Leaf area is an important parameter in plant physiology studies because it is directly related to photosynthetic activity and plant productivity. However, conventional methods for measuring leaf area still face limitations in terms of cost, equipment, and efficiency. This study aimed to analyze the leaf constant values of starfruit and sapodilla plants based on digital image processing as a foundation for applying the Montgomery method. A total of 40 leaf samples from each species were analyzed using digital imagery via ImageJ software to obtain the measured leaf area, which was then compared to the predicted leaf area using the Montgomery equation. The resulting leaf constants were 0.520 for starfruit and 0.642 for sapodilla, with a stable and consistent value distribution. Prediction accuracy evaluation using R², RMSE, NRMSE, NSE, and Willmott’s index showed low error rates and very high model efficiency. These findings suggest that the obtained leaf constants are reliable for rapid and non-destructive estimation of leaf area. This method has the potential for broader application in supporting precision agriculture and efficient monitoring of tropical plant growth.
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