[关键词]
[摘要]
为更好地说明不同紫薯品种在质构特性上的差异,本研究选取了16个紫薯品种,测定了薯块水分、淀粉组成以及原淀粉的热力学特性,并对质构特性进行了质构剖面(TPA)和感官分析。箱线图分析显示样品水分、淀粉含量和热力学参数均存在离群值。不同样品的TPA质构存在显著性差异(p<0.05),其中水分含量最低(59.16%)的育种材料QZ5070硬度(4880 g)、弹性(3.57 mm)、胶黏性(1265 mJ)、咀嚼性(43.34 mJ)和可恢复形变(1.71 mm)均为最高值。多元相关分析结果显示水分含量与TPA咀嚼性、感官硬性、感官干面性显著负相关(p<0.05),而与感官粘聚性与感官易嚼性显著正相关(p<0.05)。淀粉含量则未与质地指标表现出显著相关性,淀粉热力学参数中只有糊化焓和感官易嚼性显著正相关(p<0.05)。双向聚类分析结果显示样品聚为4类,指标聚为5类,综合指标聚类结果和标准化数据的热图分析,渝紫7号、越南紫薯、日本新紫和3种育种材料QZ5070、W36-1、W50-2表现出与其他样品不同的质地特性。研究结果为以甘薯鲜食、加工适性评价和育种方向提供有效信息。
[Key word]
[Abstract]
In order to investigate the texture difference of 16 purple sweetpotato cultivars, texture profile analysis (TPA) using texture analyzer and sensory texture profile evaluation were conducted. The moisture content, starch constitution, thermodynamic properties were also determined. Results showed that some samples displayed as outliers in boxplots and there were significant differences (p<0.05) on the texture parameters among the samples. QZ5070 showed the lowest value of moisture content (59.16%) as well as the highest values of hardness (4880 g), springiness (3.57 mm), adhesiveness (1265 mJ), chewiness (43.34 mJ), and recoverable deformation (1.71 mm). Multiple correlation analysis showed the moisture content negatively correlated with TPA chewiness, sensory hardness, and sensory floury, while it positively correlated with sensory cohesiveness and sensory chewiness (p<0.05). No significant correlations among the starch contents and texture properties. In addition, △H, a thermodynamic parameter, was positively correlated with sensory chewiness (p<0.05). Moreover, 4 sample groups and 5 parameter class were clustered using two-way cluster analysis (CA). From the heatmap of the normalized data and the cluster results, Yuzi-7, Yuenan-zishu, Riben-xinzi and 3 breeding materials (QZ5070, W36-1 and W50-2) were distinguished themselves from the other cultivars. In conclusion, the results will offer valuable texture information for sweetpotato eating, processing and breeding quality improvements.
[中图分类号]
[基金项目]
江苏省重点研发项目(BE2018382)