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. 2019 May 28;24(11):2029.
doi: 10.3390/molecules24112029.

Rapid Determination of Nutritional Parameters of Pasta/Sauce Blends by Handheld Near-Infrared Spectroscopy

Marina D G Neves  1   2 , Ronei J Poppi  3 , Heinz W Siesler  4
Affiliations

Rapid Determination of Nutritional Parameters of Pasta/Sauce Blends by Handheld Near-Infrared Spectroscopy

Marina D G Neves et al. Molecules. .

Abstract

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.

Keywords: handheld near-infrared spectroscopy; nutritional parameters; partial least squares calibration; pasta/sauce blends.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Different morphologies of the investigated pastas and a typical experimental set-up for the measurement of a pasta (here without sauce) with the handheld NIR spectrometer.
Figure 2
Figure 2
Sample preparation and spectra acquisition scheme demonstrated exemplarily for Pasta 1 and Sauce 1.
Figure 3
Figure 3
Pretreatments applied to the NIR spectra recorded for the pasta/sauce mixtures.
Figure 4
Figure 4
RMSEC (red) and RMSECV (blue) versus the latent variable number for the individual calibrations of the nutritional parameters.
Figure 5
Figure 5
Graphs of the predicted versus actual content of the respective nutritional parameter per serving (calibration fit (formula image), prediction fit (formula image), calibration samples (formula image) and predicted test set samples (formula image)).
See this image and copyright information in PMC

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