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>