Xie, H. T., Yang, X. M., Drury, C. F., Yang, J. Y. and Zhang, X. D. 2011. Predicting soil organic carbon and total nitrogen using mid- and near-infrared spectra for Brookston clay loam soil in Southwestern Ontario, Canada. Can. J. Soil Sci. 91: 53–63. Mid-infrared (MIR) and near-infrared (NIR) spectroscopy of soils have been tested to estimate soil organic carbon (SOC) and total N (TN) concentrations at local, regional and national scales. However, these methods have rarely been used to assess SOC and TN concentrations of the same soil under different management practices. The objective of this study was to determine if models developed from infrared spectra of Brookston clay loam soils under different management practices could be used to estimate SOC, and TN concentrations and the C:N ratio. Soils used for model calibration included 217 samples from a long-term fertilization and crop rotation study and a long-term compost study, whereas 78 soil samples from a long-term tillage study on the same soil type were used for model validation. Soil organic carbon and TN concentrations of all samples were also analyzed using dry combustion techniques. Soil samples were scanned from 4000 to 400 cm−1 (2500–25 000 nm) for MIR spectra and from 8000 to 4000 cm−1 (1250–2500 nm) for NIR spectra. Partial least squares regression (PLSR) analysis was used for the calibration dataset to build prediction models for SOC, TN and C:N ratio. The SOC and TN concentrations determined using dry combustion techniques were compared with the prediction from the models using the calibration datasets. The predictions of SOC and TN concentrations by the PLSR method using infrared spectra were statistically sound, with high coefficient of determination with the calibration dataset (R2cal, SOCMIR=0.99 and SOCNIR=0.97, TNMIR=0.98 and TNNIR=0.97) and the validation dataset (R2val, SOCMIR=0.96 and SOCNIR=0.95, TNMIR=0.96 and TNNIR=0.95) and low root mean square error (RMSEPcal, SOCMIR=0.93 and SOCNIR=1.60, TNMIR=0.08 and TNNIR=0.12; RMSEPval, SOCMIR=1.40 and SOCNIR=1.75, TNMIR=0.11 and TNNIR=0.12). The predictions of SOC and TN concentrations in the 5 to 30 cm depth were better than the predictions for either the surface (0 to 5 cm) soils or for soils from lower depths (>30 cm). The models could be used as an alternative method for determining SOC and TN concentrations of Brookston clay loam soils; however, larger sample populations and improved model algorithms could further improve predictions.

Yang, J. Y., Huffman, E. C., Drury, C. F., Yang, X. M. and De Jong, R. 2011. Estimating the impact of manure nitrogen losses on total nitrogen application on agricultural land in Canada. Can. J. Soil Sci. 91: 107–122. About 1 million tonnes (1 Tg=1012 g) of livestock manure N are applied to farmland in Canada each year. Comprehensive information on manure N production and losses from manure during on-farm storage, handling and field application is scarce, especially at a regional scale. However, manure N losses during storage and land application are of considerable concern with respect to nitrogen use efficiency and environmental pollution of air, soil and water. In this paper, manure N production, manure N losses during storage and land application and manure N mineralization from organic manure and the resultant manure N available for annual crops were estimated using the Census of Agriculture database, Farm Environmental Management Survey data and manure N loss factors obtained from the literature. A database of fertilizer N application rates for field crops was developed at the regional scale based on recommendations provided in agronomic extension bulletins and fertilizer N sales. Fertilizer N and available manure N (i.e., total manure N produced minus N losses plus N mineralized from manure applied in previous years) were allocated to each of 24 crops at the regional scale from 1981 to 2006. The amount of manure N produced in Canada increased by 18.7% from 0.928 Tg in 1981 to 1.102 Tg in 2006. We estimated that 35.6% of the manure N produced was immediately available to crops, 25.6% was lost during storage and land application and 38.8% was carried over to the next year as organic N. The amount of fertilizer N applied to crops increased dramatically from 0.928 Tg in 1981 to a peak level of 1.68 Tg in 2000. There were significant changes in manure N production and application to farmland both on a regional and a temporal basis.

Liu, S., Yang, J. Y., Drury, C. F., Liu, H. L. and Reynolds, W. D. 2014. Simulating maize (Zea mays L.) growth and yield, soil nitrogen concentration, and soil water content for a long-term cropping experiment in Ontario, Canada. Can. J. Soil Sci. 94: 435–452. A performance assessment of the Decision Support Systems for Agrotechnology Transfer (DSSAT) model (v4.5) including the CERES-Maize and CENTURY modules was conducted for continuous maize production under annual synthetic fertilization (CC-F) and no fertilization (CC-NF) using field data from a long-term (53-yr) cropping experiment in Ontario, Canada. The assessment was based on the accuracy with which DSSAT could simulate measured grain yield, above-ground biomass, leaf area index (LAI), soil inorganic nitrogen concentration, and soil water content. Model calibration for maize cultivar was achieved using grain yield measurements from CC-F between 2007 and 2012, and model evaluation was achieved using soil and crop measurements from both CC-F and CC-NF for the same 6-yr period. Good model–data agreement for CC-F grain yields was achieved for calibration (index of agreement, d=0.99), while moderate agreement for CC-NF grain yields was achieved for evaluation (d=0.79). Model–data agreement for above-ground biomass was good (d=0.83–1.00), but the model consistently underestimated for CC-F and overestimated for CC-NF. DSSAT achieved good model–data agreement for LAI in CC-F (d=0.82–0.99), but moderate to poor agreement in CC-NF (d=0.46–0.64). The CENTURY module of DSSAT simulated soil inorganic nitrogen concentrations with moderate to good model–data agreement in CC-F (d=0.74–0.88), but poor agreement in CC-NF (d=0.40–0.50). The model–data agreement for soil water content was moderate in 2007 and 2008 for both treatments (d=0.60–0.76), but poor in 2009 (d=0.46–0.53). It was concluded that the DSSAT cropping system model provided generally good to moderate simulations of continuous maize production (yield, biomass, LAI) for a long-term cropping experiment in Ontario, Canada, but generally moderate to poor simulations of soil inorganic nitrogen concentration and soil water content.

Yang, J. Y., Huffman, T., Drury, C. F., Yang, X. M., De Jong, R. and Campbell, C. A. 2012. Estimating changes of residual soil nitrogen in Chernozemic soils in Canada. Can. J. Soil Sci. 92: 481–491. Chernozemic soils (Mollisols) account for approximately 68% of total farmland in the prairies and 54% of farmland in Canada. Although many field studies have focused on the importance of N in Chernozemic soils, few modelling studies have been conducted to examine the risk of N contamination to the environment The objective of this research was to estimate temporal and spatial changes in residual soil nitrogen (RSN) on Chernozemic soils at the 1:1 million regional scale. An annual N budget was developed for the study area for the period 1981 to 2006, using the Canadian Agricultural Nitrogen Budget (CANB v3.0) model. The difference between N inputs and outputs is considered RSN, which is defined as the inorganic N left in the soil after harvest. Average RSN levels in the sub-humid Black and Dark Gray Chernozemic soils increased from 7–9 kg N ha−1 in 1981 to 20–23 kg N ha−1 in 2006. Changes in RSN were much less pronounced in the arid and semi-arid Brown and Dark Brown soil zones, where average values increased from approximately 1 kg N ha−1 to 4–7 kg N ha−1 over 25 yr. Commercial fertilizer, manure and biological N2 fixation were the three main sources of the increased N inputs. Drought conditions also contributed to the surplus of N in some years by reducing crop growth and thus the amount of N removed in grain and forage crops. In Chernozemic soils, more careful use of chemical fertilizer N, improved manure N management and greater use of legume-cereal rotations are recommended as methods to maintain soil fertility and reduce nitrogen loss to the environment.