A comparative study highlights superiority of LSTM in crop genomic prediction.

Abstract excerpt

MAIN CONCLUSION: We systematically evaluated three key determinants affecting prediction accuracy and the algorithm performance differences based on fifteen state-of-the-art GP methods, and found LSTM suitable for capturing additive and epistatic effects. Genomic prediction (GP) has been developed as an important method supporting crop breeding. By utilizing the phenotype values result from GP, breeders could...

Topics

• Plant Breeding
• Crops, Agricultural
• Genomics
• Algorithms
• Genome, Plant
• Machine Learning
• Polymorphism, Single Nucleotide