The escalating issue of climate change, triggered by greenhouse gas emissions, has led to widespread consequences such as floods, droughts, and ecological damage. Given that the agricultural sector alone accounts for 10% of global CO₂ emissions, it is imperative to address emissions reduction in this sector. Due to the limited short-term impact of climate change and the substantial costs and decrease in output associated with emission reduction, governmental intervention is necessary to mitigate future catastrophes. Considering that carbon taxes, which levy corporations based on CO₂ emissions, are limited in implementation, no study has analyzed agricultural emission and output changes due to carbon taxes using Evolutionary Game Theory. This gap in literature is what my proposed research is built on. Evolutionary Game Theory offers a framework to analyze the behavior of a population given multiple strategies, in this instance, full reduction, half reduction, or no reduction in emissions, and associated payoffs. By constructing a payoff matrix for each company, we can derive expected utility functions and replication dynamic equations, which facilitate the modeling of the transition to net zero emissions under different carbon tax rates. The resulting data enables the development of a comprehensive model that describes the time required to achieve a 50% reduction in emissions and the corresponding decrease in output, as measured by the expected utility functions, for each carbon taxation level. Governments can use this model to assess the impact of carbon taxation policies on the agricultural industry, facilitating informed decision-making in emissions reduction efforts.