Spectral reflectance in the detection of Persian lime (Citrus latifolia Tanaka) leaves infected with Huanglongbing under fertilization treatments

Resumen

Objective: Evaluate the spectral reflectance method, to determine whether Persian lime leaves exposed to fertilizer treatments exhibit wavelengths associated with symptoms of Huanglongbing (HLB).

Design/Methodology/Approach: An experiment with a randomized complete block design with fertilizer treatments was implemented to observe changes in reflectance, chlorophyll content, severity of HLB symptoms, and the number of bacteria in Persian lime leaves. Grafted plants inoculated with buds from a diseased tree were placed under greenhouse conditions for a 12-month period.

Results: Leaves of diseased plants exhibited significantly higher reflectance in the visible spectrum (VIS) and lower chlorophyll content than leaves of healthy plants. A reverse, but less marked trend was observed in the near-infrared spectrum (NIR). Fertilization treatments did not have a significant impact on reflectance, chlorophyll content, severity of the symptoms, and bacterial count.

Study Limitations/Implications: A spectral reflectance assessment should be extended to susceptible varieties that exhibit visible symptoms with greater rapidity. Spectrometry can be complemented with multispectral and machine learning techniques to facilitate the early detection of asymptomatic diseased plants.

Findings/Conclusions: Spectral reflectance in the visible range has effectively differentiated between leaves of healthy plants and leaves with mild symptoms of HLB. Higher reflectance and lower chlorophyll content in diseased leaves are associated with this phenomenon, even when management practices that could mask symptom expression in diseased plants, such as fertilization, are employed.