ABSTRACT The objective of this study was to fit the Logistic growth model for plant height and number of nodes of two buckwheat cultivars at sowing times, as well as comparing the cultivars and sowing times. Twenty uniformity trials were carried out, formed by the combination of two buckwheat cultivars (IPR91-Baili and IPR92-Altar), sown at five times, for two consecutive years. Evaluations were carried out twice a week throughout the vegetative stage until the end of flowering. In each evaluation, five plants were randomly collected from each trial to measure plant height and count the number of nodes on the main stem. The logistic model was fitted with the values of the five plants of each evaluation. Model parameters were estimated, as well as their respective confidence intervals. The goodness of fit of the model was assessed through the coefficient of determination, Akaike information criterion, and residual standard deviation. The plant height and number of nodes of buckwheat, cultivars IPR91-Baili and IPR92-Altar, were described by the Logistic model. The Logistic model satisfactorily describes the growth of buckwheat plants, and a specific fit considering each cultivar and sowing time is needed.

ABSTRACT: It is important to determine the number of plants to be evaluated to allow accurate inferences about the traits under evaluation. Investigating the linear relations among traits is important for identifying traits for indirect selection. So, the objectives of this study were to determine the sample size (number of plants) necessary to estimate the means of forage pea traits and to investigate the relations among the traits. Experiments were carried out in 2021 with three sowing dates (May 3, May 26 and July 13). Five hundred plants were randomly sampled, 100 plants in each of the five evaluation dates (June 25, August 30, July 24, September 17, September 16). In these 500 plants, the traits plant height, number of branches, number of nodes, number of leaves, number of pods, fresh matter of leaves, fresh matter of stems, fresh matter of pods, fresh matter of shoots, dry matter of leaves, dry matter of stems, dry matter of pods, and dry matter of shoots, were evaluated. The sample size was calculated to estimate the means of these traits, based on Student’s t-distribution, and the relations among traits were investigated through correlation and path analysis. In an experiment, to estimate the means of these 13 traits of forage pea, with an estimation error of approximately 10% of the mean, 99 plants per treatment should be sampled. The numbers of pods and leaves have a positive linear relations with fresh and dry matter of shoots.

RESUMO: É importante dimensionar o número de plantas a serem avaliadas para possibilitar inferências precisas sobre os caracteres em avaliação. Investigar as relações lineares entre caracteres é importante para a identificação de caracteres para a seleção indireta. Assim, os objetivos deste trabalho foram determinar o tamanho de amostra (número de plantas) necessário para a estimação da média de caracteres de ervilha forrageira e investigar as relações entre os caracteres. Foram conduzidos experimentos, no ano de 2021, em três datas de semeadura (03 de maio, 26 de maio e 13 de julho). Foram amostradas, aleatoriamente, 500 plantas, sendo 100 plantas em cada uma das cinco datas de avaliação (25 de junho, 30 de agosto, 24 de julho, 17 de setembro e 16 de setembro). Nessas 500 plantas avaliaram-se os caracteres altura de planta, número de ramificações, número de nós, número de folhas, número de legumes, matéria fresca de folhas, matéria fresca de caule, matéria fresca de legumes, matéria fresca de parte aérea, matéria seca de folhas, matéria seca de caule, matéria seca de legumes e matéria seca de parte aérea. Foi calculado o tamanho de amostra para a estimação da média desses caracteres, com base na distribuição t de Student e investigada a relação entre os caracteres por meio de análises de correlação e de trilha. Em um experimento, para a estimação da média desses 13 caracteres de ervilha forrageira, com erro de estimação de aproximadamente 10% da média, devem ser amostradas 99 plantas por tratamento. Os números de legumes e de folhas têm relação linear positiva com as matérias fresca e seca de parte aérea.

ABSTRACT Investigation of multicollinearity allows parameters in multivariate analysis to be estimated with higher precision and with biological interpretation. In order to generate reliable estimates of the degree of multicollinearity, it is necessary to use appropriate sample size. Thus, the objectives of this study were to determine the sample size (number of plants) necessary to estimate the indicators of the degree of multicollinearity - condition number (CN), correlation matrix determinant (DET), and variance inflation factor (VIF) - in morphological traits of rye and to verify the variability of the sample size between the indicators. Five and three uniformity trials were conducted with the cultivars BRS Progresso and Temprano, respectively. Eight morphological traits were evaluated in 780 plants in eight trials. For each trial, 22 cases were selected among the 28 formed by the combination of eight traits, taken six by six, totaling 176 cases. In each case, 197 sample sizes were planned (20, 25, 30, ..., 1,000 plants) and in each size 2,000 resampling procedures with replacement were performed, CN, DET, and VIF were determined and the average among 2,000 estimates was calculated. For each case and indicator (CN, DET, and VIF), the sample size was determined through three models: modified maximum curvature method and linear and quadratic segmented models with plateau response. There is variability between sample sizes between indicators, with larger sample sizes required for DET, followed by CN and VIF, in that order, with at least 180, 116 and 85 plants, respectively.

RESUMO A investigação da multicolinearidade permite que parâmetros em análises multivariadas sejam estimados com maior precisão e com interpretação biológica. Para ter confiabilidade nas estimativas do grau de multicolinearidade, é necessário utilizar adequado tamanho de amostra. Assim, os objetivos deste trabalho foram determinar o tamanho de amostra (número de plantas) necessário para a estimação dos indicadores do grau de multicolinearidade - número de condição (NC), determinante da matriz de correlação (DET) e fator de inflação da variância (FIV) -em caracteres morfológicos de centeio e verificar a variabilidade do tamanho de amostra entre os indicadores. Foram conduzidos cinco e três ensaios de uniformidade com as cultivares BRS Progresso e Temprano, respectivamente. Foram avaliados oito caracteres morfológicos em 780 plantas em oito ensaios. Para cada ensaio, foram selecionados 22 casos entre os 28 formados pela combinação de oito caracteres, tomados seis a seis, totalizando 176 casos. Para cada caso, foram planejados 197 tamanhos de amostra (20, 25, 30, ..., 1.000 plantas) e para cada tamanho foram realizadas 2.000 reamostragens, com reposição, determinados o NC, DET e FIV e calculada a média das 2.000 estimativas. Após, para cada caso e indicador, foi determinado o tamanho de amostra, por meio de três modelos: método da máxima curvatura modificado e modelos linear e quadrático segmentados com resposta em platô. Há variabilidade entre os tamanhos de amostra entre os indicadores, com necessidade de maiores tamanhos de amostra para DET, seguido de NC e FIV, nessa ordem, com no mínimo de 180, 116 e 85 plantas, respectivamente.

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 different levels of precision. A higher condition number of repeatability coefficients 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 efficiently 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.

Abstract The objective of this work was to determine the sample size necessary for estimating the means of wheat (Triticum aestivum) traits, obtained through measurement, counting, and weighing. Seventeen uniformity trials were performed with 1,790 plants harvested randomly, whose following traits were evaluated: lengths of the main stem and main stem ear (measurement); number of leaves, stems, and ears (counting); and mass of fresh and dry matter of leaves, stems, and ears (weighing). The Bartlett and Kolmogorov-Smirnov tests and Welch’s analysis of variance were performed. Skewness, central tendency, and variability were determined, and sample size was calculated to estimate the means of the 13 evaluated traits, considering estimation errors (semi-amplitudes of the 95% confidence interval) equal to 5, 10, 15, and 20% of the mean. There is a decrease in the sample size to estimate the means of wheat traits obtained through weighing, counting, and measuring, in this order. In an experiment to estimate the mean of wheat traits obtained by weighing, counting, and measuring with a maximum error of 10% of the mean at a 95% confidence interval, 117, 76, and 9 plants per treatment are needed, respectively.

Resumo O objetivo deste trabalho foi determinar o tamanho de amostra necessário para estimar a média de caracteres de trigo (Triticum aestivum) obtidos por meio de medição, contagem e pesagem. Dezessete ensaios de uniformidade foram feitos com 1,790 plantas colhidas aleatoriamente, cujos seguintes caracteres foram avaliados: comprimentos do colmo principal e da espiga do colmo principal (medição); número de folhas, colmos e espigas (contagem); e massa de matéria fresca e seca de folhas, colmos e espigas (pesagem). Realizaram-se os testes de Bartlett e Kolmogorov-Smirnov e a análise de variância de Welch. Determinaram-se as medidas de assimetria, tendência central e variabilidade, e calculou-se o tamanho de amostra para a estimação da média dos 13 caracteres avaliados, tendo-se considerado erros de estimação (semiamplitudes do intervalo de confiança de 95%) iguais a 5, 10, 15 e 20% da média. Há um decréscimo do tamanho de amostra para estimar a média dos caracteres de trigo obtidos por meio de pesagem, contagem e medição, nesta ordem. Em um experimento para estimar a média dos caracteres de trigo obtidos por pesagem, contagem e medição com erro máximo de 10% da média e nível de confiança de 95%, são necessárias 117, 76 e 9 plantas por tratamento, respectivamente.

RESUMO O objetivo deste trabalho foi comparar três métodos de estimação do tamanho ótimo de parcela para avaliar a matéria fresca de aveia preta (Avena strigosa Schreb), ervilhaca (Vicia sativa L.) e nabo forrageiro (Raphanus sativus L.), cultivadas em consórcio. Foram conduzidos seis ensaios de uniformidade com o consórcio de aveia preta, ervilhaca e nabo forrageiro, sendo três ensaios avaliados aos 84 dias após a semeadura e os outros três ensaios aos 119 dias após a semeadura. Foi avaliada a matéria fresca em 216 unidades experimentais básicas (36 por ensaio) de 1 m × 1 m. Foi determinado o tamanho ótimo de parcela por meio dos métodos da curvatura máxima modificado, do modelo linear de resposta com platô e do modelo quadrático de resposta com platô. O tamanho ótimo de parcela difere entre os métodos e decresce na seguinte ordem: modelo quadrático de resposta com platô (15,13 m2), modelo linear de resposta com platô (8,24 m2) e curvatura máxima modificado (5,62 m2). O tamanho ótimo de parcela para avaliar a matéria fresca de aveia preta, ervilhaca e nabo forrageiro, cultivadas em consórcio é de 15,13 m2. Esse tamanho pode ser utilizado como referência para futuros experimentos.

ABSTRACT The objective of this work was to compare three methods of estimating the optimal plot size to evaluate the fresh matter in black oat (Avena strigosa Schreb), common vetch (Vicia sativa L.) and forage turnip (Raphanus sativus L.) intercropping. Six uniformity trials with black oat, common vetch and forage turnip intercropping were carried out. Three trials were evaluated at 84 days after sowing and the other three trials at 119 days after sowing. The fresh matter was evaluated in 216 basic experimental units (36 per trial) of 1 m × 1 m. The optimal plot size was determined using the methods of modified maximum curvature, linear response and plateau model and quadratic response and plateau model. The optimal plot size differs between the methods and decreases in the following order: quadratic response and plateau model (15.13 m2), linear response and plateau model (8.24 m2) and modified maximum curvature (5.62 m2). The optimal plot size for assessing the fresh matter of black oat, common vetch and forage turnip, grown in intercropping, is 15.13 m2. This size can be used as a reference for future experiments.

RESUMO - O objetivo deste trabalho foi determinar o tamanho ótimo de parcela para avaliar a massa de matéria fresca de milheto (Pennisetum glaucum L.) e de crotalária ochroleuca (Crotalaria ochroleuca) em cenários formados por combinações de números de tratamentos, números de repetições e níveis de precisão experimental. Foram conduzidos 15 ensaios de uniformidade com milheto e crotalária ochroleuca, em cultivo solteiro e em consórcio. Foi avaliada a massa de matéria fresca em 540 unidades experimentais básicas (UEB) de 1 m × 1 m (15 ensaios × 36 UEB por ensaio). Foi estimado o índice de heterogeneidade do solo de Smith (1938). Foi determinado o tamanho de parcela por meio do método de Hatheway (1961) em cenários formados pelas combinações de i tratamentos (i = 5, 10, 15 e 20), r repetições (r = 3, 4, 5, 6, 7 e 8) e d níveis de precisão (d = 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18% e 20%). Para avaliar a massa de matéria fresca de milheto e de crotalária ochroleuca, em cultivo solteiro ou em consórcio, nos delineamentos inteiramente casualizado ou de blocos completos ao acaso, com 5 a 20 tratamentos e com cinco repetições, parcelas de 10 m² de área útil são suficientes para que diferenças entre tratamentos de 10% da média geral do experimento sejam consideradas significativas a 0.05 de probabilidade.

ABSTRACT - The objective of this study was to determine the optimal plot size to evaluate fresh matter in millet (Pennisetum glaucum L.) and slender leaf rattlebox (Crotalaria ochroleuca), in scenarios formed by combinations of numbers of treatments, numbers of replicates, and levels of precision. Fifteen uniformity trials with millet and slender leaf rattlebox, in single cropping or intercropping, were carried out. Fresh matter was evaluated in 540 basic experimental units (BEU) of 1 m × 1 m (15 trials × 36 BEU per trial). The soil heterogeneity index of Smith (1938) was estimated. Plot size was determined by the method of Hatheway (1961) in scenarios formed by combinations of i treatments (i = 5, 10, 15 and 20), r replicates (r = 3, 4, 5, 6, 7 and 8), and d precision levels (d = 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18% and 20%). To evaluate the fresh matter of millet and slender leaf rattlebox, in single or intercropping, in experiments in completely randomized or randomized block designs, with 5 to 20 treatments and with five replicates, plots with 10 m² of usable area are sufficient for differences between treatments of 10% of the overall mean of the experiment to be considered significant at 0.05 probability level.

RESUMO Pendões de milho, com maior comprimento e maior número de ramificações acabam impedindo a passagem da radiação solar para o dossel superior da planta e atuam como dreno de fotoassimilados, sendo que, poderiam ser destinados a produção de grãos. O objetivo deste trabalho foi verificar se há divergência genética, em relação à produtividade de grãos e os caracteres de pendão entre os cultivares de milho, em três anos agrícolas. Foram avaliados 20 cultivares de milho e mensurados 11 caracteres de pendão e a produtividade de grãos. Para cada caractere, foram realizadas as análises de variância individual e conjunta. Foi realizada a análise de componentes principais, determinada a matriz da distância generalizada de Mahalanobis entre os cultivares e realizada a análise de divergência genética, por meio do método de agrupamento da ligação média entre grupo (UPGMA) e, a partir disso, foi construído o dendrograma. Para validação do agrupamento calculou-se o coeficiente de correlação cofenética. Existe divergência genética entre os cultivares de milho e foram formados seis grupos de cultivares. O comprimento do pendão, o número total de ramificações, a massa de matéria seca da espiga central e a produtividade de grãos são os caracteres que mais contribuem para a divergência genética entre os cultivares de milho.

ABSTRACT Maize tassels with a longer length and higher number of branches prevent the passage of solar radiation into the upper plant canopy and act as a drain for photoassimilates that could be used for grain production. This study aimed to verify if there is genetic divergence regarding grain yield and tassel traits among maize cultivars in three agricultural years. Twenty maize cultivars were evaluated and 11 tassel traits and grain yield were measured. Individual and joint analyses of variance were performed for each trait. Principal component analysis was performed, the generalized Mahalanobis distance matrix between cultivars was determined, and the genetic divergence analysis was performed, using the unweighted pair group method with arithmetic mean (UPGMA), which allowed constructing the dendrogram. The cophenetic correlation coefficient was calculated to validate the cluster. There is genetic divergence among maize cultivars and six groups of cultivars were formed. Tassel length, total number of branches, central spike dry matter, and grain yield are the traits that most contribute to the genetic divergence among maize cultivars.

RESUMO O objetivo deste trabalho foi determinar o tamanho ótimo de parcela para avaliar a massa de matéria fresca de trigo mourisco (Fagopyrum esculentum Moench) das cultivares IPR91-Baili e IPR92-Altar, em cenários formados por combinações de números de tratamentos, números de repetições e níveis de precisão experimental. Foram conduzidos 16 ensaios de uniformidade (experimentos em branco), sendo oito com a cultivar IPR91-Baili e oito com a cultivar IPR92-Altar. Os ensaios foram realizados em oito épocas de semeadura. Foi avaliada a massa de matéria fresca em 576 unidades experimentais básicas (UEB) de 1 m * 1 m (36 UEB por ensaio). Foi estimado o índice de heterogeneidade do solo de Smith (1938). Foi determinado o tamanho de parcela por meio do método de Hatheway (1961) em cenários formados pelas combinações de i tratamentos (i = 5, 10, 15 e 20), r repetições (r = 3, 4, 5, 6, 7 e 8) e d níveis de precisão (d = 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19% e 20%). Para avaliar a massa de matéria fresca de trigo mourisco das cultivares IPR91-Baili e IPR92-Altar, nos delineamentos inteiramente casualizado e blocos completos ao acaso, com 5 a 20 tratamentos e oito repetições, parcelas de 8 m3 de área útil são suficientes para identificar diferenças significativas entre tratamentos, a 5% de probabilidade, de 15% da média geral do experimento.

ABSTRACT The objective of this work was to determine the optimal plot size to evaluate the fresh weight in buckwheat (Fagopyrum esculentum Moench) of the IPR91-Baili and IPR92-Altar cultivars, in scenarios formed by combinations of numbers of treatments, numbers of replicates, and levels of experimental precision. Sixteen uniformity trials (blank experiments) were carried out, eight with cultivar IPR91-Baili and eight with cultivar IPR92-Altar. The trials were performed in eight sowing dates. The fresh weight was evaluated in 576 basic experimental units (BEU) of 1 m x 1 m (36 BEU per trial). The soil heterogeneity index of Smith (1938) was estimated. The plot size was determined by the method of Hatheway (1961) in scenarios formed by combinations of i treatments (i = 5, 10, 15, and 20), r replicates (r = 3, 4, 5, 6, 7, and 8), and d precision levels (d = 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, and 20%). To evaluate the fresh weight in buckwheat of the IPR91-Baili and IPR92-Altar cultivars, in experiments under completely randomized and randomized block designs, with 5 to 20 treatments and eight replicates, plots of 8 m3of useful area are sufficient to identify significant differences between treatments, at 5% probability level, of 15% of the overall mean of the experiment.

ABSTRACT The aim of this study was to determine the optimum plot size to evaluate the fresh matter of aerial part of dwarf pigeon pea (Cajanus cajan (L.) Millsp), cultivar IAPAR 43 (Aratã), in scenarios formed by combinations of numbers of treatments, number of replications, and precision levels. The fresh matter of aerial part was weighed on basic experimental units of 1 m × 1 m in three uniformity trials with size of 24 m × 12 m (288 m2 in each trial). The soil heterogeneity index of Smith was estimated. Also, the optimum plot size was determined by Hatheway’s method in scenarios formed by combinations of i treatments (i = 5, 10, 15, and 20), r replications (r = 3, 4, 5, 6, 7 8, 9, and 10), and d precision levels (d = 5%, 10%, 15%, 20%, 25%, and 30%). In experiments designed on randomized block design with 5 to 20 treatments and four replications, plots with 9 m2 were enough to identify significant differences among treatments regarding the fresh matter of aerial part in dwarf pigeon pea at 5% probability of 30% of the experiment overall mean.

Abstract Phyllochron and leaf appearance rate are both important parameters in the production efficiency of agricultural crops. The objectives of this study were to determine the phyllochron and leaf appearance rate in 4 oat cultivars (Avena sativa L.) in 3 sowing dates and verify the variability of phyllochron and leaf appearance rate among cultivars and sowing dates. The experimental design was the completely randomized with 12 treatments and 20 repetitions. Treatments were formed by the combination of 4 cultivars (URS Charrua, URS Taura, URS Estampa, and URS Corona) and 3 sowing dates in 2014 (April 28, May 28, and July 14). In each plant (repetition) of each treatment, the number of expanded leaves (NEL) was counted 3 times per week from the first leaf emission until flowering. For each plant, cultivar, and sowing date, linear regression was adjusted between NEL and accumulated thermal time (ATT) and between NEL and number of days after emergence (DAE). Phyllochron was determined by the inverse of the angular coefficient of the linear regression between the NEL and ATT. The leaf appearance rate was determined by the inverse of the angular coefficient of the linear regression between NEL and DAE. In oat, there is variability of phyllochron and leaf appearance rate among cultivars and sowing dates. Phyllochron oscillates between 95.88 and 117.70 °C day∙leaf−1 and leaf appearance rate, between 6.41 and 9.65 days∙leaf−1. The oat cropping management in function of phyllochron and leaf appearance rate is dependent on cultivars and sowing dates.

RESUMO Os objetivos deste trabalho foram avaliar as relações lineares entre caracteres de linho (Linum usitatissimum L.) e identificar caracteres para a seleção indireta. Em área experimental de 15 × 15 m (225 m2), aos 134 dias após a semeadura, foram selecionadas, aleatoriamente, 300 plantas. Em cada planta, foram mensurados os caracteres altura de planta, número de ramos, número de cápsulas, massa verde de cápsulas, massa verde de parte aérea sem cápsulas, massa verde de parte aérea, massa seca de cápsulas, massa seca de parte aérea sem cápsulas e massa seca de parte aérea. Para cada caractere, foi calculada a média e o coeficiente de variação. Foi investigada a relação linear entre os caracteres por meio de análises de correlação e de trilha. Na cultura de linho, o número de cápsulas tem relação linear positiva com as massas verde e seca de cápsulas e de parte aérea e pode ser utilizado para seleção indireta.

ABSTRACT The objectives of this study were to evaluate the linear relations among traits of flax (Linum usitatissimum L.) and identify traits for indirect selection. In experimental area of 15 × 15 m (225 m2) 300 plants were randomly collected at 134 days after seeding. The traits plant height, number of branches, number of capsules, fresh matter of capsules, fresh matter of aerial part without capsules, fresh matter of aerial part, dry matter of capsules, dry matter of aerial part without capsules, and dry matter of aerial part were measured in each plant. The mean and coefficient of variation were calculated for each trait. It was studied the linear relation among the traits through correlation and path analysis. In flax, the number of capsules has positive linear relation with fresh and dry matter of capsules and aerial part and it can be used for indirect selection.

RESUMO: Os objetivos deste trabalho foram determinar o tamanho de amostra, em número de plantas, para a estimação da média de caracteres produtivos de feijão guandu e verificar se há variabilidade do tamanho de amostra entre caracteres e anos agrícolas. Foram conduzidos dois ensaios de uniformidade, um em 2011/2012 e o outro em 2012/2013. Em cada ensaio, foram demarcadas 360 plantas e, no florescimento, foram avaliadas as massas verde e seca de raiz, caule, folha, parte aérea e total, totalizando dez caracteres produtivos. Foram calculadas estatísticas descritivas, verificada a normalidade e a aleatoriedade e calculado o tamanho de amostra. Na cultura de feijão guandu, há variabilidade do tamanho de amostra entre os caracteres produtivos e entre os anos agrícolas. Para a estimação da média dos caracteres produtivos, com erro de estimação máximo de 20% da média e com grau de confiança de 95%, 70 plantas são suficientes.

ABSTRACT: The objectives of this study were to determine the sample size, in terms of number of plants, needed to estimate the average values of productive traits of the pigeon pea and to determine whether the sample size needed varies between traits and between crop years. Separate uniformity trials were conducted in 2011/2012 and 2012/2013. In each trial, 360 plants were demarcated, and the fresh and dry masses of roots, stems, and leaves and of shoots and the total plant were evaluated during blossoming for 10 productive traits. Descriptive statistics were calculated, normality and randomness were checked, and the sample size was calculated. There was variability in the sample size between the productive traits and crop years of the pigeon pea culture. To estimate the averages of the productive traits with a 20% maximum estimation error and 95% confidence level, 70 plants are sufficient.

RESUMO: Os objetivos deste trabalho foram determinar o tamanho ótimo de parcela e o número de repetições para avaliar a massa verde de feijão guandu ( Cajanus cajan (L.) Millsp.), em épocas e anos de avaliação. Foram realizados 80 ensaios de uniformidade de 6m×6m (36m2). Cada ensaio foi dividido em 36 unidades experimentais básicas (UEB) de 1m×1m, totalizando 2.880UEB. Foi pesada a massa verde das plantas de cada UEB. No ano agrícola 2011/2012, foram avaliados 16 ensaios aos 127 dias após a semeadura (DAS) e 24 aos 139DAS. Em 2012/2013, foram avaliados quatro ensaios em cada uma das épocas (163, 167, 170, 174, 177, 181, 184, 188, 191 e 195DAS). O tamanho ótimo de parcela foi determinado por meio do método da curvatura máxima do modelo do coeficiente de variação e as comparações de médias, entre épocas e os anos de avaliação, foram feitas pelo teste de Scott-Knott. O número de repetições, em cenários formados pelas combinações de i tratamentos (i=3, 4, ..., 50) e d diferenças mínimas entre médias de tratamentos a serem detectadas como significativas a 5% de probabilidade, pelo teste de Tukey, expressas em percentagem da média do experimento (d=10%, 15%, ..., 50%), foi determinado por processo iterativo até a convergência. O tamanho ótimo de parcela para avaliar a massa verde de feijão guandu é 8,39m2. Quatro repetições, para avaliar até 50 tratamentos, são suficientes para identificar, como significativas a 5% de probabilidade, pelo teste de Tukey, diferenças entre médias de tratamentos de 54,1% da média do experimento.

ABSTRACT: The objectives of this research were to determine the optimum plot size and number of repetitions, to evaluate the fresh weight of pigeonpea ( Cajanus cajan (L.) Millsp.), in times and years. Eighty uniformity trials of 6m×6m (36m2) were conducted. Each trial was divided in 36 basic experimental units (BEU) of 1m×1m, totaling 2,880BEU. The fresh weight of plants, in each BEU was weighed. The agricultural year 2011/2012, were evaluated 16 trials at 127 days after sowing (DAS) and 24 to 139DAS. In 2012/2013, four trials at each of times (163, 167, 170, 174, 177, 181, 184, 188, 191 and 195DAS) were evaluated. The optimum plot size was determined by the method of maximum curvature of the coefficient of variation model and the means compared, among evaluation times and years, by Scott-Knott test. The number of repetitions, in scenarios of combinations of i treatments (i=3, 4, ..., 50) and d minimal differences between treatments means, to be detected as significant, 5% probability by Tukey's test, expressed in percentage of experiment avarage (d=10%, 15%, ..., 50%), was determined by iterative process until convergence. The optimum plot size to evaluate the fresh weight of pigeonpea is was 8.39m2. Four replications, to evaluate up to 50 treatments, are sufficient to identify, as significant at 5% probability by Tukey's test, differences between treatment means of 54.1% of the average experiment.

Os objetivos deste trabalho foram determinar o tamanho ótimo de parcela (Xo) e o número de repetições para avaliar a massa verde de parte aérea de milheto em épocas de avaliação. Foram conduzidos 42 ensaios de uniformidade de 6 m×4 m (24 m2), sendo cada ensaio dividido em 24 unidades experimentais básicas (UEB) de 1 m×1 m (1 m2). Aos 52, 69 e 82 dias após a semeadura, foram avaliados, respectivamente 18, 6 e 18 ensaios, nos quais se pesou a massa verde das plantas de cada UEB. O Xo foi determinado pelo método da curvatura máxima do modelo do coeficiente de variação, e as comparações de médias entre as épocas de avaliação foram realizadas pelo teste t de Student. O número de repetições, para experimentos nos delineamentos inteiramente casualizados e blocos ao acaso, em cenários formados pelas combinações de i tratamentos (i=3, 4, ..., 50) e d diferenças mínimas entre médias de tratamentos a serem detectadas como significativas a 5% de probabilidade, pelo teste de Tukey, expressas em percentagem da média do experimento (d=10%, 12%, ..., 30%), foi realizado por processo iterativo até a convergência. O tamanho ótimo de parcela para avaliar a massa verde de parte aérea de milheto é de 4,46 m2, para as três épocas de avaliação. Para avaliar até 50 tratamentos, nos delineamentos inteiramente casualizados e blocos ao acaso, quatro repetições são suficientes para que diferenças entre médias de tratamentos de 28,75% da média do experimento sejam significativas, pelo teste de Tukey, a 5% de probabilidade.

The objectives of this work were to determine the optimum plot size (Xo) and number of repetitions, to evaluate the fresh weight of aerial part of millet, in evaluation times. Forty-two uniformity trials with 6 m×4 m (24 m2) were conducted. Each trial was divided in 24 experimental units basic (UEB) with 1 m×1 m (1 m2). At 52, 69 and 82 days after sowing were evaluated, respectively, 18, 6 and 18 trials, where the fresh weight of plants was weighed in each UEB. The Xo was determined by the method of maximum curvature of the model coefficient of variation and the means compared, among evaluation times, by Student’s t test. The number of repetitions for experiments on completely randomized and randomized block designs, in scenarios of combinations of i treatments (i=3, 4, ..., 50) and d minimal differences between treatments means, to be detected as significant, 5% probability by Tukey test, expressed in percentage of the average of the experiment (d=10%, 12%, ..., 30%), was determined by iterative process until convergence. The optimum plot size to evaluate the fresh weight of aerial part of millet is 4.46 m2, to the three evaluation times. To evaluate up to 50 treatments, in completely randomized and randomized block designs, four replications are sufficient for differences between treatment means of 28.75% of the average experiment are significant at 5% probability, by Tukey’s test.