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.

ABSTRACT The objectives of this study were to evaluate the agronomic performance of nine lettuce cultivars (Gloriosa, Pira Verde, Stella, Ceres, Grandes Lagos, Rubinella, Crocantela, Elisa and Vera), in three seasons (autumn-winter, spring and summer) and evaluate the effect of shade netting in spring and summer. Ten experiments were carried out, using the soilless cultivation systems in a sheltered environment. The experimental design was completely randomized, six benches were used in the autumn-winter season and four in both spring and summer, with 44 pots per bench. Lettuce seedlings were transplanted into 3-liter pots filled with sand. During the spring and summer seasons experiments were conducted with and without a 18% black shade netting placed 1.5 m above the plants. Nutritional supply was provided by nutrient solution recirculating in an automatically operated irrigation system. The evaluated traits were as follows: number of leaves, fresh and dry leaf matter, stem length, stem diameter, fresh and dry stem matter, fresh and dry shoot matter, root length and fresh and dry root matter. The cultivars Gloriosa (in autumn-winter), Grandes Lagos and Gloriosa (in the spring) and Crocantela and Vera (in the summer), presented greater matter yield and are deemed the most suitable for cultivation in these seasons. The use of a shade netting within the sheltered environment did not improve the performance of the cultivars and its use is not necessary in the spring and summer.

RESUMEN El objetivo de este trabajo fue evaluar agronómicamente nueve cultivares de lechuga (Gloriosa, Pira Verde, Stella, Ceres, Grandes Lagos, Rubinella, Crocantela, Elisa y Vera), en tres estaciones del año (otoño-invierno, primavera y verano), y el efecto de la malla de sombreado en los períodos de primavera y verano. Se realizaron diez experimentos, utilizando la técnica de cultivo sin suelo, en ambiente protegido. Se empleó un diseño experimental completamente al azar, en seis mesas en la temporada de otoño-invierno y cuatro en primavera y verano, con 44 macetas por mesa. Cada maceta tenía una capacidad de 3 L, y fueron llenadas con arena para el posterior trasplante de los plantines de lechuga. En la primavera y el verano se realizaron experimentos con y sin malla de sombreo. La malla utilizada fue de color negro, con un 18% de sombra, a 1,5 m sobre el cultivo. El suministro nutricional se se hizo por medio de una disolución nutritiva en sistema de fertirriego recirculante automático. Los parámetros evaluados fueron número de hojas, peso de materia fresca y seca de hojas, longitud del tallo, diámetro del tallo, peso de materia fresca y seca del tallo, peso de materia fresca y seca de parte aérea, longitud de raíces y peso de materia fresca y seca de raíces. Los cultivares Gloriosa (en la estación otoño-invierno), Grandes Lagos y Gloriosa (en la estación primavera) y Crocantela y Vera (en la estación verano) presentaron la mayor producción y son los más indicados para el cultivo en esas estaciones. La malla de sombreo en el interior del ambiente protegido no ha mejorado el rendimiento de los cultivares y su uso no es necesario en primavera y verano.

Resumo: O objetivo deste trabalho foi avaliar a interferência do número de repetições na precisão experimental, em milho (Zea mays). Foram utilizados dados de produtividade de grãos de 15 cultivares de milho, avaliada em blocos ao acaso, com nove repetições (r = 9). A partir do experimento com nove repetições, formaram-se experimentos pelas combinações de 2, 3, ..., r-1 repetições. Para cada experimento, foi realizada a análise de variância. Foram calculadas estatísticas de precisão experimental e medidas de tendência central e de variabilidade, confeccionados diagramas de dispersão e ajustados modelos dessas estatísticas em função do número de repetições. O número de repetições foi determinado pela análise visual dos gráficos das estatísticas de precisão experimental. O aumento do número de repetições melhora a precisão experimental, mas diminui os ganhos. Portanto, o aumento do número de repetições é importante para aumentar a discriminação das cultivares de milho. Recomendam-se seis repetições como referência para experimentos com cultivares de milho. O índice de diferenciação de Fasoulas, baseado no percentual de contrastes significativos, é uma estatística apropriada para avaliar a precisão experimental.

Abstract: The objective of this work was to evaluate the influence of the number of replicates on experimental precision in corn (Zea mays). Data on the grain yield of 15 corn cultivars, evaluated in a randomized complete block design, with nine replicates (r = 9), were used. From the experiment with nine replicates, further experiments were conducted with combinations of 2, 3, ..., r-1 replicates. The analysis of variance was carried out for each experiment. Experimental precision statistics and central tendency and variability measures were calculated, dispersion diagrams were prepared, and models of these statistics were adjusted as a function of the number of replicates. The number of replicates was determined by the visual analysis of the graphs with the experimental precision statistics. Increasing the number of replicates improves the estimates of experimental precision but decreases gains. Therefore, the increase in the number of replicates is important to improve corn cultivar discrimination. Six replicates are recommended as the benchmark for experiments with corn cultivars. Fasoulas’ differentiation index, based on the percentage of significant contrasts, is an appropriate statistic for evaluating experimental precision.

ABSTRACT This study aims to determine the most suitable model to estimate the leaf area of dwarf pigeon pea in function of the leaf central leaflet dimension. Six samplings of 200 leaves were performed in the first experiment, at 36, 42, 50, 56, 64, and 72 days after emergence (DAE). In the second experiment, seven samplings of 200 leaves were performed at 29, 36, 43, 49, 57, 65, and 70 DAE, totaling 2600 leaves. The length (L) and width (W) of the central leaflet were measured in all leaves composed by left, central, and right leaflets, the product of length times width (LW) was calculated, and the leaf area (Y – sum of left, central, and right leaflet areas) was determined by digital images. Linear, power, quadratic, and cubic models of Y as function of L, W, and LW were built using data from the second experiment. Leaves from the first experiment were used to validate the models. In dwarf pigeon pea, the linear (Ŷ = – 0.4088 + 1.6669x, R2 = 0.9790) is preferable, but power (Ŷ = 1.6097x1.0065, R2 = 0.9766), quadratic (Ŷ = – 0.3625 + 1.663x + 0.00007x2, R2 = 0.9790), and cubic (Ŷ = 0.7216 + 1.522x + 0.005x2 – 5E–05x3, R2 = 0.9791) models in function of LW are also suitable to estimate the leaf area obtained by digital images. The power model (Ŷ = 5.2508x1.7868, R2 = 0.95) based on the central leaflet width is less laborious because requires only one variable, but it presents accuracy reduction.

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 The objectives of this study were to determine the optimum plot size (Xo) and the number of replications to evaluate grain yield and verify the variability of Xo among oat cultivars. Thirtytwo uniformity trials of 3 × 3 m were performed, being 8 from each cultivar (URS Charrua, URS Taura, URS Estampa, and URS Corona). Each uniformity trial was divided in 36 basic experimental units (BEU) of 0.5 × 0.5 m. Grain yield was determined in each BEU. The Xo was determined by the method of maximum curvature of the coefficient of variation model. Mean comparisons among cultivars were performed by the Scott-Knott test via bootstrap. The number of replications was calculated by an iterative process until convergence for experiments in completely randomized design (CRD) and randomized block design (RBD). Scenarios formed by i combinations (i = 3, 4, …, 50) treatments — with d least differences among treatment means to be detected as significant at 5% probability of type I error by Tukey test, expressed as a percentage of the overall experimental mean (d = 10%, 15%, 20%, 25%, 30%, 35%, 40%, and 45%) — were planned. The Xo of 1.57 m2 is enough to evaluate the grain yield in these 4 oat cultivars. Four replications to evaluate grain yield with up to 50 treatments in the experimental designs of CRD and RBD are enough to identify significant differences among treatment means of 40.53% of the overall experimental mean, by Tukey test at 5% probability of type I error.

ABSTRACT The objectives of this work were to determine the optimum plot size and number of repetitions to evaluate the fresh matter weight of vetch (Vicia sativa L.) in sowing densities. Fortyeight uniformity trials of 6 m × 6 m were conducted. Sixteen trials were evaluated in each sowing density (40, 60, and 80 kg∙ha−1). Each trial was divided into 36 basic experimental units (BEU) of 1 m × 1 m, totaling 1,728 BEU. In each BEU, the fresh matter was weighed. The optimum plot size was determined by the method of maximum curvature of the coefficient of variation model. The means were compared among sowing densities by the Scott-Knott’s test. The number of repetitions — for experiments with completely randomized and randomized block designs, in scenarios of i treatments (i = 3, 4, …, 50) and d minimal differences between treatments means being detected as significant with 5% probability by Tukey’s test, expressed in percentage of the experiment average (d = 10%, 11%, …, 20%), was determined by iterative process until convergence. The optimum plot size to evaluate the fresh matter weight of vetch is 4.52 m2 at the 3 sowing densities. Four repetitions, to evaluate up to 50 treatments, in completely randomized and randomized block designs, are enough to identify as significant, at 5% probability by Tukey’s test, differences between treatment means of 29.15% of the experiment average.

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.

Os objetivos deste trabalho foram determinar o tamanho ótimo de parcela e o número de repetições, para avaliar a massa verde de ervilha forrageira (Pisum sativum subsp. arvense (L.) Poir). Foram realizados 27 ensaios de uniformidade de 5m×5m (25m2). Cada ensaio foi dividido em 25 unidades experimentais básicas (UEB) de 1m×1m, totalizando 675UEB. Foi pesada a massa verde das plantas de cada UEB. Nove ensaios (225UEB) foram avaliados aos 92 dias após a semeadura (DAS), nove ensaios (225UEB) foram avaliados aos 98 DAS e os outros nove ensaios (225UEB) aos 106 DAS. O tamanho ótimo de parcela (Xo) foi determinado por meio do método da curvatura máxima do modelo do coeficiente de variação e as comparações de médias, entre as épocas de avaliação, foram feitas pelo teste t de Student. O número de repetições, para experimentos nos delineamentos inteiramente casualizado 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 determinado por processo iterativo até a convergência. O tamanho ótimo de parcela para avaliar a massa verde de ervilha forrageira é de 5,03UEB de 1m2 (5,03m2). Quatro repetições, para avaliar até 50 tratamentos, nos delineamentos inteiramente casualizado e blocos ao acaso, são suficientes para identificar, como significativas a 5% de probabilidade, pelo teste de Tukey, diferenças entre médias de tratamentos de 32,4% da média do experimento.

The objectives of this research were to determine the optimum plot size and number of repetitions and to evaluate the fresh weight of forage pea (Pisum sativum subsp. arvense (L.) Poir). Twenty-seven uniformity trials of 5m×5m (25m2) were conducted. Each trial was divided in 25 basic experimental units (UEB) of 1m×1m, totaling 675UEB. The fresh weight of plants, in each UEB was weighed. Nine trials (225UEB) were evaluated at 92 days after sowing, nine trials (225UEB) at 98 days after sowing and the other nine trials (225UEB) at 106 days after sowing. The optimum plot size (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 interative process until convergence. The optimum plot size to evaluate the fresh weight of forage pea is 5.03UEB was of 1m2 (5.03m2). Four replications, to evaluate up to 50 treatments, in completely randomized and randomized block designs, are sufficient to identify, as significant at the 5% probability by Tukey test, differences between treatment means 32.4% of the average experiment.

O objetivo deste trabalho foi modelar e identificar os melhores modelos para a estimação da área foliar determinada por fotos digitais, de três híbridos de canola, em função do comprimento, ou da largura e/ou do produto comprimento vezes largura do limbo foliar. Foram conduzidos três ensaios de uniformidade com canola (Brassica napus L.), e em cada ensaio avaliou-se um dos seguintes híbridos: Hyola 61, Hyola 76 e Hyola 433. Em cada híbrido, foram coletadas 125 folhas aos 77, 84, 91 e 97 dias após a semeadura, totalizando 1.500 folhas. Nessas 1.500 folhas, foram mensurados o comprimento (C) e a largura (L), e calculado o produto do comprimento vezes a largura (C×L) do limbo foliar. Determinou-se a área foliar de cada folha, por meio do método de fotos digitais (Y). Posteriormente, para cada híbrido, foram separadas, aleatoriamente, 80% das folhas (100 folhas por coleta × 4 coletas por híbrido = 400 folhas por híbrido) para a geração de modelos do tipo quadrático, potência e linear, de Y em função do C, da L, e/ou do C×L. Os 20% das folhas restantes (100 folhas por híbrido) foram usadas, separadamente, para a validação dos modelos. Em canola, os modelos do tipo potência, para os híbridos Hyola 61 (Ŷ = 1,3000x1,9336, R2 = 0,9531), Hyola 76 (Ŷ = 1,0579x2,0383, R2 = 0,9733) e Hyola 433 (Ŷ = 1,4154x1,9096, R2 = 0,9613), são adequados para a estimação da área foliar determinada por fotos digitais (Y) em função da largura do limbo foliar (x).

The objective of this work was to model and identify the best models to estimate the leaf area determined by digital photos, of three canola hybrid, with the length or width and / or the product length width of the leaf. Three uniformity trials were carried with the culture of canola (Brassica napus L.). In each trial was valued one of the following hybrids: Hyola 61, Hyola 76, Hyola 433. In each hybrid were collected 125 leaves at 77, 84, 91, 97 days after sowing, totaling 1,500 leaves. In these 1,500 leaves were measured length (C) and width (L) and calculated the length width (C×L) of the leaf. Was determined the leaf area of each leaf, by the method of digital photos (Y). After, for each hybrid were separated, randomly, 80% of the leaves (100 leaves by collects × 4 collects by hybrid = 400 leaves per hybrid) to build models of quadratic, potency and linear type for Y function of the C, L and/or C×L. The remaining 20% of the leaves (100 leaves by hybrid), separately, were used to validate the models. In canola, the potency model for hybrid Hyola 61 (Ŷ = 1.3000x1.9336, R2 = 0.9531), Hyola 76 (Ŷ = 1.0579x2.0383, R2 = 0.9733) and Hyola 433 (Ŷ = 1.4154x1.9096, R2 = 0.9613), are adequate for estimation of leaf area determined by digital photos (Y) as function of the width of the leaf (x).

Os objetivos deste trabalho foram determinar o tamanho ótimo de parcela e o número de repetições, para avaliar a massa verde de canola (Brassica napus L.). Foram realizados 27 ensaios de uniformidade de 5m×5m (25m2), sendo nove ensaios para cada um dos seguintes híbridos: Hyola 61, Hyola 76 e Hyola 433. Cada ensaio foi dividido em 25 unidades experimentais básicas (UEB) de 1m×1m, totalizando 675 UEB. Foi pesada a massa verde das plantas de cada UEB. O tamanho ótimo de parcela (Xo) foi determinado por meio do método da curvatura máxima do modelo do coeficiente de variação, e as comparações de médias, entre os híbridos, foram feitas pelo teste de Scott-Knott. 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%, 13%, ..., 40%), foi determinado por processo iterativo até a convergência. O tamanho ótimo de parcela para avaliar a massa verde de canola é 6,41m2. Quatro repetições, para avaliar até 50 tratamentos, nos delineamentos inteiramente casualizados e blocos ao acaso, são suficientes para identificar, como significativas a 5% de probabilidade, pelo teste de Tukey, diferenças entre médias de tratamentos de 41,4% da média do experimento.

The objectives of this work were to determine the optimum plot size and number of repetitions, to evaluate the fresh weight of canola (Brassica napus L.). Twenty-seven uniformity trials of 5m×5m (25m2) were conducted. Each trials was divided in 25 basic experimental units (BEU) of 1m×1m, totaling 675BEU. The fresh weight of plants, in each BEU was weighed. The optimum plot size (Xo) was determined by the method of maximum curvature of the model coefficient of variation and the means compared, among hybrids, by Scott-Knott 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%, ..., 40%), was determined by iterative process until convergence. The optimum plot size to evaluate the fresh weight of canola is 6.41 m2. Four replications, to evaluate up to 50 treatments, in completely randomized and randomized block designs, are sufficient to identify, as significant at the 5% probability by Tukey test, differences between treatment means 41.4% of the average experiment.