A Simple Low-Cost Method For Accurate Canopy Density Evaluation Of Citrus

Citrus cultivation presents numerous challenges, and one of the key factors influencing crop health and yield is canopy density. Canopy density is a valuable tool for evaluating crop management and predicting yields, but traditional methods are often costly and dependent on specific conditions. Conventional equipment, such as leaf area index analyzers and light meters, can be expensive to maintain and are limited to optimal weather conditions.

In contrast, digital image analysis using smartphone cameras and ImageJ software offers a more affordable and versatile alternative. This method allows for canopy density measurement under any weather conditions and has been shown to correlate strongly with traditional PAR (photosynthetically active radiation) measurements (r = 0.79; P<0.0001) in ‘Valencia’ sweet orange trees. It also maintains consistency across various weather conditions, unlike PAR measurements which can vary with cloud cover. This innovative approach provides a cost-effective, flexible, and reliable option for researchers and growers.

Key Features of the New Method:

• Affordability: Designed with budget constraints in mind, this method requires minimal investment while delivering precise results.
• Simplicity: Easy to implement with straightforward procedures, allowing farmers to quickly adopt and integrate the technology into their existing practices.
• Accuracy: Utilizes advanced algorithms and data analysis to provide reliable measurements of canopy density, enabling better-informed decisions regarding irrigation, fertilization, and overall orchard management.
• Time Efficiency: Reduces the time and labor required for canopy assessment, freeing up valuable resources for other essential tasks.

The digital image analysis method involving the analysis of canopy density has been shown to be accurate, inexpensive, easy, and more accessible than traditional methods. Furthermore, it involves an inexpensive tool (with some learning of Image J software) that citrus growers can use to evaluate grove management practices and yield prediction. This method can also be used by researchers to quantitatively categorize HLB-affected trees according to their health status to achieve optimum field evaluations. Because of the ease and adaptability of this method, researchers can also obtain canopy density measurements quickly and accurately during any time of year.. It is expected to be particularly beneficial for small to mid-sized growers who may not have the resources to invest in more expensive technology.

The full article can be found on on the ASHS HortScience electronic journal website at: https://doi.org/10.21273/HORTSCI17112-23