PT  - JOURNAL ARTICLE
AU  - A. Bari
AU  - H. Ouabbou
AU  - A. Jilal
AU  - H. Khazaei
AU  - F.L. Stoddard
AU  - M.J. Sillanpää
TI  - Machine Learning Speeding Up the Development of Portfolio of New Crop Varieties to Adapt to and Mitigate Climate Change
AID  - 10.1101/2021.10.06.463347
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.10.06.463347
4099  - http://biorxiv.org/content/early/2021/10/06/2021.10.06.463347.short
4100  - http://biorxiv.org/content/early/2021/10/06/2021.10.06.463347.full
AB  - Climate change poses serious challenges to achieving food security in a time of a need to produce more food to keep up with the world’s increasing demand for food. There is an urgent need to speed up the development of new high yielding varieties with traits of adaptation and mitigation to climate change. Mathematical approaches, including ML approaches, have been used to search for such traits, leading to unprecedented results as some of the traits, including heat traits that have been long sought-for, have been found within a short period of time.Competing Interest StatementThe authors have declared no competing interest.