A conjunction of sn-2 fatty acids and overall fatty acid composition combined with chemometric techniques increase the effectiveness of lard detection in fish feed
نویسندگان
چکیده
Fish oil is a common source of fat in fish feed production. However, there tendency to substitute with other fats such as lard reduce production costs. Thus, an efficient method for detection highly needed feed’s authenticity. In this study, sn-2 fatty acids (sn-2 FAs) and acid (FA) compositions were incorporated chemometric techniques namely Principal Component Analysis (PCA), Orthogonal Partial Least Square-Discriminant (OPLS-DA), Square-Regression (OPLS-R) identify adulteration the feeds. The inclusion FAs into PCA model 2 exhibited preferable variation pattern relative 1. identified C14:0, C18:0, C18:2, C18:3, C20:0 C16:0, C18:1, C18:2 most significant discriminate FA composition improved OPLS-DA performance by providing more class discrimination between lard-adulterated, non-adulterated feeds compared C16:0 markers increment value coefficient determination (R2) decrement Root Mean Square Error Estimation (RMSEE) Standard Cross-Validation (RMSECV) values. Support Vector Machine (SVM), Random Forest (RF), Multilayer Perceptron-Artificial Neural Network (MLP-ANN), internal external validations corroborated OPLS-R performances. Therefore, incorporation coupled had quantification
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ژورنال
عنوان ژورنال: Chemometrics and Intelligent Laboratory Systems
سال: 2021
ISSN: ['1873-3239', '0169-7439']
DOI: https://doi.org/10.1016/j.chemolab.2021.104308