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.

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.

RESUMEN El objetivo de este trabajo fue ajustar el modelo Logístico para las masas fresca y seca de hojas y las masas fresca y seca de parte aérea de cuatro cultivares de lechuga para describir el crecimiento en el verano. Se utilizaron los cultivares de lechuga Crocantela, Elisa, Rubinela y Vera, cultivados en el verano de los años 2017 y 2018, en ambiente protegido y cultivo sin suelo. Después de 7 días del trasplante, se determinó las masas fresca y seca de hojas y las masas fresca y seca de parte aérea de ocho plantas, estas evaluaciones se realizaron cada cuatro días. Los parámetros del modelo fueron estimados utilizando el software R, por el método de mínimos cuadrados y proceso iterativo de Gauss-Newton. También se estimaron los intervalos de confianza de los parámetros, verificados los supuestos, calculados los indicadores de calidad del ajuste, los puntos críticos y cuantificados las no linealidades paramétrica e intrínseca. El modelo de crecimiento logístico presentó un ajuste satisfactorio para las masas fresca y seca de hojas y para las masas fresca y seca de parte aérea para las cultivares de lechuga Crocantela, Elisa, Rubinela y Vera, siendo así, indicado para describir el crecimiento de los cultivares de lechuga.

ABSTRACT The objective of this study was to fit a logistic model to leaf fresh and dry matter and shoot fresh and dry matter in four lettuce cultivars to describe growth in summer. The cultivars Crocantela, Elisa, Rubinela, and Vera were evaluated in the summers of 2017 and 2018 in soil in a protected environment and in a soilless system. Seven days after transplanting, the leaf fresh and dry matter and shoot fresh and dry matter of eight plants were weighed every four days. The model parameters were estimated using R software with the least squares method and iterative process of Gauss-Newton. This study also estimated the confidence intervals of the parameters, verified the assumptions of the models, calculated the goodness-of-fit measures and the critical points, and quantified the parametric and intrinsic nonlinearities. The logistic growth model fit well to the fresh and dry matter in the leaves and shoots in the cultivars Crocantela, Elisa, Rubinela, and Vera and described the growth of lettuce.

RESUMO: Os objetivos deste trabalho foram verificar se há variabilidade genética e avaliar as relações lineares entre a arquitetura de planta e a produtividade de grãos de milho. Foram conduzidos três experimentos no delineamento blocos completos ao acaso. Em 51 cultivares, foram avaliados caracteres relacionados ao número de folhas, às alturas de planta e de espiga, ao ângulo foliar, ao comprimento da folha, a largura da folha, a área foliar e a produtividade de grãos, totalizando 22 caracteres. Foram realizadas análises de variância individuais, verificados os pressupostos de normalidade dos erros e homogeneidade de variâncias residuais e agrupadas as médias de cultivares pelo teste de Scott-Knott. Foi determinada a matriz de correlação fenotípica entre os 22 caracteres das 51 cultivares. Há variabilidade genética entre as cultivares em relação ao número de folhas, alturas de planta e de espiga, ângulo foliar, comprimento da folha, largura da folha, área foliar e produtividade de grãos. Folhas localizadas próximas a espiga apresentam menor ângulo foliar e maiores comprimento da folha, largura da folha e área foliar. O ângulo foliar aumenta gradativamente em direção as folhas da extremidade inferior e superior da planta. O comprimento da folha, a largura da folha e a área foliar diminuem gradativamente em direção as folhas da extremidade inferior e superior da planta. Cultivares com maior número de folhas e maior área foliar estão associadas a plantas com maior produtividade de grãos.

ABSTRACT: The objectives of this study were to analyze whether there is genetic variability and assess the linear relationships between plant architecture and maize grain yield. Three experiments were carried out in a complete randomized block design. A group of 51 cultivars was assessed in relation to 22 traits: number of leaves, plant height, ear height, leaf angle, leaf length, leaf width, leaf area, and grain yield. Individual analyses of variance were performed, the assumptions of normality of errors and homogeneity of residual variances were tested, and means were grouped by the Scott-Knott test. The phenotypic correlation matrix was constructed using the 22 traits of the 51 cultivars. Results showed that there is genetic variability among cultivars for number of leaves, plant height, ear height, leaf angle, leaf length, leaf width, leaf area, and grain yield. Leaves close to the ear have smaller leaf angle and larger length, width, and area of the leaves. Leaf angle gradually increases towards the lower and upper ends of the plant. Length, width, and area gradually decreases in leaves towards the lower and upper ends of the plant. Cultivars with higher number of leaves and larger leaf area are associated with higher grain yield.

RESUMO: Os objetivos deste trabalho foram ajustar os modelos Gompertz e Logístico para as massas de matéria fresca e seca de folhas, e as massas de matéria fresca e seca de parte aérea de três cultivares de alface e indicar o modelo que melhor descreve o crescimento no outono-inverno. As cultivares de alface Gloriosa, Pira Verde e Stella, foram avaliadas no outono-inverno de 2016 e outono-inverno de 2017, em cultivo sem solo em ambiente protegido. Após o transplante, a cada sete dias, foram pesadas as massas de matéria fresca e seca de folhas e as massas de matéria fresca e seca de parte aérea. Essas variáveis dependentes foram ajustadas em função da soma térmica acumulada. Foram estimados os parâmetros dos modelos Gompertz e Logístico, verificados os pressupostos dos modelos, calculados os indicadores de qualidade do ajuste e os pontos críticos e quantificadas as medidas de curvatura intrínseca e de parametrização. Os modelos Logístico e Gompertz apresentam ajuste satisfatório para as massas de matéria fresca e seca de folhas e para as massas de matéria fresca e seca de parte aérea, para as cultivares de alface Gloriosa, Pira Verde e Stella, no outono-inverno. O modelo Logístico é o que melhor descreve o crescimento das cultivares de alface.

ABSTRACT: The objectives of this study were to fit the Gompertz and Logistic models for the fresh and dry matter of leaves and the fresh and dry matter of shoots of three lettuce cultivars and indicate the best model to describe their growth in autumn-winter. The lettuce cultivars Gloriosa, Pira Verde, and Stella were evaluated in the autumn-winter of 2016 and 2017, in soilless in a protected environment. After transplantation, the fresh and dry matter of leaves and shoots were weighed every seven days. These dependent variables were fit using the accumulated thermal sum. The parameters of the Gompertz and Logistic models were estimated, the assumptions of the models were verified, the indicators of fit quality and critical points were calculated and the parametric and intrinsic curvature measures quantified. The Logistic and Gompertz models presented a satisfactory adjustment for the fresh and dry matter of leaves and the fresh and dry matter of shoots, for the lettuce cultivars Gloriosa, Pira Verde and Stella, in autumn-winter. The Logistic model best describes the growth of the lettuce cultivars.

RESUMO A necessidade de entender o relacionamento entre variáveis dependentes faz da análise multivariada uma metodologia com grande potencial de aplicação em várias áreas do conhecimento. Objetivou-se ajustar e comparar os modelos não lineares univariados e multivariados de Gompertz e Logístico, utilizados na descrição dos caracteres produtivos de crotalária juncea (Crotalaria juncea L.). Foram realizados dois ensaios de uniformidade. Foram avaliados os caracteres produtivos: massa de matéria fresca de folha (MFF), massa de matéria fresca de caule (MFC) e massa de matéria fresca de parte aérea (MFPA), durante 94 dias, sendo avaliadas quatro plantas por dia, totalizando 376 plantas. Os modelos univariados de Gompertz e Logístico foram ajustados para cada caractere produtivo. Para o ajuste dos modelos multivariados, calculou-se a matriz de covariância dos erros. Obteve-se a matriz (fator de Cholesky) para cada caractere e foram gerados os modelos não lineares multivariados de Gompertz (GG), Logístico (LL) e a combinação de ambos os modelos (GL e LG). Para definição do melhor modelo, utilizou-se o desvio padrão residual (DPR), o coeficiente de determinação (R2), critério de informação de Akaike (AIC), desvio médio absoluto (DMA), medida de não linearidade intrínseca (LI) e medida de não linearidade paramétrica (LP). O modelo não linear multivariado LL foi adequado e obteve resultados satisfatórios para descrever os caracteres produtivos de crotalária juncea.

ABSTRACT Multivariate analysis helps to understand the relationships between dependent variables; this methodology has great potential in several areas of knowledge. The aim of this study was to adjust and compare the univariate and multivariate Gompertz and Logistic nonlinear models to describe the productive traits of sunn hemp (Crotalaria juncea L.). Two uniformity trials were performed, and the following productive traits were analyzed in 376 sunn hemp plants along 94 days of observations (four plants per day): the fresh mass of leaves (FML), the fresh mass of stem (FMS), and the fresh mass of the aerial parts (FMAP). The Gompertz and Logistic univariate models were adjusted for each productive trait. To adjust the multivariate models, the errors covariance matrix was calculated. The matrix (Cholesky factor) was obtained for each trait, and the multivariate Gompertz (GG) and Logistic (LL) nonlinear models were generated, together with the combination of both models (GL and LG). To define the best model, the residual standard deviation (RSD), the determination coefficient (R2), the Akaike information criterion (AIC), the mean absolute deviation (MAD), and the measures of intrinsic nonlinearity (INL) and parametric nonlinearity (PNL) were calculated. The nonlinear multivariate model LL was adequate and achieved satisfactory results to describe the productive traits of sunn hemp.

RESUMO: O objetivo deste trabalho foi determinar o tamanho ótimo de parcela para avaliar a massa de matéria fresca de aveia preta (Avena strigosa Schreb) e de ervilhaca (Vicia sativa L.), em cenários formados por combinações de números de tratamentos, números de repetições e níveis de precisão. Foram conduzidos 15 ensaios de uniformidade com aveia preta e ervilhaca, em cultivo solteiro e em consórcio. Foi avaliada a massa de matéria fresca em 540 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 = 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18% e 20%). Para avaliar a massa de matéria fresca de aveia preta e de ervilhaca, em cultivo solteiro ou em consórcio, nos delineamentos inteiramente casualizado e de blocos completos ao acaso, com 5 a 20 tratamentos e com cinco repetições, parcelas de 10 m2 são suficientes para identificar diferenças significativas entre tratamentos, a 0,05 de probabilidade, de 10% da média geral do experimento.

ABSTRACT: The aim of this study was to determine the optimal plot size for evaluating the fresh weight of black oats (Avena strigosa Schreb) and the common vetch (Vicia sativa L.) in scenarios comprising combinations of the number of treatments, number of replications and levels of precision. Fifteen uniformity trials were conducted with single-crop and intercropped black oats and vetch. Fresh weight was evaluated in 540 basic experimental units (BEU), each of 1 m × 1 m (36 BEU per trial). The Smith index of soil heterogeneity (1938) was estimated. Plot size was determined using the HATHEWAY method (1961), in scenarios comprising combinations of i treatments (i = 5, 10, 15 and 20), r replications (r = 3, 4, 5, 6, 7 and 8) and d levels of precision (d = 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18% and 20%). To evaluate the fresh weight of monocropped or intercropped black oats and vetch in a completely randomized or randomized complete block design, with from 5 to 20 treatments and five replications, plots of 10 m2 are sufficient to identify, at a probability of 0.05, significant differences between treatments of 10% of the overall mean value of the experiment.

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.