Search Results (8,087)

Salinity is a critical agricultural threat that reduces the productivity of several crops. Tomato (Solanum lycopersicum) is the world’s second most significant horticultural commodity, which struggles due to salt concentrations in irrigation water, even in hydroponic systems. This research evaluated seed priming treatments (hydro-, halo-, bacterio-, and halo-bacteriopriming) at different phenological stages under two salinity conditions (0 and 16 mM NaCl) to improve crop production. After evaluating physiological variables and multivariate statistical analyses, this study’s main breakthroughs are: Priming treatments modified the physiological, nutritional, and productive metabolism of tomato plants. Bacterio- and halo-bacteriopriming using an endophytic and halophytic bacterial consortium reduced germination time, enhancing uniformity and synchronizing seedling emergence. Bacteriopriming enhanced N, P, Ca and Zn absorption in seedlings. In the vegetative and reproductive stages, bacteriopriming consistently increased concentrations of K, Mg, and Zn in leaves and fruits but depleted Na uptake. Improving the nutritional balance resulted in not only a higher concentration of chlorophyll but also an increase in the yield and beta-carotene concentration in tomato fruits. The results demonstrated that halo-bacteriopriming may be a biotechnological strategy for mitigating saline stress, optimizing tomato growth and nutraceutical quality, because it outperformed the plant response in all stages of development compared to the control and hydro- and haloprimed treatments. Full article

The use of underutilized biomass improves resource-use efficiency and reduces agricultural waste, particularly in temperate systems cultivating tropical crops. Papaya (Carica papaya L.), grown as an annual crop in these systems, produces substantial trunk biomass that is typically discarded after harvest. This study evaluated the potential of papaya trunk xylem rays as an edible resource through compositional, sensory, and functional analyses. Trunks were harvested at the end of the fruiting period (December) and after exposure to a cold wave (January) and were classified by organ types and maturity level. Xylem rays showed moisture and carbohydrate contents comparable to those of green papaya fruit, and were judged as edible by all panelists (100%) in December-harvested samples. However, exposure to a cold wave reduced sweetness and increased bitterness, resulting in decreased overall acceptability. Nevertheless, boiling effectively reduced bitterness and improved palatability even in cold-exposed samples. In addition, xylem rays exhibited higher total polyphenol content than green papaya fruit, while showing comparable DPPH radical scavenging activity. These results suggest that xylem rays have potential as an edible plant resource with antioxidant-related properties, contributing to resource-use efficiency and potentially providing opportunities for biomass valorization in temperate production systems. Full article

Maize production in the black soil region of Northeast China is highly vulnerable to drought and flood stress, yet stage-specific mechanisms under rain-fed conditions remain unclear. Daily meteorological records from 1951 to 2024 were used to calculate the Crop Water Surplus Deficit Index (CWSDI) for four maize phenological stages, and 2025 in situ soil moisture and temperature observations were used to derive root-zone soil water storage (SWS), soil water depletion rate (SWDR), and the soil temperature–moisture coupling index (STMI). The growing season showed a persistent water deficit (mean CWSDI = −39.19%). Drought risk was greatest during sowing–jointing (S1; CWSDI = −64.73%; drought frequency = 73.0%) and milk–maturity (S4; CWSDI = −49.84%; drought frequency = 58.1%), whereas jointing–tasseling (S2) had the highest flood frequency (13.5%). Soil hydrothermal indicators showed that S1 drought was evaporation-driven, S2 involved potential hot-wet compound stress, tasseling–milk (S3) had rapid root-zone water depletion, and S4 drought was driven by insufficient late-season precipitation. These findings show that maize water stress is a sequence of stage-specific mechanisms rather than a uniform seasonal phenomenon. We therefore propose a regulation strategy combining soil moisture conservation, rainwater harvesting, precision supplemental irrigation, and field drainage to improve maize resilience. Full article

Containerized ornamental plant production requires efficient irrigation strategies to balance plant quality with water and nutrient conservation. This study evaluated four leaching fraction (LF) levels (0%, 20%, 40%, and 60%) in a completely randomized design with three replications, each consisting of three pots, to determine their effects on plant growth, ornamental quality, gas exchange, water use efficiency (WUE), and macronutrient leaching in off-season potted Curcuma cv. ‘Jasmine Pink’. Irrigation volumes were determined using crop coefficient (Kc)-based estimates derived from evaporation pan measurements. The results showed that the highest LF level (60%) significantly improved several ornamental quality traits, including flower number per cluster, leaf greenness, specific leaf area, and compactness index, while also increasing aerial dry weight and improving gas exchange parameters during the flowering stage. These improvements were associated with reduced substrate electrical conductivity, indicating lower soluble salt accumulation in the root zone under higher LF treatments and more favorable conditions for plant growth. Leaching fraction is commonly used in containerized crop production to prevent excessive salt accumulation in the root zone by allowing excess irrigation water to drain from the substrate. However, increasing LF also resulted in greater irrigation water consumption and higher macronutrient losses through leachate, particularly potassium. In contrast, lower LF treatments (0–20%) improved water use efficiency and reduced nutrient losses but were associated with higher substrate electrical conductivity, suggesting greater soluble salt accumulation in the root zone. Overall, the results indicate that a higher LF (60%) provided the greatest improvement in plant growth and ornamental quality under the conditions of the present study for off-season potted Curcuma alismatifolia production, although integrated strategies may be required to reduce water and nutrient losses. These findings provide practical insights for optimizing irrigation management in container-grown ornamental crops. Full article

Ball vegetables (such as cabbage, Chinese cabbage, broccoli, etc.) hold an important position in the vegetable industry due to their unique morphology and diverse applications and are widely favored by both consumers and the market. However, the harvesting of Ball vegetables poses significant challenges to agricultural production and market supply. Traditional manual harvesting struggles to meet the rapid demands of large-scale cultivation, primarily due to its high labor intensity and time-consuming nature, compounded by the increasingly prominent issues of aging and shortage of agricultural labor in recent years. As an alternative, intelligent harvesting robot technology, through integration with optimized cropping practices, innovations in preservation techniques, and improvements in processing workflows, offers an effective solution for expanding market planting areas and enhancing production efficiency. However, such harvesting robots still require further optimization and improvement in terms of adaptability, operational efficiency, and damage control. To systematically review the research progress and current status of this field, this study employs a bibliometric analysis approach to evaluate the current performance characteristics of various types of heading vegetable harvesting robots, aiming to provide a reference for future technological developments. This review analyzes solutions suitable for low-damage, high-quality harvesting of Ball vegetables in modern agriculture from five dimensions: identification and localization, row-following mechanisms, cutting mechanisms, pulling and conveying mechanisms, and leaf-removal mechanisms. It also summarizes the main challenges currently facing harvesting equipment, including the complexity of harvest targets, diversification of crop varieties and cultivation patterns, and harvest-induced damage to Ball vegetables. Finally, this review provides a future outlook on heading vegetable harvesting from four perspectives: research on the characteristics of Ball vegetables, investigation into harvest-induced damage mechanisms, improvement in machinery adaptability, and enhancement in equipment versatility and intelligence. Full article

Effective monitoring of insect populations is essential for sustainable pest management and for supporting Integrated Pest Management (IPM) strategies that reduce reliance on chemical pesticides. Bioacoustic methods have recently emerged as a promising approach for monitoring insects by analyzing the sounds and vibrations they produce during activities such as feeding, movement, and communication. This review examines the application of bioacoustics in insect monitoring and pest management, with particular emphasis on recent advances in artificial intelligence (AI) and automated detection technologies. The biological foundations of insect sound production, acoustic monitoring technologies, and AI-based analytical methods are discussed. Machine learning and deep learning models enable automated detection and classification of insect species based on acoustic signals, facilitating early pest detection and biodiversity monitoring. Bioacoustics has been applied to detect and identify insect pests, monitor stored-product insects, and manipulate insect behavior using acoustic and vibrational signals. Despite these advances, challenges remain, including environmental noise interference, limited acoustic datasets, and technical constraints of monitoring systems. Future research should focus on improving datasets, signal processing methods, and the integration of bioacoustics monitoring with precision agriculture and IPM frameworks to support sustainable crop protection. Full article

The Nutrient Tracking Tool (NTT) is a free and user-friendly modeling program developed by the Texas Institute for Applied Environmental Research (TIAER) at Tarleton State University in cooperation with the USDA Office of Environmental Markets. NTT simulates various cropping systems to evaluate management practices that optimize crop production while improving water quality and quantity. The objective of this study is to evaluate the capability of NTT to predict corn yield under different agricultural management scenarios. To assess model performance, 45 management scenarios from three field studies conducted in Iowa, Colorado, and Kansas were replicated in NTT. These scenarios included variations in nutrient sources and application rates, tillage practices, seeding rates, and irrigation management. Field data, including location, slope, planting dates, tillage practices, fertilization rates, and soil properties, were entered into NTT, and simulated crop yields were compared with measured values reported in the studies. Results showed strong agreement between measured and predicted corn yields across the evaluated scenarios. For example, the average measured yield of combined strip-tillage and manure treatment reported by Al-Kaisi and Kwaw-Mensah was 9.48 Mg ha, while NTT predicted 9.45 Mg ha. Similarly, for Halvorson et al., NTT predicted a yield of 8.06 Mg ha, compared with the measured yield of 8.23 Mg ha. Overall, the results indicate that NTT can reliably predict corn yield under a range of management practices, demonstrating its potential as a decision-support tool for agricultural management. Full article

This study explicitly assesses how crop and livestock production, along with real labor productivity, affect greenhouse gas emissions in agriculture across the European Union (EU), considering both per capita and total emissions. Using annual Eurostat data for EU Member States from 2008 to 2024, the research applies multiple regression models and a multivariate General Linear Model (GLM) to evaluate structural relationships, complemented by Holt exponential smoothing and ARIMA models to analyze temporal dynamics and generate forecasts. The empirical results indicate that crop and livestock production have a statistically significant positive effect on emissions, while real labor productivity has a significant negative impact. The models explain over 92% of the variation in total emissions and over 95% of the variation in per capita emissions, confirming strong explanatory power. Forecasts show continued growth in agricultural output but a declining trend in per capita emissions, primarily driven by productivity improvements. These findings demonstrate that improvements in labor efficiency and technological progress can partially offset the environmental pressures associated with increased agricultural production. The study concludes that achieving climate-neutral agriculture in the EU is feasible through sustained productivity gains and innovation-driven transformation. Full article

Evapotranspiration (ET) is a fundamental process within the water cycle and the agricultural water balance, optimizing resource allocation, maintaining soil health, and enhancing ecosystem resilience to climate change. Because ET represents a primary consumptive use of irrigation on agricultural lands, enhancing water-use efficiency and sustainable water management requires accurate estimation of evapotranspiration to support long-term sustainability and productivity. This study offers an effective means to visualize spatial and temporal patterns of reference evapotranspiration (ETo) across various vegetation management practices. This study examined the impacts of agroforestry buffers (ABs), grass buffers (GBs), biofuel crops in an agroforestry watershed (BCa), and biofuel crops in a grass buffer watershed (BCg) on ETo, compared to a corn (Zea mays L.)–soybean (Glycine max L.) rotation (RC) for claypan soil in Northern Missouri, USA. The experimental watersheds were located at the Greenley Memorial Research Center, Missouri, USA. Campbell Scientific sensors and Photosynthetically Active Radiation (PAR) smart sensors were installed to measure net radiation, anemometers, humidity, and air temperature. All instruments were mounted on masts at a height of 2 m above ground level in crop, tree, grass, and biofuel areas. Measured meteorological data were recorded hourly from April to October during 2017 and 2018. Daily ETo predictions were calculated using the Penman–Monteith model. These ETo predictions were displayed across the landscape using Python-based GIS for selected dates (each Saturday) for the watersheds. The methodology was implemented using the software programs of Python 2.7.10 and ArcGIS 10.3.1. The results indicated that ETo increased by 11%, 17%, 18%, and 25% in 2017, and by 7%, 9%, 14%, and 20% in 2018 for AB, BCa, BCg, and GB, respectively, compared to RC management. This process may improve soil water recharge in perennial management systems. Accurate estimation of ET in agricultural regions is critical for understanding water balance, hydrological and ecosystem processes, and climate variability. Given that agriculture constitutes the majority of global water consumption, precise ET estimation is particularly significant for sustainable water management, especially in regions experiencing water scarcity. These outcomes may support effective planning and management of agricultural water resources by enabling optimized irrigation and agricultural production. Full article

Climate change, depleting fossil fuel reserves, and instability in petroleum prices are driving developing economies to explore cost-effective, efficient, and sustainable energy sources such as hydropower. However, there is an ongoing debate regarding the relevance, suitability, and impact of mega-dams. Much of the existing research on mega-dams examines this debate through the lens of development theories. However, mega-dams impact a wide range of stakeholders at local, national, regional, and global levels, necessitating exploration of their role from a socioeconomic perspective. This interdisciplinary case study draws knowledge from management, sociology, and economics and provides a comprehensive account of multi-stakeholder perspectives on the impact of a mega-dam and addresses the research question: How do stakeholders perceive the impact of the Merowe Dam on agricultural livelihoods, and how do they interpret the role of governance processes? Participants included farmers, a focus group with 10 members from the affected communities, and 32 key informant interviews from non-governmental organizations, political actors, academics, businessmen and leaders in the catchment areas of the Merowe Dam, Sudan. The findings suggest that despite some concerns about motivations and processes of mega-dam commissioning, these projects are perceived as beneficial for long-term and sustainable socioeconomic growth and gaining support for renewable energy use in developing economies. The participants reported that modernization of agriculture, following the establishment of the dam, increased crop yields, e.g., wheat production has increased per hectare. Farmers’ income and irrigated land have increased substantially per family due to an increase in land sizes allocated to relocated communities, leading to an overall increase in land size. Therefore, with improved processes in both pre- and post-commissioning stages, transparency, accountability, and deeper stakeholder engagement, mega-dams can facilitate a smoother transition from fossil fuels to large-scale hydropower on one hand and livelihood enhancement through agriculture and other income generating activities on the other. Full article

Organic amendments can mitigate soil acidification and degradation, yet their long-term effects on soil microbiome, functions, and crop productivity remain underexplored in latosolic red soils. This study aimed to elucidate how different fertilization regimes reshape soil microbial communities and predicted functions, and how these changes link to sweet potato productivity after 15 years. Soil and plant samples were collected from a 15-year field experiment on latosolic red soil under five treatments: no fertilizer (CK), chemical fertilizer alone (NPK), and chemical fertilizer combined with commercial manure (NPK + CM), pig manure (NPK + PM), or rice straw (NPK + RS). Soil properties, bacterial and fungal communities, and predicted functions (FAPROTAX, FUNGuild) were analyzed. The results showed that long-term NPK alone significantly acidified soil (pH decreased by 1.49 units), whereas NPK + PM increased pH by 1.38 units relative to NPK, and also increased soil organic carbon, available nutrients, and sweet potato yield (by 31% compared with NPK). Soil pH was strongly associated with reshaping the microbial community. NPK + PM enriched beneficial phyla (e.g., Myxococcota, Nitrospirota, Latescibacterota, Entotheonellaeota, and Mortierellomycota) and enhanced predicted chemoheterotrophic, predatory or exoparasitic, and saprotrophic functions. Variance partitioning showed that nutrients, key microbial taxa, and predicted functions jointly explained productivity variation (adjusted R² = 0.9386). Thus, chemical fertilizer combined with pig manure is an effective strategy to mitigate soil acidification and improve sweet potato productivity by regulating soil nutrient-microbiome interactions. Our findings support reshaping the microbiome via organic amendments for sustainable agriculture in acidic soils. Full article

Verticillium wilt, caused by Verticillium dahliae, is a devastating disease that severely threatens cotton production worldwide. The long-term survival of the pathogen in soil and the limited availability of resistant cultivars make effective control strategies challenging. Although the fungal cross-kingdom RNA VdsR-1 has been reported to delay floral transition and prolong vegetative growth, the underlying plant regulatory mechanisms remain largely unclear. Here, we show that the transcription factor AtTOE1, a target of ath-miR172b-3p, displays altered expression in response to changes in ath-miR172b-3p levels during V. dahliae inoculation, coinciding with coordinated changes in plant immune-related and developmental responses. Increased AtTOE1 expression is correlated with enhanced disease resistance, reduced pathogen colonization, and delayed floral transition. Furthermore, our results indicate that the VdsR-1/AtSPL13A module is associated with modulation of AtTOE1 expression via ath-miR172b-3p, suggesting the involvement of a cross-kingdom RNA-related regulatory framework linking plant immunity and development. Notably, this regulatory relationship is also observed in cotton, indicating evolutionary conservation across plant species. Together, our findings highlight TOE1 as a potential integrator of defense and growth-related processes during pathogen challenge and provide insights that may inform strategies to improve resistance to V. dahliae in cotton and other crops. Full article

Accurate in-season crop type mapping is critical for agricultural monitoring and yield assessment, yet most operational products remain proprietary, post-seasonal or insufficiently tested across contrasting seasons. This study presents an open and transferable framework that quantifies how in-season crop classification skills evolve through the growing season across the southwest agricultural region of Western Australia (WA) using a multi-temporal (2020–2024) Sentinel-2 derived vegetation indices (VIs) time-series. Six crop classes (i.e., wheat, barley, canola, lupins, pasture, and fallow) were evaluated using extreme gradient boosting (XGBoost) and long short-term memory (LSTM) models under a leave-one-year-out cross-validation (LOYOCV) design. Classification performance increased progressively through the season, with a marked improvement in late winter (late August to early September). In LOYOCV, overall agreement with the reference dataset exceeded 90% once vegetation-index observations through August were included, indicating that reliable in-season mapping was achievable before harvest. Canola was separated consistently from mid-season onwards, whereas reliable discrimination between wheat and barley required later phenological information. Independent field-based testing was used to assess true crop identification accuracy for the three externally observed classes: wheat, barley, and canola. In this test set, precision was highest for canola (0.93), followed by wheat (0.82) and barley (0.71). These field-based results supported the main temporal pattern observed in the LOYOCV analysis, particularly the strong mid-season separability of canola and the persistent confusion between wheat and barley. SHapley Additive exPlanations (SHAP) showed thatVIs centred on late winter contributed most strongly to model predictions, consistent with peak phenological divergence among crop types. These results identify a phenologically meaningful decision window for in-season crop mapping and provide a multi-year benchmark for evaluating temporal transferability in Mediterranean broadacre systems. Full article

The increasing demand for resilient and multifunctional crops in the Mediterranean region has renewed interest in Urtica dioica L. as a potential alternative crop. This study evaluated the combined effects of fertilization and row spacing on the growth, yield, and nitrogen use efficiency of nettle in Athens, Greece. A split-plot experimental design was employed in a three-year experiment, with three fertilization treatments (C = control, U = urea, and I = urea with urease inhibitor) and two different row spacings (D1 = 30 cm × 20 cm, and D2 = 50 cm × 20 cm). Agronomic traits, seed yield, nitrogen content, vegetation indices (NDVI), chlorophyll content (SPAD), and nitrogen efficiency indices were assessed. Fertilization significantly enhanced plant performance, with the application of I consistently producing the highest values for plant height (increased by 10–30%), biomass (increased by 10–20%), and seed yield (increased up to 30%) compared to C. Row spacing influenced crop performance, with D2 favoring plant height (up to 9% compared to D1), while D1 generally increased biomass production per unit area (up to 20% compared to D2). Nitrogen-related indices (NUE, NAE, and NUtE) were markedly improved under fertilized treatments, particularly when I was applied (up to 20%, 100%, and 19% compared to U). NDVI and SPAD values were also influenced by fertilization and row spacing at early growth stages. The findings demonstrate that both factors play critical roles in optimizing nettle cultivation under Mediterranean conditions, highlighting the importance of integrated agronomic management practices. Full article

Soil quality (SQ) refers to the soil’s capacity, as influenced by management practices, to sustain productivity, maintain environmental quality, and provide essential ecosystem services. The impacts (2012–2016) of gypsum application, cover cropping, and crop rotation on SQ were evaluated under rainfed no-till (NT) systems at sites in Shorter, Alabama; Farmland, Indiana; and Hoytville and Piketon, OH, USA. Experimental treatments were arranged in a randomized complete block design in a factorial combination of gypsum (0, 1.1, and 2.2 Mg ha⁻¹), cover crop [cereal rye (Secale cereale) or no cover], and crop rotations as follows: soybean (Glycine max; SS), corn (Zea mays)–soybean (CS), and soybean–corn (SC). Composite soil samples were collected at 0–15 and 15–30 cm depths and analyzed for biological, chemical, and physical properties to compute a comprehensive SQ index (SQI_Comp). Principal component analysis identified a minimum dataset (MDS), including microbial biomass, organic carbon, and mean weight diameter, used to compute SQI_MDS. Applying gypsum at 2.2 Mg ha⁻¹ increased SQI_Comp by 3–7% and SQI_MDS by 7–17% at most sites compared with the control. The CS rotation produced the highest SQ, exceeding SS by 5–10%. Cover crops had minimal overall effects on SQ, except in Indiana. When averaged across all sites, SQ differences between depths were 19% for SQI_Comp and 33% for SQI_MDS. Significant linear relationships between SQI_MDS and SQI_Comp indicate that SQI_MDS accounted for most of the variability (R² = 0.77–0.94) in SQI_Comp. Overall, gypsum application at 2.2 Mg ha⁻¹ and the CS rotation improved surface SQ under NT systems, and SQI_MDS is better suited for relative comparisons than for absolute quantification. Full article