Photograph-HTP.rar

An automated high-throughput phenotyping platform (HTP) was used to quantify 77 image-based traits (i-traits) for 228 maize inbred lines across all developmental stages. Time-resolved i-traits with novel digital phenotypes and complex correlations with agronomic traits were characterized to reveal the dynamics of maize growth. Integrating the plant height-association network with the transcriptome profiles of specific internodes revealed 65 hub genes playing vital roles during the rapid growth. A prediction model for final plant height based on i-traits was made using machine learning, and the predictive performance was assessed in validation along developmental stages with a moderate, strong and very strong correlation between prediction and experimental dataset archived from early S4  (tenth-leaf) stage.