Abstract:
Due to the existence of many potato varieties, the quality of different raw materials will affect the quality of potato noodles. The purpose was to study the suitability of different potato varieties for processing noodles and guide the potato industry to select processing and planting varieties. The maximum-minimum normalization method was used to transform each quality index of potato dough and potato noodles into a one-dimensional comprehensive evaluation index, which was compared with 40 varieties of potato raw materials (starch, vitamin C, soluble protein, reducing sugar, crude fiber, potassium, ash, dry matter, free amino acid). Fitting and regression models were established for hardness, elasticity, cohesion, chewiness, stickiness and resilience. Forty potato varieties were classified into three categories according to processing suitability by clustering method. The results showed that the determinant coefficient R2 was 0.911, the adjusted determinant coefficient R2 was 0.904, the random error estimate was 123.113, the determinant coefficient R2 was 0.973, the adjusted determinant coefficient R2 was 0.971, and the random error estimate was 432.226; K-means clustering algorithm was used. According to processing suitability, 40 potato varieties were divided into three categories: the most suitable, the basically suitable and the unsuitable. Among them, 12 varieties were suitable for processing, including 05-44-1, Ke 9, 79(2), C11, D17, C3, T3, Zhuang 3, Hui 2, T4, L7 and Hei. The basically suitable varieties were L0524-2, Ji 8, T2, F5, Hong, Zheng 7, S3-28, Zhong901, S4-32, Zhong13, T5, Ji 12, Gannong 5, Jin 18, F6, T18 and 78. The comprehensive quality evaluation model obtained in this study had high fitting degree, small error and reliable effect. It can be used to evaluate the quality of potato noodles. The K-means clustering results are consistent with the actual application, which can provide reference for the selection of processing varieties in Xinjiang.