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Abstract The objective of this work was to define the optimal plot size and number of replicates for the evaluation of the fresh weight of sorghum (Sorghum bicolor) hybrids. Thirty-two uniformity trials were carried out with two hybrids, in two sowing dates and four evaluation periods. Each trial was divided into 48 basic experimental units (BEUs) of 0.5 m2, and fresh weight was determined for each BEU. The mean, variance, coefficient of variation, first-order spatial autocorrelation coefficient, optimal plot size, and coefficient of variation of the optimal plot size were calculated. The number of replicates was determined on the basis of the largest calculated plot size, through an iterative process, for the combinations of number of treatments and differences among means to be detected as significant by Tukey’s test, at 5% probability. The optimal plot size ranged from 1.79 to 2.58 m2, and the number of replicates from 2.6 (~3) to 49.2 (~50). The optimal plot size is 2.58 m2, and five replicates are sufficient to identify as significant the differences between treatment means of 35%.

ABSTRACT: This study analyzed the response of the Bartlett test as a function of sample size and to define the optimal sample size for the test with soybean grain yield data. Six experiments were conducted in a randomized block design with 20 or 30 cultivars and three repetitions. Grain yield was determined per plant, totaling 9,000 sampled plants. Next, sample scenarios of 1, 2, ..., 100 plants were simulated and the optimal sample size was defined via maximum curvature points. The increase in sampled plants per experimental unit favors Bartlett test’s precision. Also, the sampling of 17 to 20 plants per experimental unit is enough to maintain the accuracy of the test.

Objetivou-se avaliar a produção de mudas de Petunia x hybrida e Gomphrena globosa cultivadas em diferentes épocas e substratos a base de resíduos agropecuários. O delineamento experimental utilizado foi o inteiramente casualizado, em esquema fatorial, sendo os tratamentos compostos por quatro repetições e a unidade experimental formada por dez plantas. Foram cultivadas as espécies de flores Petunia x hybrida e Gomphrena globosa em cinco composições de substratos e em duas épocas, sendo as semeaduras realizadas em abril e junho para a Petunia x hybrida e abril e outubro para a Gomphrena globosa. Os substratos foram compostos utilizando-se substrato comercial (SC), esterco bovino curtido (EB), húmus de minhoca (HM) e cinza de casca de arroz (CC), nas proporções volumétricas: (S1) 100% SC; (S2) 40% SC + 20% EB + 20% HM + 20% CC; (S3) 60% SC + 20% HM + 20% CC; (S4) 60% SC + 20% EB + 20% CC; e (S5) 80% SC + 20% EB. Avaliou-se a emergência, índice de velocidade de emergência, altura, número de folhas, comprimento da maior folha, comprimento da maior raiz, massa seca da parte aérea, massa seca do sistema radicular e massa seca total. O crescimento das mudas de Petunia x hybrida e Gomphrena globosa modificaram-se conforme as características dos substratos e as épocas de cultivo. O substrato composto com 80% de substrato comercial e 20% de esterco bovino apresentou resultados semelhantes ou superiores ao substrato comercial, podendo ser utilizado a fim de reduzir os custos de produção sem prejuízos ao crescimento das mudas. O cultivo de Petunia x hybrida em abril resultou em mudas com maior altura, comprimento das folhas e maior acúmulo de fitomassa. As mudas de Gomphrena globosa apresentaram maior desenvolvimento da parte aérea e do sistema radicular, além de maior acúmulo de fitomassa quando cultivadas em outubro.

ABSTRACT: Sunflower produces achenes and oil of good quality, besides serving for production of silage, forage and biodiesel. Growth modeling allows knowing the growth pattern of the crop and optimizing the management. The research characterized the growth of the Rhino sunflower cultivar using the Logistic and Gompertz models and to make considerations regarding management based on critical points. The data used come from three uniformity trials with the Rhino confectionery sunflower cultivar carried out in the experimental area of the Federal University of Santa Maria - Campus Frederico Westphalen in the 2019/2020 agricultural harvest. In the first, second and third trials 14, 12 and 10 weekly height evaluations were performed on 10 plants, respectively. The data were adjusted for the thermal time accumulated. The parameters were estimated by ordinary least square’s method using the Gauss-Newton algorithm. The fitting quality of the models to the data was measured by the adjusted coefficient of determination, Akaike information criterion, Bayesian information criterion, and through intrinsic and parametric nonlinearity. The inflection points (IP), maximum acceleration (MAP), maximum deceleration (MDP) and asymptotic deceleration (ADP) were determined. Statistical analyses were performed with Microsoft Office Excel® and R software. The models satisfactorily described the height growth curve of sunflower, providing parameters with practical interpretations. The Logistics model has the best fitting quality, being the most suitable for characterizing the growth curve. The estimated critical points provide important information for crop management. Weeds must be controlled until the MAP. Covered fertilizer applications must be carried out between the MAP and IP range. ADP is an indicator of maturity, after reaching this point, the plants can be harvested for the production of silage without loss of volume and quality.

O presente trabalho teve como objetivo avaliar a influência de diferentes substratos orgânicos no crescimento, produtividade e classificação de frutos de tomateiro cereja das cultivares Cascade e Samambaia em ambiente protegido. O delineamento experimental adotado foi o inteiramente casualizado, com seis tratamentos e quatro repetições. Os tratamentos consistiram em seis substratos, resultantes da combinação de solo (SC), esterco bovino (EB), casca de arroz (CA) e cinza de casca de arroz (CC), nas proporções: 70% SC + 10% EB + 10% CA + 10% CC (S1); 60% SC + 20% EB + 10% CA + 10% CC (S2); 50% SC + 30% EB + 10% CA + 10% CC (S3); 60% SC + 30% EB + 10% CA (S4); 70% SC + 20% EB + 10% CA (S5); e 100% SC (S6). As avaliações consistiram em analisar o comprimento da parte aérea, número de folhas, número e massa fresca de frutos, diâmetro vertical e horizontal do fruto, estimação da produtividade e classificação. O substrato composto por solo não se mostrou eficiente, apresentando os menores valores para todas as variáveis. Para a cultivar Cascade, os substratos S1, S2 e S5 demonstram ser favoráveis aos parâmetros agronômicos do tomateiro cereja, possibilitando um maior número de frutos comercializáveis. Para a cultivar Samambaia novos estudos precisam ser realizados com diferentes fontes e proporções a fim de obter o substrato mais adequado para o cultivo. Portanto, para a produção de tomate cereja da cultivar Cascade os substratos compostos de resíduos obtidos do beneficiamento do arroz e dejetos de bovinos, apresentaram-se como fontes alternativas no cultivo do tomateiro.

ABSTRACT: The objective of this research was to determine the optimal plot size and the number of replications to evaluate the fresh matter of ryegrass sown to haul. Twenty uniformity trials were conducted, each trial with 16 basic experimental units (BEU) of 0.5 m2. At 117, 118 and 119 days after sowing, the fresh matter of ryegrass in the BEUs of 5, 10 and 5 uniformity trials, respectively, were determined. The optimal plot size was determined by the maximum curvature method of the variation coefficient model. Next, the replications number was determined in scenarios formed by combinations of i treatments (i = 3, 4, ... 50) and d minimum differences between means of treatments to be detected as significant at 5% of probability by the Tukey test, expressed in experimental mean percentage (d = 10, 11, ... 20%). The optimal plot size to determine the fresh matter of ryegrass seeded at the haul is 2.19 m2, with a variation coefficient of 9.79%. To identify as significant at 5% probability, by the Tukey test, differences between treatment means of 20%, are required five, six, seven and eight replications, respectively, in ryegrass experiments with up to 5, 10, 20 and 50 treatments.

ABSTRACT: The objectives of this work were estimate the leaf area of squash ‘Brasileirinha’ by linear dimensions of the leaves and check models available in the literature. An experiment was conducted in the 2015/16 sowing season. Were collected 500 leaves and in each one, were measured the length (L), width (W) and length×width product (LW) and determined the real leaf area (LA). Then, 400 leaves were separated to generate models of the leaf area (LA) as a function of linear dimension (L, W or LW) of squash. The remaining 100 leaves were used for the validation of models. A second experiment was conducted in the 2016/17 sowing season. Were collected 250 leaves, used only for the validation of the models of the first experiment. There is collinearity between L and W and, therefore, models using the LW product are not recommended. The model LA=0.5482W2 + 0.0680W (R²=0.9867) is adequate for leaf area estimation of squash ‘Brasileirinha’.

ABSTRACT: The hybridization between wheat and rye crops resulted in the triticale crop, which presents rusticity, versatility in animal and human food and possibility of use as a cover plant. The objective of this research was to determine the optimal plot size and the replications number to evaluate the fresh weight of triticale in two evaluation moments. An experiment was carried out with the triticale cultivar IPR111. The experimental area was divided into 48 uniformity trials, each containing 36 basic experimental units of 0.51 m2. The fresh weight was evaluated in 24 uniformity trials at 99 days after sowing (DAS) and in 24 uniformity trials at 127 DAS. The optimal plot size was determined by the method of the maximum curvature of the coefficient of variation and the replications number was determined in scenarios of treatments number and differences between means to be detected as significant by Tukey test. To determine the fresh weight of triticale, the optimal plot size is 3.12 m2, with coefficient of variation of 13.69%. Six replications are sufficient to identify as significant, differences between treatment means of 25% for experiments with up to seven treatments and of 30% for experiments with up to 28 treatments, regardless of the experimental design.

ABSTRACT: Leaf area is an important growth variable in agricultural crops and the leaf is the main variable of interest in the tobacco industry. So, the aim of this scientific research was to estimate the Burley tobacco leaf area by linear dimensions of the leaves and to determine which mathematical model is more adequate for this purpose. Two experiments were carried out with Burley tobacco, cultivar DBH 2252, in 2016/2017 and 2018/2019 agricultural years, respectively, in the municipalities of Itaqui and Vanini - RS - Brazil. In 600 leaves were measured length (L), width (W), length×width product (LW), length/width ratio (L/W) and determined the real leaf area (LA). Four hundred and fifty leaves were separated to generate models of the leaf area as a function of linear dimension and the other 150 leaves were used for model’s validation. The power model LA = 0.5037LW1.04435 (R² = 0.9960) is the most adequate for Burley tobacco ‘DBH 2252’ leaf area estimation. Alternatively, the models LA=2.0369W1.8619 (R²=0.9796) and LA=0.1222L2.2771 (R²=0.9738) based on width and length, respectively, can be used when only one leaf dimension is measured.