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Rapid detection of raw milk nutritional components by milk composition analyzer
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Yun-Fang WU1, 2, 3, 4, Hong-Hui WANG1, 2, 3, 4, Jian-Ping XU3, Miao-Miao HAO1, 2, 3, 4, Chun-Ling SUN1, 2, 3, 4, Yong-Ling SUN1, 2, 3, 4, Ran MENG1, 2, 3, 4, Chun-Dong LI1, 2, 3, 4, Liang GUO1, 2, 3, 4, *
Journal of Food Safety & Quality | 2025, 16(14) : 204 - 212
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Journal of Food Safety & Quality | 2025, 16(14): 204-212
Food Analysis and Detection
Rapid detection of raw milk nutritional components by milk composition analyzer
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Yun-Fang WU1, 2, 3, 4, Hong-Hui WANG1, 2, 3, 4, Jian-Ping XU3, Miao-Miao HAO1, 2, 3, 4, Chun-Ling SUN1, 2, 3, 4, Yong-Ling SUN1, 2, 3, 4, Ran MENG1, 2, 3, 4, Chun-Dong LI1, 2, 3, 4, Liang GUO1, 2, 3, 4, *
Affiliations
  • 1 Department of Grassland Ecology and Animal Husbandry & Veterinary Medicine, Xilingol Vocational College , Xilinhot 026000, China
  • 2 Xilingol Institute of Bioengineering , Xilinhot 026000, China
  • 3 Xilingol Food Science and Testing Experimental Center (Xilingol Agricultural and Animal Products Testing Center) , Xilinhot 026000, China
  • 4 Inner Mongolia Autonomous Region Meat and Milk Nutrition and Safety Engineering Research Center , Xilinhot 026000, China
Published: 2025-07-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250306006
Outline
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Objective To establish a method for rapid detection of nutritional components in raw milk by milk composition analyzer. Methods This study used commercial raw milk as the test sample, and based on Fourier transform infrared spectroscopy (FTIR), it constructed a rapid detection method for 9 parameters such moisture, protein, fat, lactose, ash, non-fat milk solids, total dry matter, relative density and freezing point in raw milk. The precision and accuracy of the rapid detection method were evaluated by comparing it with the national standard detection results. Results The determination results of the milk composition analyzer were as follows: Moisture 86.00%-89.09%, protein 2.52%-4.51%, fat 2.65%-5.39%, lactose 3.81%-5.40%, ash 0.56%-0.80%, and non-fat milk solids 6.94%-9.81%. F-test and T-test were performed on 9 parameters including fat, lactose and non-fat milk solids. The maximum F-value was 9.00, less than 9.55, indicating no significant difference in precision for the 9 parameters. The maximum T-value was 20.82, less than 22.327, confirming no significant difference in accuracy for the 9 parameters. Both the milk composition analyzer method and the national standard method could accurately determine milk nutritional indicators. The results showed that the precision and accuracy of the established rapid detection method had no significant differences from those of the national standard method. Conclusion The rapid detection method for nutrient components in raw milk constructed in this study can be used for high-throughput and low-cost rapid screening of nutrient components in raw milk. National standard methods should be used as the benchmark for high-precision scenarios, supervision and admission, while daily monitoring should primarily rely on rapid detection results from milk composition analyzers.

raw milk  /  rapid detection  /  F test  /  T test  /  Fourier infrared spectroscopy technology
Yun-Fang WU, Hong-Hui WANG, Jian-Ping XU, Miao-Miao HAO, Chun-Ling SUN, Yong-Ling SUN, Ran MENG, Chun-Dong LI, Liang GUO. Rapid detection of raw milk nutritional components by milk composition analyzer[J]. Journal of Food Safety & Quality, 2025 , 16 (14) : 204 -212 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250306006
Year 2025 volume 16 Issue 14
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250306006
  • Receive Date:2025-03-06
  • Online Date:2026-01-07
  • Published:2025-07-25
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  • Received:2025-03-06
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Affiliations
    1 Department of Grassland Ecology and Animal Husbandry & Veterinary Medicine, Xilingol Vocational College , Xilinhot 026000, China
    2 Xilingol Institute of Bioengineering , Xilinhot 026000, China
    3 Xilingol Food Science and Testing Experimental Center (Xilingol Agricultural and Animal Products Testing Center) , Xilinhot 026000, China
    4 Inner Mongolia Autonomous Region Meat and Milk Nutrition and Safety Engineering Research Center , Xilinhot 026000, 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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