[HTML][HTML] Genomic selection: A breakthrough technology in rice breeding
Y Xu, K Ma, Y Zhao, X Wang, K Zhou, G Yu, C Li, P Li… - The Crop Journal, 2021 - Elsevier
Rice (Oryza sativa) provides a staple food source for more than half the world population.
However, the current pace of rice breeding in yield growth is insufficient to meet the food …
However, the current pace of rice breeding in yield growth is insufficient to meet the food …
Crop breeding for a changing climate: Integrating phenomics and genomics with bioinformatics
Key message Safeguarding crop yields in a changing climate requires bioinformatics
advances in harnessing data from vast phenomics and genomics datasets to translate …
advances in harnessing data from vast phenomics and genomics datasets to translate …
HIBLUP: an integration of statistical models on the BLUP framework for efficient genetic evaluation using big genomic data
Human diseases and agricultural traits can be predicted by modeling a genetic random
polygenic effect in linear mixed models. To estimate variance components and predict …
polygenic effect in linear mixed models. To estimate variance components and predict …
[HTML][HTML] Digital mapping of soil salinization based on Sentinel-1 and Sentinel-2 data combined with machine learning algorithms
G Ma, J Ding, L Han, Z Zhang, S Ran - Regional Sustainability, 2021 - Elsevier
Soil salinization is one of the most important causes of land degradation and desertification,
especially in arid and semi-arid areas. The dynamic monitoring of soil salinization is of great …
especially in arid and semi-arid areas. The dynamic monitoring of soil salinization is of great …
The application of pangenomics and machine learning in genomic selection in plants
Genomic selection approaches have increased the speed of plant breeding, leading to
growing crop yields over the last decade. However, climate change is impacting current and …
growing crop yields over the last decade. However, climate change is impacting current and …
A stacking ensemble learning framework for genomic prediction
M Liang, T Chang, B An, X Duan, L Du, X Wang… - Frontiers in …, 2021 - frontiersin.org
Machine learning (ML) is perhaps the most useful tool for the interpretation of large genomic
datasets. However, the performance of a single machine learning method in genomic …
datasets. However, the performance of a single machine learning method in genomic …
Genomic prediction in hybrid breeding: I. Optimizing the training set design
AE Melchinger, R Fernando, C Stricker… - Theoretical and Applied …, 2023 - Springer
Key message Training sets produced by maximizing the number of parent lines, each
involved in one cross, had the highest prediction accuracy for H0 hybrids, but lowest for H1 …
involved in one cross, had the highest prediction accuracy for H0 hybrids, but lowest for H1 …
GMStool: GWAS-based marker selection tool for genomic prediction from genomic data
The increased accessibility to genomic data in recent years has laid the foundation for
studies to predict various phenotypes of organisms based on the genome. Genomic …
studies to predict various phenotypes of organisms based on the genome. Genomic …
Genomic selection using a subset of SNPs identified by genome-wide association analysis for disease resistance traits in aquaculture species
Z Luo, Y Yu, J Xiang, F Li - Aquaculture, 2021 - Elsevier
Genomic selection (GS) has been proved to be a useful method for selective breeding.
However, the cost for genotyping a large amount of SNPs is too expensive, especially for …
However, the cost for genotyping a large amount of SNPs is too expensive, especially for …
Target-oriented prioritization: targeted selection strategy by integrating organismal and molecular traits through predictive analytics in breeding
Genomic prediction in crop breeding is hindered by modeling on limited phenotypic traits.
We propose an integrative multi-trait breeding strategy via machine learning algorithm …
We propose an integrative multi-trait breeding strategy via machine learning algorithm …