Paper
22 October 2007 Classification of rabbit meat obtained with industrial and organic breeding by means of spectrocolorimetric technique
P. Menesatti, S. D'Andrea, P. Negretti
Author Affiliations +
Abstract
Rabbit meat is for its nutritional characteristics a food corresponding to new models of consumption. Quality improvement is possible integrating an extensive organic breeding with suitable rabbit genetic typologies. Aim of this work (financed by a Project of the Lazio Region, Italy) was the characterization of rabbit meat by a statistic model, able to distinguish rabbit meat obtained by organic breeding from that achieved industrially. This was pursued through the analysis of spectral data and colorimetric values. Two genetic typologies of rabbit, Leprino Viterbese and a commercial hybrid, were studied. The Leprino Viterbese has been breeded with two different systems, organic and industrial. The commercial hybrid has been bred only industrially because of its characteristics of high sensibility to diseases. The device used for opto-electronic analysis is a VIS-NIR image spectrometer (range: 400-970 nm). The instrument has a stabilized light, it works in accordance to standard CIE L*a*b* technique and it measures the spectral reflectance and the colorimetric coordinates values. The statistic data analysis has been performed by Partial Least Square technique (PLS). A part of measured data was used to create the statistic model and the remaining data were utilized in phase of test to verify the correct model classification. The results put in evidence a high percentage of correct classification (90%) of the model for the two rabbit meat classes, deriving from organic and industrial breeding. Moreover, concerning the different genetic typologies, the percentage of correct classification was 90%.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
P. Menesatti, S. D'Andrea, and P. Negretti "Classification of rabbit meat obtained with industrial and organic breeding by means of spectrocolorimetric technique", Proc. SPIE 6761, Optics for Natural Resources, Agriculture, and Foods II, 67611A (22 October 2007); https://doi.org/10.1117/12.735557
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KEYWORDS
Statistical analysis

Data modeling

Genetics

Statistical modeling

Reflectivity

Spectroscopy

Spectrographs

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