中国农业科学 ›› 2016, Vol. 49 ›› Issue (4): 802-812.doi: 10.3864/j.issn.0578-1752.2016.04.019

• 研究简报 • 上一篇    

桃变温压差膨化脆片品质评价研究

吕健,刘璇,毕金峰,周林燕,吴昕烨   

  1. 中国农业科学院农产品加工研究所/农业部农产品加工重点实验室,北京 100193
  • 收稿日期:2015-07-09 出版日期:2016-02-16 发布日期:2016-02-16
  • 通讯作者: 毕金峰,E-mail:bijinfeng2010@163.com
  • 作者简介:吕健,E-mail:lvjianlinjian@163.com
  • 基金资助:
    国家公益性行业(农业)科研专项(201503142)

Research on the Quality Evaluation for Peach and Nectarine Chips by Explosion Puffing Drying

Lü Jian, LIU Xuan, BI Jin-feng, ZHOU Lin-yan, WU Xin-ye   

  1. Institute of Food Science and Technology CAAS Key Laboratory of Agro-Products Processing, Ministry of Agriculture, Beijing 100193
  • Received:2015-07-09 Online:2016-02-16 Published:2016-02-16

摘要: 【目的】探讨不同品种桃脆片的综合品质差异,建立桃脆片综合品质评价判别函数模型,为桃合理加工利用提供理论支持,为桃脆片综合品质的科学评价奠定基础。【方法】试验以中国北方的49个主栽桃品种为试材,测定桃脆片包括感官品质(色泽、硬度、脆度、膨化度等)、理化与营养品质(可溶性固形物、粗脂肪、粗蛋白、粗纤维等)和加工品质(出品率和复水比)在内的17项品质评价指标,分别采用变异系数法分析不同品种桃脆片品质评价指标的差异情况,采用因子分析法系统分析指标间的相关关系并筛选得到桃脆片品质评价的核心指标,运用层次分析法得到核心指标的权重并计算不同品种桃脆片的综合品质得分,最后选用70%样品作为建模样本,综合利用K-均值聚类法和判别分析法建立桃脆片综合品质判别函数,选用其余样品作为检验样本,验证判别函数的适用性和正确性。【结果】(1)桃脆片品质指标之间离散度有差异,变异系数范围在0.70%—344.02%。(2)依据主成分解释的总变量和碎石图提取了5个主因子,反应了原变量74.626%的信息。其中第一主因子(PC1)综合了还原糖和糖酸比的信息,即口感品质;第二主因子(PC2)主要综合了出品率和复水比的信息,体现的是脆片产品的加工品质指标;第三主因子(PC3)主要综合了L值和b值信息,可命名为色泽品质指标;第四主因子(PC4)和第5主因子(PC5)中粗蛋白和膨化度指标的权重值明显高于其他指标,可分别作为该主因子的代表性指标。根据每个代表因子的权重大小并以指标测定的简便、快捷程度为依据,筛选得到5项桃脆片品质评价核心指标,即还原糖、复水比、L值、粗蛋白和膨化度。(3)依据层次分析法确立了5个核心指标的权重值分别为0.0824、0.1724、0.2732、0.0480、0.4240;选用极差法建立了桃脆片品质评价核心指标的评分标准。(4)建立了桃脆片品质等级判别函数,建模样本判别正确率为100%,检验样本仅一个被误判。其中‘瑞蟠19号’、‘德来福莱卡’、‘大久保’等15个品种是适于桃脆片的加工品种,品质为优;‘瑞蟠21’、‘菊黄’、‘艳红’等28个品种为较适宜加工桃脆片的品种,品质为中;‘瑞蟠20号’、‘森格林’、‘黄金秀’等6个品种不适于桃脆片加工,品质为差。【结论】桃脆片综合品质可用还原糖、复水比、L值、粗蛋白和膨化度等5项核心指标进行评价,建立的桃脆片综合品质判别函数具有较高的准确性,可用于桃脆片综合品质的定性判别。

关键词: 桃脆片, 品质评价, 核心指标, 因子分析, 层次分析, 判别分析

Abstract: 【Objective】 The aim of the paper was to investigate the variations in the comprehensive quality of peaches and nectarine chips from the different cultivars and establish scientific evaluation models for peach and nectarine chips. 【Method】 Peach and nectarine fruit from 49 varieties grown in the north of China were selected for the testing materials. 17 quality evaluation indexes were measured, including organoleptic quality indexes (e.g. color, hardness, crispness, explosion ratio, and so on), physical and chemical characteristic indexes (e.g., soluble solid content, crude fat content, crude protein content, crude fiber content, and so on) and processing quality indexes (output ratio and rehydration ratio). The method of a variable coefficient was used to investigate the differences in quality evaluation indexes from different peach and nectarine cultivars. The relationship between these indexes and the characteristic indexes were selected by factor analysis (FA). The weights and the levels of the characteristic indexes were calculated by an analytic hierarchy process (AHP) and a range analysis method, respectively. The levels in cultivars effectively were classified by discrimination functions which were obtained by K-means cluster (KC) and discriminate analysis (DA). 70% of the samples were selected as the testing samples, and the others were used as the verification set data, which could verify the fitness of the functions. 【Result】 (1) 17 quality evaluation indexes dispersed with the coefficient of variation ranging from 0.70%-344.02%. (2) Five characteristic indexes were determined based on the method of FA, which explained 74.626% of the total variances. The first principal component (PC1) was related to reducing sugar content and sugar-acid ratio, which were the taste quality factors. The principal component (PC2) was related to the output ratio and rehydration ratio, which were the processing quality factors. The third principle component (PC3) was related to the L value and b value, which were the color quality factors. And the fourth and fifth principal components (PC4 and PC5) were related to the crude protein content and explosion ratio, respectively, which had higher weights than the others. Five quality evaluation indexes were selected as the characteristics indexes, namely, reducing sugar, rehydration ratio, L value, crude protein content, and expansion ratio. (3) Based on the AHP, the weights of the characteristics indexes were 0.0824, 0.1724, 0.2732, 0.0480, and 0.4240, respectively. Also, the scoring standard of the characteristic indexes were established. (4) Discrimination functions of different grades were established, which had satisfactory recognition accuracy up to 100%, and only one sample was discriminated inaccurately. Ruipan19, Delaifulaika, and Dajiubao were the best cultivars used to produce peach and nectarine chips, Ruipan 21, Juhuang, and Yanhong were the good cultivars used to produce peach and nectarine chips, and Rupan 20, Sengelin, and Huangjinxiu were the worst cultivars used to processing peach chips. 【Conclusion】 Peach and nectarine chips’ comprehensive quality can be evaluated by 5 characteristics indexes, namely, reducing sugar content, rehydration ratio, L value, crude protein content, and expansion ratio. The grading standard and the scoring standard of the 5 indexes set up a scientific foundation for evaluating peach and nectarine chips’ quality. The established discrimination functions were effective in discriminating peach and nectarine chips’ quality.

Key words: peach chips, quality evaluation, characteristic indexes, factor analysis, analytics hierarchy process, discriminant analysis