Abstract
The shelf life of bakery products highly depends on the environment and it may get spoiled earlier than its expiry which results in food-borne diseases and may affect human health or may get wasted beforehand. The traditional spoilage detection methods are time-consuming and destructive in nature due to the time taken to get microbiological results. To the best of the author’s knowledge, this work presents a novel method to automatically predict the microbial spoilage and detect its spatial location in baked items using Hyperspectral Imaging (HSI) range from $395-1000\,\,nm$ . A spectral preserve fusion technique has been proposed to spatially enhance the HSI images while preserving the spectral information. Furthermore, to automatically detect the spoilage, Principal Component Analysis (PCA) followed by K-means and SVM has been used. The proposed approach can detect the spoilage almost 24 hours before it started appearing or visible to a naked eye with 98.13% accuracy on test data. Furthermore, the trained model has been validated through external dataset and detected the spoilage almost a day before it started appearing visually.
Highlights
Bakery products have been an integral part of the majority of the world population’s daily routine [1]
Cakes tend to vary in size with the passage of days [46] and the samples acquired for this study changed size in a very minute range with every passing day due to the variations in moisture content
SPOILAGE DETECTION AND MODEL TRAINING The spoiled data has been detected in acquired samples by analyzing the differenced image which were calculated by subtracting every sample (Sample 2 to 16) from sample 1 to obtain the pixels that have got changed over time
Summary
Bakery products have been an integral part of the majority of the world population’s daily routine [1]. While on the other hand there are some problems reported regarding baked food quality and shelf-life like food-borne diseases [2]. The variations in the estimated shelf-life of bakery products may result in two ways; 1) Moderate Environment: The growth of bacterial microorganisms slow-down in a moderate environment, neither too humid nor dry, which results in. Every product has a pre-defined shelf-life but if it ends before the actual spoilage occurs, the product still got wasted only because it has reached its expiry date. 2) Extreme Environment: Extreme humid or drier environment results in affecting the moisture content of the product which may lead to the early spoilage [5]. It has been estimated that 1 out of 10 (600 million per year) humans suffer and around 420, 000 died due to food-borne diseases [6]. Early detection of food spoilage is of utmost importance to limit the aforementioned concerns [7]
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