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Rapid identification of local variety lamb in Henan Province by near infrared spectroscopy
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Gai-Ying LI, Pin LI, Ying-Jie HUANG, Ru-Yi LI, Teng-Yun GAO*
Journal of Food Safety & Quality | 2025, 16(14) : 89 - 96
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Journal of Food Safety & Quality | 2025, 16(14): 89-96
Special Topic: Non-destructive Detection Technology in Food
Rapid identification of local variety lamb in Henan Province by near infrared spectroscopy
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Gai-Ying LI, Pin LI, Ying-Jie HUANG, Ru-Yi LI, Teng-Yun GAO*
Affiliations
  • College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
Published: 2025-07-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250406001
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Objective To establish a qualitative identification model and rapid identification method of local mutton in Henan province by using near infrared spectroscopy and fisher method. Methods A total of 181 mutton samples were selected from 5 local sheep breeds and 1 Huyang breed in Henan Province, and dried powder samples were prepared. Spectral scanning was performed in the wavelength range of 1400-2500 nm, and discrimination models were established through different pretreatment. Results The results showed that the spectral patterns of different breeds of mutton showed the same trend, and the original spectra could be used to identify sheep and goats with an accuracy of 94.0% and 85.0%, respectively. After spectrum processing by smoothing, first-order derivation, multiplicative scatter correction (MSC) and other different methods, the discrimination accuracy was improved, among which the combination of first-order derivation+MSC had the best effect, the discrimination accuracy of 1400-2500 nm wavelength was 100.0%, and the cross-validation rate was 92.8%. When the model was used to identify 6 varieties of mutton, the accuracy of calibration set reached 100.0%, the cross-validation rate was above 87.5%, and the prediction set of 4 varieties reached 100.0%. After wavelength segmentation, the prediction accuracy for the range of 1400-1620 nm was the best, but the accuracy of individual identification decreased; For different discrimination methods, the identification accuracy of sophora goat was all above 95.0%. Conclusion In summary, near infrared spectroscopy technology in the long-wave range of 1400-2500 nm could accurately identify the variety of mutton, of which the first derivative+MSC preconditioning was the best. For the different varieties, the accuracy of sophora goats was the highest.

near infrared reflectance spectroscopy  /  local breeds of Henan Province  /  mutton  /  qualitative identification
Gai-Ying LI, Pin LI, Ying-Jie HUANG, Ru-Yi LI, Teng-Yun GAO. Rapid identification of local variety lamb in Henan Province by near infrared spectroscopy[J]. Journal of Food Safety & Quality, 2025 , 16 (14) : 89 -96 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250406001
Year 2025 volume 16 Issue 14
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250406001
  • Receive Date:2025-04-06
  • Online Date:2026-01-07
  • Published:2025-07-25
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  • Received:2025-04-06
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    College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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