research-article

Non-invasive Grading System for Banana Tiers using RGB Imaging and Deep Learning

Authors:

Armacheska Rivero Mesa,

John ChiangAuthors Info & Claims

ICCAI '21: Proceedings of the 2021 7th International Conference on Computing and Artificial Intelligence

Pages 113 - 118

https://doi.org/10.1145/3467707.3467723

Published: 24 September 2021 Publication History

Abstract

Food losses transpire at postharvest and processing operations in developing countries, commonly caused by inaccurate manual classification of horticultural crops. The modernization of agricultural facilities and emerging technologies in agriculture has provided solutions for such losses and even increased productivity in a short duration and with higher precision. A non-invasive classification of bananas is presented in this paper, which grades banana tiers into different categories using digital images of bananas applied with deep learning techniques. The main objective of this paper is to develop a tier-based grading system for clustered fruits such as bananas and classify them in terms of quality (export class, middle class, and reject class), maturity (green, turning yellow, yellow, and overripe), and size (small, medium, and large). The classification models for the different grading parameters are developed using transfer learning and a fine-tuned VGG16 Deep CNN architecture. The system was able to automate the assembly line-like process of classifying bananas with a satisfactory overall accuracy using only a minimal number of image samples. The non-invasive technique will also serve as a paradigm for classifying other clustered fruits or horticultural crops.

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Cited By

Mahmood ATiwari ASingh S(2024)C-net: a deep learning-based Jujube grading approachJournal of Food Measurement and Characterization10.1007/s11694-024-02765-718:9(7794-7805)Online publication date: 27-Jul-2024
https://doi.org/10.1007/s11694-024-02765-7
Ghosh I(2024)Artificial Intelligence in Horticultural Crop ImprovementInnovative Methods in Horticultural Crop Improvement10.1007/978-3-031-61081-3_2(25-47)Online publication date: 1-Oct-2024
https://doi.org/10.1007/978-3-031-61081-3_2
Stasenko NShukhratov ISavinov MShadrin DSomov A(2023)Deep Learning in Precision Agriculture: Artificially Generated VNIR Images Segmentation for Early Postharvest Decay Prediction in ApplesEntropy10.3390/e2507098725:7(987)Online publication date: 28-Jun-2023
https://doi.org/10.3390/e25070987
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ICCAI '21: Proceedings of the 2021 7th International Conference on Computing and Artificial Intelligence

April 2021

498 pages

ISBN:9781450389501

DOI:10.1145/3467707

Copyright © 2021 ACM.

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Publication History

Published: 24 September 2021

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ICCAI '21

ICCAI '21: 2021 7th International Conference on Computing and Artificial Intelligence

April 23 - 26, 2021

Tianjin, China

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Cited By

Mahmood ATiwari ASingh S(2024)C-net: a deep learning-based Jujube grading approachJournal of Food Measurement and Characterization10.1007/s11694-024-02765-718:9(7794-7805)Online publication date: 27-Jul-2024
https://doi.org/10.1007/s11694-024-02765-7
Ghosh I(2024)Artificial Intelligence in Horticultural Crop ImprovementInnovative Methods in Horticultural Crop Improvement10.1007/978-3-031-61081-3_2(25-47)Online publication date: 1-Oct-2024
https://doi.org/10.1007/978-3-031-61081-3_2
Stasenko NShukhratov ISavinov MShadrin DSomov A(2023)Deep Learning in Precision Agriculture: Artificially Generated VNIR Images Segmentation for Early Postharvest Decay Prediction in ApplesEntropy10.3390/e2507098725:7(987)Online publication date: 28-Jun-2023
https://doi.org/10.3390/e25070987
Reis LSouza Ida Silva JCarvalho CJúnior WBessa AAmoedo DUrtiga E(2023)Wireless IoT System for Detection of Fruit Maturation by Color and Ethylene Gas2023 Symposium on Internet of Things (SIoT)10.1109/SIoT60039.2023.10390149(1-5)Online publication date: 25-Oct-2023
https://doi.org/10.1109/SIoT60039.2023.10390149
N AR V(2023)Banana Ripeness Classification with Deep CNN on NVIDIA Jetson Xavier AGX2023 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)10.1109/I-SMAC58438.2023.10290326(663-668)Online publication date: 11-Oct-2023
https://doi.org/10.1109/I-SMAC58438.2023.10290326
Aherwadi NMittal USingla JJhanjhi NYassine AHossain M(2022)Prediction of Fruit Maturity, Quality, and Its Life Using Deep Learning AlgorithmsElectronics10.3390/electronics1124410011:24(4100)Online publication date: 9-Dec-2022
https://doi.org/10.3390/electronics11244100
S RGanguli SSelvan PNayak MChaudhury SEspina ROfori I(2022)Deep Learning Based Dual Channel Banana Grading System Using Convolution Neural NetworkJournal of Food Quality10.1155/2022/60502842022(1-9)Online publication date: 23-May-2022
https://doi.org/10.1155/2022/6050284

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