Comparison of prediction models for soy protein isolate hydrolysates bitterness built using sensory, spectrofluorometric and chromatographic data from varying enzymes and degree of hydrolysis-Reference-Cited by-同舟云学术

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Comparison of prediction models for soy protein isolate hydrolysates bitterness built using sensory, spectrofluorometric and chromatographic data from varying enzymes and degree of hydrolysis

Published:2024-06 Issue: Volume:442 Page:138428
ISSN:0308-8146
Container-title:Food Chemistry
language:en
Short-container-title:Food Chemistry

Author:

Yolandani ,Liu Dandan,Raynaldo Fredy Agil,Dabbour Mokhtar^ORCID,Zhang Xueli,Chen Zhongyuan,Ding Qingzhi,Luo Lin,Ma Haile^ORCID

Publisher

Elsevier BV

Subject

General Medicine,Food Science,Analytical Chemistry

Reference40 articles.

1. Comparisons of AdaBoost, KNN, SVM and Logistic Regression in Classification of Imbalanced Dataset;Abd Rahman;Soft Computing in Data Science, Scds,2015

2. A review of food hydrolysis specific areas;Adler-Nissen,1986

3. Reversed-Phase High-Performance Liquid Chromatography;Aguilar,2004

4. Structural Characteristics of Food Protein-Derived Bitter Peptides;Aluko;Bitterness,2017

5. Sensory and Chemical Properties of Protein Hydrolysates Based on Mackerel (Scomber scombrus) and Salmon (Salmo salar) Side Stream Materials;Aspevik;Journal of Aquatic Food Product Technology,2021

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