一种融合多环境因子预测新环境材料表型的方法
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUAZHONG AGRI UNIV
- Filing Date
- 2024-06-19
- Publication Date
- 2026-07-17
AI Technical Summary
Existing generalized best linear unbiased prediction methods (gBLUP) fail to effectively consider the interaction between genotype and environment when predicting crop phenotypes under new environments, resulting in inaccurate prediction results and making it difficult to optimize crop breeding under climate change.
By acquiring data on the planting environment and time period of the materials, a sliding window technique is used to select the window with the highest correlation to the phenotype in the training set to represent the environmental data. A multi-environmental factor model is constructed, which is combined with GBLUP to predict new environmental phenotypes. Linear regression and quadratic interpolation techniques are used to improve the prediction accuracy.
It enables accurate prediction of crop phenotypes under new environments, improves the accuracy and efficiency of breeding, and provides suggestions for optimizing crop varieties under specific ecological environments.
Smart Images
Figure CN118629491B_ABST