基于主成分分析构建混合多糖凝胶品质综合评价模型

Construction of a Comprehensive Evaluation Model for Assessing the Quality of Mixed Polysaccharide Gels Based on Principal Component Analysis

摘要:

为了构建混合多糖凝胶的综合评价预测模型，该研究采用全质构分析法（TPA）和感官评价法对5种亲水胶体复配得到的25种混合多糖凝胶进行测定。结果表明，混合凝胶质构硬度与感官硬度、脆性呈极显著正相关；质构内聚性、咀嚼性与感官硬度、脆性、咀嚼性、弹性、总体可接受度呈极显著正相关；质构弹性与感官弹性、咀嚼性呈极显著正相关，而感官气味与质构指标均不相关。利用主成分分析法从混合凝胶的11个评价指标中提取出3个主成分，累计方差贡献率达到82.45%，建立了混合多糖凝胶的综合评价模型。根据综合评分结果知，当混合凝胶配方为k-卡拉胶0.8%、魔芋胶1.2%、低酰结冷胶0.4%、刺槐豆胶0.6%、海藻酸钠0.4%时，混合多糖凝胶的得分最高为1 476.17；而当混合凝胶中不添加k-卡拉胶时，综合评分最低为424.56。基于主成分分析得到的综合评价模型对混合多糖凝胶品质进行评价，可以客观的反映出混合多糖凝胶的品质。

Abstract:

To establish a comprehensive evaluation and prediction model for mixed polysaccharide gels, 25 mixed polysaccharide gels obtained by combining five hydrocolloids were determined by texture profile analysis (TPA) and sensory evaluation. The results indicated that the textural hardness of mixed gels was significantly and positively correlated with sensory hardness and brittleness, whereas cohesion and chewiness were significantly and positively correlated with sensory hardness, brittleness, chewiness, elasticity, and overall acceptability. Textural elasticity was significantly and positively correlated with sensory elasticity and chewiness; however, no correlation was observed between sensory odor and the textural indicators. A cumulative variance contribution rate of 82.45% was obtained for the three principal components extracted from 11 indices, and a comprehensive evaluation model of the mixed polysaccharide gels was established. According to the comprehensive scoring results, the highest score of 1 476.17 was obtained for the gel comprising 0.8% k-carrageenan, 1.2% konjac gum, 0.4% lectin, 0.6% locust bean gum, and 0.4% sodium alginate, whereas the lowest score of 424.56 was obtained for gels to which no k-carrageenan was added. The comprehensive evaluation model can thus objectively reflect the quality of mixed polysaccharide gels. Key words: mixed polysaccharide gel; texture property; sensory evaluation; correlation analysis; principal component analysis; comprehensive evaluation model