A Data-Driven Approach to Sugarcane Breeding Programs with Agronomic Characteristics and Amino Acid Constituent Profiling
Chiaki Ishikawa,
Yasuhiro Date,
Makoto Umeda,
Yusuke Tarumoto,
Megumi Okubo,
Yasujiro Morimitsu,
Yasuaki Tamura,
Yoichi Nishiba,
Hiroshi Ono
Affiliations
Chiaki Ishikawa
Institute of Food Research, National Agriculture and Food Research Organization, 2-1-12 Kannondai, Tsukuba 305-8642, Ibaraki, Japan
Yasuhiro Date
Research Center for Advanced Analysis, National Agriculture and Food Research Organization, 2-1-12 Kannondai, Tsukuba 305-8642, Ibaraki, Japan
Makoto Umeda
Kyushu-Okinawa Agricultural Research Center, National Agriculture and Food Research Organization, Annou 1742-1, Nishinoomote, Kagoshima 891-3102, Japan
Yusuke Tarumoto
Kyushu-Okinawa Agricultural Research Center, National Agriculture and Food Research Organization, Annou 1742-1, Nishinoomote, Kagoshima 891-3102, Japan
Megumi Okubo
Kyushu-Okinawa Agricultural Research Center, National Agriculture and Food Research Organization, Annou 1742-1, Nishinoomote, Kagoshima 891-3102, Japan
Yasujiro Morimitsu
Institute for Human Life Science, Ochanomizu University, 2-1-1 Otsuka, Bunkyo-ku, Tokyo 112-8610, Japan
Yasuaki Tamura
Western Region Agricultural Research Center (Kinki, Chugoku and Shikoku Regions), National Agriculture and Food Research Organization, 6-12-1 Nishifukatsu-cho, Fukuyama, Hiroshima 721-8514, Japan
Yoichi Nishiba
Kyushu-Okinawa Agricultural Research Center, National Agriculture and Food Research Organization, 2421 Suya, Koshi, Kumamoto 861-1192, Japan
Hiroshi Ono
Research Center for Advanced Analysis, National Agriculture and Food Research Organization, 2-1-12 Kannondai, Tsukuba 305-8642, Ibaraki, Japan
Sugarcane (Saccharum spp. hybrids) and its processed products have supported local industries such as those in the Nansei Islands, Japan. To improve the sugarcane quality and productivity, breeders select better clones by evaluating agronomic characteristics, such as commercially recoverable sugar and cane yield. However, other constituents in sugarcane remain largely unutilized in sugarcane breeding programs. This study aims to establish a data-driven approach to analyze agronomic characteristics from breeding programs. This approach also determines a correlation between agronomic characteristics and free amino acid composition to make breeding programs more efficient. Sugarcane was sampled in clones in the later stage of breeding selection and cultivars from experimental fields on Tanegashima Island. Principal component analysis and hierarchical cluster analysis using agronomic characteristics revealed the diversity and variability of each sample, and the data-driven approach classified cultivars and clones into three groups based on yield type. A comparison of free amino acid constituents between these groups revealed significant differences in amino acids such as asparagine and glutamine. This approach dealing with a large volume of data on agronomic characteristics will be useful for assessing the characteristics of potential clones under selection and accelerating breeding programs.
