Repository logo
 
Loading...
Thumbnail Image
Publication

An approach to predict chemical composition of goat Longissimus thoracis et lumborum muscle by Near Infrared Reflectance spectroscopy

Use this identifier to reference this record.
Name:Description:Size:Format: 
277.pdf646.54 KBAdobe PDF Download

Advisor(s)

Abstract(s)

The ability of near infrared reflectance spectroscopy (NIRS) to estimate the protein, moisture, connective tissue and ash content in the Longissimus thoracis et lumborum (LTL) muscle of goat was studied. Samples (n=240) of the LTL muscle were taken from the 8th to 13th rib cut of goat carcasses. Samples were scanned in a FT-NIR Master™ N500 (BÜCHI) over a NIR spectral range of 4000-10,000cm < sup > -1 < /sup > with a resolution of 4cm < sup > -1 < /sup > . It was collected 3 spectra per sample and subsequently, chemical analyses were performed at the Carcass and Meat Quality Laboratory of ESA-IPB. Using NirCal 1.5 it was developed a PLS regression model assaying, first and second derivatives as math treatment and multiplicative scatter correction for minimizing scattering effect on the spectra database recorded (n=240). The best calibrations' models show relatively good predictability for protein (standard error of prediction SEP=0.43; coefficient of determination R < sup > 2 < /sup > =0.91), moisture (SEP=0.48; R < sup > 2 < /sup > =0.92). Calibrations' models obtained are important as a first attempt to predict the chemical composition of goat meat by NIRS. More experimental data are needed to improve the accuracy of these calibrations.

Description

Keywords

Chemical composition Goat meat NIRS Prediction

Citation

Teixeira, Alfredo; Oliveira, António; Paulos, Katia; Leite, Ana; Marcia, Anabela; Amorim, André; Pereira, Etelvina; Silva, Severiano; Rodrigues, Sandra (2015). An approach to predict chemical composition of goat Longissimus thoracis et lumborum muscle by Near Infrared Reflectance spectroscopy. Small Ruminant Research. ISSN 0921-4488. 126, p. 40-43

Research Projects

Organizational Units

Journal Issue