Characterisation of Pineapple Cultivars under Different Storage Conditions Using Infrared Thermal Imaging Coupled with Machine Learning Algorithms
نویسندگان
چکیده
The non-invasive ability of infrared thermal imaging has gained interest in various food classification and recognition tasks. In this work, was used to distinguish different pineapple cultivars, i.e., MD2, Morris, Josapine, which were subjected storage temperatures, 5, 10, 25 °C a relative humidity 85% 90%. A total 14 features from the images obtained determine variation terms image parameters among cultivars. Principal component analysis applied for feature reduction order prevent any effect significant difference between selected features. Several types machine learning algorithms compared, including linear discriminant analysis, quadratic support vector machine, k-nearest neighbour, decision tree, naïve Bayes, obtain best performance results showed that achieved combination optimal with highest rate 100%. coupled approaches can be potentially could enhance grading sorting processes fruit.
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ژورنال
عنوان ژورنال: Agriculture
سال: 2022
ISSN: ['2077-0472']
DOI: https://doi.org/10.3390/agriculture12071013