Abstract
The new regulation about mandatory labelling on nutrition requires the declaration of specific parameters: protein, lipid, salt and carbohydrate contents. This study reports a fast, accurate method to determine the values of these mandatory nutritional parameters based on near infra-red reflectance spectroscopy (NIRs) technology and data mining techniques, used in an automatic way. For that, two batches of different Iberian pork meat products (dry-cured ham, dry-cured loin, dry-cured shoulder, dry-fermented Salchichon sausage, and dry-fermented Chorizo sausage were used. One batch of each product was used to train the method and the remaining batch was used for validation. To develop the method, prediction equations were obtained from the NIRs, while nutritional data for the training batches were obtained by applying data mining techniques, and the prediction equations were evaluated against the NIRs data from the validation batch. The prediction equations achieved from very good to excellent degrees of relationship (R > 0.75) and accurate results (MAE 0.75). This new method is rapid, as it takes around 10 minutes in comparison with traditional methods that take around 6 days.
Highlights
IntroductionIn the European Union (EU), mandatory labelling of nutritional information requires specific parameters (protein, lipid, saturated lipid, salt, carbohydrate and sugar contents) to be declared (European Union, 2011)
In the European Union (EU), mandatory labelling of nutritional information requires specific parameters to be declared (European Union, 2011)
MLR was applied to the near infra-red reflectance spectroscopy (NIRs) data from the training batch of Iberian meat products to obtain prediction equations for the main nutritional parameters of these meat products
Summary
In the European Union (EU), mandatory labelling of nutritional information requires specific parameters (protein, lipid, saturated lipid, salt, carbohydrate and sugar contents) to be declared (European Union, 2011). This regulation aims to protect consumers’ health by informing them of the food’s nutritional content It moderates the provision of useful, understandable and uniform information to consumers, allowing them to make coherent decisions and safe food choices (Benoit et al, 2016). In this regulation, the detection limits for the main nutritional parameters are 0.1 %, but if the value detected is less than this percentage, the amount can be declared as not detectable (European Union, 2011).
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