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December 1, 2018Indonesian Journal of Electrical Engineering and Computer ScienceOpen Access

Agriculture Data Analytics in Crop Yield Estimation: A Critical Review

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Authors

BSB. M. SagarGopalganj Science and Technology UniversityNCN. K. CauveryPresidency University

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Implication

Critical review evaluates data analytics methods for crop yield estimation in agriculture, highlighting persistent methodological gaps and operational challenges.

Key Points

  • Review the application of data analytics in agricultural crop yield prediction and highlight existing research gaps limiting effective implementation.
  • Reviewed published literature on big data and analytics methodologies deployed for agricultural management.
  • Evaluated computational strategies utilized for pre-sowing crop yield forecasting and crop health monitoring against environmental variables.
  • Identified climatic variability, geographic differences, and socioeconomic factors as primary obstacles affecting agricultural productivity and predictive modeling.
  • Identified critical gaps in measuring the tangible impact and effectiveness of big data analytics systems within routine agricultural practices.

Cite This Study

Sagar et al. (2018) studied this question.

synapsesocial.com/papers/6a71900635aa2c282ce2cf9bhttps://doi.org/10.11591/ijeecs.v12.i3.pp1087-1093
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