Search Results (796)

Large-scale rainfed cropping systems (broadacre agriculture) face intensifying climate and resource stresses that undermine yield stability and farm livelihoods. Remote sensing (RS) offers critical tools for improving resilience by monitoring crop performance—productivity, phenology, and environmental stress—across large areas and timeframes. This review aims to synthesize methodological advances over the past two decades in applying RS for broadacre crop monitoring and to identify key challenges and integration opportunities. Peer-reviewed studies across diverse crops and regions were systematically examined to evaluate the strengths, limitations, and emerging trends across the three RS application themes. The review finds that (1) RS enables spatially explicit yield estimation from regional to paddock scales, with vegetation indices (VIs) and phenology-adjusted metrics closely correlated with yield. (2) Time-series analyses of RS data effectively capture phenological transitions critical for forecasting, supported by advances in curve fitting, sensor fusion, and machine learning. (3) Thermal and multispectral indices support the early detection of abiotic (drought, heat, salinity) and biotic (pests, disease) stresses, though specificity remains limited. Across themes, methodological silos and sensor integration barriers hinder holistic application. Emerging approaches, such as multi-sensor/scale fusion, RS–crop model data assimilation, and operational and big data integration, provide promising pathways toward resilience-focused decision support. Future research should define quantifiable resilience metrics, cross-theme predictive integration, and accessible tools to guide climate adaptation. Full article

Every year, up to 40% of the crops in the world are lost to pests. Plants have suffered from prolonged biotic stresses and abiotic stresses, which cause significant changes in complex crop ecosystems, necessitating intensive pest management strategies that have often been accompanied by the struggle against plant pests. Plant pests and diseases control methods heavily reliant on chemical pesticides have caused many adverse effects. One innovative method involves using ultrafine bubble (UFB) waters, which can enable pesticide reduction action for the plant pest control. The classification and six properties of UFBs were summarized, and the generation approaches of UFBs were introduced based on physical and chemical methods. The applications of UFBs and ozone UFB waters in plant protection practices were comprehensively reviewed, in which UFB waters against the plant pests and the soilborne, airborne and waterborne diseases were analyzed, and the abiotic stresses of crops in high-salinity soil and contaminated soil, drought, and soil with heavy metals were reviewed. Despite promising applications, UFB technology has limitations. Aiming at pesticide reduction and replacement using UFB waters, the mechanism of UFB water controlling plant pests and diseases, the molecular mechanism of UFB water affecting plant pest resistance, the plant growth in harsh polluted environments, the UFB behavior with hydrophobic and hydrophilic surfaces of crops, and the building of an integrated intelligent crop growth system were proposed. Full article

Soil disinfection is of great significance in reducing soil pests and weeds, overcoming the problem of crop continuous cropping obstacles, and ensuring the quality and safety of agricultural products. Soil flame disinfection technology, as a supplementary soil disinfection method that can be incorporated into an integrated plant protection system, has attracted much attention in recent years due to its characteristics of low resistance, greenness, environmental friendliness, and high efficiency. However, soil flame disinfection can also have a certain impact on soil organic matter and microbial communities, which is a core challenge that limits the promotion of flame disinfection technology. Clarifying the mechanism and temperature distribution of flame disinfection, accurately controlling flame disinfection parameters, can not only kill harmful organisms in soil, but also minimize damage to soil organic matter and microbial communities is the current research focus. This paper presents a comprehensive summary and discussion of the research progress regarding the mechanism of soil flame disinfection technology, the distribution of temperature fields, and the precise control technology for disinfection machines. It thoroughly elaborates on the efficacy of flame in eliminating typical soil-borne diseases and pests, the destructive impact of flame on soil organic matter and beneficial microbial communities, as well as the current status of research and development on soil flame disinfection devices. Additionally, it explores the pressing technical challenges that remain to be addressed. The article then discusses the future market prospects of soil flame disinfection equipment, focusing on key technological breakthroughs and opportunities, providing theoretical support for the next research, optimization and promotion of soil flame disinfection technology. Full article

In Saudi Arabia, coffee (Coffea arabica L.) has been grown for centuries on the mountain terraces of the southwestern regions. Jazan region accounts for about 80% of the total production. The acreage allocated to coffee is comparatively small but it is expanding rapidly thanks to a strong government-supported drive to increase local coffee production. Despite the initial success, the effort is hampered by the limited water supply available for irrigating the new plantings and the increased incidence of pests and diseases. The magnitude of these natural handicaps appears to have increased as of late, apparently due to climate change (CC). This review examines strategies to mitigate the consequences of CC on the coffee sector through the implementation of precision agriculture (PA) techniques, with the focus on addressing the challenges posed by biotic and abiotic stresses. The impact of CC is both direct by rendering present growing regions unsuitable and indirect by amplifying the severity of biotic and abiotic tree stressors. Precision agriculture (PA) techniques can play a key role in tackling these challenges through data-driven tools like sensors, GIS, remote sensing, machine learning and smart equipment. By monitoring soil, climate, and crop conditions, PA enables targeted irrigation, fertilization, and pest control thus improving efficiency and sustainability. This approach reduces costs, conserves resources, and minimizes environmental impact, making PA essential for building climate-resilient and sustainable coffee production systems. The review synthesizes insights from case studies, research papers, and other scientific literature concerned with precision farming practices and their effectiveness in alleviating biotic and abiotic pressures on coffee trees. Additionally, it evaluates technological advances, identifies existing knowledge gaps, and suggests areas for future research. Ultimately, this study seeks to contribute to enhancing the resilience of coffee farming in Saudi Arabia amidst ongoing CC challenges by educating farmers about the potential of PA technologies. Full article

Sclerotinia sclerotiorum (Lib.) de Bary, the causal agent of Sclerotinia stem rot (SSR) or white mold, is a soil-borne hemibiotrophic fungus that causes substantial soybean yield losses worldwide. This pathogen infects over 400 plant species and persists in soil for extended periods through melanized sclerotia, which can survive under extreme environmental conditions. The wide host range, environmental adaptability, and longevity of sclerotia make SSR a persistent challenge in soybean production. No single management tactic provides reliable control, which underscores the importance of integrated pest management (IPM). Cultural practices such as crop rotation with non-hosts, optimized row spacing, adjusted seeding rates, and targeted irrigation are fundamental to reducing inoculum and modifying canopy microclimates to slow infection. Although genetic resistance remains partial, the deployment of cultivars with stable performance across environments contributes to disease suppression, particularly when combined with fungicide applications. However, fungicide efficacy is inconsistent and limited due to environmental concerns and potential resistance. Advances in disease modeling have improved the timing and precision of chemical control, while biological control agents and RNA interference approaches offer promising future options. This review synthesizes current IPM strategies for SSR and explores emerging alternatives to support sustainable soybean production. Full article

The accurate identification of crop pests and diseases is critical for global food security, yet the development of robust deep learning models is hindered by the limitations of existing datasets. To address this gap, we introduce DLCPD-25, a new large-scale, diverse, and publicly available benchmark dataset. We constructed DLCPD-25 by integrating 221,943 images from both online sources and extensive field collections, covering 23 crop types and 203 distinct classes of pests, diseases, and healthy states. A key feature of this dataset is its realistic complexity, including images from uncontrolled field environments and a natural long-tail class distribution, which contrasts with many existing datasets collected under controlled conditions. To validate its utility, we pre-trained several state-of-the-art self-supervised learning models (MAE, SimCLR v2, MoCo v3) on DLCPD-25. The learned representations, evaluated via linear probing, demonstrated strong performance, with the SimCLR v2 framework achieving a top accuracy of 72.1% and an F1 score (Macro F1) of 71.3% on a downstream classification task. Our results confirm that DLCPD-25 provides a valuable and challenging resource that can effectively support the training of generalizable models, paving the way for the development of comprehensive, real-world agricultural diagnostic systems. Full article

Global agricultural production is challenging due to climate change and a number of phyto-pathogenic organisms and pests that pose a significant threat to both crop growth and productivity. The growing resistance of pests and diseases to synthetic chemicals makes crop production even more difficult, which highlights the urgent need for alternative solutions. From this perspective, marine microorganisms have emerged as a significant natural product source for their distinctive bioactive compounds and environmentally sustainable potential pesticidal activity. The unique microbial resources and structurally diverse metabolites of the marine ecosystem have been proven to have strong antagonistic effects against a broad spectrum of agricultural diseases and pests, making them a valuable candidate for the development of novel pesticides. This review highlights 126 marine natural products from marine microorganisms with diverse metabolic pathways and bioactivities against agricultural pests, pathogens, and weeds. The findings underscore the potential of marine-derived compounds in addressing the growing challenges of crop protection and offering an appealing strategy for future agrochemical research and development. Full article

The increasing prevalence of pests and diseases in agriculture necessitates innovative strategies for crop protection that mitigate environmental impacts. This review paper investigates the synergistic potential of combining microbial biocontrol agents and phytochemical biopesticides as sustainable alternatives to chemical pesticides. Through a comprehensive review of recent literature, we analyze the mechanisms by which beneficial microbes (e.g., Trichoderma, Bacillus, and Pseudomonas) enhance plant resilience and suppress pathogens, and how plant-derived phytochemicals such as essential oils, alkaloids, and flavonoids contribute to pest deterrence and disease resistance. The integration of these bio-based resources forms an actionable framework for sustainable crop protection—enabling reduced chemical dependence, improved soil health, and enhanced biodiversity. Examples of synergistic success, such as the combined use of Bacillus thuringiensis with neem extract and Trichoderma with lemongrass oil, illustrate their field potential. Future research should prioritize the formulation of stable microbial–phytochemical consortia, field validation of synergistic efficacy, and optimization of delivery systems to support commercial-scale adoption. Ultimately, this study promotes a paradigm shift toward eco-efficient pest management, bridging fundamental research and applied innovation for resilient agroecosystems. Full article

The world population is expected to grow to over 10 billion by 2050 and therefore impose further stress on food production. Precision agriculture has become the main approach used to enhance productivity with sustainability in agricultural production. This paper conducts a technical review of how robotics, artificial intelligence (AI), and thermal imaging (TI) technologies transform precision agriculture operations, focusing on sensing, automation, and farm decision making. Agricultural robots promote labor solutions and efficiency by utilizing their sensing devices and kinematics in planting, spraying, and harvesting. Through accurate assessment of pests/diseases and quality assurance of the harvested crops, AI and TI bring efficiency to the crop monitoring sector. Different deep learning models are employed for plant disease diagnosis and resource management, namely the VGG16 model, InceptionV3, and MobileNet; the PlantVillage, PlantDoc, and FieldPlant datasets are used respectively. To reduce crop losses, AI–TI integration enables early recognition of fluctuations caused by pests or diseases, allowing control and mitigation in good time. While the issues of cost and environmental variability (illumination, canopy moisture, and microclimate instability) are taken into consideration, the advancement in artificial intelligence, robotics technology, and combined technologies will offer sustainable solutions to the existing gaps. Full article

Effective implementation and optimization of organic amendments and other management practices is essential for sustainable organic vegetable production, yet needed information is lacking on the effects and benefits of different organic matter amendments and pest management approaches under Northeastern USA production conditions. The impacts of soil amendments of biochar or humus (soluble humate complex) in conjunction with compost, as well as the presence or absence of an early-season insect netting row cover (mesotunnels), were evaluated on soil chemical and biological properties, crop development and yield, and disease and pest issues in organic vegetable production, as represented by legume (green snap bean), cucurbit (green zucchini squash), and amaranth (garden beet) vegetable crops, in a three-year field trial in Maine. Composted cow manure and a commercial organic fertilizer alone were included as controls. All plots were either covered or not covered with a permeable insect netting row cover from the time of planting until flowering. All compost-based amendments increased soil pH; organic matter; microbial activity; crop yields; and K, Mg, and Ca content relative to a fertilizer-only treatment. Biochar amendments further increased soil pH, CEC, and Ca content above those of compost alone and also resulted in the overall highest yields of bean and zucchini but were not significantly greater than with compost amendment alone. Humus amendments did not improve soil characteristics, with some indications of potential reductions in emergence and yield. Insect netting substantially improved yield of zucchini (by 59%) and somewhat improved bean yield (by 11%), in addition to improving plant emergence and reducing insect leaf damage, but it did not reduce powdery mildew on zucchini or provide any significant benefits for beets. These results help define specific management practices to improve organic vegetable production and provide useful information and options for growers. Full article

Greenhouse horticulture is a cornerstone of year-round vegetable production. However, escalating climate change is intensifying abiotic stressors (i.e., elevated temperatures, increased vapor pressure deficits, water shortage, and modified solar radiation), threatening both crop productivity and postharvest performance. This review synthesizes current knowledge on how these climatic shifts impact greenhouse microclimate, pest and disease patterns, energy and water requirements, as well as crop development in the Mediterranean region. This study focuses on three major crops (tomato, cucumber, and sweet pepper), which prevail in the regional protected cultivation sector. Among the climate-induced stressors examined, elevated temperature emerges as the primary environmental constraint on greenhouse productivity. In reality, however, a combination of climate-induced stressors is at play, acting simultaneously and often synergistically. Among crops, cucumber generally displays the highest sensitivity to climate-induced shifts, whereas sweet pepper tends to be the most resilient. Next, adaptive strategies are explored, including precision irrigation, structural retrofitting measures, renewable energy integration, Decision Support Systems, and climate-resilient cultivars. Regional case studies revealed diverse country-specific counteractive innovations. As key elements of inclusive climate adaptation, supportive policy frameworks and a practical agenda of targeted research priorities are outlined. In conclusion, the sustainability of greenhouse horticulture under a changing climate demands integrated, technology-driven, and region-focused approaches. Full article

In an era of global warming, sustainable agriculture, which emphasises the conservation of biodiversity and the rational use of natural resources, is growing in importance. One of the key elements is to increase the genetic diversity of crops through the use of crop wild relatives (CWRs) and local varieties, which provide a source of genes for resistance to biotic and abiotic stresses. Modern agricultural systems are characterised by low biodiversity, which increases the susceptibility of plants to diseases and pests. Growing mixtures of varieties, both intra- and interspecific, is a practical strategy to increase plant resistance, stabilise yields and reduce pathogen pressure. This manuscript has a review character and synthesises the current literature on the use of CWRs, local varieties, and variety mixtures in sustainable agriculture. The main research question of the study is to what extent plant genetic resources, including CWRs and local varieties, as well as the cultivation of variety mixtures, can promote plant resistance, stabilise yields and contribute to sustainable agriculture under climate change. The objectives of the study are to assess the role of genetic resources and variety mixtures in maintaining biodiversity and yield stability, and to analyse the potential of CWRs and local varieties in enhancing plant resistance. Additionally, the study investigates the impact of variety mixtures in reducing disease and pest development, and identifies barriers to the use of genetic resources in breeding along with strategies to overcome them. The study takes an interdisciplinary approach including literature and gene bank data analysis (in situ and ex situ), field trials of cultivar mixtures under different environmental conditions, genetic and molecular analysis of CWRs, the use of modern genome editing techniques (CRISPR/Cas9) and assessment of ecological mechanisms of mixed crops such as barrier effect, and induced resistance and complementarity. In addition, the study considers collaboration with participatory and evolutionary breeding programmes (EPBs/PPBs) to adapt local varieties to specific environmental conditions. The results of the study indicate that the integration of plant genetic resources with the practice of cultivating variety mixtures creates a synergistic model that enhances plant resilience and stabilises yields. This approach also promotes agroecosystem conservation, contributing to sustainable agriculture under climate change. Full article

Advancements in genome editing have transformed agricultural biotechnology by allowing for precise modifications of DNA. This technology has sparked increasing interest in enhancing important traits of major crops, including peanuts. As a nutritionally rich legume prized for its high oil content, peanut production still faces significant challenges, including disease outbreaks, nutrient deficiencies, and pest infestations. Addressing these challenges is essential for achieving high yields and sustainable cultivation. CRISPR technology, a cutting-edge genome editing tool, has emerged as a powerful platform for improving peanut traits. Its ability to facilitate gene knockouts, regulate gene expression, and introduce targeted genetic changes has accelerated research efforts in this field. The successful applications of CRISPR in peanut improvement, such as increasing oleic acid content and reducing allergenicity, reassure us about the effectiveness and potential of this technology. Despite the complexity of the peanut genome as a polyploid crop, these successes demonstrate the power of genome editing. This review emphasizes the crucial role of genome editing in enhancing peanut traits and outlines the promising future of CRISPR-based approaches in advancing peanut breeding and agricultural productivity. Full article

Food shortages are becoming increasingly urgent due to the growing global population. Enhancing oil crop yields, particularly sunflowers, is key to ensuring food security and the sustainable provision of vegetable fats essential for human nutrition and animal feed. However, sunflower yields are often reduced by diseases, pests, and other factors. Remote sensing technologies, such as unmanned aerial vehicle (UAV) scans and satellite monitoring, combined with machine learning algorithms, provide powerful tools for monitoring crop health, diagnosing diseases, mapping fields, and forecasting yields. These technologies enhance agricultural efficiency and reduce environmental impact, supporting sustainable development in agriculture. This systematic review aims to assess the accuracy of various machine learning technologies, including classification and segmentation algorithms, convolutional neural networks, random forests, and support vector machines. These methods are applied to monitor sunflower crop conditions, diagnose diseases, and forecast yields. It provides a comprehensive analysis of current methods and their potential for precision farming applications. The review also discusses future research directions, including the development of automated systems for crop monitoring and disease diagnostics. Full article

Despite the recognized social and economic importance of common beans (Phaseolus vulgaris L.), the average grain yield is far below the productive potential of cultivars. This situation is explained by several factors, such as the large number of diseases and pests that affect the crop, some of which cause significant damage. It is estimated that approximately 200 diseases can significantly affect common beans. These can be bacterial, viral, fungal, and nematode-induced. The main bean fungal diseases include anthracnose, angular leaf spot, powdery mildew, gray mold, Fusarium wilt, dry root rot, Pythium root rot, southern blight, white mold, charcoal rot and rust. This review provides a comprehensive overview of eleven major fungal diseases affecting common bean, describing their associated damage, characteristic symptomatology, and the epidemiological factors that favor disease development. It further synthesizes current knowledge on host resistance mechanisms that can be exploited to develop molecularly informed resistant genotypes. The compilation includes characterized resistance genes and mapped quantitative trait loci (QTLs), with details on their chromosomal locations, genetic effects, and potential for use in breeding. Moreover, the review highlights successful applications of molecular breeding approaches targeting fungal resistance. Finally, it discusses conclusions and future perspectives for integrating advanced genetic improvement strategies—such as marker-assisted selection, genomic selection, gene editing, and pyramiding—to enhance durable resistance to fungal pathogens in common bean. This work serves as both a reference for forthcoming resistance-mapping studies and a guide for the strategic selection of resistance loci in breeding programs aimed at developing cultivars with stable and long-lasting fungal resistance. Full article