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Data mining and decision support systems for efficient dairy production.

Sunesh Balhara1, Rishi Pal Singh2, A P Ruhil3

  • 1ICAR-Central Institute for Research on Buffaloes, Hisar, Haryana, India.

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|July 5, 2021
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Summary

Selective breeding in dairy farming identifies elite animals for profitability. Data mining and artificial intelligence enhance feed conversion efficiency and sustainable livestock production.

Keywords:
dairy farmingdata miningdecision support systems

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Area of Science:

  • Animal Science
  • Data Science
  • Agricultural Economics

Background:

  • Gainful livestock farming relies on selective breeding for desirable heritable traits.
  • Modern dairy animal selection focuses on traits contributing to high milk production.
  • Feed conversion efficiency is crucial for identifying and breeding efficient milk producers.

Purpose of the Study:

  • To review data mining techniques and decision support systems for scientific dairy farming.
  • To highlight the role of data mining and AI in improving livestock production efficiency.
  • To identify elite animals for sustainable profitability in dairy enterprises.

Main Methods:

  • Review of data mining techniques.
  • Discussion of artificial intelligence applications in livestock farming.
  • Analysis of decision support systems for dairy management.

Main Results:

  • Data mining uncovers hidden patterns for improved breeding models.
  • AI and data mining offer new pathways for resource utilization efficiency.
  • Identification of elite animals is key for sustainable profitability.

Conclusions:

  • Data mining and AI are vital tools for scientific dairy farming.
  • These technologies enable enhanced feed conversion efficiency and economic viability.
  • Selective breeding programs can be optimized using advanced data analysis.