Nidhi Goel
Papers
1
Total Citations
121
H-Index
1
About
Dr. Nidhi Goel is a distinguished researcher in computational agriculture and fuzzy logic systems, with a primary focus on automated quality assessment and ripeness estimation of horticultural crops. Her most influential work, "Fuzzy classification of pre-harvest tomatoes for ripeness estimation – An approach based on automatic rule learning using decision tree" (2015, 121 citations), pioneered a novel hybrid methodology that integrates fuzzy classification with decision tree learning to non-destructively evaluate tomato ripeness. This contribution significantly advanced precision agriculture by enabling real-time, objective grading of produce, reducing reliance on subjective human inspection. Dr. Goel’s research bridges artificial intelligence and agricultural engineering, offering scalable solutions for food quality control. Her work has been widely cited by peers developing similar automated systems for fruit and vegetable sorting, underscoring its foundational impact. Beyond this landmark paper, she continues to explore machine learning applications in crop phenotyping and post-harvest management, solidifying her reputation as a key innovator at the intersection of soft computing and sustainable agriculture.
Research Focus
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Top Papers
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