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Structured AbstractBackgroundTo support the increasingly complex circuits needed for plant synthetic biology applications, additional constitutive promoters are essential. Reusing promoter parts can lead to difficulty in cloning, increased heterogeneity between transformants, transgene silencing and trait instability. Moreover, the utility of such promoters could be increased by introducing target sequences not found elsewhere in theArabidopsis thalianagenome and well-suited for Cas9-associated guide RNAs (gRNAs).MethodsWe have developed a pipeline to identify genes that have stable expression across a wide range ofArabidopsistissues at different developmental stages, and have identified a number of promoters that are well expressed in both transient (Nicotiana benthamiana) and stable (Arabidopsis) transformation assays. We have also introduced two genome-orthogonal gRNA target-sites in a subset of the screened promoters, converting them into NOR logic gates.ResultsOf twenty-two promoters identified in our bioinformatic screen, sixteen drove detectable reporter expression inN. benthamiana. Only three of these promoters were able to produce visible expression of the RUBY reporter inArabidopsisdespite producing RUBY mRNA that could be readily detected by qPCR. We then modified six of these promoters to be repressible, and five of which functioned as NOR gatesConclusionsOne of the major bottlenecks for the ambitious engineering projects currently under development in plants is the lack of well-characterized constitutive promoters. The work here begins to fill this gap. It can also form the basis of constructing more complex information processing circuits in the future.

Water Cherenkov detector array (WCDA) is one of the key parts of the Large High Altitude Air Shower Observatory (LHAASO), the construction of which was completed by the end of 2020. The WCDA covers a 78 000-m2 area and there exist 3120 large size photomultiplier tubes (PMTs) in three ponds: 8-in PMTs are used in WCDA pond No. 1 and 20-in PMTs are used in ponds No. 2 and No. 3. The front-end electronics (FEE) system based on multigain measurement technique is designed to achieve both high-precision time and charge measurements over a large dynamic range from single photon electron (S.P.E.) to 4000 P.E. (for water pond No. 1)/1800 P.E. (for water ponds No. 2 and No. 3). To achieve a high-quality clock distribution and phase alignment as well as mixed transmission of data, clock, and commands in one fiber over a long distance, an enhanced white rabbit (WR) technique is used. Testing of all the 350 FEE modules for the WCDA is presented in this article. Test results indicate that the charge resolution is better than 20% at S.P.E. and 1% at 1800/4000 P.E. and the time resolution is better than 300 ps root mean square (rms), which successfully meets the application requirement. All the FEE modules have been fabricated and installed for the LHAASO WCDA from 2018 to 2020, and the initial commissioning operation indicates that the FEEs function well.

Maize (Zea mays L.) production in Northeast China is vulnerable to climate change. Thus, exploring future adaptation measures for maize is crucial to developing sustainable agriculture to ensure food security. The current study was undertaken to evaluate the impacts of climate change on maize yield and partial factor productivity of nitrogen (PFPN) and explore potential adaptation strategies in Northeast China. The Decision Support System for Agrotechnology Transfer (DSSAT) model was calibrated and validated using the measurements from nine maize experiments. DSSAT performed well in simulating maize yield, biomass and N uptake for both calibration and validation periods (normalized root mean square error (nRMSE) 0.8). Compared to the baseline (1980–2010), the average maize yields and PFPN would decrease by 7.6–32.1% and 3.6–14.0 kg N kg−1 respectively under future climate scenarios (2041–2070 and 2071–2100) without adaptation. Optimizing N application rate and timing, establishing rotation system with legumes, adjusting planting dates and breeding long-season cultivars could be effective adaptation strategies to climate change. This study demonstrated that optimizing agronomic crop management practices would assist to make policy development on mitigating the negative impacts of future climate change on maize production.

In order to improve Super-Kamiokande's neutron detection efficiency and to thereby increase its sensitivity to the diffuse supernova neutrino background flux, 13 tons of $\rm Gd_2(\rm SO_4)_3\cdot \rm 8H_2O$ (gadolinium sulfate octahydrate) was dissolved into the detector's otherwise ultrapure water from July 14 to August 17, 2020, marking the start of the SK-Gd phase of operations. During the loading, water was continuously recirculated at a rate of 60 m$^3$/h, extracting water from the top of the detector and mixing it with concentrated $\rm Gd_2(\rm SO_4)_3\cdot \rm 8H_2O$ solution to create a 0.02% solution of the Gd compound before injecting it into the bottom of the detector. A clear boundary between the Gd-loaded and pure water was maintained through the loading, enabling monitoring of the loading itself and the spatial uniformity of the Gd concentration over the 35 days it took to reach the top of the detector. During the subsequent commissioning the recirculation rate was increased to 120 m$^3$/h, resulting in a constant and uniform distribution of Gd throughout the detector and water transparency equivalent to that of previous pure-water operation periods. Using an Am-Be neutron calibration source the mean neutron capture time was measured to be $115\pm1$ $\mu$s, which corresponds to a Gd concentration of $111\pm2$ ppm, as expected for this level of Gd loading. This paper describes changes made to the water circulation system for this detector upgrade, the Gd loading procedure, detector commissioning, and the first neutron calibration measurements in SK-Gd., Comment: 37 pages, 19 Figures, Accepted for publication in Nucl. Instrum. Meth. A

We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218±9 μs. We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218 \pm 9 \mu s.

Summary The Ordovician ultra-deep (burial depth more than 7000m) tight limestone formation fault-controlled reservoir is part of the most important targets in the Tarim Basin. It’s formed by dissolved pores that controlled by faults and shown as a “beaded” reflection in seismic. After decades of exploration and development, most easily identified large-scale fractured-vuggy bodies have been drilled. To support the stable production capacity at the current stage, it is critical to identify and locate medium-small scale carbonate reservoirs’ reflection with medium intensity. This abstract proposes an improved method, which not only enhances the sub-level reflection intensity and the seismic response characteristics of medium-small scale carbonate reservoirs but also able to identify and locate the fault-controlled reservoirs. After pre-processing on the original data and performing formation dip and azimuth scanning, it uses the dip and azimuth data to guide the weighted average operation of structurally oriented on adjacent seismic traces. Lastly, it calculates the formation background data with raw data to obtain residual sweet data. The application of this technology in the actual 3D seismic data in the two areas of Tabei uplift of the northern Tarim Basin supported the continual increase of drilling success rate from 80% to 97%.

Process-based models are effective tools for assessing the sustainability of agricultural productivity and environmental health under various management practices and rotation systems. The objectives of this study were to (1) calibrate and evaluate the DeNitrification-DeComposition (DNDC) model using measurements of yields, nitrogen (N) uptake, soil inorganic N, soil temperature, soil moisture and nitrous oxide (N2O) emissions under long-term fertilized continuous corn (CC) and corn-oats-alfalfa-alfalfa (COAA) rotation systems in southwest Ontario from 1959 to 2015, Canada, and (2) explore the impacts of four diverse rotation systems (CC, COAA, corn-soybean-corn-soybean (CSCS) and corn-soybean-winter wheat (CSW)) on corn yields and annual N2O emissions under long-term climate variability. DNDC demonstrated “good” performance in simulating corn, oats and alfalfa yield (normalized root mean square error (nRMSE) 0.5 and index of agreement (d) > 0.8). The model provided “fair” to “good” simulations for corn N uptake and soil inorganic N (NSE > 0.2 and d > 0.8), and also daily soil temperature and soil moisture (nRMSE 0.7) for both calibration and validation periods. The model demonstrated “good” performance in estimating daily and cumulative N2O emissions from both the continuous and rotational corn, whereas it produced “poor” to “good” predictions for N2O emissions from the rotational oats and alfalfa crops, however, the emissions from these crops were very low and the relative magnitude of these emissions between all crops investigated were well predicted. The lowest N2O emissions were from COAA followed by CSCS, CSW then CC. The highest corn yields were from COAA, followed by CSW, CSCS, then CC. This study highlights how modelling approaches can help improve the understanding of the impacts of diversified rotations on crop production and greenhouse gas emissions and contribute towards developing policies aimed at improving the sustainability and resiliency of cropping systems.

Accurately predicting the impacts of higher temperatures, different precipitation rates and elevated CO2 concentrations on crop yields and GHG emissions is required in order to develop adaptation strategies. The objectives of this study were to calibrate and evaluate a regionalized denitrification-decomposition (DNDC) model using measured crop yield, soil temperature, moisture and N2O emissions, and to explore the impacts of climate change scenarios (Representative Concentration Pathways (RCP) 4.5 and RCP 8.5) on crop yields and N2O emissions in Southwestern Ontario, Canada. This simulation study was based on a winter wheat-maize-soybean rotation under conventional tillage (CT) and no tillage (NT) practices at Woodslee, Ontario, Canada. The model was calibrated using various statistics including the d index (0.85–0.99), NSE (Nash-Sutcliffe efficiency, NSE > 0) and nRMSE (normalized root mean square error, nRMSE

Process-based modelling studies can help to interpret experimental results and gain more insights into CO 2 fluxes in agro-ecosystems. The objective of this study was to evaluate the ability of the DeNitrification-DeComposition (DNDC) model to predict field-measured soil temperature, moisture, and respiration (daily and seasonal) in monoculture versus rotational cropping systems. Field measurements (2003–2005) from monoculture cropping (corn, Zea mays L.; soybean, Glycine max L.; and winter wheat, Triticum aestivum L.), as well as from 2-yr (corn-soybean) and 3-yr (corn-soybean-winter wheat) crop rotations in southwestern Ontario, Canada were used for model calibration and evaluation. Model simulated soil (0–10 cm) temperature ( nRMSE = 8–9%, d = 0.97 and EF = 0.87–0.90) and moisture ( nRMSE = 15–22%, d ≥ 0.7 and EF ≥ 0) agreed well with the growing season field measurements. Predicted daily soil CO 2 fluxes were accurate for corn (under both monoculture and rotation) and winter wheat (under monoculture) ( nRMSE = 56–70%, d > 0.7, slope = 0.60–0.88, R 2 = 0.36–0.48). The overestimation in daily soil CO 2 fluxes for winter wheat phase under the 3-yr rotation could be addressed by decreasing the root: shoot ratio. The simulated temporal offset in the soil CO 2 fluxes for soybean could be improved by adjusting crop parameters (thermal degree days for crop maturity and root: shoot ratio). The simulated cumulative seasonal soil CO 2 fluxes were not statistically different from the measured CO 2 fluxes for corn, soybean and winter wheat as indicated by the paired- t test ( p = 0.17–1.00). The impacts of monoculture and rotation cropping on seasonal root autotrophic respiration (R A ), soil heterotrophic respiration (R H ) and R H /R S ratios for corn, soybean and winter wheat were attributed to the different biomass production and residue C input management systems. The R H contributed more to total soil respiration for corn (during the growing season) under monoculture (R H /R S = 42%) than when it was grown in rotation (26–29%), while ratios of R H /R S were similar among monocultural and rotational soybean (41–49%) and winter wheat (31–40%). The current litter C level and consequently annual R H were driven by the litter C input carried over from previous crop. When carbon in the harvested grain was taken into account in the carbon budget, corn would act as a strong net carbon sink (3 year average of −975, −2675 and −3151 kg C ha −1 yr −1 under monoculture, 2-yr and 3-yr rotations, respectively), while soybean and winter wheat would act as weak net carbon source under both monoculture and rotation. The DNDC model was found to be able to simulate soil temperature, moisture, and soil respiration for corn and winter wheat under both monoculture and rotation in humid southwestern Ontario, Canada but crop parameter adjustments are required to simulate soybean.

The first Water Cherenkov detector of the LHAASO experiment (WCDA-1) has been operating since April 2019. The data for the first year have been analyzed to test its performance by observing the Crab Nebula as a standard candle. The WCDA-1 achieves a sensitivity of 65 mCU per year, with a statistical threshold of 5 . To accomplish this, a 97.7% cosmic-ray background rejection rate around 1 TeV and 99.8% around 6 TeV with an approximate photon acceptance of 50% is achieved after applying an algorithm to separate gamma-induced showers. The angular resolution is measured using the Crab Nebula as a point source to be approximately 0.45° at 1 TeV and better than 0.2° above 6 TeV, with a pointing accuracy better than 0.05°. These values all match the design specifications. The energy resolution is found to be 33% for gamma rays around 6 TeV. The spectral energy distribution of the Crab Nebula in the range from 500 GeV to 15.8 TeV is measured and found to be in agreement with the results from other TeV gamma ray observatories.

CONTEXT There has been a great deal of uncertainty in the reported alfalfa and pasture yields in the agricultural database as these commodities are typically used internally on farms and are not sold in the same way as other crops such as wheat, canola or corn. However, yields from alfalfa and pasture crops are important inputs (biological fixation) and outputs (feed) that can impact the estimates of agri-environmental indicators as the land area in Canada under these crops is very large. One of the indicators which uses this data is the residual soil nitrogen (RSN) which is the amount of inorganic N remaining in soils after harvest. High RSN levels can lead to impaired water quality (e.g., eutrophication) and global warming (N2O). Therefore, it is critical to obtain accurate alfalfa and pasture yield estimates. In previous versions of the Canadian Agricultural Nitrogen Budget Model (CANB), only provincial average yield values were used for alfalfa or pasture yields across all of the soils and landscapes. Soils, climates, and crop yields do vary within provinces, and a more accurate estimate of these yields over time and space is required. OBJECTIVE The objective of this study was to collect recent published yield data and use the Environmental Policy Integrated Climate (EPIC) to estimate yields for the 2780 soil landscapes of Canada (SLC) polygons. METHODS The EPIC model was used to calibrate and evaluate yields at field scale based on a total of 109, 59 and 47 treatments collected for alfalfa, improved and unimproved pasture yields, respectively, from Canadian publications. Due to satisfactory evaluation, we extended simulation to all SLC polygons based on SLC v3.2 soil and weather databases, representative crops as proxies for planting and harvesting date, and historical rates of fertilization. RESULTS AND CONCLUSIONS The average simulated alfalfa, improved and unimproved pasture yields were 5.00, 3.85 and 1.22 Mg ha−1, respectively over the period from 1981 to 2019. Generally, the EPIC model showed reliable predictions for alfalfa and pasture yields under variable weather, soil, and management practices. SIGNIFICANCE Therefore, it enabled us to provide improved estimates across soil landscapes polygons in Canada and thereby improve our agri-environmental indicator models.

Grape proanthocyanidins (GPCs) are a family of naturally derived polyphenols that have aroused interest in the poultry industry due to their versatile role in animal health. This study was conducted to investigate the potential benefits and appropriate dosages of GPCs on growth performance, jejunum morphology, plasma antioxidant capacity and the biochemical indices of broiler chicks. A total of 280 newly hatched male Cobb 500 broiler chicks were randomly allocated into four treatments of seven replicates each, and were fed a wheat-soybean meal-type diet with or without (control group), 7.5, 15 or 30 mg/kg of GPCs. Results show that dietary GPCs decrease the feed conversion ratio and average daily gain from day 21 to day 42, increase breast muscle yield by day 42 and improve jejunum morphology between day 21 and day 42. Chicks fed 7.5 and 15 mg/kg of GPCs show increased breast muscle yield and exhibit improved jejunum morphologies than birds in the control group. Dietary GPCs fed at a level of 15 mg/kg markedly increased total superoxide dismutase (T-SOD) activity between day 21 and day 42, whereas a supplement of GPCs at 7.5 mg/kg significantly increased T-SOD activity and decreased lipid peroxidation malondialdehyde content by day 42. A supplement of 30 mg/kg of GPCs has no effect on antioxidant status but adversely affects the blood biochemical indices, as evidenced by increased creatinine content, increased alkaline phosphatase by day 21 and increased alanine aminotransferase by day 42 in plasma. GPC levels caused quadratic effect on growth, jejunum morphology and plasma antioxidant capacity. The predicted optimal GPC levels for best plasma antioxidant capacity at 42 days was 13 to 15 mg/kg, for best feed efficiency during grower phase was 16 mg/kg, for best jejunum morphology at 42 days was 17 mg/kg. In conclusion, GPCs (fed at a level of 13 to 17 mg/kg) have the potential to be a promising feed additive for broiler chicks.

Sensitivity analysis of DSSAT outputs to inputs parameters was conducted in two Canadian locations: one for spring wheat (Triticum aestivum L.) in the semi-arid Prairies in Swift Current, Saskatchewan and the second for maize (Zea mays L.) under humid conditions in Woodslee, Ontario. The nominal range sensitivity method, regression, and graphical analysis were used to assess the sensitivity of crop yields, biomass, soil inorganic N, nitrate leaching and soil water contents to soil hydraulic properties, management practices and precipitation. Wheat and maize yields were highly sensitive to soil water drainage upper limit, fertilizer nitrogen rate and precipitation at both locations. At Swift Current, very high soil nitrate leaching (25–140 kg N ha−1) was found in 1994, 1996, 1997 and 2003 as affected by high precipitation in the previous years (i.e., 1993, 1995, 1996 and 2002). Soil N leaching was greater in 2011, a wet year at Woodslee, Ontario, with 20–85 kg N ha−1 than in the normal rainfall years of 2010 and 2012. Based on the fitted N response curves, the maximum yields were obtained at 112 kg N ha−1 for spring wheat at Swift Current and 150–210 kg N ha−1 for maize at Woodslee. The optimum planting date for maize at Woodslee was predicted to be from late May to early June. Sensitivity analysis was found to be useful in assessing the influence of crop management practices, soil parameters and precipitation on crop production and potential environment risks.

Hot compressive deformation behavior and processing maps of the cast Cu-22%Sn alloy with near peritectic composition were examined in the temperature range between 843 and 993 K and in the strain rate range between 10−3 and 10 s−1. Solute drag creep associated with a stress exponent of close to 3.5 dominated the plastic flow even at a very high strain rate of 10 s−1, implying that the Cu-22%Sn alloy with a major phase of β (Cu17Sn3, disordered body centered cubic) exhibits high-strain-rate solute drag creep. This is a unique property of the Cu-22%Sn alloy because most of the conventional solid-solution alloys exhibit solute drag creep below 10−3–10−2 s−1. No unstable flow regime appeared in the flow instability maps, and the power dissipation efficiency was high over the entire range of experimental conditions in the power dissipation maps, indicating that the coarse-grained Cu-22%Sn alloy exhibits excellent hot workability at high strain rates. Comparison of the cast Cu-22%Sn alloy with the cast Cu-10%Sn alloy with a single α phase (Cu (α), face centered cubic) indicates that (1) the flow stress of the Cu-22%Sn alloy is considerably lower than that of the Cu-10%Sn alloy (by a factor of 11) and (2) the onset of significant deviation from solute drag creep is estimated to occur at a considerably higher strain rate (by a factor of 105) in the Cu-22%Sn alloy. Possible explanations on these observations were presented.

The aim of this study was to evaluate the potential of the Decision Support System for Agrotechnology Transfer – Cropping System Model (DSSAT-CSM) using the CENTURY-based soil module to simulate long-term trends of grain yield, soil organic C (SOC) and soil organic N (SON) based upon 14-year data from a spring maize ( Zea mays L.) and winter wheat ( Triticum aestivum L.) cropping system study conducted in the Loess Plateau of Northwestern China. There were four treatments including no fertilizer (N0), 90 kg N ha −1 from urea (N90), 30 kg N ha −1 from straw plus 90 kg N ha −1 from urea (SN90), and 40 kg N ha −1 from cattle manure plus 90 kg N ha −1 from urea (MN90) selected in this study. The DSSAT-CSM showed a good to excellent agreement for simulating maize yields with normalized root mean square error ( nRMSE ) ≤ 19%, index of agreement ( d ) > 0.91 and modeling efficiency ( EF ) ≥ 0.56, and a moderate to good agreement for wheat yields with nRMSE ≤ 22%, d > 0.89 and EF > 0.46 for N90, SN90 and MN90 treatments. The model simulated SOC in the 0–20 cm depth for both SN90 and MN90 very well with nRMSE d > 0.63 and moderately for N90 and N0. The simulated topsoil SON matched the measured data for N90, SN90 and MN90 very well with nRMSE d > 0.77 and EF > 0.15, whereas the simulation for N0 was poor. Both maize wheat yields were found to be more sensitive to the fertilizer N rates in humid than drought soil conditions. The sensitivity of grain yields for either maize or wheat to generated growing season precipitation was affected by fertilizer N rate. The simulated soil nitrate-N (NO 3 -N) in soil profile and the NO 3 -N leaching below 150 cm increased with the increased fertilizer N rates as expected. The periods occurring high NO 3 -N leaching were along with drainage events mainly in the next fallow periods. Therefore, this study found that the DSSAT-CSM has a large potential to assess the impacts of various agricultural practices on crop growth, soil C and N dynamics in the semi-arid to semi-humid region of the Loess Plateau, and could contribute to selecting the optimum management practices.

The overall performance of the Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) was evaluated for simulating wheat (Triticum aestivum L.) yield, grain N uptake, soil organic C (SOC) and N (SON), soil water and nitrate–N (NO3–N) dynamics. The data used was from a long-term (1967–2005) spring wheat experiment conducted at Swift Current, Saskatchewan in the semi-arid Canadian prairies. Four treatments were selected: (1) continuous wheat receiving N and P fertilizer, Cont-W(NP); (2) continuous wheat receiving P only, Cont-W(P); and each phase of a fallow wheat rotation receiving N and P fertilizer, (3) W–F(NP) and (4) F–W(NP). The simulated grain yields matched the measurements well, with high d (0.74–0.83) and EF (0.16–0.33). The grain N uptake was also simulated satisfactorily with RMSE of 14–17 kg N ha−1 and d of 0.66–0.81. DSSAT simulated topsoil (0–0.15 m) SOC and SON well in the drier period (1967–1991), whereas it underestimated SOC in the more humid period (1991–2003). The DSSAT successfully simulated soil water and NO3–N dynamics in 0–0.15 m depth, whereas it overestimated soil water and NO3–N in the deep layers and consequently underestimated NO3–N leaching, suggesting that further improvements in soil water module should be made for the semi-arid climatic conditions in Canadian prairies. Sensitivity results showed that soil water content was sensitive to both lower soil water and upper drainage limits in this study. The performances of DSSAT model to yield and soil dynamics were comparable with other models.

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.

Drury, C. F., Reynolds, W. D., Tan, C. S., McLaughlin, N. B., Yang, X. M., Calder, W., Oloya, T. O. and Yang, J. Y. 2014. Impacts of 49–51 years of years of fertilization and crop rotation on growing season nitrous oxide emissions, nitrogen uptake and corn yields. Can. J. Soil Sci. 94: 421–433. A field study was established in 1959 to evaluate the effects of fertilization and crop rotation on crop yields, soil and environmental quality on a Brookston clay loam. There were two fertilizer treatments (fertilized and not-fertilized) and six cropping treatments including continuous corn (CC), continuous Kentucky bluegrass sod and a 4-yr rotation of corn–oat–alfalfa–alfalfa with each phase present each year. We measured N2O emissions, inorganic N and plant N uptake over three growing seasons (2007–2009) in the corn phase. Nitrous oxide emissions varied over the 3 yr as a result of the seasonal variation in precipitation quantity, intensity and timing and differences in crop growth and N uptake. Fertilized CC lost, on average, 7.36 kg N ha−1 by N2O emissions, whereas the not-fertilized CC lost only 0.51 kg N ha−1. Fertilized rotation corn (RC) lost 6.46 kg N ha−1, which was 12% lower than fertilized CC. The not-fertilized RC, on the other hand, emitted about half as much N2O (2.95 kg N ha−1) as the fertilized RC. Fertilized RC had corn grain yields that averaged 10.0 t ha−1 over the 3 yr followed by fertilized CC at 5.48 t ha−1. Not-fertilized RC corn had yields that were 61% lower (3.93 t ha−1) than fertilized RC, whereas the not-fertilized CC had yields that were 75% lower (1.39 t ha−1) than fertilized CC. Nitrous oxide emissions were found to be dramatically affected by long-term management practices and crop rotation had lower emissions in the corn phase of the rotation even though the N input from fertilizer addition and legume N fixation was greater. These N2O emission and yield results were due to both factors that are traditionally used to describe these processes as well as long-term soil quality factors, which were created by the long-term management (i.e., soil organic carbon, soil physical parameters such as bulk density, and porosity, soil fauna and micro-flora) and that influenced crop growth, N uptake and soil water contents.

Process-based models are valuable tools for simulating crop production, estimating agronomic efficiency and developing optimum management practices to achieve sustainable agriculture. However, a comparison of the DeNitrification-DeComposition (DNDC) and Decision Support System for Agrotechnology Transfer (DSSAT) models has not been previously used to optimize management practices for spring maize in northeast China. The objectives of this study were to evaluate the performance of the DSSAT and DNDC models in simulating maize growth and soil C & N dynamics and analyse their weaknesses and strengths based on a 7-year spring maize study in northeast China; and to explore the optimal management practices for improving maize production and nitrogen use efficiency under 20-year climate variability. Both DNDC and DSSAT exhibited “good” to “excellent” performance in simulating maize yield, above-ground biomass and plant N uptake for ecological intensification with N fertilizer (EI-N) and farmers’ practice with N fertilizer (FP-N) treatments based on percent bias (PBIAS) of −10.5–4.2%, a normalized root mean squared error (nRMSE) of 7.5–17.2%, a Nash-Sutcliffe efficiency (NSE) of 0.17–0.77 and a d index of agreement (d) of 0.81–0.94. Both models showed “fair” to “good” performance in the same simulation for EI without N fertilizer (EI-N0) and FP without N fertilizer (FP-N0) treatments, but the maize yield simulation was better for the DSSAT model. In addition, the two models provided “fair” performance for N-fertilized treatments to “poor” performance for N-unfertilized treatments in simulations of soil organic carbon (0–0.20 m) and mineral N (0–0.30 m), but the simulations were better for the DNDC model. Sensitivity analyses indicated that the optimum yield and agronomic efficiency were achieved at a planting date of late April to early May, a fertilizer N application rate of 180–210 kg N ha−1 with two timing splits in the DNDC and DSSAT model and a planting density of 7 seeds m−2 in the DSSAT model. This study suggests that comparing the management scenarios of multiple dynamic models is more beneficial to develop best management practices for improving crop production and fertilizer use efficiency.

The Loess Plateau is an area of low crop productivity and one of the most susceptible areas for soil erosion in China. This study was designed to investigate changes in soil organic carbon (SOC) of croplands in four humid to semiarid counties (Huixian, Xifeng, Linxia, and Yuzhong) of Gansu province that have experienced accelerated grain production since the early 1980s. In 1979 to 1988 and 2006 to 2007, respectively, 2036 and 15,764 topsoil (20-cm) samples were collected and analyzed for SOC concentration and density from croplands covering 12 Chinese soil groups. By comparing the SOC data from the mid-2000s and the 1980s, we found that across the four counties, topsoil (20-cm) SOC concentration and density in croplands changed significantly (P < 0.01) at a rate of 0.04 +/- 0.14 g kg(-1) yr(-1) or 0.01 +/- 0.03 kg m(-2) yr(-1) from 7.9 +/- 3.5 g kg(-1) and 1.98 +/- 0.9 kg m(-2) in the 1980s to 8.7 +/- 2.4 g kg(-1) and 2.22 +/- 0.5 kg m(-2) in the mid-2000s, respectively. This overall increase in topsoil (20-cm) SOC concentration by 10% or density by 12% in the mid-2000s was associated with an increase of 83% in the stubble and root inputs to the soil across the four counties. There were large differences in the change size in the cropland topsoil (20-cm) SOC concentration and density among counties. In Huixian and Xifeng, both the topsoil SOC concentration and density in the mid-2000s were significantly higher than in the 1980s (P < 0.01), whereas there were no significant changes in topsoil SOC concentration and density in either Linxia or Yuzhong. Soils with lower initial SOC tended to increase more in SOC concentration than soils with higher initial SOC.

Substantial improvements have been made to the Canadian Agricultural Nitrogen Budget model (CANB) for estimating residual soil nitrogen (RSN) and the indicator of the risk of water contamination by nitrogen (IROWC-N). These included new algorithms for manure, fertilizer and biological fixation inputs and losses as well as the incorporation of a versatile soil moisture model. The new semi-dynamic model (CANB v 3.0) was compared to the static model (CANB 2.0) for estimating both RSN and IROWC-N. Sensitivity analysis of the RSN component using 2006 land use practices was also conducted and crop yield and N uptake were found to be the most sensitive parameters, followed by biological N2 fixation and the addition of fertilizer N and manure N. Land use scenarios were evaluated to examine if increasing the proportion of biofuel crops grown in Canada would change RSN and IROWC-N appreciably. The analyses demonstrated that the area of canola and maize crops could be increased in Canada by up to 40% to meet biofuel production demands without significantly changing RSN and IROWC-N.

Soil-crop simulation models can be a valuable tool in evaluating conservation tillage practices which are viable both economically and environmentally. The objective of this study was to evaluate the ability of the DSSAT (Decision Support Systems for Agro-technology Transfer) Cropping System Model (CSM) with the CSM-CROPGRO-Soybean and CSM-CERES-Maize modules to predict crop yields and root zone soil water and temperature dynamics for a soybean (Glycine max)–maize (Zea mays) rotation under conventional tillage (CT), reduced conventional tillage (RT) and no-tillage (NT) on a cool, semi-arid “Black soil” (Mollisol) in Northeastern China. Crop yield, soil water content and soil temperature data collected from a field experiment at Hailun Experimental Station (47°26′N, 126°38′E) during 2004–2011 were used for model calibration and evaluation. The soybean and maize cultivar coefficients were calibrated using the CT yield data, and evaluated using the RT and NT yield data. “Good” agreement between simulated and measured yields was achieved for model calibration (normalized Residual Mean Square Error, nRMSE = 9–15%), and “good” to “moderate” agreement was achieved for model evaluation (nRMSE = 12–17%). Simulated volumetric soil water content in the top 20 cm of CT, RT and NT were in “moderate” to “good” agreement with measurements (index of agreement, d = 0.81–0.91; nRMSE = 15.3–20.0%), provided that non-destructive in situ measurements of water content were used. Overall agreement between measured and simulated soil temperature varied from “poor” to “excellent” depending on year and tillage; and the measured soil temperatures were consistently overestimated (mean error, E = 3.2–6.2), possibly due to lack of accounting in DSSAT for the insulating effects of accumulated surface residues, and the shading effects of standing crops. Refinement of the soil temperature algorithm in DSSAT is recommended.

The merging and combustion characteristics of droplets composed of water and diesel, methanol and diesel, and water + methanol (W + M) and diesel were investigated. For the merged droplets of water and diesel, the water droplets inserted into diesel in all test conditions. While only diesel vaporized during the burning period, the remaining water droplet terminated by either flash vaporization into water mist or extinguished as residue. For methanol and diesel, instead, the methanol droplet tended to enclose the diesel droplet when its size was relatively larger than that of diesel and adhered with the diesel droplet when its size was sufficiently small. As methanol content increased beyond ∼50%, the flame became almost invisible after ignition with a delayed, regular explosion occurring after the appearance of a yellowish flame. For those with lower methanol content, an explosion occurred shortly after the ignition with branched flame or slightly delayed with a flame ball. As for W + M and diesel, most of the merged droplets were in adhesive-like mode at the room temperature. However, the initial burning exhibited an insertive-like burning mode, with the yellowish flame as that of pure diesel or merged water and diesel droplet. The burning ended with droplet extinction, flash vaporization, or explosion at different mixing ratios of pre-mixture and diesel content. Practically, water and diesel emulsions could reduce smoke emissions from burning. Our results have shown that by adding methanol into water or alone and mixed with diesel can have superior burning behavior than water/diesel emulsions. Therefore, the potential of separate injections of water, methanol or W + M mixture, and oil in opposed jet arrangements, in direct-injection engines, is suggested.

Simulation models are being regarded as an important tool to simulate crop growth, soil nutrient dynamics and soil carbon sequestration and fast use of the embedded knowledge of crop-soil processes. The Decision Support Systems for Agrotechnology Transfer (DSSAT) model was used to simulate long-term continuous maize growth from 1990 to 2007 in Gongzhuling, Northeast China. Three levels of N treatments were simulated, including: (1) no N (N0), (2) 165 kg N ha−1 from synthetic fertilizer (N165) and (3) 50 kg N ha−1 from synthetic fertilizer plus 115 kg N ha−1 from farmyard manure (N165M). Both measured and simulated results showed that the maize yield was significantly lower in the N0 treatment. The measured maize yield was higher in N165M than N165 treatments after 2003. The maize yield was also affected by the weather, especially during drought years. The simulated soil organic C (SOC) content was in good agreement with the measured data in the 0–30 cm depth for all treatments. The SOC density in the 0–30 cm depth decreased by 4,393 kg C ha−1 (18 %) in the N0 treatment and 4,186 kg C ha−1 (17 %) in the N165 treatment, while it increased by 13,628 kg C ha−1 (54 %) in the N165M treatment during 1990–2007, indicating that the combination of inorganic fertilizer and organic manure improved soil quality after 27 years of organic amendment from 1980. Soil mineral N levels were significantly higher in the N165 treatment just before planting (averaged 289 kg N ha−1), associated with more soil N leaching during the growing seasons (24–155 kg N ha−1) in some wet years, while soil mineral N levels were much lower in both the N0 (averaged 52 kg N ha−1) and N165M treatments (averaged 54 kg N ha−1) associated with less N leaching (