Mobile-Based Smart Advisory System for Mango Disease Alerts after Harvest

DOI

10.2991/978-94-6239-678-4_40How to use a DOI?

Keywords

Convolutional Neural Networks; Raspberry Pi; IoT; Diseases

Abstract

The mango industry suffers heavily from post-harvest losses, especially in tropical agricultural economies. Approximately one-third of the total amount of mangoes that are produced will be lost through the many post-harvest losses associated with fungi that infect the mango crops, as well as other crop types such as grains and seeds. Small and medium-sized producers of mangoes are exposed to many of these pathogens, and many of the efforts put forth by the producers can be completely wiped away if an appropriate preventative action is not taken. Using modern grain and seed production methods, along with new advances in warehouse design, producers of grain and seed do not have any quick and effective means for diagnosing the crop diseases that they experience; therefore, they lose revenue and waste resources. Recently, it has become possible to apply image processing techniques based upon Convolutional Neural Networks (CNNs) to learn to distinguish between the various types of mango fruits based upon the visible symptoms of fungal infection on a mango fruit (for example, Aspergillus niger, stem-end rot and anthracnose). The highest level of accuracy (91%) for a classification system was achieved through the CNN, and the CNN has proven itself to be the most effective in accurately identifying disease.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Baig Ishrat Shamsher
AU  - P. D. Deshmukh
PY  - 2026
DA  - 2026/05/28
TI  - Mobile-Based Smart Advisory System for Mango Disease Alerts after Harvest
BT  - Proceedings of the 2nd International Conference on Recent Advancement and Modernization in Sustainable Intelligent Technologies & Applications (RAMSITA-2026)
PB  - Atlantis Press
SP  - 500
EP  - 514
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-678-4_40
DO  - 10.2991/978-94-6239-678-4_40
ID  - Shamsher2026
ER  -