Search Results - Takai, T

Time-related mapping of quantitative trait loci controlling grain-filling in rice (Oryza sativa L.) by Takai, T., Fukuta, Y., Shiraiwa, T., Horie, T.

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Genetic mechanism of heat stress tolerance at anthesis among three different rice varieties with different fertilities under heat stress by Takai, Toshiyuki, Lumanglas, Patrick, Simon, Eliza V.

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Identifying key traits in high-yielding rice cultivars for adaptability to both temperate and tropical environments by Takai, Toshiyuki, Lumanglas, Patrick, Simon, Eliza Vie, Arai-Sanoh, Yumiko, Asai, Hidetoshi, Kobayashi, Nobuya

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SPIKE, a quantitative-trait locus, increases rice grain yield under low-yield conditions by Takai, Toshiyuki, Fujita, Daisuke, Lumanglas, Patrick, Simon, Eliza Vie, Sasaki, Kazuhiro, Ishimaru, Tsutomu, Asai, Hidetoshi, Kobayashi, Nobuya

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Detection of a quantitative trait locus controlling carbon isotope discrimination and its contribution to stomatal conductance in japonica rice by Takai, Toshiyuki, Ohsumi, Akihiro, San-oh, Yumiko, Laza, Ma. Rebecca C., Kondo, Motohiko, Yamamoto, Toshio, Yano, Masahiro

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Development and evaluation of pyramiding lines carrying early or late heading QTLs in the indica rice cultivar ‘IR64’ by Takai, Toshiyuki, Lumanglas, Patrick, Fujita, Daisuke, Sasaki, Kazuhiro, Rakotoarisoa, Njato Michael, Tsujimoto, Yasuhiro, Kobayashi, Nobuya, Simon, Eliza Vie

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Robustness of the RGB image-based estimation for rice above-ground biomass by utilizing the dataset collected across multiple locations by Nakajima, Kota, Saito, Kazuki, Tsujimoto, Yasuhiro, Takai, Toshiyuki, Mochizuki, Atsushi, Yamaguchi, Tomoaki, Ibrahim, Ali, Mairoua, Salifou Goube, Andrianary, Bruce Haja, Katsura, Keisuke, Tanaka, Yu

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Development of introgression lines of an Indica-type rice variety, IR64, for unique agronomic traits and detection of the responsible chromosomal regions by Fujita, Daisuke, Santos, Rizza E., Ebron, Leodegario A., Telebanco-Yanoria, Mary J., Kato, Hiroshi, Kobayashi, Sohei, Uga, Yusaku, Araki, Etsuko, Takai, Toshiyuki, Tsunematsu, Hiroshi, Imbe, Tokio, Khush, Gurdev S., Brar, Darshan S., Fukuta, Yoshimichi, Kobayashi, Nobuya

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Characterization of introgression lines for yield-related traits with indica-type rice variety IR64 genetic background by Fujita, Daisuke, SANTOS, Rizza Eve M., Ebron, Leodegario A., TELEBANCO-YANORIA, Mary J., Kato, Hiroshi, Kobayashi, Sohei, Uga, Yusaku, Araki, Etsuko, Takai, Toshiyuki, TSUNEMATSU, Hiroshi, Imbe, Tokio, Khush, Gurdev S., Brar, Darshan S., Fukuta, Yoshimichi, Kobayashi, Nobuya

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Control of root system architecture by DEEPER ROOTING 1 increases rice yield under drought conditions by Uga, Y., Sugimoto, K, Ogawa, Satoshi, Rane, Jagadish, Ishitani, Manabu, Hara, N, Kitomi, Y, Inukai, Y., Ono, K, Kanno, N, Inoue, H, Takehisa, H, Motoyama, R, Nagamura, Y, Wu, J., Matsumoto, T, Takai, T, Okuno, K, Yano, M.

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Precise estimation of genomic regions controlling lodging resistance using a set of reciprocal chromosome segment substitution lines in rice by Ookawa, Taiichiro, Aoba, Ryo, Yamamoto, Toshio, Ueda, Tadamasa, Takai, Toshiyuki, Fukuoka, Shuichi, Ando, Tsuyu, Adachi, Shunsuke, Matsuoka, Makoto, Ebitani, Takeshi, Kato, Yoichiro, Mulsanti, Indria Wahyu, Kishii, Masahiro, Reynolds, Matthew, Piñera, Francisco, Kotake, Toshihisa, Kawasaki, Shinji, Motobayashi, Takashi, Hirasawa, Tadashi

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Deep learning-based estimation of rice yield using RGB image by Tanaka, Y, Watanabe, T., Katsura, K., Tsujimoto, Y., Takai, T., Tanaka, T., Kawamura, K., Saito, H., Homma, K., Mairoua, S., Ahouanton, K., Ibrahim, A., Senthilkumar, Kalimuthu, Semwal, V., Corredor, E., El-Namaky, R., Manigbas,N., Quilang, E.J.P., Iwahashi, Y., Nakajima, K., Takeuchi, E., Saito, Kazuki

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Physiological and morphological characterization of a high-yielding rice introgression line, YTH183, with genetic background of Indica Group cultivar, IR 64 by Ishimaru, Tsutomu, Qin, Jianquan, Sasaki, Kazuhiro, Fujita, Daisuke, Gannaban, Ritchel B., Lumanglas, Patrick D., Simon, Eliza-Vie M., Ohsumi, Akihiro, Takai, Toshiyuki, Kondo, Motohiko, Collard, Bertrand, Rustini, Sri, Voradeth, Singty, Boualaphanh, Chanthakhone, Susanto, Untung, Hairmansis, Aris, Hayashi, Keiichi, Jagadish, Krishna S.V., Fukuta, Yoshimichi, Kobayashi, Nobuya

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Deep Learning Enables Instant and Versatile Estimation of Rice Yield Using Ground-Based RGB Images by Tanaka, Y., Watanabe, T., Katsura, K., Tsujimoto, Y., Takai, T., Tanaka, T.S.T., Kawamura, K., Saito, H., Homma, K., Ahouanton, K., Ibrahim, A., Senthilkumar, K., Semwal, V.K., Matute, E.J.G., Corredor, E., El-Namaky, R., Manigbas, N., Quilang, E.J.P., Iwahashi, Y., Nakajima, K., Takeuchi, E., Saito, K., Mairoua, S.G.

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