Nilgiris Tea Yield Index (NTYI) – A Fuzzy Logic Based Model For intelligent Tea Industry Transformation

Author(s)	Dr. A Selvi, Prof. D Kousalya
Country	India
Abstract	Tea cultivation in the Nilgiris region faces increasing challenges due to irregular rainfall, steep terrain, soil variability, and fluctuating market demand. Sustainable yield prediction is therefore essential for resource efficient plantation management. However, selecting an appropriate estimation model is complex because tea yield depends on multiple uncertain factors such as rainfall distribution, slope conditions, leaf quality, soil fertility, and pest resistance. To address this, the Nilgiris Tea Yield Index (NTYI) is proposed as a fuzzy logic–based decision support framework. The model integrates Rainfall–Slope hybrid membership functions, a bell shaped Leaf Quality function, and a Weighted Centroid defuzzification scheme to capture uncertainty in tea yield estimation. Five cultivation scenarios—normal rainfall, deficit rainfall, excess rainfall, mixed slope conditions, and variable leaf quality—are considered to evaluate the robustness of the model.
Keywords	: Nilgiris tea, Fuzzy logic, Yield prediction, Rainfall–slope hybrid, Leaf quality, Sustainable agriculture, Artificial intelligence.
Field	Mathematics > Logic
Published In	Volume 8, Issue 5, September-October 2026
Published On	2026-09-17
DOI	https://doi.org/10.36948/ijfmr.2026.v08i05.87834

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