Rank-ordering coefficients of variation for popping expansion

Emmanuel Arnhold,Klayton Flávio Milani

doi:10.4025/actasciagron.v33i3.11911

Emmanuel Arnhold, Klayton Flávio Milani

Open Access

https://doi.org/10.4025/actasciagron.v33i3.11911

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Abstract

The coefficient of variation (CV) has been the most important statistic to determine the precision of experimental errors, but an even classification for guiding popcorn breeders is still lacking for popping expansion. The normality of data from 50 CVs was tested through the Shapiro-Wilk test, and the mean (m), median, standard deviation (SD), maximum and minimum values, asymmetry and kurtosis were all determined using the momentum method. The CVs were ranked as low [CV ≤ (m - 1 SD)], moderate [(m - 1 SD) < CV ≤ (m + 1 SD)], high [(m + 1 SD) < CV ≤ (m + 2 SD)] and very high [CV > (m + 2 SD)]. In summary, these data were close to the normality because the slight and flattened curve was skewed to the right. The CV’s mean was 11.08, the median was 11.94 and the standard deviation was 5.13%. Accordingly, values of CV ≤ 5.95% are low, 5.95 < CV ≤ 15.21% are moderate, 15.21 < CV ≤ 20.34% are high, and CV > 20.34% are very high.

Highlights

In Brazil, popcorn growers have been requiring new cultivars to increase the crop productivity and the grain quality
These coeficiente de variação (CV) were rank-ordered according to Scapim et al (1995), who used the classification proposed by Garcia (1989) in which the values were reported as low [CV < (m - 1 standard deviation (SD))], moderate [(m - 1 SD) < CV < (m + 1 SD)], high [(m + 1 SD) < CV < (m + 2 SD)] and very high [CV > (m + 2 SD)]
The distribution of these CVs for popping expansion was close to the normality, and the shape of this Gaussian curve was classified as platykurtic because of its flattered curvature (FERREIRA, 2005)

Summary

Introduction

In Brazil, popcorn growers have been requiring new cultivars to increase the crop productivity and the grain quality. Research methods in which quantitative data obey the normal distribution, the CV has been the most important statistic to describe the precision of the experimental error This error is evaluated for specific traits, and gives a general indication of the levels of variation within a population using the standard deviation as a fraction of the mean (BOWMAN; WATSON, 1997). The comparison of experimental responses based on the CV must consider the different conditions in which these experiments were carried out, the crop species, traits under investigation, necessity of data transformation, environmental heterogeneity, plot size and number of replications All these variables reinforce the necessity of precise references based on the nature of a specific trait (LANA et al, 2006). The objective of the present experiment was to rank the order of these coefficients of variation

Material and methods

Results and discussion

Conclusion