Validation of Diagram Scale for Leaf Spot Caused by Pestalotiopsis sp. in Coconut Seedlings

Aline Figueiredo Cardoso, Fernanda Sarmento de Oliveira Louzano, Cássia Cristina Chaves Pinheiro, Paulo Manoel Pontes Lins, Gisele Barata da Silva

Abstract


The absence of a methodology to quantify Pestalotiopsis sp. in coconut plants (Cocos nucifera L.) justified the elaboration and validation of a diagrammatic scale containing seven values (2%, 5%, 10%, 15%, 20%, 40% and 60%) of disease severity, in a sampling under natural conditions of occurrence in the field. To elaborate the diagrammatic scale, 100 leaves of Cocos nucifera L. were obtained from an experimental field of Fazenda Reunidas Sococo in Santa Isabel, Pará. The images of these leaves were obtained with the aid of a digital camera. Subsequently, with the aid of Assess 2.0 APS software, the actual disease severity values were obtained in percentage terms. The validation of the proposed diagrammatic scale was performed by ten inexperienced evaluators who evaluated the projected images without the aid of the suggested scale, and later, with the aid of the scale. From the data obtained from the evaluators with and without scale, linear regression analysis was performed, relating the real severity and the estimated severity. The accuracy of the estimates was evaluated by the regression determination coefficient (R2) and the variance of the absolute errors. The accuracy of each evaluator was determined by the t-test applied to the angular coefficient of line (b) and the linear coefficient of line (a), both obtained by linear regression. Through the coefficient of determination values, It is possible to verify that the use of the scale gave greater accuracy to 100% of the evaluators with an average of 0.94 and 94% repeatability. The use of the diagrammatic spot scale for Pestalotiopsis sp. it enables future work with accuracy and precision, as well as optimizing disease control practices within a coconut tree nursery management program.


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DOI: https://doi.org/10.5296/jas.v8i2.15621

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Paper Submission E-mail: jas@macrothink.org

Journal of Agricultural Studies   ISSN 2166-0379

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