Nutrient management of lowbush blueberry (Vaccinium angustifolium Ait.) depends on several yield-limiting features. Machine learning models can process such yield-impacting variables to predict berry yield. We investigated the effects of local variables on yields and nutrient management of lowbush blueberry. We collected 1504 observations from N-P-K fertilizer trials conducted in Quebec, Canada. Meteorological indices at various phenological stages showed the greatest impact on yield. High mean temperature at flower bud opening and after fruit maturation, and total precipitation at flowering showed positive effects. Low mean temperature and low total precipitation before bud opening, at flowering, and by fruit maturity, as well as number of freezing days (< -5ºC) before flower bud opening, showed negative effects. Soil fertility variables, leaf nutrient compositions and N-P-K fertilization showed smaller effects. Gaussian processes predicted berry yields from historical weather data, soil analysis, fertilizer dosage, and leaf nutrients with a root-mean-square-error of 1447 kg ha-1 on the testing data set. An in-house Markov chain algorithm optimized yields modelled with Gaussian processes from leaf nutrient composition, soil test value, and fertilizer dosage conditioned to specified historical weather features. We propose to use conditioned machine learning models to manage nutrients of lowbush blueberry at local scale.

Glyphosate-based herbicide products are the most widely used broad-spectrum herbicides in the world for post-emergent weed control. There are ever-increasing concerns that glyphosate, if not used judiciously, may cause adverse non-target impacts in agroecosystems. The purpose of this brief review is to present and discuss the state of knowledge with respect to its persistence in the environment, possible effects on crop health, and impacts on crop nutrition.

Examining the soil microbiome structure has a great significance in exploring the mechanism behind plant growth changes due to maize (Zea mays L.) and soybean (Glycine max Merr.) crop rotation. This study explored the effects of soil microbial community structure after soybean and maize crop rotation by designing nine treatments combining three crop rotations (continuous cropping maize or soybean; and maize after soybean) with three fertility treatments (organic compound fertilizer, chemical fertilizer, or without fertilizer). Soil was sampled to 30 cm depth the second year at approximately the middle of the growing season, and was analyzed for physical, chemical, and phospholipid fatty acid (PLFA) profiles. Bacteria was found to be the predominant component of soil microorganisms, which mainly contain the PLFAs i15:0, 16:1 ω 7c, 16:0, 10Me16:0, and 18:1 ω 7c. The concentration of soil gram-negative bacteria from the soybean and maize rotation was less than in soybean continuous cropping when organic fertilizer was applied to both. Crop rotation reduced the percentage of fungi in the soil, among which the effect of organic compound fertilizer application was significantly reduced 24%. The combined crop rotation with organic fertilizer can reduce maximum the percentage of fungi/bacteria. In addition, the content of soil aggregate and organic matter had great influence on gram-positive bacteria and actinomyces, and soil pH had a greater impact on other fungi.

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.

In the livestock industry, maintaining the health of animals is very important, and the use of technology has greatly helped this. One of the existing challenges has been that most of the available sensors and electronic processing devices are designed to fit the human body, and the use of these devices for livestock faces limitations due to the difference in the structure of the body and skin of animals and humans. Reliable solutions tailored for animal husbandry can be achieved by modifying the physical and software structure of existing devices. In this article, we have presented the current situation, by reviewing the research done and the existing technology in the field of animal husbandry. The aim is to obtain comprehensive parameters for monitoring livestock health by leveraging available information and exploring new methods based on the Internet of Things (IOT), Artificial Neural Networks (ANN), and Artificial Intelligence (AI). We take a proactive approach by utilizing available technologies based on sound-based diagnostic techniques. Initially, we propose utilizing piezoelectricity and amplifying received sound using a diaphragm attached to a collar. Subsequently, we discuss the results of relevant tests that can be conducted using the phonocardiography system. For the next phase of research and designing a more advanced livestock health monitoring system, we suggest employing an ultrasonic system to measure heart rate and blood pressure for the next phase of research and designing a more advanced livestock health monitoring system. This system, coupled with a piezoelectric system to make electric energy from the pulse of the veins, could be subcutaneously implanted for continuous monitoring

Disrupted nutrient recycling is a significant problem for Europe, while phosphorus and nitrogen are wasted instead of being used for plant nutrition. Mineral phosphate is critical raw material, which contains environmentally hazardous elements such as cadmium and uranium. Therefore, phosphorus recovery from agricultural by-product streams is critically important key priority. Phosphorus recovery from food grade animal bone by-products have been applied researched since 2002 with objective driven evolution progress towards specialized pyrolysis processing technology and animal bone char product (ABC) developments in economical industrial scale. Different animal bone by-products tested under different conditions at 400 kg/h throughput capacity in the continuously operated 3R zero emission autothermal carbonization system. The different material core treatment temperatures (between >300°C and <850°C) were combined with different residence times under industrial productive processing conditions. It has been industrial demonstrated that material core treatment temperature <850°C with 20 minutes residence time is necessary to achieve high quality ABC with useful agronomic value. The output ABC product having concentrated >30% phosphorus pentoxide (P2O5) and specific quality innovative fertilizer for agronomical efficient organic and low input farming applications as functional organic fertilizer, soil improver, growing medium and/or fertilizing product blend with high mineral phosphate fertiliser replacement value.

Timely crop yield forecasts at national level are substantial to support food policies, to assess agricultural production and to subsidize regions affected by food shortage. This study presents an operational crop yield forecasting system for Poland that employs freely available satellite and agro-meteorological products provided by the Copernicus programme. The crop yield predictors consist of: (1) vegetation condition indicators provided daily by Sentinel-3 OLCI (optical) and SLSTR (thermal) imagery, (2) a backward extension of Sentinel-3 data (before 2018) derived from cross-calibrated MODIS data, (3) air temperature, total precipitation, surface radiation, and soil moisture derived from ERA-5 climate reanalysis generated by the European Centre for Medium-Range Weather Forecasts. The crop yield forecasting algorithm is based on thermal time (growing degree days derived from ERA-5 data) to better follow the crop development stage. The recursive feature elimination is used to derive an optimal set of predictors for each administrative unit, which are ultimately employed by the Extreme Gradient Boosting regressor to forecast yields using official yield statistics as a reference. According to intensive leave-one-year-out cross validation for 2000–2019 period, the relative RMSE for NUTS-2 units are: 8% for winter wheat, and 13% for winter rapeseed and maize. Respectively, for the LAU units it equals 14% for winter wheat, 19% for winter rapeseed, and 27% for maize. The system is designed to be easily applicable in other regions and to be easily adaptable to cloud computing environments (such as DIAS or Amazon AWS), where data sets from the Copernicus programme are directly accessible.

Nano-nitrogen fertilizers (NNFs) have emerged as a promising technology in the field of agriculture, offering potential solutions to improve nutrient uptake efficiency, enhance crop productivity, and reduce environmental impacts. The NNFs showed superior characteristics and performance on crops and therefore, became a potential alternative to conventional nitrogen (N) fertilisers. These fertilizers enhance plant uptake while simultaneously reducing environmental losses. Additionally, their small particle size increases crop acclimation and decreases the application rate. With all these beneficial traits of NNFs, they potentially contribute to achieving Sustainable Development Goals (SDGs). This review article summarises the materials used in NNFs formulation, methods of preparing NNFs, and their crop responses. This review also highlights the limitations identified in the research studies and provides research recommendations for the future. Further, this review provides a critical assessment of the current state of NNFs and their prospects for revolutionizing modern agriculture to attain SDGs.

Climate change is a large and challenging collective action problem facing the world today. This seminar review impacts of climate change on r yield of major cereal crops. Literatures have indicated that climate change would likely have positive impact in the highland agro-ecology in the short run. However, in the long run climate change will have negative impact in all agro-ecology. Negative impacts will be high in low land agro-ecology. Failure to prepare for climate variability can seriously affect the livelihood of smallholder farmers. Ethiopia by enacting Climate-Resilient Green Economy strategy and National Adaptation Plan aims to minimize the impacts of CC. Despite the existing adaptation and mitigation strategies negative impacts of climate change on agriculture especially on cereal crop production is continued. Thus, both private and public investment on adaptation strategies should be expanded more. Studies regarding the impacts of climate change on labour productivity, labour market, its distributional (which section society mostly by climate change?) and why the existing adaptation strategies are not successful? are not well studied, as most literature are focused on impact of climate change on yield, its adaptation and mitigation strategies.

This study assessed the literature about the use of high tunnels (HTs) in agricultural systems in the United States since the 2009 launch of the Natural Resources Conservation Service (NRCS) High Tunnel Initiative. This NRCS program led to an increase in HT adoption nationwide. The literature searches were conducted using the Web of Science (WoS) database. The final sample was 133 peer-reviewed articles published between 2009 and February 2023. We used CiteSpace 6.2.R1 and Gephi 0.9.2 to conduct co-citation, co-author, co-institution, and clustering techniques. The findings showed that the peer-reviewed literature about HT use has increased since 2009, substantially rising between 2017 and 2021. Horticulture was the top subject category in the literature, and most articles were published in peer-reviewed journals of the American Society for Horticultural Science (i.e., HortTechnology and HortScience). The research field evolved from general HT practices, nutrient management, and plant pathology to focus on trials of specific crops and integrated pest management. The institutions with the most contributions to the HT literature were Kansas State University, the University of Florida, Michigan State University, Purdue University, and the University of Minnesota. The patterns of HT research revealed in this study offer a greater understanding of the current state of knowledge to inform the focus of future research.

To meet an ever global population's food demand, crop yields must be sustained and increased. Drought, which is getting harsher as a result of global warming, is largely impeding the agricultural productivity. Maize is widely used as food and animal feed in many regions of the world, but its yields are largely effected by drought and heat stress. Historical data on climate change predicts that drought and heat stress becoming major threat for maize cultivation in coming years, which will have huge impact on food security of the world especially in Africa and Asia. Thus there is an immense necessary to develop drought tolerant and climate resilient maize to feed the predicted population of the world. Availability and accessibility of crop genetic resources plays a huge role in development of drought-tolerant maize cultivars. A huge genetic resources of maize, including its landraces and crop wild relatives (CWR) have been reported naturally and many of them have stored in National and International gene banks globally. Conventional breeding methods have been tremendously increased maize yields, but these methods frequently fall short of achieving the demand for improved drought stress resistance. In this article, we have briefly discussed about impact of climate variability on crop production, maize yield losses due to drought, drought tolerance in maize landraces and CWR, and origin and evolution of Mexican landraces. This information may help in utilization of these potential resources in various pre-breeding programs.

Bacillus thuringiensis (Bt) is a spore-forming bacterium that produces insecticidal proteins and other virulence factors and is considered one of the most successful bioinsecticides available to control pests in agriculture. Bt strains have been reported as endophyte or rhizospheric bacteria, but little is known about the implications of this property of Bt in crop protection. Here, we review if Bt can establish as an endophyte/rhizobacterium and evaluate if Bt as an endophyte/rhizobacterium can simultaneously act against different phytopathogens (fungi, bacteria, insects and viruses) plus promote plant growth. The implications of the proposed review will broaden our understanding of Bt as a versatile entomopathogen by exhibiting differential behavior depending on context.

The desert locust remains a major threat to global food security. Control operations are a crucial tool to manage crisis; this research investigated the nature of control operations conducted between 2019-2021. Historical data on desert locust and control operations were obtained from the survey reports at the FAO Locust Hub and analysed with respect to survey reports, land cover types, cropland/rangeland extent and crop productivity data. We found that 16.1% of the grid cells with locust presence and 14.9% of the grid cells with control operations had a proportion of rangeland higher than 0.75; while 13.3% of the grid cells with locust presence and 13.2% of the grid cells with control operations had a proportion of croplands higher than 0.75, highlighting that locust presence and control operations were reported in both rangeland and cropland. Control operations continue to be used both to reduce overall locust numbers and to protect crops. Furthermore, through identifying which crops were most at risk, our analyses indicate that wheat production was under the highest strain during periods of increased locust infestations.

The genus Flavivirus includes 53 members and poses a big threat to human health among worldwide. Diseases caused by flavivirus infections can be broadly classified into hemorrhagic diseases (Dengue, Yellow fever, etc) and neurological diseases (West Nile disease, Zika disease, etc). Many flaviviruses still lack specific treatments and effective vaccines. In this context, it becomes particularly important to thoroughly characterize the pathogenesis of flavivirus infection and develop animal models. Therefore, animal models that can accurately simulate human diseases are essential for evaluating the effectiveness of therapeutic drugs and preventive vaccines. In this paper, we provide a comprehensive review of the currently available animal models that support flavivirus infection and exhibit clinical manifestations related to flavivirus infection. Additionally, we discuss the strengths and limitations of each animal model, aiming to enhance researchers understanding of the use of animal models in flavivirus research. This insight is intended to facilitate further studies into the pathogenesis of flavivirus, as well as the development of antiviral agents and vaccines.

Orthobunyaviruses (order Bunyavirales, family Peribunyaviridae) in the Simbu serogroup have been responsible for widespread epidemics of congenital disease in ruminants. Australia has a national program to monitor arboviruses of veterinary importance. While monitoring for Akabane virus, a novel orthobunyavirus was detected. To inform the priority that should be given to this detection, a scoping review was undertaken to 1) Characterise the associated disease presentations and establish which of the Simbu group viruses are of veterinary importance; 2) Examine the diagnostic assays that have undergone development and validation for this group of viruses, and 3) Describe the methods used to monitor the distribution of these viruses. Two search strategies identified 224 peer-reviewed publications for 33 viruses in the serogroup. Viruses in this group may cause severe animal health impacts, but only those phylogenetically arranged in clade B are associated with animal disease. Six viruses (Akabane, Schmallenberg, Aino, Shuni, Peaton, and Shamonda) were associated with congenital malformations, neurological signs, and reproductive disease. Diagnostic test interpretation is complicated by cross-reactivity, the timing of foetal immunocompetence and sample type. Serological testing in surveys remains a mainstay of the methods used to monitor the distribution of SGVs. Due to significant differences in survey designs, only broad mean seroprevalence estimates could be provided. Further research is required to characterise the SGV detected and determine the disease risk posed by novel orthobunyaviruses and how they could challenge current diagnostic and surveillance capabilities.

Shrews (Soricidae) are common small wild mammals with a significant overlap in their habitats with humans and domestic animals. Currently, viruses from 24 families have been identified in shrews, including Adenoviridae, Arenaviridae, Arteriviridae, Astroviridae, Bornaviridae, Caliciviridae, Circoviridae, Coronaviridae, Filoviridae, Flaviviridae, Hantaviridae, Hepadnaviridae, Hepeviridae, Nairoviridae, Orthoherpesviridae, Paramyxoviridae, Parvoviridae, Phenuiviridae, Picornaviridae, Polyomaviridae, Poxviridae, Rhabdoviridae, Sedoreoviridae, and Spinareoviridae, which pose potential threats to humans and domestic animals. This review compiled fundamental information about shrews and provided a comprehensive summary of the viruses that have been detected in shrews, with the aim to facilitating a deeper understanding of shrews and the diversity and risks of their viruses for researchers and the general public.

In China, 65 types of venomous snakes exist, with the Chinese Cobra Naja atra being prominent and a major cause of snakebites in humans. Furthermore, N. atra is a protected animal in some areas, as it has been listed as vulnerable by the International Union for Conservation of Nature. Recently, due to the medical value of snake venoms, venomics has experienced growing research interest. In particular, genomic resources are crucial for understanding the molecular mechanisms of venom production. Here, we report a highly continuous genome assembly of N. atra, based on a snake sample from Huangshan, Anhui, China. The size of this genome is 1.67 Gb, while its repeat content constitutes 37.8% of the genome. A total of 26,432 functional genes were annotated. This data provides an essential resource for studying venom production in N. atra. It may also provide guidance for the protection of this species.

The king ratsnake (Elaphe carinata) of the genus Elaphe is a common large non-venomous snake that is widely distributed in Southeast and East Asia, and is an economically important farmed snake species. As a non-venomous snake, the king snake that is predatory on venomous snakes such as cobras and pit vipers. The immune mechanisms of which has been unclear. Despite their economic and research importance, genomic resources which will benefit studies in toxicology, phylogeography and immunogenetics are lacking. In this study, we use single-tube long fragment read (stLFR) sequencing to display the first complete genome of a King ratsnake from Huangshan City, Anhui province in China. The genome size is 1.56GB with a scaffold N50 of 6.53M, the total length of the genome is approximately 621Mb, and the repeat content is 38.90%. Additionally, we predicted 22,339 protein-coding genes, of which 22,065 had functional annotations. Our genome is a potentially useful addition to those currently available for snakes.

The severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), etiological agent of the novel coronavirus disease 2019 (COVID-19), has spread since December 2019, resulting in massive health and economic crisis worldwide. While efforts to stop the pandemic are crucial, collecting epidemiological data to help manage current and future pandemics will be important. In addition to humans, serological and molecular based studies have demonstrated SARS CoV-2 exposure in several wild, domestic and farmed animals. For examples Shriner and the team showed serologically an exposure of 40% to the white deer living in close proximity to urban centers. Additional reports have also emerged of susceptibility of animal’s species like cats, ferrets, raccoon dogs, cynomolgus macaques, rhesus macaques, white-tailed deer, rabbits, Egyptian fruit bats, and Syrian hamsters to SARS-CoV-2 infection.. It’s worth emphasizing that these reports are based on experimental data mostly derived from Europe, USA, South America and parts of Asia. In limited instances natural infections of SARS-CoV-2 have been reported in pet dogs, cats, tigers, lions, snow leopards, pumas, gorillas at zoos and farmed mink and ferrets. The presence of the virus in animal species and an understanding of whether these are natural or recent human to animal transmissions is important. It’s possible that such transmission could passage the virus or subject the virus to a different immunological pressure thereby helping with the development of viral variants in addition to being a host for future reservoirs of the virus. In Kenya SARS-CoV-2 was first detected on March 12th 2020 from imported human cases of persons who had travelled from the United States. This was followed by detection of imported cases majorly from China, Sweden and United Kingdom. Later infections were confirmed in Nairobi and Mombasa suggesting further cases of disease importations through the major ports of entry. However, no comparable data on animal exposure have hitherto been generated in Kenya. To address this key concern, we focused on three objectives; 1) development of a robust antibody ELISA based on crude SARS-CoV-2 lysate. 2) SARS-CoV-2 serology of domestic animals in Kenya. 3) Corroboration of the crude lysate based seroprevalence data and a commercial ELISA kit based on the Spike receptor binding domain (RBD) antigen. Our sample set included camel sera (both pre- & post outbreak sera), as well as sera from cats and dogs collected at the peak of the pandemic. Our results using the ELISA based on crude SARS-CoV-2 lysate indicated SARS-CoV-2 antibodies in camels (71%, N=145), cats 11% (N=16) and dogs (81%, N=36) with varying titer levels. These findings were comparable to those obtained using the commercial ELISA kit based on the spike RBD antigens. In summary, the data warrants two key conclusions: (i) we have demonstrated that the crude lysate ELISA allows for SARS-CoV-2 antibody detection, and given its potential to offer robust detection could be applied for initial mass screening (ii) although the current study cannot disentangle the relative contributions of antigenic cross-reactivity, pre-pandemic exposure to SARS-CoV-2 or human-animal transmission, it nonetheless demonstrates for the first time the prevalence of SARS-CoV-2 like antibodies in domestic and wild animals in Kenya. Our findings set the scene for further research into the prevalence of SARS-CoV-2 in domestic and wild animals to understand their potential epidemiological implications.

Melanins are phenolic biopolymers synthesised by most of the living organism mainly for photoprotection or surviving in harsh conditions. Melanin is localised in different areas or complexed with different other biomolecules when observed from animals to microbes. This makes the melanin extraction procedure different in animal, plant and microbial tissues. Basically, the alkali-acid extraction is used in most protocols of which slight variations are there depending on the tissue used. This review will try to compile melanin extraction procedures from different cells and tissues ranging from animals to bacteria.

Background: Previously, our laboratory has provided evidence that pre-administration of the antioxidant, lipoic acid covalently bonded to various naturally occurring antioxidants, enhanced neuroprotective capacity compared to the administration of lipoic acid on its own. The naturally occurring compound scopoletin, a coumarin derivative, has been shown in various in vitro studies to have both antioxidant and anti-inflammatory mechanism of actions. To date, the effect of scopoletin on neuronal cell death in an in vivo model of ischemia or ischemia-reperfusion has not been investigated. Therefore, the present investigation was designed to determine if scopoletin on its own, or a co-drug consisting of lipoic acid and scopoletin covalent bond, named UPEI-400, would be capable of demonstrating a similar neuroprotective efficacy. Methods: Using a rodent model of stroke in male rats (anesthetized with Inactin®; 100 mg/kg, iv), the middle cerebral artery was permanently occluded for 6 hours (pMCAO), or in separate animals, occluded for 30 min followed by 5.5 hrs of reperfusion (ischemia/reperfusion; I/R). Results: Pre-administration of either scopoletin or UPEI-400 significantly decreased infarct volume in the I/R model (p<0.05), but not in the pMCAO model of stroke. However, UPEI-400 was ~1000 times more potent as compared to scopoletin on its own. The optimal dose of UPEI-400 was then injected during the occlusion and at several time points during reperfusion and significant neuroprotection was observed for up to 150 mins following the start of reperfusion (p<0.05). Conclusion: The data suggest that synthetic combination of scopoletin with lipoic acid (UPEI-400) is a more effective neuroprotectant that either compound on their own. Also, since UPEI-400 was only effective in a model of I/R, it is possible that it may act to enhance neuronal antioxidant capacity and/or upregulate anti-inflammatory pathways to prevent the neuronal cell death.

In the wake of rapid advancements in artificial intelligence (AI) and sensor technologies, a new horizon of possibilities has emerged across diverse sectors. Livestock farming, a domain often sidelined in conventional AI discussions, stands at the cusp of this transformative wave. This paper delves into the profound potential of AI and sensor innovations in reshaping animal welfare in livestock farming, with a pronounced emphasis on a human-centric paradigm. Central to our discourse is the symbiotic interplay between cutting-edge technology and human expertise. While AI and sensor mechanisms offer real-time, comprehensive, and objective insights into animal welfare, it's the farmer's intrinsic knowledge of their livestock and environment that should steer these technological strides. We champion the notion of technology as an enhancer of farmers' innate capabilities, not a substitute. Our manuscript sheds light on: Objective Animal Welfare Indicators: An exhaustive exploration of health, behavioral, and physiological metrics, underscoring AI's prowess in delivering precise, timely, and objective evaluations. Farmer-Centric Approach: A focus on the pivotal role of farmers in the adept adoption and judicious utilization of AI and sensor technologies, coupled with discussions on crafting intuitive, pragmatic, and cost-effective solutions tailored to farmers' distinct needs. Ethical and Social Implications: A discerning scrutiny of the digital metamorphosis in farming, encompassing facets like animal privacy, data safeguarding, responsible AI deployment, and potential technological access disparities. Future Pathways: Advocacy for principled technology design, unambiguous responsible use guidelines, and fair technology access, all echoing the fundamental principles of human-centric computing and analytics. In essence, our paper furnishes pioneering insights at the crossroads of farming, animal welfare, technology, and ethics. It presents a rejuvenated perspective, bridging the chasm between technological advancements and their human beneficiaries, resonating seamlessly with the ethos of the Human-Centric Intelligent Systems journal. This comprehensive analysis thus marks a significant stride in the burgeoning domain of human-centric intelligent systems, especially within the digital livestock farming landscape, fostering a harmonious coexistence of technology, animals, and humans.

Our wellbeing is greatly influenced by our childhood and adolescence, and the relationships that we form during those phases of our development. The human-dog bond started thousands of years ago. The higher prevalence of dog ownership around the world, especially in households including children along with the growing number of people studying dogs most likely explain the growing literature focusing on child-dog interactions. We review the potential effects of child-dog interactions on the physical, mental, and social wellbeing of both species. A scoping search of the SCOPUS database found several hundred documents meeting selection criteria. It allowed us to define the numerous ways in which children and dogs can interact, be it neutral (e.g., sharing a common area), positive (e.g., petting), or negative (e.g., biting). Then, we found evidence for an association between interacting with dogs during childhood and an array of health and mental benefits like stress relief and the development of empathy. Walking a dog and playing with one are perfect physical activity opportunities. Additionally, interacting with a dog can help lower stress and may have a role in the development of empathy. Nonetheless, a number of detrimental outcomes have also been identified in both humans and dogs. Children are the most at-risk population regarding dog bites and dog-borne zoonoses, which may lead to a subsequent fear of dogs or even death. Moreover, pet bereavement is generally inevitable when living with a canine companion and should not be trivialized. In terms of dogs, children sometimes take part in caretaking behaviors toward them which include going on walks. They are opportunities for dogs to relieve themselves outside, but also to exercise and socialize. In contrast, a lack of physical activity can lead to the onset of obesity. Dogs may present greater levels of stress when in the presence of children. Finally, the welfare of assistance, therapy, and free-roaming dogs remains underexplored. Overall, the study of the effects, positive as well as negative, on both species still requires further development. We call for more longitudinal studies and hope for cross-cultural research in the future in order to better understand the impact child-dog interactions might have.

Porcine reproductive and respiratory syndrome virus (PRRSV) infections cause significant economic losses to swine producers every year. Aerosols containing infectious PRRSV are an important route of transmission, and proper treatment of air could mitigate the airborne spread of the virus within and between barns. Previous bioaerosol studies focused on the microbiology of PRRSV aerosols; thus, the current study addressed the engineering aspects of virus aerosolization and collection. Specific objectives were to (1) build and test a virus aerosolization system, (2) achieve a uniform and repeatable aerosol generation and collection throughout all replicates, (3) identify and minimize sources of variation, (4) verify that the collection system (impingers) performed similarly. The system for virus aerosolization was built and tested (Obj. 1). The uniform airflow distribution was confirmed using a physical tracer (<12% relative standard deviation) for all treatments and sound engineering control of flow rates (Obj. 2). Theoretical uncertainty analyses and mass balance calculations showed <3% loss of air mass flow rate between the inlet and outlet (Obj. 3). A comparison of TCID₅₀ values among impinger fluids showed no statistical difference between any two of the three trials (p-value = 0.148, 0.357, 0.846) (Obj. 4). These results showed that the readiness of the system for research on virus aerosolization and treatment (e.g., by ultraviolet light), as well as its potential use for research on other types of airborne pathogens and their mitigation on a laboratory scale.

High-density olive groves, despite their interesting production potential, have several limitations, also due to the high fruit load and the irrigation requirements.The study aimed to evaluate the effects of fruit load and deficit irrigation on oil yield and fruit quality, and on olive chemical composition in a high-density olive grove (cv Sikitita). Our main hypothesis was that the primary metabolism, as influenced by crop load and stress, could modify the accumulation of different phenolic classes.Different fruit loads were generated through flower thinning (66%, 50%, 33%, 0%) and two deficit irrigation treatments (-60%, -75%) were compared to the well-watered control (920 m3/ha).Thinning treatments had a limited effect on oil yield, on the other hand, deficit irrigation caused considerably less oil accumulation in the fruit on all sampling dates.Thinning 66% and deficit irrigation 75% were considered with the control for untargeted metabolomic analysis, considering three sampling dates. 233 different phenolic compounds were annotated. Multivariate HCA results indicated the impact of harvest time on the phenolic profile of olive fruits, yielding two separate clusters grouping t1 and t2 together and apart from t3. Regarding agronomic techniques, they played a differential role in the phenolic profile (supervised OPLS – DA). Fruit load mostly affected flavonoid glycosides. In contrast, the phenolic response to deficit irrigation is more heterogeneous, with phenolic acids (35%), flavonoids (25%), LMW, and other phenols (25%).

Genetic engineering in the field for designing crop improvement has become an essential element in responding to the increasing need for food safety, environmental sustainability, and climate-resilient crops. The latest molecular technology is used by many breeders today to achieve remarkable results. Fast genome editing is currently being seen in a variety of organisms, including plants, because to the high specificity, high effectiveness, and low production cost of CRISPR/Cas [Clustered regulatory interspaced short palindromic repeat (CRISPR)-associated protein (Cas)] technology. Its applications in developing higher-yielding, nutrition rich, disease resistance, stress-tolerant crops fruits, and vegetables. Therefore, this technology has the potential to revolutionize agriculture and contribute to global food security. The Cas protein provides the enzymatic machinery necessary for the acquisition of new cells that target invasion elements. Cas proteins such as Cas9, Cas12, Cas13, and Cas14, among others, have distinct architectures and have been used to create new genetic tools that improve features that are important for agriculture. The versatility of Cas has accelerated genomic analysis and facilitated the use of CRISPR/Cas to manipulate and alter nucleic acid sequences in cells of different organisms. This review provides the evolution of CRISPR technology exploring its mechanisms and contrasting it with traditional breeding and transgenic approaches to improve different stress tolerance. We will also discuss the CRISPR/Cas system and explore the workings of the three Cas proteins that are currently known to exist: Cas12, Cas13, and Cas14. The edited crops by this technology do not have foreign DNA inserted into their genome, therefore, they are considered as non-transgenic by the regulatory bodies in most countries.

Multi-cropping is becoming an increasingly popular approach in agriculture to tackle major and complex agroecosystem problems such as biodiversity and soil fertility losses, erosion and degradation, increased greenhouse gas emissions, etc. Comprehensive assessment of the impact of multi-cropping intensity on the agroecosystem is a new and still under-researched approach that provides a better understanding of the impact of the individual indicators studied on the overall functioning of the biodiversed agroecosystems. Data from a stationary field experiment with multi-cropping at the Vytautas Magnus University, Experimental Station between 2020 and 2022 were used to achieve this objective. The study included maize, hemp and faba bean as single, binary, and ternary crops. A complex assessment approach (CEI value) was used to determine the impact of these diversified crops on the agroecosystem, the interrelationships between the main indicators and the strength of their effects. It was found that the most positive effect on agroecosystem had ternary maize-hemp-faba bean crop. The effectiveness of other crops was from 2 to 35% less. The lowest one was calculated for the maize-faba bean crop.

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

The use of biostimulants consisting of plant growth promoting rhizobacteria (PGPR) is rapidly expanding in horticulture in recent years. In the current study, a novel mix of six Bacillus sp. strains was tested as a PGPR biostimulant in two experiments with zucchini squash (Cucurbita pepo L.) cultivated in the greenhouse soil and in an open field, respectively. In both experiments, seeds of the local landrace ‘Kompokolokytho’ and the commercial hybrid ‘ARO-800’ were either inoculated or non-inoculated with the PGPR biostimulant. The application of the six Bacillus sp. strains increased both the vegetative growth and the yield of zucchini squash, and these effects were associated with significantly higher shoot phosphorus levels in both experiments and both genotypes. Furthermore, at the end of the cultivation, the colony forming units of Bacillus sp. were appreciably higher in plants originating from inoculated compared to non-inoculated seeds, indicating that the tested mix of Bacillus sp can be successfully applied through seed inoculation. ‘ARO-800’ produced more vegetative and fruit biomass than ‘kompokolokytho’ under greenhouse cropping conditions, while in the open-field crop both genotypes performed equally, presumably because the local landrace is traditionally grown in open fields, and thus it is not well adapted to greenhouse cropping.

Leaf area estimation is a critical component in the study of plant growth and productivity within agricultural systems. This research introduces the LeafArea package, a specialized tool designed to calculate the leaf area of six distinct Andean fruit species: S. quitoense, S. betaceum, P. peruviana, R. fruticosus, P. ligularis and P. edulis. Leveraging response variables such as species type, leaf length and width, the package employs advanced machine learning algorithms to estimate leaf area accurately. The primary focus of the study is to identify the most effective model for describing the relationship between leaf width, length, and area for each plant species. Currently, the LeafArea package utilizes four different machine learning algorithms, namely generalized linear model (GLM), generalized linear mixed model (GLMM), Random Forest and XGBoost. Among these, XGBoost stands out as a top-performing algorithm, exhibiting exceptional predictive accuracy. The evaluation metrics employed in the program provide valuable insights for researchers, aiding in informed decision-making. Specifically, XGBoost demonstrates significantly lower prediction errors and approaches a near-perfect R2 value, emphasizing its potential to enhance predictive accuracy. These results underscore the efficacy of machine learning techniques, as a compelling choice for researchers seeking precise and robust predictions in leaf area estimation. The LeafArea package thus represents a valuable tool for advancing our understanding of plant growth dynamics, resource allocation, and overall productivity within agricultural ecosystems.

Studies on the domestication, genetic differentiation, and crop evolution of foxtail millet are re-viewed. Several genetic studies were carried out to elucidate the genetic relationships among foxtail millet accessions originating mainly from Eurasia, based on intraspecific hybrid pollen semi-sterility, isozymes, DNA markers, and single-nucleotide polymorphisms. Most studies suggest that China is the center of diversity of foxtail millet, and landraces were categorized into geographical groups. Furthermore, the evolution of genes was reviewed (i.e., the Waxy gene conferring amylose content in the endosperm, the Si7PPO gene controlling polyphenol oxidase, the HD1 and SiPRR37 genes controlling heading time, the Sh1 and SvLes1 genes involved in grain shattering, and the C gene controlling leaf sheath pigmentation), and the variation and distribu-tion of these genes suggested complex patterns of evolution under human and/or natural selec-tion.

Screening of pollen traits in diploid wild potatoes (Solanum sect. Petota, Solanaceae) is desirable to develop heat-tolerant potato (S. tuberosum) cultivars. To accomplish this goal requires exploring potato genetic resources that are conserved in genebanks. The goal of this study was to assess pollen viability and 2n pollen production of the diploid potato wild relatives under heat stress condition. We assessed pollen viability and size of nine potato accessions conserved at the Embrapa Potato Gene Bank, including S. chacoense (BRA 00167447-2, BRA 00167017-3, BRA 00167023-1, BRA 00167028-0), S. commersonii (BRA00167007-4, BRA00167420-9, BRA00183760-8), and S. malmeanum (BRA 00183755-8), along with a control accession from the cultivated species S. tuberosum (BRA 00167251-8). The plant accessions were cultivated in different growth chambers, simulating both control temperature (ranging from 14 to 27°C) and supraoptimal temperature conditions (ranging from 24 to 34°C). At heat stress, the accessions BRA 00167251-8 did not bloom, and BRA 00167023-1 did not produce pollen. The remaining accessions did not exhibit a significant reduction in pollen viability as the temperature increased. Pollen viability at the control temperature had the lowest value in BRA-00167420-9 (S. commersonii) with 68.5% and the highest in BRA 00183755-8 (S. malmeanum) with 100%. At the supraoptimal temperature the lowest value was in BRA 00167420-9 (S. commersonii) with 54.5% and the highest in BRA 00183755-8 (S. malmeanum). The average of pollen size was 20 μm in all wild potato genotypes, and the increase of temperature did not lead to 2n pollen production. Estimated Genotypic Coefficient of Variation (GCV) was lower than Phenotypic Coefficient of Variation (PCV) for pollen viability. The observed heritability values ranged from 58.82% in BRA00167007-4 to 91.32% in BRA 00183755-8. Our results highlight the genetic variability available in wild potato germplasm concerning pollen viability under heat stress. Furthermore, these first insights offer valuable guidance for ongoing and future endeavors in diploid potato breeding.

Japanese plums form part of a multi-billion rand deciduous fruit industry in South Africa. Despite this, there is a paucity of knowledge on the seasonal water requirements of plum orchards. In a time of changing climatic conditions and diminishing water resources, this gap in literature poses an imminent threat to the long-term sustainability and global competitiveness of the South African plum industry. Therefore, this paper aimed to provide a review of the available literature on the crop water requirements of full-bearing well-irrigated Japanese plum orchards for improved agricultural water management. Full-year water requirements for well-watered full-bearing Japanese orchards ranged between 921 and 1 211 mm a-1 with a mean value of 1 084 ±140 mm a-1. Canopy growth and pruning appeared to be the most common causes of differences in water requirement estimates. Growing season length also plays a role with late-season maturing orchards having higher water requirements than their early and mid-maturing counterparts. The knowledge review provided benchmark figures for the annual water requirements of Japanese plums. However further research is required to determine the water requirement of plums from planting to full-bearing age and the response of plum trees to water stress, in a South African context.

Paleogenomics focuses on the recovery, manipulation, and analysis of ancient DNA (aDNA) from historical or long-dead organisms to reconstruct and analyze their genomes. The aDNA is commonly obtained from remains found in paleontological and archaeological sites, conserved in museums and in other archival collections. Herbarium collections represent a great source of phenotypic and genotypic information, and their exploitation allowed to infer and to clarify previously unsolved taxonomic and systematic relationships. Moreover, Herbarium specimens offered a new source to study phenological traits in plants and to disentangle biogeography and evolutionary scenarios of species. More recently, advances in the molecular technologies went in parallel with the decreasing costs of the next-generation sequencing (NGS) approaches, that paved the way to the utilization of aDNA for whole-genome studies. Although many studies have been carried out combining modern analytic techniques and Herbarium specimens, this research field is still relatively unexplored, due to the need of improving strategies for aDNA manipulation and exploitation. The higher susceptibility of aDNA to degradation and contamination during the Herbarium conservation and manipulation, and the occurrence of biochemical post-mortem damages, can result in the more challenging reconstruction of the original DNA sequence. Here, we review the methodological approaches that have been developed for the exploitation of historical Herbarium plant materials, such as the best practices for aDNA extraction, amplification and genotyping. We also focus on some strategies to overcome the main problems related to the utilization of Herbarium specimens for their exploitation in plant evolutionary studies.

The creation of crop-type maps from satellite data has proven challenging, often impeded by a lack of accurate in-situ data. This paper aims to demonstrate a method for crop-type (ie. Maize, Wheat and Other) recognition based on Convolutional Neural Networks using a bottom-up approach. We trained the model with a highly accurate dataset of crowdsourced labelled street-level imagery. Classification results achieved an AUC of 0.87 for wheat, 0.85 for maize and 0.73 for other. Given that wheat and maize are the two most common food crops globally, combined with an ever-increasing amount of available street-level imagery, this approach could help address the need for improved crop-type monitoring globally. Challenges remain in addressing the noisy aspect of street-level imagery (ie. buildings, hedgerows, automobiles, etc.), where a variety of different objects tend to restrict the view and confound the algorithms

The concept of omics-based technological approaches has promoted translational research by integrating knowledge from diverse areas to understand their dynamics by exploring the molecular mechanisms underlying various processes paving the way for further improvements in the crops quality by providing sound knowledge on controlling plant diseases. This area is not profoundly investigated a decade back and hence this knowledge has become exceedingly important in modern times as it has got potential for being utilized in crop improvement programs. In this review, the contributions of different omics technologies including genomics, transcriptomics, proteomics, and metabolomics in understanding and materializing the ways involved in the plant pathogen interaction (PPI) is discussed. Furthermore, opportunities, challenges, and perspectives of omics linked to signaling mechanisms have also been highlighted that are significantly linked to plant-microbe interactions.

The rising global population amidst the growing concerns of climate change will have a dire consequence on global food security and socio-economic activities. Wheat is one of the most important staple foods consumed by more than four billion people in the world, but climate change impacts account for a decline of 5.5% in wheat yield and predictions indicate that the production could further dwindle by nearly 30% in 2050, due to trends in temperature, precipitation, and carbon dioxide. An effective annual crop estimate is necessary not only to inform government the status of national food security, but also is used to determine the benchmark on which agricultural commodities are priced in the market. Thus, annual crop monitoring and yield estimate is paramount to determine the amount of wheat imports required to make up for the shortfalls in the national wheat production in South Africa, which has been a net importer of wheat since 1998. A joint project between South Africa and Poland investigated satellite based-crop growth monitoring using Sentinel 2 and determined the most distinguishable crop phenology for an accurate winter wheat classification during the growing season from August – December with Random Forest (RF) algorithm. The winter wheat crop was more accurately identified during the crop ‘heading’ stage in October yielding the highest user’s (75.56%) and producer’s (92.52%) accuracies, despite the relatively lower overall accuracy (78.14%) compared to that of December with OA of 83.58% obtained during the maturity stage. This study, therefore, confirms the suitability of sentinel 2 for an effective phenology-based winter wheat crop classification during the heading stage, reducing the ambiguity of spectral confusion created with surrounding grass and maize crops.

The agricultural sector is undergoing a revolution that requires sustainable solutions to the challenges that arise from traditional farming methods. To address these challenges, technical and sustainable support is needed to develop projects that improve crop performance. This study focuses on the onion crop and the challenges presented throughout its phenological cycle. Aerial monitoring using unmanned aerial vehicles (UAV) and digital image processing were used to identify patterns in the onion crop, including humid areas, weed growth, vegetation deficits, and decreased harvest performance. An algorithm was developed to identify the patterns that most affected crop growth, as the average local production reported was 40.166 ton/ha, but only 25.00 ton/ha was reached due to blight caused by constant humidity and limited sunlight. This resulted in the death of leaves and poor development of bulbs, with 50% of the production being of medium size. It is estimated that approximately 20% of the production was lost due to blight and unfavorable weather conditions.

China is a large agricultural country that produces a large amount of crop straw every year. Thus, the development of cost-effective and economic application of invasive plants is warranted. Biochars derived from crop straw has been proven to be promising for adsorbent materials. However, less studies have focused on biochar derived from different types of crop straw as adsorbent under the same conditions to compare their adsorption performance. Here, we characterized the five biochars in the same system (600 ℃). In results, GBC has higher ash content, pH, CEC, specific surface area, mineral composition and oxygen-containing functional groups. The adsorption kinetics can be explained adequately by pseudo-second-order model and Langmuir model, indicating that the adsorption behavior of the biochar is both physical adsorption and chemical adsorption, the adsorption process includes complexation reaction, cationic π bond, ion precipitation and electrostatic adsorption. In conclusion, GBC exhibited higher metal equilibrium adsorption capacities (125 mg·g-1 for Pb2+, 29 mg·g-1 for Cd2+). The solution pH, biochar dosing, pyrolysis temperature and the properties of these heavy metals were responsible for adsorption capacity, thus showing stronger affinity and better adsorption effect. Our results are important for the selection and utilization of plant-based biochar for different heavy metals.

The Roman economy of the Iberian Peninsula has habitually been characterised in terms of prestige goods and economic activities such as trade, mining and metallurgy. The analysis of plant-based foods –less prestigious but more essential in everyday life– has commonly been marginalised in state-of-the-art reviews. The O Areal saltworks is exceptional in terms of the large number of organic materials it preserves, and the excellent state of that preservation. After its abandonment (end of the 3rd/4th century AD), the saltworks was briefly used as a dumping ground for the surrounding area. The site's archaeobotanical remains, preserved under anoxic, waterlogged conditions, consist of the building materials used at the saltworks, tools and other artefacts, organic objects employed in activities such as fishing, and refuse. The assemblage suggests a wide diversity of species to have been introduced into northwestern Iberia during the Roman Period, including the mulberry, peach, fig, plum, grapevine, and melon. The notable presence of other edible fruit species that normally grew wild during this period, such as chestnut, walnut, stone pine, and cherry trees, might be related to the start of their cultivation.

In perennial fruit crops, bearing can be influenced by various factors, including environmental conditions, germplasm, rootstocks, and cultivation methods. Cherries, one of the most important and popular fruit species from the temperate climate zone, achieve high prices on the market. New agricultural technologies and environmental factors force a change in the approach to cherry cultivation. Old-type cherry orchards with their high demand for water, nutrients and manual work are replaced by orchards of self-pollinating cherry cultivars grown on dwarf rootstocks. These changes make it necessary to search for ways to regulate fruiting, in particular to thin buds, flower and fruit. In view of environmental regulations and consumer pressure, thinning methods are being sought that either do not involve the use of chemicals or that use eco-friendly chemical agents. This review examines recent progress in understanding the effect of thinning methods on the physiology, tree growth and fruit quality of cherries, discusses horticultural practices aimed to ensure regular cropping and their influence on fruit quality, and provides suggestions for future research.

In the Global North, there is an increasing interest in pulses both for their beneficial effects in cropping systems and for human health. However, despite these advantages, the acreage dedi-cated to pulses has been declining and their diversity reduced, particularly in European temperate regions, due to several social and economic factors. This decline has stimulated a political debate in the EU on the development of plant proteins. By contrast, in the Global South, a large panel of minor pulses is still cropped in regional patterns of production and consumption. The aim of this paper is to investigate the for cultivation of potential minor pulses in European temperate regions as a complement to common pulses. Our assumption is that some of these crops could adapt to different pedo-climatic conditions, given their physiological adaptation capacity, and that these pulses might be of interest for the development of innovative local food chains in an EU policy context targeting protein autonomy. The research is based on a systematic review of 269 papers retrieved in the Scopus database (1974–2019), which allowed us to identify 41 pulses as candidate species with a protein content higher than 20% that are already consumed as food. For each spe-cies, the main agronomic (e.g. temperature or water requirements) and nutritional characteristics (e.g. proteins or antinutritional contents) were identified in their growing regions. Following their agronomic characteristics, the candidate crops were confronted with variability in the annual growing conditions for spring crops in European temperate areas to determine the earliest poten-tial sowing and latest harvest dates. Subsequently, the potential sum of temperatures was calcu-lated with the Agri4cast database to establish the potential climatic suitability. For the first time, 21 minor pulses were selected to be grown in these temperate areas and appear worthy of inves-tigation in terms of yield potential, nutritional characteristics or best management practices.

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..

This research project focuses on the optimization of the hybrid energy system together with the assistance of thin-film coatings aiming to achieve self-sustainable food and crop storage facilities which will run effectively with its own generated energy. An infrastructure will be designed and constructed that will comprise a hybrid power generation system accompanied by thin-film coated semitransparent and non-transparent construction materials for energy saving. Thin-film low emissivity (Low-E) type coatings will assist the transparent or semitransparent construction materials to reflect most of the infrared (IR-mostly heat) and UV spectra of sunlight without interrupting the visible spectrum and will lead to saving energy consumption by reducing the heat and lighting during day time

Concerns of food and environmental security have increased enormously in recent years due to the vagaries of climate change and variability. Efforts to promote food security and environmental sustainability often reinforce each other and enable farmers to adapt to and mitigate the impact of climate change and other stresses. Some of these efforts are based on appropriate technologies and practices that restore natural ecosystems and improve the resilience of farming systems, thus enhancing food security. Climate smart agriculture (CSA) principles, for example, translate into a number of locally-devised and applied practices that work simultaneously through contextualised crop-soil-water-nutrient-pest-ecosystem management at a variety of scales. The purpose of this paper is to review concisely the current state-of-the-art literature and ascertain the potential of the Pfumvudza concept to enhance household food security, climate change mitigation and adaptation as it is promoted in Zimbabwe. The study relied heavily on data from print and electronic media. Datasets pertaining to carbon, nitrous oxide and methane storage in soils and crop yield under zero tillage and conventional tillage were compiled. Findings show that, compared to conventional farming, Pfumvudza has great potential to contribute towards household food security and reducing carbon emissions if implemented following the stipulated recommendations. These include among others, adequate land preparation and timely planting and acquiring inputs. However, nitrous oxide emissions tend to increase with reduced tillage and, the use of artificial fertilizers, pesticides and herbicides is environmentally unfriendly.

Climate variation and change are an unavoidable phenomenon faced by the natural habitat of this planet. For getting potential yield from vegetable crops under the changing climate conditions, the practical strategies at field level can serve as a guideline for the farmers. Moreover, there are several strategies available for mitigating the harmful effects of climate change. In this manuscript, efforts have been made for reviewing the mitigating strategies against the impact of climate change in vegetable crops via conventional approaches. Considering the situation, the information reviewed revealed that significant result of conventional approaches with climate-smart adoptions strategies has a direct bearing on vegetable production for the increasing population in frenziedly changing climate scenario.

Sustainable agricultural production is endangered by several ecological factors such as drought, extreme temperatures, excessive salts, parasitic ailments, and insect pest infestation. These challenging environmental factors may have adverse effects on future agriculture production in many countries. In modern agriculture, conventional crop breeding techniques alone are inadequate for achieving the increasing population’s food demand on a sustainable basis. The advancement of molecular genetics and related technologies are promising tools for the selection of new crop species. Gene pyramiding through marker assisted selection (MAS) and other techniques have accelerated the development of durable resistant/tolerant lines with high accuracy in the shortest possible period of time for agricultural sustainability. Gene stacking has not been fully utilized for biotic stress resistance development and quality improvement in most of the major cultivated crops. This review emphasizes on gene pyramiding techniques that are being successfully deployed in modern agriculture for improving crop tolerance to abiotic and biotic stresses for sustainable crop improvement.

Recent studies of the difficulties faced by smallholder farmers in many developing countries have echoed their disconnection with formal markets. These limitations have been attributed to a number of factors including stringent quality and volume requirements, among others. While smallholder farmers seek access to formal markets, the existing alternatives through which they sell their produce remain obscure. Using an interview of market outlets and selected smallholder farmers in the area, the study applied a crop marketing index to examine the outlets currently used by farmers and the volume of potatoes sold in each. Findings indicate that smallholder farmers on average sold sixty-eight percent of their produce. The outlet mostly used by farmers was street vendors because the large supermarkets sold potatoes supplied from external sources. It would be helpful for smallholder farmers to aggregate their produce through producer and marketing cooperatives, to better engage with these formal market outlets.

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.

Proper satellite-based crop monitoring applications at the farm-level often require near-daily imagery at medium to high spatial resolution. The synthesizing of ongoing satellite missions by ESA (Sentinel 2) and NASA (Landsat7/8) provides this unprecedented opportunity at a global scale; nonetheless, this is rarely implemented because these procedures are data demanding and computationally intensive. This study developed a complete stream processing in the Google Earth Engine cloud platform to generate harmonized surface reflectance images of Landsat7,8 and Sentinel 2 missions. The harmonized images were generated for two agriculture schemes in Bekaa (Lebanon) and Ninh Thuan (Vietnam) during the period 2018-2019. We evaluated the performance of several pre-processing steps needed for the harmonization including image co-registration, brdf correction, topographic correction, and band adjustment. This study found that the miss-registration between Landsat 8 and Sentinel 2 images, varied from 10 meters in Ninh Thuan, Vietnam to 32 meters in Bekaa, Lebanon, and if not treated, posed a great impact on the quality of the harmonized dataset. Analysis of a pair overlapped L8-S2 images over the Bekaa region showed that after the harmonization, all band-to-band spatial correlations were greatly improved from (0.57, 0.64, 0.67, 0.75, 0.76, 0.75, 0.79) to (0.87, 0.91, 0.92, 0.94, 0.97, 0.97, 0.96) in bands (blue, green, red, nir,swir1,swir2, ndvi) respectively. We demonstrated that dense observation of the harmonized dataset can be very helpful for characterizing cropland in highly dynamic areas. We detected unimodal, bimodal and trimodal shapes in the temporal NDVI patterns (likely cycles of paddy rice) in Ninh Thuan province only during the year 2018. We fitted the temporal signatures of the NDVI time series using harmonic (Fourier) analysis. Derived phase (angle from the starting point to the cycle's peak) and amplitude (the cycle's height) were combined with max-NDVI to generate an R-G-B image. This image highlighted croplands as colored pixels (high phase and amplitude) and other types of land as grey/dark pixels (low phase/amplitude). Generated harmonized datasets that contain surface reflectance images (bands blue, green, red, nir, swir1, swir2, and ndvi at 30 meters) over the two studied sites are provided for public usage and testing.

Crop breeding is as ancient as the invention of cultivation. In essence, the objective of crop breeding is to improve plant fitness under human cultivation conditions, making crops more productive while maintaining consistency in life cycle and quality. The applications of predictive breeding has been gaining momentum in agricultural industry and public breeding programs for the last decade, in the aftermath of genomic selection being recognized and widely applied for accelerating genetic gain in breeding programs. The massive amounts of data that has been generated by industry and farmers year after year through several decades has finally been recognized as an asset. A wide range of analytical methods such as machine learning, deep learning and artificial intelligence that were initially developed for diverse quantitative disciplines are now being adopted to crop breeding decision making processes. New technologies are currently being developed that would enable integration of data from various domains such as geospatial variables and a multitude of phenotypic responses as well as genetic information, in order to identify, develop and improve crop faster via partial or full automation of the decisions that pertain to variety development. Here we will discuss and summarize efforts from public and private domains for predictive analytics, and its applications to crop breeding and agricultural product development, and provide suggestions for future research.

The objective of this study was to determine the association of physiological responses and root distribution patterns on yield of the second ratoon cane and the relationships among these traits. Seventeen sugarcane genotypes were planted in a randomized complete block design with four replications. The second ratoon crop was evaluated for germination percentage, cane yield, SPAD chlorophyll meter reading (SCMR), chlorophyll fluorescence, relative water content (RWC), specific leaf area (SLA) and stomatal conductance. Root length density (RLD) was evaluated by auger method. The root samples were divided into upper soil layer and lowers soil layers to study root distribution patterns. Sugarcane genotypes were significantly different for RLD, germination percentage and cane yield. Root distribution patterns were classified into three groups based on the RLD. High RLD between plants in the upper soil layers at 90 DAH was positively correlated with high germination, whereas high RLD between rows in the lower soil layers at 90 and 270 DAH was associated with high cane yield. RWC at 90 DAH and stomatal conductance at 180 DAH were closely related to germination percentage, whereas chlorophyll fluorescence and stomatal conductance at 180 DAH were closely related to cane yield.

The diamondback moth (DBM), Plutella xylostella L. (Lepidoptera: Plutellidae) is very destructive crucifers specialized pest that has resulted in significant crop losses worldwide. The pest is well attracted to glucosinolate-containing crucifers such as; Barbarea vulgaris (Brassicaceae), and generally to other plants in the genus Barbarea. B. vulgaris on their part, build up resistance against DBM and other herbivorous insects using glucosinolates; that are plant secondary metabolites used in plant defense–contained only in plants of the order Brassicales. Aside glucosinolates, plants in this genus Barbarea (Brassicaceae) also contain saponins; which is toxic to insects and act as feeding deterrents for plant herbivores, most importantly, DBM, as it was found to prevent the survival of DBM larvae on the plant. Saponins are plant secondary metabolites have been established in higher concentrations in younger in contrast to older leaves within the same plant. Previous studies have found a relationship between ontogenetical changes in the host plant’s saponin content and attraction/resistance to P. xylostella. The younger leaves recorded higher concentrations of glucosinolates and saponins, which naturally attracts the plant herbivores. DBM was reported to have evolved mechanisms to avoid the toxicity of the former. The plant-herbivore had adapted glucosinolates for host plant recognition, feeding and oviposition stimulants. Despite the adaptation for oviposition by P. xylostella adults, larvae of the insect cannot survive on the same plant. An example is in some varieties of B. vulgaris. The triterpenoid saponins which act as feeding deterrents in larvae are responsible for this direct defense mechanism against P. xylostella. In the future, trials by plant breeders could aim at transferring this insect resistance to other crops. The previous trials had limited because of lack of knowledge on the biosynthetic pathways and regulatory networks of saponins. Herein, we discussed exclusively; saponins mediated plant defense mechanisms against the DBM.

Crop productivity is directly dependent to soil fertility. High soil organic carbon (SOC) content in soil is vital as it leads to improved soil quality, increased productivity, and stable soil-aggregates. In addition, with the signing of the climate agreement, there is growing interest in carbon sequestration in landscapes. This paper looks at how SOC can be increased so that it not only contributes to reduction of CO₂, but also translates to increased food production thereby enhancing food security. This synergy between mitigation and enhancing food security is even more relevant for mountain landscapes of the Hindu Kush Himalayan (HKH) region where there remains huge potential to increase CO₂ sequestration and simultaneously address food security in the chronic food deficit villages. Soil samples were collected from seven transects each in Bajhang and Mustang and from 4 land use types in each transect. Samples of soils were taken from two depths in each plot; 0-15 cm below the soil surface and 15-30 cm below the soil surface to compare the top soil and subsoil dynamics of the soil nutrients. The lab analysis was performed to assess the soil texture, soil color, soil acidity in 'power of hydrogen' (pH), macro-nutrients as soil fertility. Secondary data was used to analyze the level of food deficit in the villages. The result shows that most of the sample soils from Mustang were clay (82.1%) which is 46 samples out of 56. The pH value of soil from Bajhang ranged from 5.29 to 9.09. The pH value of soil ranged from 5.65 to 8.81 in Mustang. SOC contents of sampled soils from Bajhang ranged from 0.20% to 7.69% with mean amount of 2.47% ± 0.17. SOC contents of sampled soils from Mustang ranged from 0.51% to 8.56% with mean amount of 2.60% ± 0.25. By land use type, forest land had the highest carbon (C) content of 53.61 t ha^-1 in Bajhang whereas in Mustang, agricultural land had the highest C content of 52.02 tons ha-1. Based on these data, we can say that there is potential for increasing SOC through improved soil health and crop production and soil. Sustainable soil management should be practiced for higher productivity. Livestock may also provide farmyard manure, which can be used to fertilize cultivated soils, which increases soil productivity. Increasing productivity would aid in increasing the access and availability of food in these mountain villages.

Green manure could improve soil nutrients and crop production, playing a significant role in sustainable agriculture. However, the impacts of green manure on crop health and the roles soil microbial communities play in the process haven’t been clarified clearly yet. In this study, we investigated soil microbial community composition and structure in four tobacco farmlands, which were treated with different green manure (control, ryegrass, pea and rape), using 16S rRNA gene amplicons sequencing. Results showed that green manure had significant impacts on soil properties, microbial communities and tobacco health. First, soil total C, N and Ca content increased significantly in groups treated with green manure than control. Second, soil community diversity was significantly higher in groups treated with green manure. Third, green manure especially ryegrass, decreased tobacco disease (bacterial wilt) rate dramatically, and the process might be mediated by soil microbial communities. On the one hand, several microbial populations were found to be potentially disease inducible or suppressive. For example, the abundances of Dokdonella and Rhodanobacter were positively correlated to tobacco disease rate, while Acidobacteira_Gp4 and Gp6 had negative correlations with tobacco disease. On the other hand, soil microbial communities were shaped by soil properties (e.g., pH, C and N content). In conclusion, our research showed that green manure could increase soil nutrients directly, and further improve tobacco health mediated by soil microorganisms, which may shed light on revealing interactions among soil properties, microorganisms and plants.

Nanotechnology has become a popular topic in agricultural and animal research, generating sig-nificant global interest. Nanoparticles (NPs)-enabled agriculture and animal husbandry (AHs) products have three main principles: crop production, protection, and nutrient enrichment. Re-search on this topic has grown exponentially in recent years, with an increasing number of peer-reviewed literature and patents on NPs-enabled agriculture and AH products. This study examines and collects data on the various applications of NPs-enabled agricultural products for crop production, protection, and livestock improvement from the core nanotechnological database. The search returned several types of NPs and products used in agriculture and AH, countries that utilize these products at a commercial level, and analysis of these data by phyton, R-statistical software. Our findings show remarkable growth of nanotechnology in agriculture, AH, and re-search fields for future sustainability goals in the era of climate change

Blood-based biomarkers for early detection of recurrence have a significant clinical impact on the improved management of breast cancer patients, as cancer recurrence results in poor prognosis. This study aimed to investigate if the measurement of blood endocan in breast cancer patients with high ESM1 expression could be an effective tool to detect postoperative recurrence compared with existing tumor markers. Blood was collected before and after the tumor resection from the mouse models of breast cancer, and endocan levels were measured while visualizing metastatic recurrence with noninvasive luminescence imaging. In clinical settings, blood was withdrawn from 16 breast cancer patients before and after the tumor resection, and the effect of lumpectomy on blood endocan level was evaluated. Additionally, the blood endocan from 20 patients diagnosed with postoperative recurrence was measured, and their positivity rate for endocan was compared with that for serum carcinoembryonic antigen (CEA) or cancer antigen 15-3 (CA15-3). Our preclinical and clinical experiments revealed that blood endocan levels reflected tumor burden. Furthermore, over 60% of patients suffering from postoperative recurrence who tested negative for CEA or CA15-3 were positive for endocan. Our results support the clinical significance of endocan in breast cancer patients for detecting breast cancer recurrence.

Henipaviruses are single-stranded RNA viruses that have been shown to be virulent in several species including humans, pigs, horses, and rodents. Isolated nearly 30 years ago, these viruses have been shown to be of particular concern to public health, as at least two members (Nipah and Hendra viruses) are highly virulent, as well as zoonotic, and are thus classified as BSL4 pathogens. Although only 5 members of this genus have been isolated and characterized, metagenomics analysis using animal fluids and tissues has demonstrated the existence of other novel henipaviruses, suggesting a far greater degree of phylogenetic diversity than currently known. Using a variety of molecular biology techniques, it has been shown that these viruses exhibit varying degrees of tropism, on a species, organ/tissue, and cellular level. This review will attempt to provide a general overview of our current understanding of henipaviruses, with particular emphasis on viral tropism.

The study of the currently known >3,000 species of snakes can provide valuable insights into the evolution of their genomes. Deinagkistrodon acutus, also known as Sharp-nosed Pit Viper, one hundred-pacer viper or five-pacer viper, is a venomous snake with significant economic, medicinal and scientific importance. Widely distributed in southeastern China and South-East Asia, D. acutus has been primarily studied for its venom. Here, we employed next-generation sequencing to assemble and annotate a highly continuous genome of D. acutus. The genome size is 1.46 Gb; its scaffold N50 length is 6.21 Mb, the repeat content is 42.81%, and 24,402 functional genes were annotated. This study helps to further understand and utilize D. acutus and its venom at the genetic level.

Vitamin E is a group of eight compounds divided into two subgroups: four tocopherols (α-, β-, γ-, and δ-) and four tocotrienols (α-, β-, γ-, and δ-). α-Tocopherol is considered the most biologically active form. This review paper summarizes the current knowledge and historical progression of vitamin E research, with particular emphasis on its role in animal nutrition. Early studies in the 1920s identified vitamin E’s role in preventing neonatal mortality in rats. Over the following decades, scientists discovered the compound’s chemical structure and its importance for the immune system, skin health, anti-inflammatory properties, hormonal balance, and other bodily functions. Production of vitamin E products has evolved, starting with isolating the vitamin from natural sources and advancing to synthesizing it with greater efficiency and standardized potency units. Early animal studies focused on reproductive health and growth disorders, but further research demonstrated the importance of vitamin E in preventing encephalomalacia in domestic fowl and muscular dystrophy in rabbits and other animals. Today, vitamin E is commonly used as a feed additive to meet animals’ requirements and assure immune function and overall health. Despite much knowledge on vitamin E’s role in animal nutrition, many questions remain unanswered, and current research aims to determine optimal supplementation levels, interactions with other nutrients, impacts on gene expression, cell signaling and communication, and effects of supranutritional dosages in livestock. Vitamin E has a long and fascinating history in scientific research, with significant advancements in understanding its chemical structure and biological activity. In animal nutrition, vitamin E continues to play an important role in improving animal health, and ongoing research will continue to expand our understanding of its benefits and mechanisms of action.

The use of electronic means to support tasks such as pastoralism is a way of intelligently optimizing that activity. As any autonomous system, it requires human intervention in case of failure, and therefore it needs an autonomous mechanism that draws the attention of the human operator whenever the system or the animals evolve to undesired conditions. The present work progresses an existing alarm system, used in the SheepIT gateway, which can monitor the behavior of animals and equipment, warning human supervisors of the occurrence of unwanted events and the need for intervention. Concretely, given the lack of coverage of Internet access in rural areas, the system was integrated with a satellite interface to guarantee communication and the timely delivery of alarm messages. The paper compares the overall networking performance of the satellite link, against a Wi-Fi laboratorial baseline.

Leptospirosis is an important zoonotic disease that is transmitted worldwide through infected small mammals such as rodents. In Malaysia, there is paucity of information on the animal reservoirs that are responsible for leptospirosis transmission, with only few studies focusing on leptospirosis risk in recreational areas. Therefore, in this study, we characterized the species composition and the prevalence of pathogenic Leptospira spp. in non-volant small mammals of Hutan Lipur Sekayu, Terengganu. We performed ten trapping sessions totaling 3,000 trapping efforts between September 2019 and October 2020. Kidney samples from captured individuals were extracted for the PCR detection of pathogenic Leptospira spp. Overall, we captured 45 individuals from 8 species (1.56% successful trapping effort), with 9 individuals testing positive for pathogenic Leptospira, that is 20% (n = 9/45) prevalence rate. Rattus tiomanicus (n = 22) was the most dominant captured species and was found to harbour the highest positive individual with pathogenic Leptospira (44.4%, n = 4/9). Despite the low successful trapping effort in this study, the result shows that the non-volant small mammals of Hutan Lipur Sekayu are capable of maintaining and transmitting pathogenic Leptospira, thus making this recreational area a potential infestation ground for leptospirosis.

Choanoflagellates, the closest living relatives of animals, have the potential to reveal the genetic and cell biological foundations of complex multicellular development in animals. Here we describe the history of research on the choanoflagellate Salpingoeca rosetta. From its original isolation in 2000 to the establishment of CRISPR-mediated genome editing in 2020, S. rosetta provides an instructive case study in the establishment of a new model organism.

Campylobacter is one of the major foodborne pathogens of concern in its growing trend of antimicrobial resistance. C. jejuni and C. coli are the major causative agents, with C. jejuni contributing to most of the cases in approximately 90% in the world. Infection is transmitted to humans due to consumption of contaminated food and water. Campylobacteriosis caused by C. jejuni is commonly presented with severe diarrhoea, abdominal pain, fever, headache, nausea, and vomiting with some extreme cases resulting in Guillain–Barré syndrome (GBS) and acute flaccid paralysis. Symptoms are severe in cases of children below 5 years, elderly and individuals who are immunocompromised. The infection is usually sporadic, and self-limiting and thus does not require antibiotics for treatment. Still, the antimicrobial resistance in Campylobacter is a major concern because of the transmission of resistance from animal sources to humans. This review highlights the recent epidemiology, geographical impact, resistance mechanisms, spread of Campylobacter spp. and the strategies to control the transmission of Campylobacter from veterinary sources and its antimicrobial resistance.

Fullerene molecules are composed of carbon in forms of a hollow sphere, ellipsoid, or tube. Fullerenes have attracted considerable attention in different fields of science since their discovery in 1985. The unique carbon cage structure of fullerene provides immense scope for derivatization, rendering potential for various industrial applications. The prospective applications of fullerenes thus have led to assorted fullerene derivatives. The unique chemical structure also provides ease for fullerene to be synthesized through various kinds of conjugating techniques, where fullerene can be located either on the backbone or the branch chain. Here in this review, we have compiled the toxicity and biosafety aspects of fullerene in aquatic organisms. The frequent use of fullerene is likely to come in contact and interact with the aquatic environment and aquatic organisms. According to the current understanding, waterborne exposure to fullerene-based nanomaterials indeed triggers toxicities at cellular, organic, molecular as well as neurobehavioral levels.

We evaluated progress towards animal biodiversity research in Georgia, a key area in the Caucasus biodiversity hotspot. By reviewing recently (1990-2018) published articles in all areas of animal diversity research, we unmasked the trends in biodiversity inventory, ecological and biogeographical studies, and conservation issues in Georgia. We concluded that species inventory and biodiversity research in Georgia has significantly increased during the last ten years, however the rate and extent of investigation is far from satisfactory. Major gaps remain in all branches of animal diversity research in Georgia, and consequently existing knowledge is inadequate to address modern challenges related to species and ecosystem conservation. We urge local governmental authorities and international scientific societies to support development of stronger research facilities and cultivate interest in biodiversity inventory and research in Georgia as an important step towards maintaining globally important biodiversity in the Caucasus.

Fear can sometimes paralyze us, and it can sometimes be exciting; for some people, fear is so crippling it can significantly mix up their lifes! We understand a little bit about how the brain acts when we are afraid, mainly by studying the brains of animals. Recently, surprising findings were made using a humble animal, the zebrafish – a small aquarium fish that in the past has helped scientists figure out how our organs develop. Zebrafish are useful because they develop quickly, reproduce richly, and have brains which are similar to ours. They also produce what we call an “alarm substance” that alerts shoalmates when one of them has been injured; when they smell this substance in the water they act as if they are very scared. When this happens, they release serotonin in their brains, a neurotransmitter that acts as a light switch, making them less afraid but more cautious – as if trying to figure out if a predator is there or not. Hopefully, finding more about how the zebrafish brains process this serotonin signal can help scientists develop better treatments for mental disorders that are associated with fear.

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

Artificial intelligence techniques are now widely used in various agricultural applications, including the detection of devastating diseases such as late blight (Phytophthora infestans) and early blight (Alternaria solani) affecting potato (Solanum Tuberorsum L.) crops. In this paper, we present a mobile application for potato crop pest detection based on deep neural networks. The images were taken from the PlantVillage dataset with a batch of 1000 images for each of the three identified classes. An exploratory analysis of the architectures used for early and late blight diagnosis in potatoes was performed, achieving an accuracy of 98.76%, with MobileNetv2. Based on the results obtained, an offline mobile application was implemented, supported on devices with Android 4.1 or later, also featuring an information section on the 27 pests affecting potato crops and a gallery of symptoms. For future work, segmentation techniques will be used to highlight the damaged region in the potato leaf by evaluating its extent and possibly identifying different types of pests affecting the same plant.

The agricultural sector is currently confronting multifaceted challenges such as an increased food demand, a slow adoption of sustainable farming, a need for climate-resilient food systems, resource inequity, and protection of the small-scale farmers’ practices, all issues integral to food security and environmental health. Remote sensing technologies can assist precision agriculture to effectively address these complex problems, by providing farmers with a high-resolution lens. The use of vegetation indices (VIs) is an essential component of remote sensing, which combine the variability of spectral reflectance value (derived from remote sensing data) with the growth stage of crops. Currently a wide array of VIs is available that could be used to provide a classification and an evaluation of the state and health of crops. However precisely this high number leads to difficulties in selecting the best VI and combination of VIs for a specific objective. Without a thorough documentation and analysis of appropriate VIs, users might be confronted with difficulties in using remote sensing data or even with a very low accuracy of the results. Thus, the objective of this review is to conduct a critical analysis of the existing state of the art on the most important features related to the effective use of VIs for the discrimination and monitoring of the most important agricultural crops (wheat, corn, sunflower, soybean, rape, potatoes, and forage crops), grasslands and meadows. This data could be highly useful for all the stakeholders involved in agricultural activities (from farmers, researchers up to institutions dealing with the centralization and monitoring of agricultural crops).

Plant Growth Promoting Rhizobacteria (PGPR) is beneficial microorganisms that inhabit the rhizosphere of plants and play a crucial role in enhancing plant growth and development. This review provides an overview of the significant role of PGPR in sustainable agriculture. The mechanisms that promote plant growth, such as nitrogen fixation, phosphate solubilization, and growth hormones, are discussed. The potential of PGPR in improving plant tolerance to biotic and abiotic stresses, reducing the use of chemical fertilizers and pesticides, and enhancing nutrient availability, soil fertility, and uptake is also highlighted. Moreover, the ecological and economic benefits of using PGPR for sustainable agriculture include improving crop productivity, reducing environmental pollution, and ensuring food security.

This review article explores the significance of beneficial microorganisms in crop improvement, highlighting their roles in promoting plant growth, enhancing nutrient uptake, and protecting against pathogens. The symbiotic interactions between plants and microorganisms have been extensively studied, revealing the vast potential of these beneficial partnerships in sustainable agriculture. The article discusses various types of beneficial microorganisms, including mycorrhizal fungi, rhizobia, and plant growth-promoting bacteria, elucidating their mechanisms of action and their impact on plant health and productivity. Furthermore, it examines the application of microbial inoculants and biofertilizers in crop production systems, emphasizing their potential to enhance crop yield, nutrient use efficiency, and stress tolerance. The review also explores emerging technologies, such as metagenomics and synthetic biology, in harnessing the full potential of beneficial microorganisms for crop improvement. Overall, we highlight the importance of beneficial microorganisms in sustainable agriculture and provide insights into their promising applications in crop enhancement.

This research investigates the potential benefits of integrating machine learning algorithms and IoT sensors in modern agriculture. The focus is on optimizing crop production and reducing waste through informed decisions about planting, watering, and harvesting crops. The paper discusses the current state of machine learning and IoT in agriculture, highlighting key challenges and opportunities. It also presents experimental results that demonstrate the impact of changing labels on the accuracy of data analysis algorithms. The findings recommend that by analyzing wide-ranging data collected from farms, including real-time data from IoT sensors, farmers can make more informed verdicts about factors that affect crop growth. Eventually, the integration of these technologies can transform modern agriculture by increasing crop yields while minimizing waste. In our studies, we achieve a classification accuracy of 99.59% using the Bayes Net algorithm and 99. 46% using Naïve Bayes Classifier, and Hoeffding Tree algorithms. Our results indicate that we achieved high accuracy results in our experiments in order to increase crop growth.

About a decade ago, active optical crop canopy sensors are being used to manage in-season variable nitrogen (N) fertilization in cornfields to match the plant demand that occurs mid season, increasing the efficiency compared to broadcast N applications. There were also initiatives of using ultrasonic sensors to measure plant height on-the-go for N application and crop water demand estimation, but no studies have integrated the optical, ultrasonic and canopy temperature for crop water stress assessment. The objective of this chapter is to evaluate the crop water status using infrared thermometry integrated with optical and ultrasonic sensors. Specifics objectives are: (i) evaluate the corn canopy temperature under different previous crop, N rates and irrigation levels; (ii) test a procedure for water stress assessment in commercial cornfields using the integration of sensors, (iii) correlate plant based sensor measurements (N status, plant height and canopy temperature) with grain yield, soil attributes and detailed topographical features, and (iv) study the spatial dependence of canopy temperature. This study was conducted in one small plot study area and on three producer’s fields in 2010. The small plot experiment consisted of two irrigation levels (70 and 100% of evapotranspiration – ET), two previous crop schemes (corn after corn – CC and corn after soybeans – CS), and four N rates (0, 75, 150, 225 kg N ha^-1). Canopy temperature, optical reflectance and plant height was measured from R2 until R6 in the small plots. At the producer’s fields, three long strips across center pivots were used to have a non-limited N and water crop and then continuous georeferenced sensors measurements were taken during side-dress (V11 growth stage) in about 10 hectares in each field. In the small plot study the crop canopy temperature was influenced by the irrigation levels and N rates. The procedure proposed could be used to identify zones in the producer’s field where water stress can be a yield limiting factor other than N derived. Inside the zones considered that water stress played a major whole, there were low correlations between plant height, plant N status and canopy temperature, indicating that the canopy temperature had more influence from water stress than vegetation cover. Concave and lower elevation areas had higher yields compared to convex and high elevation, showing that the detailed elevation mapping can be beneficial to delineate stables zones that possibly could be used in variable irrigation systems. The spatial dependence of canopy temperature was over 65 meters across producers’ sites, showing that the commercial high clearance applicator’s swath width was adequate to obtain accurate maps. The integration of plant N status, plant height and canopy temperature was beneficial to detect water stressed zones in the field. Opportunities can be foresee also for on-the-go N fertilization using integration of these sensors because is likely that water stress can be confounded with different N supply during the growing season and in different zones in the field.

Intercropping as a practice is very crucial in livelihood sustainability among smallholder farm-ing communities in many growing countries. However, for most cropping systems, the benefits of intercropping have yet to be optimized due to a lack of knowledge regarding spatial ar-rangements and planting densities. The objective of the study was to find out the profitability of maize-vegetable intercropping and the yields obtained from various spatial arrangements and planting densities of intercrops. From May to October 2019 and 2020 respectively, Experimental trials were set up in the rainy season in Northern, Upper West and Upper East regions of Ghana comprising of eight treatments each. A randomized complete block experimental design was used for the field layout with three to four replications. Data was collected on grain and fruit yield and land equivalent ratios was estimated (LER). At the end of the trial, important spatial arrangements and planting densities were identified that can be adopted by smallholder famers for system intensification. For okra, the optimal intercropping system under sufficient rainfalls was 2 okra rows at higher density and 2 maize rows at lower density for Upper West Region. In Upper East Region, the optimal spatial arrangement to recommend is 1 row of maize at recom-mended density: 2 rows of okra at lower density under well distributed rainfalls. For roselle, intercropping with spatial arrangement of 2 rows of maize at higher density: 1 row of okra at recommended density was recommended in Northern Region.

Abstract: A lower bed single row for pineapple cultivation could protect pineapple from soil erosion in rainy season and during drought, however, disease problem could arise due to water logging. Two experiments using a lower bed single row was done to understand the ability of gypsum providing soil calcium (Ca) available to pineapple plant, resistance to heart rot disease, and give better effect on crop growth and fruit quality of the pineapple in Ultisol soil. In the first trial, four level dosis of gypsum (0, 1.0, 1.5, 2.0 Mg ha-1) and dolomite 2 Mg ha-1 were applied by spreading and incorporated into the soil which have saturated with inoculums of Phytophthora nicotianae. In the second trial, gypsum treatments (0, 1.0, 1.5, 2.0, 2.5 Mg ha-1) were applied in the row between the single row beds as a basic fertilizer. The result showed that P. nicotianae attacked the pineapple plants in all treatments at 6 weeks after planting (WAP), and at 10 WAP, the mortality of dolomite treatment reached 63.8%, significantly different than that for gypsum treatments (3.3-14.3%). In the second experiment, gypsum increased plant weight significantly at 3 until 9 months after planting especially when it was applied 1.5-2.5 Mg ha-1. Fruit texture, total soluble solid (TSS), titratable acidity (TA) were not significant different among the treatment but all meet the standards for grades of canned pineapple. Result showed that soil applied gypsum before planting provides soil calcium and met the plant Ca requirement during a period of early and fast growth step and safe for heart rot disease.

In wild habitats, fruit dehiscence is a critical strategy for seed dispersal; however, in cultivated crops it is one of the major sources of yield loss. Therefore, indehiscence of fruits, pods, etc., was likely to be one of the first traits strongly selected in crop domestication. Even with the historical selection against dehiscence in early domesticates, it is a trait still targeted in many breeding programs, particularly in minor or underutilized crops. Here, we review of this trait in pulse (grain legume) crops, which are of growing importance as a source of protein in human and livestock diets, and which have received less attention than cereal crops and the model plant Arabidopsis thaliana. We specifically focus on the i) history of indehiscence in domestication across legumes, ii) structures and the mechanisms involved in shattering, iii) the molecular pathways underlying this important trait, iv) an overview of the extent of crop losses due to shattering, and the effects of environmental factors on shattering, and, v) efforts to reduce shattering in crops. While our focus is mainly pulse crops, we also included comparisons to crucifers and cereals because there is extensive research on shattering in these taxa.

Unmanned aerial vehicles (UAV) provide an unprecedented capacity to monitor the development and dynamics of tree growth and structure through time. It is generally thought that the pruning of tree crops encourages new growth, has a positive effect on fruiting, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. To establish the response of pruning in an orchard of lychee trees, an assessment of changes in tree structure, i.e. tree crown perimeter, width, height, area and Plant Projective Cover (PPC), was undertaken using multi-spectral UAV imagery collected before and after a pruning event. While tree crown perimeter, width and area could be derived directly from the delineated tree crowns, height was estimated from a produced canopy height model and PPC was most accurately predicted based on the NIR band. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in tree crown perimeter of 1.94 m, tree crown width of 0.57 m, tree crown height of 0.62 m, tree crown area of 3.5 m², and PPC of 14.8%. In order to provide guidance on data collection protocols for orchard management, the impact of flying height variations was also examined, offering some insight into the influence of scale and the scalability of this UAV based approach for larger orchards. The different flying heights (i.e. 30, 50 and 70 m) produced similar measurements of tree crown width and PPC, while tree crown perimeter, area and height measurements decreased with increasing flying height. Overall, these results illustrate that routine collection of multi-spectral UAV imagery can provide a means of assessing pruning effects on changes in tree structure in commercial orchards, and highlight the importance of collecting imagery with consistent flight configurations, as varying flying heights may cause changes to tree structural measurements.

The main objective of the present study was to investigate arsenate [As (V)] resistance genes in rice cultivars grown in arsenic contaminated Egyptian soil in order to genetically induce resistance against arsenic in the local rice varieties as well as defining contaminated rice grains and/or soil. Three local rice cultivars; Sakha 102-104 were cultivated on modified Murashige and Skoog Basal Medium (MS medium) containing elevated concentrations of arsenate (0.1, 1 and 10 mg/l). The three varieties showed different resistant attitudes against arsenate with Sakha 104 being the most resistant. Extracted messenger RNA (mRNA) from treated and untreated Sakha 104 plantlets was scanned using differential display to demonstrate the arsenate resistant genes using three different arbitrary primers. About 100 different RNAs with (1500 bp - 50 bp) were obtained from which seven were up-regulated genes, subjected to DNA cloning using TOPO TA system and the selected clones were sequenced. The sequence analysis described four genes out of the seven namely disease resistance protein RPM1, Epstein-Barr virus EBNA-1-like, CwfJ family protein and outer membrane lipoprotein OmlA while the other three genes were hypothetical proteins. It is concluded the four induced genes in the resistant rice cultivar considered as a direct response to arsenic soil pollution. Genes detected in the present study can be used as geno-sensors for rice grains and soil contamination with As (V). Moreover, local rice cultivars may be genetically modified with such genes to induce high resistance and to overcome arsenic soil pollution.

COVID-19, caused by SARS-CoV-2, was first identified in China in 2019. The exact origin of the disease remains uncertain, with theories suggesting it may have emerged from animals or accidentally leaked from a research laboratory. If the hypothesis that COVID-19 originated from a research laboratory is accurate, it is crucial to investigate potential pathways for pathogens to escape from biocontainment research animal facilities (BRAFs). We examine key biosafety issues associated with BRAFs, including inadequate decontamination procedures for water and experimental samples, handling high biosafety level pathogens in lower level laboratories, risks of animal bites and sharps injuries, contamination of bedding and enrichment materials, and improper management and transportation of biohazard samples. Additionally, we discuss the role of veterinarians in African research animal facilities and the challenges they encounter in maintaining biocontainment standards. We emphasize the importance of routine monitoring of effluent water to detect possible disease outbreaks. We recommend a thorough investigation of the COVID-19 pandemic to identify potential sources of pathogen release from BRAFs, which could serve as hotspots for future disease outbreaks. Findings from such investigations will inform the development of policies aimed at safeguarding human populations from future pandemics and preventing BRAFs from becoming sources of infectious disease outbreaks.

Livestock farming plays a crucial role in agriculture and is important in meeting people's needs for a better life in the new era. However, due to China's "double carbon" target, the development of animal husbandry has been affected by the level of carbon emissions. To study the spatial dis-tribution and dynamic evolution of livestock carbon emissions in Shandong Province, we used panel data from 16 prefecture-level cities in Shandong Province from 2001 to 2022 to determine the spatial differentiation of livestock carbon emissions in Shandong Province and their dynamic evolution by combining spatial and non-parametric estimation methods based on livestock carbon emissions and livestock emission intensity measured by city. The results of the study show that the distribution of carbon emissions from animal husbandry in Shandong Province is in a "dis-persed-aggregated" pattern, and the intensity of carbon emissions shows a gradual downward trend, with a ladder-like distribution characterized by high in the west and low in the east. Through the analysis of the dynamic evolution of nuclear density, we observe that the regional differences of animal husbandry carbon emissions in Shandong Province are expanding, showing the characteristics of polarization. The difference of carbon emissions in the peninsula is gradually narrowing, and the phenomenon of polarization is weakening. The carbon emissions of animal husbandry in the central and western regions of Shandong are polarized.

Introduction: Overuse of antibiotics has been increasing in recent years and is currently the most prescribed drug in the paediatric age. It is estimated that 72% of patients in the neonatal intensive care unit (NICU) are treated with antibiotics. One of the effects observed with their use is the alteration of the microbiota, which is associated with metabolic disorders including obesity. In this study, the aim was to determine in newborn rats, whether most commonly prescribed antibiotics in Mexican NICUs have a differential effect on weight gain, development of adiposity, and modification of carbohydrate and lipid metabolism. Methods: This is an experimental study in newborn rats, comparing Ampicillin/Meropenem (Access/Watch groups) 100 mg/g every 12 h /10 mg/g every 12 h (each of these two antibiotics was adjusted to the required dosages based on weight); Cefotaxime 200 mg/g every 24 h; (Watch group) and Amikacin 15 mg/g every 24 h (Access group) versus Saline Solution as Control. Each antibiotic was intraperitoneal administered daily for 5 days in males (to avoid gender differences) to 14 newborn rats in each group. A comparison of anthropometric and biochemical parameters registered on day 28 was made using ANOVA analysis. Differences were considered if p < 0.05.Results: Amikacin was the antibiotic with the greatest effect on anthropometric measurements and LDL-cholesterol; as well as Cefotaxime on Glucose and triglycerides, while Meropenem plus Ampicillin showed the weakest effect on measured parameters. Conclusion: The administration of antibiotics in the neonatal stage has repercussions on the body composition of adult rats, as well as on lipids and carbohydrates serum levels. Future studies might evaluate the toxicity of antibiotics on the immature neonatal organs.

(1) Background: the popularity of rabbits has increased during the last decades and became the third common companion animals in EU. Their participation in animal assisted interventions (AAI) is growing. It is highly important to ensure the well-being of the animals in AAI. Whereas the needs and the advantages of people involved in AAI are becoming more and more evident, the needs of animals are not clearly determined, it is required not to affect the animals negatively. Those animals who are used for AAI purpose need toneed to be transported regulrarly; (2) Methods: the rabbits stress – caused by transportation – were measured by non-invasive faecaesl cortisol metabolite (FCM) analysis. 18 animals were involved in the study and experienced a 30 minutes transportation every second day duringfor two weeks (total 6 times) while 128 samples were collected; (3) Results: rabbits –could handle the transportation procedure by the first and second time but subsequently the stress hormone metabolites in faeces samples increased significantly regardless of the offered treatments (hay, carrot and apple) during the carriage. (4) Conclusions: those owners who use rabbits for Animal Assisted Intervention purpose need to take into account that transportation itself is a stressful experience for the animals.

In the dairy cattle sector, the evaluation of the effects induced by heat stress is still one of the most impactful and investigated aspects as it is strongly connected to both sustainability of the production and animal welfare. On the other hand, more recently, the possibility of collecting large dataset made available by the increasing technology diffusion is paving the way for the application of advanced numerical techniques based on machine learning or big data approaches. In this scenario driven by rapid change there could be the risk of dispersing the relevant information represented by the physiological animal component, which should maintain the central role in the development of numerical models and tools. In the light of this, the present literature review aims to consolidate and synthesize existing research on the physiological consequences of heat stress in dairy cattle. The present review provides, in a single document, an overview as complete as possible of the heat stress-induced responses in dairy cattle with the intent of filling the existing research gap for extracting the veterinary knowledge present in the literature and make it available to those who are developing numerical models and tools.

Numerous studies have shown that quinolones residues in the foods exceeding the MRL is harmful to the human health. There are some limitations in the existing methods for the residues, so we developed a new limit test method (TLC-SERS) to rapidly determine following residues: enrofloxacin(A), ciprofloxacin (B), ofloxacin(C), fleroxacin(D), sparfloxacin(E), enoxacin(F), gatifloxacin(G) and nadifloxacin(H). The residues can be preliminarily separated by TLC. Labeling the tested compounds’ position on the thin layer plate by their relative Rf under 254nm ultraviolet, and an appropriate amount of nanometer silver solution should be added to the position. The silver on the plate should be irradiated with 532nm laser to obtain SERS of the compounds. The results showed a significant differences of the 8 quinolones’ SERS; the LOD of the H, A, D, E, C, G, F and B were orderly 9.0, 12.6, 8.0, 19.0, 8.0, 8.4, 9.0 and 12.6 ng/mL, and the RSD≤4.9% for SERS of each quinolones.The limit test results of the 20 samples was consistent with that determined by the UPLC–MS/MS. The above results indicate that the TLC-SERS is specific, sensitive, stable, and accurate, providing a new reference for the rapid limit test of harmful residues in foods.

The identification and quantitative determination of wool and fine animal fibers are of great interest in the textile field because of significant price differences between them and common adulterations in raw and processed textiles. Since animal fibers have remarkable similarities in their chemical and physical characteristics, specific identification methods have been studied and proposed following advances in analytical technologies. The identification methods of wool and fine animal fibers are reviewed in this paper and the results of relevant studies are listed and summarized, starting from classical microscopy methods which are still used today not only in Small to Medium Enterprises but also in large industries, research studies and quality control laboratories. Particular attention has been paid to image analysis, Nir spectroscopy and proteomics which constitute the most promising technologies of quality control in the manufacturing and trading of luxury textiles and can find application in forensic science and archeology.

The ongoing emergence of SARS-CoV-2 virus variants remains a source of concern because it is accompanied by the potential for increased virulence as well as evasion of immunity. Here we show that, although having an almost identical spike gene sequence as another Omicron variant (BA.5.2.1), a BA.4 isolate lacked all the typical disease characteristics of other isolates seen in the Golden Syrian hamster model despite replicating almost as effectively. Animals infected with BA.4 had similar viral shedding profiles to that seen with BA.5.2.1 (up to day 6 post infection) but they all failed to lose weight or present with any other significant clinical signs. We hypothesize that this lack of detectable signs of disease during infection with BA.4 was due to a small (nine nucleotide) deletion (∆686-694) in the viral genome (ORF1ab) responsible for production of non-structural protein 1 which resulted in the loss of three amino acids (aa 141-143).

The Golden Syrian hamster (Mesocricetus auratus) is now commonly used in preclinical research for the study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the assessment of vaccines, drugs and therapeutics. Here we show that hamsters inoculated via the intranasal route with the same infectious virus dose of prototypical SARS-CoV-2 administered in a different volume present with different clinical signs, weight loss and viral shedding, with a reduced volume resulting in reduced severity of disease similar to that obtained by a 500-fold reduction in challenge dose. The tissue burden of virus and the severity of pulmonary pathology were also significantly affected by different challenge inoculum volumes. These findings suggest that direct comparison between the severity of SARS-CoV-2 variants or studies assessing the efficacy of treatments determined by hamster studies cannot be made unless both the challenge dose and inoculation volume are matched when using the intranasal route. Additionally, analysis of sub-genomic and total genomic RNA PCR data demonstrated no link between sub-genomic and live viral titres and that sub-genomic analyses do not provide any information beyond that provided by more sensitive total genomic PCR.

The number of animals bred, raised, and slaughtered each year is on the rise, resulting in increasing impacts to welfare. Farmed animals are also becoming more diverse, ranging from pigs to bees. The diversity and number of species farmed invites questions about how best to allocate currently limited resources towards safeguarding and improving welfare. This is of the utmost concern to animal welfare funders and effective altruism advocates, who are responsible for targeting the areas most likely to cause harm. For example, is tail docking worse for pigs than beak trimming is for chickens in terms of their pain, suffering, and general experience? Or are the welfare impacts equal? Answering these questions requires making an interspecies welfare comparison; a judgment about how good or bad different species fare relative to one another. Here, we outline and discuss an empirically-based methodology that aims to improve our ability to make interspecies welfare comparisons by investigating welfare range, which refers to how good or bad animals can fare. We begin our proposal with a theory of welfare. We operationalize that theory of welfare by identifying metrics that are defensible proxies for measuring welfare, including cognitive, affective, behavioral, and neuro-biological measures. We assign differential weights to those proxies that reflect their evidential value for the determinants of welfare, such as the “Delphi'' structured deliberation method with a panel of experts. Then we review the evidence and score its quality to ascertain whether a particular taxa may possess the proxies in question to construct a taxa-level welfare range profile. Finally, we use a Monte Carlo simulation to generate an overall estimate of comparative welfare range relative to our hypothetical index species - humans. Interspecies welfare comparisons will help facilitate empirically informed decision-making to streamline the allocation of resources and to ultimately better prioritize and improve animal welfare.

In order to analyse asymmetries between hemimandibles, a sample of 24 mandibles from ferrets was studied by means of geometric morphometric methods, using a set of 3 landmarks and 14 semilandmarks, on the lateral aspect. Results showed that both size and shape played a significative role in mandibular asymmetry. For shape, there appeared significative fluctuating and directional asymmetries, with an especially high level for this latter. Landmarks corresponding to muscular attachments showed greater landmark asymmetry. This it is supported the hypothesis of a chewing side preference, e.g., a mastication-related driver for mandibular shape asymmetry.

Medical and translational scientific research requires the use of animal models as an initial approach to the study of new therapies and treatments, but when the objective is an exploration of translational potentialities, classical models fail to adequately mimic problems in humans. Among the larger animal models that have been explored more intensely in recent decades, small ruminants, namely sheep and goats, have emerged as excellent options. The main advantages associated to the use of these animals in research works are related to their anatomy and dimensions very similar to those of humans in most physiological systems, in addition to their low maintenance and feeding costs, tendency to be docile, long life expectancies and few ethical complications raised in society. The most obvious disadvantages are the significant differences in some systems such as the gastrointestinal, and the reduced amount of data that limits the comparison between works and the validation of the characterization essays. Despite everything, recently these species have been increasingly used as animal models for diseases in different systems, and the results obtained open doors for their more frequent and advantageous use in the future. The purpose of this review is to summarize the general principles related to the use of small ruminants as animal models, with focus on regenerative medicine, to group the most relevant works and results published recently and to highlight the potentials for the near future in medical research.

A novel coronavirus has been reported as the causative pathogen of the Coronavirus disease 2019 (COVID-19) outbreak Wuhan city, China in December 2019. Due to the rapid spreading of COVID-19 worldwide, it has been announced as a pandemic by the World Health Organization (WHO). Hospitalized patients in Wuhan are associated with the Huanan seafood wholesale market where live animals, such as poultry, bats, snakes, frogs, rabbits, marmots, and hedgehogs are sold in that market which suggests a possible zoonotic infection. Therefore, it is essential to identify the potential animal reservoir, and the possibility of infection for other animal species. This short review aims to provide an overview on the relation between severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) infection and animals.

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

Alternative fertilizations are essential to minimize the deteriorating effects of chemical fertilizers on soil and water quality/health. Accordingly, the present work investigated the effects of combined organic-inorganic fertilization (COIF) on wheat and rice yields, soil nutrients, and soil Cd accumulation. Hence, seven different treatments were set up: control (CK); conventional fertilization (CF); optimized fertilization (OF); organic fertilizer replacing 25% (T1) and 50% (T2) of OF; and organic nitrogen (N) replacing 25% (M1) and 50% (M2) of OF-N. Overall, significant increases occurred in the yields of COIF crops. Compared with the CF, the highest wheat and rice yields happened in M1 treatment (approximately by18.5%) (P &lt; 0.05). COIF slightly alleviated soil acidification, and improved the cation exchange capacity (CEC) of the study soils. Besides, COIF treatments significantly increased the contents of total phosphorus, total potassium, available phosphorus, and available potassium by 6.35 to 16.9 %, 3.17 to 10.9 %, 5.53 to 28.7 %, and 2.6 to 12 %, respectively (P &lt;0.05). Nevertheless, negligible increases took place in Cd content of COIF soils compared with the CK. Altogether, our results concluded on 25% replacement of OF-N by organic N (M1) to effectively improve the fertility/ecological sustainability of the study soils.

Endophytic fungi (EF) have emerged as promising modulators of plant growth and stress tolerance in agricultural ecosystems. This review synthesizes current knowledge on the role of EF in en-hancing crop adaptation to abiotic stress. Abiotic stresses, such as drought, salinity, and extreme temperatures, pose significant challenges to crop productivity worldwide. EF have shown re-markable potential in alleviating the adverse effects of these stresses. Through various mechanisms including synthesis of osmolytes, production of stress-related enzymes, and induction of plant de-fense mechanisms, EF enhance plant resilience to abiotic stressors. Moreover, EF promote nutrient uptake and modulate hormonal balance in plants, further enhancing stress tolerance. Recent ad-vancements in molecular techniques have facilitated the identification and characterization of stress-tolerant endophytic fungal strains, paving the way for their utilization in agricultural prac-tices. Furthermore, the symbiotic relationship between EF and plants offers ecological benefits, such as improved soil health and reduced dependence on chemical inputs. However, challenges remain in understanding the complex interactions between EF and host plants, as well as in scaling up their application in diverse agricultural systems. Future research should focus on elucidating the mechanisms underlying endophytic fungal-mediated stress tolerance and developing sustainable strategies for harnessing their potential in crop production.

Côte d’Ivoire has substantially neglected crop residues from farms in rural areas. This study aims to provide strategies for the sustainable conversion of crop residues to hydrogen. Using existing data and theoretical approaches, up to 16,801,306 tons of crop residues of 11 crop types were available in Côte d’Ivoire in 2019. A theoretical hydrogen potential of 1,296,424.84 tons was estimated from the crop residues. Technically, 907,497.39 tons of hydrogen is expected annually. Three scenarios of hydrogen project implementation developed indicated that the Ivorian industries can be supplied with 9,026,635 gigajoules of heat. Moreover, 17,910 cars and 4,732 buses can be supported in the transport sector. It is estimated that 817,293.95 tons of green ammonia for farmers can be supplied. Five million, seven hundred twenty-seven thousand, nine hundred ninety-two (5,727,992) households are expected to have access to 1,718.40 gigawatts of electricity. Due to these changes in transport, energy, industry, and agricultural sectors, a reduction of 1,644,722.08 tons of carbon dioxide per year can be achieved theoretically. With the scenarios, some 263,276.87 tons of hydrogen are exportable to other countries. Conversion of crop residues to hydrogen is a promising opportunity with environmental and socio-economic impact. Therefore, this study requires further extensive research.

Mesoporous silica nanoparticles (MSNs) can be used as carrier materials for the controlled release of pesticides while reducing their negative environmental impact. In this study, we screened an active ingredient, p-cymene (PC), with an excellent inhibitory effect on rice bacterial blight. Subsequently, the PC was successfully loaded onto MSNs via physisorption(PC@MSNs). PC@MSNs, characterized by a regular spherical shape, smooth surface, and an MSN average size of 262.9 nm, achieved an 8.6 % drug loading capacity. The release kinetics of the PC from the PC@MSNs demonstrated a sustained release (288 h) pattern influenced by drug diffusion. The efficacy of the PC@MSNs against Xanthomonas oryzae pv. Oryzae paralleled those of PC. Acute toxicity assays re-vealed that the PC@MSNs were less toxic to aquatic life (LC50=257.867 mg/L) and that the formu-lation showed no adverse effects on rice seedling growth. In summary, these results suggest that PC@MSNs can broaden PC's application scope in managing rice diseases.

During the 1950s, the Gros Michel species of bananas were nearly wiped out by the incurable Fusarium Wilt, also known as Panama Disease. Originating in Southeast Asia, Fusarium Wilt is a banana pandemic that has been threatening the multi-billion-dollar banana industry worldwide. The disease is caused by a fungus that spreads rapidly throughout the soil and into the roots of banana plants. Currently, the only way to stop the spread of this disease is for farmers to manually inspect and remove infected plants as quickly as possible, whereas it is a time-consuming process. The main purpose of this study is to build a deep Convolutional Neural Network (CNN) using a transfer learning approach to rapidly identify fusarium wilt infections on banana crop leaves. We chose to use the ResNet50 architecture as the base CNN model for our transfer learning approach owing to its remarkable performance in image classification, which was demonstrated through its victory in the ImageNet competition. After its initial training and fine-tuning on a data set consisting of 300 healthy and diseased images, the CNN model achieved near-perfect accuracy of 0.99 and was fine-tuned to adapt the ResNet base model. ResNet50’s distinctive residual block structure could be the reason behind these results. To evaluate this CNN model, 500 test images, consisting of 250 diseased and healthy banana leaf images, were classified by the model. The deep CNN model was able to achieve an accuracy of 0.98 and an F-1 score of 0.98 by correctly identifying the class of 492 of the 500 images. These results show that this DCNN model outperforms existing models such as Sangeetha et al., 2023’s deep CNN model by at least 0.07 in accuracy and is a viable option for identifying Fusarium Wilt in banana crops.

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.

Plant roots host various microorganisms around and inside their roots, known as the root microbiome. To become healthy and productive, plants should keep under surveillance niches around the roots to recognize disease-causing microbes and similarly exploit the services of beneficial microorganisms in nutrient acquisition, stress mitigation and growth promotion. Here we presented the communication strategies between plant roots and root-associated microbes in improving plant growth and yield. Understanding how plant root and root-associated microbes communicate is vital in designing ecofriendly strategies for targeted disease suppression and improved plant growth that will help in sustainable agriculture.