Early Detection of Diseases in Crops for Efficient Application of Pesticides

Dear Colleagues,

In plant pathology, the causal agent can be identified through visual inspection for characteristic disease symptoms or through laboratory tests. Laboratory tests include isolating and identifying plant disease causal agents using various culture media, as well as diagnostic tests such as PCR and ELISA tests. These techniques are important for identifying biotic factors that may cause disease, but not for abiotic factors such as salinity or micronutrient toxicity that may cause abiotic plant disease symptoms. Diagnosis is crucial for identifying the biotic or abiotic causal agent. One of the first things that a diagnostician should note is how the diseased plants are distributed over the affected area. For example, uniform damage patterns over a large area are generally not associated with biotic agents but are usually due to abiotic causal agents. Therefore, there is a strong interest in the agricultural and horticultural sectors to replace visual inspection and some laboratory techniques with more automated and sensitive approaches for timely interventions and targeted control measures. 

Aside from the gold standard diagnostic tool (qPCR), the literature has discussed solutions for plant disease detection using imaging sensors including RGB, multispectral, hyperspectral, thermal, and chlorophyll fluorescence, and remote sensing methods, or by using a specific spectroscopic technique such as Raman spectroscopy (confocal Raman technique; surface-enhanced Raman scattering). These key innovation techniques are focused on early disease detection based on the biochemical changes induced by a specific biotic or abiotic agent during the plant–pathogen interaction. These techniques are very accurate for early disease detection when included in the process of employing statistical methods for reducing cases-by-variables data (Principal Component Analysis) or a probabilistic approach to learning and inference based on a different view of what it means to learn from data (Bayesian Classification).

Overall, to understand more about the above technologies and how they will be helpful in crop science for the effective and efficient application of pesticides, we must collect innovative ideas (research articles) providing a solution in the form of modern methods for the early detection of disease in crops caused by biotic or abiotic agents.

Dr. Ioannis Vagelas
Guest Editor

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• crop diseases
• early detection
• diagnostic tools
• laboratory analytical methods
• PCR-based diagnostics
• next-generation sequencing
• spectroscopy diagnostics
• Raman-based techniques
• machine learning models