Rural mechanisation and fleet organisation have an essential impact on agricultural production and sustainable development of farm institutions. Machine functional parameters define the fleet composition and management and, thus, play an important role in economic and environmental performance of a farm. Programming methods and decision support systems are available in the market, however, there is still a lack of applicative tools which allow modelling and forecasting of technical parameters as well as costs to complete the decision tasks. Availability of such models in relation to dimensions, mass, power or working capacity, is then particularly necessary not only to support decisions at the different applied management levels (farmer, stakeholder, policy makers), but also to study the impact of farm machine on the environment and in general to understand trends in agricultural mechanization. The present research is aimed at identifying the most relevant parameters (including working width, overall dimensions, mass and power) for different groups of agricultural machines, modelled and characterised through the application of linear regression analyses. The study is defined on the basis of a database populated on purpose with more than 5000 agricultural machines models (30 machine groups) available in the market. Extracted equations give evidence of high correlations (R2 > 0.75) in particular between prices, mass and needed power, supporting the possibility of analyses on mechanisation trends, from both economical, management and environmental point of view.

Modelling of Agricultural Machinery Trends for Power, Mass, Working Width and Price

Marinello F.
;
Yezekyan T.;Sartori L.
2020

Abstract

Rural mechanisation and fleet organisation have an essential impact on agricultural production and sustainable development of farm institutions. Machine functional parameters define the fleet composition and management and, thus, play an important role in economic and environmental performance of a farm. Programming methods and decision support systems are available in the market, however, there is still a lack of applicative tools which allow modelling and forecasting of technical parameters as well as costs to complete the decision tasks. Availability of such models in relation to dimensions, mass, power or working capacity, is then particularly necessary not only to support decisions at the different applied management levels (farmer, stakeholder, policy makers), but also to study the impact of farm machine on the environment and in general to understand trends in agricultural mechanization. The present research is aimed at identifying the most relevant parameters (including working width, overall dimensions, mass and power) for different groups of agricultural machines, modelled and characterised through the application of linear regression analyses. The study is defined on the basis of a database populated on purpose with more than 5000 agricultural machines models (30 machine groups) available in the market. Extracted equations give evidence of high correlations (R2 > 0.75) in particular between prices, mass and needed power, supporting the possibility of analyses on mechanisation trends, from both economical, management and environmental point of view.
Lecture Notes in Civil Engineering
978-3-030-39298-7
978-3-030-39299-4
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/3339136
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