Search Results (93)

Currently, devices such as solar insecticidal lamps are widely used in agricultural pest control, but routine trapping is insufficient to meet the demands of precision agriculture. Therefore, determining the nocturnal phototactic rhythm of pests to optimize the control strategies of insecticidal lamps has become key to achieving precise pest control. However, existing automated monitoring and forecasting devices struggle to effectively monitor the nocturnal phototactic rhythm of small pests. To address this issue, this study developed an automated monitoring system for phototactic rhythm based on sticky traps and machine vision. For the hardware, an image acquisition device integrating a darkroom and scheduled supplementary lighting was designed to obtain stable time-series images of nocturnal pests. For the algorithm, the YOLO-STP detection model was proposed by improving upon the baseline YOLOv11 model. This model introduces a P2 detection layer, a Coordinate Attention (CA) mechanism, and a hybrid bounding box regression loss function integrating WIoU and NWD. Combined with a sliding window cropping method, it further enhances the detection capability for small objects. Additionally, an incremental counting method based on spatial cascade matching was proposed to mitigate counting errors caused by target occlusion or detachment in the time-series images. Experimental results indicate that the mean average precision (mAP) of the detection model was 93.2%. For the counting method, the coefficient of determination ($R^2$) was 0.98, with an RMSE of 1.97 and an MAE of 1.60. Field validation in real-world paddy fields demonstrated that the system can accurately record the abundance changes of 12 pest species, intuitively visualizing the differences in phototactic rhythms among various species. This study provides a viable automated monitoring tool for acquiring the nocturnal activity rhythm data of agricultural pests in the field. Full article

Conventional hydroponic systems, although resource-efficient, face significant sustainability challenges due to the discharge of nutrient-rich effluents, resulting in severe environmental pressures. In alignment with the European Union’s “Farm to Fork” strategy, innovative circular economy approaches are required to decouple crop production from environmental degradation. This study evaluates a novel Cascade Hydroponic System (CHS), designed to maximize resource utility by recovering and reusing the drainage from a primary salt-sensitive crop (cucumber) to a secondary, more salt-tolerant cultivation (melon). A comparative Life Cycle Assessment (LCA) is performed in accordance with the Product Environmental Footprint Category Rules (PEFCRs), utilizing primary operational data and direct monitoring of nutrient concentrations in the system’s effluent. The convergence of these elements establishes the novelty of this study. The CHS is benchmarked against a conventional Separated Hydroponic System (SHS) for a functional unit (FU) defined as “the simultaneous production of 1.0 kg of cucumber and 1.0 kg of melon”. The CHS demonstrated lower characterized impacts compared to SHS across all 16 assessed Environmental Footprint categories under the examined pilot-scale conditions. The key findings include reductions of 65.7%, 41.8%, and 30% in Water Use, Climate Change, and Freshwater Eutrophication scores, respectively. Based on the normalization results, the CHS revealed a 58% lower total environmental footprint score compared to SHS. Process contribution analysis indicates that the marked decrease in the environmental burden is associated with the use of fertilizers. While these inputs represent a significant share of the conventional system’s impact scores, their contribution was substantially lower in the CHS. Although based on pilot-scale operational data from a single crop cycle, the results highlight the considerable environmental potential of cascading nutrient reuse configurations, thus enhancing resource use efficiency and mitigating the associated environmental impacts while also contributing novel empirical knowledge to a field that has been limitedly studied. Full article

Nitrate functions as both a nutrient and a signaling molecule in plants, initiating genome-wide transcriptional reprogramming and systemic developmental adjustments. Traditionally, plasma membrane nitrate sensing and nuclear transcriptional responses have been considered independent processes linked through linear transduction pathways. However, recent findings reveal that the dual-affinity nitrate transceptor NRT1.1 (NPF6.3) and the transcription factor NLP7 form an integrated signaling nexus—the Nitrate transporter 1.1 (NRT1.1)-NIN-like protein 7 (NLP7) nexus. This review examines the coupling mechanisms, including Ca²⁺-dependent phosphorylation cascades, nucleocytoplasmic shuttling, and a recently discovered MAPK amplification branch. We further explore the nexus’s conserved and diversified functions across crop species, and propose a three-tier rational design framework for reprogramming nitrate responses to enhance nitrogen use efficiency. By bridging structural biology and synthetic biology, this integrative perspective transitions crop improvement from empirical selection to structure-guided design, offering a roadmap for predictive crop engineering. Full article

Plants are constantly exposed to a wide range of abiotic stresses that have significant negative impacts on growth and yield. Plant acclimation to these stresses is governed by integrated classical phytohormone and plant peptide hormone signalling networks that control the ability of a plant to survive and adapt to extreme environments. Classical phytohormones, including abscisic acid, auxins, gibberellins, cytokinins, jasmonates, salicylic acid, brassinosteroids, and the recently recognised phytomelatonin, act in concert with peptide-based plant hormones, among which C-terminally encoded peptides (CEPs) play prominent roles in coordinating stress perception, signal transduction, and adaptive responses throughout the plant. These integrated networks control stomatal behaviour, photosynthesis, osmolyte and antioxidant levels, root architecture, and energy metabolism, thereby helping plants maintain homeostasis and optimise survival while sustaining minimal growth under unfavourable conditions. Under stressful conditions, these networks do not operate in isolation but form highly dynamic, context-dependent regulatory circuits in which each physiological process is simultaneously regulated by multiple hormones acting through convergent and overlapping signalling pathways. Phytomelatonin has emerged as a particularly important integrative node within these networks, functioning both as a potent direct antioxidant through sequential ROS-scavenging catabolite cascades and as a bidirectional regulator of classical phytohormone signalling under diverse abiotic stresses. New technologies in the fields of transcriptomics, proteomics, phosphoproteomics, metabolomics, and systems biology have provided new information on the dynamic relationships between classical phytohormones and plant peptide hormones, revealing candidate regulatory nodes and transcription factor networks that mediate stress adaptation at molecular, biochemical, and physiological levels. However, it is important to distinguish between correlative associations identified through omics profiling and causal regulatory relationships validated through rigorous genetic and biochemical experimentation, as most omics-derived candidates remain to be functionally established. Empirical studies demonstrate how these networks can be used to improve crops by increasing stress tolerance through modulating classical phytohormone and plant peptide hormone signalling, including through exogenous phytomelatonin application, CRISPR-mediated hormone pathway editing, and CEP pathway manipulation, to produce resilient cultivars without reducing yields. Although these advances represent significant progress, challenges remain, including the inherent complexity and redundancy of the networks, context-dependence and severity-dependence of hormonal responses, the persistence of a significant translational gap between laboratory findings and field application, and incomplete mechanistic understanding of peptide hormone roles under combined stress conditions. Addressing these challenges will require integrative multi-omics approaches, higher-order computational modelling, and rigorous field-based functional validation alongside emerging tools such as synthetic biology and precision breeding. Full article

Manganese (Mn) is essential for plants, but its fluctuating soil availability—deficiency in alkaline soils and toxicity in acidic soils—challenges crop productivity. Breakthroughs in Arabidopsis have uncovered Ca²⁺ signaling as a key integrator of Mn status. This review synthesizes these discoveries into an emerging Arabidopsis-centered framework. Under Mn deficiency, sustained Ca²⁺ oscillations activate CPK21/23, which phosphorylate the importer NRAMP1 at Thr498 to enhance Mn uptake. Under Mn excess, a rapid Ca²⁺ transient triggers a multi-layered cascade: CPK4/5/6/11 activates MTP8 (Ser31/32) for vacuolar sequestration, while CBL2/3–CIPK3/9/26 sequentially suppresses MTP8 (Ser35, peak 24 h) and MTP11 (Ser194/201, peak 36 h)—a multi-tiered “brake” system. Concurrently, CBL1/9–CIPK23 induces NRAMP1 endocytosis (Ser20/22) to limit Mn uptake. The IRT1 transporter directly binds cytoplasmic Mn²⁺ and triggers its own degradation via CIPK23, thereby converging with Ca²⁺ signaling. The BRI1–CNGC12 module generates Mn-induced Ca²⁺ signals. By organizing current knowledge into a hierarchical framework, this review provides a working model for future research and outlines translational opportunities for engineering Mn-resilient crops. Full article

The increasing demand for sustainable agriculture has intensified interest in beneficial microbes as eco-friendly alternatives to chemical pesticides for plant disease control. Among these, plant growth-promoting rhizobacteria (PGPR) have attracted great interest because they can suppress plant pathogens and strengthen plant health through molecular mechanisms. Recent studies suggest that PGPR protect plants from disease not only by directly attacking pathogens but also by changing how plant immune genes are expressed through epigenetic processes. This review brings together current knowledge on epigenetic regulation in plant–PGPR interactions, focusing on DNA methylation, histone modifications, and non-coding RNA pathways. PGPR colonization activates plant immune signaling through pattern recognition receptors, MAPK cascades, reactive oxygen species, and plant hormones. The review also covers the range of bacterial signals—including lipopolysaccharides, flagellin, cyclic lipopeptides, and volatile organic compounds—that prepare plant defenses, and explains how the recognition of these signals reshapes chromatin structure at defense genes. In addition, the review discusses how these changes may influence induced systemic resistance and examines emerging, though still limited, evidence on whether they could potentially be transmitted to subsequent generations. A better understanding of how microbial signals regulate host epigenetics may reveal new ways to improve plant immunity and balance growth with defense. Overall, available evidence indicates that PGPR-induced epigenetic changes represent a promising and environmentally friendly approach to crop protection; however, field-level validation and mechanistic confirmation in non-model crop species remain necessary before this strategy can be considered practically applicable. Full article

Crop cultivation involves a series of procedures from sowing till harvesting, making it a time-consuming activity. The crop cycle typically spans four to six months, during which cultivation outcomes are influenced by dynamic environmental and management factors such as water availability, temperature, and humidity. These parameters are collectively referred to as Optimum Cultivation Factors (OCFs). Once the cultivation process starts, poor OCFs may lead to reduced crop growth, leading to heavy economic loss. Historically, lessons learned from previous cultivation cycles have been a primary source for improving agricultural practices. Developing simulators that mimic agricultural environments in a controlled setting can support the analysis of cultivation factors while reducing time and resource requirements. In this study, a multifunctional agricultural simulator with a network of actuators is developed in the MATLAB/Simulink environment. The designed simulator mimics the agricultural field’s real-time environment while maintaining the temperature, humidity, and moisture content with appropriate water provision. Based on real field environmental data, the fuzzy-based membership functions are designed to emulate outdoor agricultural conditions at the laboratory scale. The designed system monitors and controls the actuators, such as water pumps for moisture, a heater for temperature, and a sun simulator for solar irradiation control. The cascaded fuzzy logic controller enables multi-factor environmental assessment by analyzing actuator responses under varying operating conditions, supporting pre-cultivation decision making. Full article

Glucosinolates (GSLs) are unique sulfur-containing secondary metabolites in Brassica crops that critically influence stress resistance, nutritional quality, and economic value. This review systematically summarizes the chemical classification, tissue-specific distribution, and conserved three-phase biosynthetic pathway of GSLs in Brassica species. We dissect the core MYB–MYC–WRKY transcriptional regulatory network, elucidate how whole-genome duplication-driven gene functional diversification shapes species-specific GSL accumulation patterns, and outline the multi-layered regulatory system integrating endogenous and exogenous signals. Furthermore, we consolidate recent advances in the genetic dissection of GSL traits and molecular breeding strategies for targeted trait improvement. Finally, we propose a three-tiered regulatory cascade model for GSL metabolism and highlight future research priorities to address current breeding bottlenecks. This work provides a systematic theoretical framework for functional research and precision breeding of GSL metabolism in Brassica crops. Full article

Soil salinization is a major threat to global crop production. Tartary buckwheat (Fagopyrum tataricum), valued for its hardiness in marginal environments, provides an excellent system for studying plant salt tolerance. Using an integrated multi-omics approach, we deciphered the physiological, metabolic, and transcriptional responses of Tartary buckwheat to prolonged NaCl stress. Physiological profiling confirmed membrane damage alongside osmotic adjustment via proline accumulation and a phased antioxidant response. Metabolomics revealed extensive reprogramming, with dynamic enrichment in pathways of flavonoid biosynthesis, lipid metabolism, and the TCA cycle. Transcriptomics delineated a time-specific cascade from early signaling to late defense activation. Critical regulators within ABA and MAPK signaling pathways showed fine-tuned, divergent expression; for instance, SnRK2.3 was suppressed while specific PP2Cs were induced, and FtMAPK10 was dramatically up-regulated. Integrated analysis demonstrated coordinated induction of osmoprotectant synthesis (e.g., galactinol and betaine pathways) and a rewiring of central carbon metabolism. Our findings reveal a sophisticated, multi-layered adaptation strategy in Tartary buckwheat, integrating enhanced osmolyte production, antioxidant defense, membrane remodeling, and metabolic reprogramming, orchestrated by key signaling networks. This study provides a comprehensive molecular framework for salt tolerance and identifies valuable genetic targets for improving crop resilience. Full article

Tomato (Solanum lycopersicum) is a widely consumed vegetable crop and an established model system for plant functional genomics and genetic research in dicotyledons. Salt stress is a major abiotic factor limiting tomato productivity worldwide. The WRKY transcription factor family, one of the largest and most conserved plant-specific transcription factor families, plays pivotal roles in stress responses. This review summarizes recent advances in understanding the functions of tomato WRKY genes under salt stress, focusing on the genomic basis and evolutionary characteristics of the WRKY family, the roles of core WRKY members under salt stress, and the multi-layered regulatory networks mediating WRKY-dependent salt and alkali tolerance. To date, approximately 10 core SlWRKY genes have been functionally validated to regulate tomato salt tolerance, mainly by maintaining ion homeostasis, regulating reactive oxygen species (ROS) balance, facilitating osmotic adjustment, and integrating hormone signaling pathways. Despite this progress, systemic regulatory hierarchies and epigenetic modulation remain poorly resolved. Furthermore, we discuss how specific WRKY members directly regulate downstream effector genes, such as SlSOS1 and SlNHX4. However, direct experimental evidence for the coordination between tomato WRKYs and mitogen-activated protein kinase (MAPK) cascades, as well as epigenetic modifiers under salt stress, is still scarce in current studies. This review provides a theoretical framework and outlines potential technical pathways for translating fundamental insights into tomato salt tolerance into practical applications for sustainable agriculture. Full article

Under maize–soybean rotation systems, weeds and crops at the seedling stage in dryland fields exhibit high similarity in morphological structure, scale distribution, and spatial arrangement. In addition, complex illumination conditions, occlusion, and background interference further complicate accurate weed discrimination. To address these challenges, this study proposes an improved YOLOv11n-based weed detection method for seedling-stage crops under dryland rotation conditions, aiming to enhance detection accuracy and robustness in UAV-acquired field images. Three key improvements were introduced to enhance model performance: (1) the incorporation of Dynamic Convolution (DynamicConv) to adaptively strengthen feature representation for weeds with varying morphologies and scales in low-altitude remote sensing imagery; (2) the design of a SlimNeck lightweight feature fusion architecture to improve multi-scale feature propagation efficiency while reducing computational cost; (3) the cascaded group attention mechanism (CGA) is integrated into the C2PSA module, thereby improving discrimination capability under complex background conditions. These results represent consistent improvements over baseline models, including YOLOv5, YOLOv6, YOLOv8, YOLOv11, and YOLOv12. Specifically, detection performance for broadleaf weeds and Poaceae weeds reached mAP@0.5 values of 87.2% and 73.9%, respectively. Overall, the proposed method demonstrates superior detection accuracy and stability for seedling-stage weed identification under rotation conditions, providing reliable technical support for variable-rate herbicide application and precision field management. Full article

Abiotic stresses severely constrain crop productivity by disrupting cellular redox homeostasis and hormone signaling. Although individual stresses differ in origin, plant responses converge on a conserved regulatory system centered on reactive oxygen species (ROS) and phytohormone crosstalk. Controlled ROS production in chloroplasts, mitochondria and the apoplast functions as a signaling mechanism that interacts dynamically with abscisic acid, auxin, ethylene, jasmonate and cytokinin pathways through shared regulatory nodes, including nicotinamide adenine dinucleotide phosphate (NADPH) oxidases and redox-sensitive transcriptional cascades. Endogenous metabolites, including phenolics, terpenoids, carotenoids, alkaloids, polyamines, glutathione and signaling peptides, are embedded within this network and modulate its amplitude and sensitivity. In parallel, non-microbial biostimulants derived from seaweeds, higher plants, protein hydrolysates and humic substances have been widely reported to enhance crop performance under abiotic stress. However, mechanistic integration between biostimulant research and plant stress signaling remains limited. In this review, we propose that terrestrial plant- and algal-derived biostimulants act not as external substitutes for hormones or antioxidants but as modulators of endogenous ROS–hormone signaling hubs. We first synthesize the current understanding of redox–hormone integration under abiotic stress, then examine endogenous metabolites as intrinsic regulators of this network, followed by an analysis of biostimulants in relation to shared regulatory nodes. By positioning biostimulant action within the established redox–hormone network, we provide a mechanistic framework that links stress biology with agronomic application and supports rational strategies to enhance crop resilience. Full article

Water management policies in desert agricultural regions critically influence both crop choices and ecosystem dynamics, yet their cascading ecological impacts remain poorly understood. In particular, the complex interactions between water quality, agricultural practices, and wildlife responses require further investigation to inform sustainable management in desert landscapes. Here, we evaluate how water policy, particularly seawater desalination initiatives influencing irrigation and cropping practices, shapes ecological systems in a hyperarid region, the southern Arava Valley of Israel. We integrated community-level questionnaires, agricultural records, animal field observations, and spatially explicit scenario tools into a mixed-methods framework to model social–ecological cascades linking water policy to predator dynamics. Bayesian Belief Networks combined with Generalized Linear Models of predator abundance were used to assess how improved water quality affects cropping patterns and, in turn, regional predator populations. Our findings indicate that desalination is unlikely to alter the predominance of date orchards or the high abundance of range-expanding jackals associated with these systems. However, water quality-driven expansion of field crops corresponds to lower modelled fox abundance and shifts in predicted predator interactions, while jackal populations remain largely influenced by date orchard availability. Under business-as-usual scenarios with lower water quality, farmers are likely to reduce field crop areas, corresponding to further changes in regional predator abundance. These findings suggest that water policy decisions may generate cascading social–ecological responses on both agricultural practices and local desert ecosystems, emphasizing the need for strategies that balance agricultural productivity with ecological sustainability in arid landscapes. Full article

Camera-based wildlife monitoring is often overwhelmed by non-target triggers and slowed by manual review or cloud-dependent inference, which can prevent timely intervention for high stakes human–wildlife conflicts. Our key contribution is a deployable, fully offline edge vision sensor that achieves near-real-time, highly accurate wildlife event classification by combining detector-based empty-image suppression with a lightweight classifier trained with a staged transfer-learning curriculum. Specifically, Stage 1 uses a pretrained You Only Look Once (YOLO)-family detector for permissive animal localization and empty-trigger suppression, and Stage 2 uses a lightweight EfficientNet-based binary classifier to confirm puma on detector crops and gate downstream actions. Our design is robust to low-quality nighttime monochrome imagery (motion blur, low contrast, illumination artifacts, and partial-body captures) and operates using commercially available components in connectivity-limited settings. In field deployments running since May 2025, end-to-end latency from camera trigger to action command is approximately 4 s. Ablation studies using a dataset of labeled wildlife images (pumas, not pumas) show that the two-stage approach substantially reduces false alarms in identifying pumas relative to a full-image classifier while maintaining high recall. On the held-out test set ($N=1434$ events), the proposed two-stage cascade achieves precision $0.983$, recall $0.975$, F1 $0.979$, accuracy $0.986$, and balanced accuracy $0.983$, with only 8 false positives and 12 false negatives. The system can be easily adapted for other species, as demonstrated by rapid retraining of the second stage to classify ringtails. Downstream responses (e.g., notifications and optional audio/light outputs) provide flexible actuation capabilities that can be configured to support intervention. Full article

Soil salinization severely constrains the productivity of Medicago sativa L. Although exogenous melatonin (MT) has been proven to effectively alleviate salt stress injury in plants, the molecular regulatory networks underlying its function during the early stages of stress response remain not fully elucidated. In this study, we systematically investigated the specific regulatory mechanisms of exogenous MT-mediated salt tolerance in alfalfa seedlings during the early phase (12–24 h) of salt stress by integrating physiological, biochemical, and transcriptomic analyses. The results showed that MT treatment significantly inhibited membrane lipid peroxidation (indicated by decreased MDA content) in leaves and upregulated the activities of antioxidant enzymes as well as the levels of osmoprotectants, such as soluble sugars. Transcriptomic (RNA-seq) analysis revealed that MT induced a precise strategy of temporal transcriptional reconfiguration. At the initial stage of stress (12 h), MT preferentially downregulated the expression of genes related to ribosome biogenesis and chromatin remodeling. This transcriptional suppression suggests that plants adopted an “energy saving strategy,” aiming to minimize basal metabolic consumption and potentially reallocate limited energy resources toward the antioxidant defense system. Subsequently, at 24 h, MT orchestrated the comprehensive activation of the ABA signaling cascade and secondary metabolic pathways, such as phenylpropanoid and flavonoid biosynthesis, thereby establishing a long-term chemical defense barrier. Furthermore, weighted gene co-expression network analysis (WGCNA) identified ABF2 and Susy as key hub genes mediating soluble sugar accumulation. This study elucidates the molecular basis by which melatonin enhances early salt tolerance in alfalfa through a temporal transition from an “energy-saving” strategy to “active defense,” providing new theoretical insights for the molecular breeding of stress resistance in leguminous forage crops. Full article