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| TOEBE,MARCOS; MACHADO,LETÍCIA N.; TARTAGLIA,FRANCIELI L.; CARVALHO,JULIANA O. DE; BANDEIRA,CIRINEU T.; CARGNELUTTI FILHO,ALBERTO. |
| ABSTRACT The objective of this study was to determine the sample size necessary to estimate the mean and coefficient of variation in four species of crotalarias (C. juncea, C. spectabilis, C. breviflora and C. ochroleuca). An experiment was carried out for each species during the season 2014/15. At harvest, 1,000 pods of each species were randomly collected. In each pod were measured: mass of pod with and without seeds, length, width and height of pods, number and mass of seeds per pod, and mass of hundred seeds. Measures of central tendency, variability and distribution were calculated, and the normality was verified. The sample size necessary to estimate the mean and coefficient of variation with amplitudes of the confidence interval of 95% (ACI95%) of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Crotalaria sp; Experimental precision; Number of pods; Resampling. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000401705 |
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| CARVALHO,JULIANA O. DE; TOEBE,MARCOS; TARTAGLIA,FRANCIELI L.; BANDEIRA,CIRINEU T.; TAMBARA,ANDRÉ L.. |
| ABSTRACT The goal of this study was to estimate the leaf area of Crotalaria juncea according to the linear dimensions of leaves from different ages. Two experiments were conducted with C. juncea cultivar IAC-KR1, in the 2014/2015 sowing seasons. At 59, 82, 102, 129 days after sowing (DAS) of the first and 61, 80, 92, 104 DAS of the second experiment, 500 leaves were collected, totaling 4,000 leaves. In each leaf, the linear dimensions were measured (length, width, length/width ratio and length × width product) and the specific leaf area was determined through Digimizer and Sigma Scan Pro software, after scanning images. Then, 3,200 leaves were randomly separated to generate mathematical models of leaf area (Y) in function of linear dimension (x), and 800... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Non-destructive method; Image processing; Mathematical models; Model validation. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000401851 |
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