[1]韩艳文,李文生,王宝刚,等.葡萄果实质地剖面分析的参数优化[J].北方园艺,2018,42(19):129-135.[doi:10.11937/bfyy.20174658]
　HAN Yanwen,LI Wensheng,WANG Baogang,et al.Optimization of Texture Determination of Grape With Texture Profile Analysis[J].Northern Horticulture,2018,42(19):129-135.[doi:10.11937/bfyy.20174658]
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葡萄果实质地剖面分析的参数优化

《北方园艺》[ISSN:1001-0009/CN:23-1247/S] 卷: 第42卷 期数: 2018年19 页码: 129-135 栏目: 出版日期: 2018-10-10
Title:
Optimization of Texture Determination of Grape With Texture Profile Analysis
作者:
韩艳文1; 李文生1; 2; 王宝刚1; 2; 王云香1
（1.北京市林业果树科学研究院，北京 100093；2.国家果品加工技术研发分中心，北京 100093）
Author(s):
HAN Yanwen1; LI Wensheng1; 2; WANG Baogang1; 2; WANG Yunxiang1
(1.Beijing Academy of Forestry and Pomology Sciences,Beijing 100093；2.National Fruit Processing Technology Research and Development Sub-center,Beijing 100093)
关键词:
质地剖面分析; 葡萄; 质构参数; 优化
Keywords:
texture profile analysis; grape; texture determination; optimization
DOI:
10.11937/bfyy.20174658
文献标志码:
A
摘要:
质地剖面分析（TPA，Texture profile analysis）已成为食品行业中多类产品质地特性的通用测试方法。以不同产地不同品种的葡萄为试材，采用物性分析仪的TPA模式测定葡萄果实的质地指标，根据质地指标来筛选TPA模式的最佳测定参数（不同的测中速度、压缩停顿时间、形变程度）。结果表明：同一品种不同规格大小的葡萄基本品质没有显著性差异（P>0.05），但是不同品种的葡萄在TPA测试时不同参数对测试结果影响较大，故选择测中速度为2 mm·s-1或3 mm·s-1，停顿时间为2 s或4 s，形变程度为35%，作为葡萄果实TPA模式评价的最优参数。
Abstract:
Texture profile analysis (TPA) method has been used to measurethe texture characteristics of food or agricultural products.Test parameters including of speed,compression pause time and degree of deformation during texture profile analysis(TPA) test to evaluate the texture change of ‘Kyoho’ different ‘Red mention’ grape varietis were optimized in this study.The results showed that different test parameters significantly affected the texture data,however not by grades of grape fruits (P>0.05).The optimum parameters during TPA test of grape fruits were selected as follows：test speed of 2 mm·s-1 or 3 mm·s-1,pause time of 2 seconds or 4 seconds and degree of deformation of 35%.

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备注/Memo

第一作者简介：韩艳文（1990-），女，硕士研究生，研究方向为果蔬贮运保鲜技术。E-mail：sxtyhanyw@126.com.责任作者：王宝刚（1979-），男，博士，副研究员，现主要从事果品物流及贮藏保鲜技术等研究工作。E-mail：fruit_postharvest@126.com.基金项目：北京市农林科学院科技创新能力建设专项资助项目（KJCX20170206）。收稿日期：2018-02-05

更新日期/Last Update: 2018-11-07