International Journal of Engineering and Manufacturing (IJEM)
IJEM Vol. 16, No. 5, 8 Oct. 2026
Cover page and Table of Contents: PDF (size: 1195KB)
Grape Leaf Doctor: Severity Assessment of Grape Black Measles via DeepLabV3+ Segmentation and Interval Type-2 Fuzzy Logic
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Author(s)
Index Terms
Grape black measles disease classification, Plant disease severity prediction, Response Surface Methodology, Disease data analysis, Interval Linguistic Type 2 Fuzzy Logic System, DeepLabV3+ semantic segmentation model, Deep Learning
Abstract
Automated diagnosis of Grape Black Measles (GBM) disease has become a pivotal aspect of modern agribusiness due to its efficiency and rapidity. Manual segmentation and diagnosis of GBM are intricate tasks due to time and cost constraints. In this study, we introduce Grape Leaf Doctor, a novel method for the automatic detection and severity analysis of GBM, utilizing the response surface approach and interval type 2 fuzzy logic inference (IT2FL). Firstly, we employ the DeepLabV3+ semantic segmentation model based on ResNet50 to perform pixel-level predictions on images of grape leaves affected by fungal lesions. This model enables the identification of “regions of interest” (ROIs) and the calculation of the percentage of infections (POI). Subsequently, the IT2FL rule-based system is constructed to assess the severity of disease damage based on these features. In the IT2FL system, Gaussian and trapezoidal “membership functions” (MFs) are explored for inputs and outputs to facilitate fuzzy inference and defuzzification. The severity of GBM infection is categorized into four levels: ‘Healthy’, ‘Mild’, ‘Medium’, and ‘Severe’. The experimental results on the IT2FL hold-out test dataset show a general classification accuracy of 98.34%, whereas RSM achieves 90.69%. By merging image processing and statistical modeling, the DeepLabV3+ framework of the IT2FL system can efficiently recognize GBM across varying disease risks.
Cite This Paper
Dipak Kumar Jana, Sourav Mandal, Sudipta Roy, "Grape Leaf Doctor: Severity Assessment of Grape Black Measles via DeepLabV3+ Segmentation and Interval Type-2 Fuzzy Logic", International Journal of Engineering and Manufacturing (IJEM), Vol.16, No.5, pp. 92-105, 2026. DOI:10.5815/ijem.2026.05.05
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