000			02691nab a2200301 i 4500
003			BR-BrBNA
005			20240209125057.0
008			240209b2023 bl.ar|pooa||| 00| 0 eng |
040			_aBR-BrBNA _beng
072			_aF50 _b0160
072			_aU10
100			_aNeu, Ismael Mario Márcio
100			_aCargnelutti Filho, Alberto
100			_aSilveira, Daniela Lixinski
100			_aPezzini, Rafael Vieira
100			_aBandeira, Cirineu Tolfo
245			_aNumber of trials to estimate the condition number in rye traits
500			_aPublicação online; 30 ref; 3 tables; Summary (En)
520			_a ABSTRACT - Multicollinearity must be diagnosed in multivariate analyses. Among the indicators, the condition number can be used to quantify the degree of multicollinearity. Hence, this study sought to determine the number of measurements (trials) necessary to estimate the number of condition in linear correlation matrices between rye traits. Five uniformity trials were carried out with ‘BRS Progresso’ rye, and eight morphological traits and eight productive traits were evaluated, forming two groups. In each group of traits, six cases (combinations of traits) were planned and the multicollinearity diagnosis was performed. Repeatability analyses were performed using the following methods: analysis of variance, principal component analysis, and structural analysis, and the number of measurements (trials) was determined for diff erent levels of precision. A higher condition number of repeatability coeffi cients was obtained by the principal component methods (based on correlation and variance and covariance matrices) and structural analysis based on the variance and covariance matrix. A greater number of measurements (trials) is necessary to estimate the number of conditions in productive traits compared to morphological ones. One trial is enough to effi ciently estimate the condition number with a minimum accuracy of 80% in morphological and productive traits of rye, whereas at least three trials are required for 95% accuracy. Key words: Secale cereale L. Repeatability analysis. Multicollinearity. Experimental planning
650			_aCENTEIO
650			_aMORFOLOGIA VEGETAL
650			_aMODELO MATEMÁTICO
650			_aMÉTODO ESTATÍSTICO
773	0		_04290 _9275636 _dFortaleza-CE Universidade Federal do Ceará. Centro de Ciências Agrárias 2002 _o2023-437436 _tRevista Ciência Agronômica (Brazil) _x0045-6888; 1806-6690 (on-line) _gv. 54 p. 1-9; (2023) _wBR2023002373
856			_uhttps://www.scielo.br/j/rca/a/rC4N3JxdWFM9DVfTBFpvJQs/?format=pdf&lang=en
942			_cAnalítica
999			_c298486 _d298486