Detection and Quantification of Ruminant Meal in Processed Animal Proteins: A Comparative Study of near Infrared Spectroscopy and near Infrared Chemical Imaging
Abstract:This study compared the performance of single-point near infrared spectroscopy (NIR) and near infrared chemical imaging (NIR-CI) for the detection and quantification of ruminant meat meal in processed animal proteins (PAPs). A set of 126 fish-meal samples adulterated with controlled amounts (0.25% to 16%) of ruminant meal were analysed using the two techniques. Comparison of results showed that spectra obtained by NIR-CI provided better qualitative information, whereas more accurate quantitative predictions we… Show more
“…Similar absorption bands have been mentioned by other authors as dominant in animal-derived proteic and lipid by-products. 45,48 The results shown in these graphs convinced the authors that it was possible to develop calibrations in both modes of analysis and that both could attain similar levels of precision and exactitude. Table I shows the mean, range, standard deviation (SD), and coefficient of variation (CV) for the total PAP set (n ¼ 346).…”
Section: Optimization Of the Spectroscopic Signal And Spectral Studymentioning
confidence: 82%
“…Similar absorption bands have been mentioned by other authors as dominant in animal-derived proteic and lipid by-products. 45,48 Figure 4.Mean NIR spectra for LAPs analyzed with the MATRIX-F instrument in static and dynamic mode.…”
Section: Resultsmentioning
confidence: 99%
“…Moreover, two of these three samples were also identified as anomalous in previous studies. 45 For all the above reasons it was decided to remove these three samples from the total set and develop the calibration equations without them.…”
This research was conducted using a spectral database comprising 346 samples of processed animal proteins (PAPs) with a range of compositions, analyzed using a Fourier transform near-infrared spectroscopy multichannel instrument (Matrix-F, Bruker Optics) coupled to a 100 m fiber optic cable. Using both its static and dynamic operating modes (on a conveyor belt), simulating the movement of the product in the plant, the predictive capabilities of both modes of analysis were assessed and compared, for the purposes of predicting moisture, protein, and ashes. The results show that both exhibit highly similar degrees of precision and accuracy for predicting these parameters. This research provides a foundation of scientific-technical knowledge, hitherto unknown, regarding the "on-line" incorporation of an instrument (equipped with a 100 m fiber optic cable) into a processing plant of by-products of animal origin.
“…Similar absorption bands have been mentioned by other authors as dominant in animal-derived proteic and lipid by-products. 45,48 The results shown in these graphs convinced the authors that it was possible to develop calibrations in both modes of analysis and that both could attain similar levels of precision and exactitude. Table I shows the mean, range, standard deviation (SD), and coefficient of variation (CV) for the total PAP set (n ¼ 346).…”
Section: Optimization Of the Spectroscopic Signal And Spectral Studymentioning
confidence: 82%
“…Similar absorption bands have been mentioned by other authors as dominant in animal-derived proteic and lipid by-products. 45,48 Figure 4.Mean NIR spectra for LAPs analyzed with the MATRIX-F instrument in static and dynamic mode.…”
Section: Resultsmentioning
confidence: 99%
“…Moreover, two of these three samples were also identified as anomalous in previous studies. 45 For all the above reasons it was decided to remove these three samples from the total set and develop the calibration equations without them.…”
This research was conducted using a spectral database comprising 346 samples of processed animal proteins (PAPs) with a range of compositions, analyzed using a Fourier transform near-infrared spectroscopy multichannel instrument (Matrix-F, Bruker Optics) coupled to a 100 m fiber optic cable. Using both its static and dynamic operating modes (on a conveyor belt), simulating the movement of the product in the plant, the predictive capabilities of both modes of analysis were assessed and compared, for the purposes of predicting moisture, protein, and ashes. The results show that both exhibit highly similar degrees of precision and accuracy for predicting these parameters. This research provides a foundation of scientific-technical knowledge, hitherto unknown, regarding the "on-line" incorporation of an instrument (equipped with a 100 m fiber optic cable) into a processing plant of by-products of animal origin.
“…This explains the excessively high limit of detection (LOD) of NIR spectroscopy methods, about 1 % (w/w), which makes them impracticable in the context of the prohibition of ABPs. NIR microscopy (NIRM) [38][39][40][41][42][43] , NIR hyperspectral imaging [44][45][46] and Raman imaging 47 were then studied. These techniques combine the advantages of microscopy and spectroscopy techniques and are based on the NIR spectral absorbance or Raman scattering signatures of individual particles.…”
Section: Alternative Methods Already Investigatedmentioning
In the context of the expansion of the human population, availability of food, and in extension of animal feed, is a big issue. Favoring a circular economy by the valorization of by-products is a sustainable way to be more efficient. Animal by-products are an interesting source of feed materials due to their richness in proteins of high nutritional value. Prevention and control efforts have allowed a gradual lifting of the feed ban regarding the use of animal by-products. Nevertheless, the challenge remains the development of analytical methods enabling a distinction between authorized and unauthorized feed materials. This review focuses on the historical and epidemiological context of the official control, the evaluation of current and foreseen legislation and the available methods of analysis for the detection of constituents of animal origin in feedingstuffs. It also underlines the analytical limitations of the approach and discusses some prospects of novel methods to ensure food and feed safety.
“…In the last decade, image analysis has been added to spectroscopy resulting in hyperspectral imaging. The inclusion of the spatial domain allows some quantitative and qualitative approximations that are not possible with traditional single-point spectroscopy [10,11]. Several hyperspectral studies have been carried out, in our laboratory, for the analysis of the chemical composition of grapes [12], grape maturity [13] and to measure phenols concentration in grape or grape seeds [14,15].…”
Developing chemometric models from near-infrared (NIR) spectra requires the use of a representative calibration set of the entire population. Therefore, generally, the calibration procedure requires a large number of resources. For that reason, there is a great interest in identifying the most spectrally representative samples within a large population set. In this study, principal component and hierarchical clustering analyses have been compared for their ability to provide different representative calibration sets. The calibration sets generated have been used to control the technological maturity of grapes and total phenolic compounds of grape skins in red and white cultivars. Finally, the accuracy and precision of the models obtained with these calibration sets resulted from the application of the selection algorithms studied have been compared with each other and with the whole set of samples using an external validation set. Most of the standard errors of prediction (SEP) in external validation obtained from the reduced data sets were not significantly different from those obtained using the whole data set. Moreover, sample subsets resulting from hierarchical clustering analysis appear to produce slightly better results.
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