An efficient tea quality classification algorithm based on near infrared spectroscopy and random Forest.

MLA

Chen, Guikun, et al. “An Efficient Tea Quality Classification Algorithm Based on near Infrared Spectroscopy and Random Forest.” Journal of Food Process Engineering, vol. 44, no. 1, Jan. 2021, pp. 1–9. EBSCOhost, https://doi.org/10.1111/jfpe.13604.

APA

Chen, G., Zhang, X., Wu, Z., Su, J., & Cai, G. (2021). An efficient tea quality classification algorithm based on near infrared spectroscopy and random Forest. Journal of Food Process Engineering, 44(1), 1–9. https://doi.org/10.1111/jfpe.13604

Chicago

Chen, Guikun, Xiangchen Zhang, Zebiao Wu, Jinhe Su, and Guorong Cai. 2021. “An Efficient Tea Quality Classification Algorithm Based on near Infrared Spectroscopy and Random Forest.” Journal of Food Process Engineering 44 (1): 1–9. doi:10.1111/jfpe.13604.