首页|Trait prediction through computational intelligence and machine learning applied to soybean (Glycine max) breeding in shaded environments
Trait prediction through computational intelligence and machine learning applied to soybean (Glycine max) breeding in shaded environments
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from biorxiv.org: “This study aims to identify more relevant predictors traits, considering different prediction approaches in soybean under different shading levels in the field, using methodologies based on artificial intelligence and machine learning. The experiments were carried out under different shading levels in a greenhouse and in the field, using sixteen cultivars.
NETL
NSTL
