This study applied near-infrared spectroscopy combined with chemometric methods to rapidly predict the nutrient content of Minqin lamb (a geographical indication product), aiming to provide a theoretical basis for the quantitative detection of the nutrient content of Minqin lamb and technical support for the nutritional properties and product value of Minqin lamb. A total of 269 meat samples were collected from the longest back muscle, foreleg meat, and hind leg meat of 90 sheep in Minqin, and near-infrared spectra were collected. The calibration models of lamb muscle fat, protein, and fatty acid content were established by using various pretreatment methods, including principal component regression (PCR), partial least squares (PLS), and modified partial least squares (MPLS). Except that the best modeling method of stearic acid was partial least squares, the best modeling method of other indicator models was improved partial least squares. Among them, the RSQ of fat, protein, and monounsaturated fatty acid models were higher than 0.9, which were 0.936, 0.916, and 0.911, respectively. The RSQ values of palmitic, oleic, linoleic, saturated, and polyunsaturated fatty acid models were greater than 0.8 and less than 0.9, which were 0.806, 0.843, 0.883, 0.852, and 0.895, respectively, while the RSQ values of myristic acid and stearic acid models were less than 0.7, which were 0.323 and 0.561, respectively. The application of the near-infrared technique combined with chemometric methods can effectively predict the nutritional composition of lamb muscle.
LIANG Jing
,
ZHAO Xiangmin
,
LI Lulu
,
KANG Jing
,
TANG Defu
,
LIU Jia
,
GUO Yiwen
,
YANG Tao
,
HAO Shengyan
,
DOU Xiaoli
,
SONG Shuzhen
. Model construction for nutrient content detection of Minqin lamb based on near-infrared spectroscopy[J]. Food and Fermentation Industries, 2023
, 49(14)
: 272
-279
.
DOI: 10.13995/j.cnki.11-1802/ts.034102
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