was reduced by 12.10%, 8.14%, 3.83%, and 1.06% in the P1, P2, P3, and P4 treatments, respectively; and the number of tillers was reduced by 23.83%, 18.91%, 13.47%, and 8.68%, respectively. With the increase in drought stress levels, SPAD values and Rubisco activity of rice leaf continued to decrease; SOD activity showed a decreasing trend, but the decreasing trend of POD and CAT activities was not significant, while MDA content showed an increasing trend. For yield components, continuous drought stress significantly reduced spike length, effective number of spikes, thousand grain weight, grain number per spike, and fruiting rate of rice compared to CK treatments during the growth period. In general, continuous drought stress during the early growth period affected the effective spike number and the grain number per spike. Continuous drought stress after the grain filling stage had the least effect on yield and water use efficiency was much higher than other treatments. The results of these studies reveal the response of rice growth and physiology to continuous drought stress, which is important for agricultural practices.

Ghana, blessed with abundant solar resources and has strategically invested in solar photovoltaic (PV) technologies to diversify its energy mix and reduce the environmental impacts of traditional energy technologies. The 50 MW solar PV installation by the Bui Power Authority exemplifies the nation's dedication to utilizing clean energy for sustainable growth. This study seeks to close the knowledge gap by providing a detailed analysis of the system's performance under different weather conditions, particularly on days with abundant sunshine and those with cloudy skies. The research consists of one-year monitoring data of the climatic and AC energy output fed into the grid. This data was used to analyze PV performance on each month's sunniest and cloudiest days. The results show that the total amount of AC energy output fed into the grid each month on the sunniest day varies between 229.3 MWh in December and 278.0 MWh in November, while the total amount of AC energy output fed into the grid each month on the cloudiest day varies between16.1 MWh in August and 192.8 MWh in February. Also, the percentage variation in energy produced between the sunniest and cloudiest days within a month ranges from 16.9% (December) to 94.1% (August). The reference and system yield analysis showed that the PV plant has a high conversion efficiency of 91.3%; however, only the sunniest and overcast days had an efficiency of 38% and 92%, respectively. The BPA plant's performance can be enhanced by using this analysis to identify erratic power generation on sunny days and schedule timely maintenance to keep the plant's performance from deteriorating. Optimizing a solar PV system's design, installation, and operation can significantly improve its AC energy output, performance ratio, and capacity factor on sunny and cloudy days.

The article presents the results of studies aimed to identify the effect of foliar treatments of winter wheat, sugar beets and soybeans with mineral and bioorganic fertilizers. Their positive effect on increasing the concentration of mineral forms of nitrogen in soil was revealed. The crop types have a greater influence on the size of nitrous oxide emissions: in winter wheat crops - 679 µg/m3, soybeans - 637.2 µg/m3, sugar beets - 576.8 µg/m3. The amounts of nitrous oxide emissions were lower in the variants without the use of phosphorus-potassium fertilizers. The Ruter AA fertilizer showed the greatest efficiency on winter wheat crops - 42.7 c/ha. Soybean grain yield of 44.2 c/ha was also achieved by using Ruter AA, as well as Geo-humate together with phosphorus-potassium fertilizers. On the background of the actual supply of phosphorus and potassium, maximum yield was obtained when using N30 on the leaf - 39.3 c/ha. Foliar feeding ensured a yield of sugar beet root crops of up to 67.1-77.4 c/ha on the backdrop of the application of phosphorus-potassium fertilizers with the advantage of using Amino turbo. The largest yield of sugar beet roots without use of mineral phosphorus and potassium was ensured by N30 treatment of the leaf in the phases of 4-6 and 8 leaves - 63.2 t/ha. Of the organo-mineral fertilizers and biostimulants, the best result was shown by the use of Ruter A - 62.6 t/ha. We believe that foliar feeding of crops can be a sustainable farming method that can increase crop yields and reduce N2O emissions.

Extreme climates such as droughts and hot extremes, may result in marked damage to crop yields and threaten regional and global food security. Maize is a major grain crop in Liaoning Province, severely affected by drought and hot events. The objective of this study is to advance an approach to estimate the risk of crop yield reduction under the compound dry-hot events (CDHE) in Liaoning Province. Results show that the ratio of stations experiencing compound dry-hot events during the twelfth leaf and maturity stage tended to increase on the time scale. On a spatial scale, the frequency of compound dry-hot events in central Liaoning Province was relatively low during the whole and various reproductive periods of maize. In addition to the twelfth leaf, western Liaoning Province is prone to compound dry-hot events. The high-risk area for the occurrence of the compound dry-hot events in maize is Chaoyang City, located in the western part of Liaoning Province, and the cities in the low-risk area account for about 64.3% of the total number of cities in Liaoning Province, mainly in the central and northern parts of Liaoning Province. Generally, this study emphasizes focusing on the impacts of compound dry-hot events on agricultural production and provides an index to assess the risk of compound dry-hot events on maize production.

Two experiments were conducted to develop a Nano green manganese and assess its effect on grapevines. The first experiment was microbiological, where several incorporation strategies were utilized to enrich the yeast with manganese, as follows: (1) adding manganese to the liquid medium (growth phase), (2) adding after 24 h of incubation (non-growth phase). As the results, growth phase reduced the possibility of medium contamination. Manganese concentration in the yeast cells was increased as that of manganese sulphate in the medium. Manganese incorporation in yeast cells was 99.93% higher than that of the medium at 0.0195 g/l of manganese. Although the concentration of manganese in the medium raised the OD of yeast cell biomass, manganese sulphate had no passive influence on it. The second experiment was horticultural, done on Flame Seedless grapevines, since both active fresh and frozen yeast enriched with manganese resulted from the first experiment were sprayed twice a year at 10 or 20 cm3/l comparing with manganese sulphate, and manganese chelate. The results demonstrated that yeast extracts in both forms increased the yield and improved fruit properties. The most effective treatment on vegetative growth, yield and fruit properties was the frozen yeast enriched with manganese at 20 cm3/l.

Temperature Cycle Induced Deracemization (TCID) offers a promising approach to obtain enantiopure solids from racemic mixtures. By combining rapid racemization in solution and temperature swings, homochirality is theoretically achieved. Despite theoretical expectations of doubled yields compared to traditional chiral separation methods, such as in Preferential Crystallization, experimental validation remains lacking. We applied TCID to (1-(4-chlorophenyl)-4,4-dimethyl-2-(1H-1,2,4-triazol-1-yl) pentan-3-one) (Cl-TAK), introducing a post-TCID cooling step to enhance yield and a washing step to augment enantiopurity. This refinement yielded an 89.8% mass yield with 99.1% enantiomeric excess in the crystal phase (c.e.e.) within 24 hours on an 8.75g scale, showcasing improved performance with insignificant process duration extension. Additionally, we explored the stochasticity of deracemization, observing the development from low initial crystal enantiomeric excesses(1-6% c.e.e0) at a 2.5 g scale. Kinetic analysis revealed that a 2% c.e.e0 effectively mitigates chiral flipping risks and induction time in our system. Our study underscores the potential for reduced initial c.e.e. to expedite deracemization and presents a straightforward method to optimize yield and purity, facilitating industrial application.

The purpose of this experiment was to assess the morphological parameters and dry matter yield of Brachiaria decumbens ILRI-10871 grown for two years under four fertilizer rates (0,100, 300kg N and manure). The field experiment was carried out at Robit Bata Kebele in the Bahir Dar Zuria district of Amhara region, Ethiopia. Each 9-m2 plot in the treatments was arranged in a 4x2 factorial configuration in a randomized complete block design with three replications. Morphological data were collected from 10 randomly selected plants grown in the middle rows of each plot. All recorded datasets were subjected to a general linear model procedure of SAS (9.0) at a significance level of alpha

Global warming caused by climate change is a challenge for dairy farming, especially in sub-Saharan countries. Under high temperature and relative humidity dairy cows suffer from heat stress. The objective of this study was to investigate the effects and relationship of heat stress (HS) measured by temperature-humidity index (THI) on physiological parameters and milk yield and composition of lactating Holstein Friesian crosses reared in the humid coastal region of Tanzania. A total of 29 lactating Holstein Friesian x Zebu crossbred dairy cattle with 50% (HF50) and 75% (HF75) Holstein Friesian blood levels in their second and third month of lactation were used. Breed composition of Holstein Friesian was determined based on animal recording system used at the Tanzania Livestock Research Institute (TALIRI), Tanga. Data collected included daily temperature, relative humidity, daily milk yield, and physiological parameters (core-body temperature, rectal temperature, respiration rate, and panting score). The THI was calculated using the equation of National Research Council [39]. The THI values were categorized into three classes i.e. low THI (76-78), moderate THI (79-81) and high THI (82-84). The effects of THI on physiological parameters and milk yield and composition were assessed. Also, the effects of genotype, parity, lactation month, and interaction of these parameters with THI i on milk yield, milk composition, and physiological parameters were investigated. The results indicate that THI and its interaction with genotypes, parity, and lactation month had highly significant effect on all the parameters. THI affected (P ˂ 0.05) average daily milk yield and milk fat %, protein %, lactose %, and solids – not – fat %. When THI increased from moderate to high values, average daily milk yield declined from 3.49 ± 0.04 to 3.43 ± 0.05 liters/day while fat % increased from 2.66 ± 0.05% to 3.04 ± 0.06% and protein decreased from 3.15 ± 0.02% to 3.13 ± 0.03%. No decline was observed on lactose % whilst solids – not – fat % declined from 8.56 ± 0.08% to 8.55 ± 0.10%, when the THI values increased from moderate to high. Also, THI affected (P˂0.05) physiological parameters. Core-body temperature (CBT), rectal temperature (RT), respiration rate (RR) and panting score (PS) increased from 35.60 ± 0.01 to 36.00 ± 0.01oC, 38.03 ± 0.02 to 38.3.30 ± 0.02oC, 62.53 ± 0.29 to 72.35 ± 0.28 breaths/min and 1.35 ± 0.01 to 1.47 ± 0.09, respectively, when THI increased from low to high. THI showed a low positive correlation with average daily milk yield and fat percentage whilst protein, lactose, and solids – not - fat percentages showed negative relationships with THI (P ≤ 0.05). The CBT, RT, RR, and PS showed positive relationships (P ≤ 0.05) with THI. These negative relationships indicate that there is an antagonistic correlation between sensitivity to HS and degree of production. It is concluded that the THI, genotype, parity, and lactation month, and their interactions with THI significantly affected milk yield, milk composition, and physiological parameters of lactating Holstein Friesian dairy crosses at THI thresholds ranging from 77 to 84.

The intensification of modern farming methods in developed nations has exacerbated the issue of soil degradation and over-utilization of naturally available resources, hence, tinkering negatively with the health and productive capacity of soil. Chemical fertilizers, while increasing crop yields, have resulted in environmental pollution and health hazards. Green manuring presents a sustainable alternative by enriching soil fertility and reducing reliance on chemical fertilizers. This paper reviews the impact of green manuring on soil properties, crop yield, and farm economies. In-situ green manuring involves growing and incorporating the crops within the field, while ex-situ green manuring incorporates plant material from external sources. Leguminous green manures are particularly effective owing to nitrogen fixation capability and rapid decomposition. The inclusion of green manure improves the availability of nutrients, microbial count and carbon content of the soil, thereby, enhancing the overall health of soil and crop productivity. Additionally, green manures reduce pests and diseases, suppress weeds, and provide supplementary forage. Despite the benefits, challenges such as limited water resources, seed availability, and farmer reluctance hinder widespread adoption. Future research should focus on raising awareness, quantifying benefits, and developing location-specific cropping systems to optimize green manuring practices.

The effect of sonication on the molecular characteristics of poliacrylic acid (Carbopol® Ultrez 10) and its rheological behavior in aqueous dispersions and microgels containing 0.25 wt. % of the polymer was analyzed in this work by rheometry, weight-average molecular weight (Mw) measurements via static light scattering (SLS), Fourier transform infrared (FTIR) spectroscopy and confocal microscopy. For this, the precursor dispersion and the microgels were sonicated in a commercial ultrasound bath at constant power and different times. We observed a softening of the microgel microstructure consisting of a systematic decrease in its shear modulus, yield stress and viscosity with increasing sonication time, while their overall Herschel-Bulkley (H-B) behavior was preserved. SLS measurements evidenced a reduction of Mw of polyacrylic acid with sonication time. Separately, FTIR measurements indicate that sonication produces scission in the C-C links of the Carbopol® backbone, which results in chains with the same chemistry but lower molecular weight. Finally, confocal microscopy measurements revealed a concomitant diminution of the size of the microsponge domains with sonication time, which is reflected in a softer microstructure resulting from reduction of the molecular weight of polyacrylic acid. The present results indicate that both the microstructure and the rheological behavior of Carbopol® microgels, in particular, and complex fluids in general, may be manipulated or tailored by high-power ultrasonication.

A 2-month incubation study was carried out using two soil types to determine nitrogen mineralization of different inorganic-organic amendments. The following seven treatments (T) were established; T1 = control, T2 = 5 g of dry algae per kg of soil (100%DA), T3 = 136g of agri-mat per kg of soil (100%GA), T4 = 61 g of ground grass per kg of soil (100%GG), T5 = 2.5 g of dry algae + 2.5 g of nitrogen fertilizer (NF) per kg of soil (50%DA50NF), T6 = 50%GA50NF, T7 = 50%GG50NF. Three samples per treatment were drawn at 0, 3, 7, 15, 30, 45, and 60 days for mineral-N determination. A 2-month glasshouse experiment was established afterwards with the following five treatments: T1 = Control, T2 = 50%DA, T3 = 50%GA, T4 = 50%GG, and T5 = 100NF. The results indicated that nitrogen mineralization was significantly higher in organic-inorganic amendments compared to sole organic amendments. The percentage differences ranged from 157% to 195%. The 50%DA treatment increased spinach yield by 20.6% in sandy loam and 36.5% in loam soil. It is difficult to fully recommend the 50%DA treatment without field-scale evaluation, but it is a promising option to be considered.

High dimensional statistical analysis for the yield of large-scale circuits is quite difficult due to expensive simulations, especially for the memory circuits with high sigma requirement (e.g., SRAM). In this paper, we developed an efficient sparse additive model to substitute simulations. To fit high sigma region accurately, the modeling center is moved to near failure boundary searched by scaling the shape of sampling function. To solve the model efficiently, the process variables are grouped by standard cells so that the model can be solved by our developed blockwise greedy algorithm. The experiments on the 28nm memory circuits validate that our method achieves high accuracy and efficiency compared with other state-of-art works.

Pea shoots is a popular vegetable in certain regions of the world due to their unique taste and abundance of health-promoting phytochemicals. The perishable nature and susceptibility of root rot of pea shoots necessitate a new soilless production system located close to the market. This study compared the growth of pea shoots using various cultivation methods in LED plant factory. The results showed that early topping (4 days after transplanting, ET) promoted early harvest compared to later topping (20 days after transplanting, LT) and increased the number of harvested shoots by extending the harvest time to 2.8 times, ultimately resulting in a substantial yield improvement. Moreover, the yield of ET with lower planting density (72 plants m-2, ET-LD) was 8.7% higher than ET with higher planting density (126 plants m-2, ET-HD). Particularly, the average fresh weight of individual pea shoots under ET-LD exceeded that of ET-HD by 48.9%. It is advisable to consider adopting ET-LD for the cultivation of pea shoots in LED plant factory. Based on ET-LD, the yield, nutritional quality, and light use efficiency of pea shoots were further explored at different stages under three levels of light intensity (50, 100, 150 μmol m-2 s-1). Contrasted against the light intensity of 50 μmol m-2 s-1, the average fresh weight per pea shoots, number of harvested, and total fresh yield under light intensity of 150 μmol m-2 s-1 treatment increased by 60.2%, 62.8%, and 165.1%, respectively. Meanwhile, the fresh weight per pea shoots, photosynthetic capacity, soluble sugar and vitamin C levels in leaves, as well as light use efficiency and photon yield, initially increased and then decreased with the extension of the planting period. Among these, soluble sugar, LUE, and PY started to decrease after reaching the maximum value at 60-70 days after transplanting. In conclusion, light intensity of 150 μmol m-2 s-1 with a photoperiod of 16 h d-1 using LEDs, combined with early topping within a planting period of 60-70 days, proves to be suitable for the hydroponic production of pea shoots in LED plant factory.

Salinity, resulting from climate change and excessive mineral fertilization, burdens farmers and negatively impacts soil and water ecosystems in the Northeastern Nile Delta. Organic and biological approaches are crucial for addressing these issues. This study examined the effects of individual and combined inoculations with cyanobacteria, yeast, and Arbuscular Mycorrhizal Fungi (AMF), with or without K-humate, on enhancing salinity tolerance, increasing yield, and improving crop quality of wheat and faba bean. The aim was to reduce NPK mineral fertilizer application rates to 25% of recommended doses. An economic evaluation was also conducted. In a preliminary laboratory experiment, the interactive effects of these microbiomes on the production of plant antioxidant enzymes and soil enzymes were investigated under salinity stress. Results showed that co-inoculation, especially with K-humate, yielded superior outcomes compared to individual inoculations. The laboratory experiment findings were confirmed by a field trial conducted in saline-alkaline soil in the Northeastern Nile Delta region. The study found that the integrated inoculation of cyanobacteria, yeast, and mycorrhizae with K-humate, along with 25% mineral NPK fertilization enhanced microbial activity, including AMF colonization, spore density, and total bacteria, cyanobacteria, and yeast counts in the plant rhizosphere. It also increased soil enzyme activity, improving soil fertility compared to individual or mineral control treatments. This integration resulted in wheat yields of 2.77 tons/ha and faba bean yields of 4.75 tons/ha. Crop quality improved, with higher levels of nitrogen, potassium, phosphorus, and protein in wheat grains and faba bean seeds. Microbiomes inoculation increased potassium uptake over sodium, enhancing the potassium/sodium ratio and salt stress tolerance. This approach reduces reliance on costly mineral fertilizers by up to 75%, enabling economically viable cultivation in marginal lands. These sustainable practices optimize resource utilization, maximize economic efficiency, and preserve natural resources.

Accurate forecasting of crop yields holds paramount importance in guiding decision-making processes related to breeding efforts. This study focused on the application of multi-sensor data fusion and machine learning algorithms based on unmanned aerial vehicles (UAVs) in wheat yield prediction. Five machine learning (ML) algorithms namely random forest (RF), partial least squares (PLS), ridge regression (RR), K-Nearest Neighbor (KNN) and eXtreme Gradient Boosting Decision Tree (XGboost) were utilized for multi-sensor data fusion, and three ensemble methods including the second-level ensemble methods (stacking and feature-weighted) and the third-level ensemble method (simple average) for wheat yield prediction. The 270 wheat hybrids were used as planting materials under full and limited irrigation treatments. A cost-effective multi-sensor UAV platform, equipped with red–green–blue (RGB), multispectral (MS), and thermal infrared (TIR) sensors, was utilized to gather remote sensing data. The results revealed that the XGboost algorithm exhibited outstanding performance in multi-sensor data fusion, with the RGB+MS+Texture+TIR combination demonstrating the highest fusion performance (R2=0.660, RMSE= 0.754). Compared with the single ML model, the employment of three ensemble methods significantly enhanced the prediction accuracy of wheat yield. Notably, the third-layer simple average ensemble method demonstrated superior performance (R2 = 0.733, RMSE= 0.668 t ha-1). It significantly outperformed both the second-layer ensemble methods of Stacking (R2= 0.668, RMSE= 0.673 t ha-1) and feature-weighted (R2= 0.667, RMSE= 0.674 t ha-1), thereby exhibiting superior predictive capabilities. This finding demonstrated that the third-layer ensemble method not only augments the predictive ability of the model but also fine-tuned the accuracy of wheat yield prediction through the employment of simple average ensemble learning. Consequently, it offers a novel perspective for crop yield prediction and breeding selection.

The Midwestern region of the United States has been experiencing periodic forage shortages due to frequent droughts, a growing livestock population, and reliance on traditional farming practices. This study evaluated the dry matter yield (DMY), forage nutritive value, water use efficiency (WUE), and economic viability of forage soybean [Glycine max (L.) Merr.] in a no-till winter wheat-based rainfed cropping system in the Midwest, USA. The research aimed to identify alternative summer forage crops that are drought-resilient, require lower inputs, mitigate seasonal gaps, and provide higher DMY and forage nutritive value compared to traditional forages. A four-year field experiment in a randomized complete block design with four replications assessed these parameters at various growth stages and planting dates. Results showed that forage soybean had a high DMY (~13 Mg ha-1), especially when optimally planted and harvested at the R3 stage. Forage nutritive value, including crude protein (CP), in vitro dry matter digestibility (IVDMD), and relative feed value (RFV), was highest at early vegetative stages (V2-V3), meeting livestock nutritional requirements. Forage soybean also demonstrated good WUE (21 kg ha-1 mm-1), making it suitable for water-limited regions. Economic analysis indicated substantial net profits ($322 per hectare), confirming its economic viability. The study concludes that forage soybean is a promising summer forage option for Midwest growers, offering high-quality forage, efficient water use, and economic benefits. Further research, particularly animal feeding trials, is recommended to validate its potential for widespread adoption in cropping systems.

Seed potato treatment is vital for plant protection, yield enhancement, and product quality. In the conducted research, the plant biostimulator Supporter was applied to evaluate its impact on potato yields. Field studies were conducted in Northeastern, Northwestern, Western, and Southwest Poland from 2015 to 2017, using a randomized complete block design with a split-plot arrangement. The use of seed treatment technology with the Supporter product resulted in increased overall and commercial potato yields and improved yield tuber structure compared to traditional cultivation methods without tuber treatment before planting. Conclusion: The application of the plant biostimulator Supporter in seed potato treatment technology brings significant benefits, including, increased potato yield and improved yield structure. The cultivation location significantly influences potato yield and tuber structure. Understanding these differences can aid in better adapting cultivation practices and selecting varieties to specific local conditions, potentially leading to increased potato crop productivity. In terms of efficiency and yield quality, further research into its application in agricultural practice is recommended, which may contribute to further increasing potato production efficiency and quality. Developing more ecological and efficient farming practices can help meet society's growing food needs.

Machine learning and computer vision have proven to be valuable tools for farmers to streamline their resource utilization to lead to more sustainable and efficient agricultural production. These techniques have been applied to strawberry cultivation in the past with limited success. To build on this past work, in this study two separate sets of strawberry images, along with their associated diseases, were collected and subjected to, resizing, and augmentation. Subsequently, a combined dataset consisting of 9 classes was utilized to fine-tune three distinct pre-trained models: Vision Transformer (ViT), MobileNetV2, and ResNet18. To address the imbalanced class distribution in the dataset, each class was assigned weights to ensure nearly equal impact during the training process. To enhance the outcomes, new images were generated by removing backgrounds, reducing noise, and flipping them. The performances of ViT, MobileNetV2, and ResNet18 were compared after being selected. Customization specific to the task was applied to all three algorithms, and their performances were assessed. Throughout this experiment, none of the layers were frozen, ensuring all layers remained active during training. Attention heads were incorporated into the first 5 and last 5 layers of MobileNetV2 and ResNet18, while the architecture of ViT was modified. The results indicated accuracy factors of 98.4%, 98.1%, and 97.9% for ViT, MobileNetV2, and ResNet18, respectively. Despite the data being imbalanced, the precision, which indicates the proportion of correctly identified positive instances among all predicted positive instances, approached nearly 99% with the ViT. MobileNetV2 and ResNet18 demonstrated similar results. Overall, the analysis revealed that the Vision Transformer model exhibited superior performance in strawberry ripeness and disease classification. The inclusion of attention heads in the early layers of ResNet18 and MobileNet18, along with the inherent attention mechanism in ViT, improved the accuracy of image identification. These findings offer the potential for farmers to enhance strawberry cultivation through passive camera monitoring alone, promoting the health and well-being of the population.

Plants support numerous microorganisms within their tissues and the rhizosphere, and these microorganisms, known as the microbiota, can influence plant growth and health. Up to 40% of a plant's photosynthetic metabolism may be invested in the rhizosphere. The microbiota is considered an extra genome that can be modulated to meet plant needs. Researchers have identified a set of genes from these microorganisms, known as the microbiome, which can be manipulated to enhance plant growth and health, improve nutrient absorption, reduce the need for chemical fertilizers, increase resistance to pathogens and pests, and increase stress tolerance. In particular, fungi exhibit large genetic and metabolic diversity and are often used to promote plant growth. For example, the fungus Purpureocillum lilacinum has been employed primarily as a biocontrol agent to manage nematodes, but some studies have suggested that it may also promote plant growth by increasing the efficiency of the plant to absorb nutrients from the soil and provide phytohormones to plants. Therefore, the current review aims to summarize the existing literature on the use of this fungus in agriculture as nematodes control and discuss its potential as a plant growth promoter.

This research was to examine the impacts of long-term rice-crayfish coculture systems(RS) on soil nutrients, carbon pools, and rice yields in paddy fields , aiming to establish a scientific basis for the sustainable development of RS in the northern region of Zhejiang. The results showed that the change from rice monoculture (CK) to RS resulted in a 24.99% increase in the 5-year average of soil ammonium nitrogen(AN), while the soil nitrate nitrogen(NN), available potassium(AK), and available phosphorus content(AP) decreased by 28.02%, 16.05%, and 28.76% respectively. Moreover, the total organic carbon(TOC), easily oxidizable organic carbon(EOC), dissolved organic carbon(DOC), and microbial biomass carbon(MBC) decreased by 2.45%, 8.82%, 35.31%, and 65.84% respectively. Correlation analysis showed that there was a significant positive correlation between NN, EOC and MBC in the RS. In terms of rice yield, 5-year average of rice yield in RS has decreased by 8.4% compared to CK.The average yield of planting early-maturing varieties of rice was reduced by 13.16%, while the average yield of planting late-maturing varieties of rice was reduced by 6.00%. In conclusion, enhancing water and nutrient management and cultivating late maturing rice varieties are essential strategies for achieving the sustainable development of RS in northern Zhejiang.

Abstract Safflower (Carthamus tinctorius L.) is a multipurpose minor crop consumed by developed and developing nations around the world with a limited research fund and genetic resources. Genomic selection (GS) is an effective modern breeding tool which could help to fast track the genetic diversity preserved in genebank collections to facilitate rapid and efficient germplasm improvement and variety development. In the present study, we simulated four GS strategies to compare genetic gains and inbreeding rates during breeding cycles in a safflower recurrent selection breeding program targeting grain yield (GY) and seed oil content (OL). We observed positive genetic gains over cycles in all four GS strategies, where the first cycle delivered the largest genetic gain. Single traits GS strategies had the greatest gain for the target trait but with very limited genetic improvement for the other trait. Simultaneous selection for GY and OL via index indicated higher gains for both traits than crossing between the two single trait independent culling strategies. The the multi-trati GS strategy with inbreeding control (GS_GY+OL+Rel) showed lower inbreeding rate but similar gain compared to GS_GY+OL (without inbreeding control) after few cycles. Our finding lay the foundation for the future safflower GS breeding.

For this research we are selected three indicators of wheat: yield (t/ha), producer price (USD/t) and share of the harvested area under wheat in relation to the total land area of country (%). The mentioned indicators were analyzed for the period 2006-2021 in thirty-two European countries. The purpose of the research is to determine which of the mentioned indicators achieve average annual growth/decrease rates, what is the correlation between them, how European countries are grouped with their similarities and differences. The research examines the impact of the COVID-19 pandemic on the mentioned indicators in a two time phases: Phase I, before the pandemic (2006-2019); Phase II, during the pandemic (2020-2021). The methodological approach to the research topic involved the application of descriptive statistics, as the method of principal components analysis (abbr. PCA) with graphics. A positive correlation exists only between the yield of wheat and the share of the harvested area under wheat in the total area of the land (0.291). PCA method showed that countries are grouped differently depending on the observed indicator and the analyzed time phase.

In the Vietnamese Mekong delta, soil quality and crop yield are steadily declining under rice monocultures with three crops per year. The objective of this study was to evaluate the medium-term effects of rotating rice with upland crops and adding organic amendments on rice yield and relate it to soil quality. A field trial with split-plot design including two factors and three replicates was carried out from 2017 to 2020, over the course of nine consecutive cropping seasons. Crop rotations and organic amendments were applied as main-plot and subplot factors, respectively. The rotations were: 1) rice–rice–rice (R–R–R), 2) soybean–rice–rice (So–R–R), and 3) sesame–rice–rice (Se–R–R), while organic amendment treatments included: i) no amendment (NO-AM); ii) compost of rice straw and cow manure (RS+CM), and iii) sugarcane compost (SGC); the composts were applied at a rate of 2.0 t ha-1. The rotation cycle started with the so-called spring–summer (SS), followed by summer–autumn (SA) and ended with the winter–spring (WS) season. Rice yield significantly (P < 0.05) increased by organic amendments after nine growing seasons (2019–2020 WS), with an increment of 5.1% for RS+CM (7.07 ton/ha) and 6.1% for SGC (7.14 ton/ha). Contrary to our expectation, rotations with upland crops did not significantly increase rice yield. Rice yield significantly and positively correlated with an integrated soil quality index SQI (r = 0.86) for the topsoil (0–15 cm), but not for the subsoil (15–30 cm). The increased availability of soil nutrients (Si and marginally also P) and improved soil physical properties probably induced by organic amendments, along with other soil properties under study, cumulatively attributed to enhanced rice yield. Use of a SQI involving several soil quality indicators enables to overall quantify the importance of soil fertility for rice yield versus other factors and it provides an effective means of quantifying the integrated effect of improved management. Moreover, integrating a wide range of soil quality indicators in a SQI ensures its applicability across diverse settings, including different crop rotations and various soil types.

To investigate the effects of organic fertilizer combined with reduced chemical fertilizer on radish yield, quality, and soil environment in high mountainous areas (elevation: 1800 m), and to mitigate the environmental pollution caused by excessive use of chemical fertilizers. The field trial was conducted to study the effects of different fertilizer treatments. (Control:local fertilizer application rate: 375 kg·hm² reduction in chemical fertilizer + 4500 kg·hm² organic fertilizer; T1:12% reduction in chemical fertilizer + 4500 kg·hm² organic fertilizer; T2:20% reduction in chemical fertilizer + 4500 kg·hm² of organic fertilizer; T3:28% reduction in chemical fertilizer + 4500 kg·hm² organic fertilizer). Four different fertilizer ratios were studied to assess their impacts on radish quality, yield, and soil environment. The findings showed that T2 significantly increased radish yield by 12.92%. Moreover, it led to significant improvements in the content of vitamin C, soluble sugars, soluble solids, soluble proteins, titratable acidity, and glucosinolates, which increased by 10.62%, 2.15%, 50.00%, 26.90%, 43.90%, and 44.57%, respectively. Treatment T2 also significantly increased soil nutrient content, with a 7.69% and 14.29% increase in total nitrogen and total phosphorus content compared to the control (Control) treatment, and a significant reduction of 21.64% in soil bulk density . T2 treatment significantly enhanced soil urease activity, sucrase activity, alkaline phosphatase activity, and catalase activity, showing an improvement of 28.97%, 55.92%, 52.08%, and 17.47% compared to the control, respectively (p<0.05). Moreover, treatment T2 resulted in a relative abundance increase of 12.25% and 10.43% in Proteobacteria and Actinobacteria respectively. Thus, the combined application of T2:20% reduction in chemical fertilizer + 4500 kg·hm² of organic fertilizer improved the quality and yield of radish while optimizing the soil environment. T2 effectively promoted radish growth, enhanced radish yield and quality, and improved the soil environment.

Ammonium sulfate has been utilized in agriculture; however, there is a dearth of research on its application in maize cultivation subsequent to the implementation of nitrification inhibitors or coating. This study aims to analyze the impacts of various combinations of ammonium sulfate fertilizers on soil nutrients, plant nutrient uptake, yield, and fertilizer utilization efficiency in maize cultivation to ascertain the optimal and stabilized disposal method for ammonium sulfate. A completely randomized design was employed with five treatments (AU, the control using urea; AS, treatment using ammonium sulfate; ASN, treatment using ammonium sulfate with a nitrification inhibitor; ASG, treatment using oil-coated ammonium sulfate; ASD, treatment using oil-humic acid-coated ammonium sulfate). Results showed that: (1) Compared with AU and AS, ASN, ASG and ASD decreased the leaching rates of TN, NH4+-N and NO3-N to the 10-20 cm soil layer, and more residual N was obtained in 0-10 cm soil layer. The first-order kinetic equation Nt=N0(1-e-kt) can better fit the process of nitrogen accumulation and release, and the N release rate constant is AU>CK>AS>ASH>ASN>ASD; (2) Compared with AU and AS treatments, the plant dry weight, grain dry weight, spike width, spike length, and yields of maize increased by 8.85-11.08%, 12.98-14.15%, 2.95-3.52%, 5.50-5.65%, and 43.21-51.10% under ASG treatment respectively. The impact of effective spike number on maize yield was found to be significant, as demonstrated by the path analysis conducted in this study. Furthermore, the accumulation levels of nitrogen, phosphorus, and potassium within above-ground plants significantly increased under the ASG treatment compared to the AU and AS treatments. The partial productivity of nitrogen, phosphorus, and potassium increased by 1.43-1.51-fold under ASG treatment, while grain nitrogen balance, grain phosphorus balance, and grain potassium balance increased by 1.41-1.58-fold, 1.51-1.95-fold, and 1.15-l.96-fold respectively. The oil-coated ammonium sulfate, therefore, exhibited the optimal slow-release effect of nutrients, thereby achieving superior performance in enhancing maize production and efficiency.

The substitution of chemical fertilizers by organic manure plays a critical role in sustainable crop production. Nevertheless, organic amendments promote the global warming potential (GWP) in rice paddies due to increased methane (CH4) emissions. Increasing evidence shows that lime application can reduce CH4 emissions from acidic paddy soils, while it is still not clear whether liming can reduce the GWP in rice fields under organic manure substitution. A two-year field experiment was conducted to investigate the impacts of pig manure substitution and lime application on grain yield, CH4 and nitrous oxide (N2O) emissions in a subtropical double-cropped rice field in China. The experiment consisted of three treatments: chemical fertilization (CF, 100% N from urea), 50% of chemical N substituted by pig manure (1/2N + M), and the 1/2N + M treatment plus lime amendment (1/2N + M + L). On average, 1/2N + M reduced rice yield by 5.65% compared to CF, while lime application had no effect on rice yield. Mean cumulative CH4 emissions were 218.8% higher in 1/2N + M than in CF, whereas 1/2N + M + L reduced CH4 emissions by 36.6% compared to 1/2N + M. Neither pig manure substitution nor lime application affected N2O emissions. Consequently, 1/2N + M increased the GWP and greenhouse gas intensity (GHGI) by 214.6% and 228.3%, respectively, compared to CF. In contrast, 1/2N + M + L reduced the GWP and GHGI by 36.4% and 36.5% compared to 1/2N + M. Lime application can mitigate CH4 emissions and GWP induced by pig manure amendment in double-cropped rice fields.

The research work explores the impact of temperature on Silicon photovoltaic (PV) panels considering Nigeria as case study. It is found that high solar radiation in Nigeria increases surface temperature of PV panel above 25oC of optimal operating temperature of PV panels. Redundant energy gain from incident solar energy is dissipated at the rear of PV panels as heat, which reduces the efficiency of PV panel. Cooling mechanism is needed to cool the PV panels to increase the efficiency. In this study we demonstrated a unique design of a bifunctional photovoltaic-thermal (PVT) system by employing heat exchanger at the rear of PV panel and water is used as a working fluid that is circulated through the heat exchanger to remove the excess heat. It is observed from the simulation results that Maiduguri peak annual electrical power output gives 1907kWh/kWp which is the highest, because of high solar radiation average of 727W/m2 in a year. And for Makurdi the peak annual electrical power output of 1542kWh/kWp while for Port Harcourt the peak power output of 1355kWh/kWp respectively. Interestingly, Polycrystalline Si-PV surface temperature decrease from 49.25oC to 38.38oC. Electrical power increased from 1526.83W to 1566.82W in a day and efficiency increase from 13.99% to 15.01%.

Soybean (Glycine max L.) is a vital leguminous crop known for its rich nutritional profile, includ-ing high protein and oil content, making it a valuable resource in global agriculture and human nutrition. In Pakistan due to regulatory issues non-GMO soybean is grown therefore, the universal herbicide control method is not applicable. Similarly, for other crops, specific herbicides are avail-able but for soybean no crop specific herbicide is present. A comprehensive study was conducted over two growing seasons, in 2022 and 2023, at Agronomic Research Farm University of Agri-culture Faisalabad. The research involved 16 different treatments, including both six pre-emergence and eight post-emergence herbicides as well as a control group and weedy check. Findings of this study showed that critical importance of weed management in soybean cultiva-tion, as unchecked weed infestation can lead to substantial yield losses. Among the pre-emergence herbicide S-Metolachlor + Pendimethalin performed best and showed higher plant height (54.33 cm & 53.67 cm), 100 grain weight (11.57 g & 12 g), seed yield plant-1 (13.07 g and 12.87 g), lower Susceptibility Index (10%), higher weed control percentage (91.21% & 95.65%) higher weed con-trol efficiency (92.02% & 93.43%), herbicide efficiency index (27.54% & 32.48%) and lower weed index (18.16% & 21.70%) during 2022 and 2023 respectively. However, in post emergence herbi-cide the Fluizefop-p-butyl is most effective herbicide due to less crop injury 10% Susceptibility In-dex, higher plant height (42.67 cm & 44 cm), whole plant weight (93.33 g & 95 g), 100-grain weight (11.40 g & 11.77 g), seed yield plant-1 (12.87 g & 13.13 g), higher weed control percentage (91.12% & 91.03%) higher weed control efficiency (89.73% & 92.36%, herbicide efficiency index (21.18% & 30.41%) and lower weed index (19.42% & 20.08%) in both 2022 and 2023 respectively. Notably, herbicides such as S-Metolachlor + Atrazine + Mesotrione, Topramezone, Mesosulfu-ron-methyl + Iodosulfuron-methyl sodium and Mesotrione + Atrazine led to complete plant mor-tality, resulting lethal to soybean. The findings of this study support the hypothesis that screened the best suitable herbicides with less plant injury, and higher efficiency index. So, it is recom-mended that the application of S-Metolachlor + Pendimethalin as PRE and Fluizefop-p-butyl as POST showed the least injury and best weed control results with higher grain yield.

The Fruit Harvest Helper, a mobile application developed by Northwest Nazarene University’s (NNU) Robotics Vision Lab, aims to assist farmers in estimating fruit yield for apple orchards. Currently, farmers manually estimate the fruit yield for an orchard, which is a laborious task. Fruit Harvest Helper seeks to simplify their process. While prior research efforts at NNU concentrated on developing an iOS app for blossom detection, this current research aims to adapt that smart farming application for apple detection across multiple platforms, iOS and Android. The old and new applications were designed with an intuitive user interface that is easy for farmers to use, allowing for quick image selection and processing. Unlike before, the adapted app utilizes a color ratio-based image segmentation algorithm implemented in OpenCV C++ to detect apples in apple tree images selected for processing. The results of testing the algorithm with a dataset of images indicate an 8.52% Mean Absolute Percentage Error (MAPE) and a Pearson correlation coefficient of 0.6 between detected and actual apples on the trees. These findings were obtained by evaluating the images from both the east and west sides of the trees, which was the best method to reduce the error of this algorithm. Although the Fruit Harvest Helper shows promise, there are many opportunities for improvement. These opportunities include exploring alternative machine-learning approaches for apple detection, conducting real-world testing without any human assistance, and expanding the app to detect various types of fruit. The Fruit Harvest Helper mobile application is among the many mobile applications contributing to precision agriculture, nearing readiness for farmers to use in yield monitoring and farm management.

Variable and sometimes contrasting effects of using artificial rhizobium inocula to increase grain legume performance have been reported. The objectives of this systematic review and meta-analysis were therefore to (i) estimate the overall effect of rhizobium inocula on grain yield and protein content and (ii) identify potential confounding factors that explain the observed variation. A web of Science database literature search was carried out in 2016. Data from all field experiments, greenhouse and pot experiments that compared grain yields and protein contents in Rhizobium/Bradyrhizobium-inoculated with non-inoculated control crops were extracted and analyzed using previously described unweighted and weighted meta-analysis protocols. GRADE assessments of the strength of evidence of results from the weighted meta-analyses were carried which included an assessment of the risk of publication bias. Results: For unweighted meta-analyses we identified eligible data in 236 and 36 studies for grain yield and protein content respectively. For weighted meta-analyses we identified eligible data in 92 and 8 studies for grain yield and protein content respectively. Rhizobium inoculation was found to (i) significantly increase grain yield in both the unweighted (mean percent difference: 41%, 95%CI 36,46, p<0.0001) and weighted meta-analysis (Standardized mean difference: 1.56, 95%CI 1.26,1.87, p<0.0001) and (ii) significantly increase protein content in the unweighted meta-analysis (mean percent difference: 11%, 95%CI 5,18, p<0.0001), but not the weighed meta-analyses which only detected a trend (0.1>p>0.05) towards higher protein content in inoculated grain legume crops. Multi-level model-based weighted meta-analyses suggest that the (i) type of experiment, (ii) type of fertilizer used in experiments, (iii) grain legume type/species and (iv) the country in which experiments were carried out, were confounding factors. The main limitation of the evidence is that a large number of publications did not report measures of variation and could therefore not be included in the more scientifically sound weighted meta-analyses. However based on the large evidence-base available for grain yield it can be concluded that overall Bradyrhizobium/Rhizobium seed inoculation results can increase grain yield by ~40% compared with non-inoculated grain legume crops.

The study was conducted to evaluate the agronomic performance, forage yield, and nutritive values of Desho grass varieties under supplementary irrigation at Dambi Dollo University experimental site, Western Ethiopia. Three Desho grass varieties (Areka /DZF#590, Kindu kosha-1/DZF #591, and Kulumsa /DZF #592) were arranged in randomized complete block design (RCBD) with three replications. The CROPWAT 8.0 model, local climate data, forage data, and soil data were used to determine Desho grass water requirements and irrigation schedules. The agronomic parameters, yield, chemical composition, and in vitro digestibility of the feed samples at standardization cut were determined following the standard procedures. The results showed significant differences (p

: Pearl millet (Pennisetum glaucum L) R. Br) is a subtropical grain and forage crop. It is privileged with several desirable forage attributes. Nevertheless, research on pearl millet is limited especially as a forage crop in the developing countries. Therefore, the objectives of this study were to investigate the field performance and stability of pearl millet genotypes for forage yield across seven environments. The study was conducted in seven environments (combination of locations and seasons) during 2016/2017-2018/2019 seasons. Twenty-five pearl millet genotypes, selected based on forage yield from a core collection of 200 accessions, were arranged in alpha lattice design with three replications. The parameters measured were fresh forage yield, days to flowering, plant height, number of culms m-2, leaf to stem ratio, and stem girth. The combined analysis revealed that environments, genotypes and their interaction had significant effects on all traits studied except the genotypic effect on stem girth. Across the seven environments, four genotypes (G14, G01, G12, and G22) out-yielded the check genotype in fresh matter yield by 20.7, 16.5, 11.0 and 9.8%, respectively. The additive main effects and multiplicative interaction (AMMI) analysis showed that the genotype, environment and their interaction were highly significant (P≤0.001) for fresh matter yield. The results of AMMI Stability Values (ASV) and the genotype selection index (GSI) combined with the AMMI estimate-based selection showed that genotypes G14, G22 and G01 were the most stable and adapted genotypes and were superior to the check genotype. These results indicate that forage pearl millet varieties could be developed directly through evaluation of the wealth available collections or indirectly through hybridization in crop breeding programs.

Understanding the genotype x environment (GE) interaction for traget trait is valuable for growers, agronomists, breeders and the seed industry. The objective of this study was to see and explore the genotype x environment interaction for grain yield of wheat to better guide genotype selection and breeding. The genotype main effect and GE interaction effect (GGE) biplots resolved the following three genotypes: 85 (ETW17-377), 82 (ETW17-374) and 13 (ETW17-281) for being the best yielding and stable. The Kulumsa site planted on 4^th of July 2017 (environment 7=E7) and the DebreZeit site on 20^th of July 2017 (E3) were the most effective environments in distinguishing the test genotypes and are thus suitable environments for future evaluation and selection with specific adaptation. Melkasa site planted on 4^th July (E9) was a representative environment where genotypes can be evaluated for wide adpaptation. The genetic covariate biplot indicated that thousand kernel weight (TKW) and plant height (PH) had significant positive associations with grain yield implying the possible concurrent indirect selection of both traits for exploiting GE interaction for grain yield of wheat.

In the century and a half since Maxwell first conjured his “finite being” which Lord Kelvin subsequently dubbed a “daemon”, researchers have explored the connections between non-equilibrium thermodynamics, entropy, and information theory. In recent years various Thermodynamic Uncertainty Relations (TURs) have been derived to inform upon the relationship between the entropy production and the precision possible in thermodynamic machines and processes. In this paper the recently derived TURs are applied to the hypothetical thermodynamic economy as described by Parker [1]. The TURs define the lower bound on the total entropy production of the economy. Changes in this entropy production rate has consequences on the stability of the economic system and plays a central role in the business cycle. This new perspective has important implications for policy makers, researchers, and other economic actors.

Throughout history, the pursuit of diagnosing and predicting crop yields has evidenced genetics, environment, and management practices' intertwined roles in achieving food security. However, the sensitivity of crop phenotypes and genetic responses to weather and climate remains unclear, hampering the identification of the underlying abilities of plants to adapt to climate change. We hypothesize that the PAWN global sensitivity analysis (GSA) coupled with a genetic by environment (GxE) model -built of environmental covariance and genetic markers structures- can evidence the contributions of climate on the predictability of maize yields in the U.S. and Ontario, Canada (US-CA). The GSA-GxE modeling framework estimates the relative contribution of climate variables such as solar radiation, temperature, rainfall, and relative humidity on improving maize yield predictions in US-CA. We use an improved version of the Genomes to Fields (G2F) initiative multi-dimensional database to build the environmental covariance matrices for the proposed GSA-GxE framework. The PAWN indices show that the aggregated GxE model’s highest sensitivity levels over US-CA were attributed to solar radiation, temperature, rainfall, and relative humidity. In one-third of the locations, rainfall was the primary climate variable responsible for maize yield predictability. Also, a consistent pattern of top sensitivity indices by location indicates that Relative Humidity, Solar Radiation, and Temperature were distributed as the main or the second most relevant drivers of maize yield predictability.

This paper presents the PEnsemble 4 model, a sophisticated machine learning framework that integrates IoT-based environmental data to accurately forecast maize yield. With the projected significant growth in global maize demand over the next decade, the inherent risks posed by the crop’s dependence on weather conditions necessitate improved prediction capabilities. The PEnsemble 4 model, developed with high accuracy, incorporates comprehensive datasets encompassing soil attributes, nutrient composition, weather conditions, and UAV-captured vegetation imagery. By employing a combination of Huber and M estimates, the PEnsemble 4 model effectively analyzes temporal patterns in vegetation indices, specifically CIre and NDRE, which serve as reliable indicators of canopy density and plant height. In addition, this research significantly contributes to precision agriculture by offering an efficient and sustainable alternative to conventional farming practices through precise yield predictions. Notably, the PEnsemble 4 model enables earlier estimation, advancing the timeline for yield prediction from the conventional day 100 in the R6 stage to day 79 in the R2 stage. This improvement enhances decision-making processes in farming operations. The remarkable accuracy rate of 91% underscores the importance of adopting a multifaceted data approach that harnesses IoT-derived environmental insights. Additionally, the PEnsemble 4 model extends its benefits beyond yield prediction, facilitating the detection of water and crop stress, as well as disease monitoring in broader agricultural contexts. Ultimately, the PEnsemble 4 model establishes a new standard in maize yield prediction, revolutionizing crop management and protection through the synergistic utilization of IoT and machine learning technologies.

The longleaf pine (Pinus palustris P. Mill.) forest type occupied a much greater area in the United States prior to the arrival of Europeans, estimated to be around 37.2 million hectares. This area has been greatly reduced, and these ecosystems now occupy only about 1.2 to 1.6 million hectares. However, there has been great interest in the restoration of this forest type, and existing stands are actively managed. Thus, managers need tools to estimate site quality and ultimately productivity. Here, 16 existing equations to estimate site index and dominant height in naturally regenerated longleaf pine stands are examined for their behavior across a range of site quality and age conditions. Others can use this information as a reference to determine which equation may be best for their situation.

A comprehensive investigation was undertaken at Vytautas Magnus University Experimental Station, located at 54°52’50” N latitude and 23°49’41” E longitude on soil (Epieutric Endocalcaric Planosol – PLe-gln-w) since 1999, to understand the impacts of different agrotechnical measures on soil health and crop yield. Two primary factors were assessed. Factor A incorporated practices of straw removal versus straw chopping and spreading, while Factor B evaluated a spectrum of tillage techniques: conventional deep ploughing, shallow ploughing, ploughless tillage, single seedbed discing, and two no-tillage practices, one of which involved cover crops. Findings from this long-term study highlight the significant potential of specific farming systems in enhancing soil organic carbon. It has a positive effect on the release of CO2 emissions from the soil, thus promoting soil resilience and increasing plant productivity. These insights are paramount in devising sustainable agricultural strategies to counter the challenges of climate change on agroecosystems. This research showcases the profound effects of combining residue management and tillage practices, setting a novel standard for sustainable soil management of climatic uncertainties.

The mechanical pre-treatment constitutes an unavoidable pre-step prior to biofuels conversion. As the cost of this step is often underestimated, recently researchers have striven to identify and characterize the mechanical pre-treatment effects in terms of post-treatment physical characterization, derived improvement of enzymatic digestibility, and output yields. The status of existing mechanical pre-treatment techniques is reviewed by substrate’s typology for lignocellulose biomass, focusing on comminution techniques. Emphasis has been dedicated to the particle size achieved after treatment, crystallinity breakage and eventual inhibitory phenomena deriving from the application of particle size reduction, which are analysed and discussed.

The agronomic characteristics of Cenchrus purpureus were assessed through a randomized block experimental design with seven accessions (Taiwan grass, King grass, Elephant grass, Merkeron, CT-115, Purpule grass and Maralfalfa) as treatments and four replications research was carried out at the Instituto Tecnológico Superior de Tantoyuca, in 2019 and 2020, under rainfed conditions. Sowing density was established at 36 tillers in 25 m2. Green and dry matter yield, daily rates of dry matter accumulation in leaves, leaf/stem ratio, height, leaf area index and cutting frequency were assessed. Rainfall amount, temperature, relative humidity and global radiation levels were recorded to assess their effect on the evaluated variables. One-way ANOVA and multivariate analysis techniques, such as multiple linear regression (MLR), Clustering, and Principal component analysis (PCA) with the Statistica V7 software, were used. The leaf area index was greatest (p < 0.05) on the dry season. Green and dry matter yield were greatest in Maralfalfa (p < 0.05). Variation in the results is attributed to weather phenomena; nonetheless, Elephant grass and Maralfalfa showed the highest yields. Quality parameters must be evaluated to identify those grasses with the best attributes.

Crop yield estimation supported by satellite remote sensing data can provide expeditious and strategic information for farmers’ decision-making. Most recent forecasting methods have indicated a promising pathway based on machine learning algorithms. However, validation performances, demand for big data and their inherent inexplicability have not yet consolidated a substantial differential to replace methods based on simpler and more understandable models. This paper proposes an approach based on simple linear models fitted from vegetation indices (VIs) assessed at regular intervals of time series derived from MODIS satellite images, aiming to forecast cotton yields in representative areas of the Brazilian Cerrado. Data from 281 commercial production plots were taken to train (167 plots) and test (114 plots) linear regression models relating seed cotton yield and nine well-known VIs averaged in 15-days intervals. Among the evaluated VIs, EVI (Enhanced Vegetation Index) and TVI (Triangular Vegetation Index) showed the lowest root mean square errors (RMSE) and the highest determination coefficients. The best periods for in-season yield prediction were from the 90-105 to 135-150 days after sowing (DAS), i.e. phenological phases corresponding to boll development, open boll and fiber maturation, with lowest RMSE of about 750 kg ha-1 and R2=0.70. The best forecasts for early crop stages were provided by models at the peaks (maximum value of the VI time-series) for EVI and TVI, which occurred around 80-90 DAS. The proposed approach makes the yield predictability more inferable along the crop time series just by providing sowing dates, contour maps and its respective VIs.

Genetic enhancement of grain production and quality is a priority in wheat breeding projects. In this study, we assessed two key agronomic traits - grain protein content (GPC) and thousand kernel weight (TKW) - across 179 Bulgarian contemporary and historic varieties, and landraces in three growing seasons. Significant phenotypic variation existed for both traits among genotypes and seasons, and no discernible difference was evident between the old and modern accessions. To understand the genetic basis of the traits, we conducted a genome-wide association study with MLM using phenotypic data from the crop seasons, best linear unbiased estimators, genotypic data from the 25K Infinium iSelect array, and a Bonferroni-adjusted p-value. As a result, 776 significant quantitative trait nucleotides (QTNs) organized into quantitative trait loci were discovered, including 25 loci associated with GPC, and 35 loci linked to TKW. Additionally, 14 environmentally stable QTNs were identified for TKW. Certain loci on chromosomes 2A, 3A, and 6B favorably in-fluenced GPC, while the locus on chromosome 6D impacted TKW positively. These loci may reflect novel associations to the two traits. Annotations for proteins involved in the remobilization of carbon and nitrogen from vegetative tissues to developing grain during senescence, as well as in the following buildup of resources required for seed germination, have been found for selected pu-tative candidate genes. These include genes coding for 11S globulin seed storage protein, glutamine synthetase, metalloendopeptidase, components of the ubiquitin/proteasome system, sucrose transporter, alpha-amylase, NAC and bZIP transcription factors. Our findings highlight promising genomic regions for targeted breeding programs aimed at improving grain yield and protein content.

This review explores the combination of renewable energy production and agriculture through agrivoltaic, with a focus on its impact on fruit crops. As the world seeks alternatives to fossil fuels, agrivoltaics offers a promising solution by integrating solar panels with farming practices. The study examines various agrivoltaic configurations with different fruit crops, emphasizing their influence on microclimatic conditions beneath the panels and the effects on crop produc-tion. In particular, it underscores the need for tailored solutions to balance energy yield and crop productivity and quality, with different shading levels affecting fruit quality/production. De-spite ongoing research, a comprehensive understanding of agrivoltaics' potential benefits and challenges remains crucial for its successful application and implementation in sustainable ag-riculture.

Yield calculation is an important link in modern precision agriculture, which is an effective means to improve breeding efficiency, and adjust planting and marketing plans. With the continuous progress of artificial intelligence and sensing technology, yield calculation schemes based on image processing technology have many advantages such as high accuracy, low cost, and non-destructive calculation, and have been favored by a large number of researchers. This article reviews the research progress of crop yield calculation based on remote sensing images and visible light images, describes the technical characteristics and applicable objects of different schemes, and focuses on detailed explanations of data acquisition, independent variable screening, algorithm selection and optimization. Common issues are also discussed and summarized. Finally, solutions are proposed for the main problems that have arisen so far, and future research directions are predicted, with the aim of achieving more progress and wider popularization of yield calculation solutions based on image technology.

In Tropical Monsoon climates, precipitation exceeds evapotranspiration, leading to increased surface runoff, especially in floodplain regions. The Bhagirathi-Hooghly River in India is the focus of the study, which analyses hydrology, sediment yield, and water balance in this floodplain area. This investigation employs the Soil and Water Assessment Tool (SWAT) model within the ArcGIS environment, using remote sensing data. The study area is divided into 4 sub-basins and 40 Hydrological Response Units (HRUs), with a focus on Land Use/Land Cover (LULC) parameters, soil attributes, and slope characteristics. Calibration (1998-2010) and validation (2011-2018) of river discharge and sediment yield are performed using the SUFI-2 algorithm within SWAT-CUP. The calibration process shows a strong correlation between observed and simulated data points, indicating the model's accuracy. The study reveals a pattern of early-year evapotranspiration followed by increasing rainfall during the monsoon season, leading to heightened surface runoff and sediment yield. Excessive rainfall, therefore, emerges as a pivotal driver of flood incidences within the floodplain. The insights derived from the SWAT model's floodplain data have the potential to inform flood control and sedimentation mitigation strategies. The assimilation of this data can empower local stakeholders and contribute to sustainable livelihoods and improved living conditions, offering guidance for future governmental policies.

Summer annual species are the most widely grown crops in the Upper Midwest, but reliance on a summer annual system has led to excessive soil and nutrient loss when crops are not present. Integrating winter rye (Secale cereale L.), known for its hardiness and environmental benefits, into the rotation can address these issues. However, there's limited understanding of the phenotypic diversity in winter rye during key growth stages that overlap with the typical planting dates for corn (Zea mays L.), soybean [Glycine max (L.) Merr], and late-planted crops like dry bean (Phaseolus vulgaris L.). Thus, the objectives of this study were to evaluate changes in biomass accumulation and quality of winter rye and triticale (x Triticosecale Wittmack) cultivars at three growth stages. Twenty cultivars were assessed over the 2014-2015 and 2015-2016 growing seasons across three environments in Minnesota. Winter rye and triticale were harvested for biomass at the tillering, booting, and soft dough growth stages and rye biomass yield and quality [i.e., crude protein, neutral detergent fiber (NDF), and 48-hour digestibility (NDFD)] were determined following harvest. Overall, there was little variation in each parameter among the cultivars within a location and growth stage. NDFD had some variation at the soft dough stage where digestibility ranged from 273 to 324 g kg-1 at the Crookston site and 332 to 406 g kg-1 at the St. Paul site. The lack of difference between cultivars indicates a wide range of choice when selecting a winter rye cultivar.

Peas are among the most widely consumed legumes and are of great benefit for human nutrition. Sowing and cultivation techniques are known to affect the yield and the quality of the seeds. Existing studies investigating the nutritional properties of the seeds from plants cultivated using different methods are continue to be of significant value. However, changes in the climate in recent years are presumed to have affected the optimum sowing dates for grain yield and quality. This study in-vestigates the effects of sowing peas at different sowing dates on the yield of the seed and on its nutrient content, as determined by certain quality traits (parameters). The experiment was con-ducted at the Aydin Adnan Menderes University Faculty of Agriculture in Turkey during the 2021-2022 and 2022-2023 pea production seasons. Specifically, it examined the yield of the seed (fresh/dry), its saponin and phenolic matter content and its amino acid composition in the case of five pea cultivars (Deren, Misya, Irmak, Karina, Local) sown at three different sowing times (November 15, November 30, December 15). The study found that the effects of sowing date on grain yield and quality characteristics were significant. However, the varieties' reactions to sowing dates were found to be different. The highest fresh seed yield (3.27 t ha-1) was obtained from samples sown at the second sowing date, while the highest dry yield (1.85 t ha-1) came from samples sown at the third sowing date. The cultivars also had a statistically significant effect on the yields. The highest fresh seed yields were obtained from the Misya (2.88 t ha-1) and Local (2.81 t ha-1) varieties, while the highest dry yields were obtained from samples of Local (1.76 t ha-1) and Irmak (1.73 t ha-1). In terms of sowing dates, the highest protein (27.75%) was obtained from the first sowing date, and the protein content decreased in the following dates. Misya was the cultivar from which the highest protein content (28.77%) was obtained. In the study, higher yields were obtained from the second and third sowing dates, while the first sowing time resulted in higher protein and amino acid composition. Similar to the protein content, the composition of almost all amino acids increased on the first sowing date. In addition, it was established that the saponin and phenolic substance contents of seeds varied with the sowing date.

Phosphorus (P) is a vital macronutrient crucial for crop productivity. Plants absorb P salts, mainly orthophosphate, from soil, yet the primary P source resides in organic materials. Soil phosphomonoesterases (APases) play a vital role in releasing P from organics via hydrolysis. Acid and alkaline phosphatases are crucial for alleviating P deficiency in plants. In this review focused on agricultural soils, we studied the relationship of biophysicochemical, agricultural management, and climate factors on APases also its connection with crop growth and yields. Our findings indicate a strong linkage between both APases and soil pH, positively influenced by clay content, organic matter, microbial biomass carbon, and nitrogen. Adopting healthy soil practices like balanced organic fertilizer usage, optimal soil water levels, reduced tillage, crop rotation, and using beneficial plant microbes help boost APase activity. However, the connection between APases and crop productivity remains uncertain due to insufficient research in this area. Our review emphasizes the vital need to evaluate the relationship between APases and meso-macrofauna, alongside essential plant nutrients such as potassium, nutrient ratios, and the synergistic effects of various factors. Understanding the rapid, efficient assimilation of P through APases in the plant-soil and/or plant-microbiota ecosystem it can be crucial for crop productivity and yields.

Litchi (Litchi chinensis Sonn.) is considered as one of the most important sub-tropical fruits of the World. Under western part of Odisha, India, the litchi growers are facing problem of unstable and lower marketable yield and inferior quality due to higher incidence of fruit cracking, fruit drop, low sugar content and higher fruit acidity. Keeping in mind the positive effects of nutrients and bioregulators, the current study was conducted to elucidate their impact on fruit yield, and quality in the farmers field of Jamankira block in Sambalpur district of Odisha under Odisha University of Agriculture and Technology, India. For the studies, eight years old litchi trees were selected. With 12 treatments, the experiment was set up in a randomized block design replicated thrice viz, T₁: Spray treatment of Borax @ 0.5%; T₂: Spray treatment of Borax @ 0.3%; T₃: Spray treatment of ZnSO₄ @ 0.75% ; T₄: Spray treatment of ZnSO₄ @ 0.5%; T₅: Spray treatment of CaCl₂ @ 0.5%; T₆: Spray treatment of CaCl₂ @ 0.1%; T₇: Spray treatment of Humic acid @ 1.5%; T₈: Spray treatment of Humic acid @ 1%; T₉: Spray treatment of Seaweed extract @ 0.5%; T₁₀: Spray treatment of Seaweed extract @ 0.1 %; T₁₁: Foliar spray of NAA @ 20 ppm and T₁₂ : Control (water spray).The current study compared foliar feeding of different nutrient and bioregulators treatments, which were applied during the first week of December, just after completion of new leaf formation and untreated control. The total number of fruits per plant was recorded highest in plants sprayed with ZnSO4 @ 0.5% (T₄) followed by those treated with humic acid @ 1% (T₈). The highest total fruit yield was recorded in plants with foliar feeding of 0.3% Borax (T₂) which was found to be statistically similar to plants treated with seaweed extract @ 0.1% (T₁₀)and seaweed extract @ 0.5% (T₉).Among the treatments better response for higher number of marketable fruits and marketable yield was recorded in plants treated with both 0.3% Borax (T₂) followed by 0.5% Zinc sulphate (T₄), 1% Humic acid (T₈) and 0.1% CaCl₂ (T₆) in litchi. Application of 1% Humic acid (T₈) followed by 1.5% Humic acid (T₉) enhanced the fruit set (%) and fruit retention (%) along with reduction in fruit drop (%). The enhanced fruit size (fruit length and fruit breadth) and higher fruit weight was obtained in plants treated with 0.3% Borax in litchi. The foliar application of 0.3% Borax (T₂) had also resulted in higher TSS, total sugars, reducing sugar, lower acidity, highest aril weight and lower seed weight in litchi cv. Bombai.

Insurance serves as a mechanism to effectively manage and transfer revenue-related risks. We conducted a study to explore the potential financial advantages of index insurance, which protects agricultural producers, specifically sugarcane, against excessive rainfall. Creation of the index involved utilizing generalized additive regression models, allowing for consideration of non-linear effects and quantile generalized additive regression to evaluate relationships with lower quantiles, such as low yield events. To quantify the financial benefits for farmers, should they opt for excessive rainfall index insurance, we employed efficiency analysis based on metrics such as Conditional Tail Expectation, Certainty Equivalence of Revenue, and Mean Root Square Loss. The results of the regression model demonstrate its accuracy in predicting sugar cane yields, with a split testing R2 of 0.691. Additionally, our study suggests that this type of insurance could also apply to sugarcane farmers and other crop producers in regions where extreme rainfall threatens the financial sustainability of agricultural production.

The present article investigates the threshold analysis of yielding in a variable thickness rotating disk based on the Tresca criterion. The analysis is conducted on a Functionally Graded Material (FGM) constructed from tailored materials, following the theory of small deformations and for the case of plane stress. The elasticity modulus, density, and yield stress are assumed to be power functions of the radial coordinate. Poisson’s ratio is considered constant due to small variations in different materials. Additionally, the governing equation for the rotating disk is solved analytically. Besides the material type, another factor affecting the distribution of effective stress magnitudes is the cross-sectional shape (profile) of the disk. The thickness of the cross-sectional disk varies radially as a power function. In the current analysis, different conditions for the onset of yielding and the evolution of plastic flow are considered. For evaluation and validation, the obtained results are compared and validated against similar results for specific cases (homogeneous disk and constant thickness graded disk) available in previous references. The results indicate that considering variable thickness for the disk section significantly affects the stresses and the location of the initiation of yielding

Weather has significant impact on growth and plants development. It is important to analyze the influence of changing climate conditions on expression of plants agronomical characters. Two flax varieties were grown from 1987 to 2018 in the North-West of Russia. Whether conditions and their influence on flax agronomic characters were analyzed using variance and correlations analyses. Significant influence of year conditions on the manifestation of all evaluated characters was revealed. Starting from June high temperatures accelerate the development of plants at all stages. Prolongation of germination - flowering period is the most important for fiber productivity improvement. Oppositely, for formation of high quality fiber fast ripening in hot weather after flowering is preferable. Such data give possibility to predict the amount and quality of yield. Usage of weather conditions data also permits to compare results obtained in different years. Suggested method of year’s meteorological conditions classification can be used in other genebanks for systematization and analyses of crops field evaluation results. Correlation analyses reviled 3 correlated pleiades: (1) pleiade of productivity, (2) pleiade of fiber quality and yield, (3) pleiade of the growing season phases duration, the sums of active temperatures and precipitation during each period. Great influence of growing conditions on economically valuable traits indicates the necessity of searching for genotypes with stable characters manifestation for breeding new varieties, which will give stable yield and fiber of good quality.

To investigate the effect of nitrogen (N) application on carbon metabolism and yield of flag leaves and grains of spring wheat under drip irrigation in Xinjiang, a split - plot design was adopted from 2020 to 2021, with strong gluten wheat Xinchun 37 (XC37) and medium gluten wheat Xinchun 6 (XC 6) as the main plot factor and different nitrogen application rates as subplot factor. Four nitrogen application rates of 0, 210, 255 and 300 kg·hm-2 (CK2, B1, A1 and CK1, respectively) were set to analyze and compare the nitrogen response of key enzyme activity, soluble sugar, sucrose and starch content in flag leaves and grains to control yield formation. The results showed that with the increase of nitrogen application, Sucrose phosphate synthetase (SPS) and sucrose synthetase (SS) in flag leaves, SS in seeds, activities of adenosine diphosphate pyrophosphorylase (ADPG - PPase), soluble starch synthase (SSS), bound starch synthase (GBSS) and starch branching enzyme (SBE) in seeds, contents of soluble sugar and sucrose and yield in flag leaves increased first increasing and then decreasing. The A1 treatment (255 kg·hm-2) showed significant differences compared to other treatments, with increases of 7.95–158.33%, 8.69–155.12%, 7.65–53.25%, 5.41–62.83%, 2.85–85.52%, 3.08–57.30%, 8.87–79.16%, 9.33–196.55%, 9.43–112.78%, and higher levels of amylose, amylopectin, and total starch content than other treatments by 1.86–30.38%, 10.58–83.69%, and 7.96–63.09%, respectively. Correlation and stepwise regression analysis indicate highly significant positive correlation between yield and solube sugar and sucrose of flag leaves and grains, as well as their key emzymes and starch. Among them, soluble sugar in grains, amylopectin, and sucrose in grains have the greatest impact on the yield of XC37, determining 84.5% of its yield. SSS, soluble sugars in grains, amylopectin, and SBE have the greatest impact on the yield of XC 6, determining 80.4% of its yield. The starch shows a highly significant positive correlation with ADPG - PPase, SSS, GBSS, and SBE. There is a significant interaction effect between nitrogen application rate and variety, with better performance observed in Xinchun 37 compared to Xinchun 6. Under drip irrigation conditions in arid areas, nitrogen application of 255 kg·hm-2 can effectively regulate the metabolism of sucrose to starch in flag leaves and grains of spring wheat, which is conducive to the accumulation of starch in grains and the formation of yield.

Globally, weeds interfere with agricultural production activities and have a very serious impact on agriculture and animal husbandry. Identifying a safe and reliable weed control strategy might increase yield, production net income, and improve crop quality. A field experiment was carried out to explore the effects of weeds interference frequency on the yield and quality of Glycyrrhiza uralensis Fisch in an arid and semi-arid area of northwest China. The experiment consisted of seven treatments and were (1) no weeding, marked as WF0; (2)-(7) artificial weeding by hoe once every 1, 2, 4, 6, 8, 10 weeks after emergence, marked as WF1, WF2, WF4, WF6, WF8 and WF10, respectively. We found that the higher weeding frequency had a higher the plant height, photosynthesis, yield and quality. The highest yield was obtained in the WF1 treatment, while the cost of weeding was the highest among all treatments. The concentration of liquiritin and glycyrrhizic acid were increased by 53.24% and 36.57%, with the highest nitrogen metabolism enzymatic activities and quality in WF4 treatment. WF4 treatment exhibited the largest increases in the net income among all treatments in both growing seasons, with respective increases up to 71.39 % and 78.81%. These findings suggested that weeding once every 4 weeks would be an effective and sustainable measure to control weeds in an arid and semi-arid area.

A new approach is presented for dynamic modeling of chemical and isotopic evolution of C1-3 during the hydrocarbon generation process. Based on systematic data obtained from published papers for pyrolysis of various hydrocarbon sources(type I kerogen/source rock, type II kerogen/source rock, type III kerogen/source rock, crude oil, asphalt, etc), the empirical evolution framework of chemical and isotopic composition of C1-3 during the hydrocarbon generation process was built. Although the empirical framework was built only by fitting large amount of pyrolysis data, the chemical and isotopic composition of C1-3 derived from the pyrolysis experiments all follow the evolution laws, convincing us that it is applicable to the thermal evolution process of various hydrocarbon sources. Based on the simplified formula of the isotopic composition of mixed natural gas at different maturities (δ13Cmixed) δ13Cmixed=(X〖*n〗_iA 〖*δ〗^13 C_iA+Y〖*n〗_iB 〖*δ〗^13 C_iB)/(X〖*n〗_iA+Y〖*n〗_iB ), it can be derived that the cumulative isotopic composition of alkane generated in certain maturity interval can be expressed by the integral of the product of instantaneous isotopic composition and instantaneous yield at certain maturity point, and then divided by the cumulative yield of alkane generated in corresponding maturity interval. Thus, the cumulative isotopic composition(A(X)), cumulative yield(B(X)), instantaneous isotope(C(X)),and instantaneous yield(D(x)) in the dynamic model comply with the following formula during the maturity interval of (X0-X) A(X)=(∫_(X_0)^X▒〖C(X)*D(X)dx〗)/(B(X)), where A(X) and B(X) can be obtained by fitting of pyrolysis data, and D(x) can also be obtained from the derivation of B(X). The dynamic model was applied on the pyrolysis data of Pingliang Shale to illustrate the quantitative evolution of cumulative yield ,instantaneous yield, cumulative isotope and instantaneous isotope of C1-3 with increasing maturity.The dynamic model can quantify the yield of methane, ethane and propane as well as δ13C1, δ13C2 and δ13C3 respectively during the hydrocarbon generation process, which is of great significance to evaluate the natural gas resources of hydrocarbon source rock with different maturity and to identify the origin and evolutionary process of hydrocarbons by chemical and isotopic data. Moreover, this model provides an approach to study the dynamic evolution of isotope series of C1-3 (including reversed isotopic series), which is hopeful to reveal the mechanism responsible for isotopic reversal when combined with post-generation studies.

Saline-alkaline aquaculture has become important breakthrough to expand available space for aquaculture in China. However, the biochemical composition and quality of Eriocheir sinensis reared in carbonate alkalinity water are still unclear. Therefore, this study investigated the edible yield, coloration, nutritional and flavor quality of Eriocheir sinensis. Significantly lower gona-dosomatic index (GSI) and meat yield (MY) were detected in intensive pond (IP) than those in semi intensive reed wetland (SIWR) (P< 0.05). Six color parameters differed between IP and SIRW in the hepatopancreas (P< 0.05). The contents of crude protein and fat in the female hepatopan-creas of IP were significantly higher than those in SIRW(P< 0.05). The higher concentrations of ∑MUFA, ∑EFA, h/H in the female edible tissues were checked in IP than those in SIRW, with significant difference including ∑MUFA in the hepatopancreas and ovary, ∑EFA in the muscle, and h/H in the ovary (P<0.05). Better total free amino acid (∑FAA) contents of muscle were de-tected in SIRW than that in IP. Significantly increasing tendency was detected in K, Ca, Mg, Fe, Zn of ovary from SIRW to IP (P< 0.05). Overall, the Eriocheir sinensis reared in carbonate alkalinity water is an important source of nutrient.

Autism spectrum disorder (ASD) is a common condition with lifelong implications. The last decade has seen dramatic improvements in DNA sequencing and related bioinformatics and databases. We analyzed the raw DNA sequencing files on the Variantyx® bioinformatics platform for the last 50 ASD patients evaluated with trio whole genome sequencing (trio-WGS). “Qualified” variants were defined as coding, rare, and evolutionarily conserved. Primary Diagnostic Variants (PDV) additionally were in genes directly linked to ASD and matched clinical correlation. A PDV was identified in 34/50 (68%) of cases, including 25 (50%) cases with heterozygous de novo and 10 (20%) with inherited variants. De novo variants in genes directly associated with ASD were far more likely to be Qualifying than non-Qualifying versus a control group of genes (P=0.0002), validating that most are indeed disease related. Sequence reanalysis increased diagnostic yield from 28% to 68%, mostly by inclusion of de novo PDVs in genes not yet reported as ASD associated. Thirty-three subjects (66%) had treatment recommendation(s) based on DNA analyses. Our results demonstrate high yield of trio-WGS for revealing molecular diagnoses in ASD that is greatly enhanced by re-analyzing DNA sequencing files. In contrast to previous reports, de novo variants dominate the findings, mostly representing novel conditions. This has implications to the cause and rising prevalence of autism.

Wheat is widely grown in the Mediterranean region, where plants frequently face water shortages. Recently, more attention to rationalizing irrigation water has been increased due to the adoption of sustainable agricultural systems. Therefore, two field trials were conducted at the Agriculture Research Station of Nubaria, Egypt, in two consecutive seasons (2017/2018 and 2018/2019) to examine three irrigation regimes' effects, i.e., 60, 80, and 100% of crop evapotranspiration (ETc) combined with foliar ascorbic acid (AsA) or vitamin B2 (VB2) on yield and water productivity of wheat in two separate experiments. A split-plot design was used with three replicates. Irrigation treatments occupied the main plots, while the subplot in the first experiment was placed by ascorbic acid (AsA) and vitamin B2 in the second experiment. Results indicated that 100% ETc produced higher wheat yield and its attributes and insignificantly surpassed 80% ETc. Compared to the unsprayed plots, the foliar application of 6 mM ascorbic acid or 2.0 mM vitamin B2 significantly increased grain yield, components, and water use efficiency. The interaction between irrigation regimes (100% ETc or 80% ETc) and foliar application of 6.0 mM ascorbic acid or 2.0 mM vitamin B2 resulted in the highest values with no significant difference. Foliar application of ascorbic acid or vitamin B2 saved 20% of irrigation water while yielding a reduction that did not exceed 10%. The biplot graph of treatments x traits (TT) was a useful statistical tool for examining the impact of treatments on yield and its characteristics and identifying the links between these factors. Results suggest that riboflavin or ascorbic acid may have a potential role as an effective antioxidant for enhancing the tolerance for drought stress in wheat.

The effect of climate change plays a significant role on groundwater level variations and crop yield. The change in climate leading to increased temperatures, decreased rainfalls and extreme drought conditions ultimately cause low groundwater level and crop yield. Judicious groundwater management technology viz., water recharge options, need based irrigation, crop selection, must be adapted for further increasing the water table level in soil ecosystem. Additionally, climate change impacts combined with changes in agricultural water use can affect groundwater dynamics. Increased irrigation demand and decreased summer precipitation can lower groundwater levels, impacting crop production. Overall, climate change affects both groundwater resources and crop yield highlighting the need for sustainable water management practices and consideration of soil properties in agricultural modelling. The authors carefully selected relevant research articles addressing the impact of climate change on ground water level in Asian countries. The review highlights the use of machine learning method to ground water level and crop yield modelling. According to the study, machine learning techniques have made significant contributions to predicting groundwater level changes and crop yield with higher accuracies, high performance and less running time.

Melon pest management relies on the excessive application of pesticides. Reducing pesticide spraying has become a global issue for environmental sustainability and human health. Therefore, developing a new cropping system that is sustainable and eco-friendly is important. This study found that melon seedlings irrigated with ultrafine water containing H2 and O2 (UFW) produced more root hairs, increased shoot height, and produced more flowers than the control irrigated with reverse osmosis (RO) water. Surprisingly, we also discovered that UFW irrigation significantly reduced aphid infestation in melon. Based on cryo-scanning electron microscope (cryo-SEM) observations, UFW treatment enhanced trichome development and prevented aphid infestation. To investigate whether it was H2 or O2 that helped to deter insect infestation, we prepared UF water enrichment of H2 (UF+H2) and O2 (UF+O2) separately and irrigated melons. Cryo-SEM results indicated that both UF+H2 and UF+O2 can increase the density of trichomes in melon leaves and petioles. RT-qPCR showed that UF+H2 significantly increased the gene expression level of the trichome-related gene GLABRA2 (GL2). We planted melons in a plastic greenhouse and irrigated them with ultrafine water enrichment of hydrogen (UF+H2) and oxygen (UF+O2). The SPAD value, photosynthetic parameters, root weight, fruit weight, and fruit sweetness were all better than the control without ultrafine water irrigation. UFW significantly increased trichome development, enhanced insect resistance, and improved fruit traits. This system thus provides useful water management for pest control and sustainable agricultural production.

Spodoptera frugiperda is a significant economic pest of maize in Uganda. Many Ugandan maize farmers employ synthetic insecticides as their main form of control despite the negative impacts of these chemicals. The study aimed to determine the effect of synthetic, semi-synthetic and bio-pesticides on maize leaf damage, and abundance of S, frugiperda and its parasitoids in Wakiso and Lira districts. The experiments were laid out in an RCBD with six treatments in 2020 and nine treatments in 2021, replicated four times. The treatments with the biggest decrease in leaf damage and infestation were Amdocs and Roket®, followed by Nimbecidine. The biopesticides were not always more effective than the untreated control, though; their efficacy was often lower than that of synthetics, semi-synthetics, and botanical. We recovered one egg parasitoid, Telenomus remus, and seven egg and egg-larval parasitoids (Coccygidium luteum, Coccygidium sp., Cotesia icipe, Chelonus sp., Micranisa sp., Charops cf. diversipes, and Tachinidae sp. Among these, C. cf diversipes, Chelonus sp., C. luteum, C. icipe and Tachinidae were the most abundant. Parasitism was low, averaging 10% for eggs and 5.3% for larvae. Synthetic, the semi-synthetic and Nimbecidine often increased higher yield when compared with the untreated control. There were genrally low population of parasitoids, althoguh there were some indications of reduced population of parasitoids in plots treated with Amdocs and Roket®, while percent parasitism was not affected. In some instances, higher yields were even realized in untreated control. While considering the tactics to integrate, assessing the practices more compatible with biological practices will be necessary.

Self-consolidating concrete (SCC) is highly workable concrete that flows under minimal vibrations into congested reinforcement and sophisticated formworks. The properties of SCC are achieved by incorporating chemical admixtures. In this study, we analyzed if SCC could be designed with a cheap, easily accessible plant extract as a bio-admixture known as aloe vera mucilage (AVM). The main aim is to determine the effect of AVM on SCC prepared from ordinary Portland cement (OPC) and blended cement LC3, consisting of clinker (50%), calcined waste clay (30%), limestone (15%), and gypsum (5%). The AVM is applied in different dosages of up to 10%. The findings showed that the LC3 had a lower rate of consistency, lower slump values, and higher initial and final setting times compared to OPC. The V-funnel and L-box values were reduced with increased plasticizer dosing. Additionally, the OPC samples with both plasticizers achieved higher compressive strength than LC3 in the 7, 14, and 28 curing ages. However, the 2.5 % dosage of AVM showed some increase in compressive strength in both OPC and LC3 samples. Overall, AVM is comparable to the commercial plasticizer used as both influence the reduction of yield stress with an increase in slump flow.

The purpose of this investigation was to study the impact of different rates of bio fertilizer on agronomic characteristics and the relations among herbaceous plant diversity and soil properties of Aloysia citrodora in central Greece. For this aim a two – year Completely Randomized Design (CRD) field experiment was carried out in central Greece. The experiments included four biological fertilizer levels, BF0: 0 kg ha-1, BF50: 50 kg ha-1, BF100: 100 kg ha-1 and BF150: 150 kg ha-1 with 3 replication. Plant height, dry stem, dry leaves, dry total yield and Leaf Area Ιndex (LAI) were measured during the two growing years. The results showed that in the 1st studied the maximum plant height was observed in BF150 treatment while the 2nd year the BF150 level provoked a raise of 16.08% and 1.09% compared to BF50 and BF100, respectively. The 1st year the values of total dry yield were better in BF150 application. The 2nd year the total yield increased by 50.27% in BF100 and 50.09% BF150 treatments. Moreover, LAI was ameliorated by applied the BF100 and BF150 treatments both in two studied years. A key finding in this study is that Aloysia citrodora ecosystem favors herbaceous plant species richness. Also, soil factors (soil organic matter, P and K) promote positive herbaceous plant diversity within the Aloysia citrodora ecosystem. Finally, Aloysia citrodora can be a promising medicinal plant, cultivated under the Mediterranean climatic conditions.

Several strategies promote phyllosphere colonization by soil-born Trichoderma plant-beneficial strains. One of these is foliar spraying with suspensions containing large amounts of chlamydospores – spores with a thick cell wall structure that makes them highly resistant to harsh environmental conditions. Trichoderma biomass was produced by cultivation on cornmeal medium and compared by microscopic and thermogravimetric analysis with the biomass produced in potato dextrose broth. Both analyses revealed higher chlamydospores content and thicker mycelium in the fungal biomass produced on cornmeal medium. The Trichoderma suspension rich in chlamydospores was sprayed on bitter gourd (Momordica charantia) leaves at two concentration levels, 106 and 108 ufc/ml. The effect of these treatments on plant physiological parameters, leaf photosynthetic pigments, polyphenol and flavonoid contents, antioxidant activity of leaves and fruits and yield was compared to the control (plants sprayed with water) and to the experimental treatment sprayed with 108 ufc propagules produced in potato dextrose broth. The effect of chlamydospore-rich suspensions on plant physiological parameters was more pronounced and long-lasting compared with the other treatments. The treatment with chlamydospore-rich suspension enhanced the accumulation of polyphenols and flavonoids in the leaves and fruits and increased the antioxidant activity. The application of the foliar treatment with Trichoderma suspensions did not modify the cytocompatibility of the extracts from fruits determined on L929 cells.

Although hydrogen gas (H2) treated soil improves crop biomass, this approach appears difficult for the field application due to the flammability of H2 gas. In this report, we investigated whether and how H2 applied in hydrogen nanobubble water (HNW) improves the yield and quality of cherry tomato (Lycopersicon esculentum var. cerasiforme) with/without fertilizers. Two-year field trials showed that compared to corresponding controls, HNW without/with fertilizers improved cherry tomato yield per plant by 39.7% and 26.5% in 2021 (Shanghai), and 39.4% and 28.2% in 2023 (Nanjing). Compared to surface water (SW), HNW increased soil available nitrogen (N), phosphorus (P), and potassium (K) consumption regardless of fertilizer application, which may be attributed to the increased NPK transport related genes in roots (LeAMT2, LePT2, LePT5, and SlHKT1,1). Also, HNW-irrigated cherry tomato displayed higher sugar-acid ratio (8.6%) and lycopene content (22.3%) than SW-irrigated plants without fertilizers. Importantly, the beneficial effects of HNW without fertilizers on yield per plant (9.1%), sugar-acid ratio (31.1%), volatiles (20.0%) and lycopene contents (54.3%) were stronger than those achieved by fertilizers alone. In short, this study clearly indicated that HNW-supplied H2 not only exhibited fertilization effect on enhancing tomato yield, but also improved fruit quality with a lower carbon footprint.

The ridge-furrow plastic mulching (RFPM) system and nitrogen application have been effective strategies for improving crop productivity in the Loess Plateau of China. However, it is not clear how the ridge-furrow ratio and nitrogen fertilizer type (NT) affect the utilization of water, nitrogen, heat and radiation resources for increased rain-fed wheat production. Two nitrogen fertilizer types [Traditional urea (TU) and controlled-release urea (CRU)] and four planting patterns [conventional flat planting (F) and the RFPM system of 20 cm ridge with 40 cm furrow (R2F4), 40 cm ridge with 40 cm furrow (R4F4), and 60 cm ridge with 40 cm furrow (R6F4)] were tested from September, 2018 to June, 2021 during winter wheat growing season. The results showed that the RFPM system can increase the soil thermal time (TTsoil) by 41.0–152.1°C d compared to F. The thermal effect of the RFPM system shortens the vegetative growth period and extends the reproductive growth period by 2–7 days, promoting the increase of the leaf area index (LAI) and final dry matter (DM) accumulation. These significantly increased the grain yield (GY) in the RFPM system by 51.6–115.2% and enhanced the thermal time use efficiency (TUE) by 48–99.5%, water productivity (WP) by 37.4–76.3%, radiation use efficiency (RUE) by 16.3–34.4%, and partial factor productivity of nitrogen (PFPN) by 51.6–115.2% compared to F. Although a high ridge-furrow ratio combined with CRU increased GY and resources use efficiency, it also exacerbated the soil water depletion, especially in the 40–140 cm soil layer. Overall, applying CRU in combination with the RFPM system of 40 cm ridge with 40 cm furrow maximized resources use efficiency and increased wheat production in the Loess Plateau of China.

Agricultural productivity is expected to decrease under changing climate conditions that correspond to the stability of West African food systems. Although numerous studies evaluated food production gaps or impacts of climate variability on crop yields, many uncertainties are associated with climate extremes, but also rapid population growth and the corresponding dietary lifestyle determine farming activities. Here, we present a food supply and demand analysis based on the relationship between climate change, crop production, as well as population growth in three experimental sites from southwestern Burkina Faso to southwestern Ghana. The method consists of a tiered approach that encompassed a statistical analysis of historical climate as well as agricultural time series using boxplots and a trend test by Mann-Kendall. Food balance sheets were calculated by estimating the demand using a population growth model linked to food supply with local consumption patterns. Results of the boxplot analysis revealed for the majority of climate time series light to strong right-skewed distributions with either a few heavy rainfall or hot temperature events. We found almost insignificant rainfall and temperature trends for both sites in the Sudano-Guinean savannah. The rainfall regime of southwestern Ghana indicated an insignificant upward or downward trend while the temperature significantly increased over time. Crop yield boxplots demonstrated mainly right-skewed distributions for cereals, legumes and tubers as well as cash crops such as cotton. Backed by the Mann-Kendall test, maize and sorghum significantly enhanced in both study areas of the Sudano-Guinean savannah. Southwestern Ghana depicted a different crop pattern where cassava and plantain showed a strong upward trend at a confidence level of 1%. The grouped food balances sheets across the regions illustrated a surplus for the Sudano-Guinean savannah ranging from 221.2 megatons (Mt) to 4,846.77 Mt while southwestern Ghana exhibited a deficit between -193.33 Mt and -16,188.82 Mt. Despite a growing yield of various crops, food demand outpaces the regional production. Hence, it is recommended to focus on a larger array of commodities, imports and marketing of farm products.

Climate change and the increasing frequency of high-temperature events are significant threats to global crop yields. To address this, a comprehensive understanding of how plants respond to heat shock (HS) is essential. Signaling pathways involving calcium (Ca2+), a versatile second messenger in plants, encode information through temporal and spatial variations in ion concentration. Ca2+ is detected by Ca2+-sensing effectors, including channels and binding proteins, which trigger specific cellular responses. At elevated temperatures, the cytosolic concentration of Ca2+ in plant cells increases rapidly, making Ca2+ signals the earliest response to HS. In this review, we discuss the crucial role of Ca2+ signaling in raising plant thermotolerance and we explore its multifaceted contributions to various aspects of the plant HS response.

The use of recombinant bovine somatotropin (rbST) leads to an increase, in variable amounts, of milk production in buffalo, but there is a lack of information on the influence of rbST on their metabolism. This study looked at the effects of a single 500 mg dose of rbST on lipid profile, liver and kidney function and physical, chemical and cellular constitution of milk in 14 buffalo over 14 days, from the 100th day of lactation, and compared them with 14 animals in a control group. From the 1st day after rbST, there was a rise in beta hydroxybutyrate (β-HBO), possibly due to the higher dry matter intake or by biotransformation of NEFA into β-HBO. Treatment did not influence blood glucose, non-esterified fatty acids (NEFA), triglycerides, cholesterol, total protein, albumin, AST, GGT, bilirubin, urea or creatinine. In 71.3% of the buffalo there was a gradual increase in milk production with maximal response in the first week that was then followed by a gradual decrease, whilst in 21.4%, the increase in production occurred between 7 and 10 days, and only 7.1% of animals did not respond. On the 3rd, 5th, 7th and 10th days after treatment, an increase was found in milk production between the two groups equal to 1.04, 1.52, 1.42 and 1.06 liters, respectively. In relative terms this means an increase in milk production, respectively, of 15.1%; 21.0%; 19.8 % and 15.1 %. The constitution of the milk showed no difference in the amounts of fat, lactose, total solids or somatic cell count; however, on the 3rd day after rbST, there was a decrease in protein; notably, from the 5th day, protein values show no statistical difference. It can be concluded that the application of rbST in buffalo from the 100th day of lactation is metabolically safe, since the treatment neither caused imbalances in fat metabolism nor overloaded the liver or renal function, and the changes in milk composition were transient and limited to a decrease in milk protein.

The effects of four cycles of recurrent selection on simple sequence repeat (SSR) marker allele frequencies and population structure were examined in the Maksimir 3 Synthetic (M3S) maize population (Zea mays L.). Genotyping of 32 plants from each cycle of selection at 38 SSR loci revealed that the mean number of alleles per locus and the mean expected heterozygosity were preserved over cycles of selection, indicating maintenance of sufficient genetic variability in the population needed for future genetic gain. Waples test of selective neutrality revealed that genetic drift was the main force in changing allele frequencies in the population. The proportion of selectively nonneutral loci in single cycles of selection varied between 16% and 37%. Some nonneutral loci shared the same genomic locations with previously published QTLs controlling important agronomic traits. Between 5% and 29% of loci were found to be in significant Hardy-Weinberg (HW) disequilibrium with the majority showing an excess of homozygosity. Excess of homozygosity at several loci was highly consistent across cycle populations suggesting positive assortative mating as the possible cause of the observed HW disequilibrium. Linkage disequilibrium (LD) tests revealed that the M3S population was essentially in linkage equilibrium. The proportion of pairs of loci in significant LD varied across cycles of selection between 0.1% and 1.8% probably due to the effects of genetic drift and epistatic selection.

Nitrogen is the most commonly managed mineral nutrient in olive groves because it is essential for plant growth. The precise management of N fertilization in olive cultivation is still not fully clarified, but it is now essential for providing sustainable production. A nitrogen fertilizer ex-periment with olive trees (cv. Kalinioti) was carried out over a six-year period. Seven levels of nitrogen fertilizer given as ammonium nitrate (control, 1, 2, 3, 4, 5, and 6 kg/tree) were annually applied in order to determine the effect of nitrogen on vegetative growth, fruit set, fruit weight, yield, maturation index and leaf N,P, and K concentrations. The results indicate that, under these conditions, application of up to 4 kg NH4NO3/tree significantly increased yield to 62.5 kg/tree compared to the control. The positive effect was attributed to the initial and final fruit set increases (7.63 and 3.73%, respectively). However, the weight of 100 olives (337 g) at the same fertilizer rate was considerably lower compared to the control. Higher nitrogen rates decreased yield while increasing overall shoot growth. Nitrogen fertilization did not significantly influence the oil content of olive fruit. Fruit weight, maturation index and concentration of oil reached maximum levels in the beginning of December, indicating a suitable start to olive harvesting with reduced yield losses due to unfavorable weather conditions. With increasing fertilizer levels from 0 to 6 kg NH4NO3,/tree concentration of N in olive leaves also increased from 1.23% to 2.38%. Maximum yield was achieved at a level of 6 kg NH4NO3/tree, which corresponded to 2.01% N in leaves. The results suggest that application of 3 kg NH4NO3/tree can be recommended for table olive pro-duction due to the fact that fruit weight was not decreased, while fertilization with 4 kg NH4NO3/tree was suitable for oil olives.

This study explores the application of numerical analysis and material models to predict ice impact loads on ships and offshore structures operating in polar regions. An explicit finite element analysis (FEA) approach was employed to simulate an ice and steel plate collision experiment conducted in a cold chamber. The pressure and strain history during the ice collision were calculated and compared with the experimental results. Various material model configurations were applied to the FEA to account for the versatile behavior of ice—whether ductile or brittle—its elastic-plastic yield criteria, and its dynamic strain rate dependency. In addition to the standard linear elastic perfectly plastic and linear elastic-plastic relationships, this study incorporated the crushable foam and Drucker-Prager models, based on the specific ice yield criteria. Considering the ice’s strain rate dependency, collision simulations were conducted for each yield criteria model to compute the strain and reaction force of the plate specimens. By comparing the predicted pressures for each material model combination with the pressures from ice collision experiments, our study proposes material models that consider the yielding, damage, and behavioral characteristics of ice. Lastly, our study proposes a combination of ice material properties that can accurately predict collision force.

Irrigation and fertilization are indispensable links in the jujube planting industry in southern Xinjiang, China. However, the water and fertilizer integration effects on jujube growth and fruit quality remain unclear. A two-year water and fertilizer optimization coupling test was conducted to determine the optimal water- and nutrient-supply scheme. The three-factor randomized block experiment included water (W), nitrogen (N), and phosphorus (P). According to the principal component analysis of each index, each treatment’s comprehensive score was obtained. Using yield and economic regression models, the theoretical value and yield value of the optimal economic benefit are inferred. When W, N, and P were applied together, the fruit quality and yield of each treatment significantly differed, and the vitamin C, soluble sugar, and sugar–acid ratio increased significantly with an increase in nitrogen fertilizer. However, the titratable acid decreased. An increase in irrigation and nitrogen application significantly increased fruit yield. The comprehensive score was the highest in the N3P3W2 treatment, which improved fruit quality, and the lowest in the N4P3W2 treatment. When the amounts of N, P, and W were 275.56 kg·hm-2, 413.66 kg·hm-2, and 7278.19 m3·hm-2, respectively, the theoretical economic benefit was the best. The N4P3W2 treatment is the optimal treatment.

The leading role of Italy in the cultivation of durum wheat stimulated intense breeding activities in the country from the beginning of the 20th century, much earlier than any other country involved in durum wheat production. Older, genetically more heterogeneous landraces became replaced with new highly productive, superior quality varieties, and this led an inevitable reduction in overall genetic diversity among new cultivars, which makes the genetic variability of the old cultivars preserved particularly valuable and important. The aim of this paper was to assist future breeding programmes by providing a detailed description of the history of durum wheat breeding in Italy and of the changes in yield, quality and related traits that subsequently occurred, starting from the most diffuse landraces present between 1900 and 1920 up until the present day. The parallel evolution of breeding techniques, breeding goals and agricultural systems in this period is also described, and some future breeding goals suggested. In the current context of climate change and of rapidly mutating pathogen populations, preserving the yield level with the continuous introduction of new cultivars by exploiting the reservoir of largely unused genetic variation stored in old cultivars and landraces could be as important as increasing grain yield and quality.

Forest-grass intercropping patterns of protected cultivation has been widely used to increase productivity and sustainability in modern agriculture. However, there have been few studies of wolfberry (L. barbarum) intercropping and it is cultivated mostly by clean tillage. This paper takes 10 kinds of wolfberry-forage intercropping patterns, compares the effects of different planting modes on the growth, yield, photosynthetic characteristics, nutritional quality, and the degree of occurrence of diseases and pests, which aims to make clear the effects of wolfberry-forage intercropping patterns on wolfberry. The results showed that different intercropping combinations had different effects on wolfberry. The overall effect of Wolfberry-forage intercropping patterns on the growth of wolfberry were promote the photosynthetic characteristics. Ryegrass could increase the branch number, Lvyuan 5 and mangel increase branch length; Mangel, clover, sweet sorghum, ryegrass and stipas could reduce the damage of powdery mildew by 69%, and alfalfa, stipa and ryegrass could reduce the occurrence of aphids by 67% (P<0.05). Intercropping could increase carotenoids, flavonoids and ascorbic acid contents to improve wolfberry quality by 21%, 53% and 127%, respectively (P<0.05). Among all the performances, wolfberry-mangel intercropping has absolute advantages in promoting wolfberry yield and quality increase. Therefore the best patterns of wolfberry-mangel, wolfberry-ryegrass, wolfberry-alfalfa and wolfberry-clover were chosen.