Classification of ripening stages of bananas based on support vector machine

• Published in: International journal of agricultural and biological engineering 2015-12, Vol.8 (6), p.99
• Main Authors: Juncai, Hou, Yaohua, Hu, Lixia, Hou, Kangquan, Guo, Satake, Takaaki
• Format: Article
• Language: English
• Subjects: Algorithms; Bananas; Chlorophyll; Classification; Consumers; Fruits; Support vector machines; Trends
• ISSN: 1934-6344; 1934-6352
• DOI: 10.3965/j.ijabe.20150806.1275

Non-destructive quality detection and automatic grading are important in fruit industry. The traditional way divides bananas into 7-level ripening stages based on color. This study investigated the changes of peel color at three positions of banana fingers, i.e. stalk, middle and tip. A support vector machine method was used to classify the ripening stages by color value L*, a* and b* as input data. The ripening stages were classified by 10-fold cross validation method of support vector machines with radial basis function kernel and linear function kernel. The results showed that the color change of middle position of banana finger adequately reflected the changes in banana ripening stages. a* value continuously increased from ripening stage 1 to ripening stage 7, L* and b* values increased from ripening stage 1 to ripening stage 5, and then decreased from ripening stage 5 to ripening stage 7. It was difficult to recognize the ripening stages using L*, a* and b* values individually. The accuracy of classification using support vector machine based on radial basis function kernel reached 96.5%, which was higher than that for linear function kernel. This research can provide a reference for automatic classification of banana ripening stages.