The influence of the basic experimental unit size on the plot size estimation determined by the method of maximum curvature of the coefficient of variation model is unknown in sunn hemp. This study aimed to verify the influence of the basic experimental unit (BEU) size in the estimate of the optimum plot size obtained by the method of maximum curvature of the coefficient of variation model for the evaluation of fresh matter of sunn hemp (Crotalaria juncea L.). Fresh matter of sunn hemp at the flowering was evaluated in uniformity trials in two sowing dates. In each sowing date, 4,608 BEU of 0.5 × 0.5 m (0.25 m 2 ) were evaluated and 64 BEU plans were formed with sizes from 0.25 to 64 m 2 . In each evaluation period for each BEU plan, the first order spatial autocorrelation coefficient, variance, standard deviation, mean, coefficient of variation of the trial and the plot size were determined with the fresh matter data. For each BEU plan, the optimum plot size was determined by the method of maximum curvature of the coefficient of variation model. The estimate of optimum plot size depends on the basic experimental unit size. Determining the plot size to assess the fresh matter in basic experimental units as small as possible is recommended in order to prevent overestimation of the plot size and to contemplate all existing variability.Key words: Crotalaria juncea L., experimental design, basic experimental unit. INTRODUCTIONThe sunn hemp (Crotalaria juncea L.) is a cover crop option for soil protection due to its hardiness, high dry matter production and nitrogen fixation (Silva and Menezes, 2007), improving and maintaining soil quality, raising to considerable levels of soil organic matter and nutrients (Leite et al., 2010). The crop rapid development enables the use of sunn hemp in cropping systems with rotation and crop succession. It is the legume with greatest dry matter production in comparison with gray velvet bean (Mucuna nivea), jack bean (Canavalia ensiformis), velvet bean (Mucuna aterrina), lab-lab (Dolichos lablab), showy crotalaria (Crotalaria spectabilis), and dwarf pigeon pea (Cajanus cajan) (Teodoro et al., 2011); in a study carried out by Andrade Neto et al. (2010), the fresh matter of aerial part values of sunn hemp were 13.9 t ha -1 . One aspect to be considered is the inferences made in agricultural research representing experimental reality which is the use of an optimum plot size to minimize the experimental error. The optimum plot size can be calculated based on data obtained from uniformity trials in which treatments are not applied (Ramalho et al., 2012;Storck et al., 2016). In order to evaluate traits of the studied crop, the experimental area is divided into basic experimental units (BEU) with the smallest possible size. Therefore, based on this information, the plot size is determined.The influence of the BEU size in estimating the optimum plot size is still an area with few studies but Oliveira et al. (2005) verified in potato (Solanum tuberosum L.) the BEU size effect on the optimum p...
This study aimed to verify the influence of the basic experimental unit (BEU) size in the estimation of the optimum plot size to evaluate the fresh matter of sunn hemp (Crotalaria juncea L.) using the modified maximum curvature method. The fresh matter of sunn hemp was evaluated in uniformity trials in two sowing season in flowering. In each sowing season, 4,608 BEUs of 0.5×0.5m (0.25m2) were evaluated and 36 BEU plans were formed with sizes from 0.25 to 16m2. In each evaluation period for each BEU plan, using fresh matter data, optimum plot size was estimated through the modified maximum curvature method. Estimation of the optimum plot size depends on the BEU size. Assessing fresh matter in BEUs that are as small as possible is recommended in order to use it to estimate the optimum plot size.
The determination of the optimum plot size in agricultural crops is important for obtaining accurate inferences in the treatments in question. This study aimed at determining the optimum plot size (Xo) and the number of replications to evaluate the fresh matter (FM) and the dry matter (DM) of oat and at verifying the variability of Xo among cultivars and sowing dates. Ninety-six uniformity trials of 3×3 m were performed and each assay was divided into 36 basic experimental units (BEU) of 0.5×0.5 m. The 96 uniformity trials were distributed in four cultivars and three sowing dates. At the flowering stage, FM and DM were determined in each BEU. Then, the Xo was determined in each uniformity assay, using the maximum curvature method of the coefficient of variation model. In oat, there is variability of Xo among cultivars and sowing dates to measure FM and DM. For the four cultivars on the three sowing dates, the Xo of 1.66 m2 and of 1.73 m2 are suitable to evaluate FM and DM, respectively. Four replications to evaluate the maximum of 50 treatments in completely randomized design and randomized blocks design are sufficient so that the differences among treatment means of 44.75% of the experiment mean may be significant, using the Tukey test at 5% probability to measure FM and DM in oat.
The objective of the present study was to fit Gompertz and Logistic nonlinear to descriptions of morphological traits of sunn hemp. Two uniformity trials were conducted and the crops received identical treatment in all experimental area. Sunn hemp seeds were sown in rows 0.5 m apart with a plant density of 20 plants per row meter in a usable area of 52 m × 50 m. The following morphological traits were evaluated: plant height (PH), number of leaves (NL), stem diameter (SD), and root length (RL). These traits were assessed daily during two sowing periods—seeds were sown on October 22, 2014 (first period) and December 3, 2014 (second period). Four plants were randomly collected daily, beginning 7 days after first period and 13 days after for second period, totaling 94 and 76 evaluation days, respectively. For Gompertz models the equation was used y=a*e^((?-e?^((b-c*xi))and Logistic models the equation was used yi= a/(1+e^((-b-c*xi)). The inflection points of the Gompertz and Logistic models were calculated and the goodness of fit was quantified using the adjusted coefficient of determination, Akaike information criterion, standard deviation of residuals, mean absolute deviation, mean absolute percentage error, and mean prediction error. Differences were observed between the Gompertz and Logistic models and between the experimental periods in the parameter estimate for all morphological traits measured. Satisfactory growth curve fittings were achieved for plant height, number of leaves, and stem diameter in both models using the evaluation criteria: coefficient of determination (R²), Akaike information criterion (AIC), standard deviation of residuals (SDR), mean absolute deviation (MAD), mean absolute percentage error (MAPE), and mean prediction error (MPE).
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