Development and validation of a diagrammatic scale for white mold incidence in tobacco leaf discs

Lopes, Fernanda Souza; Pozza, Edson Ampélio; Porto, Antônio Carlos Mota; Silva, Caroline Marcela da; Miguel, Luciana Aparecida; Pereira, Welison Andrade

doi:10.1007/s13313-021-00828-7

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…As the primary data analysis showed, when accounted without using the scale, most of assessors from both groups noticeably overestimated the level of Alternariosis development on grape leaves [14,15]. This was due to the difficulty of perception the uneven spreading of disease symptoms on the leaf surface area.…”

Section: Resultsmentioning

confidence: 95%

“…1). The scale levels were set in accordance with the minimum, maximum and intermediate values of damage degree for convenience in further application and training [14,15]. Validation and confirmation of accuracy of the developed "schematic scale" was carried out on the basis of assessment of 30 grape leaves with symptoms of Alternariosis with varying intensity by 16 specialists: group 1 -8 people with no experience in quantitative assessment of diseases; group 2 -8 people with experience in quantitative assessment of diseases.…”

Section: Methodsmentioning

confidence: 99%

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The development of phytosanitary monitoring methods – creating of a schematic scale for as-sessing the development of Alternariosis on grape leaves

Aleinikova,

Galkina,

Andreyev

et al. 2022

BIO Web Conf.

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To ensure consistent good quality grape yields it is necessary to minimize losses associated with affection of grape plants by various dis-eases. One of the main conditions to ensure the effective control of phyto-pathogens is a timely monitoring, revealing and assessing of harmful or-ganisms development intensity. In modern research, in order to improve the accuracy and reliability of quantitative characteristics of disease devel-opment intensity, as well as comparability of the results obtained, it is pro-posed to use a “set of standard diagrams” or a “schematic scale” - a set of illustrations depicting an increasing percentage of damage to the surface of one or another plant organ. To date, similar "sets of standard diagrams" were proposed for such grape diseases as mildew, anthracnose and grape leave rust. The article presents the results of creating a new "schematic scale" for assessing the development intensity of grape Alternariosis as a disease with the recorded increasing importance at a recent time of climate change. The scale was developed using colored and black–and-white pho-tographs of grape leaves affected by Alternariosis to varying degrees to de-termine the real intensity of the disease in digital form. Scale levels were established in accordance with minimum and maximum values of damage degree. Validation was carried out by two groups of assessors with differ-ent experience in accounting. The determination coefficient (R2) of regres-sion line and the absolute error variance demonstrated an increase in accu-racy, repeatability and reproducibility of estimates using the developed “schematic scale”. Using of the developed scale made it possible to in-crease the accuracy of quantitative assessment of intensity of Alternariosis damage to grape leaves.

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Section: Resultsmentioning

confidence: 95%

Section: Methodsmentioning

confidence: 99%

The development of phytosanitary monitoring methods – creating of a schematic scale for as-sessing the development of Alternariosis on grape leaves

Aleinikova,

Galkina,

Andreyev

et al. 2022

BIO Web Conf.

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RGB image-based method for phenotyping rust disease progress in pea leaves using R

Osuna-Caballero,

Olivoto,

Jiménez-Vaquero

et al. 2023

Plant Methods

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Background Rust is a damaging disease affecting vital crops, including pea, and identifying highly resistant genotypes remains a challenge. Accurate measurement of infection levels in large germplasm collections is crucial for finding new resistance sources. Current evaluation methods rely on visual estimation of disease severity and infection type under field or controlled conditions. While they identify some resistance sources, they are error-prone and time-consuming. An image analysis system proves useful, providing an easy-to-use and affordable way to quickly count and measure rust-induced pustules on pea samples. This study aimed to develop an automated image analysis pipeline for accurately calculating rust disease progression parameters under controlled conditions, ensuring reliable data collection. Results A highly efficient and automatic image-based method for assessing rust disease in pea leaves was developed using R. The method’s optimization and validation involved testing different segmentation indices and image resolutions on 600 pea leaflets with rust symptoms. The approach allows automatic estimation of parameters like pustule number, pustule size, leaf area, and percentage of pustule coverage. It reconstructs time series data for each leaf and integrates daily estimates into disease progression parameters, including latency period and area under the disease progression curve. Significant variation in disease responses was observed between genotypes using both visual ratings and image-based analysis. Among assessed segmentation indices, the Normalized Green Red Difference Index (NGRDI) proved fastest, analysing 600 leaflets at 60% resolution in 62 s with parallel processing. Lin’s concordance correlation coefficient between image-based and visual pustule counting showed over 0.98 accuracy at full resolution. While lower resolution slightly reduced accuracy, differences were statistically insignificant for most disease progression parameters, significantly reducing processing time and storage space. NGRDI was optimal at all time points, providing highly accurate estimations with minimal accumulated error. Conclusions A new image-based method for monitoring pea rust disease in detached leaves, using RGB spectral indices segmentation and pixel value thresholding, improves resolution and precision. It rapidly analyses hundreds of images with accuracy comparable to visual methods and higher than other image-based approaches. This method evaluates rust progression in pea, eliminating rater-induced errors from traditional methods. Implementing this approach to evaluate large germplasm collections will improve our understanding of plant-pathogen interactions and aid future breeding for novel pea cultivars with increased rust resistance.

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New proposed of standard area diagram scale for assessing black sigatoka in bananas

Nuñez,

Feria-Gómez,

Pérez-Ochoa

et al. 2023

Preprint

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Black sigatoka, or black leaf streak (BLS), is caused by Pseudocercospora fijiensis and is the most important foliar disease in Musa production. Our goal was to develop a new standard area diagram (SAD) with high-resolution digital images with six disease levels: 0 (0%), 1 (0.1–5.0%), 2 (5.01–13.0%), 3 (13.01–23.0%), 4 (23.01–40.0%), 5 (40.01–65.0%) and 6 (> 65.0%) and compare BLS severity results in banana leaves with those based on another SAD. Five evaluations were conducted by thirteen different evaluators and each evaluation was performed at seven-day intervals. The first assessment was done without a SADs. Evaluators performed two assessments with each SAD. The statistics were analyzed with linear regression and Lin’s concordance correlation. With the proposed SAD, the evaluators improved the precision, accuracy, repeatability and reproducibility and reduced the residual distribution, as compared using the other SAD. The proposed SAD is a tool that aids users in producing a disease estimate that is close to the real value of BLS in banana leaves.

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Development and validation of a diagrammatic scale for white mold incidence in tobacco leaf discs

Cited by 3 publications

References 27 publications

The development of phytosanitary monitoring methods – creating of a schematic scale for as-sessing the development of Alternariosis on grape leaves

The development of phytosanitary monitoring methods – creating of a schematic scale for as-sessing the development of Alternariosis on grape leaves

RGB image-based method for phenotyping rust disease progress in pea leaves using R

New proposed of standard area diagram scale for assessing black sigatoka in bananas

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