| 赖运平,刘思怡,王竹,蒋云,韦献雅,袁金娥,徐霞,邹亮.藜麦籽粒均匀度评价方法研究[J].干旱地区农业研究,2026,(3):12~22 |
| 藜麦籽粒均匀度评价方法研究 |
| Evaluation method of grain uniformity of quinoa |
| |
| DOI：10.7606/j.issn.1000-7601.2026.03.02 |
| 中文关键词: 藜麦 籽粒均匀度 形态性状 主成分分析 隶属函数法 回归分析 |
| 英文关键词:quinoa grain uniformity morphological trait principal component analysis membership function analysis regression analysis |
| 基金项目:成都市科技项目专项资金（2025-YF09-00041-SN）；农业农村部杂粮加工重点实验室/国家杂粮加工技术研发分中心/四川省杂粮产业化工程技术研究中心开放基金（2024CC006）；四川杂粮创新团队项目（SCCXTD-2024-20）；天府粮仓现代农业产教联合体项目（2024LHT） |
|
| 摘要点击次数: 340 |
| 全文下载次数: 34 |
| 中文摘要: |
| 为筛选藜麦籽粒均匀度鉴定指标并构建有效的评价模型，以93份藜麦为试验材料，测定千粒重(X1)、面积(X2)、周长(X3)、长宽比(X4)、粒长(X5)、粒宽(X6)、直径(X7)、圆度(X8)和籽粒密度因子(X9)共9项籽粒形态指标，结合相关性分析、聚类分析、主成分分析、隶属函数法、逐步回归分析等多元统计分析方法，对藜麦籽粒均匀度进行综合评价。结果表明：各性状的变异系数介于1.41%~13.79%；供试材料聚为6个类群；主成分分析将9项性状转化为3个相互独立的综合指标，其累计贡献率为99.08%。通过隶属函数法将93份材料划分为4个等级，其中超高均匀度材料10份、高均匀度材料48份、中均匀度材料32份、低均匀度材料3份。基于逐步回归分析建立了籽粒均匀度预测值(VP)与籽粒形态性状的线性回归方程：VP=-5.647+ 0.334X3+3.727X8+0.737X9 (R2=0.997)，并据此筛选出周长、圆度和密度因子为藜麦籽粒均匀度的核心鉴定和评价指标。 |
| 英文摘要: |
| The objective of this study was to establish a comprehensive evaluation and screening model for the purpose of identifying suitable identification indexes of quinoa grain uniformity. A total of 93 quinoas were used as experimental materials to determine 9 morphological traits, including 1 000-grain weight (X1), grain area (X2), grain perimeter (X3), grain length\|width ratio (X4), grain length (X5), grain width (X6), diameter (X7), roundness (X8), and density factor (X9). Combined with multivariate statistical analysis methods such as correlation analysis, cluster analysis, principal component analysis, membership function method, and stepwise regression analysis, the comprehensive evaluation of quinoa grain uniformity was carried out. The results showed that the coefficient of variation for each trait ranged from 1.41% to 13.79%. The quinoa materials were grouped into six distinct categories based on their characteristics. The principal component analysis resulted in the simplification of nine traits into three independent principal components, with a cumulative contribution rate of 99.08%. The comprehensive evaluation values of grain uniformity were calculated from the membership function analysis. The 93 accessions were thus classified into four uniformity types, comprising 10 ultra\|high uniformity materials, 48 high uniformity materials, 32 medium uniformity materials, and 3 low uniformity materials. An optimal linear regression equation was established based on stepwise regression analysis between the predicted value of grain uniformity (VP) and the grain morphological trait index: VP=-5.647+ 0.334X3 +3.727X8+0.737X9 (R2=0.997). In accordance with the stipulated formula, the indicators selected for the identification and evaluation of indices for grain uniformity in quinoa include the grain perimeter, roundness, and density factor. The findings provide a theoretical basis for breeding quinoa varieties with high uniformity. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| | |