Segmentation of hyperspectral image data is a well-established technique in remote sensing. While it is commonly applied to individual field crops, its use for individual trees is less prevalent. Conifers are crucial in forestry, and assessing physiological status, or genetic diversity is required for effective early-age treatment in nurseries and hyperspectral imaging (HSI) combined with high-throughput phenotyping (HTP) offers faster and non-destructive evaluation. NDVI-based thresholding is sufficient for detection of leaves with large projection areas, but needles of conifers present challenges due to spatial resolution constraints and increased proportion of border pixels. This study monitored the offspring of three locally adapted Scots pine (Pinus sylvestris L.) populations, representing distinct upland and lowland ecotypes. This study presents a hyperspectral image processing pipeline for segmenting and isolating individual Scots pine seedlings. Using a K-means algorithm, 23 hyperspectral centroids were successfully derived and subsequently classified into ten biologically distinct groups. Random forest classification model effectively differentiated Scots pine seedlings based on origin during water stress and recovery periods. This study highlights the potential of hyperspectral imaging and machine learning in evaluating the physiological state of conifer seedlings, demonstrating promising applications in forest tree physiology research and tree breeding.

Abiotic stress and low resource-use efficiency are among the main challenges in agricultural production systems. Stress management is key to sustainable production. It is still challenging to identify and manage prevailing stresses under field conditions due to limited knowledge of the mechanisms of multiple abiotic stressors in crops. Crop models are becoming popular in agriculture because of their diversified nature in identifying multiple abiotic stresses and resource-use management in the complex nature of agricultural production systems. This study combined field measurements and crop modeling to improve the understanding of below- and above-ground resources use (water, nutrients, and light) and their impact on crop productivity and stress management under various planting conditions. A two-year field trial was conducted in the Thai uplands, comparing six treatments: (T1) maize sole crop with tillage and fertilization; (T2) maize-chili intercropping with tillage and fertilization; (T3) same as T2 but with minimum tillage and Canavalia ensiformis relay cropping; (T4) same as T3 plus Leucaena hedgerows; (T5) same as T3 without fertilization; and (T6) same as T4 without fertilization. The Water Nutrient and Light Capture in Agroforestry Systems (WaNuLCAS) model was calibrated using data from T1, T4, and T6 and evaluated against independent observations from T2, T3, and T5. Row-wise aboveground biomass, grain nitrogen (N) and phosphorous (P) concentrations, δ¹³C values, soil volumetric water content, and root length density were measured over two growing seasons. Grain δ¹³C values were significantly less negative in rows near the hedge (−10.33‰) than in distant rows (−10.64‰). More negative grain δ¹³C values (−9.32‰, p ≤0.001) were observed in T6. Both field observations and model simulations showed reduced maize biomass and lower grain N and P concentrations in rows closest to the hedgerows, driven by root competition for nutrients. Soil moisture was consistently higher in intercropped systems, and hedgerow height control prevented shading, indicating no water or light limitations. From the results it is concluded that WaNuLCAS model accurately reproduced spatial biomass patterns ( EF = 0.95 , RMSE = 0.98 , and R2 = 0.96 ) and correctly identified nitrogen and phosphorus stress in maize rows planted closely with leucaena hedgerows. Scenario simulations demonstrated that balanced increases in both N and P inputs most effectively alleviated nutrient competition and improved the long-term system productivity. This integrated field-model approach provides a robust framework for diagnosing resource competition and optimizing nutrient management in hedgerow-based agroforestry systems under upland conditions.

The socio-economic constraints-driven under provision of scientifically designed landfills for effective management of hazardous industrial wastes like tannery solid waste (TSW) in the developing countries. Disposal of TSW at designated and non-designated open dumps (OD) renders seasonal leachate runoff into adjacent agricultural fields when intense precipitation hits mountainously stacked TSWOD during summer and winter monsoon. However, TSWOD driven impacts on soil and crop productivity and biosafety of the adjacent agricultural fields has been missing in the literature. The objective of the current study was spatiotemporal quantification of productivity and biosafety threats of seasonal TSW leachate to recurrent corn and potato food crops in the adjoining agricultural fields of TSWOD of combined effluent plant of KTWMA, Kasur Pakistan. Based on data collected from two agricultural fields (2 ha each), it was observed that: (1) the TSW leachate arising from TSWOD severely affected soil productivity potential due to its immoderate pH, EC, COD, and BOD; being significantly higher than the local irrigation water; (2)Cd, Cr. Cu, Mn, Ni, Na and K in the TSW leachate exceeded the provincial industrial effluent discharge limits and had significant impact on soil health than the non-polluted fields; (3) the productivity of corn and potato in polluted fields remained as low as one third of the productivity in non-polluted fields; (4) the environmental contaminants' food biosafety hazards were determined as metal pollution index being variable for different metals, hazard index (HI < 1.0), and risk quotient (chronic risk with 1.0 level of concern). (4) Statistically, the productivity decline of corn and potato crops was function of the changes in soils chemistry. The study concluded that TSWOD seasonal leachate increasingly reduced suitability of adjoining soils for safer edible cropping by significantly reducing productivity and posing long-term biosafety hazards caused by vulnerability of food chain to heavy metals and organic pollutants.

Abstract This study investigates the adoption of precision agriculture technologies (PATs) in the Czech Republic. Using unbalanced panel data from the Czech Farm Accountancy Data Network (FADN) survey spanning the period from 2017 to 2021, it aims to identify the drivers and barriers to the adoption of PATs in Czech field crop production. The estimation of a probit binary choice model with a within-between random effects (WBRE) specification – a novel approach to addressing heterogeneity in panel data choice models – reveals that PATs adoption is significantly influenced by socio-economic factors such as labor intensity, indebtedness, manager education, and farm economic size, as well as environmental factors such as localization and land quality. Furthermore, the adoption of PATs is associated with temporal dynamics in labor intensity, production efficiency, specialization, and land ownership. The findings underscore the need for targeted policy measures to promote the adoption of technology and enhance agricultural efficiency. The contribution of this study lies in deepening the understanding of the determinants and barriers to precision agriculture adoption in the EU context, where empirical research remains relatively scarce.

Bumblebees are efficient pollinators of fruits and vegetables in greenhouses and field crops. However, pesticide use in agricultural landscapes is causing a sharp decline in pollinating insect populations. The impact of pesticides on bumblebee health is a growing concern. Cyfluthrin, atrazine, and prothioconazole are 3 commonly used pesticides in agricultural production. Although the Food and Agriculture Organization of the United Nations has published the acute median lethal dose (LD50) data for these 3 pesticides on Apis mellifera honey bee, there is still a lack of LD50 data for non-Apis bees, such as Bombus terrestris (Linnaeus, 1758). Therefore, this study determined the oral median lethal dose (LD50) of 3 pesticides, cyfluthrin, atrazine, and prothioconazole, in European bumblebees (Bombus terrestris). The active ingredient of each pesticide was first dissolved in dimethyl sulfoxide and then diluted in a sucrose solution to prepare the pesticide-sucrose mixture for feeding. The oral LD50 values of cyfluthrin for worker bees were 4.27, 3.36, and 2.16 μg/bee at 24, 48, and 72 h, respectively. The 24-h LD50 for virgin queens was 13.49 μg/bee. For 24-h exposures in worker bees, the oral LD50 values of atrazine, prothioconazole, and their mixture were 355.3, 530.0, and 480.4 μg/bee, respectively. Pesticide-sucrose solution intake decreased as pesticide concentration increased. This study provides a preliminary evaluation of the toxicity of 3 pesticide types on bumblebees and offers insight for improving the conservation and sustainability of pollinators in agriculture. Additionally, the findings contribute to regulatory assessments by providing crucial data on pesticide effects on B. terrestris, supporting more comprehensive and effective pesticide regulations.

Understanding the nature of trees should provide an important step for improving the productivity of the components and designing agroforestry systems. The study was aimed to evaluate the impacts of parkland Christ's thorn and Mango trees species on the yield of sorghum within and outside the canopy of the tree in Harari Region Ethiopia. Accordingly, twelve trees (six for each) isolated and nearly similar Mango and Christ's thorn trees growing on more or less similar site conditions, management practices, canopy coverage and height were selected. Sorghum variety (bullo) which is dominantly grown around the study area was sown during rainy season along with existing both tree species in crop field. Three quadrates 1 m*1 m were laid out under, edge and outside the canopy of the trees in the sorghum farmland to assess the sorghum grain and biomass yield in parkland. The finding of the study also showed that the grain and biomass yield of sorghum were significantly (P&lt;0.05) increased under canopy of Christ's thorn trees. Mango -sorghum interaction showed highly significant (p&lt;0.01) reduction of sorghum biomass and grain yield under the tree canopy compared with open area. It can be concluded that the integration of trees particularly Mango with sorghum in parkland agroforestry should be promoted with effective tree crown management to reduce crop shading, particularly near the tree where the shading effect is high.

The study was intended to investigate the effects of parkland Mangifera indica and Ziziphus spina-christi trees species on the selected physicochemical properties of soil within and outside the canopy of the tree and at varying soil depths in Sofi district, Harari Region, Ethiopia. Accordingly, twelve trees isolated and nearly similar M. indica and Z. spina-christi trees in crop field growing on similar site conditions, management practices, canopy coverage and height were selected. Soil samples were collected from under the canopy of trees, edge of canopy, outside of the canopy and three soil depth; 0-20 cm, 20-40 cm and 40-60 cm for analysis of selected soil physicochemical properties. The result of the study revealed that lower soil bulk density was observed under trees canopy and surface soil of both tree species than open field and subsurface soil (p&lt;0.01), While soil water content at FC, PWP and AWHC were significantly (p&lt;0.01) higher on subsurface than surface soil and under canopy of trees than open fields. However, no significant differences were observed in the texture and pH of soil (p&gt;0.05). Soil EC, SOC, SCS, TN, AP and CEC were significantly (p&lt;0.01) higher under the trees canopy than open field and on the surface than subsurface soil for both trees species in sorghum field. Thus, the finding suggests that retaining these important trees species with proper management on farmland improve and maintain soil fertility and reduce chemical fertilizer amendments.

Application of Arbuscular Mycorrhiza (AM) to field crops has remained yet unresolved as AM fungi are obligate symbionts and cannot be cultured in the laboratory. At present soil based inoculum production and application as such to crops is in vogue. To ease the application procedure, this study was carried out to understand whether or not AM fungi inoculated at nursery level can serve as inoculum to transplantable crops in field. The experiment was conducted under glass house conditions to screen different substrates viz., Vermicompost, Farm Yard Manure, Tank silt for obtaining enhanced colonization and spore numbers. The vermicompost enhanced the colonization and spore numbers. Further, study was carried out to determine the colonization interval of nursery inoculated finger millet seedlings. The root colonization was observed after 20 days of sowing. The colonization percentage increased as days increased. At 30 days interval, root colonization was increased to &gt;50 %. The seedlings thus colonized were used for transplantation to study the interaction effects with Nitrogen fixing and Phosphate solubilizing bacteria on growth and yield of finger millet under glass house conditions. The results showed that the AM colonized seedlings treated with N2 fixer and Phosphate solubilizer during transplantation, significantly increased the growth, yield and root colonization compared to uninoculated plants. Thus, this study revealed the possibility of application of AM fungi at nursery level to transplantable crops.

Weeds pose a significant threat to crop yields, both in quantitative and qualitative terms. Modern agriculture relies heavily on herbicides; however, their excessive use can lead to negative environmental impacts. As a result, recent research has increasingly focused on Integrated Weed Management (IWM), which employs multiple complementary strategies to control weeds in a holistic manner. Nevertheless, large-scale adoption of this approach requires a solid understanding of the underlying tactics. This systematic review analyses recent studies (2013–2022) on herbicide alternatives for weed control across major cropping systems in the EU-27 and the UK, providing an overview of current knowledge, the extent to which IWM tactics have been investigated, and the main gaps that help define future research priorities. The review relied on the IWMPRAISE framework, which classifies weed control tactics into five pillars (direct control, field and soil management, cultivar choice and crop establishment, diverse cropping systems, and monitoring and evaluation) and used Scopus as a scientific database. The search yielded a total of 666 entries, and the most represented pillars were Direct Control (193), Diverse Cropping System (183), and Field and Soil Management (172). The type of crop most frequently studied was arable crops (450), and the macro-area where the studies were mostly conducted was Southern Europe (268). The tactics with the highest number of entries were Tillage Type and Cultivation Depth (110), Cover Crops (82), and Biological Control (72), while those with the lowest numbers were Seed Vigor (2) and Sowing Depth (2). Overall, this review identifies research gaps and sets priorities to boost IWM adoption, leading policy and funding to expand sustainable weed management across Europe.

Directional droplet transport without external energy input has garnered considerable attention in the development of transportation systems. Introducing a wettability gradient or topography onto the surface has successfully harnessed the water to move directionally. However, classical capillary force requires complete wetting of the movement pathway, causing hydrodynamic dissipation and poor collection efficiency. Inspired by the water absorption of cactus spines and the droplet spreading of the pitcher plant, we designed hydrophobic water droplet patterns (WDPs) on a superhydrophobic background. Synergistic actuation of the sharp edge effect of the round end and the pinning effect of the pointed end enables the directional droplet transport with high flux (166.7 μL/s). Sharp edge effect on the hydrophobic surface enables water contact angle (WCA) to exceed 180°, achieving continuous cross-structural transport (transport speed: 11.67 mm/s). The nonwettability of the movement pathway reduces hydrodynamic dissipation. Through the patterning design of irrigation pathways, water could be delivered to the designed plant or crop to achieve precision fertilization or irrigation. Equipping the fertigation system with the WDP tracks will benefit experimental field cultivation and crop breeding. The functional surface features a simplified two-dimensional (2D) structure that provides more possibilities for the development of fluid delivery technologies.

Timely and accurate prediction of crop traits is critical for precision breeding and regional agricultural production. Previous studies have primarily focused on single crop yield traits, neglecting other crop traits and variety-specific analyses. To address this issue, we employed a Meta-Hybrid Regression Ensemble (MHRE) approach by using multiple machine learning (ML) approaches as base learners, integrating regional multi-year, multi-variety crop field trials with satellite remote sensing indices, meteorological and phenological data to predict major crop traits. Results demonstrated MHRE's optimal performance for rice and cotton, significantly outperforming individual models (RF, XGBoost, CatBoost, and LightGBM). Specifically, for rice crop, MHRE achieved highest accuracy for yield trait (R2 = 0.78, RMSE = 0.59 t ha-1) compared to the best individual model (XGBoost: R2 = 0.76, RMSE = 0.61 t ha-1); traits like effective spike also showed strong predictability (R2 = 0.64, RMSE = 27.81 10,000·spike ha-1). Similarly, for cotton, MHRE substantially improved yield trait prediction (R2 = 0.82, RMSE = 0.33 t ha-1) compared to the best individual model (RF: R2 = 0.77, RMSE = 0.36 t ha-1); bolls per plant accuracy was highest (R2 = 0.93, RMSE = 2.27 bolls plant-1). Moreover, rigorous validation confirmed that crop-specific MHRE models are robust across five rice and three cotton varietal groups and are applicable across six distinct regions in China. Furthermore, we applied the SHAP (SHapley Additive exPlanations) method to analyze the growth stages and key environmental factors affecting major traits. Our study illustrates a practical framework for regional-scale crop traits prediction by fusing multi-source data and ensemble machine learning, offering new insights for precision agriculture and crop management.

ABSTRACTBiodiversity is a key indicator of an ecosystem's resilience to disturbances, but farming practices like monocultures can be disruptive. Assessing the biodiversity levels in abandoned fields can help to reveal recovery patterns and inform strategies to conserve biodiversity in agricultural landscapes. The main aim of this study was to assess the pace of natural recovery for a chronosequence of formerly planted fields in a grassland habitat in the Eastern Cape, South Africa. The plant communities were evaluated using species counts, while the bacterial communities were assessed through high‐throughput sequencing (HTS) of the 16S rRNA gene. The alpha diversity indices indicated that the diversity levels within the old fields have started to resemble natural conditions for both the plant and microbial communities. Furthermore, the NMDS analyses identified clear variations in bacterial and plant community compositions among differently aged successional groups and the natural habitats. This study provides evidence that biodiversity levels within crop fields can recover from agricultural disturbances. However, considering the significant changes in climate and rainfall patterns in the study area, it remains unclear whether the community structures of the crop fields will reach native conditions in the coming decades, if at all.

Application of zinc and boron fertilizers in field crops: Effectiveness of direct, residual and cumulative doses in an intensively cropped soil of Bangladesh

This study introduces a novel one-step microwave-assisted (MW-AT) synthesis strategy for a TpTTA COF and demonstrates the fabrication of a MoO3-x-TpTTA COF-based nanocomposite (NC) for the first time. This method significantly reduces synthesis time (∼1 h) while achieving a high yield at a moderate temperature (120 °C). In contrast, traditional solution-based COF synthesis methods may take several days with continuous heating at higher temperatures (≤200 °C). The as-synthesized MoO3-x-COF-based NC was shown to serve as an affordable and straightforward substrate for surface-enhanced Raman scattering (SERS) detection of an organic dye, such as methylene blue (MB), achieving a maximum enhancement factor (EF) of 7.76 × 104. The incorporation of MoO3-x into the COF provides several advantages, including plasmonic enhancement by nonstoichiometric transition metal oxide (TMO) without requiring the addition of noble nanocrystals (e.g., Ag, Au, etc.), improved stability of the SERS substrate, comparable SERS sensitivity, and reduced costs. Furthermore, the as-synthesized MoO3-x-TpTTA COF-based SERS substrate demonstrated exceptional detection capabilities with high reproducibility, achieving a limit of detection (LOD) as low as 12.5 ppm for Mancozeb (Mz), a common commercially used dithiocarbamate insecticide used on various vegetables, fruits, nuts, and field crops. Notably, Mz is classified as a category III carcinogen by the International Agency for Research on Cancer. This highlights the potential for developing TMO-COF-based NCs for next-generation SERS-based applications in environmental and food safety monitoring.

Photoperiodic flowering in field crops: Mechanisms and the link to abiotic stresses

Corrigendum to “Nitrogen losses trade-offs through layered fertilization to improve nitrogen nutrition status and net economic benefit in wheat-maize rotation system” [Field Crops Res. 312 (2024) 109406

Herd immunity in crops? Lessons from human epidemiology.

Background: The Indian peafowl (Pavo cristatus L.), the national bird of India, is a widely distributed species known for its ecological adaptability and omnivorous feeding habits. It inhabits diverse environments such as forests, agricultural lands and urban areas. However, increasing human interference and habitat modification have influenced its feeding behavior and often led to conflicts with farmers. Understanding the feeding preferences of P. cristatus across different habitats is essential for its conservation and for minimizing human-peafowl conflicts. Methods: To study the feeding preferences of Indian peafowl (Pavo cristatus) on different food types (trees, grasses, herbs, field crops and animals), data were collected based on the number of pecks per minute using binoculars from a safe distance. The feeding sites were revisited after feeding to confirm food types. Feeding habits were recorded using the point count method. The mean pecks per minute and standard errors were calculated by food type, location and month. Data were analyzed using one-way ANOVA in Minitab 11 for Windows. Result: The Indian Peafowl is omnivorous, mainly feeding on herbs, crops and small animals. It consumes various tree parts, grasses and crops seasonally, with higher activity on plant matter. Animal diet includes insects, worms and small vertebrates across different months.

A laboratory experiment was carried out in the Seed Technology Laboratory of the Field Crops Department - College of Agricultural Engineering Sciences - University of Baghdad- Al-Jadriyah, aiming to study the effect of planting dates and spraying with kinetin and the interaction between them on the vitality and vigor parameters of the resulting (stevia rebaudina) plant seeds. The experiment was implemented according to the completely randomized design (CRD) with three replications comprising two factors. The first factor represented the dates of planting seedlings, as it included three spring dates: February 15, March 1, and March 15,. The second factor was spraying with three concentrations of kinetin (25, 50, and 75mg L-1), in addition to the control treatment of spraying with distilled water only, referred to as K0. The results showed that the late planting date was superior in the first count and the second count in the standard laboratory germination test, radical length, plumule length, seedling dry weight, cold test, and seedling vigor index (21.50%, 55.56%, 15.936 mm, 8.719 mm, 3.494 mg, 24.23%, 1374.0 mg, respectively). The highest concentration of kinetin in the first count and the second count was superior in the standard laboratory germination test, radical length, plumule length, seedling dry weight, cold test, and the seedling vigor index (20.00%, 49.58%, 14.998 mm, 7.745 mm, 2.758 mg, 20%, 1170.5 mg, respectively). Based on the findings of this study, altering the planting date and using kinetin spray significantly impacts the viability of the resulting seeds. Delaying the planting date until mid-March and using the highest concentration of kinetin (75 mg L-1) has been observed to increase the seed viability.

The transition toward sustainable and circular agricultural systems is increasingly important, yet evidence linking circularity and farm profitability in transition economies remains limited. This study examines the determinants of farm profitability in Serbia by combining micro-level structural and productivity indicators with a macro-level agro-eco efficiency measure, used here as a sector-wide ecological pressure indicator rather than a direct proxy for circular practices. Using a balanced Farm Accountancy Data Network (FADN) panel of 443 farms (2015–2022) across dairy, mixed, field crop, and fruit &amp; wine sectors, dynamic panel estimators (difference and system Generalized Method of Moments-GMM) reveal strong sectoral heterogeneity. Asset turnover is the primary driver of profitability in field crops and perennial systems, while dairy farms benefit from scale and land productivity. Energy intensity consistently reduces profitability across all sectors. Agro-eco efficiency shows a negative effect in livestock-based systems, indicating higher sensitivity to macro-ecological pressures. These findings suggest that environmental and economic vulnerabilities differ across production systems, highlighting the need for sector-specific strategies aimed at improving resilience rather than inferring the profitability of circular technologies.