AIMC Topic: Crops, Agricultural

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Genomic selection: Essence, applications, and prospects.

The plant genome Jun 1, 2025
Genomic selection (GS) emerged as a key part of the solution to ensure the food supply for the growing human population thanks to advances in genotyping and other enabling technologies and improved understanding of the genotype-phenotype relationship...
Phenotype Genomics Selection, Genetic Genome, Plant Plant Breeding Genotype Crops, Agricultural
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An efficient plant disease detection using transfer learning approach.

Scientific reports May 30, 2025
Plant diseases pose significant challenges to farmers and the agricultural sector at large. However, early detection of plant diseases is crucial to mitigating their effects and preventing widespread damage, as outbreaks can severely impact the produ...
Plant Diseases Plant Leaves Crops, Agricultural Machine Learning Image Processing, Computer-Assisted
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Using supervised machine-learning approaches to understand abiotic stress tolerance and design resilient crops.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences May 29, 2025
Abiotic stresses such as drought, heat, cold, salinity and flooding significantly impact plant growth, development and productivity. As the planet has warmed, these abiotic stresses have increased in frequency and intensity, affecting the global food...
Stress, Physiological Plant Breeding Climate Change Crops, Agricultural Supervised Machine Learning
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AI-IoT based smart agriculture pivot for plant diseases detection and treatment.

Scientific reports May 13, 2025
There are some key problems faced in modern agriculture that IoT-based smart farming. These problems such shortage of water, plant diseases, and pest attacks. Thus, artificial intelligence (AI) technology cooperates with the Internet of Things (IoT) ...
Artificial Intelligence Deep Learning Agriculture Plant Diseases Internet of Things Plant Leaves Crops, Agricultural Robotics
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Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency.

The Plant cell May 9, 2025
Systems biology aims to uncover gene regulatory networks (GRNs) for agricultural traits, but validating them in crops is challenging. We addressed this challenge by learning and validating model-to-crop transcription factor (TF) regulons governing ni...
Arabidopsis Regulon Nitrogen Crops, Agricultural Plant Proteins Transcription Factors Gene Expression Regulation, Plant Machine Learning Zea mays Gene Regulatory Networks
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Integration of machine learning and genome-wide association study to explore the genomic prediction accuracy of agronomic trait in oats (Avena sativa L.).

The plant genome Mar 1, 2025
Machine learning (ML) has garnered significant attention for its potential to enhance the accuracy of genomic predictions (GPs) in various economic crops with the use of complete genomic information. Genome-wide association studies (GWAS) are widely ...
Plant Breeding Machine Learning Genome, Plant Genomics Quantitative Trait Loci Crops, Agricultural Polymorphism, Single Nucleotide Phenotype Avena Genome-Wide Association Study
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A framework for identifying calcium accumulation problem in cropland: Integrating field surveys, legacy soil map, and machine learning models.

PloS one Jan 1, 2025
The calcium accumulation problem (CAP) in cinnamon soil regions of northern China significantly impacts crop yields. Identifying and mitigating CAP is crucial for improving soil quality and agricultural productivity. This study, based on field resear...
Machine Learning Agriculture Calcium Crops, Agricultural Soil China
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Segmentation-based lightweight multi-class classification model for crop disease detection, classification, and severity assessment using DCNN.

PloS one Jan 1, 2025
Leaf diseases in Zea mays crops have a significant impact on both the calibre and volume of maize yield, eventually impacting the market. Prior detection of the intensity of an infection would enable the efficient allocation of treatment resources an...
Plant Diseases Zea mays Neural Networks, Computer Plant Leaves Crops, Agricultural
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Recent advances of machine learning in the geographical origin traceability of food and agro-products: A review.

Comprehensive reviews in food science and food safety Jan 1, 2025
The geographical origin traceability of food and agro-products has been attracted worldwide. Especially with the rise of machine learning (ML) technology, it provides cutting-edge solutions to erstwhile intractable issues to identify the origin of fo...
Geography Machine Learning Food Analysis Agriculture Crops, Agricultural
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Early and late blight disease identification in tomato plants using a neural network-based model to augmenting agricultural productivity.

Science progress Jan 1, 2024
Computer-advanced technologies have a significant impact across various fields. It is widely recognized that diseases have a detrimental effect on crop productivity and can significantly impact the economy, particularly in agricultural countries. Tom...
Crops, Agricultural Plant Leaves Plant Diseases Solanum lycopersicum Neural Networks, Computer Agriculture
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