RESUMO A produção de biomassa de aveia voltada à elaboração de silagem de qualidade é dependente de elementos climáticos e nitrogênio sem ocorrência de acamamento. O objetivo do presente estudo é a definição da dose ideal do regulador de crescimento que possibilite, no máximo, 5% de acamamento de plantas de aveia, bem como a identificação das variáveis potenciais para composição do modelo de regressão linear múltipla com simulação da produtividade de biomassa à elaboração de silagem nas condições de uso do regulador, em reduzida, alta e muito alta fertilização com nitrogênio. O estudo foi conduzido em 2013, 2014 e 2015, em delineamento de blocos ao acaso, com quatro repetições em esquema fatorial 4x3, para doses de regulador (0, 200, 400 e 600mL ha-1) e doses de nitrogênio (30, 90 e 150kg ha-1), respectivamente. A dose de 495mL ha-1 de regulador se mostra eficiente na redução do acamamento de plantas de aveia em condição de reduzida, alta e muito alta fertilização com nitrogênio. A soma térmica, a precipitação, a radiação, a dose de regulador e o nitrogênio qualificam a composição do modelo de regressão linear múltipla, tornando eficiente a simulação da produtividade de biomassa da aveia para silagem ao longo do ciclo.

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ABSTRACT In order to be considered highly reliable (showing very accurate results), an experiment needs to be very well planned. Defining the experimental plot size and number of replicates is fundamental to control the experimental error at the beginning of the experiment. The aim of this study was to estimate the plot size and the number of replicates sufficient to perform experiments with Cucumis sativus. A uniformity trial was installed in the first week of January 2017. The spacing used was 0.3 m between plants and 1 m between rows, resulting in 12 plants in each of the 12 cultivation rows and each basic experimental unit was composed of one plant. The variables observed in 18 harvests were average fruit mass (MMF, in g), average fruit length (CMF, in cm) and average fruit diameter (DMF, in cm). The harvests were analyzed individually and grouped to reduce experimental variability. The number of replicates and the plot size were estimated using the method of maximum curvature of the coefficient of variation. The plot size and the number of replicates were influenced by the variability in the rows and between the harvests. We recommend plots consisting of four plants per cultivation row with six replicates for the minimum significant difference by Tukey’s test, expressed in 25% the means percentage.

The growth regulator modifies the expression of lodging and panicle components in oat plants, with reflexes in yield. The objective of this study was to define the optimal dose of growth regulator in oat for a maximum lodging of 5%. In addition, this study aimed to identify potential variables of the panicle to compose the multiple linear regression model and the simulation of grain yield in conditions of use of the regulator under low, high and very high fertilization with nitrogen. The study was conducted in 2011, 2012 and 2013 in a randomized block design with four replicates in a 4 x 3 factorial scheme, for growth regulator doses (0, 200, 400 and 600 mL ha-1) and N-fertilizer doses (30, 90 and 150 kg ha-1), respectively. The growth regulator doses of 395, 450 and 560 mL ha-1 are efficient, with maximum oat lodging of 5%, under low, high and very high nitrogen fertilization, respectively. The grain weight per panicle and panicle harvest index are potential variables to compose the multiple linear regression model. Multiple linear regression equations are efficient in the simulation of oat grain yield under the conditions of use of growth regulator, regardless of the N-fertilizer dose.

The great economic importance attributed to strawberry cultivation raises the interest in cultivars of high productivity and superior fruit quality. The quality of fruit is the most impacting factor for the strawberry marketing, but selecting genotypes that combine high production and high fruit quality has been a difficult task. The objective of this study was to determine the linear relationships between phenological, quality and production variables of strawberry aiming at identifying potential variables for indirect selection in future selection processes of strawberry genotypes. A trial was conducted in a randomized block design with two cultivars and two transplant origins, grown in four types of substrate. Fifteen variables, including phenological, productive and fruit quality-related variables were assessed. The selected variables explained 45.2 and 39.1 % for PC1 and PC2 respectively, totaling 84.3 % of the total variance of the variables in the PCA, and indicated important relationships between the variables, and a path analysis revealed success for indirect selection of total mass of fruits based on the total number of fruits (0.81413). Changes in crop management that reduces the period between planting date and full flowering may be an alternative to increase the production of strawberry and provide fruits with higher quality.