Coefficient of Variation: A New Approach for the Study in Maize Experiments

Abstract

<jats:p>&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; The magnitude of the variation coefficient (CV) is insufficient to validate the quality of the experiment, regardless of the number of treatments, repetitions and effect of treatments. The objective was to develop a new approach to the study of coefficient of variation, as well as evaluations of these nuances with applicability in new scientific research. The study was conducted via computer simulation. The replicates (r) ranged from 2, 3, 4, 5, 10 to 20. The treatment number (t) ranged from t 5, 10, 15, 20, 25 and 30. In each of these combined scenarios we have the variation of 25 different CVs, ranging from 1, 3, 5, 7, ..., 49 to 51 %. It was imposed the variation of 11-1 treatment effects 0, 240, 480, 720, ..., 2000, 2400 kg ha-1, totaling 9,900.00 scenarios. The type I error is statistically invariant in the scenarios studied. With high treatment effect the CV has no implications on the power of the test (1-β). The results obtained in this research reveal that experiments with a high percentage of CV are sufficient to obtain high probabilities of the power of the F test, which do not compromise the complementary analyzes.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; </jats:p>

Meta-analysis of the experimental coefficient of variation in wheat using the Bayesian and Frequentist approaches

“…The Bayesian and Frequentist approaches demonstrated contrasting distributions, while the estimate and posterior means as well as the credible and confidence intervals were similar. This significant variation is observed to justify the classification coefficient variation for these traits individually (Costa et al, 2002, Nardino et al, 2020.…”

“…This measurement considers the experimental estimate error ( σe 2 is the relation mean overall of the experiment and can be easily obtained as Classifications for the CVe magnitude have been proposed for several crops (Albert and Zhang, 2010;Fritsche-Neto et al, 2012;Couto et al, 2013;Aerts et al, 2015). The Frequentist approach has been used to estimate the CVe (Fritsche-Neto et., 2012;Mora and Arriagada, 2016;Nardino et al, 2020); nevertheless, few proposals take into account the CVe distribution for a trait that follows a non-normal distribution, that is, robust methods are necessary, since the distribution is unknown in many cases.…”

Morphological parameters, heritability, yield component correlation, and multivariate analysis to determine secondary characters in selecting hybrid maize

“…The CV value provides an overview of the diversity within the population . The smaller the CV value, the stronger the character selection in predicting plant populations at different growth stages (Nardino et al 2020). The CV value is often used by maize plant breeders as an alternative method in the selection process, providing an overview of diversity in a population (Patel et al 2023).…”