The Role of Artificial Intelligence in Crop Seed Quality Assurance in Ethiopia: -A Review

Abstract

Artificial intelligence (AI) technologies are increasingly being deployed to enhance crop seed quality assurance processes, which are critical for agricultural productivity and food security. This paper examines the potential role and applications of AI in improving seed quality assessment and management in Ethiopia. It provides an overview of current seed quality assurance practices in Ethiopia and explores how AI tools like machine learning algorithms, computer vision, and predictive analytics can be leveraged to enhance seed selection, monitoring, and quality control. The paper discusses challenges in implementing AI-based systems in the Ethiopian context, including limited infrastructure and farmer training. It also highlights opportunities for AI to address issues like climate change impacts on seed viability. Case studies of AI applications in seed quality assurance are presented, along with an analysis of relevant agricultural policies and regulations in Ethiopia. The paper concludes with recommendations for future research and development of AI-driven seed quality assurance systems tailored to Ethiopia's needs. Overall, AI has significant potential to transform seed quality management practices in Ethiopia, contributing to improved agricultural productivity and sustainability.

keywords: artificial intelligence, quality assurance, Ethiopia, machine learning, predictive analytics, data-driven decisions, seed quality assessment

DOI: 10.7176/CEIS/16-1-02

Publication date: April 30^th 2025