The current Chinese cooking nutritional and scientific degree is not high. Chinese cooking technology has made it difficult to meet people’s health needs. This paper explores the path of nutritional scientificization in digital cooking. The FCM algorithm based on MapReduce has been found to have a good clustering effect and execution efficiency. Based on big data processing for fuzzy clustering application research, the samples are preprocessed using big data processing techniques to determine the functions in the sample descriptions. The data analysis is completed using Mapreduce-based parallelized FCM, and the rules for optimizing the objective function are given. The method proposed in this paper can efficiently and accurately complete the data analysis, as evidenced by examples. Residents can choose the cooking technique that best suits their nutritional needs by reducing the ABT antioxidant capacity and FRAP antioxidant capacity of coriander by 42.67% and 44.21% by boiling and high pressure. Big data analysis-based cooking techniques outperformed traditional cooking techniques in all dimensions, ensuring a balance between food flavor and health and wellness.