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Modeling of Mechanized Sugarcane Harvesting to Support Decision-Making on Asset Management

  • S.I. : Innovation for Sustainability of the Sugar Agro-Industry
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Abstract

The development and application of modeling in agriculture are a valuable tool that can be used as a guide for research and technology management. Several studies were carried out to evaluate the operational performance of sugarcane harvesters, but always focussed on measuring operational capacity at constant speed. This study aims to propose a model that simulates the harvesting operational capacity using as variables the components that define the harvestability index and the nominal capacity of the harvester to feed on and process sugarcane with its active components. The mechanized harvest model was validated by a performance test on a harvest front with four harvesters lasting 24 h. The Chi-square statistical test indicated that the values obtained from operational yield in the field and the model estimates agreed with each other, indicating that the model fits for the  purpose. Subsequently, the model was submitted to explore  analysis where we could verified the impact of the main offenders—harvestability index (HI) and the nominal yield of the harvester (NY)—on the performance of the mechanized harvesting, demonstrating that the osperational speed is a function of HI and NY.

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Acknowledgements

The authors thank the UMOE Bioenergy to support for performing the fieldwork.

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Authors and Affiliations

  1. Department of Agricultural Machinery, Universidade Estadual de Campinas/FEAGRI, Campinas, SP, Brazil

    Américo Ferraz Dias Neto & Daniel Albiero

  2. Programa Cana de Açúcar, UPD Jau, Scientific researcher VI IAC, Jau, SP, Brazil

    Raffaella Rossetto

  3. Department of Post Harvest Technology, Universidade Estadual de Campinas/FEAGRI, Campinas, SP, Brazil

    João D. Biagi

Authors
  1. Américo Ferraz Dias Neto
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  2. Daniel Albiero
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  3. Raffaella Rossetto
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  4. João D. Biagi
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Contributions

Dias Neto, A. F. involved in conceptualization. Dias Neto, A. F. took part in data acquisition. Dias Neto, A. F.; Rossetto, R.; Biagi, J. D.; Albiero, D. took part in data analysis. Dias Neto, A. F. involved in design of methodology. Dias Neto, A. F. took part in writing. Dias Neto, A. F. took part in editing.

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Correspondence to Américo Ferraz Dias Neto.

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Dias Neto, A.F., Albiero, D., Rossetto, R. et al. Modeling of Mechanized Sugarcane Harvesting to Support Decision-Making on Asset Management. Sugar Tech 24, 798–812 (2022). https://doi.org/10.1007/s12355-022-01126-2

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  • DOI: https://doi.org/10.1007/s12355-022-01126-2

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