Optimize Banana Production through Innovative Growing System

Authors

  • T.P.Wijewardena Department of Information Technology, Sri Lanka Institute of Information Technology, Malabe, SRI LANKA
  • K.A.D.C. Kaluarachchi Department of Information Technology, Sri Lanka Institute of Information Technology, Malabe, SRI LANKA
  • V.S.V. Vitharana Department of Information Technology, Sri Lanka Institute of Information Technology, Malabe, SRI LANKA
  • W.M.S.D. Wijayasundara Department of Information Technology, Sri Lanka Institute of Information Technology, Malabe, SRI LANKA
  • Udara Srimath S. Samaratunge Arachchillage Department of Computer Science and Software Engineering, Sri Lanka Institute of Information Technology, Malabe, SRI LANKA
  • Thilini Jayalath Department of Information Technology, Sri Lanka Institute of Information Technology, Malabe, SRI LANKA

DOI:

https://doi.org/10.31033/ijemr.13.4.21

Keywords:

Banana Cultivation, Convolutional Neural Networks, Leaf Disease Detection, Optimal Cultivation Practices, Product Differentiation

Abstract

Optimizing banana production through innovative systems is essential for sustainable cultivation. This research primarily focuses on banana variety identification using images and Convolutional Neural Networks (CNNs), detection of leaf diseases in banana trees through a machine learning approach, analysis and recommendation of optimal cultivation practices derived from interactions with farmers and external supervisors, and the generation of unique product ideas using differentiation strategies based on market research, consumer preferences, and insights from industry experts. Collectively, this study aims to revolutionize banana cultivation and marketing by amalgamating traditional farming insights with modern technological tools.

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Published

2023-08-31

How to Cite

T.P.Wijewardena, K.A.D.C. Kaluarachchi, V.S.V. Vitharana, W.M.S.D. Wijayasundara, Udara Srimath S. Samaratunge Arachchillage, & Thilini Jayalath. (2023). Optimize Banana Production through Innovative Growing System. International Journal of Engineering and Management Research, 13(4), 164–170. https://doi.org/10.31033/ijemr.13.4.21