Tracing the geographical origin of rice is of great significance in protecting the rights and interests of consumers and legitimate producers, as well as ensuring food safety. Here, we propose the combination of machine learning (ML) and clustering-t...
Accurate nitrogen management in rice (Oryza sativa L.) is essential for optimizing both crop productivity and environmental sustainability. This study evaluated the potential of Near-Infrared Spectroscopy (NIRS) combined with chemometric modeling to ...
This study links rice leaf metabolome to yield traits, identifying 13 key metabolites through computational metabolomics. These enable early prediction of high-yield varieties, enhancing screening strategies in crop breeding. Metabolites serve as dyn...
Black gram, also known as urad bean, is an economically crucial crop widely cultivated in India, particularly in the central and southern regions. However, black gram is highly prone to multiple leaf diseases, resulting in considerable crop losses an...
In modern precision agriculture, early and accurate identification of crop diseases is crucial for reducing yield loss and minimizing pesticide overuse. This study proposes an IoT-enabled framework that integrates convolutional neural networks (CNNs)...
In the search to improve the sustainability of the food supply chain, the market for plant-based cheese analogs is growing. However, sensory defects, particularly related to flavor, remain a challenge. Here we developed a hybrid plant-dairy cheese th...
Journal of agricultural and food chemistry
Oct 22, 2025
The brown planthopper (BPH) is a major rice pest in Asia, with the most severe damage occurring at the adult stage in rice. Although breeding resistant varieties is key to pest control, current screening focuses mainly on seedlings using destructive,...
During rice cultivation, common rice diseases and pests such as Rice blast, Bacterial blight, Brown-planthopper and Leaf-folder will significantly affect the yield and quality. The current model is limited to detecting rice diseases or pests alone, a...
Accurate and early disease detection in paddy crops is essential for maximizing crop yield which ensures food security. Traditional methods are often labor-intensive, time-consuming, and domain-specific expertise. Feed-forward deep-learning models wi...
BACKGROUND: Drought is a global challenge that severely restricts crop yields and threatens food security. Plants respond to drought stress by modulating gene expression before visible phenotypic changes occur. However, most studies of drought resist...
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