ABSTRACT: In order to ensure reliable inferences in scientific experiments, sampling criteria should be determined and defined during the experimental design phase. Determining plot and sample sizes without scientific criteria could result in resource and labor inefficiencies with no gain in experimental precision. In this work we estimate plot and sample sizes for biometric variable analyses in lettuce seedlings. The seedlings were sown in four expanded polystyrene foam transplant trays with 128 and 200 cells. Foliar area, stem diameter, shoot height, root length, root volume, root area, fresh and dry shoot and root masses. The methods described by Paranaiba (PARANAIBA et al., 2009) and Cochran (COCHRAN, 1977) were used for plot size and sample size estimations, respectively. Sample size varied according to the variables analysed and transplant tray cell number. Root variables required the highest number of samples. For a 10% margin of error, 12 seedlings were necessary for evaluations in a 128 cell tray, while 11 seedlings were required for analysis in 200 cell trays. ABSTRACT experiments phase precision 20 cells area diameter height length volume masses PARANAIBA al al. 2009 COCHRAN, COCHRAN (COCHRAN 1977 estimations respectively samples 10 error 1 2 197 19

RESUMO: A fim de garantir inferências confiáveis em experimentos científicos, os critérios de amostragem devem ser determinados e definidos durante a fase de planejamento experimental. Determinar tamanhos de parcelas e amostras sem critérios científicos pode resultar em ineficiências de recursos e mão de obra sem ganho de precisão experimental. Neste trabalho estimamos tamanhos de parcelas e amostras para análises de variáveis biométricas em mudas de alface. As mudas foram semeadas em quatro bandejas de transplante de espuma de poliestireno expandido com 128 e 200 células. Área foliar, diâmetro do caule, altura da parte aérea, comprimento da raiz, volume da raiz, área da raiz, parte aérea fresca e seca e massas radiculares. Os métodos descritos por Paranaíba (PARANAÍBA et al., 2009) e Cochran (COCHRAN, 1977) foram utilizados para estimativas de tamanho de parcela e tamanho de amostra, respectivamente. O tamanho da amostra variou de acordo com as variáveis analisadas e o número de células da bandeja de transplante. As variáveis de raiz exigiram o maior número de amostras. Para uma margem de erro de 10%, foram necessárias 12 mudas para avaliação em bandeja de 128 células, enquanto 11 mudas foram necessárias para análise em bandeja de 200 células. RESUMO experimental alface 20 foliar caule radiculares PARANAÍBA al al. 2009 COCHRAN, COCHRAN (COCHRAN 1977 respectivamente 10 10% 1 2 197 19

ABSTRACT: The carrotculture stands out on the world stage due to its nutritional characteristics and economic importance, an aspect that demands the constant development of research aiming greater productivity. Thus, this study proposed an experimental plan, determining the estimates of plot size, sample size, and number of repetitions, with the purpose of increasing the precision and reliability of the results of the experiments with the carrot crop. Six uniformity trials were conducted, using three cultivars in two growing seasons (Season: 2019 and 2021).Each plant was considered a basic experimental unit and in each BEU, the variables shoot height, root length, shoot fresh mass, root fresh mass, and root diameter were measured. The size of the plot, sample, and the number of repetitions was estimated by the method of maximum curvature of the coefficient of variation. The results recommend that for experiments with the carrot crop, plots with twelve plants should be used. For a sampling of carrot plants in the plot, samples of eleven plants must be used in the direction of the row, considering a semi-amplitude of the confidence interval (D%) equal to 20% of the mean, with a confidence level of 95%. For a minimum significant difference in the Tukey test expressed as a percentage of the 50% mean, plots of twelve plants per crop row, with eight replicates, are recommended. ABSTRACT importance productivity Thus plan conducted Season (Season 201 2021.Each 2021Each Each 2021 .Each BEU height length mass measured variation row semiamplitude semi amplitude D% D (D% 20 mean 95 95% 50 replicates recommended 202 (D 2 9 5

RESUMO: A cultura da cenoura se destaca no cenário mundial por suas características nutricionais e importância econômica, aspecto que demanda o constante desenvolvimento de pesquisas visando maior produtividade. Assim, o objetivo deste trabalho foi propor um plano experimental, determinando as estimativas de tamanho de parcela, tamanho de amostra e número de repetições, com a finalidade de aumentar a precisão e confiabilidade dos resultados dos experimentos com a cultura da cenoura. Foram conduzidos seis ensaios de uniformidade, utilizando três cultivares em duas safras (Safra: 2019 e 2021). Cada planta foi considerada uma unidade experimental básica e em cada BEU foram medidas as variáveis altura da parte aérea, comprimento da raiz, massa fresca da parte aérea, massa fresca da raiz e diâmetro da raiz. O tamanho da parcela, da amostra e o número de repetições foram estimados pelo método da máxima curvatura do coeficiente de variação. Os resultados recomendam que para experimentos com a cultura da cenoura sejam utilizadas parcelas com doze plantas. Para amostragem de plantas de cenoura na parcela, devem ser utilizadas amostras de onze plantas no sentido da linha, considerando uma semi-amplitude do intervalo de confiança (D%) igual a 20% da média, com nível de confiança de 95%. Para uma diferença mínima significativa no teste de Tukey expressa em porcentagem da média de 50%, recomendam-se parcelas de doze plantas por fileira de cultivo, com oito repetições. RESUMO econômica produtividade Assim parcela uniformidade Safra (Safra 201 2021. 2021 . 2021) aérea variação linha semiamplitude semi amplitude D% D (D% 20 95 95% 50 50% recomendamse cultivo 202 (D 2 9 5

ABSTRACT This study aimed to evaluate the use of the product of thermal efficiency and photosynthetically active radiation (TEP) to model the growth of tomato seedlings across different growing seasons. The work was conducted in a completely randomized design with four replicates in two seasons (summer/autumn and winter/spring). Height, diameter, the Dickson’s Quality Index (DQI), and total plant mass (TPM) were measured at 15, 20, 25, 30, 35 and 40 days after sowing (DAS). The logistic model was fitted for each measured variable as a function of TEP, and the partial derivatives of the fitted function estimated the critical points. The results demonstrated that the logistic function effectively explained the nonlinear relationships of seedling growth. The fit quality parameters showed high fitted coefficients of determination and low values for the standard error of fit, residual standard deviation, and intrinsic and parametric nonlinearity. It was possible to characterize the growth process of tomato seedlings in both growth periods investigated. The logistic model fitted for the studied variables as a function of TEP becomes an accurate model capable of describing growth aspects of tomato seedlings, such as growth estimation, growth speed, and growth rate, essential parameters for decision-making in tomato cultivation. (TEP summer/autumn summerautumn summer autumn winter/spring. winterspring winter/spring . winter spring winter/spring) Height diameter Dicksons Dickson s DQI, DQI , (DQI) TPM (TPM 15 20 25 30 3 4 DAS. DAS (DAS) points deviation nonlinearity investigated estimation speed rate decisionmaking decision making cultivation (DQI 1 2 (DAS

ABSTRACT. Imputation methods were developed to define estimates for missing data and hence solve possible problems generated by the loss of this information. This study aims to assess whether data variability influences the results obtained after applying an imputation method. Incomplete databases were generated from complete real databases of experiments of tomato plants conducted using the randomized block design with three replications and 12 treatments by removing different amounts of data. The evaluated variables consisted of fruit weight per plant, number of fruits per plant, and average fruit length and width, forming eight balanced databases. Subsequently, the distribution-free multiple imputation method was applied, generating complete databases from imputation. The number of missing information influenced the accuracy measures for the data in this study. Data imputation was inadequate when there was high variability but more precise and accurate in cases of low variability. It confirmed the importance of assessing data variability before choosing to apply the imputation method. ABSTRACT 1 plant width Subsequently distributionfree distribution free applied

ABSTRACT. Nonlinear regression models represent an alternative way to describe plant growth. In this study, we aimed to model the growth of linseed using four methods for data collection (longitudinal, mean, random, and cross-sectional) and fitting the logistic and Von Bertalanffy nonlinear regression models. The data came from experiments conducted between 2014 and 2020 in the municipality of Curitibanos, Santa Catarina, Brazil. The study had a randomized block design, with experimental units consisting of six lines, 5.0 m long and 3.0 m wide, containing the varieties and cultivars of linseed with four replicates. We performed weekly assessments of the number of secondary stems and plant height and measured total dry mass fortnightly. After tabulation, the data were analyzed using the four methods, and the logistic and Von Bertalanffy models were fitted. The logistic model for the plant height variable exhibited the best performance using the longitudinal, mean, and cross-sectional methods. It was an alternative approach that reduced the time and labor required to conduct the experiment. ABSTRACT longitudinal (longitudinal mean random crosssectional cross sectional 201 202 Curitibanos Catarina Brazil design lines 50 5 0 5. 30 3 3. wide replicates fortnightly tabulation fitted experiment 20 2

ABSTRACT: This study was conducted with the aim of analyzing the implications of removing the parameters from the mathematical model on the results of path analysis, with oats grown in different years and agricultural scenarios (with and without fungicide). For this, two field trials were conducted in southern Brazil, in five years of growth. The experimental design used in trial I (with fungicide application) was randomized complete blocks (RCB), in a 22 × 4 bifactorial arrangement, characterized by twenty-two oat cultivars and four fungicide applications. For trial II (without fungicide application) the RCB design was used, and the treatments were characterized by twenty-two oat cultivars, with three replications. The traits measured were panicle length, panicle mass, number of spikelets, number of grains, grain mass, and grain yield. For each year, data group, and scenario, the correlation coefficients between the explanatory variables and grain yield were calculated. The diagnosis of multicollinearity indicated violation of the statistical assumption, so it was necessary to proceed with a path analysis under multicollinearity (ridge). The removal of parameters from the mathematical model caused changes in the linear relationships between the oat yield traits, with the maintenance of the linear correlation coefficients in 3.30% and 20% of the situations, for the scenarios with and without fungicide application, respectively. Regarding the path coefficients, it was observed that the direct effects were maintained in 3.30% and 30% and indirect effects in 7.33% and 24.67% of the situations, for the scenarios with and without fungicide application, respectively. ABSTRACT fungicide. . fungicide) this Brazil growth application RCB, , (RCB) 2 arrangement twentytwo twenty applications replications length mass spikelets grains year group scenario calculated assumption ridge. ridge (ridge) 330 3 30 3.30 20 situations respectively 733 7 33 7.33 2467 24 67 24.67 (RCB (ridge 3.3 73 7.3 246 6 24.6 3. 7. 24.

RESUMO: O estudo foi conduzido com o intuito de analisar as implicações da remoção dos parâmetros do modelo matemático sobre os resultados da análise de trilha, com aveia cultivada em diferentes anos e cenários agrícolas (com e sem fungicida). Para isso, dois ensaios de campo foram conduzidos no sul do Brasil, em cinco anos de cultivo. O delineamento experimental empregado no ensaio I (com aplicação de fungicida) foi o de blocos completos ao acaso, sendo um bifatorial 22 × 4, caracterizado por vinte e duas cultivares de aveia e quatro aplicações de fungicidas. Para o ensaio II (sem aplicação de fungicida) foi empregado o delineamento em blocos completos ao acaso, sendo os tratamentos caracterizados por vinte e duas cultivares de aveia, com três repetições. Os caracteres mensurados foram comprimento da panícula, massa da panícula, número de espiguetas, número de grãos, massa de grãos e rendimento de grãos. Para cada ano, grupo de dados e cenário foram calculados os coeficientes de correlação entre as variáveis explicativas e a produtividade de grãos. O diagnóstico de multicolinearidade indicou a violação do pressuposto estatístico, sendo necessário proceder a análise de trilha sob multicolinearidade (em crista). A remoção dos parâmetros do modelo matemático promoveu alterações nas relações lineares entre os caracteres de rendimento da aveia, sendo verificado a manutenção no padrão dos coeficientes de correlação linear em 3,30% e 20% das situações, para os cenários com e sem aplicação de fungicida, respectivamente. Com relação aos coeficientes de trilha, foi verificado manutenção na direção e magnitude dos efeitos diretos em 3,30% e 30% e os efeitos indiretos em 7,33% e 24,67% das situações, para os cenários com e sem aplicação de fungicida, respectivamente. RESUMO fungicida. fungicida . isso Brasil cultivo acaso 2 4 fungicidas repetições panícula espiguetas ano estatístico crista. crista crista) 330 3 30 3,30 20 situações respectivamente 733 7 33 7,33 2467 24 67 24,67 3,3 73 7,3 246 6 24,6 3, 7, 24,

ABSTRACT This study aimed to identify the correlations between traits of the groups stem cutting, seedling, stem, and root of cassava. Length, diameter, and weight of stem cutting (Group 1) were measured at each growing season (July, August, September, and October). A total of 300 cuttings were collected after sprouting and planted at seasons of September 22, October 7 and 19, and November 25. Plant height at planting, number of leaves at planting, and number of leaves at 7 days after planting were measured. The number of leaves at transplanting and plant height at transplanting were determined after acclimation (Group 2). Seedling transplanting was carried out on November 9 and 24 and December 3 and 26, and the traits stem (Group 3) and root (Group 4) yield were measured at harvest. Associations between the groups stem cutting and seedling were established by stem cutting diameter and weight, and height and number of leaves at planting. Seedling traits had the greatest influence on the number of buds per stem and stem diameter. Main stem branching height and stem diameter can be used for selecting plants with an indication of the best quality and yield of root traits. cassava Length Group 1 July, July (July August October. . October) 30 22 19 25 2. 2 2) 26 4 harvest

ABSTRACT The flaxseed is little explored under Brazilian cultivation conditions, generating a gap in information about the appropriate management of the crop, in the country. Hence, the objective was to find the appropriate dose of nitrogen for the development of the variables: technical length, yield length, main stem diameter, number of grains per pod, plant grain yield, and plant dry mass of two flaxseed varieties, brown and golden, in places with subtropical and tropical climate in Brazil. The treatments consisted of a two-factor 2 x 6 experiment, consisting of two flax varieties (brown and golden) and six nitrogen doses (0; 30; 60; 90; 120 and 150 kg ha-1), in randomized blocks with four repetitions and three different environments: Santa Maria and Frederico Westphalen, in the state of Rio Grande do Sul, and Viçosa, in the state of Minas Gerais. The brown variety obtained greater technical and yield length compared to the golden variety, on the other hand, the golden variety showed a higher number of grains per capsule and higher plant grain yield compared to the brown variety, in the three environments. The plant dry mass increased linearly and proportionally to the increase in nitrogen doses in Santa Maria and Frederico Westphalen environments. Therefore, flaxseed responds differently to nitrogen supplementation according to the cultivation environment, showing wide variability. The different doses of nitrogen influenced the variables analyzed and the varieties of flaxseed differently, depending on the environment. conditions crop country Hence diameter pod Brazil twofactor factor experiment 0 (0 30 60 90 12 15 ha1, ha1 ha 1 , ha-1) environments Sul Viçosa Gerais hand Therefore environment variability ( 3 9 ha-1 ha-

ABSTRACT Seedling production is an important step in growing vegetables. The study of relationships between variables has applications in practically all areas of study and is useful in identifying relationships among quality variables in vegetable seedlings. Thus, this work aims to estimate linear relationships between biometric variables in lettuce seedlings. The seedlings were grown in expanded polystyrene trays (n = 4) with 128 and 200 cells each. Leaf area, stem diameter, shoot height, length, area, volume of the root, dry and fresh shoot mass variables were measured and evaluated with Pearson's correlation analysis, multicollinearity diagnosis, condition number and the variance inflation factor, path analysis and canonical correlations. The results show linear relationships between the variables. For the 128 cell trays, there was a relationship between the total fresh mass and fresh shoot mass variables and between the total fresh mass and dry shoot mass variables. For the 200-cell trays, significant correlation was observed between the characters total fresh mass and fresh shoot mass variables and between root area and root volume variables, indicating that the greater the total fresh mass, the greater the fresh shoot mass and the greater the root area, the greater the root volume. vegetables Thus n 4 12 20 each diameter height length Pearsons Pearson s diagnosis factor correlations 200cell 1 2

ABSTRACT The aim of this study was to evaluate, using logistic model, the differences in early production, production rate and total productivity of two strawberry cultivars with transplants from different origins grown in substrate. The experiment was carried out in a randomized block design (RBD), with two strawberry cultivars (Albion and Camarosa) and two origins of transplants (National and Imported), with four repetitions consisting of eight plants. For the variable fruit mass, the logistic model was adjusted as a function of the accumulated thermal sum, and from the partial derivatives of the adjusted function, the critical points of the model were estimated. The use of the Logistic model allows evaluating precocity and rate of fruit production efficiently and accurately. The cultivar Camarosa was the most productive compared to the Albion cultivar, presenting a shorter production cycle, with a high production peak. The Albion cultivar was earlier, presenting more constant production during the evaluated production cycle. The transplant's origin did not show significantly different results for the cultivars evaluated. The producer must choose the cultivar that will be used based on its performance and also based on consumer preferences and fruit demand.

ABSTRACT The cultivation of onion Allium cepa L. is of extreme economic importance globally, and, because of this, research must be constantly updated in order to increase productivity. This study was designed to estimate the optimal plot size, sample size and number of repetitions for experiments evaluating variables in the onion crop. Uniformity tests were carried in the years 2016 and 2017 in the experimental area of the Crop Science Department at Universidade Federal de Santa Maria, Santa Maria (RS), Brazil. Each plant was considered a basic experimental unit. Bulb mass, bulb height, and bulb diameter were measured for each basic experimental unit. The optimal plot size, sample size, and number of repetitions were estimated by the method of maximum curvature of the variation coefficient. For onion culture, the optimal plot size to evaluate the bulb mass, bulb height and bulb diameter is eight, six and six, respectively. The optimal sample size for evaluating the bulb mass of the onion crop is six plants, while for the height and diameter variables the optimal sample size is four plants in the direction of the row considering a semi-amplitude of the confidence interval (D%) equal to 20% of the average. Bulb mass variables require 10 repetitions to assess up to 20 treatments in a randomized block design for the least significant difference of the Tukey’s test, expressed as a percentage of the average of 35%. Bulb height and bulb diameter require just six repetitions for the same assessment.

RESUMO: O objetivo deste trabalho foi avaliar as relações entre os caracteres biométricos de mudas de tomate com os caracteres de produção obtidos ao final do ciclo da cultura, para determinar como a qualidade das mudas interfere na produtividade do tomate. O experimento foi conduzido em duas épocas de cultivo, em delineamento inteiramente casualizado, com quatro repetições e a unidade experimental composta por cinco plantas. Os tratamentos foram constituídos por mudas com diferentes idades, diferenciadas pelos dias após a semeadura (DAS): (15, 20, 25, 30, 35 e 40 DAS). Após cada avaliação das mudas, eram transplantadas para o local de produção definitivo, sendo avaliadas até o final do ciclo. Avaliaram-se os caracteres biométricos das mudas e os caracteres da produção de frutos. Análise de correlação de Pearson e componentes principais (PCA) foram realizados para determinar as relações entre os caracteres, análise de trilha para determinar os efeitos diretos e indiretos e análise de correlações canônicas entre os grupos de caracteres. Em todas as análises realizadas, foi identificada correlação fraca entre os caracteres biométricos das mudas (que avaliam a qualidade) com os caracteres da produção de frutos de tomate em cultivo em substrato.

ABSTRACT: This study evaluated the relationships between the biometric characters of tomato seedlings with the production characters obtained at the end of the crop cycle, to determine how the quality of seedlings interferes with tomato productivity. An experiment was carried out in two growing seasons, in a completely randomized design, with four replications and the experimental unit consisting of five plants. The treatments consisted of seedlings with different ages, differentiated by the days after sowing (DAS): (15, 20, 25, 30, 35, and 40 DAS). After each evaluation of the seedlings, they were transplanted to the definitive production site, being evaluated until the end of the cycle. Biometric characters of seedlings and characters of fruit production were evaluated. Pearson correlation analysis and principal components (PCA) were performed to determine the relationships between the characters, path analysis to determine the direct and indirect effects, and analysis of canonical correlations between the groups of characters. In all analyses performed, weak correlation between the biometric characters of the seedlings (which evaluate the quality) with the characters of tomato fruit production in substrate cultivation was identified.

RESUMO Modelos de crescimento de base biológica podem ser uma alternativa na identificação da resposta produtiva de hortaliças de múltiplas colheitas. Ao interpretar as estimativas dos parâmetros dos modelos, é possível estimar a produção total, a taxa de produção de frutos e o momento em que a cultura atinge seu potencial máximo de produção. Além disso, estimando intervalos de confiança, essas respostas podem ser comparadas entre genótipos ou entre diferentes tratamentos. Portanto, o objetivo do manuscrito foi apresentar uma revisão de literatura em um passo a passo para análise e interpretação do ciclo de produção de hortaliças de múltiplas colheitas, com base em regressão não linear. Todos os requisitos que devem ser atendidos neste tipo de análise foram apresentados detalhadamente, fornecendo o passo a passo necessário para análises de regressão não linear. A demonstração é realizada usando dados do cultivo de morango junto com os scripts R associados e a interpretação da saída da análise em um material suplementar. Esta abordagem pode permitir inferências mais relevantes do que análises tradicionais realizadas, através de um melhor exame e modelagem dos processos biológicos subjacentes.

ABSTRACT Biologically based growth models can be an alternative in identifying the productive response of multiple harvest vegetables. By interpreting the estimates of the parameters of the models, it is possible to estimate the total production, the rate of fruit production, and the moment when the crop reaches its maximum production potential. Besides, by estimating confidence intervals, these responses can be compared between genotypes or between different treatments. Therefore, the purpose of this manuscript is to present a literature review, and a detailed step-by-step, to interpreting the evolution of the production cycle of vegetables with multiple harvests crops based on non-linear regression. All the requirements that must be met in this type of analysis were presented in detail based on non-linear regression, providing the necessary steps for this type of analysis in details. Demonstration is given using data from strawberry cultivation along with the associated R scripts and interpretation of analysis output in material supplemental. This approach can allow for more relevant inferences than standard means analyses through better examination and modeling of the underlying biological processes.

RESUMO O objetivo deste estudo foi identificar a resposta do ciclo produtivo de genótipos de abobrinha italiana cultivadas em condições de campo em duas épocas de cultivo por meio do modelo não linear logístico e seus pontos críticos. Para isso dois experimentos foram conduzidos em delineamento blocos ao acaso, com três genótipos (Caserta, PX13067051 e Tronco) e duas épocas de cultivo (primavera-verão e verão-outono) com oito repetições e a unidade experimental composta por 7 plantas. Ajustou-se o modelo não linear logístico para a variável massa de frutos, em função da soma térmica acumulada, e estimou-se os pontos críticos pelas derivadas parciais da função ajustada. Os pressupostos do modelo não linear não foram atendidos para nenhum genótipo em ambas as épocas avaliadas, e para contornar este problema foi realizado o ajuste por reamostragens bootstrap. Os resultados de não linearidade intrínseca e paramétrica confirmam a qualidade do ajuste do modelo. Pelos parâmetros e pontos críticos do modelo foi possível determinar que os genótipos de abobrinha italiana avaliados foram mais produtivos na primavera-verão. Os genótipos PX13067051 e Caserta apresentaram produtividade superior ao genótipo Tronco, além de serem mais precoces e apresentar maiores taxas de produção. O modelo de crescimento logístico e seus pontos críticos foram capazes de caracterizar o ciclo de produção dos genótipos de abobrinha italiana em diferentes épocas de cultivo, e permitiu que inferências fossem realizadas com vistas a diferenciar os genótipos e as épocas de cultivo avaliadas.

ABSTRACT This study aimed to identify the productive cycle response of Italian zucchini genotypes grown under field conditions in two growing seasons using the nonlinear logistic model and its critical points. Two randomized block experiments were conducted, with three genotypes (Caserta, PX13067051, and Tronco) and two growing seasons (spring-summer and summer-fall), with eight replicates and each experimental unit consisting of 7 plants. The logistic nonlinear model was adjusted for the fruit mass variable, as a function of the accumulated thermal sum, and the critical points were estimated by the partial derivatives of the adjusted function. Adjustment by bootstrap resampling was performed to address the violation of assumptions. The results of intrinsic and parametric nonlinearity confirm the quality of the model fit. This experiment demonstrated that the zucchini genotypes evaluated were more productive in the spring-summer growing season, using the parameters and critical points obtained from the logistic nonlinear model. Genotypes PX13067051 and Caserta showed superior productivity to the Tronco genotype, and also fruited earlier and at a higher rate of production. The logistic growth model and its critical points characterized the production cycle of the zucchini genotypes in different growing seasons and allowed inferences to be made to differentiate the genotypes and the growing seasons.

Abstract In agricultural experiments, measuring all plants that constitute an experimental unit is the most appropriate method for estimating averages. This study analyzed sample sizes (number of plants) for estimating averages of agronomic traits in cassava. The experiment for seedling production was conducted on four sowing dates: September 22, October 7, October 19, and November 25, 2017. The evaluated characters were plant height at planting, number of leaves at planting, number of leaves at 7 days after planting, number of leaves at transplanting, and plant height at transplanting. The seedlings were transplanted to the field on November 9, November 24, December 3, and December 26. Root characteristics and root yield were measured at harvest. The following statistics were measured: minimum, maximum, range, mean, median, variance, standard deviation, and coefficient of variation. The sample size was determined by resampling with replacement when the range of the 95% confidence interval (CI) was 10%, 20%, 30%, and 40% of the average estimate. Larger sample sizes were needed to estimate trait averages with a 95% CI range of 10% of the average estimate, i.e., when estimation accuracy was higher. In contrast, lower sample sizes were required to estimate averages of all characters in all planting times with a 95% CI range of 40%. For measuring seedling production and stem and root yield, 63 and 153 plants are sufficient to estimate averages when the range of the 95% confidence interval was 20%.

Resumen En experimentos agrícolas, medir todas las plantas que constituyen una unidad experimental es el método más apropiado para estimar promedios. Este estudio analizó tamaños de muestra (número de plantas) para estimar promedios de caracteres agronómicos en yuca. El experimento para la producción de plántulas se realizó en cuatro fechas de siembra: 22 de septiembre, 7 de octubre, 19 de octubre y 25 de noviembre de 2017. Los caracteres evaluados fueron la altura de la planta en la siembra, el número de hojas en la siembra, el número de hojas a los 7 días después de la siembra, el número de hojas en el trasplante y la altura de la planta en el trasplante. Las plántulas se trasplantaron al campo el 9 de noviembre, 24 de noviembre, 3 de diciembre y 26 de diciembre. Las características de la raíz y el rendimiento de la raíz se midieron en la cosecha. Se midieron las siguientes estadísticas: mínimo, máximo, rango, media, mediana, varianza, desviación estándar y coeficiente de variación. El tamaño de la muestra se determinó mediante remuestreo con reemplazo cuando el rango del intervalo de confianza (IC) de 95% fue de 10%, 20%, 30% y 40% de la estimación promedio. Se necesitaron tamaños de muestra más grandes para estimar los promedios de rasgos con un rango de IC de 95% de 10% de la estimación promedio; es decir, cuando la precisión de la estimación fue mayor. En contraste, se requirieron tamaños de muestra bajos para estimar promedios de los caracteres en los tiempos de siembra con un rango de IC de 95% de 40%. Para medir la producción de plántulas y rendimiento de tallos y raíces, 63 y 153 plantas son suficientes para estimar promedios cuando el rango del intervalo de confianza de 95% fue de 20%.