浙江农业学报 ›› 2026, Vol. 38 ›› Issue (2): 248-257.DOI: 10.3969/j.issn.1004-1524.20250508

• 园艺科学 • 上一篇    下一篇

南瓜果实品质评价的指标筛选与模型构建

刘静1(), 王尖2, 黄钰1, 吴晓花2, 郭轩赫1, 汪颖2, 李国景2, 许小江1,*()   

  1. 1.绍兴市农业科学研究院, 浙江 绍兴 312003
    2.浙江省农业科学院 蔬菜研究所, 浙江 杭州 310021
  • 收稿日期:2025-07-25 出版日期:2026-02-25 发布日期:2026-03-24
  • 作者简介:刘静,研究方向为葫芦科蔬菜育种。E-mail:172547603@qq.com
  • 通讯作者: *许小江,E-mail:13858539612@163.com
  • 基金资助:
    浙江省农业科学院院地合作项目(ZJTY2024-A-58);绍兴市科技计划项目(2023A12001);浙江省农业(蔬菜)新品种选育重大科技专项(2021C02065-2-3)

Indicator screening and model development for evaluating pumpkin fruit quality

LIU Jing1(), WANG Jian2, HUANG Yu1, WU Xiaohua2, GUO Xuanhe1, WANG Ying2, LI Guojing2, XU Xiaojiang1,*()   

  1. 1. Shaoxing Academy of Agricultural Sciences, Shaoxing 312003, Zhejiang, China
    2. Institute of Vegetables, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
  • Received:2025-07-25 Online:2026-02-25 Published:2026-03-24

摘要:

为构建南瓜果实品质综合评价模型,本研究以51份中国南瓜(Cucurbita moschata)和95份印度南瓜(Cucurbita maxima)为材料,测定其11项果实品质指标,综合运用相关分析、因子分析与聚类分析方法,结合公因子二维分布图,建立南瓜果实品质评价模型。结果表明,中国南瓜的含水量、纤维素含量、可溶性糖含量、β-胡萝卜素含量和甜度均显著高于印度南瓜;印度南瓜的淀粉含量、直链淀粉含量、黏度、干湿度和纤维感均极显著高于中国南瓜。11项品质指标的变异系数范围为9.00%~69.04%,其中含水量变异系数最小,可溶性糖含量变异系数最大。通过因子分析提取出5个公因子,累计方差贡献率为90.27%;第一公因子(F1)的方差贡献率最高(34.60%),主要关联含水量、可溶性糖含量、淀粉含量和直链淀粉含量。基于此构建南瓜果实品质评价模型:Y=0.383 2F1+0.263 2F2+0.132 1F3+0.127 5F4+0.094 0F5。通过相关分析与聚类分析,进一步将11项品质指标简化为淀粉含量、纤维感和可溶性糖含量3个代表性指标。F1与第二公因子(F2)的散点图显示,模型预测值与实际测定值高度一致。本研究建立的评价模型可为南瓜果实品质评价提供方法依据,对高品质南瓜品种选育具有参考价值。

关键词: 南瓜, 果实, 品质, 因子分析, 聚类分析, 综合评价

Abstract:

To establish a comprehensive evaluation model for pumpkin fruit quality, 51 accessions of Cucurbita moschata and 95 accessions of Cucurbita maxima were used as materials. Eleven fruit quality indicators were measured, and correlation analysis, factor analysis, cluster analysis, and two-dimensional factor ordination were applied to construct the evaluation model. The results indicated that moisture content, cellulose, soluble sugar, β-carotene content, and sweetness of C. moschata were significantly higher than those in C. maxima. In contrast, starch content, amylose content, viscosity, dryness/wetness, and fibrous texture in C. maxima were significantly higher than those in C. moschata. The coefficients of variation for the 11 fruit quality indicators ranged from 9.00% to 69.04%. Moisture content showed the smallest coefficient of variation, while soluble sugar content exhibited the largest. Factor analysis extracted five common factors, with a cumulative variance contribution rate of 90.27%. The first common factor (F1) had the highest variance contribution rate (34.60%) and was primarily associated with moisture content, soluble sugar content, starch content, and amylose content. Based on this, an evaluation model for pumpkin fruit quality was established: Y=0.383 2F1+0.263 2F2+0.132 1F3+0.127 5F4+0.094 0F5. Furthermore, correlation analysis and cluster analysis simplified the eleven original quality indicators into three representative indicators: starch content, fibrous texture, and soluble sugar content. The scatter distribution of F1 and the second common factor (F2) confirmed high consistency between model-predicted values and actual measured values. The evaluation model developed in this study provides a methodological basis for pumpkin fruit quality assessment and serves as a reference for breeding high-quality pumpkin varieties.

Key words: pumpkin, fruit, quality, factor analysis, cluster analysis, comprehensive quality evaluation

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