Optical screening of citrus leaf diseases using label-free spectroscopic tools: A review

Abstract

Citrus diseases pose threats to citrus farming and result in economic losses worldwide. Nucleic acid and serology-based methods of detection such as polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and immunochromatographic assays are commonly used but these laboratory tests are laborious, expensive and might be subjected to cross-reaction and contamination. Timely intervention for better control over the spread of disease is essential to minimize crop loss, as no cure is available for citrus diseases like Huanglongbing. Modern optical spectroscopic techniques offer a promising alternative to traditional methods, as they are label-free, sensitive, rapid, and non-destructive. They also demonstrate potential as a mass screening tool and could be incorporated into autonomous systems for disease detection in citrus orchards. Nevertheless, the majority of optical spectroscopic methods for citrus disease detection are still in the trial phases and, require additional efforts to be established as efficient and commercially viable methods. The review presents an overview of fundamental working principles, the state of the art, and explains the applications and limitations of the optical spectroscopy technique including the spectroscopic imaging approach (hyperspectral imaging) in the identification of diseases in citrus plants grown over a large area. The review highlights (1) majorly used optical spectroscopic tools that can potentially be utilized in field measurements, (2) their applications in screening citrus diseases through leaf spectroscopy, and (3) discusses their benefits, challenges, and limitations, including future insights on how to enhance them further for efficient label-free identification of citrus diseases. Moreover, the role of artificial intelligence is reviewed as potential effective tools for spectral analysis, enabling accurate detection of infected citrus leaves even before the appearance of visual symptoms by leveraging compositional, morphological, and chemometric characteristics of the plant leaves. The review aims to encourage researchers to enhance the development and commercialization of field-based, label-free optical tools for the rapid and early-stage screening of citrus diseases in plants.

Keywords

• Citrus disease
• Citrus greening
• Fluorescence spectroscopy
• Raman spectroscopy
• Hyperspectral imaging
• Precision agriculture