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Compositional method for measuring the nutritional label components of industrial pastries and biscuits based on Vis/NIR spectroscopy

AuthorsCayuela, José Antonio ; Palarea-Albaladejo, Javier; Zira, Tatiana P.; Moriana-Correro, Elena
KeywordsNutritional label
Compositional data
Monounsaturated fat
Polyunsaturated fat
Saturated fat
Issue DateSep-2020
CitationJournal of Food Composition and Analysis 92: 103572 (2020)
AbstractFood nutritional labeling is compulsory in the European Union since 13 December 2016. The analysis of all batches of foodstuff using the official methods is expensive and the food industry seeks cost-efficient solutions for measuring the components of nutritional labels. The information is commonly provided in the form of fractions or parts of a number of nutritional categories, typically expressed in percentage units. This corresponds with so-called compositional data for which specific statistical methods and models have been developed. Compositional data analysis focuses on log-ratios between the parts, so that their relative scale and inherent interplay are accounted for. This study set up and validates a new rapid technique to measure the nutritional makeup of industrial pastries and biscuits for labelling purposes. Nutritional components and types of fat were separately modeled. Compositional partial least squares (PLS) calibration models, formulated through adequate log-ratio coordinates, were fitted based on visible and near infrared spectroscopy (NIRS) and applied to estimate the composition of (1) moisture, total fat, protein, and carbohydrates and (2) saturated, polyunsaturated and monounsaturated fats from intact and ground samples of a variety of types of industrial pastry and biscuit present in the market. This investigation proposes a useful and methodologically well-founded approach for measuring the components of the nutritional label or its verification, which may be set-up to other foodstuffs.
Description6 Figuras.-- 6 Tablas
Publisher version (URL)http://dx.doi .org/10.1016/j.jfca.2020.103572
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