10.6084/m9.figshare.7451768.v1 Rafaela Greici da Motta Camicia Rafaela Greici da Motta Camicia Marcio Furlan Maggi Marcio Furlan Maggi Eduardo Godoy de Souza Eduardo Godoy de Souza Claudio Leones Bazzi Claudio Leones Bazzi Evandro André Konopatzki Evandro André Konopatzki Gabriela Karoline Michelon Gabriela Karoline Michelon José Bruno Santos Pinheiro José Bruno Santos Pinheiro Productivity of soybean in management zones with application of different sowing densities SciELO journals 2018 precision agriculture grain production management zones 2018-12-12 02:47:06 Dataset https://scielo.figshare.com/articles/dataset/Productivity_of_soybean_in_management_zones_with_application_of_different_sowing_densities/7451768 <div><p>ABSTRACT: The present study aimed to assess the efficiency of sowing at variable rates for soybean cultivation in two management zones (MZs) which were defined based on stable attributes and correlated with productivity using the Fuzzy C-means clustering algorithm and the kriging interpolation.Seeding was carried out in the 2015/2016 and 2017/2018 crops with a variation of 20% of seeds and crop row spacing of 0.70m. In each MZ, 8 plots with higher and lower seed density were established. Productivity was measured using a harvest monitor connected to a harvester. Data were filtered and submitted to descriptive analysis. Productivity maps were generated using the inverse square distance interpolation for each seeding density. In the MZ with the highest productive potential (MZ 1), the productivity was 3.39 and 3.18t ha-1, and in the MZ with the lowest productive potential (MZ 2) the productivity was 3.30 and 3.11t ha-1 for the years 2016 and 2018, respectively. Interpolation estimated higher productivity with the application of 15 plants m-1. Based on the economic analysis, it is suggested in this study the application of 214,000 plants ha-1 in both MZs.</p></div>