RESUMEN
Iberian pig ham is one of several high value European food products that are the subject of significant attempts at fraud because of the high price differences between commercial categories. Iberian pig products are classified by the Spanish regulations into different categories, mainly depending on the feeding regime during the fattening phase and the race involved, being of Premium quality those products obtained from the animals fed with acorns and other natural resources. Most of the previous NIRS studies related to the Iberian pig have involved the use of at-line instruments to predict quantitative quality parameters. This paper explores the use of the NIR spectra (369 for training and 199 for validation) to classify samples according to the categories Premium (animals fed with acorn) and Non Premium (animals fed with compound feeds), using a MicroNIR™ Pro1700 microspectrometer to analyse individual carcasses in situ at the slaughterhouse line. Four discriminant methods were explored: linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), Kernel Bayes and Logistic Regression. These are all discriminant methods that naturally produce classification probabilities to quantify the uncertainty of the results. Rules were tuned and methods compared using both classification error rates and a probability scoring rule. LDA gave the best results, attaining an overall accuracy of 93% and providing well-calibrated classification probabilities.
Asunto(s)
Espectroscopía Infrarroja Corta , Animales , Teorema de Bayes , Análisis Discriminante , PorcinosRESUMEN
This study assesses the capacity of a Fourier transform near-infrared (FT-NIR) spectrometer operating in the range 4500-12 000 cm-1 (833.33-2222.22 nm) to provide quantitative predictions for the parameters of acidity (AV), p-anisidine (pAV), total polar materials (TPM), peroxide value (PV), and oxidative stability index (OSI). 562 samples of frying oil were analyzed from 14 distinct types of oil. The calibrations obtained accounted for 96%, 95%, 99%, 92%, and 91% of the AV, pAV, TPM, PV, and OSI variations in the study set and the similarity between the standard error of laboratory (RMSEP) values and the reference method errors (RMSEL), enabling the authors to conclude that NIR technology has the capacity to replace traditional methods in thermo-oxidative degradation studies in frying oils.
Asunto(s)
Culinaria , Grasas Insaturadas en la Dieta/análisis , Grasas Insaturadas/química , Espectroscopía Infrarroja por Transformada de Fourier/métodos , Espectroscopía Infrarroja Corta/métodos , Compuestos de Anilina/química , Concentración de Iones de Hidrógeno , Oxidación-Reducción , Reproducibilidad de los ResultadosRESUMEN
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.
Asunto(s)
Proteínas en la Dieta/análisis , Productos de la Carne/análisis , Productos de la Carne/normas , Espectroscopía Infrarroja por Transformada de Fourier/métodos , Espectroscopía Infrarroja Corta/métodos , Animales , Reproducibilidad de los ResultadosRESUMEN
This paper proposes a method based on near-infrared hyperspectral imaging for discriminating between terrestrial and fish species in animal protein by-products used in livestock feed. Four algorithms (Mahalanobis distance, Kennard-Stone, spatial interpolation, and binning) were compared in order to select an appropriate subset of pixels for further partial least squares discriminant analysis (PLS-DA). The method was applied to a set of 50 terrestrial and 40 fish meals analyzed in the 1000-1700 nm range. Models were then tested using an external validation set comprising 45 samples (25 fish and 20 terrestrial). The PLS-DA models obtained using the four subset-selection algorithms yielded a classification accuracy of 99.80%, 99.79%, 99.85%, and 99.61%, respectively. The results represent a first step for the analysis of mixtures of species and suggest that NIR-CI, providing valuable information on the origin of animal components in processed animal proteins, is a promising method that could be used as part of the EU feed control program aimed at eradicating and preventing bovine spongiform encephalopathy (BSE) and related diseases.