Optimization of Leaf Area Estimation in a High-Density Apple Orchard Using Hemispherical Photography | WSU Tree Fruit | Washington State University Skip to main content Skip to navigation

Optimization of Leaf Area Estimation in a High-Density Apple Orchard Using Hemispherical Photography Published In HortScience, 53(6):799-804, 2018, by A. Knerl, B. Anthony, S. Serra, S. Musacchi

Abstract: Leaf area is evaluated as leaf area index (LAI), the ratio of leaf to ground area, and is known to be crucial to understanding forests and high-quality fruit production in orchards. Nondestructive tools have been available for decades that pair hemispherical photography with gap fraction theories to understand LAI. Those tools do not allow for rapid assessment in the field, and there is no standardized protocol to acquire accurate estimates yet. This experiment has developed an optimized method with the CID Plant Canopy Imager (CI-110) in a high-density apple orchard. This novel tool for LAI estimation allows image acquisition and processing in real time in the field. LAI assessments of hemispherical images were taken under five light environments, at three imaging heights, processed with two thresholding methods, and were compared with destructive LAI values for accuracy. The difference between estimated and destructive LAI (ΔLAI) was determined for trees on an individual or grouped by a three tree basis. Estimations for triplet groupings were more accurate, and the significantly lower ΔLAI in each treatment occurred for the no-net environment, 10 cm from the ground and processed with the Otsu threshold. When combined as triplet groupings, this method-ology sequence yielded an LAI estimation with a 13% prediction error (ΔLAI = 0.19). The use of the CI-110 with this methodology can give useful, real-time information regarding orchard canopies to address pruning and training decisions for high-quality fruit production.

Link: https://doi.org/10.21273/HORTSCI12969-18

Washington State University