OICC Press Agricultural Marketing and Commercialization 2676-7570 10 1 2026 06 30 Feasibility of Using Artificial Intelligence and Big Data in Wheat Seed Production 10.57647/amc.2026.100103 EN Farshad Habibi Department of Agriculture, Miy.C. Islamic Azad University, Miyndoab, Iran; Artificial Intelligence and Big Data Automation Research Center, Urmia Branch, Islamic Azad University, Urmia, Iran Journal Article 2026 06 30 The integration of Artificial Intelligence (AI) and Big Data analytics is revolutionizing agriculture by en hancing productivity and sustainability. This study investigates the feasibility of applying these technologies to optimize wheat seed production, a critical component of food security. We analyzed a two-year dataset (2022-2024) of ‘Pishgam’ wheat variety yield from a commercial seed production company, covering four distinct cities (Urmia, Naghadeh, Piranshahr, Oshnaviyeh) in West Azerbaijan, Iran, with 11 farm locations sampled within each city. A two-way Analysis of Variance (ANOVA) was conducted to assess the effects of ‘Year’, ‘City’, and their interaction on seed yield. The results revealed significant main effects for both Year (p<0.001p < 0.001p<0.001) and City (p<0.001p < 0.001p<0.001). Crucially, a statistically significant interaction effect between Year and City was observed (p=0.043p = 0.043p=0.043), indicating that yield performance across cities varied non-uniformly between the two years. This complex spatio-temporal variability, influenced by fluctuating local environmental conditions, underscores the inadequacy of traditional predictive models. We conclude that the application of AI and Big Data technologies is not only feasible but essential for accurately forecasting yield, managing production risks, and developing resilient, location-specific agricultural strategies for wheat seed productio