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The state of Rio Grande do Sul (RS) is the third largest sunflower producer in Brazil. This study verified the existence of linear relationships between grain yield, oil content, and oil yield in sunflower (Helianthus annuus L.) genotypes evaluated in RS. The data on grain yield (GY), oil content (OC), and oil yield (OY) were obtained from 73 sunflower cultivar trials in 21 municipalities in RS from 1999 to 2018. Scatter diagrams were createdto investigate the relationships between the variables GY, OC, and OY. Then, Pearson's linear correlation coefficient (r) was calculated between the variables, and the Student's t-test was performed at a 5% significance level. There is a positive and significant linear relationship between PG and OY. However, no linear relationship was found between grain yield and oil content in sunflower genotypes. Additionally, a positive linear association of high magnitude (r = 0.9672) was observed between grain yield and oil yield, while a low magnitude (r = 0.2245) was found between oil content and oil yield. [ABSTRACT FROM AUTHOR]

Due to the economic importance of maize, it is essential to evaluate the performance of genotypes under environmental variations (years, locations, and seasons). Consequently, researchers have scrutinized genotype-environment (G×E) interactions to ensure reliability in genotype recommendations. Furthermore, when a G×E interaction exists, adaptability and stability analysis can be performed. This analysis enables one to identify genotypes with predictable responses and adaptability to environmental variability. Hence, this study sought to determine if there is a G×E interaction and evaluate the response of 16 maize genotypes across seven environments through adaptability and stability analyses. Seven experiments were conducted with 16 maize genotypes using a randomized complete block design with three replications. Tassel length (TL), tassel branch number (TBN), tassel dry matter (TDM), and grain yield (GY) were evaluated. Individual and joint variance analyses were performed, along with the F-test at a 5% significance level. The complex parts of the interaction between genotypes and pairs of environments were estimated, followed by adaptability and stability analyses using the Eberhart and Russell method. A genotype-environment interaction was found for TL, TBN, TDM, and GY, indicating that genotypes respond differently in various environments. However, considering all four traits, there is no indication of the ideal genotype. [ABSTRACT FROM AUTHOR]

Com o objetivo de verificar a existência de variabilidade temporal e espacial do tamanho de amostra da temperatura mínima do ar média mensal de trinta e sete municípios do Rio Grande do Sul, utilizaram-se os dados de temperatura mínima do ar do período de 1931 a 2000. Determinou-se o tamanho de amostra da temperatura mínima do ar média mensal em cada mês e município. Realizou-se análise de agrupamento dos meses e dos municípios pelo método hierárquico "vizinho mais distante". Há variabilidade do tamanho de amostra (número de anos) para a estimativa da temperatura mínima do ar média mensal no Estado do Rio Grande do Sul no tempo e no espaço. Maior tamanho de amostra, no Estado do Rio Grande do Sul, é necessário nos meses de maio, junho e julho, com diminuição gradativa em direção a janeiro e dezembro. Há variabilidade do tamanho de amostra entre os municípios do Estado do Rio Grande do Sul.

A falta da comparabilidade dos efeitos nos ensaios de competição de genótipos de milho (Zea mays) pode resultar em recomendações equivocadas. O objetivo deste trabalho foi verificar se o enquadramento dos genótipos de milho quanto ao ciclo é correto e se este altera a comparação das médias. Foram conduzidos seis experimentos de competição de genótipos de milho de ciclo superprecoce, precoce e normal, em dois níveis tecnológicos, na área experimental da UFSM, durante o ano agrícola de 2000/2001. O experimento bifatorial (genótipos nas parcelas principais e densidades nas subparcelas) foi conduzido no delineamento blocos ao acaso com três repetições. A proporção de experimentos de pressuposições adequadas foi alta, indicando análise de boa qualidade. Os genótipos de milho encontram-se mal agrupados quanto ao ciclo e, por conseqüência, quanto à estatura de plantas, aumentando a heterogeneidade nos experimentos e prejudicando a comparação das médias. Genótipos de milho com ciclo e/ou estatura de plantas diferentes não devem ser comparados na mesma densidade e experimento.

Hectolitre weight (HW) is the principal quantitative parameter used by receiving units as an indicator of the quality of wheat grain (Triticum aestivum L.). The moisture content and the equipment used can be considered important sources of variation to assess a batch, requiring correct sizing of the sample used to measure the HW. This research identified the variability between the equipment used to evaluate HW with or without correcting the grain moisture content, and to estimate the ideal number of samples for the commercial classification of wheat batches. The experiment was carried out in a randomised block design with four replications. Seven batches of wheat grain from different cultivars and/or production sites were used to measure the HW using three types of equipment (Equipment ‘A’, Equipment ‘B’ and Equipment ‘C’), with and without correcting the grain moisture content to 13%. Higher values for HW were determined with Equipment ‘A’ (77.15) compared to Equipment ‘B’ (75.08) and Equipment ‘C’ (74.69), classifying the wheat according to type. The moisture content affected the HW, but did not change the final classification of the wheat in terms of type. The ideal number of samples for HW ranged from 1 to 18 at the lowest level of precision (HW=mean±1 kg hl-1) and from 67 to 1820 samples for the highest precision (HW=mean±0.1 kg hl-1). Equipment ‘B’ requires a smaller number of samples (possibly as few as one) for the same level of precision (HW=mean±1 kg hl-1), whereas Equipment ‘A’ requires a greater number of samples for the majority of batches. Correctly classifying wheat by HW therefore depends on a larger number of samples. [ABSTRACT FROM AUTHOR]

Fungal diseases in Brazilian regions with tropical and subtropical climates reduce the production potential of corn crops. The use of fungicides is one of the strategies to maintain productivity. This study evaluated the agronomic performance and grain quality of corn hybrids associated with the preventive use of fungicides in subtropical environments. Six experiments were conducted in Santa Maria-RS, São Vicente do Sul-RS, and Frederico Westphalen-RS during two sowing seasons. The experiment was conducted in a randomized complete block design with a split-plot arrangement, in which the main plot consisted of two levels of the fungicide factor (with and without) and the sub-plot consisted of six levels of corn hybrids (AG9025, AS1730, P3016, MG300, DKB230, and FEROZ). A total of 216 experimental plots were evaluated for grain productivity, and eight plants per plot were evaluated for other traits, totaling 1,728 evaluated plants. Therefore, environmental conditions influence the interaction between the factors of fungicide use and hybrid cultivar positioning, with no significant interaction in years with a water deficit. Early sowings in subtropical environments indicate better agronomic performance and a lower percentage of moldy grains regardless of the cultivation location, contributing to grain quality. [ABSTRACT FROM AUTHOR]

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 cidtivars 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. [ABSTRACT FROM AUTHOR]

The objective of this research was to determine the influence of the basic experimental unit size (BEU) to estimate the optimum plot size, in the evaluation of white lupine (Lupinus albus L.) fresh matter weight. Data from fresh matter weight to 123, 137 and 150 days after sowing were evaluated. In every season 432BEU 1m x 1m (1m²) were evaluated and 16BEU plans of sizes from 1 to 16m² were formed. For each BEU plan, the optimum plot size was determined by the method of maximum curvature of the coefficient of variation model. The least significant difference by Tukey's test in 448 scenarios formed by the combinations of 16 plot sizes, i treatments (i=5, 10, 15 and 20), and r replicates (r=3, 4, 5, 6, 10, 15 and 20) for randomized block designs was calculated. Estimate of optimum plot size depends of the basic experimental unit size. It is indicated to evaluate the fresh matter weight in basic experimental units smallest possible size, for use in the estimation of optimum plot size. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the sample size, in number of years, to estimate the means monthly rainfall in locations of Mato Grosso do Sul and verify its spacetemporal variability. It was used the rainfall data for the period 1954-2013, collected from the Hydrological Information System of the National Water Agency - ANA. The means and standard deviation were calculated for each of the 384 time series (12 months × 32 locations) and the aleatory and normality data were tested. Then it was verified the homogeneity of variance among months in each locality and among locality in each month and it was determined the sample size to estimate the means monthly rainfall in each month and locality. The sample size (number of years) to estimate the means monthly rainfall is dependent on the month and locality. One concluded that 63 years of data are enough to predict the average monthly rainfall, with an estimation error equal to 45% of estimated average, with a degree confidence of 95%. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]