Eclidean distance can recognize the best Stevia genotype and environment to produce rebaudioside and stevioside under controlled conditions
DOI:
https://doi.org/10.21704/pja.v6i3.1974Keywords:
Biostatistics, research methods, glucoside, phenotypic traits, sweet grassAbstract
Stevia rebaudiana is considered an important medicinal plant possessing low-calorie glucoside sweeteners. The present work describes the comparison of three stevia genotypes (IBT 1, IBT 2 and IBT 3) in two contrasting environments simulated under controlled conditions: Sullana in Peru; and Misiones in Paraguay (regarded as the center of origin of Stevia). In the study, we explored the Euclidean distance as an integrating indicator for simultaneous selection of several stevia traits. Plant scientists often record multiple morphological, physiological and biochemical indicators in their experiments. Common statistical data evaluations involve univariate analyses such as t-test, Mann-Whitney and Analysis of Variance followed by Tukey HSD. However, these analyses do not evaluate integrally the effects of the experimental treatments because each indicator is analyzed independently. Euclidean distance from each treatment combination to the ideal phenotype of the stevia plantlets was calculated. IBT 2 grown in Sullana environmental conditions showed the best integral results, while IBT 1 displayed the worst results. esponse parameters to different contrasting environments. The analysis shown here indicates that the use of the Euclidean distance could contribute to establishing a more integrated evaluation of the contrasting Stevia genotypes. On the other hand, the Euclidean distance, as a non-dimensional indicator, can help to compare different phenotype traits.
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