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Global Food Production and Distribution Analysis using Data Mining and Unsupervised Learning.

Himanshu Shekhar1, Abhilasha Sharma1

  • 1Department of Software Engineering, Delhi Technological University, New Delhi, 110042, India.

Recent Advances in Food, Nutrition & Agriculture
|January 27, 2023
PubMed
Summary
This summary is machine-generated.

Global food supply chains are complex. Data mining and machine learning reveal production and distribution patterns, highlighting that current output is insufficient to feed the growing global population.

Keywords:
Food industryagricultural creditclusteringdata miningeconomic foundations.food distribution

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Area of Science:

  • Agricultural Economics
  • Food Systems Analysis
  • Supply Chain Management

Background:

  • The global food industry's complexity impacts biodiversity and ecosystem sustainability.
  • Understanding consumption patterns is key to optimizing nutrition for a growing population without expanding agricultural land.
  • Food preservation and efficient supply chains are crucial for economic advancement and social sustainability.

Purpose of the Study:

  • To quantitatively analyze global and regional food supply chains.
  • To reveal the flow of food and feed products worldwide.
  • To comprehend shifts in supply and consumption patterns using AI for global food instability.

Main Methods:

  • Utilized data mining and machine learning for quantitative analysis of food production and distribution.
  • Employed statistical approaches and feature engineering to identify key variables.
  • Applied clustering algorithms (e.g., K-Means) to group and identify significant patterns in food supply data.

Main Results:

  • Identified the global food production and distribution subsystem using data mining and machine learning.
  • Revealed relationships between food supply elements and factors like urbanization, economic conditions, and demand.
  • Established the efficiency and dynamism of food supply and distribution systems through exploratory analysis.

Conclusions:

  • Demonstrated crop flow patterns, with a few high-production countries insufficient for global needs.
  • Highlighted the need for significant socioeconomic and dietary changes to support global food security.
  • Emphasized the importance of boosting agricultural credit and economic foundations for sustainable food systems.