Fusarium poses a significant threat to the global crop productivity and food security. This study evaluated the mechanisms of nanoscale boron nitride (nano-BN, 0-500 mg/kg) against Fusarium oxysporum in cucumber. Fusarium infection severely impaired plant growth with biomass declining by 60%. However, 50 mg/kg nano-BN treatment significantly increased shoot biomass by 64.9% compared to disease controls, restoring photosynthetic parameters to near-healthy levels. Nano-BN inhibited Fusarium proliferation by disrupting hyphal and spore structures and reduced mycotoxin production (beauvericin and enniatin) by over 63%. Metabolomic analysis demonstrates that nano-BN mitigated oxidative stress by enhancing glutathione metabolism, with significant increases in glutathione and ascorbic acid content by 166.67% and 478.78%, respectively. Importantly, the protein-protein interaction network shows that nano-BN counteracted Fusarium-induced suppression of ribosomal proteins and endoplasmic reticulum stress-related proteins, promoting protein synthesis and folding. The coexpression network identified sucrose and geshoidin as key metabolites linked to ribosomal and mitochondrial proteins, bridging metabolic resilience with enhanced disease resistance. Multiomics analysis suggests that nano-BN alleviated the Fusarium stress by regulating the phenylpropanoid biosynthesis and restoring the expression levels of key enzymes in carbohydrate metabolism. Overall, nano-BN effectively mitigates Fusarium stress by enhancing plant growth and modulating metabolic processes, offering a promising strategy for plant protection.

ABSTRACT Land degradation is currently one of the major threats to global food security and ecosystem stability, often leading to diminished soil organic carbon (SOC) and reduced agricultural productivity. Restoring soil health through sustainable practices is, therefore, paramount, with a critical knowledge gap regarding the synergistic mechanisms between the high‐biomass grass Pennisetum hydridum and the nitrogen‐fixing legume Sesbania cannabina , and how nitrogen management optimizes their combined potential to enhance soil carbon sequestration. Soil carbon sequestration is critical for mitigating climate change and improving soil health in agricultural systems. While well‐studied in forests and grasslands, the interactive effects of planting patterns and nitrogen (N) fertilization on carbon dynamics in cultivated farmland require further exploration. This study investigates the influence of N application levels (0, 100, and 200 kg N ha −1 ) and cropping systems on SOC sequestration and its mechanisms. Through integrated pot and field experiments, changes in SOC components, including particulate organic carbon (POC), readily oxidizable organic carbon (ROC), and microbial biomass carbon (MBC) were assessed. Our findings revealed that cultivated soils significantly enhanced all measured carbon fractions compared to abandoned land, with an increase of 16.01% in soil organic matter, 12.94% in total nitrogen, 46.07% in POC, 31.78% in ROC, and 248.59% in MBC. Higher carbon storage capacity was noted under monocropped Pennisetum hydridum , whereas the leguminous Sesbania cannabina (MSc) contributed significantly to nitrogen fixation and labile carbon pools. The intercropping system (IPc‐Sc) synergized these benefits, boosting carbon sequestration by enhancing organic matter input and stabilizing soil structure more effectively than monocropping. Furthermore, N fertilization significantly altered soil enzyme activities, indicating a shift in microbial‐mediated carbon cycling. However, excessive N application (200 kg N ha −1 ) risked accelerating SOC decomposition. This study demonstrates that intercropping P. hydridum with S. cannabina under optimized N fertilization (100 kg N ha −1 ) effectively enhances soil carbon storage, boosts agroecosystem productivity, and promotes sustainable land management.

This paper aims to reflect on the current state of digital transformation in Turkish agriculture and to evaluate the ICT data published by the Turkish Statistical Institute and the Agricultural Outlook Field Surveys published by the Credit Registry Office. One of the important objectives of this study is to measure the level of digital literacy among farmers and to identify the needs and opportunities in this area for agricultural enterprises and present them to relevant stakeholders. In addition, the article discusses the development of digital technologies in agriculture, barriers to the use of ICT, activities, and ongoing initiatives related to the use of ICT. As a result, Turkey has made significant progress in digitalization in the agricultural sector in recent years, with higher-income agricultural enterprises tending to use more ICT. The main barriers to ICT utilization are farmers' technology acceptance dynamics, lack of ICT knowledge, and technology cost. With 91% of farmers owning smartphones and 85% using the internet—numbers that continue to rise—increasing digital literacy enables agricultural enterprises to develop products and services that support participation, efficiency, and sustainability. The most common uses of ICT by farmers are 78% agricultural weather/meteorological information services, 66% agricultural news, and 34% crop/input prices. Digital services that farmers may be interested in, in addition to the existing ones are 35% satellite monitoring of their land, 35% asking agricultural questions via mobile/internet, 17% information about diseases and pests, and 11% agricultural technologies. The integration of young people in the agricultural sector offers an excellent opportunity for the effective use of agricultural technologies. Digitalization of agriculture will ensure global food security, environmental sustainability, combating climate change, creating a more efficient and sustainable agricultural system, as well as economic gain and competitive advantage.

Wheat blast disease, caused by the Triticum pathotype of Magnaporthe oryzae (MoT), poses a significant threat to global food security. The blast resistance gene Rmg8, recently isolated from a hexaploid wheat cultivar, strongly confers resistance to all Bangladeshi and Zambian MoT isolates that carry the eI type of AVR-Rmg8. However, the molecular interactions underlying this recognition at the protein level remain poorly understood. In this study, we elucidated the structural and biological characteristics of RMG8 proteins and their recognition of the AVR-Rmg8 effector proteins using computational biology approaches. Amino acid sequence comparison of four AVR-Rmg8 types revealed that only three amino acid residues distinguish the eI type of AVR-Rmg8, which induces a higher level of resistance conferred by RMG8. The most intriguing finding of this study is that only the eI type effector interacts with ATP through the Pro26 residue, a feature not present in the other AVR-Rmg8 types. We identified that the Protein Kinase C (PKC) domain of RMG8, where proline dependency mediates the phosphorylation of a serine residue, is involved in the strong recognition of the eI type of AVR-Rmg8. Phylogenetic analyses indicated that RMG8 might have evolved from proteins closely associated with plant signaling pathways. Although Rmg8 is an atypical resistance gene, our data suggest that it may function as a hub in the plant defense network, as it is a type of nuclear membrane protein, specifically a calcium-dependent multiple C2 domain protein with transmembrane regions (MCTP) kinase, which integrates signaling for effector recognition. Taken together, our study provides detailed insights into the molecular recognition mechanism between AVR-Rmg8 and RMG8, which is expected to aid in wheat blast resistance breeding. Future studies involving the purification and structural characterization of MoT effector proteins and Rmg8 gene products are necessary to validate these findings.

Abiotic and biotic stresses are major global challenges that reduce plant productivity, quality and sustainability worldwide. These stresses threaten global food security as the human population continues to grow. These stresses threaten global food supply in the current era of increasing population. Stresses negatively affect the normal growth and development of plants. They are mainly divided into 2 groups: abiotic and biotic stress. In particular, abiotic stresses lead to impaired growth and development of plants, disruption of the photosynthesis process and water regime. High temperatures lead to protein denaturation and decreased enzyme activity, while low temperatures lead to membrane damage. Abiotic stressors are one of the primary elements influencing the growth and production of major agricultural income crops. Environmental elements that cause physiological and biochemical pain in plants include salinity, drought, low temperature, heavy metals and chemical pollution. This article examines biotechnological approaches that use modern genetic engineering technologies such as RNA interference (RNAi) and CRISPR/Cas9 systems to improve plant resilience to abiotic stressors. RNAi plays a crucial role in activating plantdefence mechanisms by modulating the expression of stress-responsive genes, whereas CRISPR/Cas9 technology allows for the creation of new, stress-tolerant types by introducing precise alterations in the genome. These biotechnologies have significant potential to develop stable, high-yielding and stress-resilient crops. Overall, this review summarizes recent advances in RNAi and CRISPR/Cas9 technologies for improving plant resilience to abiotic stresses.

The world faces an incredible challenge to produce food in an environmentally sustainable manner. In the next 25 years, almost as much protein must be produced as has been produced in the last 2,000 years. Ruminant animal protein sources are key contributors to essential amino acids and human micronutrient needs. This must be achieved while using less land, having a smaller environmental footprint and while providing greater care for production animals; and this must be accomplished in the face of a more volatile climate. Grazing systems are a significant contributor to global food security, with 10-15% dairy products and more than 30% of red meat produced from grazing animals, and there is a growing consumer trend for ‘grass-fed’ or ‘pasture-raised’ animal products. In New Zealand, almost all dairy and red meat are produced from pasture. The symbiotic relationship between asexual Epichloë endophytes and improved pasture grass species has been critical in developing sustainable animal production systems in many parts of the world, where insect attack would otherwise limit productivity. This need is likely to grow with climate change, as the habitat for these insects grow to regions previously unsuitable, and as consumers demand fewer chemical interventions. Advances in endophyte selection have reduced some of the negative effects on animal health and welfare and further developments will continue to improve their function in grazing systems. Furthermore, advances in genetic technologies may allow the development of endophytes that produce chemicals that confer productivity or sustainability benefits for production systems. With a world in need of more food sustainably produced, advanced genetic manipulation of endophytes with novel traits should be a focus of future research and development.

Plant diseases pose a significant threat to global food security, affecting crop yield, quality, and overall agricultural productivity. Traditionally, diagnosing plant diseases has relied on time-consuming visual inspections by experts, which can often lead to errors. Machine learning (ML) and artificial intelligence (AI), particularly Vision Transformers (ViTs), and Convolutional Neural Networks, offer a faster, automated alternative for identifying plant diseases through leaf image analysis. However, these models are often criticized for their “black box” nature, limiting trust in their predictions due to a lack of transparency. Our findings show that incorporating Explainable AI (XAI) techniques, such as Grad-CAM, Integrated Gradients, and LIME, significantly improves model interpretability, making it easier for practitioners to identify the underlying symptoms of plant diseases. This study not only contributes to the field of plant disease detection but also offers a novel perspective on improving AI transparency in real-world agricultural applications through the use of XAI techniques. With training accuracies of 100.00% for ViT, 96.88% for EfficientNetB7, 93.75% for EfficientNetB0, and 87.50% for ResNet50, and corresponding validation accuracies of 96.39% for ViT, 86.98% for EfficientNetB7, and 82.00% for EfficientNetB0, our proposed models outperform earlier research on the same dataset. This demonstrates a notable improvement in model performance while maintaining transparency and trustworthiness through interpretable and reliable decision-making.

Plant immune inducers from fundamental research to applications: Past achievements, current challenges and future perspectives.

Heavy metal contamination from industrial activities threatens global food security by causing phytotoxic effects in crops like wheat. This study examines the impact of heavy metals (As, Cd, Cr, Ni, and Pb) on the physiological, anatomical, and agronomic traits of two wheat cultivars, Pak-13 and SKD-1, through hydroponic and field experiments. In the hydroponic experiment, plants were grown for 21 days in metal-contaminated solutions. Anatomical studies revealed significant changes under heavy metal stress, such as increased thickness of the root endodermis, xylem, cortex, and stellar cells. Cd exposure caused enlarged parenchyma in Pak-13, while Ni and Pb led to cortical dissolutions in SKD-1. Both cultivars showed thickening of leaf tissues under metal exposure, with SKD-1 displaying better structural adaptations. In the field experiment, agronomic results indicated significant reductions in grain yield (GY) under heavy metal stress. Pak-13 experienced GY reductions of 60.94% (Cd), 91.96% (Ni), 62.68% (Cr), 27.45% (As), and 92.62% (Pb), while SKD-1 showed declines of 2.40% (Cd), 77.48% (Ni), 66.83% (Cr), and 86.76% (Pb). The field data also highlighted a decrease in traits such as tillers per plant (T/P) and spike length per spike (SL/S) for Pak-13, whereas SKD-1 exhibited increased grain yield under As stress and enhanced biomass yield under Cd, Ni, and Pb stress, reflecting better tolerance. This study highlights the importance of anatomical adaptations in understanding metal stress tolerance, with SKD-1 proving more resilient. These findings are essential for breeding wheat cultivars with enhanced tolerance to metal toxicity, contributing to sustainable agriculture in contaminated areas.

Chickpea (Cicer arietinum L.) is vital for global food security; however, its productivity is limited by genotype-environment interactions and restricted genetic diversity. This study dissected the genetic architecture of six agronomic traits in chickpea using genome-wide association studies (GWAS) to identify stable quantitative trait loci (QTLs). Phenotypic analysis of 238 chickpea accessions across three growing seasons revealed significant variation in plant height (PH), height to lowest pod (HLP), number of lateral branches (NLB), number of seeds per plant (NSP), thousand-seed weight (TSW), and yield per plant (YP). Broad-sense heritability (h2) ranged from 0.15 (NSP) to 0.88 (TSW). GWAS identified 40 stable QTLs, including major-effect loci on chromosomes 2 (Q_YP_2.1, R² = 0.45) and 4 (Q_TSW_4.1, R² = 0.22). Candidate genes linked to polyamine biosynthesis (LOC101508792) and carbohydrate metabolism (LOC101492955) were implicated. The study highlights the potential of marker-assisted selection for enhancing chickpea resilience and productivity, particularly in drought-prone regions such as Kazakhstan.

Soybean (Glycine max), is an important oilseed crop that plays a vital role in ensuring global food security. However, it is susceptible to multiple abiotic stresses that can reduce yield. The ubiquitination-proteasome pathway is a crucial regulatory mechanism that controls a broad range of processes in plants. We investigated the function of Glycine max drought-induced SINA (GmDIS1), an E3 ligase gene, in soybean abiotic stress tolerance using Agrobacterium-mediated transformation to develop soybean GmDIS1-RNAi transgenic lines. GmDIS1 was significantly induced under drought and heat stress. Several physiological traits revealed resilience of GmDIS1-RNAi lines under drought and heat stress. The functions of stress-related genes, such as AOS and GmPAL were investigated to dissect the pathways that contribute to drought and heat tolerance in GmDIS1-RNAi lines. The results suggest that decreasing expression of GmDIS1 can enhance soybean tolerance to drought and heat, and also provide a significant target for developing more drought- and heat-tolerant soybean varieties and other crops.

Introduction Microplastics (MPs), ubiquitous and insidious pollutants pervading agricultural systems, pose an escalating threat to global food security. This makes the development of nondestructive methods for the early detection of MPs stress in rice seedling an urgent scientific imperative. Method Rice seedlings were cultivated under exposure to polyethylene terephthalate (PET), polystyrene (PS), and polyvinyl chloride (PVC) MPs at concentrations of 0 (control), 10, and 100 mg/L. Based on the stress-induced alterations in root exudates composition, a novel detection method for MPs stress in rice seedlings was developed using excitation-emission matrix fluorescence (EEMF) spectra combined with deep learning. Results Analysis of the original EEMF spectra revealed discernible differences. Feature extraction was performed using both the peak method and the PARAFAC method. Spectral changes in seedlings exposed to the low MP concentration (10 mg/L) were relatively minor compared to the control group. In contrast, exposure to the high concentration (100 mg/L) induced significant alterations in humic acid-like and amino acid-like substances. Subsequently, enhanced Vision Transformer (VIT) models were developed utilizing three distinct data representations: full EEMF spectra, emission spectra at specific excitation wavelengths, and extracted characteristic fluorescence values. The optimal model achieved 100% classification accuracy. Furthermore, SHapley Additive exPlanations (SHAP) analysis was employed to evaluate feature importance, identifying both humic acid-like and marine humic acid-like components as major contributors to the model’s predictions. Conclusion In summary, this study establishes a novel, non-destructive, and interpretable framework for the early detection of MPs stress in rice seedlings based on EEMF spectra of root exudates combined with deep learning.

Sustainable fruit production is essential for global food security, rural livelihoods, and environmental health; however, it faces mounting challenges from intensification practices, climate change, and socioeconomic disparities. This comprehensive review synthesizes recent advances (2018–2025) in ecological and regenerative approaches, precision agriculture, technological innovations, and socioeconomic policy frameworks that underpin resilient fruit production systems. Ecological strategies including soil health restoration, water conservation, biodiversity enhancement, and ecosystem-based adaptation form the foundation for sustainable productivity. Precision agriculture, artificial intelligence, robotics, and digital platforms enable data-driven optimization and climate-smart management. Socioeconomic factors, particularly equitable market access, gender inclusion, and value chain resilience, ensure inclusive benefits across stakeholders. Climate change impacts on phenology, pest dynamics, and resource availability necessitate adaptive breeding, canopy management, and technological interventions. Future prospects emphasize genomics, circular economy integration, and synergistic policy-education frameworks as pathways to sustainably intensify fruit cultivation. This holistic, interdisciplinary framework balances productivity with environmental stewardship and social equity, offering actionable insights to guide researchers, policymakers, and practitioners in transforming fruit production into a sustainable, climate-resilient enterprise.

Drought poses a severe threat to global food security and agricultural sustainability. Despite substantial efforts to enhance crop yield tolerance to drought, the effectiveness varies spatiotemporally across different environments and management practices. In this study, we compiled long-term grain yield data alongside multiple environmental indicators, including the multiscalar Standardized Precipitation Evapotranspiration Index (SPEI), climate, soil moisture (SWC), groundwater storage (GWS), nitrogen fertilizer (Nfer), and atmospheric CO2 records. We aim to assess the variability and drivers of grain yield sensitivity to drought across the North China Plain. We found a significantly positive correlation between the interannual variability of wheat yield and SPEI over the 9-month scale, suggesting that wheat yield variations were sensitive to medium-term (>9 month) and long-term (>22 month) drought. Surprisingly, the sensitivity (SSPEI: correlation coefficient between wheat yield variations and SPEI) of wheat yield to medium-term and long-term drought has declined substantially in the past three decades. The effects of SWC, GWS, Nfer, and CO2 on SSPEI varied situationally as the duration of the drought extended. Typically, SWC primarily governed short-term (<10 month) SSPEI, with a relative weight of 38.9 ± 3.2% in explaining SSPEI variability. The decrease in medium-term SSPEI was at the expense of GWS, which contributed a relative weight of 33.7 ± 12.3% in explaining the variations. SWC, CO2, and Nfer jointly dominated long-term SSPEI variations, and the cumulative relative weight as high as 84.0 ± 6.2%. Specifically, Nfer notably enhanced the SSPEI during prolonged drought, and the anticipated enriched CO2-induced “fertilizer effect” and “water-saving effect” in decreasing SSPEI were evident during long-term drought, contrasting with CO2 enrichment-enhanced yield reductions observed in short-term drought. Our findings highlight that prediction-based practices to mitigate drought-induced yield loss and enhance agricultural sustainability, including water conservation and fertilizer addition, may differ radically depending on drought episodes.

ABSTRACT Increasing waterlogging events due to intense rainfall pose a significant threat to global food security, risking the production of the third most important staple crop, maize by 25%–34%. Therefore, futuristic studies focusing on understanding the stage‐wise response of maize to varying intensities of waterlogging, along with effective mitigation strategies, are essential. In this context, studies were conducted over 2 years (2022–23 and 2023–24), involving three factors: crop growth stages, different waterlogging durations, and mitigation strategies. Among the growth stages, waterlogging at 15 days after emergence (DAE) was found to be the most sensitive, resulting in poor root morphological features, impaired physiological activities, and the highest grain yield reduction (46.01%). In contrast, maize plants exhibited higher tolerance to waterlogging at 25 DAE. Similarly, increasing waterlogging duration from 3 to 15 days consistently reduced maize growth and grain yield. Regarding mitigation strategies, foliar application of urea (2%) improved stomatal conductance by 41.32%, net photosynthetic rate by 36.03%, and dry matter accumulation compared to water‐sprayed plants. Consequently, it increased grain yield by 17.37%, enhancing stress tolerance and yield stability. Notably, urea spray (2%) on plants subjected to 3–5 days of waterlogging at 25 DAE effectively prevented the negative impacts of waterlogging on grain yield by promoting superior growth and yield‐determining traits. Thus, this study demonstrates that foliar application of 2% urea is an effective and practical strategy to minimise waterlogging‐induced yield losses by enhancing stress recovery and tolerance in maize.

The production and productivity of cereal crops, which form the foundation of global food security, are increasingly threatened by unstable water regimes and recurring droughts linked to climate change. Fortunately, a wide diversity of cereal crops is endowed with natural resilience to drought and heat stress, enabling them to survive under conditions that are critical for other plants. Understanding the key morphological, genetic, physiological, biochemical, and ecological mechanisms—and their interactions—is crucial for unraveling the processes involved in drought tolerance in these species. A comprehensive study of cereal crops, their variability, and their ability to survive and thrive under arid conditions will unlock new opportunities for breeding drought-resistant agricultural varieties. This review highlights the role of root system architecture (RSA) and gravitropic mechanisms (e.g., EGT1, DRO1), the integration of phytohormonal crosstalk, the potential of wild relatives and genome editing, and the emerging role of plant growth-promoting rhizobacteria (PGPR) in enhancing drought resilience. We propose a novel synthesizing concept focused on overcoming the fundamental yield-survival trade-off by framing drought resilience through the lens of optimizing three interconnected functional modules: water budget architecture, metabolic homeostasis, and integrative signaling networks. The central advance of this framework is its systems-level perspective that redefines these well-studied components as dynamically interacting, tunable modules, providing a practical blueprint for designing crop ideotypes that break the yield-survival trade-off.

Label-free electrochemical biosensor for real-time detection of live Salmonella typhimurium in salad samples using non-Faradaic EIS.

Investigative studies on protein quality, absorption pathways, and techno-functional comparison of mycoprotein, insect, and algal proteins for global food security and sustainability.

Asymmetric window detection of abrupt global drought-wetness alternations and ecological responses.

Herbicides play an irreplaceable role in ensuring global food production and security. The low dispersion, non-uniform deposition, and negligible translocation of low water-soluble contact herbicides restrict the bioactivity. Therefore, there is an urgent need to develop novel, promising, and eco-friendly pesticide formulations to improve bioactivity and reduce the environmental input of herbicides. The diflufenican nanosuspension (NS) with satisfactory physical stability was prepared by wet media milling. The uniform deposition of diflufenican nanoparticles in NS on the surface of weed leaves improved the contact area with the target and enhanced the efficiency in penetrating the biological barrier. The indoor and field experiments showed that NS can exhibit comparable contact herbicidal activity against broadleaf weeds even with a 50% reduction in dosage compared to conventional pesticide formulations without negatively affecting the safety of wheat. The superior herbicidal activity of NS was due to its stronger ability to bind to the phytoene desaturase and prevent carotenoid biosynthesis, which further accelerated chlorophyll degradation. Our research represents an eco-friendly, low-cost, and scalable pathway for the efficient delivery of low water-soluble contact herbicides, which can provide practical support for reducing the environmental inputs and increasing the efficiency of contact herbicides. © 2025 Society of Chemical Industry.