To address the complex challenges of green sustainable agriculture arising from regional economic growth, this study proposes a novel five-way decision (F-WD) architecture. The framework is evaluated using a Bayesian risk mechanism to minimize expected losses, leveraging the flexibility of q-rung orthopair fuzzy logic ( q ¨ ≥ 1 ) combined with outranking relations and decision-theoretic rough sets (DTRS). This approach defines alternatives across five semantically interpretable regions, extending the conventional three-way decision (T-WD) framework to provide a more granular and versatile classification system. Outranking relations enable partial preference modeling among alternatives by incorporating dominance and incomparability, offering nuanced judgments when criteria conflict or are incommensurable unlike traditional ranking methods. The study begins by formulating F-WD specific relative gain and loss functions, laying the groundwork for the five zone decision-making process. It further validates the reliability of threshold values, their properties, and their role in defining decision boundaries. Compared to conventional methods like TOPSIS, Fuzzy AHP, T-WD-DTRS, IVIFS-ELECTRE, and the proposed technique demonstrates superior decision granularity, interpretability, and classification accuracy. These results underscore the method's credibility, soundness, and practical effectiveness in handling uncertainty, hesitation, and compromise in risk-sensitive environments. The q-ROFS-based F-WD model not only outperforms existing approaches but also serves as a powerful, adaptive tool for sustainable development, strategic planning, and policymaking in complex scenarios.