Statistical process control applied to mechanized peanut sowing as a function of soil texture

• Autor(a) principal: Zerbato, Cristiano [UNESP]
• Data de Publicação: 2017
• Outros Autores: Angeli Furlani, Carlos Eduardo [UNESP], Santana Ormond, Antonio Tassio [UNESP], Silva Girlo, Lucas Augusto da [UNESP], Carneiro, Franciele Morlin [UNESP], Silva, Rouverson Pereira da [UNESP], Behalf Lab Agr Machinery Mec [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1371/journal.pone.0180399; http://hdl.handle.net/11449/165684

The successful establishment of agricultural crops depends on sowing quality, machinery performance, soil type and conditions, among other factors. This study evaluates the operational quality of mechanized peanut sowing in three soil types (sand, silt, and clay) with variable moisture contents. The experiment was conducted in three locations in the state of Sao Paulo, Brazil. The track-sampling scheme was used for 80 sampling locations of each soil type. Descriptive statistics and statistical process control (SPC) were used to evaluate the quality indicators of mechanized peanut sowing. The variables had normal distributions and were stable from the viewpoint of SPC. The best performance for peanut sowing density, normal spacing, and the initial seedling growing stand was found for clayey soil followed by sandy soil and then silty soil. Sandy or clayey soils displayed similar results regarding sowing depth, which was deeper than in the silty soil. Overall, the texture and the moisture of clayey soil provided the best operational performance for mechanized peanut sowing.