A Non-Destructive Leaf Area Prediction Model and Some Physical Leaf Properties in Apples

Abstract

Leaf area and some physical leaf properties play an important role in the vital events of the plant, such as photosynthesis, respiration, growth, yield, and quality. Therefore, knowing the leaf area and models that estimate the leaf area is crucial in the development of a fruit tree. Determination of leaf area, especially by non-destructive methods, is very important in terms of examining leaf development in different periods. Therefore, a leaf area estimation model and some physical leaf properties were produced using 'Jeromine', 'Fuji Zehn Astec', 'McIntosh', 'Granny Smith Challenger', 'Buckeye Gala', 'Honeycrisp', 'Rosy Glow', 'Super Chief', 'Golden Reinders', 'Ginger Gold' and 'Amasya' apple cultivars. This study was conducted in the Bafra Plain in Northern Anatolia in 2023. Leaf width, length and leaf area were measured to develop the model. The leaf area of the cultivars were measured by PLACOM Digital planimeter, and multiple regression analysis with Microsoft Office XP Excel 2016 program was performed for the cultivars separately. The developed leaf area estimation model in the present study was: LA = [0.887-0.224*(W + L) + 0.786*W*L] (r2 = 0.975). In addition to the model generation procedure, the model was validated using the residual values between predicted and measured leaf areas from new leaf samples collected from different apple trees. R2 values for the relationships between actual and predicted leaf areas of the tested apple cultivars were found to be 0.971. In this study, the brightest colored leaves were obtained from the 'Golden Reinders' cultivar. The highest chlorophyll content was obtained from 'Honeycrisp' and 'Ginger Gold' cultivars.