A Simple Low-cost Method for Accurate Canopy Density Evaluation of Citrus

Abstract

The use of canopy density for crop production is a useful tool for evaluating management practices for informed decision-making and predicting crop yields. Traditional methods for analyzing canopy density include expensive equipment that requires advanced software and costly repairs, such as leaf area index analyzers, or equipment that can only be used during optimal weather conditions, such as light meters, that quantify photosynthetically active radiation (PAR), thus making it difficult for researchers to maximize the time needed for field research evaluations and data collection. Digital image analyses using technologically advanced cameras, such as smartphone cameras, have allowed new ways of collecting data without the need to purchase specialized instruments. Using a combination of smartphone cameras and ImageJ software, canopy density can be measured in any weather conditions for a much lower cost than that of traditional equipment. This low-cost, digital image analysis method was compared with traditional PAR measurements for ‘Valencia’ sweet orange [Citrus sinensis (L.) Osb.] trees with varying levels of canopy density. A strong positive correlation between the digital image analysis method and standard canopy density measurement method using PAR measurements (r = 0.79; P<0.0001) was found, indicating that this method can be used as an alternative to the PAR method. The digital image analysis method was also consistent when used during different weather conditions, whereas the PAR method was highly variable when quantifying the canopy when clouds were present in comparison with clear sky conditions. This novel method provides researchers and growers with an easy, flexible, consistent, and low-cost option for analyzing canopy density.