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Ai N, Liu R, Chi X, Song Z, Shao Y, Xi Y, Zhao T, Sun B, Xiao J, Deng J. Rapid discrimination of the identity of infant formula by triple-channel models. Food Chem 2023; 423:136302. [PMID: 37167671 DOI: 10.1016/j.foodchem.2023.136302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 04/11/2023] [Accepted: 05/01/2023] [Indexed: 05/13/2023]
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.
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Affiliation(s)
- Nasi Ai
- 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
| | - Ruirui Liu
- 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
| | - Xuelu Chi
- 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
| | - Zheng Song
- 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
| | - Yiwei Shao
- 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
| | - Yanmei Xi
- 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
| | - Tong Zhao
- 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
| | - Baoguo Sun
- 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
| | - Jianbo Xiao
- 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.
| | - Jianjun Deng
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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Fekete T, Šnirc M, Belej Ľ, Židek R, Golian J, Haščík P, Zeleňáková L, Zajác P. Authentication of caprine milk and cheese by commercial qPCR assay. POTRAVINARSTVO 2017. [DOI: 10.5219/780] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The objective of the study was to investigate potential adulteration of commercial caprine milks and cheeses with bovine milk using commercial qPCR assay. The assay comprised of bovine-, ovine- and caprine-specific primers and TaqMan probe and mammalian internal control. Specificity, sensitivity, linearity, reproducibility and efficiency of the bovine assay were tested as well. Specificity was verified by running reaction on the DNA of other milk-producing species (caprine and ovine) and made-up bovine-caprine (v/v) milk mixes. In both experiments, a bovine DNA fragment was amplified whereas no amplification was obtained from the other species. Sensitivity, linearity, reproducibility and efficiency were tested on 10-fold dilution series of 10 ng bovine DNA. The assay has shown good linearity (R2 = 0.983) within whole range, with efficiency of 86% and excellent reproducibility (SD around the CT for the technical replicates <0.5). The sensitivity was adequate, as calculated LOD and LOQ were 1.44 pg and 2.94 pg of bovine DNA, respectively. Finally, the assay was used to authenticate 5 caprine milk samples and 5 caprine cheese samples, purchased from local supermarkets. Totally, 1 milk sample has shown the fluorescence signal, which exceeded baseline in cycle 39.01 ±0.69. However, the signal was above LOD and LOQ suggesting that there could not be unambiguously declared any adulteration with bovine milk. Amplification of bovine-specific DNA was not observed in the other samples indicating products were not adulterated. The commercial qPCR assay has proved that real-time PCR assays, as well as DNA-based techniques in a general, are the excellent and reliable tools for fighting with frauds in the food industry and protecting the public health.
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Liao J, Liu Y, Ku T, Liu M, Huang Y. Qualitative and quantitative identification of adulteration of milk powder using DNA extracted with a novel method. J Dairy Sci 2017; 100:1657-1663. [DOI: 10.3168/jds.2016-11900] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Accepted: 11/16/2016] [Indexed: 11/19/2022]
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