MDPI and ACS Style
Chu, C.; Wang, H.; Luo, X.; Wen, P.; Nan, L.; Du, C.; Fan, Y.; Gao, D.; Wang, D.; Yang, Z.;
et al. Possible Alternatives: Identifying and Quantifying Adulteration in Buffalo, Goat, and Camel Milk Using Mid-Infrared Spectroscopy Combined with Modern Statistical Machine Learning Methods. Foods 2023, 12, 3856.
https://doi.org/10.3390/foods12203856
AMA Style
Chu C, Wang H, Luo X, Wen P, Nan L, Du C, Fan Y, Gao D, Wang D, Yang Z,
et al. Possible Alternatives: Identifying and Quantifying Adulteration in Buffalo, Goat, and Camel Milk Using Mid-Infrared Spectroscopy Combined with Modern Statistical Machine Learning Methods. Foods. 2023; 12(20):3856.
https://doi.org/10.3390/foods12203856
Chicago/Turabian Style
Chu, Chu, Haitong Wang, Xuelu Luo, Peipei Wen, Liangkang Nan, Chao Du, Yikai Fan, Dengying Gao, Dongwei Wang, Zhuo Yang,
and et al. 2023. "Possible Alternatives: Identifying and Quantifying Adulteration in Buffalo, Goat, and Camel Milk Using Mid-Infrared Spectroscopy Combined with Modern Statistical Machine Learning Methods" Foods 12, no. 20: 3856.
https://doi.org/10.3390/foods12203856