Akito Kaga

The paper proposes a nonlinear two-step model integrating proxy intermediate omics traits to improve phenotypic prediction in soybean, showing better accuracy than linear models.

This paper introduces Cross Potential Selection (CPS), a strategy for selecting crossing pairs in plant breeding to accelerate novel variety production, showing higher genetic improvements in early cycles of simulated breeding programs.

This study uses UAV remote sensing and deep learning to estimate soybean biomass traits and extract latent features for breeding applications.

This study evaluates drought tolerance stability in soybean using time-series multispectral data and genomic prediction models, finding higher accuracy with changing irrigation treatments.

The paper identifies MYB26 as a genetic factor for twisting legume pods through fine-mapping of shattering-related traits in azuki and yard-long beans.

This study performs QTL analysis on zombi pea to identify genetic factors underlying domestication traits, finding conserved QTLs for seed and pod size between zombi pea and cowpea.

This study reduces AmpliSeq library preparation costs by miniaturizing PCR reactions, achieving 100% success with 1500 amplicons in 2.4 L reactions.

This study uses SMRT sequencing to assemble the azuki bean genome, achieving better contiguity and gene annotation compared to second-generation sequencing methods.