2017
DOI: 10.1590/s0102-05362017042020
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Minimum plot size to evaluate potato tuber yield traits

Abstract: The proper plot size is essential to reduce experimental error and thereby maximize precision of data obtained in an experiment. The objective of this work was to estimate the minimum number of plants per plot to assess tuber yield traits of potato genotypes. Four advanced potato clones (F161-07-02, F189-06-09, F97-08-07 and F131-08-06) of the breeding program of Embrapa were evaluated. The experiment was conducted in the fall season of 2015, in Canoinhas, Santa Catarina State, Brazil. A randomized complete bl… Show more

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Cited by 5 publications
(5 citation statements)
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“…The maximum modified curvature method (MMCM), through a regression equation, algebraically determines the optimal point of the plot size using the relationship between the coefficients of variation and its respective sizes (Pereira et al, 2017). With this model it is possible to minimize experimental error, optimize resources and ensure maximum precision (Cargnelutti Filho et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…The maximum modified curvature method (MMCM), through a regression equation, algebraically determines the optimal point of the plot size using the relationship between the coefficients of variation and its respective sizes (Pereira et al, 2017). With this model it is possible to minimize experimental error, optimize resources and ensure maximum precision (Cargnelutti Filho et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…Plot sizes with lower CVs are recommended for experimental purposes (8). The inverse behavior between plot size (BU) and coefficient of variation (table 3, page 60) has also been found in several similar studies (4,8,27,30).…”
Section: Tablementioning
confidence: 61%
“…Among them, the Modified Maximum Curvature Method (MMCM) (20) stands out. This method algebraically determines through a regression equation the optimal relationship between plot sizes and their respective coefficients of variation (27). With this model, one can minimize experimental error, optimize resources, and ensure maximum precision (8).…”
Section: Introductionmentioning
confidence: 99%
“…The experimental design was randomized complete blocks with four replications in the two experiments. The experimental plots consisted of a 3 m long row, with 10 tubers spaced 30 cm within rows, and 80 cm between rows (Pereira et al, 2017).…”
Section: Methodsmentioning
confidence: 99%