An innovative multivariate tool for fuel consumption and costs estimation of agricultural operations

Abstract

The estimation of operating costs of agricultural and forestry machineries is a key factor in both planning agricultural policies and farm management. Few works have tried to estimate operating costs and the produced models are normally based on deterministic approaches. Conversely, in the statistical model randomness is present and variable states are not described by unique values, but rather by probability distributions. In this study, for the first time, a multivariate statistical model based on Partial Least Squares (PLS) was adopted to predict the fuel consumption and costs of six agricultural operations such as: ploughing, harrowing, fertilization, sowing, weed control and shredding. The prediction was conducted on two steps: first of all few initial selected parameters (time per surface-area unit, maximum engine power, purchase price of the tractor and purchase price of the operating machinery) were used to estimate the fuel consumption; then the predicted fuel consumption together with the initial parameters were used to estimate the operational costs. Since the obtained models were based on an input dataset very heterogeneous, these resulted to be extremely efficient and so generalizable and robust. In details the results show prediction values in the test with r always ≥ 0.91. Thus, the approach may results extremely useful for both farmers (in terms of economic advantages) and at institutional level (representing an innovative and efficient tool for planning future Rural Development Programmes and the Common Agricultural Policy). In light of these advantages the proposed approach may as well be implemented on a web platform and made available to all the stakeholders.

Multivariate Analysis of Peanut Mechanized Harvesting

“…The use of Multivariate exploratory techniques to control mechanized farming operations is a reality, as an innovative tool in the estimat ion of operating costs of Engenharia Agrícola, Jaboticabal, v.38, n.2, p.244-250, mar./apr. 2018 agricultural and forestry machineries (Guerrieri et al, 2017). The studies about the impact of mechanization through soil tillage on the behavior of weeds were efficient based on the similarity (CA) of the weeds (Boscardin et al, 2016;Nagahama et al, 2014).…”

Validation of Criteria for Predicting Tractor Fuel Consumption and CO2 Emissions When Ploughing Fields of Different Shapes and Dimensions

“…The calculation and planning of the working time of agricultural machinery is closely related to the economic and ecological indicators of the farm and its productivity. The ability to pre-calculate the efficiency of tillage operations, especially fuel consumption and exhaust gas pollution, is one of the more important tasks in order to rationally use energy resources in agricultural production and have less harmful impact on the environment [8,9]. Paris et al conducted a review emphasising the need to create and apply standardized methodologies for the analysis of energy use in agricultural systems [10].…”

Performance of agricultural tractor with and without automatic transmission and engine rotation management

“…Onboard systems for transmission and engine rotation management are constituted of hardware, which stores and executes customized software (Jha et al, 2019) in order to increase the economic return by reducing fuel consumption, which may interfere with the operational performance of agricultural tractors and production costs (Guerrieri et al, 2016).…”