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Food plays a vital role in our daily life. Providing good quality food to consumers is essential. Food quality can be accessed using the Electronic nose. Electronic nose (E-nose) is an instrument for odor analysis. E-nose mimics the human olfaction system. It is widely used in predicting the quality of foodstuffs and detecting the contamination in foods. E-nose can also be used in outdoor monitoring such as air quality monitoring and detect the hazardous odors emitted wastewater treatment plants. Application of Enose is increasing day by day. In this paper, we consolidated the previous works on E-nose. They had applied different machine learning algorithms to construct a model. In most of the works, for the classification of data, they used Support Vector Machine and Linear Discriminant Analysis, which shows higher accuracy when comparing to other algorithms.
Keerthana et al. (Sun,) studied this question.
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