0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessColor deterioration is inevitable during the thermal sterilization of cloudy kiwifruit juice (CKJ), which seriously affects its sensory quality. This study explored the effects of citric acid, Ca(OH)2, CuSO4, and α-cyclodextrin on protecting the color and quality of thermally sterilized CKJ. Results showed that the all fixatives reduced the a*, L*, browning index (BI), and ΔE* of CKJ; significantly increased the h°, and effectively prevented the color deterioration of CKJ during thermal sterilization. Except for citric acid, none of the color fixatives changed the sugar-acid ratio of CKJ. Citric acid and α-cyclodextrin treatments significantly enhanced or considerably retained the nutritional quality and antioxidant activity of CKJ. Furthermore, three models of principal component analysis (PCA), entropy weight-TOPSIS and grey relation analysis (GRA) were established based on the multi-criteria decision-making (MCDM) method for comprehensive quality evaluation. The model composite score of CKJ treated with 6 g/kg α-cyclodextrin was the highest, and 0.6 g/kg citric acid was the lowest.
Min Zhang, Haoli Wang, Shihan Bao, Peng Wen, Xinyi Li, Xiangyu Sun, Tingting Ma (2023). Using multi-criteria decision-making method to select the optimal color fixative for cloudy kiwi juice during thermal sterilization processing. , 187, DOI: https://doi.org/10.1016/j.lwt.2023.115266.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2023
Authors
7
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1016/j.lwt.2023.115266
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access