欢迎访问《中国农学通报》，
中国农学通报

中国农学通报 ›› 2025, Vol. 41 ›› Issue (7): 138-144.doi: 10.11924/j.issn.1000-6850.casb2024-0363

• 食品·营养·检测·安全 • 上一篇    下一篇

3种数学方法在灰枣果实品质评价中的应用

王欢欢(), 王晶晶(), 陈奇凌   

  1. 新疆农垦科学院林园研究所/库尔勒香梨种质创新与提质增效兵团重点实验室，新疆石河子 832000
  • 收稿日期:2024-06-03 修回日期:2024-11-15 出版日期:2025-03-05 发布日期:2025-03-03
  • 通讯作者:
    王晶晶，女，1983年出生，甘肃武威人，研究员，硕士，研究方向为果树栽培与生理。E-mail：。
  • 作者简介:

    王欢欢，女，1997年出生，新疆伊犁人，助理研究员，硕士，研究方向为果树栽培与生理。E-mail：。

  • 基金资助:
    第一师科技项目“红枣病虫害绿色标准化防控关键技术研究与示范”(S202202NY015); 新疆生产建设兵团重大科技项目“果园主干结果型栽培技术与主要生产环节机械化技术研发与应用”(2021AA005)

Application of Three Mathematical Methods in Quality Evaluation of Jujube Fruit

WANG Huanhuan(), WANG Jingjing(), CHEN Qiling   

  1. Institute of Forestry and Horticulture, Xinjiang Academy of Agricultural and Reclamation Science/ Xinjiang Production & Construction Corp Key Laboratory of Korla Fragrant Pear Germplasm Innovation and Quality Improvement and Efficiency Increment, Shihezi, Xinjiang 832000
  • Received:2024-06-03 Revised:2024-11-15 Published:2025-03-05 Online:2025-03-03

RichHTML

2

PDF (PC)

69

摘要：

本研究旨在探讨确定可行的数学分析方法，准确评价新疆灰枣的品质。以4个药剂复配处理后的灰枣果实为试验材料，通过测定果实品质指标，采用因子分析、熵值法和层次-灰色关联度分析分别对12个果实品质指标进行综合分析。结果表明，果实各性状指标间存在不同程度变异，变异范围为1.56%~37.58%。其中单果重和单株产量变异系数较大(>10%)，其余指标变异系数较小(<10%)。因子分析结果表明，灰枣的12个品质指标可转化成3个特征值大于1的公因子，累计方差贡献率达89.974%，包含了参试灰枣果实性状大部分信息，综合得分结果显示T2处理(0.25 mmol/L SA+30 mg/L DA-6+0.01 g/L BR)后果实品质综合评价最高。熵值法结果表明，除果实纵径、果形指数、单果重和有机酸4个指标外，其余性状指标的差异系数均大于10%，果糖的权重最高为14.83%，其次为维生素C，果实横径权重最低，得分排名显示T1处理(0.25 mmol/L SA+30 mg/L DA-6)后灰枣综合品质最佳。层次-灰色关联度结果显示，单果重和单果产量的权重最高，有机酸和纤维素权重最低，得分结果表明T2处理后灰枣综合品质最佳。在灰枣品质评价中，果实性状指标数据量多、关键指标离散程度小，结合不同处理灰枣的生产表现，以层次-灰色关联度评价结果更符合实际情况。

关键词: 灰枣, 果实品质, 因子分析, 熵值法, 多层次灰色关联度分析, 品质评价

Abstract:

The study aims to investigate and identify feasible mathematical analysis methods to provide a reference for the quality evaluation of gray jujubes in Xinjiang. In this study, gray jujube fruits subjected to a compound treatment with four agents being used as test materials, and 12 fruit quality indicators were comprehensively analyzed using factor analysis, entropy value method and level-gray relation analysis, respectively. The results showed that there were different degrees of variability among the fruit traits, ranging from 1.56% to 37.58%. Among them, the coefficients of variation of single fruit weight and single plant yield were large (>10%), whereas the coefficients of variation of the remaining indicators were relatively small (<10%). The results of factor analysis demonstrated that the 12 quality indicators of the gray jujube were converted into three common factors, each with eigenvalues greater than 1. The cumulative variance contribution rate was 89.974%, which encompassed the majority of the information regarding the participating gray jujube fruit traits. Moreover, the results of the composite scores demonstrated that the comprehensive evaluation of fruit quality was highest after T2 treatment (0.25 mmol/L SA+ 30 mg/L DA-6+ 0.01 g/L BR). The results of the entropy value method indicated that the coefficients of variation for the trait indices exceeded 10% in all cases, with the exception of four indices of longitudinal fruit diameter, fruit shape index, single fruit weight, and organic acid. Among these, the weight of fructose was the highest at 14.83%, followed by vitamin C, while the weight of transverse fruit diameter was the lowest, and the ranking of the scores revealed that the comprehensive quality of gray jujube was best after T1 treatment (0.25 mmol/L SA+ 30 mg/L DA-6). The results of the level-gray relation analysis indicated that single fruit weight and single fruit yield had the highest weights, while organic acid and cellulose exhibited the lowest weights. Furthermore, the scoring results demonstrated that the integrated quality of gray jujube was optimal following the T2 treatment. In evaluating the quality of gray jujube, the extensive data on fruit trait indices will lead the limited variation in key indices. Combined with the production performance of different treatments, the evaluation results of hierarchical-gray correlation degree are more in line with the actual situation.

Key words: grey jujube, fruit quality, factor analysis, entropy method, multi-level gray relation analysis, quality evaluation