| 小麦品质相关分析和聚类分析 |
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| 引用本文： | 夏利娟,蔡鲲鹏,马莉娟,陈文强,王宇,丁晨露,冉强,蔡健.小麦品质相关分析和聚类分析[J].农学学报,2021,11(8):1-7. |
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| 作者姓名： | 夏利娟 蔡鲲鹏 马莉娟 陈文强 王宇 丁晨露 冉强 蔡健 |
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| 作者单位： | 1.临泉县城关街道农业综合服务站,安徽临泉 236400;2.阜阳师范大学信息工程学院,安徽阜阳 236037;3.阜阳师范大学历史与文化旅游学院,安徽阜阳 236037;4.阜阳师范大学生物与食品工程学院,安徽阜阳 236037 |
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| 基金项目： | 安徽高校自然科学研究重点项目“白藜芦醇和褪黑素对小鼠卵泡发育主要调控因子TGF-β的作用机制研究”(KJ2018A0352);安徽省林业科技创新项目“芍药属新品种培育”(AULYCX-2020-);2018年国家级大学生创新创业训练计划项目“外源添加白藜芦醇对益生菌发酵大豆酸乳工艺条件优化的研究”(201810371043);安徽省教研项目“基于一二三产业融合发展的地方高校新农科多样化人才培养模式的创新与实践”(2020xnkyjsj3);2019年省级大学生创新创业训练计划项目“樱花色素成分鉴定及其优质种质资源开发利用”(S201910371026) |
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| 摘 要： | 为了提高小麦的品质,确定小麦品种的优良品质性状,进而选育出更为优质的小麦品种。本研究以35个小麦品种为试材,对蛋白质含量、降落值、湿面筋含量等8个品质性状进行相关分析和聚类分析。相关分析结果表明：降落值与蛋白质,湿面筋与蛋白质,降落值与湿面筋,稳定性与降落值,弱化度与吸水率呈极显著相关;稳定性与蛋白质,弱化度与降落值呈显著负相关。聚类分析结果表明：供试35个小麦品种在遗传距离3水平上可聚为4个大类。类群Ⅰ为‘中涡18’;‘远育17’、‘太麦2号’、‘乐麦Z0708’、‘淮师0812’和‘良源508’聚为类群Ⅱ：‘荃麦102099’、‘HS44’和‘安1211’聚为类群Ⅲ：类群Ⅳ共有26个小麦品种,其中包括保‘丰1269’、‘华成870’、‘皖科101547’、‘民得利2号’、‘龙麦一号’、‘鉴20651’、‘亳麦0610’、‘金丹6166’、‘安农1203’、‘保丰2018’、‘JM-1’、‘王家坝1110’、‘安农大0622’、‘GR123’、‘安1243’、‘绿雨9号’、‘皖麦4308’、‘阜0652’、‘皖麦52’、‘蜀鑫麦318’、‘宿11037’、‘豪麦56’、‘阜100’、‘中麦1023’、‘诺丰568’和‘奥特麦1号’。通过本次实验,为选育优质小麦品种和杂交组配提供了理论依据。
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| 关 键 词： | 小麦 品质性状 相关性分析 聚类分析 选育品种 |
| 收稿时间： | 2020-02-23 |
Wheat Quality: Correlation Analysis and Cluster Analysis |
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| Xia Lijuan,Cai Kunpeng,Ma Lijuan,Chen Wenqiang,Wang Yu,Ding Chenlu,Ran Qiang,Cai Jian.Wheat Quality: Correlation Analysis and Cluster Analysis[J].Journal of Agriculture,2021,11(8):1-7. |
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| Authors: | Xia Lijuan Cai Kunpeng Ma Lijuan Chen Wenqiang Wang Yu Ding Chenlu Ran Qiang Cai Jian |
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| Institution: | 1.Linquan County Street Agricultural Comprehensive Service Station, Linquan 236400, Anhui, China;2.College of Information Engineering, Fuyang Normal University, Fuyang 236037, Anhui, China;3.Fuyang Normal University, College of History and Cultural Tourism, Fuyang 236037, Anhui, China;4.Fuyang Normal University, College of Biology and Food Engineering, Fuyang 236037, Anhui, China |
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| Abstract: | The aims are to improve the quality of wheat, determine the excellent quality traits of wheat varieties, and select and breed high quality wheat varieties. In the study, 35 wheat varieties were used as materials. 8 quality traits such as protein content, falling value and wet gluten content were studied with correlation analysis and cluster analysis. Correlation analysis results showed that: the falling value and protein, wet gluten and protein, falling value and wet gluten, stability and falling value, the weakening degree and the water absorption rate were extremely and significantly related; stability and protein, weakening degree and falling value were significantly and negatively related. The results of cluster analysis showed that the 35 wheat varieties tested were clustered into 4 categories at the genetic distance of 3. Group I was ‘Zhongwo 18’; ‘Yuanyu 17’, ‘Taimai 2’, ‘Lemai Z0708’, ‘Huaishi 0812’and ‘Liangyuan 508’ clustered into group II: ‘Tuanmai 102099’, ‘HS44’ and ‘An 1211’ clustered into Group III. Group IV had 26 wheat varieties, including ‘Baofeng 1269’, ‘Huacheng 870’, ‘Wanke 101547’, ‘Mindeli 2’ and ‘Longmai 1’, ‘Jian 20651’, ‘Bomai 0610’, ‘Jindan 6166’,’ Annong 1203’, ‘Baofeng 2018’, ‘JM-1’, ‘Wangjiaba 1110’, ‘Annong 0622’, ‘GR123’, ‘ An 1243’, ‘Luyu No. 9’, ‘Wanmai 4308’, ‘Fu 0652’, ‘Wanmai 52’, ‘Shu Xinmai 318’, ‘Su 11037’', ‘Haomai 56’, ‘Fu 100’, ‘Zhongmai 1023’, ‘Nuofeng 568’ and ‘Aotemai No. 1’. This experiment could provide a theoretical basis for breeding high-quality wheat varieties and hybrid combinations. |
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| Keywords: | Wheat Quality Traits Correlation Analysis Clustering Analysis Variety Breeding |
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