Influência de datas de semeadura no desempenho agronômico de cultivares de soja

Abstract

The present study seeks to study how different sowing dates can influence the agronomic performance of soybean crops, with the main objective of evaluating changes in the yeld characteristics that each sowing time presents in the crop, taking into account all the biotic and abiotic factors that directly impact its productive potential. Ten soybean cultivars were sown in 3 different dates (11/06/2022, 11/23/2022 and 12/09/2022) in a 10 x 3 factorial scheme, in the Northwest Region of the State of Rio Grande do Sul, Brazil. Before sowing, it was a chemical analysis and soil correction were carried out to implement the crop. Throughout the cycle, flowering, plant height, height of the first pod, number of grains per pod, number of pods per plant, number of nodes, thousand grains weight, productivity and cycle duration were evaluated. Data analysis was carried out with the help of the Genes Program, where it was verified that there was an interaction between the genotypes and the environment (cultivars X sowing times), through joint data analysis (Test F at 5% error probability), for the analyzed variables. The data obtained from each cultivar at different times indicate that the sowing dates 06/11/2022 and 23/11/2022 had greater difficulties in establishment and prolonged periods of water stress in important phases of the crop, which harmed the development of some characters such as number of pods and number of grains per pod. The sowing date 09/12/2022 was the most productive, due to the highest rainfall in important phases of the crop. The cultivar most adapted to different environments was BMX Lótus, as its average productivity in the three sowing seasons was the one that stood out the most, while Pionner's cultivar 95R51 was the least productive cultivar, which may be combined with the low rainfall and to the short cycle. The highlighted cultivars, in addition to the BMX Lótus cultivar, on the sowing date of 12/09/2022 were also BMX Cromo and DM 56i59, both showing average productivity above 3,000 ha-1, even in conditions not favorable to production.