Machine learning in plant science and plant breeding
Technological developments have revolutionized measurements on plant genotypes and
phenotypes, leading to routine production of large, complex data sets. This has led to …
phenotypes, leading to routine production of large, complex data sets. This has led to …
Genomic selection: A tool for accelerating the efficiency of molecular breeding for development of climate-resilient crops
Since the inception of the theory and conceptual framework of genomic selection (GS),
extensive research has been done on evaluating its efficiency for utilization in crop …
extensive research has been done on evaluating its efficiency for utilization in crop …
Artificial intelligence in plant breeding
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 …
modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data …
Whole-genome regression and prediction methods applied to plant and animal breeding
G de Los Campos, JM Hickey, R Pong-Wong… - Genetics, 2013 - academic.oup.com
Genomic-enabled prediction is becoming increasingly important in animal and plant
breeding and is also receiving attention in human genetics. Deriving accurate predictions of …
breeding and is also receiving attention in human genetics. Deriving accurate predictions of …
[HTML][HTML] Machine learning approaches for crop improvement: Leveraging phenotypic and genotypic big data
H Tong, Z Nikoloski - Journal of plant physiology, 2021 - Elsevier
Highly efficient and accurate selection of elite genotypes can lead to dramatic shortening of
the breeding cycle in major crops relevant for sustaining present demands for food, feed …
the breeding cycle in major crops relevant for sustaining present demands for food, feed …
Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat
Background In the study of associations between genomic data and complex phenotypes
there may be relationships that are not amenable to parametric statistical modeling. Such …
there may be relationships that are not amenable to parametric statistical modeling. Such …
Benchmarking parametric and machine learning models for genomic prediction of complex traits
The usefulness of genomic prediction in crop and livestock breeding programs has
prompted efforts to develop new and improved genomic prediction algorithms, such as …
prompted efforts to develop new and improved genomic prediction algorithms, such as …
Parametric and nonparametric statistical methods for genomic selection of traits with additive and epistatic genetic architectures
R Howard, AL Carriquiry… - G3: Genes, Genomes …, 2014 - academic.oup.com
Parametric and nonparametric methods have been developed for purposes of predicting
phenotypes. These methods are based on retrospective analyses of empirical data …
phenotypes. These methods are based on retrospective analyses of empirical data …
Kernel-based whole-genome prediction of complex traits: a review
Prediction of genetic values has been a focus of applied quantitative genetics since the
beginning of the 20th century, with renewed interest following the advent of the era of whole …
beginning of the 20th century, with renewed interest following the advent of the era of whole …
Machine learning methods and predictive ability metrics for genome-wide prediction of complex traits
Genome-wide prediction of complex traits has become increasingly important in animal and
plant breeding, and is receiving increasing attention in human genetics. Most common …
plant breeding, and is receiving increasing attention in human genetics. Most common …