This presentation discusses research aimed at developing an index of nitrogen losses from intensively cultivated corn fields that receive high rates of nitrogen fertilizers and animal manures. The index includes losses from nitrous oxide emissions, nitrogen uptake by the plant, nitrogen transformations in the soil, and nitrate fluxes at tile drainage outlets. The research is being conducted on six corn fields under both inorganic and organic fertilization practices around Saint-Hyacinthe, Quebec. My research examines the impacts of soil type and fertilizer application methods (fertilizer type, amount of nitrogen, and time of application) on the nitrate fluxes in tile drainage water. To examine this relationship, a DRAINMOD-N model will be developed and calibrated using drainage data from study sites, and the results validated and extrapolated to other sites. Historic data collected by IRDA (Research and Development Institute for the Agri-environment), Environment Canada, Info-sols, and data obtained from literature will be used to validate the N index developed. The N index can be used to select fertilizer practices that are economically efficient and environmentally sustainable. The research is part of a larger project with the goal of forming a similar initiative to Alberta’s Nitrous Oxide Emissions Reduction Protocol (NERP)

Near-surface geophysical techniques, such as electromagnetic induction (EMI), can help investigate heterogeneous podzolic soils. Multi-coil (MC-EMI) and multi-frequency (MF-EMI) sensors were selected to maximize soil moisture (SMC) prediction in this study. The objectives of this study were (i) comparing apparent electrical conductivity (ECa) measurements from the MC and MF EMI sensors under different land use conditions. (ii) investigating the spatial variation of apparent electrical conductivity (ECa), soil moisture content (SMC), texture, soil organic matter (SOM), and bulk density (BD) under different land use conditions (iii) characterizing SMC under different land use conditions using statistical and geostatistical approaches considering the texture, SOM, and BD contents in each land use. The results of the study showed that MC-EMI sensors had more coil orientations showing statistically significant relations (p-value  0.05) with SMC relative to the MF-EMI sensor. Multiple linear regression (MLR) models were also shown to be more effective in representing SMC variations (higher coefficient of determination and lower root mean square error) than simple linear regression models. MC-EMI sensors provided better predictions of SMC than the MF-EMI sensor, likely because the differences in sampling depths between the TDR measured SMC and MF-EMI sensor were much greater than those between TDR measured SMC and MC-EMI sensor. Lastly, cokriging of measured SMC offered more accurate maps than cokriging of predicted SMC obtained from MLR across different land use conditions. This study shows that EMI has the potential as a robust technique for accurately predicting soil moisture in boreal podzolic soils.

Site specific irrigation management (SSIM), where irrigation depths are varied spatially during a field application, is often presented as a method to increase water use efficiency (WUE). However, recent work has shown that any WUE gains are crop, field, and weather dependent. This has implications for the overall effect of adoption of this type of management in a watershed and for the return on investment for producers wishing to adopt the technology required to implement SSIM. Whether SSIM will benefit regions larger than specific fields or crops remains poorly understood.

Here we present an analysis that combines regional analysis, a theoretical framework to map the relationship between field heterogeneity and the profit obtained from SSIM technology relative to uniform irrigation, and observational data from 99 sites within 19 commercial, irrigated fields (5-6 sites per field) in southern Alberta from 2019 to 2022. Using a mixed linear modelling approach, we considered the relative influence of soil, weather, and topography on potato productivity. Sites classified as ‘flat’ tended to have approximately 10% higher yields than the ‘non flat’ sites (p=0.008). Meanwhile soil complexity (measured as entropy of soil classification types) had a negative impact (p=0.08) that exceeds that of topography in highly complex soils. Variability of soil moisture within a field was weakly correlated with topographical complexity. We determined topographic complexity of >250 fields in the main potato producing areas of southern Alberta to estimate where the adoption of SSIM technology would be the most valuable.

Extremely low emergence rates have been reported for canola crops in Manitoba, Canada. One of the major causes of the low emergence is excessive soil compaction. In this study the emergence and early growth of canola were investigated under five different compaction levels (L0, L1, L2, L3, and L4) for three different soil types (sandy loam, silt clay, and clay). Canola was seeded in containers, and emergence and growth were monitored in an environmental chamber. Plant emergence and growth were recorded daily for a time period of 14 days. The results indicated that for the sandy loam and silt clay soils, the increase in soil compaction reduced the emergence rate, plant height, and biomass of canola. For the clay soil, the effects of soil compaction were not significant. Assuming an acceptable emergence rate of 80%, the recommended compaction level for the sandy loam soil was L1 or lower (i.e. light compaction or no compaction), and that for the silt clay was L0 (i.e. no compaction). At the indicated compaction level for those two soils, plant height and biomass were found to be good as well. However, the clay soil did not reach the acceptable emergence rate at any of the applied compaction levels.