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@article{161738,
        author = {Prof. Swati. B. Ghawate and Shrihari Sharad Shinde and Jayesh Ravindra Banda and Nisarg Sunil Wani and Aditya Dinesh Nimse},
        title = {Milk quality prediction and yogurt fermentation analysis using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {6},
        pages = {31-36},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=161738},
        abstract = {During the development of innovative products, consumer preferences are the essential factors for yogurt producers to improve their market share. A high-performance prediction method will be beneficial to understanding the intrinsic relevance between preferences and sensory attributes. In this study, a novel deep learning method is proposed that uses an autoencoder to extract product features from the sensory attributes scored by experts, and the sensory features bought are regressed on consumer preferences with support vector machine analysis. Ensuring Milk quality is crucial for producing high-quality dairy products, such as yogurt. This study aims to develop a comprehensive approach for predicting Milk quality and analyzing yogurt fermentation. The proposed method combines machine learning techniques for Milk quality prediction and advanced bioprocess analysis for yogurt fermentation.},
        keywords = {yogurt; Model-train; consumer preference; autoencoder; support vector Machine.},
        month = {},
        }