Jingyi Yang

Optimizing Parameters of CSM-CERES-Maize Model to Improve Simulation Performance of Maize Growth and Nitrogen Uptake in Northeast China

Abstract Crop models can be useful tools for optimizing fertilizer management for a targeted crop yield while minimizing nutrient losses. In this paper, the parameters of the decision support system for agrotechnology transfer (DSSAT)-CERES-Maize were optimized using a new method to provide a better simulation of maize ( Zea mays L.) growth and N uptake in response to different nitrogen application rates. Field data were collected from a 5 yr field experiment (2006-2010) on a Black soil ( Typic hapludoll ) in Gongzhuling, Jilin Province, Northeast China. After cultivar calibration, the CERES-Maize model was able to simulate aboveground biomass and crop yield of in the evaluation data set ( n-RMSE =5.0-14.6%), but the model still over-estimated aboveground N uptake (i.e., with E values from −4.4 to −21.3 kg N ha −1 ). By analyzing DSSAT equation, N stress coefficient for changes in concentration with growth stage ( CTCNP2 ) is related to N uptake. Further sensitivity analysis of the CTCNP2 showed that the DSSAT model simulated maize nitrogen uptake more precisely after the CTCNP2 coefficient was adjusted to the field site condition. The results indicated that in addition to calibrating 6 coefficients of maize cultivars, radiation use efficiency ( RUE ), growing degree days for emergence ( GDDE ), N stress coefficient, CTCNP2 , and soil fertility factor ( SLPF ) also need to be calibrated in order to simulate aboveground biomass, yield and N uptake correctly. Independent validation was conducted using 2008-2010 experiments and the good agreement between the simulated and the measured results indicates that the DSSAT CERES-Maize model could be a useful tool for predicting maize production in Northeast China.

Effect of conservation and conventional tillage on soil water storage, water use efficiency and productivity of corn and soybean in Northeast China

Abstract The dominant factors affecting crop production in Northeast China are the low amount of rainfall in spring and high loss of soil water through evaporation during summer, both of which contribute to the lower soil water use efficiency (WUE). The objective of this study was to evaluate the long-term effects of no-till (NT), reduced tillage (RT) and conventional tillage (CT) on soil water storage (SWS), WUE, and soybean and corn yields in Northeast China from 2009 to 2011. The soil water contents under NT were higher than CT, especially in the 0–30 cm soil. SWS was lower in spring and autumn but higher in summer and it was influenced by both rainfall and tillage practices. NT had the greatest SWS and CT the least, with RT having intermediate values in the 30-cm surface. Leaf area index was higher for CT compared with the RT and NT in corn, but it was higher for RT than CT and NT in soybean. The evapotranspiration in the crop growing seasons was higher for NT and RT than for CT in the two corn years (2009, 2011), but no differences were found in the soybean year (2010). The WUE was greatly affected by weather conditions, (i.e., 64% lower in the wet year), and also affected by tillage; that is, CT and RT were 36 and 15% higher than NT in 2009, but no differences in other years. We conclude that RT was a good compromise for both soybean and corn crops, as it was associated with higher economic returns for farmers. Further research is required to compare the effect of the conservation tillage on the WUE and economic returns for other locations in Northeast China.

Long-term Trends in Corn Yields and Soil Carbon under Diversified Crop Rotations

Agricultural practices such as including perennial alfalfa ( L.), winter wheat ( L.), or red clover ( L.) in corn ( L.) rotations can provide higher crop yields and increase soil organic C (SOC) over time. How well process-based biogeochemical models such as DeNitrification-DeComposition (DNDC) capture the beneficial effects of diversified cropping systems is unclear. To calibrate and validate DNDC for simulation of observed trends in corn yield and SOC, we used long-term trials: continuous corn (CC) and corn-oats ( L.)-alfalfa-alfalfa (COAA) for Woodslee, ON, 1959 to 2015; and CC, corn-corn-soybean [ (L.) Merr.]-soybean (CCSS), corn-corn-soybean-winter wheat (CCSW), corn-corn-soybean-winter wheat + red clover (CCSW+Rc), and corn-corn-alfalfa-alfalfa (CCAA) for Elora, ON, 1981 to 2015. Yield and SOC under 21st century conditions were projected under future climate scenarios from 2016 to 2100. The DNDC model was calibrated to improve crop N stress and was revised to estimate changes in water availability as a function of soil properties. This improved yield estimates for diversified rotations at Elora (mean absolute prediction error [MAPE] decreased from 13.4-15.5 to 10.9-14.6%) with lower errors for the three most diverse rotations. Significant improvements in yield estimates were also simulated at Woodslee for COAA, with MAPE decreasing from 24.0 to 16.6%. Predicted and observed SOC were in agreement for simpler rotations (CC or CCSS) at both sites (53.8 and 53.3 Mg C ha for Elora, 52.0 and 51.4 Mg C ha for Woodslee). Predicted SOC increased due to rotation diversification and was close to observed values (58.4 and 59 Mg C ha for Elora, 63 and 61.1 Mg C ha for Woodslee). Under future climate scenarios the diversified rotations mitigated crop water stress resulting in trends of higher yields and SOC content in comparison to simpler rotations.

Visualization Analysis of Subject, Region, Author, and Citation on Crop Growth Model by CiteSpace II Software

A detailed visual analysis of publications related to crop growth model development and trend was carried out based on the latest version of information visualization and analysis software CiteSpace II. A total of 6,079 publication data between 1995 and 2011 were collected from Thomson ISI’s SCI (Web of science in the Science Citation Index Expanded Edition). After analysis by CiteSpace, the most productive countries related to Crop Growth Model, as well as institutes, key scholars, co-citation patterns, etc., were visualized and identified from 1995 to 2011.

Interactions between reactive nitrogen and the Canadian landscape: A budget approach

The movement of excess reactive nitrogen (Nr) from anthropogenic activities to natural ecosystems has been described as one of the most serious environmental threats facing modern society. One of the approaches for tracking this movement is the use of budgets that quantify fluxes. We constructed an Nr budget for Canada using measured and modeled values from the scientific literature, government databases, and data from new agri-environmental indicators, in order to produce information for policy makers and scientists to understand the major flows of nitrogen to allow a better assessment of risks to the Canadian environment. We divided the Canadian territory south of 60°N into areas dominated by natural ecosystems, as well as by agricultural and urban/industrial activities to evaluate Nr flows within, between, and out of these units. We show that Canada is a major exporter of Nr due to the availability of inexpensive commercial fertilizers. The large land area suitable for agriculture makes Canada a significant agricultural Nr exporter of both grain crops and livestock. Finally, Canada exports petroleum N mainly to the United States. Because of its location and prevailing atmospheric transport patterns, Canada is a net receptor of Nr air pollution from the United States, receiving approximately 20% of the Nr leaving the U.S. airshed. We found that overall, terrestrial natural ecosystems as well as the atmosphere are in balance between Nr inputs and outputs when all N reactive and nonreactive fluxes are included. However, when only reactive forms are considered, almost 50% of N entering the Canadian atmosphere cannot be accounted for and is assumed to be lost to the Atlantic and Arctic oceans or to unmeasured dry deposition. However, agricultural and freshwater landscapes are showing large differences between measured inputs and outputs of N as our data suggest that denitrification in soils and aquatic systems is larger than what models predict. Our work also shows that Canada is a major contributor to the global flow of nitrogen through commercial exports.

Infrared spectroscopy estimation methods for water-dissolved carbon and amino sugars in diverse Canadian agricultural soils

Abstract: Infrared spectroscopy has the potential to rapidly analyse soil water-dissolved carbon and amino sugars. In this study, mid-infrared (MIR) and near-infrared (NIR) spectra collected from soil water extracts or from bulk soils were analysed with partial least squares regression (PLSr) to estimate the concentrations of water-dissolved carbon and amino sugars in diverse agricultural soils collected from five field sites in two western and two eastern Canadian provinces. The MIR-PLSr models developed from soil water extract spectra estimated hot-water (100 °C) dissolved carbon (HWDC) [R2 = 0.97–0.70, ratio of prediction to deviation (RPDp) = 6.13–1.83] well, but the MIR-PLSr models did not estimate cold-water (21 °C) dissolved carbon (CWDC) well (R2 = 0.82–0.50, RPDp = 2.35–1.42). The model estimates of HWDC at the multisite scale (all samples together) and for the two western Canada sites (R2 = 0.97–0.93, RPDp = 6.13–3.68) surpass the modal estimates for the three eastern Canadian sites (R2 = 0.81–0.70, RPDp = 2.28–1.83). The MIR- and NIR-PLSr models derived from bulk soil spectra both estimated HWDC well at the multisite scale (R2 = 0.91–0.88, RPDp = 3.32–2.90) and for the western Canada sites (R2 = 0.90–0.87, RPDp = 3.18–2.96). Models developed from hot-water extract spectra and bulk soil spectra resulted in poor estimates of soil amino sugars (R2 = 0.74–0.21, RPDp = 1.99–1.12), except for the approximate quantitative estimation of muramic acid by models based on soil spectra at the western and the multisite scale (R2 = 0.82–0.80, RPDp = 2.33–2.21). We concluded that MIR and NIR models at regional and multisite scales can be used as a tool to monitor HWDC but that additional research is required for estimating soil amino sugars.