AIMC Topic: Plant Breeding

Clear Filters Showing 81 to 85 of 85 articles

Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics.

Bioinformatics (Oxford, England) Jun 1, 2023
MOTIVATION: Developing new crop varieties with superior performance is highly important to ensure robust and sustainable global food security. The speed of variety development is limited by long field cycles and advanced generation selections in plan...
Phenotype Deep Learning Genomics Genotype Triticum Edible Grain Selection, Genetic Plant Breeding Phenomics
View on PubMed DOI

Multimodal deep learning methods enhance genomic prediction of wheat breeding.

G3 (Bethesda, Md.) May 2, 2023
While several statistical machine learning methods have been developed and studied for assessing the genomic prediction (GP) accuracy of unobserved phenotypes in plant breeding research, few methods have linked genomics and phenomics (imaging). Deep ...
Phenotype Deep Learning Genomics Genotype Models, Genetic Triticum Plant Breeding
View on PubMed DOI

Integrating a crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning.

Journal of experimental botany Nov 2, 2022
A major challenge for the estimation of crop traits (biophysical variables) from canopy reflectance is the creation of a high-quality training dataset. To address this problem, this research investigated a conceptual framework by integrating a crop g...
Deep Learning Water Plant Leaves Triticum Chlorophyll Plant Breeding
View on PubMed DOI

Challenges for FAIR-compliant description and comparison of crop phenotype data with standardized controlled vocabularies.

Database : the journal of biological databases and curation May 15, 2021
Crop phenotypic data underpin many pre-breeding efforts to characterize variation within germplasm collections. Although there has been an increase in the global capacity for accumulating and comparing such data, a lack of consistency in the systemat...
Phenotype Metadata Biological Ontologies Vocabulary, Controlled Plant Breeding
View on PubMed DOI

Applications of Machine Learning Methods to Genomic Selection in Breeding Wheat for Rust Resistance.

The plant genome Jul 1, 2018
New methods and algorithms are being developed for predicting untested phenotypes in schemes commonly used in genomic selection (GS). The prediction of disease resistance in GS has its own peculiarities: a) there is consensus about the additive natur...
Neural Networks, Computer Machine Learning Genomics Models, Genetic Support Vector Machine Triticum Plant Diseases Linear Models Basidiomycota Disease Resistance Genome, Plant Plant Breeding
View on PubMed DOI
Popular Topics
Recent Journals