AUTHOR=Li Yufei , Liu Ling , Shu Xin , Zhu Fan , Xiang Xinpeng , Wu Chenhao , Tang Bocheng , Hu Yajun , Chen Guanghui , Wang Yue 

TITLE=Key quality traits in rice grains determining fresh wet rice noodles quality: a multivariate statistical methods across varieties

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2025.1685290

DOI=10.3389/fpls.2025.1685290

ISSN=1664-462X

ABSTRACT=Fresh wet rice noodles is one of the delicacies for young and old in East and Southeast Asia. Its main material is rice. However, there are many varieties of rice. Not all rice is suitable for processing into fresh wet rice noodles. In this study, we used 22 rice varieties as raw materials to produce fresh wet rice noodles. Multiple analysis methods, including correlation analysis, principal component analysis, affiliation function analysis, cluster analysis, stepwise regression, and gray correlation analysis, were used to evaluate and classify the quality of rice and fresh wet rice noodles. Identification indices and measurement standards were determined for the evaluation of the quality of the fresh wet rice noodles. The results showed that the 22 rice varieties had large coefficients of variation for rice gel consistency, amylose content, broken noodle rate, and adhesiveness. There were highly significant correlations between all of the individual indices in terms of fresh wet rice noodle quality. Four principal components (composite decision indices) were extracted using principal component analysis, and the cumulative contribution reached 91.442%. In this study, the composite decision index F3 referred to the amylose content and index F4 was the gel consistency. The results of the principal component composite scores and affiliation functions showed that the quality of the rice and fresh wet rice noodles made from Zhuliangyou 4026 and Yuliangyou 22 was excellent. On the basis of the D-value of the combined evaluation of rice quality and fresh wet rice noodle quality, the 22 rice varieties were clustered into four categories at a distance of 0.20. By combining stepwise regression analysis, correlation analysis, and gray correlation analysis, it was determined that amylose content and gel consistency could be used as rice quality indices for evaluating the quality of fresh wet rice noodles. Moreover, the screening conditions for varieties with an amylose content of between 20% and 25% and a gel consistency of less than 40 mm were found to be suitable for fresh wet rice noodle processing. Therefore, multivariate statistical analysis can be an effective means of evaluating flour rice. This study provides a foundation for the standardization, scalability, and industrialization of fresh wet rice noodle production.