LOSS SAMPLING METHODS FOR SOYBEAN MECHANICAL HARVEST

• Autor(a) principal: Paixão, Carla Segatto Strini
• Data de Publicação: 2022
• Outros Autores: Voltarelli, Murilo Aparecido, Souza, Jarlyson Brunno Costa [UNESP], DE BRITO FILHO, Armando Lopes [UNESP], DA SILVA, Rouverson Pereira [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.14393/BJ-v38n0a2022-56409; http://hdl.handle.net/11449/242166
• topic: Control Charts; Glycine max L; Grain Harvester; Loss Methodology; Statistical Process Control

Harvesting is one of the most important stages of the agricultural production process. However, the lack of monitoring during this operation and the absence of efficient methodologies to quantify losses have contributed to the decline in the quality of the operation. The objective of this study was to monitor mechanized soybean harvest by quantifying losses through two methodologies using statistical process control. The study was conducted in March 2016 in an agricultural area in the municipality of Ribeirão Preto, SP, using a John Deere harvester model 1470 with a tangential-type track system and separation by a straw-blower. The experimental design followed the standards established by statistical process control, and every 8 min of harvest, the total losses by the circular framework and rectangular framework methodologies were simultaneously quantified, totaling 40 points. Data were analyzed using descriptive statistics and statistical process control. The averages of the circular methodology framework were values above those found in the rectangular methodology framework, presenting greater representativeness of losses. The process was considered unable to maintain losses of soybeans at acceptable levels during mechanical harvest throughout the operation of the two frameworks. The circular framework for collecting samples at different locations resulted in higher reliability of data.