基于品种比较试验建立陆地棉综合评价体系
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1.新疆农业大学作物遗传改良与种质创新重点实验室;2.新疆维吾尔自治区标准化研究院;3.新疆仟朵种植农民专业合作社联合社;4.沙湾市农业技术推广中心

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国家科技创新2030-重大项目(项目编号:2023ZD04041);新疆维吾尔自治区重大科技专项项目(2023A02003-4);2023年自治区首批产学协同育人项目(507390758);“天山英才”培养计划项目(2023TSYCLJ0012)资助。Foundation projectMajor Science and Technology Special Projects in Xinjiang Uygur Autonomous Region(2023A02003-4);The first batch of industry-academia collaborative education programs in the Autonomous Region in 2023(507390758);


Establishment of a comprehensive evaluation system for upland cotton based on comparative variety trials
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National Science and Technology Innovation 2030 - Major Project (Project No. 2023ZD04041);Major Science and Technology Special Projects in Xinjiang Uygur Autonomous Region(2023A02003-4);The first batch of industry-academia collaborative education programs in the Autonomous Region in 2023(507390758);

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    摘要:

    为筛选适宜性较好的优质棉花品种,服务于生产。以24个早熟和早中熟陆地棉品种为材料,进行为期三年3年的品种比较试验,使用相关性、主成分、聚类、灰色关联度等方法进行分析。三年3年误差项变异系数(CEV)在0.40%~4.18%之间,2022年变异系数相对较高,在1.01%~20.48%之间,单株成铃数和单铃重变异程度更大最大;6对性状之间相关性达到显著水平,14对达到极显著水平,农艺性状与产量、纤维品质性状间相关性错综复杂,纤维品质性状内部相关性较为密切;筛选出5个主成分,解释79.87%的变化率;根据品种特性聚类得到5大类群。以隶属函数、灰色关联模型和AHP模型为基础,提出一套资源综合评价体系,筛选得到金丰6号、J8031、新农大棉1号等综合品质较优品种。在两套不同陆地棉资源群体分别在资源群体和优良品系中验证构建的综合评价体系,评价结果与田间表现一致,证明评价体系具有进一步推广的基础。

    Abstract:

    To screen high quality cotton varieties with better suitability for production purposes.. The 24 early and early-mid maturing upland cotton varieties were used as materials for a 3-years comparative variety trials, and analyzed by correlation, principal component, clustering, gray correlation, etc. The coefficient of variation (CEV) of the 3 years test ranged from 0.40% to 4.18%, and the coefficient of variation was relatively high in 2022., between 1.01% and 20.48%, The greatest variation was observed in the number of bolls per plant and single boll weight; 6 pairs of correlations between traits reached the significant level, 14 pairs reached the highly significant level, the correlation between agronomic traits and yield and fiber quality traits was intricate and complex, and the internal correlations among fiber quality traits are relatively close; 5 principal components were screened, explaining 79.87% of the variability; and 5 major groups were obtained by clustering according to the varietal characteristics. Based on the affiliation function, gray correlation model and AHP model, a set of comprehensive resource evaluation system was proposed, and Jinfeng 6, J8031, Xinnongda Cotton 1 and other varieties with better comprehensive quality were screened. The comprehensive evaluation system was verified in resource groups and superior lines respectively, and the evaluation results were consistent with the field performance, which proved that the evaluation system has the basis for further popularization.

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历史
  • 收稿日期:2024-08-09
  • 最后修改日期:2024-12-05
  • 录用日期:2024-12-23
  • 在线发布日期: 2025-01-07
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