AI Medical Compendium Journal:
Journal of the science of food and agriculture

Showing 11 to 20 of 48 articles

A novel method combining deep learning with the Kennard-Stone algorithm for training dataset selection for image-based rice seed variety identification.

Journal of the science of food and agriculture Jun 21, 2024
BACKGROUND: Different varieties of rice vary in planting time, stress resistance, and other characteristics. With advances in rice-breeding technology, the number of rice varieties has increased significantly, making variety identification crucial fo...
Seeds Oryza Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Algorithms
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Deep recognition of rice disease images: how many training samples do we really need?

Journal of the science of food and agriculture Jun 15, 2024
BACKGROUND: With the rapid development of deep learning, the recognition of rice disease images using deep neural networks has become a hot research topic. However, most previous studies only focus on the modification of deep learning models, while l...
Neural Networks, Computer Deep Learning Oryza Plant Diseases Image Processing, Computer-Assisted Plant Leaves
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Investigating the effect of climate factors on fig production efficiency with machine learning approach.

Journal of the science of food and agriculture May 31, 2024
BACKGROUND: This study employs a machine learning approach to investigate the impact of climate change on fig production in Turkey. The eXtreme Gradient Boosting (XGBoost) algorithm is used to analyze production performance and climate variable data ...
Temperature Agriculture Machine Learning Ficus Crop Production Turkey Climate Change
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Integrating deep learning with non-destructive thermal imaging for precision guava ripeness determination.

Journal of the science of food and agriculture May 28, 2024
BACKGROUND: To mitigate post-harvest losses and inform harvesting decisions at the same time as ensuring fruit quality, precise ripeness determination is essential. The complexity arises in assessing guava ripeness as a result of subtle alterations i...
Psidium Fruit Deep Learning
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EResNet-SVM: an overfitting-relieved deep learning model for recognition of plant diseases and pests.

Journal of the science of food and agriculture Apr 27, 2024
BACKGROUND: The accurate recognition and early warning for plant diseases and pests are a prerequisite of intelligent prevention and control for plant diseases and pests. As a result of the phenotype similarity of the hazarded plant after plant disea...
Pest Control Deep Learning Support Vector Machine Insecta Plant Diseases Neural Networks, Computer Animals
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Integrating mid-infrared spectroscopy, machine learning, and graphical bias correction for fatty acid prediction in water buffalo milk.

Journal of the science of food and agriculture Apr 15, 2024
BACKGROUND: Buffalo milk, constituting 15% of global production, has higher fatty acids content than Holstein milk. Fourier-transform mid-infrared (FT-MIR) spectroscopy is widely used for dairy analysis, but its application to buffalo milk, with larg...
Milk Animals Spectroscopy, Fourier Transform Infrared Machine Learning Fatty Acids Buffaloes
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Modelling tomato pericarp microstructure as force control reference for harvesting robot.

Journal of the science of food and agriculture Mar 25, 2024
BACKGROUND: The harvest of fruit can be significantly advanced with the thriving development of intelligent and automated robot technologies. Nevertheless, the picking success rate of tomato fruit still requires improvement as some fruits are unexpec...
Fruit Robotics Food Handling Solanum lycopersicum Algorithms
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Electronic eye and electronic tongue data fusion combined with a GETNet model for the traceability and detection of Astragalus.

Journal of the science of food and agriculture Mar 22, 2024
BACKGROUND: Astragalus is a widely used traditional Chinese medicine material that is easily confused due to its quality, price and other factors derived from different origins. This article describes a novel method for the rapid tracing and detectio...
Electronic Nose Neural Networks, Computer Taste Drugs, Chinese Herbal Astragalus Plant
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Optimization of computational intelligence approach for the prediction of glutinous rice dehydration.

Journal of the science of food and agriculture Mar 22, 2024
BACKGROUND: Five computational intelligence approaches, namely Gaussian process regression (GPR), artificial neural network (ANN), decision tree (DT), ensemble of trees (EoT) and support vector machine (SVM), were used to describe the evolution of mo...
Oryza Dehydration Bayes Theorem Support Vector Machine Neural Networks, Computer Decision Trees Artificial Intelligence Water
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Models for predicting coffee yield from chemical characteristics of soil and leaves using machine learning.

Journal of the science of food and agriculture Mar 15, 2024
BACKGROUND: Coffee farming constitutes a substantial economic resource, representing a source of income for several countries due to the high consumption of coffee worldwide. Precise management of coffee crops involves collecting crop attributes (cha...
Machine Learning Soil Agriculture Plant Leaves Crop Production Coffea Coffee
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