Estimation of Leaf Area and Leaf Area Density for Design Optimization of a Recycling Tunnel Sprayer

Abstract

A tunnel sprayer system is considered as one of the most economical and reasonable sprayers for protection of an orchard crop. The performance of the spraying system (spray deposition %, recycling %, and deposition % on abaxial and adaxial surface) could be improved through appropriate design. However, the morphological parameter of the orchard significantly influenced accuracy and effectiveness of the same spraying system. Therefore, this study was conducted to determine the morphological parameters of guava tree. Three techniques were used for estimation of leaf area: Grid Count Method (GCM), Image Processing Technique (IPT) and Regression Model (RM). The grid count method was used as a reference for area estimation. R² was 0.98 and 0.94 for IP & RM compared to GCM, respectively. In the regression model, only length and width of the guava leaf were found statistically significant (P < 0.01). It was concluded that the image processing technique provided better results for leaf area estimation with mean error ± standard deviation (−0.23 ± 3.41) than regression developed model. This study ensured the accuracy of image processing technique for the leaf area estimation and allows the researchers to deal with voluminous of leafs with accurate and quick response. Leaf area density (LAD) was recorded to be in range of 0.07–2.73 m²/m³. These morphological parameters could be used for design optimization of recycling tunnel sprayer in future, which would help to improve the performance of tunnel system.