食品科学 ›› 2017, Vol. 38 ›› Issue (4): 223-230.doi: 10.7506/spkx1002-6630-201704036

• 工艺技术 • 上一篇    下一篇

基于均匀设计和主成分分析的甘薯薯片油炸工艺优化

李玉龙,杨 烨,陆国权   

  1. 浙江农林大学薯类作物研究所,浙江省农产品品质改良技术研究重点实验室,杭州 临安 311300
  • 出版日期:2017-02-25 发布日期:2017-02-28
  • 基金资助:
    国家现代农业(甘薯)产业技术体系建设专项(CARS-11-B-18)

Optimization of Frying Process for Sweet Potato Chips Based on Uniform Design and Principal Component Analysis

LI Yulong, YANG Ye, LU Guoquan   

  1. The Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, Institute of Root and Tuber Crops, Zhejiang A&F University, Lin’an 311300, China
  • Online:2017-02-25 Published:2017-02-28

摘要: 为优化甘薯薯片油炸工艺,采用单因素和均匀设计相结合进行试验,对均匀设计试验数据进行多元回归分析。单因素试验表明:切片厚度、预干燥阶段和油炸阶段对含油量、L*值和b*值有较大影响;均匀设计逐步回归分析表明:油炸时间对含油量影响显著(P=0.011),食盐水质量分数对含水量影响显著(P=0.022),油炸温度和油炸时间对L*值影响极显著(P=0.001),预干燥时间和油炸时间对b*值影响显著,食盐水浸泡时间、食盐水质量分数、预干燥温度、预干燥时间和切片厚度对脆度的影响符合二次多项式回归模型(P=0.001);指标主成分分析表明:提取2 个主成分能解释87.4%的指标信息,达到指标降维目的;岭回归分析建立了综合得分回归模型,相关系数R为0.997,能很好地拟合产品的综合得分;偏最小二乘法回归分析预测最佳综合评分工艺参数为切片厚度2 mm、热烫时间1 min、质量分数1%食盐水浸泡20 min、预干燥温度60 ℃、预干燥时间70 min、油炸温度150 ℃、油炸时间1 min,验证综合评分为0.89,综合评分高于均匀设计试验组最高值0.86。优化工艺所得产品具有含油量低、颜色和脆度俱佳等特点,相关模型具有良好的预测能力。

关键词: 均匀设计, 主成分分析, 综合评价, 含油量, 颜色, 脆度

Abstract: In this work, we optimized the frying process for sweet potato chips using combination of one-factor-at-a-time method and uniform design through multiple regression analysis of the uniform design experimental data. The results of the one-factor-at-a-time experiments showed slice thickness, pre-drying and frying to be the factors with a great influences on the oil content, L* and b*. Uniform design and stepwise regression analysis indicated that frying time significantly influenced the oil content (P = 0.011), saline concentration influenced significantly water content (P = 0.022), frying temperature and frying time affected very significantly L* (P = 0.001), drying time and frying time significantly influenced b*, and saline immersion time, saline concentration, pre-drying temperature and time and slice thickness affected brittleness, which was fitted to a quadratic polynomial regression model (P = 0.001). Principal component analysis (PCA) showed that the two principal components extracted accounted for 87.4% of the total variation, thus achieving dimensional reduction. Through ridge regression analysis, we established a regression model for comprehensive score with a correlation coefficient R of 0.997, suggesting a good degree of fitting. Partial least squares regression analysis predicted that the best process parameters were as follows: slice thickness, 2 mm; blanching time, 1 min; saline immersion time, 20 min; saline concentration, 1%; pre-drying temperature, 60 ℃; pre-drying time, 70 min; frying temperature, 150 ℃; and frying time, 1 min. The validation experiment gave a comprehensive score of 0.89, which was higher than the highest score (0.86) from uniform design. The product obtained under the optimized conditions had a low oil content, and accepted color and brittleness, and the proposed model had good prediction ability.

Key words: uniform design, principal component analysis, comprehensive assessment, oil content, color, brittleness

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