Effective weed detection for precise management remains a pertinent issue in modern agriculture. In this study, hyperspectral imaging (HSI) was combined with machine learning (ML) to differentiate between peanut plants and four common weeds found in ...
Peanut (Arachis hypogaea L.), a globally important oilseed crop, increasingly challenged by rising edible oil demands as well as biotic and abiotic stresses. This review synthesizes recent advances in peanut genomics, evolutionary biology, and breedi...
Environmental pollution (Barking, Essex : 1987)
Jun 3, 2025
In China, the co-contamination of soil with cadmium (Cd) and arsenic (As) is one of the most severe forms of combined pollution. Modeling the transfer of Cd and As from co-contaminated soil to crops has not been thoroughly studied. In this study, fiv...
Sensitive and rapid detection of aflatoxin B (AFB) is vital for safeguarding food safety, considering its potent carcinogenic toxicity. Herein, an artificial intelligence-enabled microsphere imaging (AI-MI) immunosensor based on magnetic metal-organi...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Apr 9, 2025
This study developed a convolutional neural network (CNN) model based on feature-level data fusion for quantitatively detecting aflatoxin B1 (AFB1) in peanuts. Using a portable near-infrared (NIR) spectrometer and a Raman spectrometer, NIR and Raman ...
Aflatoxin is a highly toxic substance found in peanuts, posing a serious threat to human health. To address this issue, an improved 1D-MCFViT model combining the Vision Transformer with multi-scale convolutional fusion is proposed to detect aflatoxin...
Cereals are a primary source of sustenance for humanity. Monitoring, controlling, and preventing mycotoxins in cereals are vital for ensuring the safety of the cereals and their derived products. This study introduces transfer learning strategies int...
Food research international (Ottawa, Ont.)
Mar 6, 2025
The natural conditions of various regions, including climate, soil, and water quality, significantly influence the nutrient composition and quality of agricultural products. Identifying the origin of agricultural products can prevent adulteration, im...
Estimating the optimal answer is expensive for huge data resources that decrease the functionality of the system. To solve these issues, the latest groundnut leaf disorder identification model by deep learning techniques is implemented. The images ar...
Groundnut is a noteworthy oilseed crop. Attacks by leaf diseases are one of the most important reasons causing low yield and loss of groundnut plant growth, which will directly diminish the yield and quality. Therefore, an Optimized Wasserstein Deep ...
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