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Open AccessArticle

Modelling of Harvesting Machines’ Technical Parameters and Prices

1
Department of Land, Environment, Agriculture and Forestry, University of Padova, Via dell’Università 16, 35020 Legnaro, Italy
2
Edizioni L’Informatore Agrario srl, Via Bencivenga-Biondani, 16, 37133 Verona, Italy
*
Author to whom correspondence should be addressed.
Agriculture 2020, 10(6), 194; https://doi.org/10.3390/agriculture10060194
Received: 3 April 2020 / Revised: 23 May 2020 / Accepted: 28 May 2020 / Published: 1 June 2020
(This article belongs to the Special Issue Selected Papers from Engineering for Rural Development)
Technical and performance parameters of agricultural machines directly impact the operational efficiency and entire crop production. Sometimes, overestimation of technical and dimensional parameters of harvesting equipment is carried out with the intention of enhancing the operational efficiency, but this approach might turn out to negatively impact productivity due to unbalanced system design, and ultimately lead to financial losses. Therefore, a balanced preliminary estimation of technical parameters of equipment needs to be carried out before investment quantification, especially on the large capital-intensive machinery units, such as harvesting systems. In addition, availability of ready to use, simplified models for the price estimation from input technical parameters would reduce the complexity involved in this latter analysis. The current study is an attempt to provide tools to address these issues. A large dataset of combine and forage harvesters has been analyzed to investigate relevant parameter-to-parameter and parameter-to-price relations. The study of the available data allowed the determination of indicative models for the estimation of machine price, power, weight, tank capacity and working width. A significant correlation between power and price (R2 > 0.8) has been observed for two groups of harvesting machines. For combine harvesters, satisfactory correlations were found between power and weight, and power and tank capacity. A regression model for combine harvesters showed a satisfactory behavior at predicting the average working width that can be operated by a given power. On the other hand, for the forage harvesting group, the relation between these quantities has lower values; therefore, for better accuracy of the association, more sophisticated considerations should be incorporated, taking into account other parameters. View Full-Text
Keywords: cost modelling; harvesting operation; combine harvester; forage harvester; machinery price; farm management; decision support cost modelling; harvesting operation; combine harvester; forage harvester; machinery price; farm management; decision support
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MDPI and ACS Style

Yezekyan, T.; Marinello, F.; Armentano, G.; Trestini, S.; Sartori, L. Modelling of Harvesting Machines’ Technical Parameters and Prices. Agriculture 2020, 10, 194.

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