| Title: | Rapid discrimination of the identity of infant formula by triple-channel models |
| Author(s): | Ai N; Liu R; Chi X; Song Z; Shao Y; Xi Y; Zhao T; Sun B; Xiao J; Deng J; |
| Address: | "Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Higher Institution Engineering Research Center of Food Additives and Ingredients, Beijing Technology & Business University, Beijing 100048, China. Nutrition and Bromatology Group, Department of Analytical Chemistry and Food Science, Faculty of Food Science and Technology, University of Vigo - Ourense Campus, E-32004 Ourense, Spain. Electronic address: jianboxiao@yahoo.com. State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China. Electronic address: dengjianjun@nwu.edu.cn" |
| DOI: | 10.1016/j.foodchem.2023.136302 |
| ISSN/ISBN: | 1873-7072 (Electronic) 0308-8146 (Linking) |
| Abstract: | "Infant formula is related to children's life and health. However, the existing identification methods for infant formula are time-consuming, costly and prone to environmental pollution. Therefore, a simple, efficient and less polluting identification method for infant formula is urgently needed. The aim of this study was to distinguish between goat and cow infant formula using HS-SPME-GC-MS and E-nose combined with triple-channel models. The results indicated that the main difference of them attributed to thirteen volatile compounds and three sensor variables. Based on this, the linear discriminant and partial least squares discriminant analyses were conducted, and a multilayer perceptron neural network model was constructed to identify the commercial samples. There was a high percentage of correct classifications (>90%) in samples. Together, our work demonstrated that the volatile compounds of infant formula combined with chemometric analysis were effective and rapid for detecting two infant formulas" |
| Keywords: | Animals Cattle Female *Infant Formula/analysis Gas Chromatography-Mass Spectrometry/methods Discriminant Analysis Electronic Nose Least-Squares Analysis Goats *Volatile Organic Compounds/analysis Solid Phase Microextraction/methods Cow infant formula E-no; |
| Notes: | "MedlineAi, Nasi Liu, Ruirui Chi, Xuelu Song, Zheng Shao, Yiwei Xi, Yanmei Zhao, Tong Sun, Baoguo Xiao, Jianbo Deng, Jianjun eng England 2023/05/12 Food Chem. 2023 Oct 15; 423:136302. doi: 10.1016/j.foodchem.2023.136302. Epub 2023 May 4" |
