Predicting Acorn-Grass Weight Gain Index using non-destructive Near Infrared Spectroscopy in order to classify Iberian pig carcasses according to feeding regime

Abstract

RESUMEN Predicción del Índice de Reposición en Montanera para la clasificación de canales de cerdo Ibérico según régimen alimenticio mediante el análisis no destructivo por Espectroscopía del Infrarrojo CercanoLa clasificación en distintas categorías comerciales según régimen alimenticio de canales de cerdo Ibérico fue evaluada mediante el análisis no destructivo de muestras de tejido adi poso subcutáneo por Espectroscopía del Infrarrojo Cercano (NIRS). Partiendo de una aproximación cuantitativa para pre decir el Índice de Reposición en Montanera (IRM) se estable cieron una serie de criterios para proceder a su clasificación comercial. Se analizaron un total de 719 animales pertene cientes a diversas partidas, que recogen una amplia variabili dad de muestras de distintos regímenes alimenticios, campa ñas y sistemas productivos, para el desarrollo y evaluación de los modelos NIRS cuantitativos. Los resultados de validación externa de los modelos indicaron que es posible discriminar con una gran exactitud entre partidas de distintos categorías (Bellota, Recebo y Cebo), en base al espectro medio repre sentativo de cada partida. Además, el análisis individualizado de los animales mostró un amplio consenso entre la informa ción recibida de campo y la clasificación en base a la predic ción del parámetro IRM por NIRS, sobre todo para categorías con características extremas (Bellota y Cebo). PALABRAS CLAVE: Cerdo Ibérico -Clasificación -Espectroscopía Infrarrojo Cercano -Índice de Reposición en Montanera -Intacto -Régimen alimenticio -Tejido adiposo. SUMMARY Predicting Acorn-Grass Weight Gain Index using non-destructive Near Infrared Spectroscopy in order to classify Iberian pig carcasses according to feeding regimeThe classification of Iberian pig carcasses into different commercial categories according to feeding regime was evaluated by means of a nondestructive analysis of the subcutaneous adipose tissue using Near Infrared Spectroscopy (NIRS). A quantitative approach was used to predict the AcornGrass Weight Gain Index (AGWGI), and a set of criteria was established for commercial classification purposes. A total of 719 animals belonging to various batches, reflecting a wide range of feeding regimes, production systems and years, were analyzed with a view to developing and evaluating quantitative NIRS models. Results for the external validation of these models indicate that NIRS made clear differentiation of batches as a function of three feeding regimes possible with high accuracy (Acorn, Recebo and Feed), on the basis of the mean representative spectra of each batch. Moreover, individual analysis of the animals showed a broad consensus between field inspection information and the classification based on the AGWGI NIRS prediction, especially for extreme categories (Acorn and Feed).

Miniature near infrared spectroscopy spectrometer and information and communication technologies to guarantee the integrity of the EU high added-value "acorn Iberian pig ham" (IP)

“…A key factor in the cloning process is the number of samples used when selecting a cloning algorithm (De Pedro et al 2013;De Boor 1978). Here, 66 samples were analyzed in parallel and, as explained in section 2.2.3, two strategies were compared: the selection of ten samples using the CENTER algorithm and the selection of one sample.…”

Portable Raman Spectrometer as a Screening Tool for Characterization of Iberian Dry-Cured Ham

“…In this case, raw pig fat was analyzed in order to differentiate ham samples of pigs fed with fodder that emulate a free-range regime from samples of pigs fed within a genuine extensive system. Furthermore, a fast and non-destructive technique, near-infrared spectroscopy (NIRS), has been studied as a tool for Iberian pig carcass classification according to feeding regime [ 9 , 10 , 11 , 12 ].…”