AIMC Topic: Plant Breeding

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Artificial intelligence in plant breeding.

Trends in genetics : TIG Aug 7, 2024
Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scien...
Artificial Intelligence Phenotype Crops, Agricultural Gene Editing Plant Breeding Genotype Genetic Variation
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Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Jul 23, 2024
Incorporating feature-engineered environmental data into machine learning-based genomic prediction models is an efficient approach to indirectly model genotype-by-environment interactions. Complementing phenotypic traits and molecular markers with hi...
Plant Breeding Machine Learning Environment Zea mays Phenotype Gene-Environment Interaction Genomics Models, Genetic Edible Grain Genotype
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Machine learning for genomic and pedigree prediction in sugarcane.

The plant genome Jun 26, 2024
Sugarcane (Saccharum spp.) plays a crucial role in global sugar production; however, the efficiency of breeding programs has been hindered by its heterozygous polyploid genomes. Considering non-additive genetic effects is essential in genome predicti...
Genome, Plant Plant Breeding Saccharum Pedigree Machine Learning Polymorphism, Single Nucleotide Genotype Genomics
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Integrating genomics, phenomics, and deep learning improves the predictive ability for Fusarium head blight-related traits in winter wheat.

The plant genome Jun 9, 2024
Fusarium head blight (FHB) remains one of the most destructive diseases of wheat (Triticum aestivum L.), causing considerable losses in yield and end-use quality. Phenotyping of FHB resistance traits, Fusarium-damaged kernels (FDK), and deoxynivaleno...
Phenotype Triticum Fusarium Plant Diseases Deep Learning Genomics Phenomics Disease Resistance Plant Breeding
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TrG2P: A transfer-learning-based tool integrating multi-trait data for accurate prediction of crop yield.

Plant communications May 15, 2024
Yield prediction is the primary goal of genomic selection (GS)-assisted crop breeding. Because yield is a complex quantitative trait, making predictions from genotypic data is challenging. Transfer learning can produce an effective model for a target...
Neural Networks, Computer Machine Learning Crops, Agricultural Plant Breeding Phenotype Zea mays Triticum Genotype Oryza
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Enhancing genome-wide populus trait prediction through deep convolutional neural networks.

The Plant journal : for cell and molecular biology May 13, 2024
As a promising model, genome-based plant breeding has greatly promoted the improvement of agronomic traits. Traditional methods typically adopt linear regression models with clear assumptions, neither obtaining the linkage between phenotype and genot...
Populus Genome, Plant Plant Breeding Genotype Bayes Theorem Phenotype Deep Learning Neural Networks, Computer
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PlantMine: A Machine-Learning Framework to Detect Core SNPs in Rice Genomics.

Genes May 9, 2024
As a fundamental global staple crop, rice plays a pivotal role in human nutrition and agricultural production systems. However, its complex genetic architecture and extensive trait variability pose challenges for breeders and researchers in optimizin...
Genomics Polymorphism, Single Nucleotide Oryza Machine Learning Genome, Plant Plant Breeding
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Machine learning methods in near infrared spectroscopy for predicting sensory traits in sweetpotatoes.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy May 4, 2024
It has been established that near infrared (NIR) spectroscopy has the potential of estimating sensory traits given the direct spectral responses that these properties have in the NIR region. In sweetpotato, sensory and texture traits are key for impr...
Ipomoea batatas Food Quality Plant Breeding Models, Statistical Sensation Spectroscopy, Near-Infrared Food Analysis Humans Machine Learning Algorithms
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BreedingAIDB: A database integrating crop genome-to-phenotype paired data with machine learning tools applicable to breeding.

Plant communications Apr 3, 2024
Plant Breeding Machine Learning Crops, Agricultural Databases, Genetic Phenotype Genome, Plant
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A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction.

Scientific reports Mar 11, 2024
To explore a robust tool for advancing digital breeding practices through an artificial intelligence-driven phenotype prediction expert system, we undertook a thorough analysis of 11 non-linear regression models. Our investigation specifically emphas...
Glycine max Artificial Intelligence Plant Breeding Algorithms
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