Search Results (544)

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

Durum wheat, the world’s second most cultivated wheat species, is a staple crop, critical for global food security, including in Ethiopia where it serves as a center of diversity. However, climate change and genetic erosion threaten its genetic resources, necessitating genomic studies to support conservation and breeding efforts. This study characterized genome-wide diversity, population structure (STRUCTURE, principal coordinate analysis (PCoA), neighbor-joining trees, analysis of molecular variance (AMOVA)), and selection signatures (F_ST, Hardy–Weinberg deviations) in Ethiopian durum wheat by analyzing 376 genotypes (148 accessions) using an Illumina Infinium 25K single nucleotide polymorphism (SNP) array. A set of 7842 high-quality SNPs enabled the assessments, comparing landraces with cultivars and breeding populations. Results revealed moderate genetic diversity (mean polymorphism information content (PIC) = 0.17; gene diversity = 0.20) and identified 26 loci under selection, associated with key traits like grain yield, stress tolerance, and disease resistance. AMOVA revealed 80.1% variation among accessions, with no significant differentiation by altitude, region, or spike density. Landraces formed distinct clusters, harboring unique alleles, while admixture suggested gene flow via informal seed exchange. The findings highlight Ethiopia’s rich durum wheat diversity, emphasizing landraces as reservoirs of adaptive alleles for breeding. This study provides genomic insights to guide conservation and the development of climate-resilient cultivars, supporting sustainable wheat production globally. Full article

Climate change presents urgent and complex challenges to agricultural sustainability and food security, particularly in regions reliant on resource-intensive staple crops. Smart agriculture—through the integration of crop modeling, satellite remote sensing, and artificial intelligence (AI)—offers data-driven strategies to enhance productivity, optimize input use, and mitigate greenhouse gas (GHG) emissions. This study introduces Farmdee-Mesook, a mobile-first smart agriculture platform designed specifically for Thai rice farmers. The platform leverages AquaCrop simulation, open-access satellite data, and localized agronomic models to deliver real-time, field-specific recommendations. Usability-focused design and no-cost access facilitate its widespread adoption, particularly among smallholders. Empirical results show that platform users achieved yield increases of up to 37%, reduced agrochemical costs by 59%, and improved water productivity by 44% under alternate wetting and drying (AWD) irrigation schemes. These outcomes underscore the platform’s role as a scalable, cost-effective solution for operationalizing climate-smart agriculture. Farmdee-Mesook demonstrates that digital technologies, when contextually tailored and institutionally supported, can serve as critical enablers of climate adaptation and sustainable agricultural transformation. Full article

Cassava is the sixth most important food crop and is cultivated in more than 100 countries. The crop tolerates low soil fertility and drought, enabling it to play a role in climate adaptation strategies. Cassava generally requires careful preparation to remove toxic hydrogen cyanide (HCN) before its consumption, but HCN concentrations can vary considerably between varieties. Climate change and low inputs, particularly carbon and nutrients, affect agriculture in Pacific Island countries where cassava is commonly grown alongside traditional crops (e.g., taro). Despite increasing popularity in this region, there is limited experimental data about cassava crop management for different local varieties, their relative toxicity and nutritional value for human consumption, and their interaction with changing climate conditions. To help address this knowledge gap, three field experiments were conducted at the Koronivia Research Station of the Fiji Ministry of Agriculture. Two varieties of cassava with contrasting HCN content were planted at three different times coinciding with the start of the wet (September-October) or dry (April) seasons. A time series of measurements was conducted during the full 18-month or differing 6-month durations of each crop, based on destructive harvests and phenological observations. The former included determination of total biomass, HCN potential, carbon isotopes (δ¹³C), and elemental composition. Yield and nutritional value were significantly affected by variety and time of planting, and there were interactions between the two factors. Findings from this work will improve cassava management locally and will provide a valuable dataset for agronomic and biophysical model testing. Full article

Rice is one of the most important staple foods worldwide. Asia, particularly South and Southeast Asia, is a major rice producer, and rice production is also gradually increasing in Africa. However, rice cultivation poses economic and environmental challenges, which are exacerbated by climate change. Hence, diversification of rice-based production systems is highly imperative to improve soil health and thus sustain productivity while also enhancing income opportunities. Vegetables and pulses are crucial components for diversifying rice-based production systems as they have the potential to increase income and improve soil health. The World Vegetable Center has introduced mungbeans and vegetable soybeans to diversify the cereal-based production systems in Asia. About 27–93% of the mungbean area in India, Pakistan, Bangladesh, and Myanmar is planted with varieties containing improved germplasm developed by WorldVeg in collaboration with national agricultural research systems. Additionally, the introduction of vegetables and legumes is highly remunerative and improves dietary diversity, leading to better nutrition. For instance, the productivity of vegetable crops increased by 200–350% when they were combined with improved production practices. Such diversification also holds great promise for improving income and nutrition in Africa. It also enhances the resilience of farming systems, particularly in a changing climate. Hence, governments should prioritize system diversification to enhance the income and livelihood opportunities for smallholders in Asia and Africa. Full article

Iron deficiency is a widespread public health concern, particularly in regions where rice (Oryza sativa) and beans (Phaseolus spp.) are staple foods with naturally low bioavailable iron content. Agronomic biofortification is a practical strategy to increase micronutrient levels in crops through soil, foliar, and seed-based fertilization techniques. This review synthesizes scientific studies published between 2014 and 2024 that evaluated the effectiveness of agronomic iron biofortification methods in rice and beans. The results demonstrate that site-specific interventions, such as the selection of iron sources and application methods, can improve iron concentration in grains and contribute to more nutritious and resilient food systems. However, challenges remain. There is limited information about human iron bioavailability, and the response to fertilization varies depending on soil and environmental conditions. To address these gaps, future research should include bioavailability assessments and field validation. Even so, integrating iron biofortification into standard fertilization practices is a promising approach to improve food quality and combat hidden hunger in vulnerable populations. Full article

Cassava (Manihot esculenta) is a vital tropical staple crop with expanding relevance beyond food security, particularly in developing functional beverages and nutraceutical products. This review discusses the implications of selected chemicals in cassava roots for beverage production, notably cyanogenic glycosides and phenolic compounds. We further highlight the role of cassava as a substrate for beverage production, the nutritional significance of cassava-based beverages, and the health benefits and functional potential of cassava as a key ingredient in beverage production. We also discuss the probiotic and prebiotic properties and the antioxidant activity of chemicals in cassava-based beverages for health benefits. Additionally, we review the challenges, opportunities, and innovations regarding commercialization. Full article

Rice is a staple food for over half of the world’s population, and it is grown in over 100 countries. Rice blast disease can cause 10% to 30% crop loss, enough to feed 60 million people. Breeding for resistance can help farmers avoid costly fungicides. This study assessed the relationship between rice blast disease and zinc or anthocyanin content in biofortified rice. Susceptibility to foliar and panicle blast was assessed in a rice panel which differed on grain zinc content and pigmentation. A rice panel (n = 23) was challenged with inoculum of two isolates of Magnaporthe oryzae in a screenhouse-based assay. The zinc content with foliar blast severity was analyzed in the leaves and grain of a subset of non-inoculated rice plants. The effect of foliar zinc supplementation on seedlings was assessed by varying levels of zinc fertilizer solution on four blast susceptible cultivars at 14 days after planting (DAP), followed by inoculation with the blast pathogen at 21 DAP. Foliar blast severity was scored on a 0–9 scale at 7 days after inoculation. The rice panel was scored for anthocyanin content, and the data were correlated with foliar blast severity. The panel was grown in the field, and panicle blast, grain yield and yield-related agronomic traits were measured. Significant differences were observed in foliar blast severity among the rice genotypes, with IRBLK-KA and IR96248-16-2-3-3-B having mean scores greater than 4, as well as BASMATI 370 (a popular aromatic variety), while the rest of the genotypes were resistant. Supplementation with foliar zinc led to a significant decrease in susceptibility. A positive correlation was observed between foliar and panicle blast. The Zn in the leaves was negatively correlated with foliar blast severity, and had a marginally positive correlation with panicle blast. There was no relationship between foliar blast severity and anthocyanin content. Grain yield had a negative correlation with panicle blast, but no correlation was observed between Zn in the grain and grain yield. This study shows that Zn biofortification in the grain may not enhance resistance to foliar and panicle blast. Furthermore, the zinc-biofortified genotypes were not agronomically superior to the contemporary rice varieties. There is a need to apply genomic selection to combine promising alleles into adapted rice genetic backgrounds. Full article

Aflatoxins, toxic secondary metabolites produced primarily by Aspergillus flavus and Aspergillus parasiticus, pose significant risks to food safety, public health, and global trade. These mycotoxins contaminate staple crops such as maize and peanuts, particularly in warm and humid regions, leading to economic losses and severe health effects, including hepatocellular carcinoma, immune suppression, and growth impairment. In addition to aflatoxins, Aspergillus species produce other toxic metabolites such as ochratoxin A, sterigmatocystin, and cyclopiazonic acid, which are associated with nephrotoxic, carcinogenic, and neurotoxic effects, respectively. This review provides a comprehensive analysis of aflatoxin toxicity, mitigation strategies, and chemical detection methods. The toxicity of aflatoxins is discussed in relation to their biochemical mechanisms, carcinogenicity, and synergistic effects with other mycotoxins. Various mitigation approaches, including pre-harvest biocontrol, post-harvest storage management, and novel detoxification methods such as enzymatic degradation and nanotechnology-based interventions, are evaluated. Furthermore, advances in aflatoxin detection, including chromatographic, immunoassay, and biosensor-based methods, are explored to improve regulatory compliance and food safety monitoring. This review underscores the need for integrated management strategies and global collaboration to reduce aflatoxin contamination and its associated health and economic burdens. Future research directions should focus on genetic engineering for resistant crop varieties, climate adaptation strategies, and improved risk assessment models. Full article

Sustainable agriculture and food security are challenged by the indiscriminate use of synthetic nitrogen (N₂) fertilizers, inefficient water management, and land degradation. Hydroponic cultivation uses nutrient-rich aqueous media and is a climate-resilient and resource-efficient alternative to traditional farming methods, whose dependence on synthetic N₂ fertilizers reduces their long-term sustainability. Biological nitrogen fixation (BNF), which is mediated by diazotrophs that reduce atmospheric N₂ to plant-available ammonium, has emerged as a sustainable alternative to synthetic N₂ input in hydroponic systems. This review discusses the integration of BNF into hydroponic systems by exploring the functional diversity of diazotrophs, root–microbe interactions, and environmental constraints. It further highlights recent advances in strain improvement, microbial consortia development, nitrogenase protection, and genome editing tools, novel bioformulation strategies to enhance microbial compatibility with hydroponic nutrient regimes, and omics-based tools for the real-time assessment of N₂ fixation and microbial functionality. Key challenges, such as microbial leaching, nitrate-induced inhibition of nitrogenase activity, and the absence of standardized biostimulant protocols, are discussed. Case studies on staple crops have demonstrated enhanced NUE and yield productivity following diazotroph applications. This review concludes with future perspectives on synthetic biology, regulatory policies, and omics-based tools for the real-time assessment of N₂ fixation and microbial functionality. Full article

Farm household pluriactivity has become increasingly prevalent in China; however, its influence on crop structure remains insufficiently explored. This study examines the impact of farm household pluriactivity on crop structure in China, focusing on factor input mechanisms. Based on survey data from 473 farm households in Sichuan Province, this study employs ordinary least squares (OLS), two-stage least squares (2SLS), and mediation analyses to systematically assess the impact of pluriactivity on crop structure through factor input mechanisms. The analysis reveals three key findings. First, rather than reducing the grain planting area, an increase in part-time farming is associated with a significant rise in the proportion of grain cultivation. Second, factor inputs partially mediate this relationship: while pluriactivity tends to reduce staple crop cultivation through mechanisms such as cultivated land transfer-out, land abandonment, and increased non-agricultural labor input, it simultaneously promotes staple crop expansion via enhanced agricultural technical services. Third, heterogeneity tests indicate that the positive effect of pluriactivity on staple crop cultivation is especially pronounced among households in hilly areas and those that have adopted agricultural insurance. These findings provide valuable policy insights for fostering sustainable agricultural transitions and enhancing food security in developing regions. Full article

Rice is one of the three primary staple crops worldwide. The accurate monitoring of its key growth stages is crucial for agricultural management, disaster early warning, and ensuring food security. The effective collection of ground reference data is a critical step for monitoring rice growth stages using satellite imagery, traditionally achieved through labor-intensive field surveys. Here, we propose utilizing UAVs as an alternative means to collect spatially continuous ground reference data across larger areas, thereby enhancing the efficiency and scalability of training and validation processes for rice growth stage mapping products. The UAV data collection involved the Nanchuan, Yongchuan, Tongnan, and Kaizhou districts of Chongqing City, encompassing a total area of 377.5 hectares. After visual interpretation, centimeter-level high-resolution labels of the key rice growth stages were constructed. These labels were then mapped to Sentinel-2 imagery through spatiotemporal matching and scale conversion, resulting in a reference dataset of Sentinel 2 data that covered growth stages such as jointing and heading. Furthermore, we employed 30 vegetation index calculation methods to explore 48,600 spectral band combinations derived from 10 Sentinel-2 spectral bands, thereby constructing a series of novel vegetation indices. Based on the maximum relevance minimum redundancy (mRMR) algorithm, we identified an optimal subset of features that were both highly correlated with rice growth stages and mutually complementary. The results demonstrate that multi-feature modeling significantly enhanced classification performance. The optimal model, incorporating 300 features, achieved an F1 score of 0.864, representing a 2.5% improvement over models based on original spectral bands and a 38.8% improvement over models using a single feature. Notably, a model utilizing only 12 features maintained a high classification accuracy (F1 = 0.855) while substantially reducing computational costs. Compared with existing methods, this study constructed a large-scale ground-truth reference dataset for satellite imagery based on UAV observations, demonstrating its potential as an effective technical framework and providing an effective technical framework for the large-scale mapping of rice growth stages using satellite data. Full article

Maize (Zea mays L.) is one of the most important staple food crops globally. One-third of global maize production is located in areas with high or extreme water scarcity and concurrently faces the challenge of low nitrogen use efficiency. Therefore, achieving synergistically high-efficiency water and nitrogen utilization in maize production is of great significance for agricultural sustainable development and global food security. In recent years, more articles have focused on the physiological mechanisms and management practices of efficient water and nitrogen utilization in maize. Unfortunately, there is a relative scarcity of research on the interactive effects between water and nitrogen on the development of young ears, which plays a crucial role in maize productivity. By compiling the most pertinent publications, this review endeavors to consolidate the existing knowledge on the interactive effects between water and nitrogen on maize production. Moreover, it advances potential physiological mechanisms and strategies for high-efficiency water and nitrogen utilization in terms of root system functioning, phytohormones, metabolism, and organ development. The changes in the availability of water and nitrogen have a significant impact on the development of young ears during the critical period, which in turn directly determines the grain number per ear and grain weight. Full article

Potatoes, as the world’s fourth-largest staple crop, are vital for global food security. Efficient methods for assessing yield and quality are essential for policy-making and optimizing production. Traditional yield assessment techniques remain destructive, labor-intensive, and unsuitable for large-scale monitoring. While remote sensing has offered a promising alternative, current approaches largely depend on empirical correlations rather than physiological mechanisms. This limitation arises because potato tubers grow underground, rendering their traits invisible to aboveground sensors. This study investigated the mechanisms underlying hyperspectral remote sensing for assessing belowground yield traits in potatoes. Field experiments with four cultivars and five nitrogen treatments were conducted to collect foliar biochemistries (chlorophyll, nitrogen, and water and dry matter content), yield traits (tuber yield, fresh/dry weight, starch, protein, and water content), and leaf spectra. Two approaches were developed for predicting belowground yield traits: (1) a direct method linking leaf spectra to yield via statistical models and (2) an indirect method using structural equation modeling (SEM) to link foliar biochemistry to yield. The SEM analysis revealed that foliar nitrogen exhibited negative effects on tuber fresh weight (path coefficient b = −0.57), yield (−0.37), and starch content (−0.30). Similarly, leaf water content negatively influenced tuber water content (0.52), protein (−0.27), and dry weight (−0.42). Conversely, chlorophyll content showed positive associations with both tuber protein (0.59) and dry weight (0.56). Direct models (PLSR, SVR, and RFR) achieved higher accuracy for yield (R² = 0.58–0.84) than indirect approaches (R² = 0.16–0.45), though the latter provided physiological insights. The reduced accuracy in indirect methods primarily stemmed from error propagation within the SEM framework. Future research should scale these leaf-level mechanisms to canopy observations and integrate crop growth models to improve robustness across environments. This work advances precision agriculture by clarifying spectral–yield linkages in potato systems, offering a framework for hyperspectral-based yield prediction. Full article