Spatial and temporal variability in maize emergence causes a decrease in crop yield and resource use efficiency, impacting the environment and producers’ profit. The overarching goal of this dissertation was to evaluate the effect of the spatial and temporal variability of maize emergence on the crop growth, yield, nitrogen (N) uptake, and N use efficiency (Chapter 1). Chapter 2 aims to compare the timing of maize plant emergence across and within sub-field yield stability zones, evaluate the impact of delayed emergence on crop yield and yield components by yield stability zone, and compare the effect of spatial and temporal variation of plant emergence on crop yield and yield components. Temporal variability has a higher impact than within-row plant spatial variability on crop yield and its components. The decrease in maize yield caused by the delay in emergence was not statistically related to yield stability zones but had a more negative impact in the low yield stability zones. Chapter 3 investigates maize biomass accumulation and variation in plants with temporal variability in the emergence by yield stability zones and evaluates the plant nitrogen concentration, uptake and use efficiency in plants with temporal variability in emergence. Emergence delay caused a reduction in grain per plant through a reduction in plant growth rate (PGR) around silking. Although the delay in emergence did not affect nitrogen concentration in the grain, it caused a decrease in plant biomass and consequently, an increase in biomass nitrogen concentration, resulting in less nitrogen accumulated in late emerged plants compared with early emerged plants. late emerged plants set fewer grains than early emerged plants and this lack of sink caused a change in plant N partitioning. Chapter 4 presents an approach to determine maize plant emergence time by using plant height obtained from LIDAR images and Machine Learning (ML) techniques and uses the estimated emergence as an input in SALUS model to estimate yield accounting for spatial and temporal variation. LiDAR images provided an accurate plant height in the three evaluated plant growth stages (V6, V14, and R1). Emergence was adequately estimated with the ML model and an “accurate” yield map was obtained using SALUS model. The integration of several digital tools allowed us to adequately simulate the spatial and temporal effect of emergence on crop yield. Conclusions from the research projects and recommendations on managing fields with spatial and temporal variation in maize emergence are outlined in Chapter 5.
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