Search Results (1,298)

Cassava (Manihot esculenta Crantz) is essential for global food security, especially in tropical regions. As an important genetic resource, its genetics plays a key role in crop breeding, enabling the development of more productive and pest- and disease-resistant varieties. Scientometrics, which quantitatively analyzes the production and impact of scientific research, is crucial for understanding trends in cassava genetics. This study aimed to apply bibliometric methods to conduct a scientific mapping analysis based on yearly publication trends, paper classification, author productivity, journal impact factor, keywords occurrences, and omic approaches to investigate the application of genetics to the species from 1960 to 2022. From the quantitative data analyzed, 3246 articles were retrieved from the Web of Science platform, of which 654 met the inclusion criteria. A significant increase in scientific production was observed from 1993, peaking in 2018. The first article focused on genetics was published in 1969. Among the most relevant journals, Euphytica stood out with 36 articles, followed by Genetics and Molecular Research (n = 30) and Frontiers in Plant Science (n = 25). Brazil leads in the number of papers on cassava genetics (n = 143), followed by China (n = 110) and the United States (n = 75). The analysis of major methodologies (n = 185) reveals a diversified panorama during the study period. Morpho-agronomic descriptors persisted from 1978 to 2022; however, microsatellite markers were the most widely used, with 102 records. Genomics was addressed in 87 articles, and transcriptomics in 65. By clarifying the current landscape, this study supports cassava conservation and breeding, assists in public policy formulation, and guides future research in the field. Full article

Soybean (Glycine max (L.) Merrill) is a major oilseed crop rich in phytosterols and tocopherols, compounds associated with functional and nutritional properties of vegetable oils. This study aimed to apply, for the first time, Independent Component Analysis (ICA) to discriminate the composition of phytosterols (β-sitosterol, campesterol, stigmasterol) and tocopherols (α, β, γ, δ) in 20 soybean genotypes—14 non-transgenic and six transgenic—cultivated in two major producing regions of Paraná state, Brazil (Londrina and Ponta Grossa). Lipophilic compounds were extracted from soybean seeds, quantified via gas chromatography and HPLC, and statistically analyzed using ICA with the JADE algorithm. The extracted independent components successfully differentiated soybean varieties based on phytochemical profiles. Notably, transgenic cultivars from Ponta Grossa exhibited higher levels of total tocopherols, including α- and β-tocopherol, while conventional cultivars from both regions showed elevated phytosterol content, particularly campesterol and stigmasterol. ICA proved to be a powerful unsupervised method for visualizing patterns in complex compositional data. These findings highlight the significant influence of genotype and growing region on the nutraceutical potential of soybean, and support the use of multivariate analysis as a strategic tool for cultivar selection aimed at enhancing functional quality in food applications. Full article

Legumes are among the most important crops globally, serving as a major food source for protein and oil. In tropical regions, the cultivation of legumes has expanded significantly due to the increasing demand for food, plant-based products, and sustainable agriculture practices. However, tropical environments pose unique challenges, including high temperatures, erratic rainfall, soil infertility, and a high incidence of pests and diseases. Indeed, legumes are vulnerable to infections caused by bacteria, fungi, oomycetes, viruses, and nematodes. This review highlights the importance of legumes in tropical farming and discusses major diseases affecting productivity and their impact on the economy, environment, and lives of smallholder legume farmers. We emphasize the use of legume genetic resources and breeding, and biotechnology innovations to foster resistance and address the challenges posed by pathogens in legumes. However, an integrated approach that includes other cultivation techniques (e.g., crop rotation, rational fertilization, deep plowing) remains important for the prevention and control of diseases in legume crops. Finally, we highlight the contributions of plant genetic resources to smallholder resilience and food security. Full article

Achieving food security for a growing population under a changing climate is a key concern in Senegal, where agriculture employs 77% of the workforce with a majority of small farmers who rely on the production of crops for their subsistence and for income generation. Moreover, due to the underproductive soils and variable rainfall, Senegal depends on imports to fulfil 70% of its food requirements. In this research, we considered four crops that are crucial for Senegalese agriculture: millet, sorghum, peanuts and rice. We used crop simulation models to explore existing yield gaps and optimal agronomic practices. Improving the N fertilizer management in sorghum and millet resulted in 40–100% increases in grain yields. Improved N symbiotic fixation in peanuts resulted in yield increases of 20–100% with highest impact in wetter locations. Optimizing irrigation management and N fertilizer use resulted in 20–40% gains. The best N fertilizer strategy for sorghum and millet included applying low rates at sowing and in early development stages and adjusting a third application, considering the expected rainfall. Peanut yields of the variety 73-33 were higher than Fleur-11 in all locations, and irrigation showed no clear economic advantage. The best N fertilizer management for rainfed rice included applying 30 kg N/ha at sowing, 25 days after sowing (DAS) and 45 DAS. The best combination of sowing dates for a possible double rice crop depended on irrigation costs, with a first crop planted in January or March and a second crop planted in July. Our work confirmed results obtained in field research experiments and identified management practices for increasing productivity and reducing yield variability. Those crop management practices can be implemented in pilot experiments to further validate the results and to disseminate best management practices for farmers in Senegal. Full article

Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO₂ concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article

Soil salinization is a major environmental constraint that poses a significant threat to global agricultural productivity and food security. Coix lacryma-jobi L., a minor cereal crop that is valued for its nutritional and medicinal properties, displays moderate susceptibility to salinity stress. Although exogenous treatments have been demonstrated to enhance plant resilience against various biotic and abiotic stresses, the potential of nano-silicon (NaSi), melatonin (MT), and their combined application in mitigating salinity-induced damage, particularly in relation to the medicinal properties of this medicinal and edible crop, remains poorly understood. This study investigated the effects of exogenous NaSi and MT application on Coix under salinity stress using two varieties with contrasting salinity tolerances. The plants were subjected to salinity stress and treated with NaSi, MT, or a combination of both. The results revealed that salinity stress significantly impaired the agronomic traits, physiological performance, and accumulation of medicinal compounds of Coix. Exogenous MT application effectively alleviated salinity-induced damage to agronomic and physiological parameters, exhibiting superior protective effects compared to NaSi treatment. Strikingly, the combined application of MT and NaSi demonstrated synergistic effects, leading to substantial improvements in growth and physiological indices. However, the medicinal components were only marginally affected by exogenous treatments under both control and salinity-stressed conditions. Further clarification of the molecular mechanisms underlying salinity stress responses and exogenous substance-induced effects is critical to achieving a comprehensive understanding of these protective mechanisms. Full article

MicroRNA528 (miR528) is a microRNA found only in monocotyledonous (monocot) plants. It has been widely reported that miR528 is involved in the regulation of plant growth and development, such as flowering, architecture, and seed and embryogenic development, in addition to playing a crucial role in response to various biotic and abiotic stresses, such as plant pathogens, salt stress, heat/cold stress, water stress, arsenic stress, oxidative stress, heavy-metal stress, and nutrient stress. Given that it is specific to monocot plants, to which the major staple food crops such as rice and wheat belong, a review of studies investigating its diverse functional roles and underlying mechanisms is presented. This review focuses on the processes in which miR528 and its targets are involved and examines their regulatory relationships with significant participation in plant development and stress responses. It is anticipated that more biological functions and evolutionary effects of miRNA targets will be elucidated with the increase in knowledge of miRNA evolution and examination of target mRNAs. Full article

Cowpea (Vigna unguiculata [L.] Walp) is a vital food security crop in sub-Saharan Africa, including Eswatini. The productivity of the crop is low (<600 kg/ha) in the country due to a lack of improved, locally adapted, and farmer-preferred varieties with biotic and abiotic stress tolerance. The objective of the study was to assess the agronomic performance of newly developed elite cowpea mutants to select best-yielding and adapted pure lines for production and genetic improvement in Eswatini. A total of 30 cowpea genotypes, including 24 newly developed advanced mutant lines, their 3 founder parents and 3 local checks, were profiled for major agronomic traits in two selected sites (Lowveld Experiment and Malkerns Research Stations) using a 6 × 5 alpha lattice design with three replications. A combined analysis of variance revealed that the genotype x location interaction effects were significant (p < 0.05) for germination percentage (DG %), days to flowering (DTF), days to maturity (DMT), number of pods per plant (NPP), pod length (PDL), number of seeds per pod (NSP), hundred seed weight (HSW), and grain yield (GYD). Elite mutant genotypes, including NKL9P7, BRR4P11, SHR9P5, and NKL9P7-2 exhibited higher grain yields at 3158.8 kg/ha, 2651.6 kg/ha, 2627.5 kg/ha, and 2255.8 kg/ha in that order. The highest-yielding mutant, NKL9P7, produced 70%, 61%, and 54% more grain yield than the check varieties Mtilane, Black Eye, and Accession 792, respectively. Furthermore, the selected genotypes displayed promising yield components such as better PDL (varying from 13.1 to 26.3 cm), NPP (15.9 to 26.8), and NSP (9.8 to 16.2). Grain yield had significant positive correlations (p < 0.05) with DG %, NSP, and NPP. The principal component analysis (PCA) revealed that 81.5% of the total genotypic variation was attributable to the assessed quantitative traits. Principal component (PC) 1 accounted for 48.6%, while PC 2 and PC 3 contributed 18.9% and 14% of the overall variation, respectively. Key traits correlated with PC1 were NPP with a loading score of 0.91, NSP (0.83), PDL (0.73), GYD (0.68), HSW (0.58), DMT (−0.60), and DTF (−0.43) in a desirable direction. In conclusion, genotypes NKL9P7, BRR4P11, SHR9P5, NKL9P7-2, Bira, SHR3P4, and SHR2P7 were identified as complementary parents with relatively best yields and local adaptation, making them ideal selections for direct production or breeding. The following traits, NPP, NSP, PDL, GYD, and HSW, offered unique opportunities for genotype selection in the cowpea breeding program in Eswatini. Full article

To promote high-quality agricultural development and implement the “storing grain in the land” strategy, the construction of Well-Facilitated Farmland (WFF) plays a critical role in enhancing grain production capacity and optimizing the spatial distribution of food supply, thereby contributing to national food security. However, accurately assessing the potential impact of WFF construction on China’s grain production and regional self-sufficiency by 2030 remains a significant challenge. Existing studies predominantly focus on the provincial level, while fine-grained analyses at the city level are still lacking. This study quantifies the potential increase in grain production in China under the 2030 WFF construction target by employing effect size analysis, multi-weight prediction, and Monte Carlo simulation across multiple spatial scales (national, provincial, and city levels), thereby addressing the research gap at finer spatial resolutions. By integrating 2030 population projections and applying a grain self-sufficiency calculation formula, it further evaluates the contribution of WFF to regional grain self-sufficiency: (1) WFF could generate an additional 31–48 million tons of grain, representing a 5.26–8.25% increase; (2) grain supply in major crop-producing regions would expand, while the supply–demand gap in balanced regions would narrow; and (3) the number of cities with grain self-sufficiency ratios below 50% would decrease by 11.1%, while those exceeding 200% would increase by 25.5%. These findings indicate that WFF construction not only enhances overall grain production potential but also facilitates a transition from “overall supply-demand balance” to “structural security” within China’s food system. This study provides critical data support and policy insights for building a more resilient and regionally adaptive agricultural system. Full article

Over the past few decades, scientific interest in mycotoxins—fungal metabolites that pose serious concern to food safety, crop health, and both human and animal health—has increased. While major mycotoxins such as aflatoxins, ochratoxins, deoxynivalenol, fumonisins, zearalenone, citrinin, patulin, and ergot alkaloids are well studied, emerging mycotoxins remain underexplored and insufficiently investigated. Among these, moniliformin (MON) is frequently detected in maize-based food and feed; however, the absence of regulatory limits and standardized detection methods limits effective monitoring and comprehensive risk assessment. The European Food Safety Authority highlights insufficient occurrence and toxicological data as challenges to regulatory development. This study compares three analytical methods—CE-DAD, HPLC-DAD, and HPLC-MS/MS—for moniliformin detection and quantification in maize, evaluating linear range, correlation coefficients, detection and quantification limits, accuracy, and precision. Results show that CE-DAD and HPLC-MS/MS provide reliable and comparable sensitivity and selectivity, while HPLC-DAD is less sensitive. Application to real samples enabled deterministic dietary exposure estimation based on consumption, supporting preliminary risk characterization. This research provides a critical comparison that supports the advancement of improved monitoring and risk assessment frameworks, representing a key step toward innovating the detection of under-monitored mycotoxins and laying the groundwork for future regulatory and preventive measures targeting MON. Full article

This study investigates farmers’ knowledge, perceptions, and adaptation strategies to climate change in Rwanda’s Eastern Province, integrating social and physical science approaches. Analyzing meteorological data (1981–2021) and surveys from 204 farmers across five districts, we assessed climate trends and adaptation behaviors using statistical methods (descriptive statistics, Chi-square, logistic regression, Regional Kendall test, dynamic linear state-space model). Results show that 85% of farmers acknowledge climate change, with 54% observing temperature increases and 37% noting rainfall declines. Climate data confirm significant rises in annual minimum (+0.76 °C/decade) and mean temperatures (+0.48 °C/decade), with the largest seasonal increase (+0.86 °C/decade) in June–August. Rainfall trends indicate a non-significant decrease in March–May and a slight increase in September–December. Farmers report crop failures, yield reductions, and food shortages as major climate impacts. Common adaptations include agroforestry, crop diversification, and fertilizer use, though financial limitations, information gaps, and input scarcity impede adoption. Despite limited formal education (53.9% primary, 22.3% no formal education), indigenous knowledge aids seasonal prediction. Farm location, group membership, and farming goal are key adaptation enablers. These findings emphasize the need for targeted policies and climate communication to enhance rural resilience by strengthening smallholder farmer support systems for effective climate adaptation. Full article

Although microplastic pollution has been recognized as one of the major environmental challenges of the 21st century, its toxicological impact on crops, especially vegetables, has attracted limited scientific attention until recently. Vegetables represent a key component of the human diet, making any potential contamination of great importance for food safety. In recent years, an increasing number of studies have been conducted to investigate the interactions between microplastics and vegetable crops. This review aims to synthesize the current knowledge on the sources of microplastics in agroecosystems, the mechanisms of uptake and translocation in plants, and the physiological and biochemical responses induced by micro- and nanoplastics. This work aims to improve the scientific basis for assessing the risk of microplastic contamination by identifying gaps in current understanding and suggesting future research directions. Full article

Insect pests remain a major threat to agricultural productivity, particularly in open-field cropping systems where conventional monitoring methods are labor-intensive and lack scalability. This study presents the design, implementation, and field evaluation of a neural network-guided smart trap specifically developed to monitor and selectively capture nocturnal insect pests under real agricultural conditions. The proposed trap integrates light and rain sensors, servo-controlled mechanical gates, and a single-layer perceptron neural network deployed on an ATmega-2560 microcontroller by Microchip Technology Inc. (Chandler, AZ, USA). The perceptron processes normalized sensor inputs to autonomously decide, in real time, whether to open or close the gate, thereby enhancing the selectivity of insect capture. The system features a removable tray containing a food-based attractant and yellow and green LEDs designed to lure target species such as moths and flies from the orders Lepidoptera and Diptera. Field trials were conducted between June and August 2023 in La Barca, Jalisco, Mexico, under diverse environmental conditions. Captured insects were analyzed and classified using the iNaturalist platform, with the successful identification of key pest species including Tetanolita floridiana, Synchlora spp., Estigmene acrea, Sphingomorpha chlorea, Gymnoscelis rufifasciata, and Musca domestica, while minimizing the capture of non-target organisms such as Carpophilus spp., Hexagenia limbata, and Chrysoperla spp. Statistical analysis using the Kruskal–Wallis test confirmed significant differences in capture rates across environmental conditions. The results highlight the potential of this low-cost device to improve pest monitoring accuracy, and lay the groundwork for the future integration of more advanced AI-based classification and species recognition systems targeting nocturnal Lepidoptera and other pest insects. Full article

Sorghum is a versatile crop that serves as a major source of food, feed, fodder and biofuel globally. Lignin content in sorghum affects multiple important traits, including lodging resistance, forage digestibility and the efficiency of bioenergy production. However, the genetic regulation of lignin content in sorghum remains poorly understood. In this study, we combined transcriptomic and comparative genomic approaches to uncover the genetic network underlying lignin biosynthesis in sorghum. Through comparative genomic analysis, we identified 104 candidate genes involved in lignin biosynthesis. Transcriptome analysis of four sorghum accessions with contrasting lignin contents identified 6132 differentially expressed genes with an enrichment of genes related to phenylpropanoid biosynthesis and cell wall biogenesis. The 104 lignin biosynthesis candidates were significantly enriched (p-value < 0.01) in these differentially expressed genes, with most differentially expressed candidate genes related to monolignol biosynthesis and polymerization being up-regulated in high-lignin accessions. These up-regulated genes are related to all key enzymes involved in lignin biosynthesis, suggesting that the elevated lignin content in these accessions results from a collective increase in enzyme activity. Sequence analysis revealed a significant reduction in genetic diversity across lignin biosynthesis genes in cultivated sorghum compared to wild sorghum. Moreover, selection signals during domestication were identified in 30 lignin biosynthesis genes, 22 of which were differentially expressed, further supporting the functional relevance of these differentially expressed genes in lignin biosynthesis. Overall, our findings uncover the lignin biosynthesis gene network in sorghum and offer potential targets for future functional studies and trait manipulation. Full article