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| Galvão,Cezario B.; Garcia,Angel P.; Albiero,Daneil; Ribeiro,Admilson Í.; Banchi,Ângelo D.. |
| ABSTRACT In the mechanical harvesting of sugarcane, a self-propelled harvester is used in conjunction with an agricultural implement named infield wagon, which has the function of storing and transporting the harvested product. Much of the cost of sugarcane production comes from this operation (30 to 60%). Among the operational costs of agricultural machinery, the cost of repair and maintenance (CRM) is relevant. Therefore, the objective of this study was to determine the parameters of the CRM mathematical model based on the life (hours of use) for the infield wagon, using the method of the American Society of Agricultural and Biological Engineers (ASABE). These CRM models were obtained for two sets of infield wagon from different manufacturers and their... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Mechanical harvesting of sugarcane; Management of mechanization; Agricultural costs. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662018000300218 |
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| Banchi,Ângelo D.; Garcia,Angel P.; Grespan,Andrei; Albiero,Daniel; Favarin,Luis G. A.; Galvão,Cezario B.. |
| ABSTRACT The brazilian agriculture has expanded and improved its techniques in the last decades as well as the mechanization of sugarcane cultivation. Overall, the mechanization cost of this cultivation is the highest of the total cost of production in relation to other crops. That cost consists of several elements such as the cost of the harvester. This study aimed to develop a mathematical model that represents the operational cost of the harvester in relation to its operating life and agricultural productivity, parameters that are associated with its operational capacity. Simulations of this cost were conducted, raging the operating life of harvesters between 0 and 17,900 h, and the agricultural productivity of the cultivation from 50 to 130 Mg ha-1.... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Economic performance indicators; Multiple regression; Agricultural management; Agricultural machinery efficiency. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000700552 |
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