Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/6401
Title: Harnessing Artificial Intelligence and Machine Learning for Enhanced Agricultural Practices: A Pathway to Strengthen Food Security and Resilience
Authors: David Mhlanga
Farai Mlambo
Mufaro Dzingirai
David Mhlanga
Mufaro Dzingirai
College of Business and Economics, The University of Johannesburg, Johannesburg, South Africa
University of the Witwatersrand, Johannesburg, South Africa
Department of Business Management, Faculty of Commerce, Midlands State University, Gweru, Zimbabwe
College of Business and Economics, University of Johannesburg, Auckland Park, South Africa
Department of Business Management, Midlands State University, Gweru, Zimbabwe
Keywords: Artificial Intelligence
Machine Learning
Enhanced Agricultural Practices
Food Security
Issue Date: 31-Aug-2024
Publisher: Palgrave Macmillan, Cham
Abstract: The global population is expected to exceed nine billion by 2050, necessitating at least a 70% increase in agricultural output to meet the demands of this growth. It is anticipated that only about 10% of this increase will come from newly developed areas, with the majority—90%—arising from enhanced productivity in existing agricultural practices. Addressing this challenge requires leveraging the latest advancements in technology to maximize agricultural efficiency. This research focuses on assessing the role of artificial intelligence (AI) and machine learning (ML) in enhancing food security and resilience, especially in developing economies. The study explains how AI and ML contribute to food security and resilience, offering practical recommendations for emerging markets to harness these technologies. The chapter concludes with an exploration of the impact of various AI and ML-driven technologies on food security.
URI: https://cris.library.msu.ac.zw//handle/11408/6401
Appears in Collections:Book Chapters

Files in This Item:
File Description SizeFormat 
Harnessing Artificial Intelligence and Machine Learning for Enhanced Agricultural Practices.pdfAbstract57.82 kBAdobe PDFView/Open
Show full item record

Page view(s)

22
checked on Jan 31, 2025

Download(s)

2
checked on Jan 31, 2025

Google ScholarTM

Check

Altmetric


Items in MSUIR are protected by copyright, with all rights reserved, unless otherwise indicated.