1932 papers
This study of 375 farmers in Kamyaran County, Iran, demonstrates that an extended Theory of Planned Behavior model, incorporating moral norms and knowledge, effectively predicts their high willingness to recycle agricultural waste, with attitude, subjective norms, and moral norms identified as key drivers.
This paper proposes a hybrid deep learning model based on MobileNetV3 with attention and fusion mechanisms that achieves 98% accuracy in detecting and classifying maize leaf diseases, offering a lightweight and efficient solution suitable for mobile and IoT deployment.
This study utilized AMMI and GGE biplot analyses to evaluate 15 buckwheat genotypes across three environments in Prayagraj, identifying genotype G15 as the ideal high-yield performer for favorable conditions and G14 as the most stable and broadly adaptable variety for diverse agro-climatic settings.
This study establishes a simple and accurate HPLC-MS/MS method utilizing pass-through solid-phase extraction and isotope dilution for the simultaneous determination of 20 veterinary drug residues in grass carp, demonstrating good linearity, recovery, and precision.
This study demonstrates that decomposed organic amendments primarily reshape rhizosphere bacterial communities by altering soil nutrient availability, which subsequently drives root metabolic reprogramming in maize.
Although Wudil's peri-urban agricultural soils are generally unpolluted, the study reveals that Cadmium accumulation in vegetables poses a significant non-carcinogenic health risk to consumers, necessitating targeted monitoring and intervention despite low overall soil contamination levels.
This study demonstrates that replacing up to 50% of cottonseed cake with *Gliricidia sepium* hay in the diets of growing Bunaji bulls improves metabolic status, nitrogen retention, and rumen fermentation while maintaining nutrient digestibility, establishing it as a viable and sustainable alternative protein source.
This paper proposes "ClimateResCrop-XAI++," a novel deep learning framework that integrates enhanced soil fertility and weather data with explainability and counterfactual decision intelligence to achieve 98.86% accuracy in recommending climate-resilient crops for sustainable precision agriculture.
This study of 1,240 tie-stall dairy cows across four Sri Lankan regions identifies significant regional variations in lameness, subclinical mastitis, and hock wounds, revealing that specific flooring characteristics and hygiene management are critical, interacting risk factors that can be optimized to substantially improve cow welfare and milk production.
This study utilizes an open and reproducible workflow combining mixed models and multivariate analyses on a large spring wheat population to demonstrate that the Rht-B1p allele is the strongest multivariate discriminator for agronomic traits, while emphasizing the critical need to account for family structure to obtain unbiased effect estimates for marker-assisted selection.