Detection and characterisation of frauds in bovine meat in natura by non-meat ingredient additions using data fusion of chemical parameters and ATR-FTIR spectroscopy
Detection and characterisation of frauds in bovine meat in natura by non-meat ingredient additions using data fusion of chemical parameters and ATR-FTIR spectroscopy
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DOI：
10.1016/j.foodchem.2016.02.158
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发表时间：
2016-08-15
期刊：
影响因子：
8.8
通讯作者：
Sena, Marcelo M.
中科院分区：
文献类型：
--
作者：
Nunes, Karen M.;Andrade, Marcus Vinicius O.;Sena, Marcelo M.
最近，由于大量的欺诈丑闻，人们对肉类真实性的担忧日益增加。本文分析了来自巴西警方捣毁的犯罪网络的真实样本（43个掺假样本和12个对照样本）。这种欺诈包括在牛肉中注射非肉类成分（NaCl，磷酸盐，卡拉胶，麦芽糊精）的溶液，旨在增加其持水能力。测定了5个理化变量：蛋白质、灰分、氯化物、钠、磷酸盐。此外，还记录了红外光谱。对每个数据集分别建立监督分类PLS-DA模型，通过数据融合获得最佳模型，正确率达91%。从该模型中，根据最高vipscore进行变量选择，并仅使用一个化学变量构建新的数据融合模型，提供略低的预测，但具有良好的成本/性能比。最后，选定的一些红外波段与掺假物NaCl、三聚磷酸盐和卡拉胶的存在有特定的关联。(C) 2016 Elsevier Ltd.版权所有。
Concerns about meat authenticity are increasing recently, due to great fraud scandals. This paper analysed real samples (43 adulterated and 12 controls) originated from criminal networks dismantled by the Brazilian Police. This fraud consisted of injecting solutions of non-meat ingredients (NaCl, phosphates, carrageenan, maltodextrin) in bovine meat, aiming to increase its water holding capacity. Five physicochemical variables were determined, protein, ash, chloride, sodium, phosphate. Additionally, infrared spectra were recorded. Supervised classification PLS-DA models were built with each data set individually, but the best model was obtained with data fusion, correctly detecting 91% of the adulterated samples. From this model, a variable selection based on the highest VIPscores was performed and a new data fusion model was built with only one chemical variable, providing slightly lower predictions, but a good cost/performance ratio. Finally, some of the selected infrared bands were specifically associated to the presence of adulterants NaCl, tripolyphosphate and carrageenan. (C) 2016 Elsevier Ltd. All rights reserved.