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AI model simulates fertilizer adoption for dairy farm decarbonization

Researchers have developed an agent-based modeling framework to simulate the adoption of low-emission fertilizers on Irish dairy farms. The model incorporates social contagion, farm characteristics, and policy interventions to predict decarbonization trajectories. It estimates greenhouse gas emissions and cost trade-offs, showing strong agreement with observed adoption patterns and predicting a saturation level of approximately 91%. AI

影响 Provides a novel simulation tool for evaluating climate mitigation strategies in agriculture.

排序理由 Academic paper detailing a new agent-based modeling framework for simulating fertilizer adoption.

在 arXiv cs.AI 阅读 →

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AI model simulates fertilizer adoption for dairy farm decarbonization

报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Surya Jayakumar, Kieran Sullivan, John McLaughlin, Christine OMeara, Indrakshi Dey ·

    Agent-Based Modeling of Low-Emission Fertilizer Adoption for Dairy Farm Decarbonisation using Empirical Farm Data

    arXiv:2605.03648v1 Announce Type: new Abstract: To understand complex system dynamics in dairy farming, it is essential to use modeling tools that capture farm heterogeneity, social interactions, and cumulative environmental impacts. This study proposes an agent-based modeling (A…

  2. arXiv cs.AI TIER_1 English(EN) · Indrakshi Dey ·

    Agent-Based Modeling of Low-Emission Fertilizer Adoption for Dairy Farm Decarbonisation using Empirical Farm Data

    To understand complex system dynamics in dairy farming, it is essential to use modeling tools that capture farm heterogeneity, social interactions, and cumulative environmental impacts. This study proposes an agent-based modeling (ABM) framework to simulate nitrogen management an…