Author

A. Kaga

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Plant Biology· 3 Bioengineering· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:plant (other)· 3 Approach:experimental assay· 2 Assay:imaging· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:development & morphogenesis· 1

Frequent Co-Authors

S. Ninomiya· 2 shared A. Itoh· 1 shared A. J. Nagano· 1 shared A. Onogi· 1 shared A. Sugiyama· 1 shared D. Sekine· 1 shared E. Moriyoshi· 1 shared H. Iwata· 1 shared

Activity by Year

2019-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 11 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersPlant Biology

S. Ninomiya

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Apoplast-localized β-Glucosidase Elevates Isoflavone Accumulation in the Soybean Rhizosphere

H. Matsuda, Y. Yamazaki, E. Moriyoshi, M. Nakayasu, S. Yamazaki, Y. Aoki, H. Takase, S. Okazaki, A. J. Nagano, A. Kaga, K. Yazaki, A. Sugiyama

This study shows that apoplast-localized β-glucosidase (ICHG) increases isoflavone accumulation in the soybean rhizosphere but is not required for plant-microbe interactions.

bioRxiv · Dec 13, 2022Plant Biology

A method for identifying environmental stimuli and genes responsible for genotype-by-environment interactions from a large-scale multi-environment data set

A. Onogi, D. Sekine, A. Kaga, S. Nakano, T. Yamada, J. Yu, S. Ninomiya

This paper introduces a method to identify environmental stimuli and genes involved in genotype-by-environment interactions using large-scale multi-environment data.

bioRxiv · Oct 25, 2021Plant Biology

Time-series Multi-spectral Imaging in Soybean for Improving Biomass and Genomic Prediction Accuracy

K. Sakurai, Y. Toda, H. Kajiya-Kanegae, Y. Ohmori, Y. Yamasaki, H. Takahashi, H. Takanashi, M. Tsuda, H. Tsujimoto, A. Kaga, M. Nakazono, T. Fujiwara, H. Iwata

This study uses multi-spectral imaging to predict soybean biomass by analyzing growth stages and irrigation effects on genomic and phenotypic accuracy.

bioRxiv · Sep 30, 2021 · PreprintPlant Biology

Easy MPE: Extraction of quality microplot images for UAV-based high-throughput field phenotyping

L. Tresch, Y. Mu, A. Itoh, A. Kaga, K. Taguchi, M. Hirafuji, S. Ninomiya, W. Guo

Easy MPE automates microplot extraction from UAV images, achieving 91% average IOU accuracy compared to manual methods.

bioRxiv · Nov 20, 2019Bioengineering