[PDF][PDF] Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction
The first paradigm of plant breeding involves direct selection-based phenotypic observation,
followed by predictive breeding using statistical models for quantitative traits constructed …
followed by predictive breeding using statistical models for quantitative traits constructed …
Machine learning bridges omics sciences and plant breeding
J Yan, X Wang - Trends in Plant Science, 2023 - cell.com
Some of the biological knowledge obtained from fundamental research will be implemented
in applied plant breeding. To bridge basic research and breeding practice, machine learning …
in applied plant breeding. To bridge basic research and breeding practice, machine learning …
Artificial intelligence in food safety: A decade review and bibliometric analysis
Z Liu, S Wang, Y Zhang, Y Feng, J Liu, H Zhu - Foods, 2023 - mdpi.com
Artificial Intelligence (AI) technologies have been powerful solutions used to improve food
yield, quality, and nutrition, increase safety and traceability while decreasing resource …
yield, quality, and nutrition, increase safety and traceability while decreasing resource …
A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species
Genomic selection is an integral tool for breeders to accurately select plants directly from
genotype data leading to faster and more resource-efficient breeding programs. Several …
genotype data leading to faster and more resource-efficient breeding programs. Several …
Yield prediction through integration of genetic, environment, and management data through deep learning
Accurate prediction of the phenotypic outcomes produced by different combinations of
genotypes, environments, and management interventions remains a key goal in biology with …
genotypes, environments, and management interventions remains a key goal in biology with …
Rapid identification of high and low cadmium (Cd) accumulating rice cultivars using machine learning models with molecular markers and soil Cd levels as input data
Excessive accumulation of cadmium (Cd) in rice grains threatens food safety and human
health. Growing low Cd accumulating rice cultivars is an effective approach to produce low …
health. Growing low Cd accumulating rice cultivars is an effective approach to produce low …
Genomic prediction and association mapping of maize grain yield in multi-environment trials based on reaction norm models
Genotype-by-environment interaction (GEI) is among the greatest challenges for maize
breeding programs. Strong GEI limits both the prediction of genotype performance across …
breeding programs. Strong GEI limits both the prediction of genotype performance across …
Maize yield prediction using artificial neural networks based on a trial network dataset
PVD de Souza, LP de Rezende, AP Duarte… - … , Technology & Applied …, 2023 - etasr.com
The prediction of grain yield is important for sowing, cultivar positioning, crop management,
and public policy. This study aims to predict maize productivity by applying an artificial …
and public policy. This study aims to predict maize productivity by applying an artificial …
Recent advances in artificial intelligence, mechanistic models, and speed breeding offer exciting opportunities for precise and accelerated genomics‐assisted …
Given the challenges of population growth and climate change, there is an urgent need to
expedite the development of high‐yielding stress‐tolerant crop cultivars. While traditional …
expedite the development of high‐yielding stress‐tolerant crop cultivars. While traditional …
Stacked ensembles on basis of parentage information can predict hybrid performance with an accuracy comparable to marker-based GBLUP
PG Heilmann, M Frisch, A Abbadi, T Kox… - Frontiers in Plant …, 2023 - frontiersin.org
Testcross factorials in newly established hybrid breeding programs are often highly
unbalanced, incomplete, and characterized by predominance of special combining ability …
unbalanced, incomplete, and characterized by predominance of special combining ability …