Agricultural activities have a significant impact on the formation of nitrous oxide (N₂O) emissions, a potent greenhouse gas (GHG). Few studies have compared N₂O emissions from annual and perennial crops over extended periods.  These types of emission data are necessary for comprehensive GHG assessments of the life-cycle of dairy milk production. Quasi-continuous N₂O emissions from agricultural fields including annual and perennial crops can be obtained using micrometeorological techniques. However, the time series of N₂O fluxes have periods with missing data which need to be gap-filled to calculate annual N₂O emissions. The objective of this study is to compare annual N₂O emissions simultaneously from corn (annual crop) and hay fields (perennial crop) using the flux gradient technique, and various gap-filling methods. Measurements of N₂O flux emissions were conducted in the province of Ontario, starting in November 2011 and are still on-going. The total annual N₂O emissions for the first year measured for the hay crop were 0.5 Kg N ha^-1 y^-1 and for the corn crop were 2.5 Kg N ha^-1 y^-1. Two gap-filling techniques including moving average and artificial neural networks (ANNs) are examined to reconstruct the missing N₂O fluxes and preliminary results will be presented.

Key words: N₂O fluxes, Flux gradient, Annual crop, Gap-filling, Perennial crop