This dataset, “Food Freshness Electronic Nose Dataset”, contains measurements collected using an electronic nose equipped with MQ sensors (MQ2, MQ3, MQ4, MQ5, MQ6, MQ7, MQ8, MQ9, MQ135). Data were recorded at room temperature (mean ≈ 23°C) over 3-minute sampling intervals. Each sample was taken at 24-hour intervals, capturing variations in food freshness over time. The dataset includes multiple sample combinations and is suitable for research in food quality monitoring, source separation, sensor analysis, and related machine learning applications. Key features: Multi-sensor electronic nose measurements Controlled room-temperature recordings Time-series data with 24-hour sampling intervals Designed for research in food freshness detection, sensor analysis, and source separation