{"title":"NARO 水稻育种历史表型数据集。","authors":"Kei Matsushita, Akio Onogi, Jun-Ichi Yonemaru","doi":"10.1270/jsbbs.23040","DOIUrl":null,"url":null,"abstract":"<p><p>Data from breeding, including phenotypic information, may improve the efficiency of breeding. Historical data from breeding trials accumulated over a long time are also useful. Here, by organizing data accumulated in the National Agriculture and Food Research Organization (NARO) rice breeding program, we developed a historical phenotype dataset, which includes 6052 records obtained for 667 varieties in yield trials in 1991-2018 at six NARO research stations. The best linear unbiased predictions (BLUPs) and principal component analysis (PCA) were used to determine the relationships with various factors, including the year of cultivar release, for 15 traits, including yield. Yield-related traits such as the number of grains per panicle, plant weight, grain yield, and thousand-grain weight increased significantly with time, whereas the number of panicles decreased significantly. Ripening time significantly increased, whereas the lodging degree and protein content of brown rice significantly decreased. These results suggest that panicle-weight-type high-yielding varieties with excellent lodging resistance have been selected. These trends differed slightly among breeding locations, indicating that the main breeding objectives may differ among them. PCA revealed a higher diversity of traits in newer varieties.</p>","PeriodicalId":9258,"journal":{"name":"Breeding Science","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11442108/pdf/","citationCount":"0","resultStr":"{\"title\":\"NARO historical phenotype dataset from rice breeding.\",\"authors\":\"Kei Matsushita, Akio Onogi, Jun-Ichi Yonemaru\",\"doi\":\"10.1270/jsbbs.23040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Data from breeding, including phenotypic information, may improve the efficiency of breeding. Historical data from breeding trials accumulated over a long time are also useful. Here, by organizing data accumulated in the National Agriculture and Food Research Organization (NARO) rice breeding program, we developed a historical phenotype dataset, which includes 6052 records obtained for 667 varieties in yield trials in 1991-2018 at six NARO research stations. The best linear unbiased predictions (BLUPs) and principal component analysis (PCA) were used to determine the relationships with various factors, including the year of cultivar release, for 15 traits, including yield. Yield-related traits such as the number of grains per panicle, plant weight, grain yield, and thousand-grain weight increased significantly with time, whereas the number of panicles decreased significantly. Ripening time significantly increased, whereas the lodging degree and protein content of brown rice significantly decreased. These results suggest that panicle-weight-type high-yielding varieties with excellent lodging resistance have been selected. These trends differed slightly among breeding locations, indicating that the main breeding objectives may differ among them. PCA revealed a higher diversity of traits in newer varieties.</p>\",\"PeriodicalId\":9258,\"journal\":{\"name\":\"Breeding Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11442108/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Breeding Science\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1270/jsbbs.23040\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/8 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Breeding Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1270/jsbbs.23040","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/8 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"AGRONOMY","Score":null,"Total":0}
NARO historical phenotype dataset from rice breeding.
Data from breeding, including phenotypic information, may improve the efficiency of breeding. Historical data from breeding trials accumulated over a long time are also useful. Here, by organizing data accumulated in the National Agriculture and Food Research Organization (NARO) rice breeding program, we developed a historical phenotype dataset, which includes 6052 records obtained for 667 varieties in yield trials in 1991-2018 at six NARO research stations. The best linear unbiased predictions (BLUPs) and principal component analysis (PCA) were used to determine the relationships with various factors, including the year of cultivar release, for 15 traits, including yield. Yield-related traits such as the number of grains per panicle, plant weight, grain yield, and thousand-grain weight increased significantly with time, whereas the number of panicles decreased significantly. Ripening time significantly increased, whereas the lodging degree and protein content of brown rice significantly decreased. These results suggest that panicle-weight-type high-yielding varieties with excellent lodging resistance have been selected. These trends differed slightly among breeding locations, indicating that the main breeding objectives may differ among them. PCA revealed a higher diversity of traits in newer varieties.
期刊介绍:
Breeding Science is published by the Japanese Society of Breeding. Breeding Science publishes research papers, notes and reviews
related to breeding. Research Papers are standard original articles.
Notes report new cultivars, breeding lines, germplasms, genetic
stocks, mapping populations, database, software, and techniques
significant and useful for breeding. Reviews summarize recent and
historical events related breeding.
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