AI-Powered Predictions of Sugarcane and Forage Grass performance in the Field

Artificial intelligence predicts sugarcane performance in the field

According to a Brazilian study published by Scientific Reports, artificial intelligence (AI), can be used for creating efficient models for genomic selection for sugarcane and foragegrass varieties. It also predicts their performance on the field based on their DNA.

The proposed method improved the accuracy of prediction by over 50% compared to traditional breeding techniques. It is the first time that a highly effective genomic selection method using machine learning was proposed for polyploid (where cells have two or more complete sets of chromosomes), which includes the grasses.

Machine learning, a branch in AI and computer sciences that involves statistics and optimization and has countless applications, is a branch involving AI and computer. Its primary goal is to create algorithms which automatically extract patterns from data sets. It can be used for predicting the performance of plants, such as whether they will be resistant or tolerant to biotic stressors such as pests or diseases caused by insects or nematodes or bacteria.