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THE IMPACT OF ARTIFICIAL INTELLIGENCE IN ENHANCING POST-HARVEST MANAGEMENT: A CASE STUDY OF RICE MILLS IN BENUE STATE

  • Project Research
  • 1-5 Chapters
  • Abstract : Available
  • Table of Content: Available
  • Reference Style:
  • Recommended for :
  • NGN 5000

Background of the Study

Post-harvest losses in agriculture pose a significant challenge to food security and economic stability, particularly in Nigeria. Benue State, known as the "food basket" of Nigeria, faces substantial post-harvest losses in rice production due to poor storage, handling, and processing techniques.

Artificial Intelligence (AI) has the potential to revolutionize post-harvest management by providing advanced tools for monitoring crop conditions, predicting spoilage risks, and automating processing tasks. AI-powered systems can analyze environmental conditions, optimize storage parameters, and enhance the efficiency of rice milling processes. These technologies can reduce losses, improve product quality, and increase profitability for rice farmers and millers.

This study investigates the impact of AI in enhancing post-harvest management in rice mills across Benue State.

Statement of the Problem

Post-harvest losses in rice production remain a persistent issue in Benue State, leading to reduced income for farmers and millers. Traditional methods of post-harvest management lack the precision and efficiency required to minimize these losses. This study explores how AI-driven solutions can address these challenges.

Aim and Objectives of the Study

Aim:
To assess the impact of Artificial Intelligence in enhancing post-harvest management in rice mills in Benue State.

Objectives:

  1. To identify the challenges in post-harvest management of rice in Benue State.
  2. To evaluate the effectiveness of AI-powered solutions in reducing post-harvest losses.
  3. To assess the impact of AI on the quality and profitability of rice production.

Research Questions

  1. What are the primary challenges in post-harvest rice management in Benue State?
  2. How can AI-driven solutions enhance the efficiency of post-harvest processes?

Research Hypotheses

  1. AI-driven systems reduce post-harvest losses in rice mills.
  2. AI-powered technologies improve the quality of post-harvest rice products.
  3. The use of AI increases the profitability of rice production in Benue State.

Significance of the Study

The findings of this study provide practical solutions for reducing post-harvest losses, contributing to food security and economic development. It offers valuable insights for farmers, rice millers, and policymakers.

Scope and Limitation of the Study

The study focuses on the application of AI in post-harvest management within rice mills in Benue State. Limitations include access to proprietary data and the study's focus on rice production alone.

Definition of Terms

  1. Post-Harvest Management: The processes involved in handling, storage, and processing of crops after harvest.
  2. Artificial Intelligence (AI): The use of advanced algorithms to analyze data and optimize processes.
  3. Rice Mills: Facilities where harvested rice is processed and prepared for distribution.




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