Search Results (1,733)

Acrobeloides nanus is a cosmopolitan, parthenogenetic soil nematode that is widely distributed across various terrestrial environments, including forests, sand dunes, and agricultural lands. In Korea, this nematode was first isolated from soil collected from a potato farm. It has been used as a biological indicator for monitoring contamination caused by divalent metals such as copper and zinc. In this study, A. nanus was isolated from the soil collected from a cucumber farm, and its identity was confirmed using both morphological and molecular markers. Spray-induced gene silencing using double-stranded RNA (dsRNA) represents a promising new strategy for pest control. Here, we tested a spraying dsRNA that would specifically suppress the target genes in A. nanus. Three genes (Pat-10, Unc-87, and vATPase-B) were targeted, and their expression levels were assessed following treatment with their corresponding dsRNAs. The dsRNAs were sprayed onto the nematode diet. As the concentration of dsRNA increased, the expression levels of the target genes were significantly reduced, leading to notable nematode mortality. However, nematicidal activity varied among the three different dsRNAs. To practically assess these dsRNAs under field conditions, the dsRNAs were applied to the soil containing the nematodes by a drenching application. Significant mortality was observed in treatments with dsRNAs targeting vATPase-B or Pat-10, but not with dsRNA targeting Unc-87. To enhance nematicidal activity in soil, the dsRNAs were formulated with chitosan. This formulation significantly improved the stability of dsRNAs under soil conditions and increased their control efficacy against A. nanus. This study suggests that the drenching technique offers an effective strategy to the control of soil-dwelling nematode pests affecting agricultural crops. Full article

The genus Sclerodermus Latreille (Hymenoptera: Bethylidae) comprises over 80 species of ectoparasitoids of insect pests in forests, agricultural environments, and stored products with a cosmopolitan distribution. Despite its growing significance in biological control, behavioral ecology, and public health, the taxonomy of the genus remains poorly resolved. This is largely due to morphological reduction and simplification among species, outdated or incomplete original descriptions, and limited access to type material. A particularly problematic case is Sclerodermus cereicollis Kieffer, originally described from two geographically disjunct populations: Giglio Island (Italy, Palaearctic) and Annobón Island (Equatorial Guinea, Afrotropical). The syntype series includes morphologically divergent specimens, casting doubt on their conspecificity. In this study, we redescribe S. cereicollis based on both the original syntypes and newly collected material from Italy. A lectotype is designated to stabilize the nomenclature, and we provide the first molecular data for the species to assess genetic cohesion among populations. Comparative morphological and molecular analyses reveal that the Afrotropical syntypes represent a distinct, previously undescribed species. Accordingly, we describe Sclerodermus annobonensis Masini, Colombo & Azevedo sp. nov., designating a holotype. This study refines species boundaries within Sclerodermus and highlights the value of integrative taxonomy, combining historical and contemporary data, in resolving persistent systematic ambiguities in morphologically conservative taxa. Full article

Water plays a fundamental role in sustaining biological processes, ecological functions, and economic systems. However, the progressive pollution of water sources compromises these functions, posing significant threats to water purity, human well-being, and environmental sustainability. Human activities, such as industrial waste, agriculture, and urbanization, alongside natural processes, are major contributors to the deterioration of surface water quality, which in turn leads to environmental and economic risks. The decline in water quality results in issues such as waterborne diseases, loss of biodiversity, and a shortage of clean water for consumption and industrial use. This paper emphasizes the critical need for maintaining good water quality and the importance of implementing effective strategies for the removal of physical, chemical, and biological contaminants. In response, this work presents an intelligent embedded system (electronic control unit, ECU) developed as part of a modular filtration system designed to improve surface water quality, provide more precise water analyses, and perform tests within a controlled environment. Full article

The implementation of autonomous rovers in agriculture could be a promising solution to ensure, at the same time, productivity and sustainability. One of the key points of this kind of vehicle concerns their autonomous driving strategy. Generally, the strategy should include the path planning and path following algorithms. In this paper, an autonomous driving strategy assessing both is presented. To evaluate the effectiveness of this strategy, a case study of an agricultural rover is presented. A co-simulation model, including a multibody model of the rover, is developed in Matlab/Simulink and Hexagon Adams environments to virtually test the rover capabilities and the effects of its dynamics on the robustness of the algorithm. Given different orchard configurations, common but critical work scenarios are investigated, namely a 180° turn and an obstacle avoidance manoeuvre. The actual trajectory obtained during simulations are compared to the ideal trajectory defined in the path planning stage. Furthermore, the torque demand at the electric motors is evaluated. To consider a wide range of possible operating conditions, additional tests with different terrains, payloads and road slopes are included. Results showed that the rover managed to accomplish the considered manoeuvres on loam soil with a maximum trajectory deviation of 0.58 m, but a temporary overload of the motors is needed. On the contrary, in case of difficult terrains, such as muddy soil, the rover was not able to perform the manoeuvre. To limit tire slip, a traction control algorithm is developed and implemented, and the results are compared with the case without control. Full article

Vegetables such as lettuce, tomato, carrot, and beet are vital to the global food industry, providing essential nutrients and supporting sustainable agriculture. Their cultivation in greenhouses across diverse climatic zones (temperate, Mediterranean, tropical, subtropical, and arid) has gained prominence due to controlled environments that enhance yield and quality. However, these crops face significant threats from climate change, including rising temperatures, erratic light availability, and resource constraints, which challenge optimal growth and nutritional content. This study investigates the influence of microclimatic conditions—temperature, light intensity, and CO₂ concentration—on the growth, physiology, and biochemistry of these vegetables under varying greenhouse types and climatic zones, addressing these threats through a systematic review. The methodology followed the PRISMA guidelines, synthesizing peer-reviewed articles from 1995 to 2025 sourced from Web of Science, Pub Med, Scopus, Science Direct, Springer Link, and Google Scholar. Search terms included “greenhouse microclimate”, “greenhouse types”, “Climatic Zones, “and crop-specific keywords, with data extracted on microclimatic parameters and analyzed across growth stages and climatic zones. Eligibility criteria ensured focus on quantitative data from greenhouse studies, excluding pre-1995 or non-peer-reviewed sources. The results identified the following optimal conditions: lettuce and beet thrive at 15–22 °C, 200–250 μmol·m⁻²·s⁻¹, and 600–1100 ppm CO₂ in temperate zones; tomatoes at 18–25 °C, 200–300 μmol·m⁻²·s⁻¹, and 600–1100 ppm in Mediterranean and arid zones; and carrots at 15–20 °C, 150–250 μmol·m⁻²·s⁻¹, and 600–1000 ppm in subtropical zones. Greenhouse types (e.g., glasshouses, polytunnels) modulate these optima, with high-tech systems enhancing resilience. Conclusively, tailored microclimatic management, integrating AI-driven technologies and advanced greenhouse designs, is recommended to mitigate threats and optimize production across climatic zones. Full article

Hydroponic agriculture based on the Internet of Things (IoT) is an innovative solution to face the challenges of land limitations and climate uncertainty. This study aims to analyze the role of IoT in accelerating the growth of hydroponic plants through monitoring and automation of the planting environment, as well as evaluating its impact on productivity, especially for the planting process in land with minimal sunlight. The system integrates sensors to monitor environmental parameters such as pH, temperature, and humidity, which are then processed in real-time to optimize nutrient delivery and irrigation. The results show that the use of IoT in hydroponic systems is able to significantly improve the quality and quantity of crop yields compared to conventional methods. However, there are several challenges in implementation, such as high initial costs, limited infrastructure in certain areas, and potential cybersecurity threats. Nonetheless, innovation and collaboration opportunities between the public and private sectors can accelerate the adoption of these technologies in sustainable agriculture. Full article

Speed breeding technology has been used as a promising approach to accelerate plant breeding cycles and enhance agricultural productivity. However, systematic research on optimizing speed breeding conditions for alfalfa (Medicago sativa L.) in controlled plant factory environments remains limited. This study aimed to optimize light intensity, nutrient solution formulations, and photoperiod conditions for alfalfa speed breeding in plant factories equipped with full-spectrum LEDs, and to validate the applicability of these conditions across cultivars with different fall dormancy levels. Results demonstrated that a light intensity of 250 μmol·m⁻²·s⁻¹ significantly enhanced photosynthetic parameters, antioxidant enzyme activities, and biomass accumulation while minimizing malondialdehyde (MDA). The 75% concentration of the Japanese garden-test formula (JGTF) outperformed the Hoagland solution in promoting growth and photosynthetic pigment synthesis. An extended photoperiod (22 h/d) substantially accelerated growth and shortened flowering time. Under optimized conditions (250 μmol·m⁻²·s⁻¹ light intensity, 22 h/d photoperiod, and 75% Japanese Garden Test Formula), alfalfa cultivars reached initial flowering in approximately 37 days, regardless of fall dormancy level. This study establishes an effective speed breeding protocol for alfalfa, and the optimized conditions demonstrate broad applicability across cultivars with varying fall dormancy characteristics, providing a valuable foundation for accelerated alfalfa breeding programs and contributing to enhanced forage crop development efficiency. Full article

Controlled environment agriculture (CEA) has emerged as a vital solution to address the escalating global food demand amidst urbanization and diminishing arable land. However, the high energy consumption of CEA poses significant challenges for sustainable development. This paper provides a comprehensive review of the energy management models within CEA. The basic models of environmental factors such as light, temperature, humidity, and CO₂ concentration are introduced, highlighting their impact on plant growth and energy use. This paper elaborates on the coupling relationships between plant physiological activities and environmental control, facility environment and energy systems, and energy consumption and carbon emissions. Applications of energy management in CEA, including optimal energy scheduling, interaction with microgrids, and planning issues, are reviewed. Future research directions, such as multi-time-scale dynamic modeling, uncertainty modeling, and demand response (DR) modeling under market-oriented mechanisms, are also discussed. Full article

As the global digital transformation of agriculture accelerates, the widespread deployment of farming equipment has triggered an exponential surge in agricultural production data. Consequently, traditional cloud computing frameworks face critical challenges: communication latency in the field, the demand for low-power devices, and stringent real-time decision constraints. These bottlenecks collectively exacerbate bandwidth constraints, diminish response efficiency, and introduce data security vulnerabilities. In this context, edge computing offers a promising solution for smart agriculture. By provisioning computing resources to the network periphery and enabling localized processing at data sources adjacent to agricultural machinery, sensors, and crops, edge computing leverages low-latency responses, bandwidth optimization, and distributed computation capabilities. This paper provides a comprehensive survey of the research landscape in agricultural edge computing. We begin by defining its core concepts and highlighting its advantages over cloud computing. Subsequently, anchored in the “terminal sensing-edge intelligence-cloud coordination” architecture, we analyze technological evolution in edge sensing devices, lightweight intelligent algorithms, and cooperative communication mechanisms. Additionally, through precision farming, intelligent agricultural machinery control, and full-chain crop traceability, we demonstrate its efficacy in enhancing real-time agricultural decision-making. Finally, we identify adaptation challenges in complex environments and outline future directions for research and development in this field. Full article

Tomato (Solanum lycopersicum L.) production in greenhouse systems increasingly relies on integrated fertilization and soil management strategies to enhance yield, fruit quality, and resilience to biotic stressors. This study evaluated the combined effects of five fertilization regimes and two contrasting soil tillage systems—rotary tillage (RT) and conventional plowing (P)—on the performance of greenhouse-grown ‘Bacuni’ tomatoes. Experimental assessments encompassed biometric traits, photosynthetic pigments (chlorophyll and anthocyanins), carotenoid concentrations (carotenes and lycopene), soluble solids, and total dry matter contents, as well as agronomic variables including fruit weight, fruit number, and total yield. Incidence of key pests and diseases, alongside soil compaction levels, were also quantified. Fertilization with Nutriplant 20:20:20, as well as the application of Albit both resulted in a marked stimulation of vegetative growth, while the highest yields were recorded in P × Orgevit + Kerafol (6962.65 g plant⁻¹; +44.6% vs. control) and RT × Albit + Turboroot (6208.22 g plant⁻¹; +16.2% vs. control). Rotary tillage consistently improved nutrient uptake efficiency and yield relative to plowing, highlighting the role of soil structure in modulating plant performance. Treatments with Albit and Turboroot also enhanced resistance to Tetranychus urticae and Xanthomonas campestris, indicating a dual benefit for productivity and phytosanitary status. The results underscore the importance of harmonizing fertilization strategies with soil management practices to optimize greenhouse tomato production. Integrative approaches that combine biostimulants, organic amendments, and soil structural optimization offer a viable pathway toward high-yield, high-quality, and disease-resilient crops in controlled environment agriculture. Full article

The impact of invasive alien species (IAS) is one of the direct factors causing global biodiversity decline and economic losses, and predicting the potential invasion risks of invasive species is crucial for developing prevention and control strategies. In recent years, an increasing number of studies have shown that invasive species undergo rapid shifts in climate niche in invaded areas. Accurately quantifying the dynamic shifts in the climate niche of invasive species in invaded areas is crucial for developing a more accurate framework for early warning of invasive species risks. Pomacea canaliculata is a freshwater snail found in South America and has become one of the most aggressive aquatic species in the world. Since its introduction to China in 1981, it has rapidly spread and caused multiple serious damages to agriculture, ecology, and public health. Therefore, based on multi-source distribution data of P. canaliculata, this study calculated the climate niche overlap by Schoener’ s D, quantified the niche shifts between the P. canaliculata in native and invaded areas (China) via the COUE scheme (a unified terminology representing niche centroid shift, overlap, unfilling, and expansion), and analyzed their changes on a time scale. The results revealed that there have been significant climate niche shifts (Schoener’s D < 0.2, niche similarity tests p > 0.01, niche equivalence tests p < 0.01) between the native and invaded areas (China) of P. canaliculata, which does not support the climate niche conservation hypothesis. The minimum temperature of the coldest month (Bio 6) and precipitation seasonality (Bio 15) were the key climate variables driving the climatic niche shift, and P. canaliculata can survive in colder and more arid regions than their native counterparts. The changes in the niche shifts in P. canaliculata on a time scale show significant temporal heterogeneity, and its invasion behavior in China presents a discontinuous and phased expansion pattern, with strong adaptability to new environments. The results are of great significance for the future development of more accurate ecological niche model (ENM), the formulation of more targeted prevention and control strategies, and the study of adaptive evolution mechanisms of invasive species. Full article

Kuwait has reported a problematic increase in the prevalence of Antimicrobial Resistance (AMR). However, the absence of studies that analyze AMR from combined human, agricultural (animal), and environmental domains limits our ability to assess the extent of the problem in Kuwait. Therefore, this systematic review provides a comprehensive insight into the AMR status in Kuwait regarding humans, agriculture (animals), and the environment from the perspective of the One Health approach. A systematic search was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify the relevant literature on AMR in Kuwait. Multiple online electronic databases, including the Cochrane Library, Google Scholar, Web of Science, PubMed, BioMed Central (BMC), and Scopus, were searched to perform a narrative synthesis and meta-analysis. Twenty-eight studies published between 2009 and 2024 were included in this study. Domain-wise distribution varied, with 11 studies related to clinical settings, 11 to the environment, 4 to agricultural (animal), and 2 to both clinical and community settings. The narrative synthesis indicated a high occurrence of AMR bacteria in human, agriculture (animal), and environmental domains. In human domains, the dominant AMR isolates belonged to four Gram-negative species: E. coli, K. pneumoniae, P. aeruginosa, and Acinetobacter baumannii. In agriculture (animals), Salmonella isolates from poultry display high resistance to cefotaxime, ampicillin, and amoxicillin. Camel milk analyses revealed that 80% of bacterial isolates are resistant to antibiotics such as penicillin, tetracyclines, and carbapenems. An environmental analysis of sewage, seawater, sediment, and aerosol samples documented widespread antibiotic resistance genes (ARGs) with resistance mechanisms such as extended-spectrum beta-lactamase, carbapenemases, and colistin. The cross-domain analysis identified the overlapping of ARGs. Regarding the One Health approach, none of the studies used this approach to interlink these sectors. Meanwhile, the meta-analysis indicated a high resistance rate in humans (34.05%, 95% CI (22.81 to 46.27, p < 0.0001, I² = 98.94%)), agriculture (animals) (67.42%, 95% CI (30.30 to 94.93, p < 0.0001, I² = 97.40%)), and environment (69.86%, 95% CI (48.80 to 87.26, p < 0.0001, I² = 98.78%)). The reported spread of AMR and the overlap of resistance genes among isolates across the domains demonstrate the interconnected nature of AMR in Kuwait. These findings underscore the need to adopt the One Health approach to strengthen surveillance, implement control measures, and enhance public education strategies to address the complexity of AMR challenges in Kuwait. Full article

Digital twin technology is reshaping modern agriculture. Digital twins are the virtual replicas of real-world farming systems, which are continuously updated with real-time data, and are revolutionizing the monitoring, simulation, and optimization of agricultural processes. The literature on agricultural digital twins is multidisciplinary, growing rapidly, and often fragmented across disciplines, which lacks well-curated documentation. A bibliometric analysis includes thematic content analysis and science mapping, which provides research trends, gaps, thematic landscape, and key contributors in this continuously evolving and emerging field. Therefore, in this study, we conducted a bibliometric review that included collecting bibliometric data via keyword search strategies on popular scientific databases. The data was further screened, processed, analyzed, and visualized using bibliometric tools to map research trends, landscapes, collaborations, and themes. Key findings show that publications have grown exponentially since 2018, with an annual growth rate of 27.2%. The major contributing countries were China, the USA, the Netherlands, Germany, and India. We observed a collaboration network with distinct geographic clusters, with strong intra-European ties and more localized efforts in China and the USA. The analysis identified seven major research theme clusters revolving around precision farming, Internet of Things integration, artificial intelligence, cyber–physical systems, controlled-environment agriculture, sustainability, and food system applications. We observed that core technologies, such as sensors, artificial intelligence, and data analytics, have been extensively explored, while identifying gaps in research areas. The emerging interests include climate resilience, renewable-energy integration, and supply-chain optimization. The observed transition from task-specific tools to integrated, system-level approaches underline the growing need for adaptive, data-driven decision support. By outlining research trends and identifying strategic research gaps, this review offers insights into leveraging digital twins to improve productivity, sustainability, and resilience in global agriculture. Full article

Improving agricultural by-product utilization can alleviate tropical feed shortages. This study used corn stover (CS, Zea mays L.) at the maturity stage as the material, with four silage treatments: control, lactic acid bacteria (LAB, Lactiplantibacillus plantarum), cellulase (AC, Acremonium cellulolyticus), and LAB+AC. After 60 days fermentation in plastic drum silos, the silos were opened for sampling. PacBio single-molecule real-time sequencing technology was used to study bacterial community structure, symbiotic network functionality, and pathogenic risk to clarify CS fermentation regulatory mechanisms. The CS contained 59.9% neutral detergent fiber and 7.1% crude protein. Additive-treated silages showed better quality than the control: higher lactic acid (1.64–1.83% dry matter, DM), lower pH (3.62–3.82), and reduced ammonia nitrogen (0.54–0.81% DM). Before ensiling, the CS was dominated by Gram-negative Rhizobium larrymoorei (16.30% of the total bacterial community). Functional prediction indicated that the microbial metabolism activity in diverse environments was strong, and the proportion of potential pathogens was relatively high (14.69%). After ensiling, Lactiplantibacillus plantarum as Gram-positive bacteria were the dominant species in all the silages (58.39–84.34% of the total bacterial community). Microbial additives facilitated the establishment of a symbiotic microbial network, where Lactiplantibacillus occupied a dominant position (p < 0.01). In addition, functional predictions showed an increase in the activity of the starch and sucrose metabolism and a decrease in the proportion of potential pathogens (0.61–1.95%). Among them, the synergistic effect of LAB and AC inoculants optimized the silage effect of CS. This study confirmed that CS is a potential high-quality roughage resource, and the application of silage technology can provide a scientific basis for the efficient utilization of feed resources and the stable development of animal husbandry in the tropics. Full article

The Elfeija Dune Field (EDF) is a continental aeolian system in an arid region of southeastern Morocco. Studying this system is critical for understanding the effects of mounting climatic and anthropogenic pressures. This study provides a comprehensive characterization of the EDF’s morphology, sedimentology, aeolian dynamics, genesis, and recent evolution. A multi-scale, multidisciplinary approach was adopted, integrating field observations, sedimentological analyses, MERRA-2 reanalysis wind data, cartographic analysis, digital terrain modeling, and morphometric measurements. The results reveal an active 30 km² dune field, elongated WSW-ENE, which is divisible into three morphodynamic zones with a high dune density (80–90 dunes/km²). The wind regime is predominantly from the W to WSW, driving a net ENE sand transport and creating conditions conducive to barchan formation (RDP/DP > 0.78). Sediments are quartz dominated, with significant calcite and various clay minerals (illite, kaolinite, and smectite). Dune sands are primarily fine- to medium-grained and well sorted, in contrast to the more poorly sorted interdune deposits. The landscape is dominated by barchans (mean height H = 2.5 m; mean length L = 50 m) and their coalescent forms, indicating sustained aeolian activity. The potential sand flux was estimated at 1.7 kg/m/s, with a dune collision probability of 32%. The field’s genesis is hypothesized to be controlled by a topographically induced Venturi effect, with an initiation approximately 1000 years ago, potentially linked to the Medieval Climatic Optimum. Significant anthropogenic impacts from expanding irrigated agriculture are observed at the dune field margins. By providing a detailed characterization of the EDF and its sensitivity to natural and anthropogenic forcings, this study establishes a critical baseline for the sustainable management of arid environments. Full article