In this experiment, we selected pepper strips, camel lin, large cucumber strips, belly meat, tendon meat, tenderloin, milong, upper brain, rump, outer spine, breast meat, and small cucumber from the carcass of Alashan Bactrian camel aged 3-5 years old. Thirteen meat samples such as strips and eye meats were scanned by a near-infrared spectrometer under the wavenumber condition of 4 000-10 000 cm-1, and the moisture, protein and fat content of the camel meat samples were also been measured. First, savitzky-golay (S-G), derivative (Der), standard normal variate (SNV), and multiplication scatter correction (MSC) methods were selected for comparation of the spectral preprocessing. Then, partial least square-discrimination analysis (PLS-DA) was used to establish water, protein, and fat content models. The results showed that the best pretreatment method for the moisture content model of different parts of camel meat samples was MSC. The determination coefficients Rc2, root mean square error of calibration (RMSEC), Rp2, and root mean square error of prediction (RMSEP) of the model were 0.745 9, 0.008 5, 0.774 1, 0.013 4, respectively. The best pretreatment for the protein content model was SNV, and the determination coefficients Rc2, RMSEC, Rp2, and RMSEP of the model were 0.660 2, 0.287 9, 0.672 5, and 0.276 0, respectively. The best preprocessing method of the fat content model was S-G, and the determination coefficients of the model Rc2, RMSEC Rp2, and RMSEP were respectively 0.988 5, 0.086 3, 0.996 3, 0.056 7. The results showed that near-infrared spectroscopy technology was the best way to predict the fat content of different parts of camel meat, followed by the prediction of moisture content, and the prediction of protein content was the worst.
WU Dandan
,
LIU Yueru
,
HE Jing
,
MING Liang
,
JIRIMUTU
. The detection of nutrient components in different parts of camel meat and the establishment of near infrared rapid prediction model[J]. Food and Fermentation Industries, 2022
, 48(16)
: 264
-269
.
DOI: 10.13995/j.cnki.11-1802/ts.029454
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