Prediction of pH and color in pork meat using VIS-NIR Near-infrared Spectroscopy (NIRS)

被引:15
|
作者
Granemann Furtado, Elton Jhones [1 ]
Bridi, Ana Maria [2 ]
Barbin, Douglas Fernandes [3 ]
Pinheiro Barata, Catia Chilanti [1 ]
Peres, Louise Manha [1 ]
Ayub da Costa Barbon, Ana Paula [1 ]
Andreo, Nayara [1 ]
Giangareli, Barbara de Lima [1 ]
Terto, Daniela Kaiser [4 ]
Batista, Joao Paulo [4 ]
机构
[1] Univ Estadual Londrina, Programa Posgrad Ciencia Anim, Campus Univ, Londrina, PR, Brazil
[2] Univ Estadual Londrina, Dept Zootecnia, Programa Posgrad Ciencia Anim, Campus Univ, Londrina, PR, Brazil
[3] Univ Estadual Londrina, Programa Posgrad Ciencia & Tecnol Alimentos, Campus Univ, Londrina, PR, Brazil
[4] Univ Estadual Londrina, Curso Zootecnia, Campus Univ, Londrina, PR, Brazil
来源
FOOD SCIENCE AND TECHNOLOGY | 2019年 / 39卷 / 01期
关键词
carcasses; color analysis; longissimus dorsi; partial least squares regression; pH analysis; CHEMICAL-COMPOSITION; REFLECTANCE SPECTROSCOPY; QUALITY CHARACTERISTICS; SENSORY CHARACTERISTICS; POST-MORTEM; MUSCLE; PROTEIN; WATER; FAT; FEASIBILITY;
D O I
10.1590/fst.27417
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
The potential of near-infrared spectroscopy (NIRS) to predict the physicochemical characteristics of the porcine longissimus dorsi (LD) muscle was evaluated in comparison to the standard methods of pH and color for meat quality analysis compared to the pH results with Colorimeter and pH meter. Spectral information from each sample (n = 77) was obtained as the average of 32 successive scans acquired over a spectral range from 400 - 2498 nm with a 2 - nm gap for calibration and validation models. Partial least squares (PLS) regression was used for each individual model. An R-2 and a residual predictive deviation (RPD) of 0.67/1.7, 0.86/2, and 0.76/1.9 were estimated for color parameters L*, a*, and b* respectively. Final pH had an R-2 of 0.67 and a RPD of 1.6. NIRS showed great potential to predict color parameter a* of porcine LD muscle. Further studies with larger samples should help improve model quality.
引用
收藏
页码:88 / 92
页数:5
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