Greenhouse gas (GHG) emissions evaluations from agroecosystems are critical, particularly as technology improves. Consistent GHG measurement methods are essential to the evaluation of GHG emissions. The objective of the study was to evaluate potential differences in gas-flux-determination (GFD) options and carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) fluxes and growing-season-long emissions estimates from furrow-irrigated cotton (Gossypium hirsutum) in southeast Arkansas. Four GFD methods were evaluated [i.e., linear (L) or exponential (E) regression models, with negative fluxes (WNF) included in the dataset or replacing negative fluxes (RNF)] over the 2024 growing season using a LI-COR field-portable chamber and gas analyzers. Exponential regression models were influenced by abnormal CO₂ and N₂O gas concentration data points, indicating the use of caution with E models. Season-long CH₄ emissions differed (p < 0.05) between the WNF (−0.51 kg ha⁻¹ season⁻¹ for L and−0.54 kg ha⁻¹ season⁻¹ for E) and RNF (0.01 kg ha⁻¹ season⁻¹ for L and E) GFD methods, concluding that RNF options over-estimate CH₄ emissions. Gas concentration measurements following chamber closure should remain under 300 s, with one concentration measurement obtained per second. The choice of GFD method needs careful consideration to result in accurate GHG fluxes and season-long emission estimates.