Fungal disease detection in plants: Traditional assays, novel diagnostic techniques and biosensors

Metabolic response and volatile profile induced by temperature, on Colletotrichum fragariae and Rhizopus stolonifer

“…Fungal presence on the host could be detected in time for it to be controlled if a biomarker is found. On this, Ray et al () reported the existence of current technologies, such as immunological and molecular assays, the detection of VOCs and some methods for the isolation of non‐volatile metabolites that describe the fungi growth. To accomplish this, a better understanding of the complex behaviour of the above‐mentioned fungi is necessary, and this is best done by means of in vitro growth assessment, since conditions can be controlled.…”

Evaluation of Expert Systems Techniques for Classifying Different Stages of Coffee Rust Infection in Hyperspectral Images

“…Fungi are the most diverse group of plant pathogens; there are more than 20,000 species of fungi that can cause diseases in crops and plants, and these fungi are responsible for 70-80% of plant diseases. 4 Crop loss due to plant diseases may cause food insecurity and famines 1 ; consequently, detecting plant diseases and their pathogens is an operation of primary importance to agricultural field management 5,6 and an essential research topic in agriculture. 3 Given this scenario, there is a need for research to focus on the rapid design of tools for the early detection of symptoms of a particular disease.…”

“…This characteristic is of considerable interest for its application in precision agriculture 2 disease evaluation. 4 However, this technique requires the use of special methods, such as those based on machine learning techniques such as artificial neural networks (ANNs), decision tree (DT), K-means (KM), Knearest neighbor (KNN), and support vector machine (SVM), for data analysis. These techniques have been applied in agricultural research and shown potential for automatic classification methods in site-specific weed detection.…”

“…28,31 Thus, to prepare mitigation actions, it is necessary to evaluate rust damage during the early stages of infection. 32 Therefore, in the diagnosis of plant fungal infections, it is essential to perform a correct disease detection process, 4 particularly using non-destructive and real-time techniques. 1 Consequently, the main objective of this work was to evaluate the use of expert systems techniques and hyperspectral imaging to classify different stages of coffee rust infection in coffee (Coffea Typica) leaves.…”

“…3,4,5,6 To identify the pathogens that cause a particular disease, morphological, microbiological and biochemical techniques may be used. 4 However, visual inspection methods are subjective, occasionally inconsistent and generally slow, and given their high cost, such methods are often prohibitive on large farms. Meanwhile, laboratory analyses, such as molecular, immunological or pathogen culturing-based approaches, are often time consuming and destructive.…”