Publications - Enhancing Cocoa Crop Resilience in Ghana: The Application of Convolutional Neural Networks for Early Detection of Disease and Pest Infestations

Atianashie Miracle. (2024). Enhancing Cocoa Crop Resilience in Ghana: The Application of Convolutional Neural Networks for Early Detection of Disease and Pest Infestations. Qeios. doi:10.32388/DPS5ZH.Atianashie Miracle. (2024). Enhancing Cocoa Crop Resilience in Ghana: The Application of Convolutional Neural Networks for Early Detection of Disease and Pest Infestations. Qeios. doi:10.32388/DPS5ZH.Atianashie Miracle. (2024). Enhancing Cocoa Crop Resilience in Ghana: The Application of Convolutional Neural Networks for Early Detection of Disease and Pest Infestations. Qeios. doi:10.32388/DPS5ZH.

This study explores the revolutionary integration of Artificial Intelligence (AI), specifically Convolutional Neural Networks (CNNs), in combating cocoa disease and pest infestations in Ghana. As a significant stride towards sustainable agriculture and food security, the research explores AI's transformative impact on cocoa farming, a critical sector in Ghana's economy and the global chocolate supply.

The use of CNNs has emerged as a potent tool for accurate disease and pest detection, offering a new era of efficiency and precision in agricultural practices. The research was strategically focused on the practical applications of AI and CNNs in identifying and managing cocoa plant diseases and pests in Ghana, avoiding overly technical dissections of AI mechanisms. It aimed to illuminate the tangible, on-the-ground impacts of this technology and the transformative advancements it brings to the agricultural sector, particularly in cocoa farming.

The effort involved gathering up-to-date information on AI nuances, CNN specifics and applications, and the dynamics of cocoa disease and pest detection. The study's results highlight the profound potential of AI to augment productivity in the Ghanaian cocoa industry. CNNs have proven to be a powerful tool in analyzing and interpreting agricultural data, providing unprecedented insights into crop health and development.

Furthermore, the capability of AI to enhance disease and pest detection has been recognized as critical in maintaining crop health and ensuring the sustainability of cocoa farming in the face of evolving challenges. The study underscores the potential of AI in safeguarding food security and highlights its role as a powerful ally in addressing agricultural challenges through technological innovation.