Search Results (9,291)

Agriculture is dealing with numerous challenges of increasing production while decreasing the amount of chemicals and fertilizers used. The intensification of agricultural systems has been linked to the use of these inputs which nevertheless have negative consequences for the environment. With new technologies, and progress in precision agriculture associated with decision support systems for farmers, the objective is to optimize their use. This review focused on the progress made in utilizing machine learning and remote sensing to detect and identify crop diseases that may help farmers to (i) choose the right treatment, the most adapted to a particular disease, (ii) treat diseases at early stages of contamination, and (iii) maybe in the future treat only where it is necessary or economically profitable. The state of the art has shown significant progress in the detection and identification of disease at the leaf scale in most of the cultivated species, but less progress is done in the detection of diseases at the field scale where the environment is complex and applied only in some field crops. Full article

The risk of soil salinization is prevalent in arid and semi-arid regions, posing a critical challenge to sustainable agriculture. This study addresses the need for accurate assessment of regional root-zone soil salt content (SSC) and understanding of underlying driving mechanisms, which are essential for developing effective salinization mitigation and water management strategies. A remote sensing inversion technique, initially proposed to estimate root-zone SSC in cotton fields, was adapted and validated more widely to non-cotton farmlands. Validation results (with a coefficient of determination R² > 0.53) were obtained using data from a three-year (2020–2022) regional survey conducted in the arid Manas River Basin (MRB), Xinjiang, China. Based on this adapted technique, we analyzed the spatiotemporal distributions of root-zone SSC across all farmlands in MRB from 2001 to 2022. Findings showed that root-zone SSC decreased significantly from 5.47 to 3.77 g kg⁻¹ over the past 20 years but experienced a slight increase of 0.15 g kg⁻¹ in recent five years (2017–2022), attributed to cultivated area expansion and reduced irrigation quotas due to local water shortages. The driving mechanisms behind root-zone SSC distributions were analyzed using an approach combined with two machine learning algorithms, eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanation (SHAP), to identify influential factors and quantify their impacts. The approach demonstrated high predictive accuracy (R² = 0.96 ± 0.01, root mean squared error RMSE = 0.19 ± 0.03 g kg⁻¹, maximum absolute error MAE = 0.14 ± 0.02 g kg⁻¹) in evaluating SSC drivers. Factors such as initial SSC, crop type distribution, duration of film mulched drip irrigation implementation, normalized difference vegetation index (NDVI), irrigation amount, and actual evapotranspiration (ET_a), with mean ($\left|\mathrm{SHAP} \mathrm{value}\right|$) ≥ 0.02 g kg⁻¹, were found to be more closely correlated with root-zone SSC variations than other factors. Decreased irrigation amount appeared as the primary driver for recent increased root-zone SSC, especially in the mid- and down-stream sections of MRB. Recommendations for secondary soil salinization risk reduction include regulation of the planting structure (crop choice and extent of planting area) and maintenance of a sufficient irrigation amount. Full article

Spraying is currently one of the main methods of pesticide application worldwide. It converts the pesticide solution into fine droplets through a sprayer, which then deposit onto target plants. Therefore, in the process of pesticide application, improving the effectiveness of spraying while minimizing or preventing crop damage has become a key issue. Combining the advantages of electrostatic spraying technology with the characteristics of ground boom sprayers, a contact-type electrostatic boom spraying system based on a rod–plate electrode structure was designed and tested on a self-propelled boom sprayer. The charging chamber was designed based on the characteristics of the rod–plate electrode and theoretical analysis. The reliability of the device was verified through COMSOL numerical simulations, charge-to-mass ratio, droplet size, and droplet size spectrum measurements, and a droplet size prediction model was established. The deposition characteristics in soybean fields were analyzed using the Box–Behnken experimental design method. The results showed that the rod–plate electrode structure demonstrated its superiority with a maximum spatial electric field of 2.31 × 10⁶ V/m. When the spray pressure was 0.3 MPa and the charging voltage was 8 kV, the droplet size decreased by 26.6%, and the charge-to-mass ratio reached 2.88 mC/kg. Field experiments showed that when the charging voltage was 8 kV, the spray pressure was 0.3 MPa, the traveling speed was 7 km/h, and the number of deposited droplets was 8517. This study provides some basis for the application of electrostatic spraying technology in large-scale field operations. Full article

Groundwater depletion in arid regions poses a significant threat to agricultural sustainability and rural livelihoods. This study employs geospatial analysis and economic modeling to address groundwater depletion in the arid Barind region of Northwest Bangladesh, where 84% of the rural population depends on agriculture. Using remote sensing and GIS, we developed an elevation map revealing areas up to 60 m above sea level, exacerbating evaporation and aquifer dryness. Field data collected through Participatory Rural Appraisal tools showed farmers exhibiting “ignorant myopic” behavior, prioritizing short-term profits over resource conservation. To address this, an Increasing Block Tariff (IBT) water pricing model was developed, dividing water usage into three blocks based on irrigation hours: 1–275 h, 276–550 h, and 551+ h. The proposed IBT model significantly increases water prices across the three blocks: 117 BDT/hour for the first block (from current 100–110 BDT/hour), 120 BDT/hour for the second block, and 138 BDT/hour for the third block. A demand function (y = −0.1178x + 241.8) was formulated to evaluate the model’s impact. The results show potential reductions in groundwater consumption: 59 h in the first block, 26 h in the second block, and 158 h in the third block. These reductions align with the principles of integrated water resource management (IWRM): social equity, economic efficiency, and environmental integration. The model incorporates economic externalities (e.g., well lifting costs) and environmental externalities (e.g., crop pattern shifts), with total costs reaching 92,709,049 BDT for environmental factors. This research provides a framework for sustainable groundwater management in arid regions, potentially reducing overextraction while maintaining agricultural productivity. The proposed IBT model offers a locally driven solution to balance resource conservation with the livelihood needs of farming communities in the Barind tract. By combining remote sensing, GIS, and economic modeling, this research provides a framework for sustainable groundwater management in arid regions, demonstrating the power of geospatial technologies in addressing complex water resource challenges. Full article

Climate change significantly threatens crops, mainly through drought stress, affecting barley, which is essential for food and feed globally. Ten barley cultivars were evaluated under normal and drought stress conditions during the 2019/20 and 2020/21 seasons, focusing on traits such as days to heading and maturity, plant height, number of spikes m⁻², spike length, 1000-kernel weight, and biological and grain yield. Drought stress significantly reduced most of these traits. The genotypes showed significant differences in their responses to irrigation treatments, with the interaction between seasons and cultivars also being significant for most traits. The grain yield and 1000-kernel weight were among the least affected traits under drought stress, respectively. Notably, Giza138 and Giza126 showed strong drought tolerance, suitable for drought-resilient breeding. In season one, Giza126, Giza134, and Giza138 yielded 13%, 9%, and 11%, respectively, while Giza135 and Giza129 showed higher reductions at 31% and 39%. In season two, Giza126, Giza134, and Giza138 had reductions of 14%, 10%, and 13%, respectively, while Giza135 and Giza129 again exhibited higher reductions at 31% and 38%. These cultivars also showed strong performance across various stress tolerance indices, including the MP, YSI, STI, GMP, and YI. Giza 134 demonstrated the lowest values for the SDI and TOL, indicating superior drought stress tolerance. On the other hand, Giza 129 and Giza 135 were the most sensitive to drought stress, experiencing significant reductions across critical traits, including 6.1% in days to heading, 18.37% in plant height, 28.21% in number of kernel spikes⁻¹, 38.45% in grain yield, and 34.91% in biological yield. In contrast, Giza 138 and Giza 2000 showed better resilience, with lower reductions in the 1000-kernel weight (6.41%) and grain yield (10.61%), making them more suitable for drought-prone conditions. Giza 126 and Giza 132 also exhibited lower sensitivity, with minimal reductions in days to heading (2%) and maturity (2.4%), suggesting potential adaptability to water-limited environments. Giza 126 maintained the highest root lengths and had the highest stomatal conductance. Giza 138 consistently had the highest chlorophyll content, with SPAD values decreasing to 79% under drought. Despite leading in shoot length, Giza 135 decreased to 42.59% under drought stress. In conclusion, Giza 126 and Giza 138 showed adaptability to water-limited conditions with minimal impact on phenological traits. Giza 126 had the longest roots and highest stomatal conductance, while Giza 138 consistently maintained a high chlorophyll content. Together, they and Giza 134 are valuable for breeding programs to improve barley drought tolerance. Full article

The effects of integrated nutrient-management (INM) practices on soil quality are essential for sustaining agro-ecosystem productivity. The soil quality index (SQI) serves as a tool to assess the physical, chemical, and biological potential of soils as influenced by various edaphic and agronomic practices. A multiyear (2018–2021) field experiment was performed at the University Organic Research Farm, Narendrapur, West Bengal, India, to investigate the influence of integrated and sole applications of different conventional fertilizers, organic (e.g., vermicompost), and natural farming inputs (e.g., Dhrava Jeevamrit and Ghana Jeevamrit) on SQIs and crop productivity of rice–mustard–green gram-based cropping systems. A total of 12 parameters were selected for the assessment of SQI, amongst which only four, namely pH, organic carbon %, total actinomycetes, and bulk density, were retained for the minimum data set based on principal component analysis (PCA). In this study, the maximum SQI value (0.901) of the experimental soil was recorded in the INM practice of 25% organic and 25% inorganic nutrient inputs, and the rest with natural farming inputs, which augments the SQI by 24% compared to the 100% inorganic nutrient treatment. Amongst the different soil parameters, the highest contribution was from the pH (35.18%), followed by organic carbon % (26.77%), total actinomycetes (10.95%), and bulk density (6.98%). The yields in different cropping systems varied year-wise across treatments. Notably, the highest yield in rainy rice was estimated in the 100% organic treatment, followed by INM practices in the subsequent years, and finally, the combination of organic and natural inputs in the final year. In the case of mustard, the combination of organic and natural inputs resulted in the highest productivity in the initial and last years of study, while the 100% organic treatment resulted in higher productivity in subsequent years. Green gram showed a dynamic shift in yield between the 100% organic and integrated treatments over the years. Further, a strong correlation was also established between the soil physico-chemical parameters and the SQI. Overall, this study concludes that the natural and organic input-based INM practice enhances the soil quality and crop productivity of the rice–mustard–green gram cropping system under the coastal saline zone. Full article

The increasing use of tractors and implements is replacing manual labor, but adds financial burdens on small-scale farmers due to rising costs. Many farmers have turned to leasing and renting machinery to mitigate these expenses, while repair and maintenance costs remain significant. Government interventions aim to alleviate these burdens, but income disparities between urban and rural areas persist, and the impact of machinery use on climate change and the environment poses further challenges. Strategies like omitting some operation steps and adopting versatile machinery are proposed to cut costs and promote economic sustainability for small-scale farmers. Therefore, this study assessed the economic benefits of using versatile machinery in farming, especially for small-scale rural farmers. Farming processes were divided into field preparation and crop season activities. Field preparation included rotary tillage, ridge formation, and mulching, whereas crop season activities included harvesting and transportation. Annual usage and production cost analyses per hectare, including labor, fuel, and interest, alongside purchasing cost surveys, were conducted. Versatile machinery reduced annual usage costs for field preparation and crop season activities by 63.54% and 71.71%, respectively. This effect was more pronounced for farms under 2 ha, especially those employing manual harvest and transportation. Small-scale farmers, such as those cultivating hot pepper farms, are strongly encouraged to adopt versatile machinery to mitigate expenses and labor costs. The significance of adopting studied methodology will be amplified with the rising cost of labor. Consequently, utilization of versatile machinery in field farming for small-scale farms is projected to increase incomes not through enhanced production, but by significantly reducing the annual usage costs associated with agricultural machinery. This approach not only alleviates financial burdens but also enhances the sustainability of farm management, ensuring long-term viability and environmental stewardship. Full article

Pigeon pea (Cajanus cajan (L.) Millsp.), a potential legume as an economic source of protein, is commonly cultivated in tropical and subtropical regions of the world. It possesses medicinal properties and acts as a cash crop, benefiting low-income farmers economically. The identification of pigeon peas exhibiting drought tolerance has become crucial in addressing water scarcity issues in the agriculture sector. In addition, exploring the genetic diversity among genotypes is important for conservation, management of genetic resources, and breeding programs. The aim of this study was to evaluate the morpho-physiological and biochemical responses of selected pigeon pea genotypes under pot-induced water stress conditions through different field capacities as well as the genetic diversity using start codon targeted (SCoT) markers. A significant variation was observed for the physiological traits studied. The accumulation of fresh weight (FW) and dry weight (DW) was significantly reduced in moderate and severe drought stress conditions. The lowest % DW decrease was found in LM (35.39%), KAT (39.43%), and SM (46.98%) than other genotypes at severe drought stress. Analyses of physiological responses including the photosynthetic efficiency (Phi2), the chlorophyll content (SPAD), and the relative water content (RWC) revealed positive and negative correlations with various parameters, reflecting the impact of drought stress on the chlorophyll content. The results revealed that biochemical traits including the total phenolic content, soluble sugars, proline, total protein, total amino acids, and free amino acids were variably and significantly increased under water stress. Antioxidant enzyme activity levels, specifically ascorbate peroxidase (APX) and catalase, varied among the genotypes and in response to severe water stress, offering further insights into adaptive responses. The eight genotypes analysed by use of 20 SCoT markers revealed 206 alleles and an average of 10.3 alleles per locus. Genetic similarity ranged from 0.336 to 0.676, clustering the pigeon pea genotypes into two major groups by the unweighted pair group method of arithmetic averages (UPGMA) cluster analysis. Principal coordinate analysis (PCoA) explained 43.11% of genetic variation and based on analysis of molecular variance, a high genetic variation (80%) within populations was observed, emphasizing the potential for genetic improvement. Among the eight genotypes studied, LM and KAT were drought tolerant and genetically diverse and therefore could be used as parents for developing drought tolerance in pigeon pea. Full article

Weed canopy cover assessment, particularly using drone-acquired data, plays a vital role in precision agriculture by providing accurate, timely, and spatially detailed information, enhancing weed management decision-making in response to environmental and management variables. Despite the significance of this approach, few studies have investigated weed canopy cover through drone-based imagery. This study aimed to fill this gap by evaluating the effects of conventional tillage (CT) and no-till (NT) practices on weed canopy cover in a winter wheat field over two growing seasons. Results indicated that in the 2022–2023 season, weed populations were similar between tillage systems, with a high mean weed cover of 1.448 cm² ± 0.241 in CT plots. In contrast, during the 2023–2024 season, NT plots exhibited a substantially higher mean weed cover (1.784 cm² ± 0.167), with a significant overall variation (p < 0.05) in weed distribution between CT and NT plots. These differences suggest that, while CT practices initially mask weed emergence by burying seeds and disrupting root systems, NT practices encourage greater weed establishment over time by leaving seeds near the soil surface. These findings provide valuable insights for optimizing weed management practices, emphasizing the importance of comprehensive approaches to improve weed control and overall crop productivity. Full article

Aiming at the operation scenario of existing crop coverage and the need for precise row alignment, the sowing prior navigation information of cotton fields in Xinjiang was used as the basis for the study of path planning for subsequent operations to improve the planning quality and operation accuracy. Firstly, the characteristics of typical turnaround methods were analyzed, the turnaround strategy for dividing planning units was proposed, and the horizontal and vertical operation connection methods were put forward. Secondly, the obstacle avoidance strategies were determined according to the traits of obstacles. The circular arc–linear and cubic spline curve obstacle avoidance path generation methods were proposed. Considering the dual attributes of walking and the operation of agricultural machinery, four kinds of operation semantic points were embedded into the path. Finally, path generation software was designed. The simulation and field test results indicated that the operation coverage ratio C_R ≥ 98.21% positively correlated with the plot area and the operation distance ratio D_R ≥ 86.89% when non-essential reversing and obstacles were ignored. C_R and D_R were negatively correlated with the number of obstacles when considering obstacles. When considering non-essential reversing, the full coverage of operating rows could be achieved, but D_R would be reduced correspondingly. Full article

Climate-driven changes have raised concerns about their long-term impacts on the yield resilience of cereal crops. This issue is critical in Poland as it affects major cereal crops like winter triticale, spring wheat, winter wheat, spring barley, and winter barley. This study investigates how soil nutrient profiles, fertilization practices, and crop management conditions influence the yield resilience of key cereal crops over a thirteen-year period (2009–2022) in the context of changing climate expressed as varying Climatic Water Balance. Data from 47 locations provided by the Research Centre for Cultivar Testing were analyzed to assess the combined effects of agronomic practices and climate-related water availability on crop performance. Yield outcomes under moderate and enhanced management practices were contrasted using Classification and Regression Trees to evaluate the relationships between yield variations and agronomic factors, including soil pH, nitrogen, phosphorus, potassium fertilization, and levels of phosphorus, potassium, and magnesium in the soil. The study found a downward trend in Climatic Water Balance, highlighting the increasing influence of climate change on regional water resources. Crop yields responded positively to increased agricultural inputs, especially nitrogen. Optimal soil pH and medium phosphorus levels were identified as crucial for maximizing yield. The findings underscore the importance of tailored nutrient management and adaptive strategies to mitigate the adverse effects of climate variability on cereal production. The results provide insights for field crop research and practical approaches to sustain cereal production in changing climatic conditions. Full article

Biostimulants include a wide array of microorganisms and substances that can exert beneficial effects on plant development and growth, often enhancing nutrient uptake and improving tolerance against abiotic and biotic stress. Depending on their composition and time of application, these products can influence plant physiology directly as growth regulators or indirectly through environmental condition changes in the rhizosphere, such as nutrient and water availability. This review evaluated 48 case studies from 39 papers to summarize the effects of biostimulant application on fruit and tuber yields and on the quality of processing tomato and potato in open field conditions. For potato, PGPR bacteria were the main studied biostimulant, whereas the low number of studies on processing tomato did not permit us to delineate a trend. The yield and quality were greatly influenced by cultivars and biostimulant composition, application method, period, and dose. For processing tomato, a positive effect of the biostimulant application on the marketable yield was reported in 79% of the case studies, whereas for potato, the effect was reported in only 47%. Few studies, on processing tomato and potato, also reported data for quality parameters with contrasting results. The variability of crop response to biostimulant application in open field conditions highlights the need for more comprehensive studies. Such studies should focus on diverse cultivars, deeply understand the interaction of biostimulant application with agronomic management (e.g., irrigation and fertilization), and evaluate yield and quality parameters. This approach is crucial to fully understand the potential and limitations of biostimulant applications in agriculture, particularly regarding their role in sustainable crop production. Full article

This study presents a one-step multiplex reverse transcription polymerase chain reaction (RT-PCR) method for the simultaneous detection of multiple viruses affecting melon crops. Viruses such as Watermelon mosaic virus (WMV), Cucumber mosaic virus (CMV), Zucchini yellow mosaic virus (ZYMV), Squash mosaic virus (SqMV), Tobacco mosaic virus (TMV), Papaya ring spot virus (PRSV), and Melon yellow spot virus (MYSV) pose a great threat to melons. The mixed infection of these viruses is the most common observation in the melon-growing fields. In this study, we surveyed northern Xingjiang (Altay, Changji, Wujiaqu, Urumqi, Turpan, and Hami) and southern Xingjiang (Aksu, Bayingolin, Kashgar, and Hotan) locations in Xinjiang province and developed a one-step multiplex RT-PCR to detect these melon viruses. The detection limits of this multiplex PCR were 10³ copies/μL for ZYMV and MYSV and 10² copies/μL for WMV, SqMV, PRSV, CMV, and TMV. The detection results in the field showed 242 samples were infected by one or more viruses. The multiplex RT-PCR protocol demonstrated rapid, simultaneous, and relatively effective detection of viruses such as WMV, CMV, ZYMV, SqMV, TMV, PRSV, and MYSV. The technique is designed to identify these melon viruses in a single reaction, enhancing diagnostic efficiency and reducing costs, thus serving as a reference for muskmelon anti-virus breeding in Xinjiang. Full article

Carbon dioxide flux emissions (CFE) from agricultural areas exhibit spatial and temporal variability, and the best time of collar fixation to the soil prior to the collection of CO₂ flux, or even its existence as a factor, is unclear. The objective of this study was to evaluate the effect of the fixation time of collars that support the soil-gas flux chamber based on the influence of CFE on different pasture management practices: control (traditional pasture management practice) (CON), chisel (CHI), fertilized (FER), burned (BUR), integrated crop-livestock (iCL), and plowing and harrowing (PH). A field study was conducted on the clayey soil of Udults. The evaluations were performed monthly by fixing the PVC collars 30 d and 30 min prior to each CFE measurement. Although a linear trend in CFE was observed within each pasture management practice between the two collar-fixation times, collar fixation performed 30 min prior led to an overestimation of CFE by approximately 32.7% compared with 30 d of collar fixation. Thus, CFE were higher (p ≤ 0.10) in the MC, when compared to the FC, when the CON, BUR, and iCL managements were evaluated. Overall, fixing the collar 30 d prior to field data collection can improve the quality of the data, making the results more representative of actual field conditions. Full article

The use of non-degradable plastic mulch has become an essential agricultural practice for increasing crop yields, but continued use has led to contamination problems and in some cropping areas decreases in agricultural productivity. The subsequent emergence of biodegradable plastic mulches is a technological solution to these issues, so it is important to understand how different soil characteristics and field management strategies will affect the rate at which these new materials degrade in nature. In this work, a series of lab-scale hydrolytic degradation experiments were conducted to determine how different soil characteristics (type, pH, microbial community composition, and particle size) affected the degradation rate of a sprayable polyester–urethane–urea (PEUU) developed as a biodegradable mulch. The laboratory experiments were coupled with long-term, outdoor, soil degradation studies, carried out in Clayton, Victoria, to build a picture of important factors that can control the rate of PEUU degradation. It was found that temperature and acidity were the most important factors, with increasing temperature and decreasing pH leading to faster degradation. Other important factors affecting the rate of degradation were the composition of the soil microbial community, the mass loading of PEUU on soil, and the degree to which the PEUU was in contact with the soil. Full article