TY - JOUR AU - De Pedro-Sanz, E. AU - Serrano, A. AU - Zamora-Rojas, E. AU - Garrido-Varo, A. AU - Guerrero-Ginel, J. E. AU - Pérez-Marín, D. AU - García-Casco, J. M. AU - Núñez-Sánchez, N. PY - 2013/06/30 Y2 - 2024/03/28 TI - Predicting Acorn-Grass Weight Gain Index using non-destructive Near Infrared Spectroscopy in order to classify Iberian pig carcasses according to feeding regime JF - Grasas y Aceites JA - Grasas aceites VL - 64 IS - 2 SE - Research DO - 10.3989/gya.131012 UR - https://grasasyaceites.revistas.csic.es/index.php/grasasyaceites/article/view/1426 SP - 210-218 AB - The classification of Iberian pig carcasses into different commercial categories according to feeding regime was evaluated by means of a non-destructive analysis of the subcutaneous adipose tissue using Near Infrared Spectroscopy (NIRS). A quantitative approach was used to predict the Acorn-Grass 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 (<i>Acorn, Recebo</i> and <i>Feed</i>), 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 (<i>Acorn</i> and <i>Feed</i>). ER -