Rapid Determination of Goose Tenderness Using Near Infrared Spectroscopy

doi:10.7506/spkx1002-6630-201408052

Abstract

Abstract:

Objective: To propose a rapid method for the identification of goose tenderness by near infrared spectroscopy
(NIR) technology. Methods: NIR spectra (950–1 650 nm) of goose meat were collected. After multiple correction and
pretreatment of the spectra, mathematical models for the quantitative prediction of goose tenderness were established by
principal component regression (PCR) and partial least squares regression (PLSR). Results: The PLSR model based on
five-point moving window smoothing was the best predictive model with a determination coefficient (R2) of 0.908 0 and
a root mean square error of cross validation (RMSECV) of 113.618 6. No significant difference (P ＞ 0.05) was found
between the predicted and measured values for 20 samples in the prediction set, with a correlation coefficient of 0.971 1,
and the predicted values showed an average bias of 21.673 g. Conclusion: NIR can be used in the evaluation of goose meat
tenderness as a fast nondestructive detection method.

Key words: near infrared spectroscopy (NIR), goose meat, tenderness , Warner-Bratzler shear force (WBSF)

CLC Number:

TS251.7

YANG Yong, YANG Qing-yu, LIN Wei, WANG Cun-tang, ZHANG Duo, DONG Yuan, SONG Chun-li, PEI Shi-chun*, LI Mao-mao, XU Hong-li. Rapid Determination of Goose Tenderness Using Near Infrared Spectroscopy[J]. FOOD SCIENCE, doi: 10.7506/spkx1002-6630-201408052.

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Rapid Determination of Goose Tenderness Using Near Infrared Spectroscopy

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