# Applications of Raman Microscopy/Spectroscopy-Based Techniques to Plant Disease Diagnosis
## 2 Plant Disease Diagnosis an Overview--Why Early Detection Matters--The Problem  
As mentioned above, plant disease diagnosis is a crucial aspect of plant pathology, essential for mitigating economic losses and ensuring food security. In general, plant diseases are caused by many pathogenic agents, including viruses, bacteria, mycycl plasmas, rickettsias, fungi, nematodes and parasitic higher plants [15; 16]. These agents can be transmitted naturally from plant to plant by various means, such as the wind, rain or physical disturbance of plant tissues by other animals. Plant pathologists have attempted to characterize and classify each disease based on the host or the associated host-pathogen relationship, the environmental patterns of disease frequency and the mode of the pathogen's survival, dispersal and infection [15; 16; 17; 18]. Once diseases are characterized, agronomists can focus on important methods for managing them. The first step in disease management is the accurate diagnosis of each disease. Some common methods used for plant disease diagnosis are visual observations (identifying characteristic symptoms such as lesions on plants to identify the plant pathogen), microscopy (involving examining tissue samples under a microscope to identify pathogenic microorganisms), serological tests (involving antibodies to detect the presence of specific pathogens in plant tissue) and molecular diagnostics (involving techniques such as PCR or DNA sequencing to identify plant pathogens) [16]. Besides the new tools and technologies, e.g., PCR, that have been created for plant disease diagnosis, recent advances in computer technology offer tools that can be used to develop systems for accurate and timely plant disease diagnostics [19; 20; 21]. These systems have introduced computer applications in disease diagnostics focused on providing fast information access, from databases of disease symptoms and their causes to computerized practical aids and expert systems for plant disease diagnostics [22]. The above-mentioned disease diagnostic systems enable the rapid and accurate identification of plant diseases, which can help farmers and plant breeders take timely action to control the spread of diseases. However, they have limitations in terms of understanding the interactions between plants and pathogens, including the host's immune system, the pathogen's virulence factors and environmental factors [1]. Furthermore, while we have a general understanding of plant defense mechanisms, there is still much to be learned about the specific mechanisms involved in plant-pathogen interactions. For example, walnut blight pathogen (_Xanthomonas arboricola_ pv. _juglandis_) causes one of the most destructive diseases of the walnut (_Juglans regia_ L.), so specific and reliable diagnosis tools for this nut based on either conventional PCR or real-time PCR have been developed [23]. However, these tools can become somewhat inappropriate (due to different genomic profiles when it comes to in-field diagnosis, as demonstrated by symptomatic plants [24]). Moreover, due to heavy rainfall and high relative humidity and temperatures in the main walnut-producing areas, walnut disease occurs frequently, with severe pathogenesis. By addressing these limitations, prompt diagnosis (in-field diagnosis) of the occurrence of this disease provides the potential to undertake effective management responses to reduce damage to walnut trees, minimize economic losses and protect the environment [25; 26]. Many more plant-pathogen interactions are complex and influenced by many factors, making it challenging to develop accurate diagnostic methods. Furthermore, multiple virulence factors being produced by pathogens, such as toxins, enzymes and signaling molecules, which can interact with each other, increases the risk of false diagnosis and makes it challenging to develop effective diagnostic methods [1; 27]. Why does early detection matter?