Definition of linear regression models to calculate the technical parameters of Italian agricultural tractors

Published: 16 June 2023
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As it is known, the modern agricultural tractor is no longer just a machine capable to pull agricultural trailers and to operate implements but has evolved into a multi-purpose and mobile energy source with standardized interfaces (mechanical, hydraulic and electronic) to connect to a several typologies of agricultural operating machines. It follows that the selection of the most appropriate tractors for the specific production realities is a crucial aspect for farmers, advisors, contractors and farm machinery experts. The tractors choice thus must consider different parameters, concerning not only the cost of the machines but also their dimensions, power, weight, technological level, etc. The availability of simplified models for estimating the purchase investment and sizing the machine in relation to its mechanical characteristics could be a useful tool in the choice of the tractor more suitable for the specific agricultural context. The aim of this study was to collect and to analyse the technical parameters of tractors present on the Italian market (more than 1300 models), divided into: i) four wheel-drive (4WD) standard tractors, ii) two wheel-drive (2WD) standard tractors, iii) narrow track 4WD tractors, iv) Isodiametric specialized 4WD tractors, v) crawler tractors and vi) rubber-tracked tractors), in order to define the most relevant parameter-to-parameter and parameter-to-price relations for updating reference models to calculate the machine price and the weight to engine power ratio. Other relations, including the three-point hitch efficiency with respect to tractor’s weight and the relationship between the rated engine power and its displacement, are proposed in order to provide synthetic tools to characterise and to compare - from the mechanical point of view - the different categories of agricultural tractors.

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Citations

ASABE, 2015. ASABE Standard EP496.3 FEB2006 (R2015): Agricultural Machinery Management. ASABE, St. Joseph, Michigan, USA.
Biondi P., Maraziti F., Monarca D. 1996. Technical trends of tractors and combines (1960 – 1989) based on Italian type-approval data. J. Agric. Eng. Res. 65:1-14.
Bodria L., Pellizzi G., Piccarolo P. 2013. Meccanica e meccanizzazione agricola. Ed. Edagricole, Milano, Italy.
Brenna M., Foiadelli F., Leone C., Longo M., Zaninelli, D. 2018. Feasibility proposal for heavy duty farm tractor. Proc. International Conference of Electrical and Electronic Technologies for Automotive, Milan, Italy: 1-6.
Calcante A., Brambilla M., Bisaglia C., Oberti R. 2019. Estimating the total lubricant oil consumption rate in agricultural tractors. Trans. ASABE, 62(1):197-204.
Estrada J.S., Schlosser J.F., Silveira de Farias M., Tellechea Martini A., Oliveira dos Santos G. 2016. Massa dos tratores agrícolas comercializados no mercado brasileiro. Ciênc. Rural, 46(08):1-5.
European Commission. 2016. Regulation (EU) 2016/1628 of 14 September 2016 on requirements relating to gaseous and particulate pollutant emission limits and type-approval for internal combustion engines for non-road mobile machinery, 2016/1628 In: Official Journal, L 252/53, 16/09/2016.
FAO (Food and Agricultural Organization). 2013. Mechanization for rural development: A review of patterns and progress from around the world. Vol. 20. Ed. FAO, Rome, Italy.
Golmohammadi G., Prasher S., Madani A., Rudra R. 2014. Evaluating Three Hydrological Distributed Watershed Models: MIKE-SHE, APEX, SWAT. Hydrology, 1:20-39.
Hawkins E.M., Buckmaster D.R. 2015. Benchmarking costs of fixed-frame, articulated, and tracked tractors. Appl. Eng. Agric. 31(5):741–745.
ISO, 2021. Tractors and machinery for agriculture and forestry — Basic types — Vocabulary . Norm ISO 12934:2021. International Organization for Standardization Publ., Geneva, Switzerland.
Jahn H. 2022. Regulations and measures for limiting emissions from non-road mobile machinery in Europe. VDI Berichte, 2022(2402): 13-28.
Lankenau G.F.D., Winter A.G.. 2018. An engineering review of the farm tractor’s evolution to a dominant design. Proc. ASME 2018 International Design Engineering/Technical Conferences and Computers and Information in Engineering Conference, Quebec City, Canada:1-19.
Lazzari M., Mazzetto F. 2016. Meccanica e meccanizzazione dei processi produttivi agricoli. Ed. Reda, Torino, Italy.
MAD Macchine Agricole Domani. 2022. Guida all’acquisto 2022. 1-2:60-89.
MAD Macchine Agricole Domani. 2022. Guida all’acquisto 2022. 3:73-88.
Márquez L. 2012. Tractores agrícolas: tecnología y utilización. Ed. B&H Grupo Editorial, Madrid, Spain.
Masek J., Novak P. 2018. Overview of combine harvester and tractor structure on farms in the Czech Republic. Engineering for Rural Development, 17:240-245.
McHugh M.L. 2008. Standard error: meaning and interpretation. Biochem Med, 18:7-13.
Moriasi D. N., Arnold J. G., Van Liew M. W., Bingner R. L., Harmel R. D., Veith. T. L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans. ASABE, 50(3):885–900.
OECD, 2022. Code 2: OECD Standard code for the official testing of agricultural and forestry tractor performance. Available from: http://www.oecd.org.
Renius K.T. 1994. Trends in tractor design with particular reference to Europe. J. Agr. Eng. Res. 57(1): 3-22.
Renius K.T. 2019. Fundamentals of tractor design. Ed. Springer Nature Switzerland AG, Cham, Switzerland.
Ruiz-Garcia L, Sanchez-Guerrero P. 2022. A Decision Support Tool for Buying Farm Tractors, Based on Predictive Analytics, Agriculture. 12(3):1-26.
Santhi C., Arnold J.G., Williams J.R., Dugas W.A., Srinivasan R., Hauck L.M. 2001. Validation of the SWAT Model on a Large River Basin with Point and Nonpoint Sources. J. Am. Water Resour. Assoc. 37:1169–1188.
Schlosser J.F., Debiasi H., Willes J.A., Dias da Costa Machado O. 2005. Análise comparativa do peso específico dos tratores agrícolas fabricados no Brasil e seus efeitos sobre a seleção e uso. Ciênc. Rural, 35(1):92-97.
Spoor G., Carillon R., Bournas L., Brown E.H. 1987. The Impact of Mechanization. Ed. John Wiley and Sons Ltd., Chichester, New York, USA.
Stirnimann R., Engelmann D. 2017. Development of Tractor Engines in the Past Twenty Years. ATZ Offhighw. Worldw. 10:70-77.
Stoss, K.J., Sobotzik J., Shi B., Kreis E.R. 2013. Tractor Power for Implement Operation − Mechanical, Hydraulic, and Electrical: An Overview. ASAE Lecture Series No. 37. St. Joseph, Michigan,USA
Tona E., Calcante A., Oberti R. 2018. The profitability of precision spraying on specialty crops: a technical–economic analysis of protection equipment at increasing technological levels. Precis. Agric. 19:606-629.
Van Liew M.W., Arnold J.G., Garbrecht J.D. 2003. Hydrologic simulation on agricultural watersheds: Choosing between two models. Trans. ASAE, 46:1539–1551.
Walley K., Custance P., Taylor S., Lindgreen A., Hingley M. 2007. The importance of brand in the industrial
purchase decision: A case study of the UK tractor market. J. Bus. Ind. Mark. 22:383–393.
Yezekyan T., Marinello F., Armentano G., Trestini S., Sartori L. 2018. Definition of reference models for power, weight, working width, and price for seeding machines. Agriculture, 8:2-13.
Yezekyan T., Marinello F., Armentano G., Trestini S., Sartori L. 2020. Modelling of harvesting machines’ technical parameters and prices. Agriculture, 10(6):1-12.

How to Cite

Calcante, A., Oberti, R. and Tangorra, F. M. (2023) “Definition of linear regression models to calculate the technical parameters of Italian agricultural tractors”, Journal of Agricultural Engineering, 54(4). doi: 10.4081/jae.2023.1525.