NARO 水稻育种历史表型数据集。

IF 2 4区 农林科学 Q2 AGRONOMY Breeding Science Pub Date : 2024-04-01 Epub Date: 2024-03-08 DOI:10.1270/jsbbs.23040
Kei Matsushita, Akio Onogi, Jun-Ichi Yonemaru
{"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":"74 2","pages":"114-123"},"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\":\"74 2\",\"pages\":\"114-123\"},\"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}
引用次数: 0

摘要

育种数据(包括表型信息)可提高育种效率。长期积累的育种试验历史数据也很有用。在此,我们通过整理国家农业与食品研究组织(NARO)水稻育种项目中积累的数据,开发了一个历史表型数据集,其中包括 1991-2018 年在国家农业与食品研究组织六个研究站进行的产量试验中获得的 667 个品种的 6052 条记录。我们利用最佳线性无偏预测(BLUPs)和主成分分析(PCA)确定了包括产量在内的 15 个性状与各种因素(包括品种发布年份)的关系。与产量相关的性状,如每圆锥花序粒数、株重、谷物产量和千粒重,随着时间的推移显著增加,而圆锥花序数则显著减少。成熟时间明显延长,而糙米的结实率和蛋白质含量则明显下降。这些结果表明,具有优异抗倒伏性的穗粒重高产品种已被选育出来。这些趋势在不同育种地点略有不同,表明不同育种地点的主要育种目标可能不同。PCA 显示,新品种的性状多样性更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Breeding Science
Breeding Science 农林科学-农艺学
CiteScore
4.90
自引率
4.20%
发文量
37
审稿时长
1.5 months
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. Manuscripts should be submitted by corresponding author. Corresponding author must have obtained permission from all authors prior to submission. Correspondence, proofs, and charges of excess page and color figures should be handled by the corresponding author.
期刊最新文献
Identification of a major QTL conferring resistance to wheat yellow mosaic virus derived from the winter wheat 'Hokkai 240' on chromosome 2AS. Phenotyping and a genome-wide association study of elite lines of pearl millet. Screening corn hybrids for early-stage drought stress tolerance using SPAR phenotyping platform. Substitution mapping and characterization of brown planthopper resistance genes from traditional rice cultivar 'Rathu Heenati' (Oryza sativa L.). THB1, a putative transmembrane protein that causes hybrid breakdown in rice.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1