Abstract
BACKGROUND: Understanding the complex interactions between plants, Arbuscular Mycorrhizal Fungi (AMF), and elevated atmospheric CO(2) (eCO(2)) is crucial for enhancing agricultural sustainability and productivity, particularly in the face of future climate change. While elevated CO(2) concentrations can influence AMF colonization development, AMF are known to benefit plants by improving nutrient uptake, especially phosphorus, enhancing drought tolerance, and increasing resistance to certain soil-borne pathogens. These beneficial effects of AMF can potentially mitigate some of the negative impacts of climate change on crop yields. This study explores the interplay between wheat (Triticum aestivum L.), AMF inoculation, and eCO(2) levels using the Mamdani Fuzzy Inference System (MFIS), a tool well-suited to handle uncertainties in modeling complex plant responses to environmental changes. By integrating fuzzy logic-based approaches, this research aims to elucidate how AMF inoculation can modulate wheat productivity under projected future elevated CO(2) levels, thereby providing insights into strategies for maintaining or improving crop yields in changing climatic conditions. The goal was to explore the relationship between CO(2) levels, AMF inoculation, and wheat yield, specifically investigating the potential of AMF to enhance wheat performance under elevated CO(2). RESULTS: Statistical analyses revealed that eCO(2) significantly increased ear length (p < 0.05), while AMF inoculation significantly enhanced the number of spikelets per ear (p < 0.05), number of grains per ear (p < 0.05), and weight of 1000 seeds (p < 0.05). The Mamdani Fuzzy Inference System (MFIS) models demonstrated that under eCO(2) conditions, the predicted 1000-seed weight stabilized around 40 g/plant in AMF-inoculated wheat, compared to approximately 37 g/plant in uninoculated plants. Similarly, ear length simulations showed stabilization at around 14 cm with AMF inoculation under eCO(2), versus 12.2 cm without AMF. These results highlight the synergistic effects of eCO(2) and AMF inoculation on key wheat productivity parameters. CONCLUSION: This study underscores the importance of integrating fuzzy logic-based approaches into agricultural management strategies to optimize crop yields while minimizing environmental impacts. The findings encourage further research into refining experimental designs and expanding datasets to enhance our understanding of plant responses to changing environmental conditions.