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Identification of Indian jujube varieties cultivated in Saudi Arabia using
an artificial neural network
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Abstract: This study aimed to develop a method for identifying different cultivars of Indian jujube fruits (Ziziphusmauritiana Lamk.) based on a single Indian jujube fruit color and morphological attributes using an artificialneural network (ANN) classifier. Eleven Indian jujube fruit cultivars were collected during winter ofseason 2020 from a local orchard located at Riyadh region, Saudi Arabia to measure their lengths, majordiameters, and minor diameters. Different morphological descriptors were calculated, including thearithmetic mean diameter, the sphericity percent, and the surface area. Moreover, the color values ofL*, a*, and b* of the skin of fruits were recorded. The ANN classifier was used to identify the appropriateclass of Indian jujube fruit by using a combination of morphological and color descriptors. The proposed
method achieved an overall identification rate of 98.39% and 97.56% in training and testing phases,respectively. In addition to color and morphological features, ANN classifier is a useful tool for identifyingIndian jujube fruit cultivars and circumventing the difficulties met during fruit grading.
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| Publication year |
2021
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| Pages |
5765–5772
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| Organization Name |
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| serial title |
Saudi Journal of Biological Sciences
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| Web Page |
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| Author(s) from ARC |
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| Publication Type |
Journal
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