Smart Agricultural Technology 6 (2023) 100370 Available online 25 November 2023 2772-3755/© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Contents lists available at ScienceDirect Smart Agricultural Technology journal homepage: www.journals.elsevier.com/smart-agricultural-technology Exploring the optimal climate conditions for a maximum maize production in Ghana: Implications for food security Samuel Asante Gyamerah a,∗ , Clement Asare a , Desmond Mintah a , Bernice Appiah a , Florence Abiodun Kayode b a Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana b Department of Environmental Management, University of Energy and Natural Resources, Ghana A R T I C L E I N F O A B S T R A C T Editor: Spyros Fountas Keywords: Climate change Cereal production Machine learning techniques Artificial neural network Sustainable development goals In Sub-Saharan African (SSA) countries like Ghana, where a significant portion of the population relies on agriculture for their livelihoods and sustenance, climate variability poses a substantial threat to crop productivity and food security. Therefore, it is crucial to employ advanced methodologies to study the intricate relationship between climate change and crop yield. This study therefore aims to assess the impact of different climatic variables on the variation of maize yield in Ghana from 1992 to 2018 and the pivotal role of machine learning techniques in predicting the variations in maize yield, considering the complex climate-crop yield interactions. The machine learning techniques utilized include the Random Forest (RF) Model, the Extreme Gradient Boosting (XGBoost) model, and the Artificial Neural Network (ANN) model for prediction. The results demonstrate that rising temperatures and precipitation have a positive impact on Ghana’s maize yield. Additionally, the study identified a critical range of climatic conditions that maximized maize production during the study period. Specifically, an average temperature between 27.9 ◦ C and 28.1 ◦ C, coupled with a precipitation range of 1290 mm to 1390 mm, corresponds to the optimal conditions for achieving maize yields exceeding 2.0 MT/ha. Among the machine learning models utilized for the prediction, the ANN emerged as the optimal model with an approximate mean squared error of 1%. Ultimately, our results provide a comprehensive and actionable framework for stakeholders in the agricultural sector, equipping them with the knowledge and tools needed to adapt to climate change and optimize maize production in Ghana. 1. Introduction The growing global concern about climate change has heightened in recent decades, revealing its extensive impacts across various sec- tors. Agriculture is one such sector profoundly affected [1], as shifts in temperature, rainfall patterns, and extreme weather occurrences pose significant challenges to food security and crop productivity. Such con- cerns are of utmost importance in Sub-Saharan Africa (SSA), where a considerable portion of the population depends on agriculture for their livelihoods and sustenance [2,3]. Within this context, Ghana stands out as a key West African nation, playing a crucial role in cultivating essential crops like maize, rice, and wheat [4]. Among these agricul- tural yields, maize stands out as a prominent cereal yield in Ghana [5]. Recent years have shown a consistent growth trajectory with a positive trend that has been noticeable since 2016 [5]. Despite this progress, Ghana’s maize yield remains below international standards * Corresponding author. E-mail address: asante.gyamerah@knust.edu.gh (S.A. Gyamerah). [6], performing even lower than the African continent’s average [7]. To enhance maize productivity within the nation, it becomes impera- tive to comprehend the influence of climate change on this crop’s yield. Additionally, the prevalence of rain-fed agriculture in Ghana makes it highly vulnerable to the impacts of climate change, creating substan- tial concerns for local farmers and communities. This necessitates the identification of optimal conditions to increase maize productivity in the country. In attempts to evaluate the influence of climate change on crop yields in Ghana and enhance the precision of maize productivity fore- casts, numerous researchers have engaged in investigations on the po- tential impacts of climate change on crop yields in the country. Peprah [4], for instance, delved into the correlation between fluctuations in temperature and precipitation across multiple crops like maize, plan- tain, rice, cassava, cocoyam, and yam. The outcomes of the study revealed that about 40.9% of the fluctuations noticed in crop yields https://doi.org/10.1016/j.atech.2023.100370 Received 4 September 2023; Received in revised form 13 November 2023; Accepted 15 November 2023