Advancements in Detecting Spot Fungal Diseases on Date Palm Leaves: Development and Validation of Chlorophyll-Based Detection Models

Abstract

The importance of chlorophyll content as an early indicator for the detection and prediction of leaf spot diseases in date palms (Phoenix dactylifera L.) caused by fungi such as Alternaria and Curvularia was demonstrated. Studies have shown that there is a strong association between disease severity (DS%) and chlorophyll levels in date palm seedlings infected with various fungal pathogens. Statistical models can be used to accurately predict disease severity based on the presence of fungi and chlorophyll levels. This suggests that measuring chlorophyll levels may be a useful tool for early detection of disease, even before visible symptoms appear. A study was conducted in which date palm seedlings were inoculated with various fungal pathogens and disease severity and chlorophyll content were monitored over a period of time. The results showed a clear inverse relationship between disease severity and chlorophyll levels. Statistical models were able to accurately predict disease severity based on fungal presence and chlorophyll content. Remarkably, changes in chlorophyll levels were observed early in the infection, before visible symptoms appeared. This highlights the potential of using a SPAD meter to monitor and treat diseases in date palms. The models were validated on a variety of infected and healthy date palm leaves and demonstrated high accuracy in disease classification and severity estimation. These results suggest that chlorophyllbased detection models can be used for rapid and accurate diagnosis of leaf spot fungal diseases in date palm without the need for invasive procedures.