南京林业大学学报(自然科学版) ›› 2023, Vol. 47 ›› Issue (4): 61-72.doi: 10.12302/j.issn.1000-2006.202109034

所属专题: 乡村振兴视域下经济林果培育专题(Ⅱ)

• 专题报道:乡村振兴视域下经济林果培育专题(Ⅱ)(执行主编 李维林 方升佐) • 上一篇    下一篇

3种综合评价方法在柿果品质评价中的应用

程文强1,2(), 徐阳1, 吴开云1, 赵献民1, 龚榜初1,*()   

  1. 1.中国林业科学研究院亚热带林业研究所,浙江 杭州 311400
    2.南京林业大学林学院,江苏 南京 210037
  • 收稿日期:2021-09-17 修回日期:2021-11-27 出版日期:2023-07-30 发布日期:2023-07-20
  • 通讯作者: * 龚榜初(gongbc@126.com),研究员。
  • 作者简介:程文强(1181086494@qq.com)。
  • 基金资助:
    国家重点研发计划(2019YFD1001204);中央级公益性科研院所基本科研业务费专项资金重点项目(CAF-YBB2017ZA004-3);浙江省农业(果品)新品种选育重大科技专项项目(2021C02066-10)

Comparison of three comprehensive evaluation methods to evaluate the quality of persimmon fruit

CHENG Wenqiang1,2(), XU Yang1, WU Kaiyun1, ZHAO Xianmin1, GONG Bangchu1,*()   

  1. 1. Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
    2. College of Forestry, Nanjing Forestry University, Nanjing 210037, China
  • Received:2021-09-17 Revised:2021-11-27 Online:2023-07-30 Published:2023-07-20

摘要:

【目的】通过比较不同果实评价方法的评价效果,选择适合柿果实品质综合评价的统计分析方法,为优异柿种质的精准选择和高效利用提供理论依据。【方法】以浙江省85份柿种质资源为评价对象,测定柿果13项品质指标(单果质量、果实横径、纵径、粗蛋白、维生素C、淀粉、钙及β-胡萝卜素含量、含水率、可溶性固形物、可溶性糖、单宁和粗纤维含量),分别采用主成分分析法、熵值法和熵权TOPSIS法进行果实品质综合评价。【结果】不同柿种质果实品质存在较大差异,变异系数范围为3.82%~87.89%,β-胡萝卜素、单宁、淀粉、粗蛋白、维生素C及钙含量、单果质量和粗纤维含量变异比较丰富,纵径、可溶性糖含量、横径、可溶性固形物含量和含水率的变化较小。主成分分析法综合评价时,长兴1、富阳2、奉化1、莲都2等10个种质资源综合得分最高;熵值法进行综合评价时,武义3、永嘉10、武义4、黄岩2等10个种质柿果品质综合表现较好;采用熵权TOPSIS法进行综合评价时,武义3、永嘉10、武义4、淳安14等10个种质柿果品质综合表现较好。其中,熵值法和熵权TOPSIS法结果较一致,而主成分分析法结果差异较大,3种评价方法造成结果差异的原因主要与理论差异、数据标准化方法的不同以及指标权重的赋值方法不同有关。在柿果品质评价中,由于果实性状指标数据量多,关键指标离散程度小,结合不同种质的生产表现,以熵权TOPSIS法的评价结果更符合实际情况。【结论】基于熵权的TOPSIS模型不但提高了指标赋权的合理性,而且评价结果客观准确,计算简便,更适合用于柿种质果实品质综合评价。

关键词: 柿, 果实品质, 主成分分析, 熵值法, 熵权TOPSIS

Abstract:

【Objective】 This research aims to evaluate the quality of persimmon fruits using three comprehensive methods in order to provide a theoretical basis for the precise selection and efficient utilization of high quality persimmon germplasm. 【Method】 We selected 85 persimmon germplasm resources in Zhejiang Province as the object of evaluation, and examined 13 quality indicators (weight per fruits, diameter of horizontal cross section, diameter of vertical cross section, content of the crude protein, vitamin C, starch, calcium and β-carotene, water content, content of the soluble solids, soluble sugar, tannin and crude fiber) of persimmon fruit. We employed the principal component analysis, the entropy evaluation method and the entropy-weighting TOPSIS method to evaluate fruit comprehensive quality. 【Result】 Fruit quality of different persimmon germplasm resources varied significantly with variation coefficients of 3.82%-87.89%. High variations were found in content of the β-carotene, tannin, starch, crude protein, vitamin C, calcium, fruit weight and crude fiber, and low variations were showed in horizontal and vertical cross section diameters, soluble sugar, soluble solids and water content. The principal component analysis revealed that top scoring persimmon germplasm fruits were Changxing 1, Fuyang 2, Fenghua 1 and Liandu 2. The entropy evaluation method ranked the top scoring persimmon fruits as Wuyi 3, Yongjia 10, Wuyi 4 and Huangyan 2. The entropy-weighting TOPSIS method gave top scoring persimmon fruits to Wuyi 3, Yongjia 10, Wuyi 4, and Chun'an 14. The entropy method and the entropy-weighting TOPSIS method showed relatively similar ranking, while the principal component analysis deviated from the other two methods in scoring. These three methods differ in their theoretical bases, in data standardization methods, and in an index weight assignment. The entropy-weighting TOPSIS based scoring overcame the complexity of the large amount of data on fruit trait indicators and the problem of small dispersion degree of key indicators, and matched best with the production performances and overall quality of different germplasm. 【Conclusion】 The entropy-weight based TOPSIS model simplifies and improves comprehensive evaluation of persimmon germplasm fruit quality compared with scoring by the principal component analysis and the entropy evaluation method.

Key words: Diospyros kaki (persimmon), fruit quality, principal component analysis (PCA), entropy evaluation method, entropy-weighting TOPSIS

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