Increasing domestic rapeseed production is an important national goal in China. Researchers often use tools such as crop models to determine optimum management practices for new varieties to ...increased production. The CROPGRO-Canola model has not been used to simulate rapeseed in China. The overall goal of this work was to identify key inputs to the CROPGRO-Canola model for calibration with limited datasets in the Yangtze River basin. First, we conducted a global sensitivity analysis to identify key genetic and soil inputs that have a large effect on simulated days to flowering, days to maturity, yield, above-ground biomass, and maximum leaf area index. The extended Fourier amplitude test method (EFAST) sensitivity analysis was performed for a single year at 8 locations in the Yangtze River basin (spatial analysis) and for seven years at a location in Wuhan, China (temporal analysis). The EFAST software was run for 4520 combinations of input parameters for each site and year, resulting in a sensitivity index for each input parameter. Parameters were ranked using the top-down concordance method to determine relative sensitivity. Results indicated that the model outputs of days to flowering, days to maturity, yield, above-ground biomass, and maximum leaf area index were most sensitive to parameters that affect the duration of critical growth periods, such as emergence to flowering, and temperature response to these stages, as well as parameters that affect total biomass at harvest. The five model outputs were also sensitive to several soil parameters, including drained upper and lower limit (SDUL and SLLL) and drainage rate (SLDR). The sensitivity of parameters was generally spatially and temporally stable. The results of the sensitivity analysis were used to calibrate and evaluate the model for a single rapeseed experiment in Wuhan, China. The model was calibrated using two seasons and evaluated using three seasons of data. Excellent nRMSE values were obtained for days to flowering (≤1.71%), days to maturity (≤ 1.48%), yield (≤ 9.96%), and above-ground biomass (≤ 9.63%). The results of this work can be used to guide researchers on model calibration and evaluation across the Yangtze River basin in China.
Melatonin is effective in enhancing various abiotic stress resistances of plants. However, its underlying mechanisms in drought-resistance in winter wheat (Triticum aestivum L.) is not clear. The ...goal of this work was to investigate the effect of melatonin on seed germination and to evaluate leaf antioxidant physiology for two wheat varieties. Experiments included 20% PEG, melatonin plus 20% PEG and a control using two contrasting wheat varieties (JM22- drought sensitive and HG35- drought resistant). Melatonin levels were 0, 1, 10, 100 and 300 mumol L.sup.-1 . Results revealed that 300 mumol L.sup.-1 of melatonin alleviated the negative effect of water stress on germination and increased radicle length, radicle number, and plumule length of the germinated seeds. Principal component analysis showed a significant change in amino acid content during germination and this change was dependent on melatonin concentration and the variety. Lysine (Lys) content in wheat seeds under the PEG plus 300 mumol L.sup.-1 melatonin treatment increased compared with that of the seeds under PEG alone. There was a significant and positive correlation between Lys content and morphological index of germination. During seedling growth, soluble protein was involved in osmotic adjustment and superoxide dismutase (SOD) activity was increased to mitigate the damage in the cytomembrane of JM 22 leaf under 300 mumol L.sup.-1 melatonin plus PEG treatment. The effect of melatonin was dependent on SOD activity increasing significantly for HG35-a drought resistant variety. The results of this work lays a foundation for further studies to determine if melatonin can be economically used to mitigate the impact of dry planting conditions on wheat productivity in North China Plain.
The North China Plain is one of the most important grain production regions in China, but is facing serious water shortages. To achieve a balance between water use and the need for food ...self-sufficiency, new water efficient irrigation strategies need to be developed that balance water use with farmer net return. The Crop Environment Resource Synthesis Wheat (CERES-Wheat model) was calibrated and evaluated with two years of data which consisted of 3-4 irrigation treatments, and the model was used to investigate long-term winter wheat productivity and water use from irrigation management in the North China Plain. The calibrated model simulated accurately above-ground biomass, grain yield and evapotranspiration of winter wheat in response to irrigation management. The calibrated model was then run using weather data from 1994-2016 in order to evaluate different irrigation strategies. The simulated results using historical weather data showed that grain yield and water use was sensitive to different irrigation strategies including amounts and dates of irrigation applications. The model simulated the highest yield when irrigation was applied at jointing (T9) in normal and dry rainfall years, and gave the highest simulated yields for irrigation at double ridge (T8) in wet years. A single simulated irrigation at jointing (T9) produced yields that were 88% compared to using a double irrigation treatment at T1 and T9 in wet years, 86% of that in normal years, and 91% of that in dry years. A single irrigation at jointing or double ridge produced higher water use efficiency because it obtained higher evapotranspiration. The simulated farmer irrigation practices produced the highest yield and net income. When the cost of water was taken into account, limited irrigation was found to be more profitable based on assumptions about future water costs. In order to increase farmer income, a subsidy will likely be needed to compensate farmers for yield reductions due to water savings. These results showed that there is a cost to the farmer for water conservation, but limiting irrigation to a single irrigation at jointing would minimize impact on farmer net return in North China Plain.
Excessive ammonia (NH3) emitted from nitrogen (N) fertilizer applications in global croplands plays an important role in atmospheric aerosol production, resulting in visibility reduction and regional ...haze. However, large uncertainty exists in the estimates of NH3 emissions from global and regional croplands, which utilize different data and methods. In this study, we have coupled a process‐based Dynamic Land Ecosystem Model (DLEM) with the bidirectional NH3 exchange module in the Community Multiscale Air‐Quality (CMAQ) model (DLEM‐Bi‐NH3) to quantify NH3 emissions at the global and regional scale, and crop‐specific NH3 emissions globally at a spatial resolution of 0.5° × 0.5° during 1961–2010. Results indicate that global NH3 emissions from N fertilizer use have increased from 1.9 ± 0.03 to 16.7 ± 0.5 Tg N/year between 1961 and 2010. The annual increase of NH3 emissions shows large spatial variations across the global land surface. Southern Asia, including China and India, has accounted for more than 50% of total global NH3 emissions since the 1980s, followed by North America and Europe. Rice cultivation has been the largest contributor to total global NH3 emissions since the 1990s, followed by corn and wheat. In addition, results show that empirical methods without considering environmental factors (constant emission factor in the IPCC Tier 1 guideline) could underestimate NH3 emissions in context of climate change, with the highest difference (i.e., 6.9 Tg N/year) occurring in 2010. This study provides a robust estimate on global and regional NH3 emissions over the past 50 years, which offers a reference for assessing air quality consequences of future nitrogen enrichment as well as nitrogen use efficiency improvement.
Based on the process‐based DLEM‐Bi‐NH3 module, global NH3 emissions from N fertilizer use have increased by 14.8 Tg N/year during the period 1961–2010. At the regional scale, southern Asia, including China and India, has accounted for more than 50% of total global NH3 emissions since the 1980s. Rice cultivation has been the largest contributor to total global NH3 emissions since the 1990s, followed by corn and wheat. In addition, results show that empirical methods without considering environmental factors (constant emission factor in the IPCC Tier 1 guideline) could underestimate NH3 emissions in the context of climate change, with the highest difference (i.e., 6.9 Tg N/year) occurring in 2010.
An integrated model WHCNS (soil Water Heat Carbon Nitrogen Simulator) was developed to assess water and nitrogen (N) management in North China. It included five main modules: soil water, soil ...temperature, soil carbon (C), soil N, and crop growth. The model integrated some features of several widely used crop and soil models, and some modifications were made in order to apply the WHCNS model under the complex conditions of intensive cropping systems in North China. The WHCNS model was evaluated using an open access dataset from the European International Conference on Modeling Soil Water and N Dynamics. WHCNS gave better estimations of soil water and N dynamics, dry matter accumulation and N uptake than 14 other models. The model was tested against data from four experimental sites in North China under various soil, crop, climate, and management practices. Simulated soil water content, soil nitrate concentrations, crop dry matter, leaf area index and grain yields all agreed well with measured values. This study indicates that the WHCNS model can be used to analyze and evaluate the effects of various field management practices on crop yield, fate of N, and water and N use efficiencies in North China.
Background and aims
Organic farming has been viewed as a sustainable practice that can maintain yields and improve soil quality in greenhouse vegetable production. However, little attention has been ...given to the leaching of dissolved organic nitrogen (DON) due to excessive application of organic manure. The objectives of this study were to compare the characteristics of dissolved inorganic nitrogen (DIN) and DON leaching under different greenhouse vegetable production systems.
Methods
A 2-year lysimeter field experiment was conducted with three different farming systems in North China, i.e. conventional (CON, 70% chemical fertilizer +30% organic manure), integrated (INT, 50% chemical fertilizer +50% organic manure) and organic (ORG, 100% organic manure).
Results
The results indicated that vegetable yields under the ORG system were normally larger than the CON or INT. The amount of water drainage and dissolved total N (DTN, DIN + DON) leaching differed during two cropping seasons, with spring and summer seasons giving greater leaching than autumn and winter seasons. The total DIN leaching throughout four seasons of vegetable production under ORG was 176 kg N ha
−1
, which was much lower than that of CON (327 kg N ha
−1
) and INT (269 kg N ha
−1
). The DTN leaching under ORG (485 kg N ha
−1
) was also less than that of CON (528 kg N ha
−1
) and INT (521 kg N ha
−1
). However, the total DON leaching under the ORG was 309 kg N ha
−1
, far higher than the amounts for CON (202 kg N ha
−1
) and INT (252 kg N ha
−1
). The average DON leaching ratio (DON/DTN) under the ORG system was 63.7%, which was also much higher than that of the CON (38%) and INT (48%) systems. The increase in the proportion of organic manure in fertilizer types and over-irrigation were the main reasons for the increase in DTN leaching. Structural equation modeling analysis showed that the soil bulk density, saturated hydraulic conductivity and saturated soil water content were the most important factors influencing the DTN leaching.
Conclusions
While the ORG system has many advantages, irrigation and fertilizer scheduling should be optimized under the ORG system in order to minimize DON leaching.
The threat of global climate change on wheat production may be underestimated by the limited capacity of many crop models to predict grain quality and protein composition. This study aimed to ...integrate a wheat quality module of protein components into the CROPSIM-CERES-Wheat model to investigate the impact of climate change on wheat grain yield and protein quality in the North China Region (NCR) using five Global Climate Models (GCMs) from CMIP6 under three shared socioeconomic pathways. The CERES-Wheat model with a quality module was developed and calibrated and validated using data from several sites in the NCR. The results of the calibration and validation showed that the modified CERES-Wheat model can accurately predict grain yield, protein content and its components in field experiments. Compared with the baseline period (1981-2010), the annual mean temperature and annual cumulative precipitation increased in the NCR in the 2030's, 2050's and 2080's. The radiation was higher under the SSP126 and SSP585 scenarios, and lower under the SSP370 scenario compared to the baseline period. The anthesis and maturity date occurred earlier under the three future scenarios. The average grain yield increased by 13.3-30.9 % under three future scenarios. However, the regional average grain protein content of winter wheat in the future decreased by 2.0 %- 3.5 %. The reduction in wheat grain protein at the regional was less pronounced under SSP370 than that under SSP126 and SSP585. The structural protein content of winter wheat decreased under future climate conditions compared with the baseline period, but the storage protein content showed the opposite tendency. The model provided a useful tool to study the effects of future climate on grain quality and protein composition. These findings are important for developing agricultural practices and strategies to mitigate the potential impacts of climate change on wheat production and wheat quality in the future.
Display omitted
•A greenhouse vegetable water and N management tool was developed.•The sensitivity analysis of the model was conducted base on PEST methods.•The input parameters were auto-calibrated ...by coupling PEST.•The model performed well in modeling water and N fates, and vegetable growth.
Excessive water and fertilizer inputs have led to a series of environmental problems in vegetable production areas in China. Identifying the fates of water and nutrients is crucial to develop best management strategies in intensive vegetable production systems. The objectives of this study were to (i) develop a scientific water and nitrogen (N) management tool for intensive greenhouse vegetable production in China, and (ii) evaluate the model performance in the simulating the fate of water and N, and vegetable growth under different water and N management practices in China. A vegetable growth component was added to the field soil-crop system model WHCNS (soil Water Heat Carbon Nitrogen Simulator), named WHCNS_Veg. Parameters for the model were estimated and a sensitivity analysis was conducted by coupling the model with the model-independent parameter estimation program (PEST). Data used to test the model came from two years of cucumber and tomato experiments with various water and N combinations in Shandong province, China. The results of sensitivity analysis showed that the soil hydraulic parameters and vegetable genetic parameters had a relatively higher sensitivity compared with those of N transformation parameters. The saturated soil water content had the highest sensitivity among soil hydraulic parameters, and the total available accumulated temperature, crop coefficient and maximum root depth had higher sensitivity for both vegetable crops. Among the N transformation parameters, the parameters related to nitrification had the highest sensitivity. The automatic optimization algorithm performed well in adjusting soil hydraulic parameters, vegetable genetic parameters and N transformation parameters. The normalized root mean square error for soil water content, soil nitrate concentration, marketable fresh yield and vegetable N uptake were 5.7%, 28.0%, 2.7% and 8.3%, respectively, and indices of agreement were 0.727, 0.730, 0.997 and 0.832, respectively. The results indicated that the WHCNS_Veg model has great potential to simulate and analyze water and N fates, and vegetable growth for the intensive greenhouse vegetable production in China.
Site-specific crop management is based on the postulate of varying soil and crop requirements in a field. Therefore, a field is separated into homogenous management zones, using available data to ...adapt management practices environment to maximize productivity and profitability while reducing environmental impacts. Due to advancing sensor technologies, crop growth and yield data on more minor scales are common, but soil data often needs to be more appropriate. Crop growth models have shown promise as a decision support tool for site-specific farming. The Decision Support System for Agrotechnology Transfer (DSSAT) is a widely used point-based model. To overcome the problem of inappropriate soil input data problem, this study introduces an external plug-in program called Soil Profile Optimizer (SPO), which uses the current DSSAT v4.8 to calibrate soil profile parameters on a site-specific level. Developed as an inverse modelling approach, the SPO can calibrate selected soil profile parameters by targeting available in-season plant data. Root Mean Square Error (RMSE) and normalized RMSE as error minimization criteria are used. The SPO was tested and evaluated by comparing different simulation scenarios in a case study of a 3-yr field trial with maize. The scenario with optimized soil profiles, conducted with the SPO, resulted in an R
2
of 0.76 between simulated and observed yield and led to significant improvements compared to the scenario conducted with field scale soil profile information (R
2
0.03). The SPO showed promise in using spatial plant measurements to estimate management zone scale soil parameters required for the DSSAT model.
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