Estimating tomato plant leaf area in greenhouse environment using multiple RGB-D cameras

The estimation of leaf area is an important measurement in understanding the growth, development, and productivity of tomato plants. In this study, we focus on the leaf area of each tomato plant in a greenhouse environment and propose a method for estimating its leaf area using multiple RGB-D cameras, which we call D<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> method. In the D<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> method, we use instance segmentation and multiple RGB-D cameras to estimate the leaf area of each tomato plant in the greenhouse environment. The performance of the D<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> method is assessed in an experiment with 30 "Momotaro Peace" tomato plants. This experiment highlights that the D<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> method has a mean absolute percentage error on a test set of 10.1%, which has a better performance than the conventional other methods.