Rapid Determination of Nutritional Parameters of Pasta/Sauce Blends by Handheld Near-Infrared Spectroscopy
Institute of Chemistry, University of Campinas, Campinas CP 6154, Brazil
Department of Physical Chemistry, University of Duisburg-Essen, D 45117 Essen, Germany
Author to whom correspondence should be addressed.
Academic Editor: Christian Huck
Molecules 2019, 24(11), 2029; https://doi.org/10.3390/molecules24112029
Received: 6 May 2019 / Revised: 24 May 2019 / Accepted: 25 May 2019 / Published: 28 May 2019
(This article belongs to the Special Issue Advances in Near Infrared Spectroscopy and Related Computational Methods)
Nowadays, near infrared (NIR) spectroscopy has experienced a rapid progress in miniaturization (instruments < 100 g are presently available), and the price for handheld systems has reached the < $500 level for high lot sizes. Thus, the stage is set for NIR spectroscopy to become the technique of choice for food and beverage testing, not only in industry but also as a consumer application. However, contrary to the (in our opinion) exaggerated claims of some direct-to-consumer companies regarding the performance of their “food scanners” with “cloud evaluation of big data”, the present publication will demonstrate realistic analytical data derived from the development of partial least squares (PLS) calibration models for six different nutritional parameters (energy, protein, fat, carbohydrates, sugar, and fiber) based on the NIR spectra of a broad range of different pasta/sauce blends recorded with a handheld instrument. The prediction performance of the PLS calibration models for the individual parameters was double-checked by cross-validation (CV) and test-set validation. The results obtained suggest that in the near future consumers will be able to predict the nutritional parameters of their meals by using handheld NIR spectroscopy under every-day life conditions.