SAMPLING PLAN FOR ASSESSING BROWN ROT SEVERITY IN PEACHES SUBJECTED TO DIFFERENT PLANT EXTRACTS

Authors

  • Kelly Pazolini Department of Plant Pathology and Nematology, Escola Superior de Agricultura "Luiz de Queiroz", Piracicaba, SP
  • Idalmir dos Santos Agronomy postgraduate program, Universidade Tecnológica Federal do Paraná, Pato Branco, PR
  • Idemir Citadin Agronomy postgraduate program, Universidade Tecnológica Federal do Paraná, Pato Branco, PR
  • Lindolfo Storck Agronomy postgraduate program, Universidade Tecnológica Federal do Paraná, Pato Branco, PR
  • Mariana Faber Flores Sector of Agricultural Science, Universidade Federal do Paraná, Curitiba, PR

DOI:

https://doi.org/10.1590/1983-21252016v29n301rc

Keywords:

Monilinia fructicola. Experimental Precision. Sample Size. Post-harvest.

Abstract

The identification of brown rot control derivatives has been the focus of intense research owing to the negative effects of the unrelenting usage of fungicides. Brown rot, caused by Monilinia fructicola, is an important post-harvest disease of peaches. The goal of this study was to estimate the optimum sample size of peaches in order to assess the average lesion size and the influence of different plant extracts on the fruits. Three preparation forms (FPE) were evaluated, as well as another seven forms of application (FAE) of canola and mustard extracts on peaches, with applications of the pathogen’s inoculum. Five fruits were utilized in five repetitions per treatment. Evaluation involved measurement of the fruits’ lesioned areas. The necessary sampling size was determined for estimation of the averages for each treatment and experiment. For measurement of the lesion size, 99 fruits in FPE and 23 fruits in FAE were sufficient for estimating the average with an estimation error of 10%. Based on the same estimation error, the sampling size is contingent on the extracts (canola, and mustard), batches of fruits, forms of extraction, and extract application on the fruits.

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Published

19-07-2016

Issue

Section

Agronomy