Cannabis (Cannabis Sativa L.) is now legally produced in many regions worldwide. Cannabis flourishes under high light intensities (LI); making it an expensive commodity to grow in controlled environments, despite its exceptionally high market value. It is commonly believed that cannabis secondary metabolite levels may be enhanced both by increasing LI and by exposing crops to ultraviolet radiation (UV). However, there is sparse scientific evidence to guide cultivators. Therefore, the impact of LI and UV on yield and quality must be elucidated to enable cultivators to optimize their lighting protocols. We explored the effects of LI, ranging from 350 to 1400 μmol m^-2 s^-1 and supplemental UV spectra on cannabis yield and potency. There were no spectrum effects on inflorescence yield, but harvest index under UVA+UVB was reduced slightly (1.6%) vs. the control. Inflorescence yield increased linearly from 19.4 to 57.4 g/plant and harvest index increased from 0.565 to 0.627, as LI increased from 350 to 1400 μmol m^-2 s^-1. Although there were no UV spectrum effects on total equivalent Δ⁹-tetrahydrocannabinol (T-THC) content in leaves, the neutral form, THC, was 30% higher in UVA+UVB vs. control. While there were no LI effects on inflorescence T-THC content, the content of the acid form (THCA) increased by 20% and total terpenes content decreased by 20% as LI increased from 350 to 1400 μmol m^-2 s^-1. High LI can substantially increase cannabis yield and quality, but we found no commercially-relevant benefits of adding supplemental UV radiation to indoor cannabis production.

Most smallscale farmers still use the traditional way of agricultural crop farming, and relay mostly use of chemical fertilizers (CF). Recently CF have become expensive and could in some way have a negative impact on soil quality after long term application. However, co-application of biogas slurry (BGS) with CF could help reduce farming costs while improving dry matter yields, grain yields, primary macronutrient uptake of (Nitrogen) N, (Phosphorus) P, (Potasium) K, (Calcium) Ca and (Magnesium) Mg and soil concentration of pH, (organic carbon) OC, N, P, K, Ca and Mg after crop harvest. The study was a field experiment conducted in 2016-2017 and 2017-2018 growing seasons. The field experiment was arranged in a randomized complete block design with four replicates. The treatments were based on percentages of recommended N rates of 120 kg N ha-1 for maize production. The BGS/CF treatments were (i) 0/0, (ii) 0/120, (iii) 24/96, (iv) 48/72, (v) 72/48, (vi) 96/24, (vii) 120/0 kg N ha-1. The spreading of the combination of BGS/CF treatments was performed by hand and incorporated into the top soil (0-10 cm) in each experimental plots. BGS/CF (48/72) treatment resulted into higher dry matter yield in 2016-2017, which was higher than all other treatment combinations, while in the 2017-2018 season, treatment of (0/120) resulted into higher dry matter than all other treatment combinations. The 48/72 and 0/120 treatments resulted into similar grain yield in 2016-2017 season which were higher than all other treatments. Treatments of 48/72, 72/48 and 120/0 had higher N, P, K, Ca and Mg uptake than 0/0, 0/120, 24/96 and 96/24 treatments in both seasons. Soil pH, total N, K, and Mg were high from the treatment of (120/0) than all other treatments in 2016-2017 while in the 2017-2018 season, treatment of (48/72) had higher OC, P and K after maize harvest. The findings of his study show that co-application of BGS/CF at 48/72 and 72/48 have maize yield benefits compared to the two resources, BGS/CF (120/0) and BGS/CF (0/120), applied separately in soil especially in the arid and semi-arid regions.

Mungbean [Vigna radiata (L.) Wilczek] in Australia has been transformed from a niche opportunistic crop into a major summer cropping option for dryland growers in the summer-dominant rainfall regions of Queensland and New South Wales. This transformation followed stepwise genetic improvements in both grain yields and disease resistance. For example, more recent cultivars such as ‘Crystal’, ‘Satin II’ and ‘Jade-AU‘ have provided up to a 20% yield advantage over initial introductions. Improved agronomic management to enable mechanised management and cultivation in narrow (<50 cm) rows has further promised to increase yields. Nevertheless, average yields achieved by growers for their mungbean crops remain less than 1 t/ha, and are much more variable than other broad acre crops. Further increases in yield and crop resilience in mungbean are vital. In this review, opportunities to improve mungbean have been analysed at four key levels including phenology, leaf area development, dry matter accumulation and its partitioning into grain yield. Improving the prediction of phenology in mungbean may provide further scope for genetic improvements that better match crop duration to the characteristics of target environments. There is also scope to improve grain yields by increasing dry matter production through the development of more efficient leaf canopies. This may introduce additional production risks as dry matter production depends on the amount of available water, which varies considerably within and across growing regions in Australia. Improving crop yields by exploiting photo-thermal sensitivities to increase dry matter is likely a less risky strategy for these variable environments. Improved characterisation of growing environments using modelling approaches could also better define and identify the risks of major abiotic constraints. This would assist in optimising breeding and management strategies to increase grain yield and crop resilience in mungbean for the benefit of growers and industry.

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.

CONTEXT: The sustained White corn (Zea mays L.) yield relies on supply of Nitrogen (N), which is an important element in improving soil fertility. OBJECTIVE: The research aim to determine the effect of Nitrogen on white corn yield and grain mass. METHOD: The experimental design was a 4 × 4 factorial arranged in randomized complete block design with 2 replications each. The effect of nitrogen was determined in terms of the flow within the soil, initial component, addition, uptake, loss and use of nitrogen by the White corn plants. Nitrogen was applied as Granular Urea using zero broadcast method. The grain yield was determined hand-harvesting and shelling. RESULTS AND CONCLUSIONS: There were no statistically significant differences between the mean samples from the two replicates (blocks 1 & 2) across the two seasons for corn sugar concentration, corn yield estimates and grain yields. In 2021, the mean yield estimate was 12,552 Kg ha-1, while that of 2022 averaged 12687 Kg ha-1. Similarly, the grain yield achieved in 2022 was 844.1kg more than the average grain yield in 2021. The white corn yield estimate and grain yield increased linearly with an increase in nitrogen application level, with the highest yields achieved when nitrogen fertilizer was applied at 150kg N/ha. This demonstrates that nitrogen has a positive influence on the yield quantity of white corn. SIGNIFICANCE: The White maize model may be used to improve the formulation of decisions and enhance the precision of estimates for yield and N fate within the soil-plant-atmosphere continuum. Further, the findings of this study can significantly enhance agricultural productivity while keeping an eye on the environment.

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 depletion and environmental problems associated with fossil fuels have encouraged us to look for alternative feedstock that do not compromise food security and the environment. Sorghum is a fast-growing crop that can be harvested twice a year and produces both food and straw that can be utilized in the production of bio-based fuels. In this study, the production of bioethanol and the effects of fermentation parameters on ethanol yield are presented. A sequential pretreatment method was employed, using dilute sulfuric acid (1%) at 125 °C in the first stage and dilute sodium hydroxide (1.25 %) at 90 °C in the second stage. The residues left after the sequential pretreatment stage were hydrolyzed using acid hydrolysis. The sugar concentration of the hydrolysates was determined using the phenol sulfuric acid method, and three hydrolysates having sugar levels of 30.42 g/L, 31.79 g/L, and 32.9875 g/L were selected for fermentation. The ethanol yield was determined after 72 hours of fermentation at 30 °C with varying inoculum sizes (5%, 10%, and 15%) and pH (4.5, 5, and 5.5). With a maximum ethanol yield of 0.617 mL/g (48.742%) produced at a sugar content of 32.9875 g/L, pH of 5, and inoculum size of 15%, statistical analysis showed that all three independent parameters affected ethanol yield. According to these findings, while raising sugar content, inoculum amount, and pH all initially result in higher ethanol yields, doing so further reduces yield. So, in order to increase ethanol yield, fermentation conditions must be carefully managed while producing ethanol from sequential acidic-alkaline pretreated sorghum straw. The strategy followed by using sequential acidic-alkaline pretreatment of sorghum straw provides prospects for efficient and effective production of biofuels from alternative feedstock.

A field experiment was conducted during Kharif 2018, laid out in Randomized Block Design with three replications having seven treatments viz. N omission (T1), N applied as basal and AT (T2), N as basal, AT and PI (T3), N as basal and top dressing at NDVI threshold of 0.75 (T4), at NDVI threshold of 0.8 (T5), at SPAD threshold of 35.0 (T6) and SPAD threshold of 37.5 (T7) with Rice variety Sahabhagidhan.The study revealed that application of 30 kg N/ha as basal dose and top dressing of 20 kg N/ha twice at 35 and 63 DAS guided by NDVI threshold value of 0.8 (T5) was found to be superior over other treatments with respect to productivity. T5 recorded highest grain yield of 4438 kg/ha which was 17.0% higher than that top dressed at NDVI threshold of 0.75 (T4) and 7.1% higher than that top dressed at SPAD threshold value of 37.5 (T7). In case of SPAD meter, nitrogen top dressed at threshold value of 37.5 (T7) produced grain yield of 4143 kg/ha which was 15.0% higher than T6. T5 produced maximum dry matter of 8678 kg/ha with highest grain yield (4438 kg/ha), straw yield (5092 kg/ha) and harvest index 46.0%.

Site Index has been widely used as an age normalised metric to account for variation in forest height at a range of spatial scales. Although previous research has used a range of modelling methods to describe regional variation in Site Index little research has examined gains that can be achieved through use of regression kriging or spatial ensemble methods. In this study an extensive set of environmental surfaces were used as covariates to predict Site Index measurements covering the environmental range of \textit{Pinus radiata} D. Don plantations in Chile. Using this dataset, the objectives of this research were to (i) compare predictive precision of a range of geostatistical, parametric and non-parametric models, (ii) determine if significant gains in precision can be attained through use of regression kriging, (iii) evaluate the precision of a spatial ensemble model that utilises predictions from the five most precise models, through using the model prediction with lowest error for a given pixel and (iv) produce a map of Site Index across the study area. The five most precise models were all geostatistical and included ordinary kriging and four regression kriging models that were based on partial least squares or random forests. A spatial ensemble model constructed from these five models was the most precise of those developed (RMSE = 1.851 m, RMSE% = 6.38%) and had relatively little bias. Climatic and edaphic variables were the strongest determinants of Site Index and in particular, variables related to soil water balance were well represented within the most precise predictive models. These results highlight the utility of predicting Site Index using a range of approaches, as these can be used to construct a spatial ensemble that may be more precise than predictions from the constituent models.

On-farm research was conducted at Gouripur sub-district under Mymensingh district of Bangladesh during the boro (mid November-June) season in 2013-14 and 2014-15 to evaluate the performance of non-puddled rice cultivation with and without crop residue retention. The rice var. BRRI dhan28 was transplanted by two tillage practices viz., puddled conventional tillage (CT) and non-puddled strip tillage (ST) and at two levels of mustard residues, i.e., no residue (R₀) and 50% residue (R₅₀). The experiment was designed in a randomized complete block design with four replications. There were no significant yield differences between tillage practices and residue levels in 2013-14. But in the following year, ST yielded 9% more grain compared to CT leading to 22% higher BCR. Retention of 50% residue increased yield by 3% compared to no-residue, which contributed to 10% higher benefit-cost ratio (BCR). The ST combined with 50% residue retention yielded the highest grain yield (5.81 t ha^-1) which contributed to produce the highest BCR (1.06).

Rice is an essential crop for national food security in Egypt. Increasing the population calls for regular increases in rice production. At the same time, cultivated rice crop areas should be decreased because of the gradual scarcity of irrigation water. This means more rice production should be gained from less rice area. This situation calls for the annual accurate system for rice monitoring and yield estimation. Therefore, it is necessary to apply a remotely sensed based system for rice cultivation assessment using satellite imagery parallel with field measurements of some biophysical parameters. Multi-temporal normalized difference vegetation index (NDVI) extracted from twelve sentinel-2 imagery cover the whole summer season with variance and maximum value assessed by ground control points (GCPs), were used to isolate uncultivated areas, then to isolate rice areas and other vegetation covers. object-based classification methods with kappa co-efficient 0.9261 and overall accuracy 94.92% was generated to discriminate rice crop area and other summer crops on the study area. Leaf area index (LAI) for the experiment the l site was calculated using the surface energy balance algorithm for Land (SEBAL) model and then tested versus measured (LAI). NDVI and LAI were used to generate an empirical ran rice yield prediction model. Then, this model was used to produce rice to yield a map. The study was carried out in an experimental site in Kafr Elsheikh governorate with a total area of 5040 Hectare. Produced cultivated land use map showed 95% overall accuracy. High similarity was observed between measured and calculated (LAI) with high accuracy of R2 = 0.94. of Rice, yield map showed expected to yield more to than a month before harvest. The generated yield map was tested using a correlation coefficient between actual yield and estimated yield with high accuracy R2 = 0.9. This method is applicable to estimate the acreage and productivity of rice in the northern Nile delta in adequate time before harvest.

This study presents results of the sediment yield Watershed of Ribeirão do Pinhal, in the city of Limeira, São Paulo, conducted under three different scenarios of the land use: 1 – land use in 2008, 2 – with reforested protection areas, 3 – the increase sugarcane's areas over grassland and citrus areas. The Soil and Water Assessment Tool (SWAT) was used as a hydro-sedimentological modeling tool to simulate these scenarios. This watershed was divided into five sub-watersheds according to the prevalent use, and adjustments were made in soils database parameters and cultures that are in SWAT, to adapt it to the Brazilian reality. Was used climatological data of eight years (2007-2014) for this modeling. Different sediment yield could be noted in the different types of land use, sub-watersheds and scenarios. The uses that presented higher sediment yield, in ascending order, were: natural vegetation, sugarcane, citrus, annual crop e grassland. Sub-watershed number 2 had the highest sediment yield (~10Mg.ha^-1), while the sub-watershed 5, the lowest (5.51Mg.ha^-1). This remained in the three scenarios. Overall, scenario 2 had the lowest sediment yield (7.74Mg.ha^-1). Scenario 1 had 8.37 Mg.ha^-1 and scenario 3, 8.58Mg.ha^-1. SWAT was considered efficient to simulate the sediment yield by scenarios and by use, combining different thematic and tabular data when performing the necessary adjustments on their original database.

A simple approach was developed to predict corn yields using the MoDerate Resolution Imaging Spectroradiometer (MODIS) data product from two geographically separate major corn crop production regions: Illinois, USA and Heilongjiang, China. The MOD09A1 data product, which are 8-day interval surface reflectance data, were obtained from day of the year (DOY) 89 to 337 to calculate the leaf area index (LAI). The sum of the LAI from early in the season to a given date in the season [end of DOY (EOD)] was well fitted to a logistic function and represented seasonal changes in leaf area duration (LAD). A simple phenology model was derived to estimate the dates of emergence and maturity using the logistic function parameters b1 and b2, which represented the rate of increase in LAI and the date of maximum LAI, respectively. The phenology model predicted emergence and maturity dates fairly well, with root mean square error (RMSE) values of 6.3 and 4.9 days for the validation dataset, respectively. Two simple linear regression models (YP and YF) were established using LAD as the variable to predict corn yield; the yield model (YP) used LAD from predicted emergence to maturity, and the yield model (YF) used LAD for a predetermined period from DOY 89 to a particular EOD. When state/province corn yields for the validation dataset were predicted at DOY 321, near completion of the corn harvest, the YP model performed much better than the YF model, with RMSE values of 0.68 t/ha and 0.66 t/ha for Illinois and Heilongjiang, respectively. The YP model showed a similar or better performance, even for the much earlier yield prediction at DOY 257, compared to that of the YF model. In conclusion, the phenology and yield models were developed based only on logistic changes in remote sensing-derived LAD, and predicted phenological dates and corn yields with considerable accuracy and precision for the two regions selected for this study. However, these models must be examined for spatial portability in more diverse agro-climatic regions.

This 16-month study aimed to evaluate the extended effects of administering direct-fed microbials (DFM) on milk yield and components in 150 dairy cows. The cows were randomly divided into two groups: control (n=75) and DFM (n=75) based on parity and days in milk. Throughout the study, the two groups of cows were housed separately in a free stall yard, and each group had their own feeding area. The DFM group received 10 ml/cow of the Lacticaseibacillus- and Lentilactobacillus-based DFM via top dressing of the feed during lactation and drying off. Milk yield and liveweight were recorded daily. Milk samples were collected every two months for milk components analysis. Both groups produced less milk in the second production season due to adverse weather conditions. DFM cows gained more liveweight across the study (19.40 kg, 95% CI 0.44; 38.30) compared to controls. In the second season, DFM cows lost weight at a slower rate (-6.06, 95% CI -10.49; -1.61) during the postpartum period and produced more milk (0.39 L/d 95% CI 0.10; 0.89). Over a full lactation, DFM cows yielded at least 258L (95% CI 252L; 265L) more milk than controls. No significant differences were found in fat yield, protein yield, or somatic cell counts. The study suggests that prolonged DFM administration positively impacted milk production, but further research is needed to understand the underlying mechanism.

Autism spectrum disorder (ASD) is a common condition with lifelong implications and a strong hereditary component suggesting genetic underpinnings. 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 not associated with ASD (P = 0.0002, odds ratio 29), validating that most are indeed disease related. Only 14/34 (41%) of PDV cases had the variant listed on the laboratory report, and reanalysis increased diagnostic yield from 28% to 68%. Variants that we assigned as PDVs yet not on the report were predominately de novo in genes not yet reported as ASD associated. Many subjects both with and without a PDV had inherited Qualifying variants in known ASD-associated genes, suggesting polygenic inheritance. 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.

Rapeseed (Brassica napus L.) is one of the most important oil crops in China. Improving oil production of rapeseed is an important way to ensure the safety of edible oil in China. Oil production is an important index to reflect the quality of rapeseed and is determined by oil content and yield. Applying nitrogen is an important way to ensure a high yield. However, increasing nitrogen application would decrease oil content. Thus, it is critical to screen elite germplasm resources with stable or improved oil content under high nitrogen and to investigate the molecular mechanisms of nitrogen regulation of oil accumulation. In this paper, we review the effects of nitrogen levels on rapeseed yields and oil content, aiming to reveal the mechanisms of nitrogen regulation in oil accumulation and thereby provide a theoretical basis for breeding varieties with high oil content.

Nitrogen is crucial for plant physiology due to the fact that plants consume a significant amount of nitrogen during the development period. Nitrogen supports the root, leaf, stem, branch, shoot and fruit development of plants. At the same time, it also increases flowering. To monitor the vegetation nitrogen concentration, one of the best indicator developed in the literature is Normalized Difference Nitrogen Index (NDNI) which is based on the usage of the spectral bands: 1510 and 1680 nm. from Short-Wave Infrared (SWIR) region of electromagnetic spectrum. However, majority of the remote sensing sensors like cameras and/or satellites do not have a SWIR sensor due to the high costs. Many vegetation indexes like NDVI, EVI, MNLI, have been developed in also VNIR region to monitor the greenness and healthy of the crops. However these indexes are not very correlated to the nitrogen content. Therefore, in this study, a novel method is developed which transforms the estimated VNIR band indexes to NDNI by using a regression method between a group of VNIR indexes and NDNI. Training is employed by using VNIR band indexes as input and NDNI as output which are both calculated from the same location. After training, 0.93 correlation is achieved. Therefore, by using only VNIR band sensors, it is possible to estimate the nitrogen content of the plant with high accuracy.

The enormous increase in the volume of Earth Observations (EOs) has provided the scientific community with unprecedented temporal, spatial, and spectral information. However, this increase in the volume of EOs has not yet resulted in proportional progress with our ability to forecast agricultural systems.This study examines the applicability of EOs obtained from Sentinel2 and Landsat8 for constraining the APSIM-Maize model parameters. We leveraged leaf area index (LAI) retrieved from Sentinel2 and Landsat8 NDVI to constrain a series of APSIM-Maize model parameters in three different Bayesian multi-criteria optimization frameworks across 13 different sites across the U.S Midwest. A time variant sensitivity analysis was performed to identify the most influential parameters driving the LAI estimates in APSIM-Maize model. Then surrogate models were develop using random samples taken from the parameter space using Latin hypercube sampling to emulate APSIM’s behavior in simulating NDVI and LAI at all sites. Site-level, global and hierarchical Bayesian optimization models were then developed using the site-level emulators to simultaneously constrain all parameters and estimate the site to site variability in crop parameters. For within sample predictions, site-level optimization showed the largest predictive uncertainty around LAI and crop yield, whereas the global optimization showed the most constraint predictions for these variables. Lowest RMSE for within sample yield prediction was found for hierarchical optimization scheme (1423 Kg ha−1) while the largest RMSE was found for site-level (1494 Kg ha−1). In out-of-sample predictions within the spatio-temporal extent of the training sites, global optimization showed lower RMSE (1627 Kg ha−1) compared to the hierarchical approach (1822 Kg ha−1) across 90 independent sites in the U.S Midwest. On comparison between these two optimization schemes across another 242 independent sites outside the spatio-temporal extent of the training sites, global optimization also showed substantially lower RMSE (1554 Kg ha−1) as compared to the hierarchical approach (2532 Kg ha−1). Overall, EOs demonstrated their real use case for constraining process-based crop models and showed comparable results to model calibration exercises using only field measurements.

The objective was to estimate the monetary loss of potato producers up to the year 2100 as a result of temperature and precipitation impacts, taking into account the A2 and B2 scenarios of the IPCC (Intergovernmental Panel on Climate Change). The Pooled Production Panel Model was used, whose database was prepared taking into account climatic variables (temperature and precipitation) and agricultural variables (production, harvested area, farm-gate price) for the period 1996 - 2020, which form the independent variables of the study. The estimations used 60 observations and a total of 38 estimations were run in the econometric software EViews8, of which Equation 05 of the Production Pooled Panel Model was chosen as the best. The model obtained used temperature and precipitation forecasts from Brazil's INPE (National Institute for Space Research), validated for the study area. The results indicate a concave function between potato production (t/ha), temperature and precipitation. Finally, based on the A2 climate scenario, which is the most pessimistic and using the period 2021 - 2100, a loss for potato producers of approximately 8'927,521.48 million soles was estimated.

Pepper plants experience complex environmental factors including abiotic and biotic stresses in field and the importance of climate changes including low and high temperatures has been emerged. Low temperature stress in the growth and development is one of the most critical issues, which directly impact on the crop yield and productivity of pepper plants. It is essential to select and breed low temperature-(LT) tolerant pepper (Capsicum annuum L.) cultivars. The research was performed to assess the agronomical traits of 39 pepper accessions belonging to chili and bell fruit types which cultivated two different night temperature set-points at 15°C for suboptimal temperature (CT) and at 10°C for low temperature (LT), respectively. Plant heights (PH) of most pepper accessions in LT were significantly decreased compared to those in CT. The stem diameter (SD) and the length of main axis (LMA) were various depending on the genotypes under LT. Moreover, the number of flowers (NFL), the total number of fruits (NFR), fruit yield (FY), fruit fresh weight (FFW), fruit length (FL), fruit diameter (FD), and the number of seeds in a fruit (NSF) were notably declined in LT compared to CT. The evaluated agronomical traits between LT and CT were further applied for the correlation analysis, the principal component analysis (PCA), and the hierarchical cluster analysis. Notably, FY trait was correlated with other reproductive traits including NFR, FFW, FD, and FL on positive directions and LT treated-39 pepper accessions were clustered into seven groups by the clustering analysis. The selected accessions were primarily involved with the positive trends with the reproductive index including NFR, FL, FD, and FW traits and would be used for pepper breeding programs on developing LT-tolerant cultivars.

The experiment was conducted in three locations Jari, Chefa and Sirinka of Eastern Amhara to select the best performing varieties, in terms of biomass yield, chemical composition, haulm yield, seed yield and other agronomic characteristics of Glycine max (L.) Merrill grown under the rain- fed condition of lowland areas of Eastern Amhara in a randomized complete block design with tree replications. Twelve released soybean varieties were Afgat ,Belesa-95, Boshe , Cheri , Dhidhessa, Gishama , Gizo, Korme, Pawe-03, katta, Wegayen and Wollo were used as a treatments. The seeds were planted in 40 cm between rows and 10 cm between plants on a plot size of 3.2m*4m. Spacing between blocks and plots were 1 and 0.5m, respectively. The seed rate was 60 kg/ha and a fertilizer rate 100 kg/ha NPS was applied during seed planting. The combined analysis of variance over two years at location Jari for dry matter yield of varieties Afgat, Gizo, Pawe-03, Wogayen and Wollo were significantly higher as compared to other soybean varieties. The combined analysis across locations at Jari and Sirinka (2019-second year) showed that varieties Afgat, Gishama, Gizo, Pawe-03, Wogayen and Wollo had higher dry matter yield and varieties Gishama (3.97 t/ha), Gizo (3.60 t/ha), Pawe-03 (4.04 t/ha) and Wogayen (3.36 t/ha) had higher haulm yield as compared with other varieties. The combined analysis across locations at Jari and Sirinka (2019) showed that varieties Pawe-03(2951 kg/ha), Gizo (2862 kg/ha), Afgat (2859 kg/ha), Gishama (2654 kg/ha),Wollo (2461 kg/ha) and Wogayen (2404 kg/ha) had higher seed yield as compared with other varieties. The variety Wollo gave higher crud protein content in two locations (Jari and Sirinka) .Therefore, varieties Afgat, Pawe-03 and Wollo were recommends for the given areas of Jari , Chefa, Sirinka and could be produced in similar environments for the best of produced optimal amount of dry matter, haulm and seed yield and good protein supplement for production of ruminants.Thus, further researches will be needed to investigate on the utilization of livestock.

Inappropriate use of fertilizers is one of the major production constraints in sesame. Studies to optimize the use of N fertilizer on sesame were conducted at Humera Agricultural Research Center (HuARC) under rain fed and irrigation conditions. Thirteen (13) N doses were evaluated in a Randomized Complete Block Design (RCBD) during 2016, 2017 and 2018. In the rain fed condition; results showed higher number of days to 50% flowering on the higher N application. The 31-121.5 kg N ha-1 have scored higher seed yield, where the lower (18 kg N ha-1) and higher (156 kg N ha-1) N doses scored lower seed yield. In the irrigation condition; higher N application rate prolonged the flowering time to some extent and days to 90% maturity was reduced as N rate increased. Heavier seed weights and maximum seed yield were recorded on 64 and 75 kg N ha-1 and the lower N doses scored low seed yield. Agronomic efficiency of N fertilizer (N-AE) was higher on 64 kg N ha-1 under both growing conditions. The partial budget analysis revealed that 64 kg N ha-1 (rain fed) and 75 kg N ha-1 (irrigation) had the higher net profit, MRR and residual ranking. Therefore, for the greater sesame productivity 64 kg N ha-1 has to be recommended for rain fed and 64 to 75 kg N ha-1 for the irrigated sesame.

Due to increase demand of food grain in the world, assessment of yield before actual production is important in making policies and decisions in agricultural production system. For a large area, forecast models developed from vegetation indices derived from remote sensing satellite data possesses the potential to give quantitative and timely information on crops over large areas. Different vegetation indices are being made used for this purpose, however, their efficiency in estimating crop yield is needed to be certainly tested. In this study, wheat yield forecast was derived by regressing ground truthing yield data against time series of spatial vegetation indices for the 2013 to 2019 growing seasons. These spatial vegetation indices derived from Landsat 8 image data: Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were compared to evaluate the most appropriate index that performs better in forecasting wheat production at Karcag, Kunhegyes and Ecsegfalva settlements in Jász-Nagykun-Szolnok county, in the Northern Great Plain region of central Hungary. The best time for making wheat yield prediction with Landsat 8- SAVI and NDVI was found to be the beginning of ripening period (160th day of the year) with higher correlation between the vegetation indices and the wheat yield. The validation results revealed that the model from SAVI provides more consistent and accurate forecasts yield compared to NDVI. The SAVI model forecast yield for the validation years, 2018 and 2019 were within 6.00% and 4.41% of the final reported values while that of NDVI model were within 8.31% and 6.27%. Nash-Sutcliffe efficiency index is positive with E1= 0.99 for the model from SAVI and for NDVI, E1=0.57, which connote that the forecasting method developed and evaluated performs acceptable forecast efficiency.

Background and Objectives: The site types of Eucalyptus urophylla × Eucalyptus grandis clonal plantations in southern Yunnan were compared, aiming to provide basis for site selection and scientific plantations management. Materials and Methods: In this study, 80 standard plots were set up in the 6−9-year-old Eucalypts plantations in Pu'er City and Lincang City. Furthermore, the quantitative theory I model and canonical correlation analysis were used to analyze the relationship between dominant tree growth traits and site factors, and evaluate the growth potential of E. urophylla × E. grandis plantation. Results: The multiple correlation coefficient between 8 site factors (altitude, slope, slope level, soil thickness, slope direction, texture, soil bulk density, and litter thickness) and the quantitative growth of the dominant wood was 0.825 (P < 0.05). According to the correlation coefficient of the quantitative regression model, slope, altitude, and soil thickness were the main factors for the classification of E. urophylla × E. grandis plantations in southern Yunnan. In addition, E. urophylla × E. grandis plantations grew best downhill and mid uphill at relatively low altitude, where the soil layer was thick and composed of weathered red soil. Contrastingly, E. urophylla × E. grandis plantation growth was extremely poor in uphill sites at higher altitude, where the soil layer was thin and composed of semi-weathered purple soil. Furthermore, total N, and available B, Cu, and Zn content, as well as soil organic matter content in the soil had a great influence on the growth of E. urophylla × E. grandis. Conclusions: Nitrogen and phosphate fertilizer as well as trace elements such as B, Zn, and Cu can be properly applied in middle- and low-yield forests to promote the growth and development of E. urophylla × E. grandis plantations.

This work is aimed at promoting a healthier means of livelihood by investigating insignificant areas of pollution. In this work, soy candles produced from soybeans were proven as healthier alternatives to paraffin candles. Soxhlet extraction method was used with hexane as solvent. The extracted oil were then solidified. The wax was moulded into candle and tests were carried out to prove its claims as a safer alternative to paraffin wax. The results supported this claims that soy candles is more economical and produced lesser soot than the paraffin candles.

In Bangladesh, climate change is a major concern because of its geophysical location and climate dependent agriculture. As sessile organisms, crops plants have to face difficulties often in this environmentally vulnerable country. Therefore, this study examines the seasonal trend of two climatic parameters viz. temperature (maximum and minimum) and rainfall over a period of 1983 to 2013. Besides, this study provides insight into the relationship between climatic parameters and crop yield of two major crops viz. rice and wheat during 1997-2013. To assess the relationship of climatic parameters with time and yield using Pearson correlation analysis, time series data used at an aggregate level. SPSS software utilized for this analysis. The cropping seasons such as rice growing seasons Aus (summer rice), Aman (autumn rice) and Boro (winter rice) exhibited a significant increase in maximum and minimum temperature. Rainfall found to have a decreasing trend for all the seasons. This study also revealed that the climatic parameters had significant effects on rice yield, but these results varied among three rice crops. Maximum temperature had positive effects on all rice yields, especially on Aus and Aman. Minimum temperature had a negative effect on Aman rice yield but a positive effect on Aus rice yield. Wheat yield negatively associated with temperature. Rainfall exhibited negative relation with both rice and wheat yield.

Abstract: A two-year study of pearl millet-groundnut cropping systems across two fertilizer levels was conducted at the INRAN/TARNA research station in Maradi, Niger in the Sahelian zone of West Africa. The objective of this study was to identify the best cropping system with and without fertilizer application to optimize pearl millet and groundnut yields, land use efficiency, and economics as measured by value-to-cost ratio. The experiment was conducted with three replications, and ten treatments combination of five pearl millet and groundnut cropping systems (pearl millet and groundnut sole crops, and three pearl millet – groundnut intercrops), and two fertilizer levels. Sole cropping produced the highest pearl millet grain by over 300 kg ha-1 and groundnut pod yields by over 500 kg ha-1, but all the intercropping systems had a LER above 1.0 with land use efficiency increased by 19 to 41%, also intercropping increased diversity, and reduced risk. Fertilizer application increased yields in all cropping systems by 200 to 600 kg ha-1. Government subsidy increased the value-to-cost ratio by 0.5 to 2, 5 units, and was required for economic response for pearl millet sole and intercrops in 2022. The groundnut sole cropping system had the greatest economic response to fertilizer application. Based on the risky environment and multiple end uses needed by producers, the intercrop system M-G: 1:3:1 with fertilizer application is usually the best option to optimize pearl millet and groundnut production.

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.

Conservation tillage and deep side-fertilization both hold the potential to reduce nitrogen leaching and improve grain yield and nitrogen use efficiency in fragrant rice cultivation practices. However, the combined impact of different tillage practices with deep side-fertilization on nitrogen leaching remains uncertain. Therefore, this study conducted on-site experiments for four rice growing seasons in both early and late seasons in 2018 and 2019, using the fragrant rice varieties "Meixiangzhan 2"(MX) and "Xiangyaxiangzhan"(XY). The four experimental treatments included:conventional tillage with regular fertilization (T1), conventional tillage with simultaneous deep fertilization (T2), reduced tillage with simultaneous deep fertilization (T3) , and no-tillage with simultaneous deep fertilization (T4). Our results indicate that the T4 treatment exhibited higher nitrogen leaching rates and potential nitrogen losses throughout the entire rice growth cycle, with a 4.51% increase in total nitrogen leaching and a 1.86% increase in potential nitrogen leaching compared to T1. In contrast, the T2 treatment demonstrated the lowest nitrogen leaching rate, resulting in a 6.01% reduction in total nitrogen leaching and a 9.57% decrease in potential nitrogen leaching compared to T1, demonstrating the most optimal performance. For MX, the T1 treatment resulted in lower daily grain outputs compared to the other treatments, with disparities ranging from 5.35% to 9.94%. Similarly, for the XY, the T1 treatment yielded significantly lower daily grain outputs compared to the other treatments, with discrepancies ranging from 6.26% to 10.81% during the late season of 2019. Overall, this study shows that conventional tillage with deep fertilization effectively reduces nitrogen leaching and boosts fragrant rice yields. Minimizing nitrogen leaching enhances nitrogen utilization efficiency. These insights highlight the significance of strategic fertilization and cultivation for environmental conservation and agricultural sustainability.

Producing cherry tomatoes became interesting to know watering volume and growing design on growth, yield, and quality of cherry tomatoes. The research aimed to intend the best treatment for each treatment of watering volume and Growing design on the productivity and quality of cherry tomato cultivar Ruby. The study is an experimental exploration using RCBD factorial. The treatment factors include: Growing Design (greenhouse, Rain shelter, Screen house) and Watering Volume (100% Etc, 75% ETc, 50% ETc). The result showed that root dry weight and root-shoot ratio were found higher in the screen house design, while fruit firmness was higher in the rain shelter design. Considering the effect of watering volume, higher fruit diameter, heavier fruit, fruits per plant, ultimate fruit &amp; biological yield per plant, higher root &amp; shoot biomass, root-shoot ratio, leaf chlorophyll content, greater fruit skin firmness and elasticity was noted in the 100% ETc treatment. In contrast, the growth rate was higher in 50% ETc treatment. Cultivating cherry tomatoes in a greenhouse using a watering volume of 100% ETc under the results is recommended. These conditions have led to better growth, higher fruit yield, and improved fruit quality, making them favorable options for successful cherry tomato production.

Magnesium matrix composites have attracted significant attention due to their lightweight nature and impressive mechanical properties. However, the fabrication process for these alloy compo-sites is often time-consuming, expensive, and labor-intensive. To overcome these challenges, this study employed machine learning (ML) techniques to predict the mechanical properties of magnesium matrix composites. Regression models were utilized to forecast the yield strength of magnesium alloy composites reinforced with various materials. The study incorporated previous research on matrix type, reinforcement type, heat treatment, and mechanical working. The re-gression models employed in this study included decision tree regression, random forest re-gression, extra tree regression, and XGBoost regression. Model performance was assessed using metrics such as RMSE and R2. The XGBoost Regression model out-performed others, exhibiting an R2 value of 0.94 and the lowest error rate. Feature importance analysis indicated that the rein-forcement particle form had the greatest influence on the mechanical properties. The study iden-tified the optimized parameters for achieving the highest yield strength, which was 186.99 MPa. Overall, this study successfully demonstrates the effectiveness of ML as a valuable tool for opti-mizing the production parameters of magnesium matrix composites.

Lead-free copper halide perovskite nanocrystals (NCs) are emerging materials with excellent photoelectric properties. Herein, we present a colloidal synthesis route of orthorhombic Cs2CuCl4 NCs with well-defined cubic shape and an average diameter of 24 ± 2.1 nm. The Cs2CuCl4 NCs exhibit bright deep blue photoluminescence, which is attributed to the Cu(II) defects. In addition, passivating the Cs2CuCl4 NCs by Ag+ can effectively improve the photoluminescence quantum yield (PLQY) and environmental stability.

The present study aimed to investigate influence of genotypic differences to zinc and iron agronomic biofortification responses among yield of finger millet. A field experiment was conducted over two seasons in farmers’ fields in Ethiopia (2019, 2020). The experimental design had 15 treatment combinations comprising 3 finger millet varieties and application of different combinations of zinc and iron mineral fertilizers. 5 soil-applied fertilizer treatments (20 kg h-1 FeSO4 + 25 kg h-1 ZnSO4 + NPKS, 25 kg h-1 ZnSO4 + NPKS, 20 kg h-1 FeSO4 + NPKS, NPKS, and 30% NPKS), at 2 locations (Gojjam and Arsi Negelle, Ethiopia), and two 2 slope positions (Foot and hill), replicated four times in a randomized complete block design. Grain yield and biomass were evaluated on plot basis. Plant height, total and productive tiller number, finger length of the longest spike and number of fingers per main ear were measured at maturity stage. The combined soil application of FeSO47H2O and ZnSO47H2O increased yield to Meba variety by 51.6%. Also, ZnSO47H2O fertilizer application increased yield to Urji variety by 27.6%. About 18.3% of yield enhancement of Diga-01 variety was achieved due to the FeSO47H2O fertilizers application. The findings of the present study suggests that the influence of Zn and Fe agronomic biofortification on yield of finger millet could be affected by genotype differences and environmental conditions.

This study aimed to investigate how transplanting date affects the agronomic and grain quality traits of two early maturing rice varieties. The experiment was conducted in the rice research field of Chungnam Agricultural Research and Extension Services, South Korea and rice materials were transplanted at intervals of approximately 15 days from April 16 to July 16 in 2019 and 2020. Results showed that agronomic and grain quality traits varied according to the transplanting date, and earlier transplanting resulted in the longer period of days from transplanting to heading (DTH). The spikelet number m-2 was highly correlated with the milled rice yield (r = 0.963** for Jinbuol, r = 0.909** for Yeoreumi) and it significantly decreased as the transplanting date was delayed, which was leading to lower yield. Environmental factors, the mean temperature during the grain filling stage, had a negative correlation with head rice rate (r2 = 0.825** for Jinbuol, r2 = 0.803** for Yeoreumi), and the number of days from transplanting to heading showed negative correlation with protein content (r2 = 0.777** for Jinbuol, r2 = 0.833** for Yeoreumi). Therefore, increasing the number of days from transplanting to heading date can lead to higher milled rice yield and lower protein content, and avoiding heading dates on July 17 can improve the appearance traits. As a results, it is suggested that early transplanting is advantageous to increase the milled rice yield and grain quality of early maturing rice.

Crop yield data is critical for managing sustainable agriculture and assessing national food security. Current study aims to increase Peanut productivity from current levels by analyzing the yield gap of production potential between theoretical yield and actual farmers’ yields. The spatial yield gap of Peanut for Thiruvannamalai district of Tamil Nadu is examined in this paper by integrating the products of microwave remote sensing (SAR Sentinel-1A) with DSSAT CROPGRO peanut simulation model. CROPGRO Peanut model was calibrated and validated by conducting field experiment at Oilseeds Research Station, Tindivanam during Rabi 2019 for predominant cultivars viz. TMV 7, TMV 13, VRI 2 and G 7. Actual attainable yield was recorded by organizing CCE with help of Department of Agriculture Economics and Statistics in the respective monitoring Villages. Regression analysis between maximum recorded DSSAT Leaf Area Index (LAI) at peak flowering stage of peanut and yield recorded by Crop Cutting Experiment (CCE) for spatial yield estimation of Peanut in Thiruvannamalai district of Tamil Nadu during Rabi 2021 was carried out using ArcGIS 10.6 software. The results showed that the simulated potential yield ranged from 3194 to 4843 kg/ha, whereas actual yield ranged from 1228 to 3106 kg/ha, with a considerable disparity between the actual and potential yield levels (1217 to 2346 kg/ha) of the monitored locations. The minimum, maximum and average yield gaps in Peanut for Thiruvannamalai district was assessed as 1890, 2324 and 2134 kg/ha, respectively. To reduce the production difference (Yield gap) of Peanut cultivation, farmers should focus more on management issues such as time of sowing, irrigation or water management, quantity and sources of nutrients, cultivar selection and availability of quality seeds tailored to each region.

The study was carried out to investigate the growth response of Tetrapluera tetraptera to selected organic fertilizers. Organic fertilizers: poultry manure and cow dung of different concentration and mixture were used to raise seedlings from Germination experiment for a period of 12 weeks. Six treatments were used for this research: T1 (control experiment), T2 (10g of poultry manure), T3 (10g of cow dung), T4 (20g of poultry manure), T5 (20g of cow dung), T6 (15g of poultry manure + 15g of cow dung). Growth parameters such as diameter, plant height and number of leaves were measured weekly over a period of twelve (12) weeks. Data obtained were subjected to Anova and mean separated using Duncan multiple range tests. on the height parameter assessed on Tetrapluera tetraptera, the highest plant height mean of 12.20cm was recorded in treatment 6 (15g of poultry manure + 15g of cow dung) while the lowest mean plant height 7.19cm was recorded in treatment 3 (10g of cow dung) . the highest mean stem diameter was recorded in treatment 4 with a value of 0.43mm from while the least was recorded in Treatment 1 with mean value of 0.21 m. also, highest mean number of leaves was recorded treatment 4 (12.81) while the least was observed in T3 (11.01) . The results showed that organic manure has considerable effect on the growth of Tetrapluera tetraptera seedlings and it use should be encouraged. T3 (10g of poultry Manure + 10g of cow dung) was hereby recommended to be the best of all in the growth of Tetrapluera tetraptera.

The study investigated the comparative effect organic fertilizers on the growth of Khaya senegalensis (Desr). Four treatments were used for this research: T1 20g of poultry manure, T2 (20g of cow dung), T3 (10g of poultry Manure + 10g of cow dung), T4 (Control experiment). Growth parameters such as diameter, plant height and number of leaves were measured weekly over a period of twelve (12) weeks. Data obtained were subjected to ANOVA and mean separated using Duncan Multiple Range Test. on the height parameter assessed on Khaya Senegalensis, the highest plant height mean of 8.40cm was recorded in treatment 1(20g of poultry Manure) while the lowest mean plant height 7.19cm was recorded in treatment 4 (Control experiment). Also, the highest mean stem diameter was recorded in Treatment 1 with a value of 0.309mm from while the least was recorded in Treatment 4 with mean value of 2.1175mm. However, highest mean number of leaves was recorded treatment 1 (20g of poultry manure) while the least was observed in T3 (10g of poultry Manure + 10g of cow dung). The results showed that organic manure has considerable effect on the growth of Khaya senegalensis seedlings and it use should be encouraged. T3 (10g of poultry Manure + 10g of cow dung) is hereby recommended to be the best of all in the growth of Khaya senegalensis.

Sediment accumulation in a dam reservoir is a common happening environmental problem throughout the world. Topographic conditions, land use land cover change, the intensity of rainfall, and the soil characteristics are the major driving factors for sedimentation to occur. The effect of sedimentation in a dam reservoir is very visible in the watershed as a result of hilly topographic conditions, high rainfall intensity, thin land cover, and less soil infiltration capacity. In this paper, an integrated RUSLE and GIS technique was implemented to estimate a mean annual sediment yield based on spatial and temporal variations in Nashe dam reservoir situated in Fincha catchment, Abaya River basin, Ethiopia. Spatial and temporal estimation of mean annual sediment yield was estimated using the Revised Universal Soil Loss Equation (RUSLE) model and GIS. Historical 6-year (2014-2019) rainfall for the temporal variations and other physical factors such as soil erodibility, slope and length steepness, management and land used land cover, and support practice for spatial variations were used as sediment driving factors. The mean annual sediment yield ranges from 0 to 2712.65 t ha-1 year-1 was seen. Spatially, Very high, high, moderate, low, and very low sediment yield severity with total area coverage with 25%, 10%, 30%, 15%, and 20% in 2017, 2015, 2019, 2014, and 2018 respectively. The information about the spatial and temporal variations of the severity of sediment yield in RUSLE model has a paramount role to control the entry of sediment into the dam reservoir in this watershed. The results of the RUSLE model can also be further considered along with the watershed for planning strategies for dam reservoirs in the catchment.

Tanzania with 945 million hectares of land area and annual rainfall of 300 mm on 67% of its territorial land is considered as a semi-dry region in the world. Rice production in Tanzania needs to be increased to feed a growing population, whereas water for irrigation is getting scarce. One way to decrease water consumption in paddy fields is to change the irrigation regime for rice production and to replace continuous flooding with alternate wetting and drying. In order to investigate the effect of different regimes of irrigation and nitrogen fertilizer on yield and water productivity of hybrid rice, two greenhouse pot experiments comprising soils from upland and lowland production ecologies were conducted at Sokoine University of Agriculture, Tanzania during crop seasons of 2019. The experiment was arranged in split plots based on randomized completely block design with 3 replications. Water regimes were the main factor comparing continuous flooding (CF) and alternate wetting and drying (AWD) with nitrogen fertilizer levels as the sub-factor including absolute control , 0, 60, 90, 120 and 150 kg/ha. Alternate wetting and drying (AWD) improved water productivity in both upland and lowland production ecologies compared to CF. AWD increased yield under lowland production by 13.3% while in upland there was 18.5% decrease in yield. The average water use varied from 31.5 to 84 L pot-1 under upland trials, while in lowland trials it was 36 to 82.3 L. Higher yield and lower water application led to an increase in WP varying from 1.2 to 1.8 kg cm-3 under upland trials, and 0.6 to 1.5 kg cm-3 under lowland trials. The variation in water productivity among treatments was mainly due to the differences in the yield, water and nitrogen levels used in the production process. Both sets of trials recorded water saving up to 34.3% and 17.3% under lowland and upland trials, respectively. Under upland trials, the yield varied from 39.9 to 124.1 g pot-1 and in lowland trials yield ranged from 20.6 to 118.2 g pot-1 representing paddy rice. The measurements showed that less water can be used to produce more crops under alternative rice growing practices. The results are important for water-scarce areas, providing useful information to policy makers, farmers, agricultural departments, and water management boards in devising future climate-smart adaptation and mitigation strategies.

Low soil nitrogen status of savanna soils in Nigeria contributes to the persistent Striga hermonthica (Del.) Benth. infestation that limits maize production. The application of nitrogen fertilizer to Striga-resistant hybrids may reduce Striga infection and increase grain yields. This study assessed the performance of maize hybrids at low (30 kg ha-1) and high (120 kg ha-1) nitrogen application under natural infestation with Striga at Kafin Madaki and Tudun Wada in 2014 and 2015. Results showed that the application of nitrogen at 120 kg ha-1 reduced number of Striga plants by 59% compared to application at 30 kg N ha-1 in Kafin Madaki and by 21% in Tudun Wada. Compared to 30 kg N ha-1, the 120 kg N ha-1 rate also reduced Striga damage rating by 22% in Kafin Madaki and by 33% in Tudun Wada across the hybrids. Hybrids 8338-1 (5.3) and OBASUPER 1 (4.3) were the only entries with Striga damage rating greater than 4.5 (SDR > 4.5) when averaged across the nitrogen levels at both locations. Grain yield was 86 and 98% higher in Kafin Madaki and Tudun Wada, respectively when N was applied at 120 kg N ha-1 than at 30 kg N ha-1. The hybrids M1124-3 and M1227-14 produced grain yields that were significantly higher than those of the other hybrids in all locations. The hybrid 8338-1 produced the lowest grain yield across locations. Our results showed that, the application of 120 kg N ha-1 to Striga resistant maize hybrids will reduce Striga infection and increase grain yield.

The precise information regarding the date of sowing, seed rate and row spacing is critical for achieving yield targets and better economic returns of barley. Therefore here, we determined the information regarding the optimum date of sowing, seed rate, spacing and economic aspects for barley production. This study was conducted for three years, in north Indian plains. Early sowing date of barley (last week of October) recorded higher yield in comparison to late sown crop (3^rd week of November). Moreover, the higher barley production proved more remunerative when sown early in the last week of October to the first week of November as compared to late sown the late sown crop. Furthermore, the enhanced seed rate of 10% then recommended did not affect the grain yield of barley. But, the closer spacing of 20 cm (row to row) produced higher grain yield (5.45 Mg ha^-1 ) than the recommended spacing of 22.5 cm (5.30 Mg ha^-1). Likewise, the economical parameters (net returns) were higher with 20 cm row spacing. Overall, this study determines the optimum date of sowing, seed rate and spacing for scoring better returns of barley crop under north Indian conditions.

Best horticulture management has been practiced to reduce the amount of inorganic fertilizer in connection with net (mosquito net) for higher production of Indian spinach. Excessive use of chemical fertilizers in agriculture promoted negative effect on the environment and human health in Bangladesh. The experiment was conducted at the Horticulture Farm of Bangladesh Agricultural University (BAU), Mymensingh during the period February to May 2016. Two factor experiments were conducted on nettings: control (N₀), Netting (N₁) and different fertilizers: control (F₀), Vermicompost 10 t/ha (F₁), Vermicompost 15 t/ha (F₂), 2/3^rdof F₂+ 1/3^rdof F₄ (F₃), Inorganic fertilizer (F₄). Combination of mosquito net and combined of organic and inorganic fertilizers (N₁F₃) gave the significantly higher growth and yield of Indian spinach compared to other treatment combination. The maximum vine length (77.71 cm), after 45 days after sowing was found from N₁F₃ which was 72% higher compared to control. The highest yield of Indian spinach was 38.67 t/ha from N₁F₃ which was 80% higher compared to control. The treatment combination of N₁F₃ provided maximum leaf numbers per plant, leaf length.

Bread wheat (Triticum aestivum L.) is staple of Pakistani people. However, its yield at farmer field is low as compared with its genetic potential. Integration of various crop and soil management strategies might be an option to enhance wheat productivity at farmer field. This 2-year experiment was conducted to check the influence of combine application of natural plant water extracts and biochar on the productvity of wheat during the winter season of 2015-16. The experiment consisted of seven treatment viz. (1) control (2) application of biochar (0.18 kg pot-1) alone, (3) application of sorghum water extract (SWE) alone, (4) application of moringa water extract (MWE) alone, (5) application of biochar + SWE, (6) application of biochar + MWE, (7) application of biochar + SWE+MWE. The results revealed that application of both crop water extracts in combination with biochar improved the growth and grain yield of wheat. Use of MWE in combination with biochar enhanced the grain weight, grain number and grain yield of wheat by 44, 14, and 24%, respectively than the control treatment. In crux, use of MWE in combination with biochar might be a viable option to improve the productivity of bread wheat.

Several studies have quantified the responses of Eucalyptus globulus plantations to weed control on its early development (2-3 years after establishment). However, long-term results of competing vegetation effects have been rarely incorporated into growth and yield models that forecast the long-term effects of reducing the intensity of competing vegetation control and its interaction with site resource availability on stem volume production close to rotation age. We compared several models predicting stand stem volume yield of Eucalyptus globulus plantations established across a water and fertility gradient growing under different intensity levels of free area of competing vegetation maintained during the first 3 years of stand development. Four sites were selected encompassing a gradient in rainfall and amount of competing vegetation. Treatments were applied at stand establishment and were monitored periodically until age 9 years. Competing vegetation control intensity levels considered 0, 5, 20, 44 and 100% weed-free cover around individual E. globulus seedlings. Maximum competing vegetation biomass production during the first growing season were 2.9, 6.5, 2.2 and 12.9 Mg ha^-1, for sites ranging from low to high annual rainfall. As expected, reductions in volume yield at age 9 years were observed as competing vegetation control intensity decreased during the first growing season. A strong relationship was established between stem volume yield loss and the intensity of competing vegetation control, the amount of competing vegetation biomass produced during the first growing season and mean annual rainfall. The slope of the relationship was different among sites and was related mainly to water and light limitations. Our results, suggest that the biomass of competing vegetation (intensity of competition) affecting site resource availability, contribute to observed long-term effects on E. globulus plantations productivity. The site with the lowest mean annual rainfall showed the highest volume yield loss at age 9 years. Sites with highest rainfall showed contrasting results related to the amount of competing vegetation biomass.

Highly photoluminescent C-Dots are prepared by hydrothermal reaction of citric acid and piperazine as dual reason in both hydrolysis and surface passivation agent along with the N-doping agent. The resulting C-Dots without external passivation showed PL enhancement by electron transfer from C-Dots-donor to piperazine-acceptor with the maximum emission yields of more than 84%. After mixing the prepared C-Dots with the mixture of EtOH and acetone (1:1 vol %), a novel washing process was performed by centrifugation to remove the precursors and by-products. The resulting C-Dots showed much better stability than dialysis. For evaluating the possible application of the C-Dots as a fluorescent biological probe which possess the wide dosing window and multicolor properties. The C-Dots were localized in perinuclear vacuole-like structures with granular pattern in cytoplasm sparing the nucleus. No signs of any morphological deterioration like nuclear shrinkage were observed.

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.

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.

Abstract: A multitude of biotic and abiotic stress factors do harm to plants by bringing about diseases and inhibiting normal growth and development. As an omnipotent signaling molecule, salicylic acid (SA) plays crucial roles in plants' tolerance responses to both biotic and abiotic stresses, thereby maintaining plants’ normal growth and improving yields under stresses. In view of this, this paper mainly discusses the role of SA in both biotic stresses, and abiotic stresses of plants. SA regulates the expression of genes involved in defense signaling pathways, thus enhancing plants’ immunity. In addition, SA mitigates the negative effects of abiotic stresses, and acts as a signaling molecule to induce the expression of stress-responsive genes and the synthesis of stress-related proteins. In addition, SA also improves certain yield-related photosynthetic indexes, thereby enhancing crop yield under stresses. On the other hand, SA acts with other signaling molecules in regulating plants’ growth and improving tolerances under stresses. This paper reviews recent advances in SA’s roles in plant stress tolerances, so as to provide theoretical references for further studies concerning the decryption of molecular mechanisms for SA’s roles and the improvement of crop management under stresses.

Onion is not just an edible food but its seeds can also be an important source of valuable oil with various sensitive applications mainly in pharmaceutical, cosmetic and food fields. This has encouraged the use of a supercritical fluid extraction in the present study to obtain oil from local onion seeds, hence avoiding even traces of organic solvents. For several advantages carbon dioxide at supercritical conditions was used as the fluid. The effects of four key operating parameters like pressure, temperature, particle size and CO2 mass flowrate were investigated in ranges of [150, 250 bars], [35, 65°C], [0.25, 0.85mm] and [50, 100g/min], respectively, using a Box-Behnken experimental design, for a constant extraction time of 3 hours. This led to optimal operating conditions of 250 bar, 57°C, 0.25mm and 50g CO2/min for the highest oil extraction yield value of 24.36%. Furthermore, gas chromatography-mass spectrometry (GC-MS) was used to identify qualitatively and quantitatively the chemical composition of the onion seed oils. About ten components were identified in the extracts, but with four major ones, namely 9,12-Octadecadienoic acid ,methyl ester, 9,12-Octadecadienoic acid (Z,Z)-,methyl ester, 9-Octadecadienoic acid (Z)-,methyl ester and Hexadecanoic acid, methyl ester, present with significant percentages, depending on the operating parameters values. These fatty acids are well known for their benefits for human health. Finally the study shows the importance and the merits of fluids when used under particular conditions of pressure and temperature, in very sensitive industrial fields.

The use of nitrogen (N) fertilizers can have detrimental effects on the environment due to nitrate leaching. This study aims to examine the impact of N fertilizer source and application timing on wheat yield and nitrate leaching in various soil textures. A randomized complete block design (RCBD) was employed to conduct the experiment. The treatments consisted of two N fertilizer sources: ammonium nitrate (AN) and urea (NN), applied at three different times throughout the year, with a control treatment. The three application timings were total application before sowing (T₁), total application in spring (T₂), and half the amount before sowing and the other half in spring (T₃). The experiment was conducted in three different soil textures (sandy loam, silty clay loam, and silty clay), with three replications over three growing seasons: 2018-19 (Y₁), 2019-20 (Y₂), and 2020-21 (Y₃). The results indicated significant effects of different soil textures on grain yield. Specifically, the silty clay loam soil differed significantly from the sandy loam and silty clay soils in terms of grain yield. The interaction effects between the N fertilizer source and application timing were also found to be significant for all soil textures (p<0.01). In sandy loam and silty clay soils, the grain yield increased when using the T₃ application timing compared to the silty clay loam soil. Notably, the silty clay loam soil with the T₂ application timing exhibited the highest grain yield, with a yield of 6863.6 kg ha^-1. Furthermore, the study revealed that N fertilizers and their application timing significantly influenced the protein content in the silty clay and sandy loam soils. The protein percentages were 10.76 and 10.93 for the silty clay and sandy loam soils, respectively, following the T₂ treatment. Additionally, ammonium nitrate (AN) demonstrated a noticeable effect on the percentage of grain protein compared to urea (NN). In conclusion, the application timing of N fertilizers had an impact on grain yield and protein content in different soil textures. Moreover, nitrate concentration increased throughout the experiment, with the highest soil nitrate concentration observed in both fertilizer treatments, particularly in the sandy loam soil.

High-quality rice (Oryza sativa L.) is increasingly widely planted in China with the improvement of people's living standards and the achievement of rice breeding efforts in recent years. However, the agronomic and physiological performances of high-quality indica rice (HQIR) under different nitrogen(N) application conditions in southern China are little known. Two-year consecutive field experiments were conducted with two HQIR and two ordinary-quality indica rice (OQIR) varieties under moderate and high N application rates, with yield and yield components, biomass, N up-take, and their related traits investigated. We found that grain yields of HQIR were slightly de-creased, but grain yields of OQIR were significantly increased by 6.60%-8.88% under high N rate compared with moderate N rate in both years. Thereby, OQIR produced 8.34%-11.87% and 22.00%-22.50% higher grain yield than HQIR under moderate and high N rates, respectively. The different responses of grain yield to N application rates were mainly due to decreased grain set-ting rate in HQIR and increased spikelets m-2 in OQIR under high N rate. Furthermore, high N rate significantly reduced pre-anthesis AE and improved grain-leaf area ratio, while did not in-crease post-anthesis DM compared with moderate N rate in HQIR, which might result in carbon metabolic deterioration and imbalance of source-sink relationship and subsequently lower supply of carbohydrate to panicle. Our results suggest that a moderate N rate (165 kg N ha-1) is beneficial for HQIR varieties to balance the maximum grain yield and high quality in southern China

Chemical fertilizers are commonly used to meet the nutritional demands of the crops and boost their yield. However, their high costs and excessive application in soils increases the cost of production and have negative effects on the soil and environmental health. Vermicompost is an organic amendment that can potentially lessen the dependence on chemical fertilizers with additional advantages of sustainable nutrient supply to crops and maintaining soil health. To evaluate the potential of two diverse vermicomposts, sole and combined application of these vermicomposts with reduced rates of chemical fertilizers were used for tomato cultivation in a field study. The results indicated that vermicompost produced from cow dung combined with chemical fertilizers proved to be more effective in improving tomatoes' growth, physiology, yield and nutritional attributes. Combined application of vermicompost and chemical fertilizer significantly improved root length (21.6%), plant height (167%), SPAD value (13.5%),chlorophyll 'a' (96%), chlorophyll 'b' (161%), relative water content (16%), membrane stability index (18%), carotenoid (87%), yield (82%), photosynthetic rate (148%), and fruit diameter (83%) protein (89%), fat (27.5%), fiber (12%), vitamin C (52%), calcium (54%), magnesium (117%), phosphorus (38%), potassium (128%), as compared to control treatment (NP applied). In addition, significant improvements in different soil physico-chemical properties were also pragmatic. The results suggest that vermicompost application with reduced doses of chemical fertilizers can be used to improve crop yield and soil physico-chemical properties.

In recent years, the production of renewable energy represents one of the main challenges of modern and future society. The new cultivation method called Agrivoltaic (hereafter AV), combines and associates agricultural production and renewable energy (photovoltaic) production in a collaborative synergy from which both benefit. In this study, the dry matter and essential oils yield of six medicinal species (Salvia officinalis L., Origanum vulgare L., Rosmarinus officinalis L., Lavendula angustifolia L., Thymus citriodorus L. and Mentha spicata L.) grown underneath a dynamic AV system in comparison to those in full sun (T), were evaluated. In particular, below the dynamic AV system, due to the rotation of the panels, two plot areas on the ground were distinguished: one always covered by the panels (UP), and another one covered alternatively (BP). During the aromatic crop cycles, the solar radiation, infrared leaf temperature and air temperatures in UP, BP and T plot, were measured. In addition, at harvest time, weed survey was carried out. The results showed that, in general, the solar radiation and infrared leaf temperature were lower in UP plot than in either the BP and T plots, while the air temperatures were similar in all compared plots. Also the weed cover percentage was lower in the UP plot than other ones. The essential oils yield in the sage, thyme, mint and rosemary plants were higher in both UP and BP plots than for T plot. Thus, shading and/or less weed infestation may have been the main factors favorably influencing the performance of medicinal crops under a dynamic AV system.

Climate and land use changes are two factors affecting the hydrology of watersheds. The greatest effect of climate change is probably the change in the hydrological cycle, thus water availability for human consumption, industry, and power generation. While the change in land use can cause changes in the hydrological components of the basin, such as evapotranspiration, runoff, and groundwater recharge. From these projections, it is necessary to understand the processes involved in climate change and land use and its impact on water systems. In this context, the objective of this study was to simulate climate change scenarios combined with the land use change and to analyze the impacts on the hydrology in the Piracicaba basin. Two periods were selected based on the preliminary result of detection of the abrupt change point of the annual flow series, using Petitt's non-parameter test. The first period selected prior to the occurrence of the point of the change was from 1985 to 2000. The other period after the point of the change was 2001 to 2015. Land use maps of the years 1990 and 2010 were used to represent the two periods. The results showed a good performance of the SWAT model. The NS (Nash-Sutcliffe coefficient) was 0.88 in calibration for both periods. In the validation, the NS was 0.92 and 0.94 for the first and second periods respectively. We then simulate climate and land use changes scenarios and compare them to the current scenario (baseline). The simulation results showed that the hydrological processes in the Piracicaba basin in the period 1985-2015, had more intense responses to land use change than climate.

: Our study aim to test the influence of RGB reflectance and chlorophyll content on grain fill and grain yield of 15 durum wheat cultivars sown under semi-arid conditions. the evolution of chlorophyll content during three stages showed a stability during the heading stage, the chlorophyll content begins at this degradation during grain filling. Boutaleb genotype which was the best yielding genotype was characterized by low values ​​of RGB reflectance and high values ​​of majority of grain filling parameters and thousand kernels weight. Grain filling follows a sigmoid curve. Chlorophyll content was positively correlated with reflectance under the green band and negatively with both Red and Blue bands. A positive correlation was recorded between thousand kernel weight and grain yield, maximum grain dry weight and grain filling duration. The duration of the grain filling was positively influenced by the maximum dry weight of the grain and negatively by the grain filling ratio, the grain filling ratio was positively affected by reflectance at blue band. The principal component analysis separated the cultivars considered into 3 principal components, the absorption/reflectance component, the profitability component and the component of grain filling rate to which the local landrace Boutaleb belongs in terms of grain yield.

The use of machine learning techniques to predict yield based on remote sensing is a no-return path and studies conducted on farm aim to help rural producers in decision-making. Thus, commercial fields equipped with technologies in Mato Grosso, Brazil, were monitored by satellite images to predict cotton yield using supervised learning techniques. The objective of this research was to identify how early in the growing season, which vegetation indices and which machine learning algorithms are best to predict cotton yield at the farm level. For that, we went through the following steps: 1) We observed the yield in 398 ha (3 fields) and eight vegetation indices (VI) were calculated on five dates during the growing season. 2) Scenarios were created to facilitate the analysis and interpretation of results: Scenario 1: All Data (8 indices on 5 dates = 40 inputs) and Scenario 2: best variable selected by Stepwise regression (1 input). 3) In the search for the best algorithm, hyperparameter adjustments, calibrations and tests using machine learning were performed to predict yield and performances were evaluated. Scenario 1 had the best metrics in all fields of study, and the Multilayer Perceptron (MLP) and Random Forest (RF) algorithms showed the best performances with adjusted R2 of 47% and RMSE of only 0.24 t ha^-1, however, in this scenario all predictive inputs that were generated throughout the growing season (approx. 180 days) are needed, so we optimized the prediction and tested only the best VI in each field, and found that among the eight VIs, the Simple Ratio (SR), driven by the K-Nearest Neighbor (KNN) algorithm predicts with 0.26 and 0.28 t ha^-1 of RMSE and 5.20% MAPE, anticipating the cotton yield with low error by ±143 days, and with important aspect of requiring less computational demand in the generation of the prediction when compared to MLP and RF, for example, enabling its use as a technique that helps predict cotton yield, resulting in time savings for planning, whether in marketing or in crop management strategies.

Potato is one of the main crops grown worldwide under different climatic conditions. Potato is conventionally produced under intensive tillage practices under the same or different soil types. Research has shown some contrasting effects of the tillage practices on the soil properties, crop growth, yield, and quality. Under the reducing available freshwater for food production, soil management practices are more targeting conservation and system sustainability. It is therefore critical to revisit literature on the tillage practices and their impact on the soil, crop, and crop yield. This review presents research results of studies conducted exclusively on potatoes comparing different types of tillage practices and is a valuable source of information for potato growers and scientists as it is not only focused on the impact of tillage practices on soil properties but also on potato tuber yield and grade, tuber specific gravity, and the impact of tillage practices on diseases in potatoes.

Among the many neglected underutilized species, tuberous Andean root crops like the ahipas (Pachyrhizus ahipa) constitute a promising alternative for increasing diversity in nutrient sources and food security at a regional level. In this study, we present the content of some functional compounds in tuberous roots from several ahipa accessions and the progenies of the interspecific hybrid X207 (P. ahipa × P. tuberosus). A significant objective was to determine protein and free amino acids in the roots to evaluate their food quality as protein supply. The interspecific hybrids have been found to possess the root quality to provide the crop with a higher dry matter content. The high dry matter content of the P. tuberosus Chuin materials is retained in the root quality of the hybrids. Food functional components like carbohydrates, organic acids, and proteins were determined in several ahipa accessions and a stable (non-segregating) progeny of the interspecific hybrid, X207. The X207 roots showed a significantly higher dry matter content and a lower content in soluble sugars, but no significant differences were found in starch content or organic acids compared to the ahipa accessions. About the root mineral contents, Fe and Mn concentrations in X207 were significantly raised compared to the average of ahipa accessions. Among the ahipa and the hybrid, no prominent differences in protein content or protein amino acids were found, being both partially defective in providing sufficient daily intake of some essential amino acids. Root weight, a central component of root yield, was significantly higher in X207, but thorough field studies are required to substantiate the hybrid’s superior yield performance..

Understanding the mechanism for heat tolerance is important for the hot pepper breeding program to develop heat-tolerant cultivars in changing climate. This study was conducted to investigate physiological and biochemical parameters related to heat tolerance and to determine leaf heat damage levels critical for selecting heat-tolerant genotypes. Seedlings of two commercial cultivars, heat-tolerant ‘NW Bigarim’ (NB) and susceptible ‘Chyung Yang’ (CY), were grown in 42 °C for ten days. Photosynthesis, electrolyte conductivity, proline content were measured among seedlings during heat treatment. Photosynthetic rate was significantly reduced in ‘CY’ but not in ‘NB’ seedlings in 42 °C. Stomatal conductivity and transpiration rate was significantly higher in ‘NB’ than ‘CY’. Proline content was also significantly higher in ‘NB’. After heat treatment, leaf heat damages were determined as 0, 25, 50 and 75% and plants with different leaf heat damages were moved to a glasshouse (30–32/22–24 °C in day/night). The growth and developmental parameters were investigated until 70 days. ‘NB’ was significantly affected by leaf heat damages only in fruit yield while ‘CY’ was in fruit set, number and yield. ‘NB’ showed fast recovery after heat stress compared to ‘CY’. These results suggest that constant photosynthetic rate via increased transpiration rate as well as high proline content in heat stress condition confer faster recovery from heat damage of heat-tolerant cultivars in seedlings stages.

Millions of people worldwide have an inadequate intake of selenium (Se) and zinc (Zn), and agronomic biofortification may minimise these problems. To evaluate the efficacy of combined foliar Se and Zn fertilisation in bread making wheat (Triticum aestivum L.), foliar Se (as NaSeO4) and soil and foliar Zn applications (as ZnSO4·7H2O) were tested individually and in all combinations. A 2-year field experiment was established in southern Spain under semiarid Mediterranean conditions, by following a split-split-plot design. The study year (2017/2018, 2018/2019) was considered as the main-plot factor, soil Zn application (50 kg Zn ha-1, nil Zn) as a subplot factor, and foliar application (nil, 10 g Se ha-1, 8 kg Zn ha-1, 10 g Se ha-1 + 8 kg Zn ha-1) as a sub-subplot factor. The best treatment to increase both Zn and Se concentration in both straw, 12.3- and 2.7-fold respectively, and grain, 1.2- and 4.1-fold respectively was the combined foliar application of Zn and Se. This combined Zn and Se application also increased on average the yield of grain, main product of this crop, by almost 26%. Therefore, bread-making wheat seems to be a very suitable crop to be used in biofortification programs with Zn and Se to alleviate their deficiency in both, people when using its grain and livestock when using its straw.

To increase rice production, fertilizer plays a crucial role in rice yield. In this research, we applied the coupled atmospheric and crop model, which is based on the WRF and CERES-Rice models, to find the appropriate nitrogen fertilizer level for increasing rice yield production in northern Thailand. The model was conducted from October to December in 2011 to 2015. To evaluate the model capability, the output from the model, including meteorological data, i.e., precipitation and temperature, and rice production, as compared to actual observation data. The modeling system shows an acceptable level of output for statistical examination; for example, the R² values were 0.93, 0.76, and 0.97 for precipitation, temperature, and rice production, respectively. To assess the optimization of the nitrogen fertilizer level, we designed 9 experiments: control cases and other cases that were multiplied by a factor of 2 – 10 times the nitrogen fertilizer levels. The model suggested that we can produce worthwhile rice yield production by approximately 4830 kg/ha if we increase the nitrogen fertilizer levels by 36 kg/ha.

The study was carried out to determine the influence of organic and inorganic fertilizers on maize yield and soil fertility; to determine economically optimum organic and inorganic fertilizer combinations for maize production. The study was performed in a randomized complete block design consisting of 10 treatments and 3 replications. The treatments were: Control, 100% of R-NP (138 N and 92 P), 100% of vermicompost,100% of conventional compost, 25% R-NP +75% of vermicompost, 50% of R-NP + 50% of vermicompost, 75% of R-NP+25% of from vermicompost, 25% of R-NP +75% of conventional compost, 50% of R-NP+50% of conventional-compost, 75% of R-NP +25% of conventional-compost. All rates of vermicompost and conventional compost were applied based on N equivalence. Results indicate that applications of inorganic fertilizers with a combination of organic source fertilizers were increases maize yield and yield components and improves the nutrient status of the soil. The highest maize grain yield (7494.3 kg ha-1) and above-ground biomass yield (18718.0 kg ha-1) were obtained from the applications of 50% recommended NP fertilizer plus 50% vermicompost which is based on the recommended N equivalent respectively. Similarly, we found that a combination of both inorganic and organic fertilizers application also is the best strategy to improve major soil nutrients, maintain soil fertility. The economic analysis revealed that the highest net benefit of (108,872.0 ETB ha-1) was obtained from the application of 50% recommended NP fertilizer plus 50% vermicompost based on the recommended N equivalence. Yet, the lowest yield and net benefit value were attained from the control or unfertilized plot. Therefore, this study suggests that an appropriate proportion of organic fertilizer with inorganic fertilizer not only for higher yield maize production with an assurance of potential economic returns to the small hold farmers but also improve and maintain the soil fertility and should be adopted with similar soil type and agro-ecologies.

Precision agriculture is a technology used by farmers to help food sustainability amidst growing population. One of the tools of precision agriculture is yield monitoring, which helps a farmer manage his production. Yield monitoring is usually done during harvest, however it could also be done early in the growing season. Early prediction of yield, specifically for fruit trees, aids the farmer in the marketing of their product and assists in managing production logistics such as labor requirement and storage needs. In this study, a machine vision system is developed to estimate fruit yield early in the season. The machine vision system uses a color camera to capture images of fruit trees during the full bloom period. An image segmentation algorithm based on an artificial neural network was developed to recognize and count the blossoms on the tree. The artificial neural network segmentation algorithm uses color information and position as input. The resulting correlation between the blossom count and the actual number of fruits on the tree shows the potential of this method to be used for early prediction of fruit yield.

Since the discovery of the aggregation-induced emission effect in 2001, diaminodicyanoquinone derivatives (DADQs) have presented interesting fluorescence properties, allowing them to be considered fluorescent dyes capable of showing quantum yields above 90%. Besides, the diaminodiacyanoquinone core represents a versatile building block propense either to modification or integration into different systems to obtain and provide them unique photophysical features. Herein, we carried out a theoretical study on the fluorescence properties of three different diaminodicyanoquinodimethane systems. Therefore, time-dependent density functional theory (TD-DFT) was used to obtain the values associated with the dipole moments, oscillator strengths, and the conformational energies between the ground and the first excited states of each molecule. The results suggest that only two of the three studied systems possess significant luminescent properties. In a further stage, the theoretical insights were confirmed by means of experimental measurements, which not only retrieved the luminescence of the DADQs, but also suggest a preliminary and promising antibacterial activity of these systems.

The inter-subspecific crossing between indica and japonica subspecies in rice have been utilized to improve the yield potential of temperate rice. In this study, a comparative study of the genomic regions in the eight high-yielding varieties (HYVs) was conducted with those of the four non-HYVs. The Next-Generation Sequencing (NGS) mapping on the Nipponbare reference genome identified a total of 14 common genomic regions of japonica-originated alleles. Interestingly, the HYVs shared japonica-originated genomic regions on nine chromosomes, although they were developed through different breeding programs. A panel of 94 varieties was classified into four varietal groups with 38 single nucleotide polymorphism (SNP) markers from 38 genes residing in the japonica-originated genomic regions and 16 additional trait-specific SNPs. As expected, the japonica-originated genomic regions were only present in the japonica (JAP) and HYV groups, except for Chr4-1 and Chr4-2. The Wx gene, located within Chr6-1, was present in the HYV and JAP variety groups, while the yield-related genes were conserved as indica alleles in HYVs. The japonica-originated genomic regions and alleles shared by HYVs can be employed in molecular breeding programs to further develop the HYVs in temperate rice.

Bread wheat (Triticum aestivum L.) is one of the most important cereal crops for food security. Of all the stresses that curtail wheat productivity, drought has the most detrimental effects. Especially terminal drought stress i.e. at the time of flowering imposes a big challenge to sustain grain production. In the current study, 339 pre-breeding lines derived from three-way crosses of exotics x elite lines were evaluated in the irrigated and drought stress environments at Obregon, Mexico for the year 2016 and 2018. Drought significantly reduced yield (Y), spike length (SL), number of grains per spikes (NGS) and thousand kernel weight (TKW) by 46.4, 19.2, 23.5 and 25.9%, respectively in comparison to irrigated conditions. Kernel abortion (KA), highly correlated with Y, increased significantly (11.6%) under drought stress environment. Population structure analysis in this panel revealed three sub-populations and a genome wide linkage disequilibrium (LD) decay was at 2.5 cM. Single marker and haplotypes-based genome wide association study (GWAS) revealed significant associations on three chromosomes; 4A (HB10.7), 2D (HB6.10) and 3B (HB8.12) with Y, SL and TKW, respectively. Likewise, associations on chromosomes 6B (HB17.1) and 3A (HB7.11) were identified for NGS and on 3A (HB7.12) for KA. Five traits i.e. normalized difference vegetation index (NDVI), canopy temperature depression (CTD) days to heading (DTH), NGS, KA were associated at chromosome 3A both under irrigated and drought conditions however, different haplotypes were estimated. Twenty-six SNPs were part of 10 haplotype blocks associated with Y, SL, TKW, NGS and KA. In silico analysis of the associated SNPs/haplotypes showed hits with candidate genes known to confer abiotic stress resistance in model species and crops. Potential candidate genes include those coding for sulfite exporter TauE/SafE family in Arabidopsis thaliana, TBC domain containing protein in Oryza sativa subsp. Japonica and heat shock proteins in Aegilops tauschii subsp. tauschii were revealed. The SNPs linked to the promising genes identified in the study can be used for marker-assisted selection.

This study was conducted to investigate the impact of El Niño Southern Oscillation on rainfall distribution and productivity of major Agricultural crops in the Kembta Tembaro Zone of Southern Ethiopia over the past 30 years. Precipitation and temperature data were obtained from the National Meteorology Agency, crop data from the Central Statistical Agency of Ethiopia, and the Sea Surface Temperature data from the NOAA website. The rainfall trend had shown decreasing trend with high variability at all the stations (p<0.05). Over the same period, El Niño and La Niña event were observed and highly affected rainfall distribution. It was found that Coefficient Variation was greater than 30%, which indicates the area was prone to drought episodes. The impacts of the ENSO events on the yield of Maize, Wheat, Barely, Sorghum and Enset were assessed. Wheat and Maize were highly affected by the ENSO events. Enset was found to be more resistant crop to the influence of ENSO. Barely and Sorghum were affected at varying magnitude. Among the five chosen crop for this investigation two of the crops were seriously affected during the two extremes, i.e. El Niño and La Niña. From this investigation it is conclude that the overall cereal crop productivity was decreased and precipitation variability was noticed. So, having the information about ENSO phase in advance can be used to forecast ENSO and select crop types and varieties to maximize agricultural rain fed cereal crop productivity while minimizing the crop risk associated with seasonal rainfall and ENSO phases.

ABSTRACT: Waterlogging is a common abiotic stress in global maize production. Maize flowering stage (from tasseling to silking) is more fragile to environmental stresses among different growth stages. The effects of waterlogging at flowering stage on the grain yield and starch quality of waxy maize were studied using Suyunuo5 (SYN5) and Yunuo7 (YN7). The grain yield and starch concentration of both hybrids were reduced by waterlogging. The size of starch granules and proportion of small-molecule amylopectin increased in SYN5 and decreased in YN7 when plants suffered waterlogging at flowering, in contrast to the change trend of relative crystallinity. The pasting viscosities and gelatinization temperatures were reduced, whereas the gelatinization enthalpy was unaffected by waterlogging in both hybrids. Our study indicated that waterlogging at flowering reduced the grain yield, restricted starch deposition, and deteriorated the pasting property of waxy maize. Between the two hybrids, YN7 and high pasting viscosities and low retrogradation percentage than SYN5, indicated its advantages on produce starch for viscous and less retrograde food. Results provide information for utilization of waxy maize grain in food production.

The broad bean plant contains L-DOPA, a compound that is essential for patients with Parkin-son’s disease. However, little has been reported on other broad bean compounds that have bene-ficial effects on health. The objective was to evaluate plants of four Mexican broad bean varieties to determine the content and yield of total phenolic compounds (TPC), total flavonoids (TF), and L-DOPA, as well as to analyze the flavonoid profile and antioxidant (AA) and anti-inflammatory (AANTI) activity in vitro. Broad bean seeds were sown in the field and plants were harvested 20 days after emergence. The analyses were performed with visible UV spectrophotometry and HPLC. The variety José María produced the highest yield of TPC (9.30 g m-2), TF (8.08 g m-2) and L-DOPA (5.64 g m-2) per unit of area. The highest yields per plant were obtained with the Rojita variety: TPC (0.25 g plant-1), TF (0.21 g plant-1) and L-DOPA (0.17 g plant-1). This variety also had the highest antioxidant (CI50= 87.68 µg mL-¹) and anti-inflammatory (CI50= 74.40 mg mL-1) activi-ty, which was attributed to the L-DOPA compounds and to rutin and isoorientins, respectively. The flavonoid profile revealed the presence of rutin and isoorientins, which had not been previ-ously detected in the broad bean plant.

Carbon dots are carbon based nanoparticles, which have the characteristics of simple preparation process, photoluminescence, biocompatibility, adjustable surface function, water solubility, and low toxicity. They are widely used in biological applications such as imaging, biosensing, photocatalysis, and molecular transfer. It has also aroused great interest among researchers in agriculture and has made significant progress in improving crop growth and production. This review presents the physiological functions of carbon dots for crop growth and development, photosynthesis, water and nutrient absorption, and abiotic stress resistance and their applications in improving ecological environment and agriculture as biosensors, and the future application prospects and research directions of carbon dots in agriculture were prospected.

The use of saline water under drought conditions is critical for sustainable agricultural development in arid regions. Biochar used as a soil amendment to enhance soil properties such as water-holding capacity and the source of nutrition elements of plants. Therefore, the experiment was conducted to evaluate the effects of biochar application on the morpho-physiological traits and yield of tomatoes under combined salinity and drought stress into greenhouses. There were 16 treatments consist two water quality fresh and saline (0.9 and 2.3 dS m-1), three deficit irrigation levels (DI) 80, 60, and 40% addition 100% of ETc, and biochar application by rate 5% (BC5%) (w/w) and untreated soil (BC0%). The results indicated that the salinity and water deficit negatively affected morphological, physiological, and yield traits. In contrast, the application of biochar improved all traits. The interaction between biochar and saline water leads to decreased vegetative growth indices, leaf gas exchange, relative water content of leaves (LRWC), photosynthetic pigments, and yield, especially with the water supply deficit (60 and 40% ETc), where the yield decreased by 42.48% under the highest water deficit at 40% ETc compared to the control. The addition of biochar with freshwater led to significantly increased of vegetative growth, physiological, yield, WUE, and less proline content under all various water treatments compared to untreated soil. In general, biochar combined with DI and freshwater could be improve morpho-physiological attributes, to sustain the growth of tomato plants, and increase productivity in arid and semi-arid regions.

Grain yield prediction affects policy making in various aspects such as agricultural production planning, food security assurance, and adjustment of foreign trade. Accurately predicting grain yield is of great significance in ensuring global food security. This paper is based on the MODIS remote sensing image data products from 2010 to 2020, and adds band information such as vegetation index and temperature to form composite remote sensing data as a data set. Aiming at the lack of models for large-scale forecasting and the need for human intervention in traditional models, this paper proposes a grain production estimation model based on deep learning. First, image cropping and yield mapping techniques are used to process the data to generate training samples. Then the channel and spatial attention mechanism (Convolutional Block Attention Module, CBAM) is added for extracting spatial information in different remote sensing bands to improve the efficiency of the model. Long Short-Term Memory (LSTM) neural networks is also added to obtain feature information in the time dimension. Finally, a national-scale grain yield prediction model is constructed. The proposed model was tested on data from 2018 to 2020 showing an average R2 of 0.940 and an average RMSE of 80,020 tons, indicating that it can predict Chinese grain yield better. The model proposed in this paper extracts grain yield information directly from the composite remote sensing data, and solves the problem of small-scale research and imprecise yield prediction in an end-to-end manner.

This study aimed to evaluate the effect of incorporating linseed oil and fish oil in the diet on intake, ruminal fermentation milk yield and milk fatty acid profile in dairy goats. Four crossbred Saanen lactating goats in mid-lactation and milking 1.30±0.28 g/day were used in a 4 × 4 Latin square design. The basal diet consisted of concentrate and Para grass (C:F 40:60). Treatments included the basal diet without oil supplement (Ctrl) or with 2.5% linseed oil (LO2.5), 2.5% linseed oil and fish oil (3:2, w/w, LFO2.5), and 4.16% linseed oil and fish oil (3:2, w/w, LFO4.16). Diets had no effect on intake, milk yield, milk composition and ruminal fermentation patterns (P > 0.05). The lower (P < 0.05) proportions of C10:0-C14:0 in milk fat were observed with LFO4.16 compared with Ctrl. Compared with the Ctrl and linseed oil added alone, feeding LFO4.16 resulted in a 589% and 303% increase in C18:1 t11, respectively. Milk c9,t11 CLA was markedly increased with the LFO4.16 diet, accounting for 4.53 and 2.94 times greater concentrations than those in Ctrl and LO2.5 diets, respectively (P < 0.01). Goats fed LFO2.5 and LFO4.16 had greater levels of C22:6n-3 (0.63% and 0.87%; P < 0.001) compared with those fed Ctrl and LO2.5 diets (0.06% and 0.08%). Overall, the combined data suggested that including 4.16% linseed oil and fish oil in the diet of dairy goats is effective for improving the concentrations of healthy fatty acids in milk, without affecting milk production.

The modeling and prediction of crop seed yield can be a vital improvement in the precision agriculture industry as it provides reliable assessments of the effectiveness of agro-traits. Here, multiple machine learning (ML) techniques are established for predicting sesame (Sesamum indicum L.) seed yield (SSY) and incorporating agro-morphological features. Models utilized for coupled PCA-ML (Principal component analysis-Machine Learning) methods were compared with original ML models to evaluate predicted efficiency. The Gaussian process regression (GPR) and Radial basis function neural network (RBF-NN) models exhibited the most accurate SSY predictions with determination coefficients or R2 values of 0.99 and 0.91, respectively. The root-mean-square error (RMSE) for the ML models fluctuated between 0 to 0.30 t/ha (metric tons/hectare) for the varied modeling process phases. Estimation of sesame seed yield with coupled PCA-ML models improved performance accuracy. The K-fold process suggested the utilization of datasets with the lowest error rates to ensure the continued accuracy of GPR and RBF models. Sensitivity analysis revealed the capsule number per plant (CPP), seed number per capsule (SPC), and 1000-seed weight (TSW) were the most significant seed yield determinants.

Often yam varieties grown in different agro-ecologies show differential responses across production environments, a term known as genotype-by-environment interaction. Genotype-by-environment interaction makes selecting the best genotypes under varied production environments more complex. This study tested twenty yam genotypes evaluated in six test environments to assess genotype, environment, and the interaction between genotypes and environmental effect for tuber yield, yam mosaic virus, and dry matter content. The experiments were conducted in two seasons across three locations in Uganda using a randomized complete block design with three replications. The results showed a significant effect (p ≤ 0.001) for genotype (G), environment (E), and genotype by environment interaction for all the traits. Serere 2021 and Namulonge 2021 were identified as the most discriminating and representative environments for testing the yam mosaic virus, respectively. Serere 2021 was recognized as the most discriminating environment, whereas Arua 2021 was identified as the closest to an ideal environment for assessing yam tuber yields. The tested genotypes also exhibited high resistance to yam mosaic virus disease, high tuber yields, and high dry matter content. Genotypes UGY16020, UGY16034, UGY16042, and UGY16080 demonstrated great resistance to yam mosaic virus disease, high yielding, and considerable dry matter content and are thus potential parents for yam improvement. Further evaluation of the four genotypes should be done under farmers' production systems for selection, improvement, and release as new yam varieties for Uganda

In dry season paddy farming, the alternate wetting and drying (AWD) irrigation improves water productivity, paddy production, and has the potential to decrease greenhouse gas (GHG) such as methane (CH4) and nitrous oxide (N2O) emissions when compared to continuous flooding (CF). However, there is a lack of research in Bangladesh on the effects of water management on CH4 and N2O emissions. During November 2017–April 2018, participatory on-farm trials were conducted at Feni and Chattogram districts of Bangladesh. Total 105 farmers comprising 20-hectare of land (62 farmers at Feni and 43 farmers at Chattogram district, each location having 10 hectare of land). We compared irrigation water and cost reductions, paddy yield, and CH4 and N2O emissions from paddy fields irrigated using AWD and CF irrigation methods. The CH4 and N2O emissions were determined using the Cool Farm Beta-3 methodology, and the global warming potential (GWP) was estimated using the Intergovernmental Panel on Climate Change-2014 standard approach. The mean results of randomly selected 30 farmers from two locations (15 of each) showed that AWD remarkably decreased irrigation water consumption by about 24% and increased water productivity by 224%. We estimated 23% savings for irrigation costs in AWD. By this time, AWD improved paddy production by 3% over CF. The AWD irrigation resulted in a 47% reduction in cumulative CH4 emissions having a lower CH4 emission factor (0.74 kg ha-1 day-1) than CF (1.39 kg ha-1 day-1). There was no obvious difference in N2O emission between AWD and CF. When compared to CF, AWD decreased the overall GWP by 27% and lowered the GHG intensity by 42%. The CH4 and N2O emissions did not differ substantially between Feni and Chattogram.

Microbial communities play a key role in sustainable agriculture. However, we still need more in-formation, to understand the complex response of the microbial community to long-term organic farming, which aims to reduce synthetic fertilizer and pesticide use in order to produce sustainably and improve soil quality. We have assessed the long-term effect of two organic cropping systems and a conventional system on the microbial soil community structure using high-throughput se-quencing analysis. We analyzed the link between these communities and changes in soil properties and crop yield. Results showed that the crop yield was similar among the three cropping systems. Soil properties, such as total organic carbon, nitrogen, ammonium, magnesium and boron, influ-enced changes in the bacterial community structure. A linear discriminant analysis effect size (LEfSe) showed different bacteria and fungi as key microorganism of each of the three different cropping systems, in addition, our results reflected that fungal community were more sensitive than bacteria to cropping system. This research provides an insight about changes occurred in soils, especially in microbial communities considering the effect of that changes in crop yield which were remained stable among the different cropping systems.

Faba bean (Vicia faba L) is the first grain legume in terms of hectarage, total production and foreign exchange earnings in Ethiopia. The current study was designed to evaluate effect of NPS and bio-organic fertilizers on the yield and yield components of faba bean in Debre Markos University research farm. A total of 16 treatments were made from the factorial combination of four levels NPS (0, 50, 100 and 150 kg ha-1) and four levels bio-organic fertilizer (Nil BOF (Bio(Nil)), rhizobium (Bio(IR)), 10 t ha-1 FYM (Bio(FYM)) and FYM+Rhizobium (Bio(FYM+IR))) in randomized complete block design (RCBD) with three replications. The Walki (EH 96049-2) variety, which is high yielding, moderate disease resistant and water-logging tolerant used as test crop. The result experiment showed that, plot treated with Bio(FYM+IR)+NPS100 treatment gave statically maximum effective number of tillers (2.73), maximum number of pods per plant (20.30), hundred seeds weight (76.11g), grain yield (5.62 t ha-1), biomass yield (10.94 t ha-1) and Harvest index (59.91%) than over other treatments received NPS fertilizer with and without bio-organic fertilizers. Therefore, the combined use of 100kg ha-1 NPS with 10 tha-1 FYM and rhizobium inoculation is superior for optimum production of faba bean in study area.

Cowpea yield improvement is done by adding agricultural inputs. The use of natural substances as pesticides is being encouraged to fight against cowpea field pests. The pesticidal potentials of aqueous extracts of Azadirachta indica and Boswellia dalzielii, Metarhizium anisopliae, alone and in combination with plant extracts, as well as the commercial insecticide Decis were tested on two Vigna unguiculata varieties in field in two agroecological zones (Guinean Savanah and Sahelian Savanah) of Cameroon. The field trials were arranged in a completely randomized block design with nine treatments including control. Each treatment was replicated four times. Vigna unguiculata plants were sprayed at flowering stage thrice with insecticidal products at 5 days interval. Data assessment consisted of counting ramifications per plant, the number of pods per block, and seed yield. All the tested insecticides significantly (p&lt;0.0001) improved the cowpea yield in the two agro-ecological zones. The productions parameters were highly influenced by variety and agroecological zone. The extracts and their combinations were as effective as synthetic pesticide (Decis). Bafia variety recorded the highest ramification rate (37.03±1.59) when treated with the combination of M. anisopliae and A. indica in Maroua (Sahelian Savanah). The same variety also produced most important pods number (90.50±16.66) in Ngaoundere (Guinean Savanah) with the combination of A. indica and B. dalzielii. The highest seed yield (44.23±2.31) was recorded in Ngaoundere with B125 variety treated with the combination of the three treatments (A. indica, B. dalzielii, M. anisopliae). A. indica, B. dalzielii, M. anisopliae and their combinations could be considered as potential natural input in the improvement of V. Unguiculata yield. This would not only increase V. unguiculata yield but also preserves environment from the pollution due to the use of synthetic residual chemicals.

The aim of the present study was to assess the efficacy of All Cosmos Industries (ACI) bio-organic and bio-chemical fertilizers and ACI N-Fixer (N-Bio Booster) on the paddy yields based on the field trial plots at Langkat, Medan, Indonesia. This application of ACI bio-organic fertilizer (NPK 5/5/5) and ACI bio-chemical (NPK 15/15/15) fertilizer and ACI N-Fixer tests were conducted at the paddy farm at Langkat from May-October 2018. This study employed a factorial randomized complete block design which consisted of two factors, namely: Factor I with four types of fertilizers while Factor II consisted of two paddy varieties (Inpari 30 and Inpari 32). Overall, the filled grains in the ACI treatments are significantly (P< 0.05) higher than those in the control treatments that used Normal Chemical Compound NPK. Overall, total weight per meter² (368-617g) in ACI treatments are also significantly (P< 0.05) higher than those (319-371g) in the control treatments. At harvesting time at 105 days after transplanting, significantly higher (P< 0.05) colony counts (13-15 x 10⁶ CFU/mL) (for ACI treatments), than those (8 x 10⁶ CFU/mL) in the controls positively indicated higher total yields of paddy grains per hectare. It was found that the application of ACI bio-organic and bio-chemical fertilizers and ACI N-Fixer can improve paddy yields of the two rice varieties, between 16.4-38.2% (up to 5.75 MT/ha), in the field trial plots at Langkat. These commercial fertilizers play an imperative role in refining the soil fertility and thereby can increase the yield of rice production. Therefore, it is highly recommended that ACI bio-organic and ACI bio-chemical fertilizers and ACI N-Fixer (N-Bio Booster) can be employed to increase the paddy yield in this region.

Rice-Tartary buckwheat is a special type of Tartary buckwheat with easy hulling thin shell. The local rice-Tartary buckwheat ‘cv. Xiaomiqiao’ (XMQ) was used to explore the characteristics of photosynthesis, starch synthesis, yield and quality, as compared to Tartary buckwheat ‘cv. Jinqiao 2’(JQ2). XMQ showed significantly lower values of net photosynthetic rate, ADPGase activity and starch synthase activity at one or more periods during grain filling, as compared to that of JQ2. The effective branch number and grain number per plant of XMQ were similar to that of JQ2 regardless of different years, but the 1000-grain weight was significantly lighter that resulted in the significantly lower yield. XMQ accumulated similar contents of starch (amylose, amylopectin) and protein (glutelin, albumin, prolamin, globulin) to that of JQ2, but exhibited significantly lower flavonoid content. The values of peak viscosity and hot paste viscosity in XMQ were similar to that of JQ2, but the values of cool paste viscosity, breakdown and setback were significantly lower. In conclusion, XMQ showed low yield due to the insufficient of photosynthesis and starch synthesis. XMQ exhibited high nutritional quality as well as normal Tartary buckwheat and stored 18.88mg g-1 of flavonoid, that can be consumed as daily diet. The present results will provide a basis for food processing and breeding of rice-Tartary buckwheat.

An experiment was carried out at Nabogram Khamarbari, near the Manannogor, Sadar Upazila, Noakhali District, Noakhali-3814, Bangladesh during the period from 12th January 2018 to 17th April 2018, with two varieties of tomatillo (Physalis ixocarpa Brot.) SAU tomatillo-1 and SAU tomatillo-2. It was laid out in RCBD method having three replications and was conducted to observe the influence of staking and non-staking on tomatillo cultivation in coastal areas. For the study, growth indicating characters like no. of leaves plant^-1, size of leaf plant^-1, height of each plant, no. of branches plant^-1 and yield attributing parameters such as days to first flowering, days to 50% flowering, no. of fruits branch^-1, fruit weight and yield were obtained from the plants with the treatments of staking and non-staking. A wide variation was observed between two varieties of tomatillo with the effect of these treatments. According to the results highest no. of leaves branch^-1, maximum size of leaves branch^-1, tallest height of each plant, uppermost no. of branches plant^-1, highest no. of fruits branch^-1, maximum weight of each fruit and yield were obtained in the staking treatment over the non-staking treatment of SAU tomatillo-1 and in case of SAU tomatillo-2, with the same parameters the result indicated significantly upper in the staking treatment over non-staking treatment. Considering the two varieties of tomatillo, the outcome were significantly superior with staking treatment for the similar parameters. The findings of the experiment indicated that the best yield (21 tha¹) and highest financial benefit could be obtained by SAU tomatillo-1 and the best tomatillo production in saline soil of coastal areas is possible by cultivating SAU tomatillo-1.

The effects of climate change on yield and quality for different climate regions had high uncertainty. Risk assessment is an effective measure to assess the seriousness of the projected impacts for decision-makers. The modified quality model was used to simulate integrated impacts of climate change, environment and management on wheat yield and quality. Then, the Canadian Earth System Model (CanESM2) was used to forecast the daily meteorological data, and Statistical Down Scaling Model was used for downscaling. CERES-Wheat was combined with the forecasted meteorological data to simulate the future wheat yield and grain protein concentration (GPC). The risk of wheat yield and quality in three climatic regions of Shaanxi combined with two climate change scenarios of CanESM2 were assessed. Temperature increased 0.22-3.34 °C and precipitation increased 10-60 mm for RCP4.5 and RCP8.5. Elevated temperature and precipitation had positive effects on yield in all regions. The yield risk of most regions with climate change decreased 3.8%-25.1%. The GPC risk of all regions with climate change decreased 7.3%-27.2%. Irrigation decreased yield risk greatly in all regions, while had totally different effects for the three climatic regions. Yield risk with irrigation decreased 37.7%-52.1% in different climate. In contrast to previous studies, GPC risk with irrigation increased greatly 25.8%-28.9% in humid region, 3.9%-8.8% in sub-humid region, and decreased 37.7%-52.1% in semi-arid region. Climate change decreased yield risk and GPC risk together. While irrigation decreased yield risk greatly in all regions, had totally different effects for the three climatic regions.

The mechanical hill wet-seeded rice machine is benefits to establish uniform seedling, and ditches were established by using this machine. However, little knowledge is known on the effect of the establishment of ditches on growth, lodging and yield, and their relationship with root traits. In this study, two field experiments were conducted during 2012 and 2013 with using two super rice varieties (i.e. hybrid rice ‘Peizataifeng’ and inbred rice ‘Yuxiangyouzhan’) grown under three ditches establishment treatments (i.e. T1: both water ditches and seed ditches were established by the machine, T2: seed ditches were established by the machine, T3: neither water nor seed ditches were established by the machine). The lodging index and lodging resistance traits, the grain yield and above-ground dry weight and the root traits were measured. The results showed that the lodging index was significantly affected by the treatments with ditches. The strongest lodging resistance was detected in mechanical hill wet-seeded rice with ditches treatment in both 2012 and 2013. The lodging resistance was strongly related to the breaking resistance, the root volume and root superficial area at the heading stage and maturity stage and the total root length at the heading stage. No significant difference was investigated in grain yield or dry weight of mechanical hill wet-seeded rice. Yuxiangyouzhan showed higher grain yield, dry weight and better lodging resistance but unfavorable root growth attributes than Peizataifeng. Therefore, the mechanical hill wet-seeded rice with ditches treatment increased rice lodging resistance is related to root traits.

Heat stress occurring during the reproductive stage of wheat has a detrimental effect on productivity. A durum wheat core set was exposed to simulated terminal heat stress by applying plastic tunnels at the time of flowering over two seasons. Mean grain yield was reduced by 54% compared to control conditions, and grain number was the most critical trait for tolerance to this stress. The combined use of tolerance indices and grain yield identified five elites: Kunmiki, Berghouata1, Margherita2, IDON37-141, and Ourgh. The core set was also subjected to genome wide association study using 7,652 polymorphic SNPs markers. The most critical genomic regions were identified in association with spike fertility and tolerance indices on chromosome 1A, 5B and 6B. Haplotype analysis on a set of 208 elites confirmed that lines that carried the positive allele at all three QTLs resulted in a yield advantage of 8% when field tested under daily temperatures above 31° C. Two of the QTLs were successfully validated into KASP markers and explained >10% of the phenotypic variation for an independent elite germplasm set. These genomic regions can now be readily deployed via breeding to improve resilience to climate change and increase productivity in heat-stressed areas.

A new method for wide-area urban roof assessment of suitability for solar photovoltaics is introduced and validated. Knowledge of roof geometry and physical features is essential for evaluation of the impact of multiple rooftop solar photovoltaic (PV) system installations on local electricity networks. This paper begins by reviewing and testing a range of existing techniques for identifying roof characteristics. It was found that no current method is capable of delivering accurate results with publicly available input data. Hence a different approach is developed, based on slope and aspect using LIDAR data, building footprint data, GIS tools and aerial photographs. It assesses each roof’s suitability for PV installation. That is, its properties should allow the installation of at least a minimum size photovoltaic system. In this way the minimum potential solar yield for region or city may be obtained. The accuracy of the new method is then established, by ground-truthing against a database of 886 household systems. This is the largest validation of a rooftop assessment method to date. The method is flexible with few prior assumptions. It is based on separate consideration of buildings and can therefore generate data for various PV scenarios and future analyses.

Dryland winter wheat in Loess Plateau is facing yield reduction due to shortage of soil moisture and delayed sowing time. Field experiment was conducted at Loess Plateau in Shanxi Province, China from 2012 to 2014, to study the effect of subsoiling and conventional tillage and different sowing dates on the soil water storage and contribution of N accumulation and remobilization to yield of winter wheat. The results showed that subsoiling significantly improved the soil water storage at 0-300 cm depth, improved the number of tillers and pre-anthesis N translocation in various organs of wheat and post-anthesis N accumulation, eventually increased the yield up to 17-36%. Delaying sowing time had reduced the soil water storage at sowing and winter accumulated temperature by about 180˚C. The contribution of N translocation to grain yield was maximum in glume+spike followed by in leaves and minimum by stem+sheath. In addition a close relationship was found between the N accumulation and translocation and the soil moisture in the 20-300 cm. Subsoiling during the fallow period and the medium sowing date was beneficial for improving the soil water storage and increased the N translocation to grain, thereby increasing the yield of wheat, especially in dry year.

The Geostationary Ocean Color Imager (GOCI) of the Communication, Ocean, and Meteorological Satellite (COMS) increases the chance of acquiring images with greater clarity at eight times a day and is equipped with spectral bands suitable for monitoring crop yield with a moderate spatial resolution. The objectives of this study were to classify nationwide paddy fields and to project rice (Oryza sativa) yield and production using the grid-based GRAMI-rice model and GOCI satellite products over South Korea from 2011 to 2014. Solar insolation and temperatures were obtained from COMS and the Korea local analysis and prediction system for model inputs, respectively. The paddy fields and transplanting dates were estimated using Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and land cover products. The crop model was calibrated using observed yield data in 11 counties and was applied to 62 counties in South Korea. The overall accuracies of the detected paddy fields ranged from 89.5 to 90.2%. The simulated rice yields statistically agreed with observed yields, with root-mean-square errors of 0.219 to 0.451 ton ha-1 and Nash–Sutcliffe efficiencies of 0.241 to 0.733 in four years, respectively. According to paired t-tests (α = 0.05), the simulated and observed rice yields were not significantly different. These results demonstrate the possible development of a crop information delivery system that can classify land cover, simulate crop yield, and monitor regional crop production on a national scale.

Rhizosphere microbiomes which have been implicated to enhance plant growth and yield are modulated or influenced by a couple of environmental factors such as soil type, plant cultivar, climate change and anthropogenic activities. In particular, anthropogenic activity such as the use of nitrogen-based chemical fertilizers is associated with environmental destruction and this call for a more ecofriendly strategy to increase nitrogen level of agricultural land. This feat is attainable by harnessing nitrogen-fixing endophytic and free-living rhizobacteria. Rhizobium, Pseudomonas, Azospirillum and Bacillus have been found to have positive impacts on crops by enhancing both above and belowground biomass and could therefore play positive roles in achieving sustainable agriculture. Thus, it is needful to study these rhizosphere microbiomes with more sophisticated culture-independent technologies such as next generation sequencing (NGS) with the prospect of discovering novel bacteria with plant growth promoting traits. This review is therefore aimed at discussing factors that can modulate rhizosphere microbiomes with focus on the contributions of nitrogen fixing bacteria towards sustainable agricultural development and the techniques that can be used for their study.

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.

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.

Psychrophilic anaerobic digestion emerges as an appealing integrated solution for the management of agricultural waste, particularly for farmers in regions where the average temperature does not exceed 26°C, as seen in coffee cultivation. Therefore, this study seeks to assess the biomethane potential of thermochemical treated coffee husk through psychrophilic anaerobic digestion (C3-20°C-w/pretreatment). To examine its viability, outcomes were compared with reactors operating at both mesophilic (C1-35°C) and psychrophilic (C2-20°C) conditions, albeit without the use of pretreated coffee husk. The C3-20°C-w/pretreatment test demonstrated a 36.89% increase (150.47 mL CH4/g VS; 161.04 mL CH4/g COD), while the C1-35°C test exhibited a 24.03% increase (124.99 mL CH4/g VS; 133.77 mL CH4/g COD), both in comparison to the C2-20°C test (94.96 mL CH4/g VS; 101.63 mL CH4/g COD). Notably, the C3-20°C-w/pretreatment trial yielded superior outcomes, accompanied by an associated energy output of 4262.2 KWh/year, sufficient to meet the annual energy demands of 588 residences. This marks an increase of 100 and 217 residences compared to mesophilic and psychrophilic AD of CH without pretreatment, respectively.

The production of plants and crops is influenced by environmental stress, which is a serious scientific issue. Cotton is an essential crop for producing natural fibers that are used to make biofuel and edible oils. Salinity is the main element that influences cotton growth during the beginning of germination. The type of salt and the growth stage affects how sensitive a plant is to salt stress. Developing ways to enhance cotton performance in salty circumstances can be aided by an understanding of the response of cotton to salt, its mechanism of resistance, and its management methods. Osmotic and ionic imbalances originate due to the deposition of soluble salts under salinity stress in the plant's root zone. Soil salinity significantly reduces plant growth due to several factors, such as nutritional ion imbalance, which reduces K+, PO4-, and NO- absorption, excessive salt chloride concentrations, and osmotic stress, which hinders water availability. Research has revealed that compared to subsequent stages, the germination, emergence, and seedling phases are more vulnerable to salinity stress, which ultimately affects the seed cotton yield by delaying blooming, reducing fruiting positions, shedding fewer fruits, and reducing boll weight. The morphology, growth of cotton roots, shoots, yield, and fiber quality are all strongly impacted by salinity stress. It slows down plant feeding, cellular metabolism, and photosynthesis. The soil, water, and climate all affect how the plant responds to salinity stress. During salt stress, excessive exclusion of sodium or its compartmentalization is the key adaptation process in cotton. A major adaptive potential to create cotton types that can withstand salt is provided by the up-regulation of both physicochemical and non-enzymatic antioxidant genes. A successful strategy to increase cotton germination in saline soils is seed priming. Moreover, the transgenic strategy might be a viable choice for improving cotton yield in saline environments. Our review focuses on the impacts of salinity on cotton productivity as well as how plants react to salt stress. It also clarifies recent genetic advancements and molecular breeding for cotton's resistance to soil salt. To create salt-tolerant cultivars, a combination of traditional breeding and novel molecular approaches will be useful.

Crop yield enhancement is crucial for ensuring food security and meeting the growing global demand for agricultural products. The development of innovative technologies, such as CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats), has provided new avenues for precise genetic modifications in crops. In this research article, we explore the application of CRISPR technology for crop yield improvement. We discuss the methodology, present recent results, and engage in a comprehensive discussion of the potential benefits, challenges, and future prospects of CRISPR-mediated crop yield enhancement.

A Fall armyworm (FAW) is a major pest of maize and causes huge losses. Chemical control is the commonly used strategy FAW among farmers. Efficacy of baculovirus against FAW has been proven, however, farmers may not afford the products. The use of farmer produced baculovirus mixtures could provide an opportunity for a nature-based solution for FAW at low cost. This study evaluated the potential of virus extracted from FAW larvae treated with a commercial baculovirus (Littovir) for the management of FAW under laboratory and field conditions. In Laboratory, the virus extracted from 25, 50, 75 and 100 FAW larvae caused varied mortality on FAW instars. The highest mortality (45%) on 1st-3rd instars was caused by Littovir followed by virus extract from 100 FAW larvae (36%). Under field conditions, even though virus extracts did not offer adequate protection against the FAW damage, the maize yield was comparable to commercial insecticides treated plots. This study has shown the potential of use of virus extracts for management of FAW. This would offer the farmers a sustainable and affordable option for management of FAW as it would require the farmers to purchase the commercial baculovirus once and collect larvae from treated plots for repeat applications.

In the context of market relations in agriculture in the Kyzylorda region, in order to meet the needs of animal husbandry in complete feed, it is necessary to create a solid forage base. The successful solution to the tasks of increasing the number of livestock and increasing the productivity of animal husbandry in the ecological conditions of the Aral Sea region largely depends on the timely procurement of feed and the transfer of feed production to an industrial basis. It is possible to increase the production of high-quality feeds through the introduction of high-yielding varieties, the use of new resource-saving cultivation and harvesting technologies, the optimal organization of cultivation production processes, and increasing the efficiency of the use of technical means. Of all the harvested types of feeds, alfalfa has the best effect on increasing milks yield and meat gains. The green mass of alfalfa is well-eaten by all farm animals. For example, when feeding cattle, its utilization rate is 92.6%. In terms of protein richness, alfalfa hay surpasses many other feeds, so 100 kg of alfalfa hay contains 11.6 kg of digestible protein, 1.77 kg of calcium, 0.22 kg of phosphorus, and 4.5 g of carotene. In addition, in the conditions of rice crop rotation, according to its biological characteristics, alfalfa (Medicago sativa L.) is considered indispensable in agrotechnical and reclamation relations, especially in saline soils. The economic value of alfalfa lies in its wide ecological plasticity, the ability to grow back quickly after mowing, and high productivity.

Drip irrigation systems are becoming more and more mature and are present extensively applied to increase crop yield and water use efficiency in Xinjiang, northwest China. To investigate the effects of irrigation quota on maize growth, the grain yield, and the irrigation water use efficiency (IWUE), a field experiment with four irrigation quotas (T1 4200m3·hm-2, T2 4800m3·hm-2, T3 5400m3·hm-2 and T4 6000m3·hm-2.) were conducted from 2013 to 2021 in Xinjiang China. The re-sults showed significant changes in maize growth, yield, and irrigation water use efficiency in response to different irrigation quotas. The plant height, leaf area index, SPAD, biomass, yield and harvest index of maize at different irrigation quotas all showed a “single peak curve”, and its change was closely related to the irrigation level. The growth index, dry matter accumulation, yield and irrigation water use efficiency with T3 were the highest. The dry matter transfer effi-ciency, contribution of dry matter translocation to grain and the harvest index with T3 showed significant increase of 13.86%, 26.06%, 29.93% and 7.62% compared to T1, respectively. In com-parison to T1, T2 and T4, the yield of T3 increased by 32.17%, 13.54% and 11.27% respectively, and the irrigation water use efficiency (IWUE) increased by 2.80%, 0.93% and 23.63% respectively. The significant correlations established between the maize yield and irrigation quotas could be sim-ulated by kuznets-style relation. The maize yield was negative correlated with irrigation quotas, When the irrigation quota (x) was 5376.73m3·hm-2, the maize yield (y) was 15841.00m3·hm-2. These results demonstrate that the optimized irrigation quota (5400m3·hm-2 treatment) can effectively improve the growth, yield and irrigation water use efficiency of drip irrigation maize in North-west China. In the meanwhile, it can provide theoretical reference and data support for the op-timal irrigation amount of drip irrigation maize in Northwest Xinjiang.

This research was specifically aimed at assessing the influence of sulfur in triple-super phosphate (TSP) on wheat yield. From the results, wheat showed response to sulfur (S) from gypsum (in 67%); and nitrogen (N) from urea in about 100% (of 24 sites). Based on this N was found to be the most limiting element to wheat production followed by sulfur, and then by phosphorus. TSP is tested to contain agronomically up to 2-6% by weight of S. However, wheat didn’t show response to S impurity supplied in the form of TSP. Though, not statistically significant, it is observed that there have always been yield increments by certain percent due to S from TSP in 8 out of 10 target sites, which is depicted in the increasing trends of yield response curves. From this it is learnt that, the benefits of the accidental/incidental application of such high analysis fertilizers can be many-folds in the quality attributes of wheat, if the soils of such investigation at the same time would contain significant amount of organic matter (OM). Indeed, such analysis would be vital in varietal specific nutrient requirement studies in precision-farming and/or in categorizing soils into fertility gradients and fertilizer recommendation domains.

Rapid assessment of maize yields in smallholder farming system is important to understand its spatial and temporal variability and for timely agronomic decision-support. Imageries acquired with unmanned air vehicles (UAV) offer opportunity to assess agronomic variables at field scale, however, it is not clear if this can be translated into reliable yield assessment on smallholder farms where field conditions, maize genotypes, and management practices vary within short distances. In this study, we assessed the predictability of maize grain yield using UAV-derived vegetation indices (VI), with(out) biophysical variables, in smallholder farms. High-resolution images were acquired with UAV-borne multispectral sensor at 4 and 8 weeks after sowing (WAS) on 31 farmers’ managed fields (FMFs) and 12 nearby Nutrient Omission Trials (NOT), all distributed across 5 locations within the core maize region of Nigeria. The NOTs included non-fertilized and fertilized plots (with and without micronutrients), sown with open-pollinated or hybrid maize genotypes. Acquired multispectral images were post-processed into several three (s) vegetation indices (VIs), normalized difference vegetation index (NDVI), normalized difference red-edge (NDRE), green-normalized difference vegetation index (GNDVI). Biophysical variables, plant height (Ht) and percent canopy cover (CC), were measured with the georeferenced plot locations recorded. In the NOTs, the nutrient status, not genotype, influenced the grain yield variability and outcome. The maximum grain yield observed in NOTs was 9.3 tha^-1, compared to 5.4 tha^-1 in FMF. Without accounting for between- and within-field variations, there was no relationship between UAV-derived VIs and grain yield at 4WAS (r<0.02, P>0.1), but significant correlations were observed at 8WAS (r≤0.3; p<0.001). Ht was positively correlated with grain yield at 4WAS (r=0.5, R²=0.25, p<0.001), and more strongly at 8WAS (r=0.7, R²=0.55, p<0.001), while relationship between CC and yield was only significant at 8WAS. By accounting for within- and between-field variations in NOTs and FMF (separately) through linear mixed-effects modeling, predictability of grain yield from UAV-derived VIs was generally (R²≤0.24), however, the inclusion of ground-measured biophysical variable (mainly Ht) improved the explained yield variability (R² ≥0.62, RMSEP≤0.35) in NOTs but not in FMF. We conclude that yield prediction with UAV-acquired imageries (before harvest) is more reliable under controlled experimental conditions (NOTs), than in actual farmer-managed fields where various confounding agronomic factors can amplify noise-signal within the vegetation canopy.

Owing to the reduction of rupture instability and the avoidance of wrinkle defect, hydrodynamic deep drawing (HDD) process is gradually becoming attractive for fabricating lightweight and complicated products. Meanwhile, since metallic material presents anisotropic deformation behavior, it is necessary to select an appropriate constitutive model for the prediction of plastic deformation behavior of applied material with high precision. In the present research, several anisotropic yield criteria namely, Hill’48, Yld2000-2d and BBC2005 are implemented to investigate the effect of yield functions on the prediction accuracy of the critical process window and deformation behavior for HDD process of 2024 and 5754 aluminum alloys. Material constants in the yield criteria are determined by applying uniaxial and equi-biaxial tension tests and optimizing an error-function by using the Levenberg-Marquardt algorithm. Furthermore, the process window diagram is computed utilizing the stress analytical model combined material properties with workpiece geometrical features. Numerical simulation results of predicted material anisotropic parameters, process window and HDD deformation for aluminum alloys are compared with the experimental data. Through the comparison of diverse yield criteria based on materials anisotropic coefficients, critical process window prediction, earing profile, and thickness distribution, it is revealed that the Yld2000-2d and the BBC2005 yield criteria can offer more precise models of material behavior in planar anisotropy properties for HDD process of 2024 and 5754 aluminum alloys.