Sahila Beegum

Abstract Accurate prediction of methane (CH4) emissions from agricultural lands, particularly rice paddies, is essential for effective climate change mitigation. Although current models capture broad emission trends, they often struggle to represent the complex interactions among the processes that govern CH4 production, oxidation, transport, and release.

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1. Introduction Corn seedling emergence is a crucial factor that significantly affects the final yield of this widely grown crop [1]. A delay in the emergence by a few hours can shift the critical growth stages to a different environment and influence crop yield [2,3]. The corn seedling emergence model is vital in process-based crop models because it represents the primary and initial stages of crop growth.