Models for predicting coffee yield from chemical characteristics of soil and leaves using machine learning.

Journal: Journal of the science of food and agriculture
PMID: 38323721

Abstract

BACKGROUND: Coffee farming constitutes a substantial economic resource, representing a source of income for several countries due to the high consumption of coffee worldwide. Precise management of coffee crops involves collecting crop attributes (characteristics of the soil and the plant), mapping, and applying inputs according to the plants' needs. This differentiated management is precision coffee growing and it stands out for its increased yield and sustainability.

Authors

  • Rafael de Oliveira Faria
    Agricultural Engineering Department, Federal University of Lavras, Lavras, Brazil.
  • Aldir Carpes Marques Filho
    Agricultural Engineering Department, Federal University of Lavras, Lavras, Brazil.
  • Lucas Santos Santana
    Agricultural Science Institute, Federal University of Vale do Jequitinhonha e Mucuri - UFVJM, Unaí, Brazil.
  • Murilo Battistuzzi Martins
    Mato Grosso do Sul State University - UEMS, Dourados, Brazil.
  • Renato Lustosa Sobrinho
    Federal University of Technology-Paraná (UTFPR), Pato Branco, Brazil.
  • Tiago Zoz
    Mato Grosso do Sul State University - UEMS, Dourados, Brazil.
  • Bruno Rodrigues de Oliveira
    Pantanal Editora, Nova Xavantina, Brazil.
  • Yasmeen A Alwasel
    Botany and Microbiology Department, College of Science, King Saud University, Riyadh, Saudi Arabia.
  • Mohammad K Okla
    Botany and Microbiology Department, College of Science, King Saud University, Riyadh, Saudi Arabia.
  • Hamada Abdelgawad
    Integrated Molecular Plant Physiology Research, Department of Biology, University of Antwerp, Antwerp, Belgium.

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