基于质构和感官评价方法构建绿葡萄干干燥标准及快速检测技术

绿葡萄干较高的经济价值是维持新疆葡萄产业优势地位的重要支撑,葡萄干含水率对葡萄干的色泽、营养品质、质构特性和感官品尝体验具有较大的影响,但相关研究较少。本研究通过对不同含水率绿葡萄干品质、质构特性和感官品尝结果进行关联性分析,将定量检测技术应用到葡萄干的生产中。结果表明,不同含水率葡萄干的营养品质具有一定的差异,色泽分析中绿色色泽的差异最为显著;11.9%~19.2%含水率区间内葡萄干的质构特性呈现出较好的线性上升或下降趋势;不同人群对不同含水率葡萄干的感官品尝结果具有较大差异,含水率高的葡萄干在不同年龄段人群中的感官评分较高,根据感官评价结果和葡萄干的贮藏特性综合评价,生产中葡萄干含水率应控制在14%~17%;对葡萄干含水率与质构指标进行拟合,预测值与实测值的相对误差较小,弹性的相对误差最小为2.91%,粘附性的相对误差最大为13.33%;含水率14%~17%的葡萄干硬度预测值分别为1349.86、1191.75、1033.64、875.53 g;以硬度为快速检测指标,快速计算葡萄干含水率、弹性、咀嚼性等指标,拟合度较高,硬度与含水率的拟合方程为y=(-0.00006x+0.2191)×100,R²值为0.9171。综上,不同含水率葡萄干的色泽品质具有较大的差异,不同人群均喜欢较高含水率的葡萄干,采用硬度值快速计算葡萄干含水率及其他质构特性指标具有一定的可行性。研究结果可为绿葡萄干的标准化生产提供数据支撑和理论依据。

Drying Standard and Rapid Detection Technology of Green Raisin Based on Texture and Sensory Evaluation Method

The high economic value of green raisins is an important support to maintain the dominant position of Xinjiang grape industry. The moisture content of raisins has a great influence on the color, nutritional quality, texture characteristics, and sensory taste experience of raisins, but there are few related studies. In this study, the correlation analysis was carried out on the quality, texture characteristics and sensory tasting results of raisins with different moisture contents, to apply the quantitative texture determination technology to the production of raisins. The results showed that the color of raisins with different moisture contents had certain differences, of which the difference in green color was the most significant. The texture characteristics of raisins showed a good linear upward or downward trend in the range of 11.9%-19.2% moisture content. The sensory taste results of raisins with different moisture contents were quite different in different populations. Raisins with high moisture content had higher sensory scores in different age groups. According to the sensory evaluation results and the comprehensive evaluation of storage characteristics of raisins, the moisture content of raisins in production should be controlled at 14%-17%. Fitting the moisture content and texture index of raisins, the relative error between the predicted value and the measured value was small, the relative error of elasticity was the minimum of 2.91%, and the relative error of adhesion was the maximum of 13.33%. The hardness prediction values of 14%-17% raisin moisture content were 1349.86, 1191.75, 1033.64, 875.53g respectively. Using hardness as an index, this paper explored the rapid calculation of moisture content, elasticity, chewiness and other indexes of raisins. The fitting degree was high. The fitting equation between hardness and moisture content was y=(-0.00006x+0.2191)×100, and R² value was 0.9171. To sum up, the color quality of raisins with different moisture contents was quite different. Different groups of people preferred to raisins with higher moisture content. It is feasible to quickly calculate the moisture content and other texture characteristics of raisins by using hardness value. The research results can provide data support and a theoretical basis for standardized production of green raisins.