Zobrazeno 1 - 10
of 172
pro vyhledávání: '"Akito Kaga"'
Publikováno v:
ACS Omega, Vol 9, Iss 2, Pp 2134-2144 (2024)
Externí odkaz:
https://doaj.org/article/75568403903f45d395ca461e791581ea
Autor:
Mashiro Okada, Clément Barras, Yusuke Toda, Kosuke Hamazaki, Yoshihiro Ohmori, Yuji Yamasaki, Hirokazu Takahashi, Hideki Takanashi, Mai Tsuda, Masami Yokota Hirai, Hisashi Tsujimoto, Akito Kaga, Mikio Nakazono, Toru Fujiwara, Hiroyoshi Iwata
Publikováno v:
Plant Phenomics, Vol 6 (2024)
High-throughput phenotyping serves as a framework to reduce chronological costs and accelerate breeding cycles. In this study, we developed models to estimate the phenotypes of biomass-related traits in soybean (Glycine max) using unmanned aerial veh
Externí odkaz:
https://doaj.org/article/13ad694cc6ca4be8abcde94a694f65bf
Autor:
Kengo Sakurai, Yusuke Toda, Kosuke Hamazaki, Yoshihiro Ohmori, Yuji Yamasaki, Hirokazu Takahashi, Hideki Takanashi, Mai Tsuda, Hisashi Tsujimoto, Akito Kaga, Mikio Nakazono, Toru Fujiwara, Hiroyoshi Iwata
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Plant response to drought is an important yield-related trait under abiotic stress, but the method for measuring and modeling plant responses in a time series has not been fully established. The objective of this study was to develop a method to meas
Externí odkaz:
https://doaj.org/article/d9840b8e8bc94202b304e2afbab4f795
Autor:
Jiangsan Zhao, Akito Kaga, Tetsuya Yamada, Kunihiko Komatsu, Kaori Hirata, Akio Kikuchi, Masayuki Hirafuji, Seishi Ninomiya, Wei Guo
Publikováno v:
Plant Phenomics, Vol 5 (2023)
Developing automated soybean seed counting tools will help automate yield prediction before harvesting and improving selection efficiency in breeding programs. An integrated approach for counting and localization is ideal for subsequent analysis. The
Externí odkaz:
https://doaj.org/article/96840275a35d4d91b7769d48fb00d184
Autor:
Khuynh The Bui, Toshiya Naruse, Hideki Yoshida, Yusuke Toda, Yoshihiro Omori, Mai Tsuda, Akito Kaga, Yuji Yamasaki, Hisashi Tsujimoto, Yasunori Ichihashi, Masami Hirai, Toru Fujiwara, Hiroyoshi Iwata, Makoto Matsuoka, Hirokazu Takahashi, Mikio Nakazono
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
Increasing the water use efficiency of crops is an important agricultural goal closely related to the root system —the primary plant organ for water and nutrient acquisition. In an attempt to evaluate the response of root growth and development of
Externí odkaz:
https://doaj.org/article/61066d8aa4934e2f847836bf87871774
Autor:
Kengo Sakurai, Yusuke Toda, Hiromi Kajiya‐Kanegae, Yoshihiro Ohmori, Yuji Yamasaki, Hirokazu Takahashi, Hideki Takanashi, Mai Tsuda, Hisashi Tsujimoto, Akito Kaga, Mikio Nakazono, Toru Fujiwara, Hiroyoshi Iwata
Publikováno v:
The Plant Genome, Vol 15, Iss 4, Pp n/a-n/a (2022)
Abstract Multispectral (MS) imaging enables the measurement of characteristics important for increasing the prediction accuracy of genotypic and phenotypic values for yield‐related traits. In this study, we evaluated the potential application of te
Externí odkaz:
https://doaj.org/article/e4503a3bf5be4dfd958c0328b8feb572
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
The culmination of conventional yield improving parameters has widened the margin between food demand and crop yield, leaving the potential yield productivity to be bridged by the manipulation of photosynthetic processes in plants. Efficient strategi
Externí odkaz:
https://doaj.org/article/487d3d7e37ea4892b27549a0a51468d3
Genomic Prediction of Green Fraction Dynamics in Soybean Using Unmanned Aerial Vehicles Observations
Autor:
Yusuke Toda, Goshi Sasaki, Yoshihiro Ohmori, Yuji Yamasaki, Hirokazu Takahashi, Hideki Takanashi, Mai Tsuda, Hiromi Kajiya-Kanegae, Raul Lopez-Lozano, Hisashi Tsujimoto, Akito Kaga, Mikio Nakazono, Toru Fujiwara, Frederic Baret, Hiroyoshi Iwata
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
With the widespread use of high-throughput phenotyping systems, growth process data are expected to become more easily available. By applying genomic prediction to growth data, it will be possible to predict the growth of untested genotypes. Predicti
Externí odkaz:
https://doaj.org/article/449a40935d1942dd903f14eddfba3f85
Autor:
Yusuke Tokumitsu, Takuto Kozu, Hiroshi Yamatani, Takeshi Ito, Haruna Nakano, Ayaka Hase, Hiroki Sasada, Yoshitake Takada, Akito Kaga, Masao Ishimoto, Makoto Kusaba, Taiken Nakashima, Jun Abe, Tetsuya Yamada
Publikováno v:
Frontiers in Plant Science, Vol 12 (2022)
The degradation of chlorophyll in mature soybean seeds is closely related to the development of their yellow color. In this study, we examined G, its homologue G-like (GL), and their mutant alleles and investigated the relationship between these gene
Externí odkaz:
https://doaj.org/article/3e304c3e66fe422b9e6a209fb42d83c0
Publikováno v:
Frontiers in Plant Science, Vol 12 (2021)
Early leaf senescence phenotype in soybean could be helpful to shorten the maturation period and prevent green stem disorder. From a high-density mutation library, we identified two early leaf senescence soybean mutant lines, els1-1 (early leaf senes
Externí odkaz:
https://doaj.org/article/9c8ad6e76e1644b0b03dca41b7ac5ca9