Description
AgAdapt, short for Agriculture Adapt, was a project to develop a robust multimodal approach for phenotype prediction of maize plants.
Phenotype Prediction
Traditionally, phenotype prediction is done with a linear model, which hardly accounts for the environmental influence on genetic data and SNP-SNP interactions. Instead, we propose a Multimodal Deep Learning Approach that combines a variety of dimensionality reduction techniques with a gradient-boosting model.
Data Source
This project uses data from the 2017 dataset collected by the Genomes2Fields Initiative. This includes 32 planting fields across the United States.