领学术科研之先，创食品科技之新
—— 中国食品杂志社
In the field of food flavor, there exists a substantial amount of structured and unstructured data originating from flavoromics, databases, and social media. To effectively extract valuable information from these diverse data sources and promote rational application, extensive data mining efforts have been undertaken. This review provides a systematic overview of data mining in the context of food flavor and summarizes various multivariate data processing strategies. This review examines a wide array of current research in flavoromics and discusses pre-processing methods designed to address challenges such as small dataset sizes and complex manual data preparation. Furthermore, this review summarizes innovative approaches based on artificial intelligence and large language models, elucidating their prospective applications in flavor molecule prediction and recipe development. Lastly, we discuss the challenges and opportunities of applying data mining to flavor research.
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