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Identifying Issues and Proposing Solutions to Improve Sir Lankan Tea Cultivation
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 40 |
| Year of Publication: 2022 |
| Authors: Heshani Weerasinghe, Isuri Tissera, Kithmi Welivitigoda, Amandi Maheshavi |
10.5120/ijca2022922502
|
Heshani Weerasinghe, Isuri Tissera, Kithmi Welivitigoda, Amandi Maheshavi . Identifying Issues and Proposing Solutions to Improve Sir Lankan Tea Cultivation. International Journal of Computer Applications. 184, 40 ( Dec 2022), 14-19. DOI=10.5120/ijca2022922502
Abstract
Tea production is one of the most significant parts of Sri Lanka's economy. Sri Lankan tea holds a unique position in the global market. Traditional and non-standardized approaches affect tea cultivation manually monitoring tea leaf diseases is time-consuming. This study aims to develop a mobile application that uses image processing and machine learning to diagnose tea leaf diseases based on visual indications and provide treatment recommendations. With the advancements of technology, this farming process can be performed with the deep learning model. This research applies Convolutional Neural Networks (CNN) to Identify the tea leaves disease spread with an accuracy of 99%, Pest disease Identification 90 % and tea leaves classification 96% respectively. This system predicts the yield of tea leaves cultivation with an accuracy of 100%. This developed system which aids tea cultivation and production industry is connected through the mobile application.
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