ABSTRACT The use of corn hybrids adapted to the soil and climate conditions of the cultivation region under adequate optimum plant density is a determining factor for the maximization of grain yield. In this sense, the objective was to evaluate the productivity of corn hybrids under two sowing densities during the 2020/21 crop season in the medium-high Uruguay region of the state of Rio Grande do Sul. The corn hybrids AS1555 PRO3, B2401 PWU, B2418 VYHR, B2612 PWU, BG7061 YHR, DKB235 PRO3, NS45 VIP3, NS73 VIP3, NS80 VIP3, P2501, P3016 VYHR, P3565 PWU and 30F53 VYHR were submitted to densities of 66,667 and 88,889 plants ha-1, in a randomized block design with ten replications. Corn hybrids showed superior grain yield when subjected to the density of 88,889 plants ha-1 in the medium-high Uruguay region of Rio Grande do Sul, surpassing in most cases the state and national average yield of harvest 2020/21. Most of the corn hybrids used present potential for cultivation at higher sowing density than their respective recommendations. Considering the superior productivity of hybrids NS80 VIP3, B2401 PWU and NS73 VIP3, their cultivation under conditions similar to those of the study is recommended. sense 202021 2020 21 2020/2 mediumhigh medium high Sul AS AS155 PRO3 PRO B B240 B241 B261 BG BG706 YHR DKB DKB23 NS NS4 VIP3 VIP NS7 NS8 P2501 P P301 P356 F 30F5 66667 66 667 66,66 88889 88 889 88,88 ha1, ha1 ha 1, 1 replications ha- recommendations recommended 20202 202 2 2020/ AS15 B24 B26 BG70 DKB2 P250 P30 P35 30F 6666 6 66,6 8888 8 88,8 20 AS1 B2 BG7 P25 P3 666 66, 888 88, P2

ABSTRACT Considering the expressive number of commercial soybean cultivars available for cultivation in Brazil and the constant search for improvements in the production system, the objective was to evaluate the productive components and grain yield and to estimate the correlation between them in soybean cultivars sown in the northwest region of Rio Grande do Sul, during the 2019/20 harvest. Sixteen commercial soybean cultivars were sown under their respective plant density recommendations, in a randomized block design with three replications. At the end of the cultivation cycle, the following variables were evaluated: plant height; height of insertion of the first pod; number of nodes; number of pods with one, two, three and four grains; pods per plant; grains per plant; weight of thousand grains, and; grain yield. The cultivars BMX ZEUS IPRO, NS 5445 IPRO and NS 5700 IPRO presented the highest grain yields, mainly due to the high relationship between the number of pods and grains per plant and the weight of a thousand grains. The indirect selection of more productive genotypes can be carried out through the variables weight of thousand grains, number of pods, grains and nodes per plant, given the significant positive correlation between them. system Sul 201920 2019 20 2019/2 harvest recommendations replications cycle evaluated pod one two 544 570 yields 20192 201 2 2019/ 54 57 5

ABSTRACT The aim of this study was to assess yield components and grain yield of soybean cultivars in response to sowing densities. For this, two soybean cultivars and five sowing densities were tested, in a two-factor scheme. The following yield components were measured by the end of the cycle: plant height; insertion height of the first pod; number of nodes per plant; number of pods with one, two, three and four grains; number of pods per plant; number of grains per plant; weight of a thousand grains; humidity and grain yield. Sowing densities did not cause significant variations of grain yield (bags ha-1) for any cultivar, however, higher populational densities promoted a reduction in the number of pods with two and three grains, as well as a reduction in the total number of pods and grains per plant for both cultivars. Cultivar NS 5700 IPRO was the most productive, with a higher number of pods with two and three grains and number of pods and grains per plant.

RESUMO: O girassol produz aquênios e óleo de qualidade, além de servir para produção de silagem, forragem e biodiesel. A modelagem de crescimento permite conhecer o padrão de crescimento da cultura e otimizar o manejo. O objetivo deste trabalho foi caracterizar o crescimento da cultivar de girassol Rhino por meio dos modelos Logístico e Gompertz e fazer considerações a respeito do manejo com base em pontos críticos. Os dados utilizados são oriundos de três ensaios de uniformidade com a cultivar de girassol confeiteiro Rhino, conduzidos na área experimental da Universidade Federal de Santa Maria, Campus Frederico Westphalen, na safra 2019/2020. Foram realizadas 14, 12 e 10 avaliações semanais de altura em 10 plantas, respectivamente, no primeiro, segundo e terceiro ensaio. Os dados foram ajustados em função da soma térmica acumulada. Os parâmetros foram estimados por meio do método dos mínimos quadrados ordinários, usando o algoritmo de Gauss-Newton. A qualidade de ajuste dos modelos aos dados foi medida pelo coeficiente de determinação ajustado, critério de determinação de Akaike, critério bayesiano de informação, e por meio da não linearidade intrínseca e paramétrica. Foram determinados os pontos de inflexão (IP), máxima aceleração (MAP), máxima desaceleração (MDP) e desaceleração assintótica (ADP). As análises estatísticas foram realizadas com Microsoft Office Excel® e o software R. Os modelos descreveram de forma satisfatória a curva de crescimento da altura do girassol, fornecendo parâmetros com interpretações práticas. O modelo Logístico apresenta melhor qualidade de ajuste, sendo o mais adequado para caracterização da curva de crescimento. Os pontos críticos estimados fornecem informações importantes para o manejo da cultura. As plantas daninhas devem ser controladas até o MAP. As aplicações de fertilizantes em cobertura devem ser realizadas entre MAP e IP. O ADP é um indicador de maturidade, após atingir este ponto, as plantas podem ser colhidas para a produção de silagem sem perda de volume e qualidade.

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.