Detection of Lesions in Lettuce Caused by <i>Pectobacterium carotovorum</i> Subsp<i>. carotovorum</i> by Supervised Classification Using Multispectral Images

Carmo, Glecia Júnia dos Santos; Castoldi, Renata; Martins, George Deroco; Jacinto, Ana Carolina Pires; Tebaldi, Nilvanira Donizete; Charlo, Hamilton César de Oliveira; Zampiróli, Renan

doi:10.1080/07038992.2021.1971960

Cited by 7 publications

(2 citation statements)

References 69 publications

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“…Multiple ITS RNA seq Bean [190] Multiple RT PCR Fabaceae [191] Multiple Machine vision Cucumber [185] Multiple Multiplex PCR Cucumber [192] Multiple ITS barcoding Tomato [193] Pectobacterium carotovorum Sensors Lettuce [194] Table 3. Cont.…”

Section: Applications Of Different Tools For the Detection Of Fungal ...mentioning

confidence: 99%

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: Applications Of Different Tools For the Detection Of Fungal ...mentioning

confidence: 99%

Applicability of Smart Tools in Vegetable Disease Diagnostics

Ovesná

Tsiropoulos²,

Collier

et al. 2023

Agronomy

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show abstract

“…Initial symptoms are difficult to see and, when observed, almost impossible to control. As such, any strategy aimed at detecting these anomalies in the early stages of development is vitally important, since the disease is aggressive and the growth cycle of lettuce short (Carmo et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Diagrammatic scale for evaluation of Bremia lactucae sporulation in lettuce seedlings

2023

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In disease assessment, the use of diagrammatic scales provides a standard reference point for comparison. There is still no precise and accurate scale for the evaluation of sporulation intensity of downy mildew in lettuce seedlings.The objective of this study was to propose a diagrammatic scale for the evaluation of downy mildew severity in lettuce seedlings. Thirty lettuce seedlings with different sporulation intensities were used to develop the proposed diagrammatic scale. Solaris lettuce cultivar was sown, and fifteen days after sowing, inoculations occurred using distilled water, the pathogen sporangia, and Tween 20. The monitoring of disease development was performed daily.When the first sporulation appeared on the cotyledonaryleaves,the proposed scale was verified to meet the minimum and maximum levels of disease severity. Two evaluators verified the accuracy, precision and performed the estimation of the sporulation and reproducibility using a scale. The images obtained are important in the standardization of a scale to identify resistant, tolerant and susceptible plants to downy mildew. Furthermore, it allows validating a diagrammatic scale of sporulation intensity of B. lactucae in lettuce seedlings. Thus, it is the diagrammatic scale developed in the work will guide future research to accelerate the detection of mildew severity in lettuce seedlings.

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Drones in vegetable crops: A systematic literature review

Canicattì,

Vallone

2024

Smart Agricultural Technology

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Detection of Lesions in Lettuce Caused by Pectobacterium carotovorum Subsp. carotovorum by Supervised Classification Using Multispectral Images

Cited by 7 publications

References 69 publications

Applicability of Smart Tools in Vegetable Disease Diagnostics

Applicability of Smart Tools in Vegetable Disease Diagnostics

Diagrammatic scale for evaluation of Bremia lactucae sporulation in lettuce seedlings

Drones in vegetable crops: A systematic literature review

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