Comprehensive account of present techniques for in-field plant disease diagnosis

Mansotra, Ritika; Vakhlu, Jyoti

doi:10.1007/s00203-021-02529-7

Cited by 4 publications

(2 citation statements)

References 94 publications

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“…Several approaches and techniques have been developed to facilitate the diagnosis, monitoring, and study of phytopathogenic agents in plants and [7][8][9] various vegetable species. Some of these techniques have been validated and are used by accredited laboratories for official controls [6,[10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…Some of these techniques have been validated and are used by accredited laboratories for official controls [6,[10][11][12]. Others have significant potential for application in "smart" farming [7,9], possibly leading to the implementation of phytopathogen surveillance through intelligent and goal-oriented analysis, planning, and observation [13]. Currently, the importance of smart approaches for disease diagnosis on farms is increasing [14,15].…”

Section: Introductionmentioning

confidence: 99%

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Applicability of Smart Tools in Vegetable Disease Diagnostics

Ovesná

Tsiropoulos²,

Collier

et al. 2023

Agronomy

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Various diseases and pests cause serious damage to vegetable crops during the growing season and after harvesting. Growers attempt to minimize losses by protecting their crops, starting with seed and seedling treatments and followed by monitoring their stands. In many cases, synthetic pesticide treatments are applied. Integrated pest management is currently being employed to minimize the impact of pesticides upon human health and the environment. Over the last few years, “smart” approaches have been developed and adopted in practice to predict, detect, and quantify phytopathogen occurrence and contamination. Our review assesses the currently available ready-to-use tools and methodologies that operate via visual estimation, the detection of proteins and DNA/RNA sequences, and the utilization of brand-new innovative approaches, highlighting the availability of solutions that can be used by growers during the process of diagnosing pathogens.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Applicability of Smart Tools in Vegetable Disease Diagnostics

Ovesná

Tsiropoulos²,

Collier

et al. 2023

Agronomy

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A Deep Learning Approach for Detection of Disease in Plant Leaves

Khatri,

Tripathy,

Kumar

et al. 2023

Lecture Notes in Networks and Systems

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A Loop-Mediated Isothermal Amplification Assay for the Rapid Detection of Didymella segeticola Causing Tea Leaf Spot

Tu,

Wang,

Jiang

et al. 2024

JoF

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Tea leaf spot caused by Didymella segeticola is an important disease that threatens the healthy growth of tea plants (Camellia sinensis) and results in reductions in the productivity and quality of tea leaves. Early diagnosis of the disease is particularly important for managing the infection. Loop-mediated isothermal amplification (LAMP) assay is an efficient diagnostic technique with the advantages of simplicity, specificity, and sensitivity. In this study, we developed a rapid, visual, and high-sensitivity LAMP assay for D. segeticola detection based on sequence-characterized amplified regions. Two pairs of amplification primers (external primers F3 and B3 and internal primers FIP and BIP) were designed based on a specific sequence in D. segeticola (NCBI accession number: OR987684). Compared to common pathogens of other genera in tea plants and other species in the Didymella genus (Didymella coffeae-arabicae, Didymella pomorum, and Didymella sinensis), the LAMP method is specific for detecting the species D. segeticola. The assay was able to detect D. segeticola at a minimal concentration of 1 fg/μL genomic DNA at an optimal reaction temperature of 65 °C for 60 min. When healthy leaves were inoculated with D. segeticola in the laboratory, the LAMP method successfully detected D. segeticola in diseased tea leaves at 72 h post inoculation. The LAMP assays were negative when the DNA samples were extracted from healthy leaves. Leaf tissues with necrotic lesions from 18 germplasms of tea plants tested positive for the pathogen by the LAMP assay. In summary, this study established a specific, sensitive, and simple LAMP method to detect D. segeticola, which provides reliable technical support for estimating disease prevalence and facilitates sustainable management of tea leaf spot.

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Comprehensive account of present techniques for in-field plant disease diagnosis

Cited by 4 publications

References 94 publications

Applicability of Smart Tools in Vegetable Disease Diagnostics

Applicability of Smart Tools in Vegetable Disease Diagnostics

A Deep Learning Approach for Detection of Disease in Plant Leaves

A Loop-Mediated Isothermal Amplification Assay for the Rapid Detection of Didymella segeticola Causing Tea Leaf Spot

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