3414 field experiment （including three nutrient elements at four gradient levels, a total of 14 unrepeated incomplete treatments） was designed to study the fertilization measures for wheat interplanted with cotton i...3414 field experiment （including three nutrient elements at four gradient levels, a total of 14 unrepeated incomplete treatments） was designed to study the fertilization measures for wheat interplanted with cotton in Qianjiang City, Hubei Province. Fertilizer model for wheat interplanted with cotton in Jianghan Plain was finally established, based on which the soil nutrient indices in wheat-cotton inter- planting field were screened; and optimal nitrogen, phosphorus and potassium appli- cation for wheat was put forward as 130-210 kg/hm2 N, 40-70 kg/hm2 P2O5 and 40-60 kg/hm2 K2O.展开更多
The response of rice to N fertilizer applicationhas shown that high rates of N application donot always ensure a proportional increase inyield due to high N losses. A model, ORYZA-0 was developed by ten Berge for desi...The response of rice to N fertilizer applicationhas shown that high rates of N application donot always ensure a proportional increase inyield due to high N losses. A model, ORYZA-0 was developed by ten Berge for designingoptimum N fertilizer management strategy inrice. We evaluated the performance ofORYZA-0 in Jinhua, Zhejiang Province. ORYZA-0 includes N uptakes, partition-ing of N among the organs, and utilization ofleaf N in converting solar energy to dry mat-ter. It can predict the amount and time of Nfertilizer application to achieve a maximumbiomass or yield combining with Price algo-rithm optimization procedure.展开更多
Crop models can be useful tools ibr 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...Crop models can be useful tools ibr 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 upfake 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-~）. 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.展开更多
优化氮肥施用和秸秆还田技术为途径的农业管理措施被认为是提升农业可持续性的有效手段,然而当前关于氮肥和秸秆还田对小麦产量和N_(2)O排放影响的研究仍十分有限。为此,本研究基于2000—2022年发表的关于长江中下游流域氮肥和秸秆投入...优化氮肥施用和秸秆还田技术为途径的农业管理措施被认为是提升农业可持续性的有效手段,然而当前关于氮肥和秸秆还田对小麦产量和N_(2)O排放影响的研究仍十分有限。为此,本研究基于2000—2022年发表的关于长江中下游流域氮肥和秸秆投入下小麦产量和N_(2)O排放变化的文献,运用随机森林建模,定量分析氮肥和秸秆还田对小麦产量和N_(2)O排放的影响,并结合情景设置进行了特定地点的小麦产量和N_(2)O排放模拟,同时评估了碳排放强度(CEE)和净生态系统经济效益(NEEB)。结果表明,建立的区域尺度小麦产量与N_(2)O排放对氮秸互作响应的随机森林模型,验证结果R^(2)分别为0.66和0.65,RMSE分别为0.70和1.11。结果表明施氮量和土壤有机质是影响小麦产量和N_(2)O排放的重要因素。综合来看,达到最大产量所需的氮肥量为208~212 kg hm^(-2),达到最小CEE所需的氮肥量为113~130 kg hm^(-2),达到最高的NEEB所需的氮肥量为202~205 kg hm^(-2),其中在6.75 t hm^(-2)的秸秆投入下施用202 kg hm^(-2)的氮肥可以获得最高的生态收益1.37万元。优化氮肥和秸秆投入具备减少作物碳排放强度并获得最大净生态环境效益的潜力。展开更多
基金Supported by the Fund from Agricultural Science and Technology Innovation Center of Hubei Province(2011-620-001-03)the Supporting Program of Hubei Academy of Agricultural Sciences(2014FCXJH06)+1 种基金the Fund from Key Laboratory of Soil Quality Research,Chinese Academy of Agricultural Sciences(CAAS-2010HB)Financial Subsidy for National Soil Test-based Fertilization Recommendation Research(CNCT09-32)~~
文摘3414 field experiment （including three nutrient elements at four gradient levels, a total of 14 unrepeated incomplete treatments） was designed to study the fertilization measures for wheat interplanted with cotton in Qianjiang City, Hubei Province. Fertilizer model for wheat interplanted with cotton in Jianghan Plain was finally established, based on which the soil nutrient indices in wheat-cotton inter- planting field were screened; and optimal nitrogen, phosphorus and potassium appli- cation for wheat was put forward as 130-210 kg/hm2 N, 40-70 kg/hm2 P2O5 and 40-60 kg/hm2 K2O.
文摘The response of rice to N fertilizer applicationhas shown that high rates of N application donot always ensure a proportional increase inyield due to high N losses. A model, ORYZA-0 was developed by ten Berge for designingoptimum N fertilizer management strategy inrice. We evaluated the performance ofORYZA-0 in Jinhua, Zhejiang Province. ORYZA-0 includes N uptakes, partition-ing of N among the organs, and utilization ofleaf N in converting solar energy to dry mat-ter. It can predict the amount and time of Nfertilizer application to achieve a maximumbiomass or yield combining with Price algo-rithm optimization procedure.
基金funded by the National Basic Research Program of China (2007CB109306 and 2013CB127405)The authors acknowledge Ministry of Education,China,for providing the scholarship (2008325008)
文摘Crop models can be useful tools ibr 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 upfake 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-~）. 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.
文摘优化氮肥施用和秸秆还田技术为途径的农业管理措施被认为是提升农业可持续性的有效手段,然而当前关于氮肥和秸秆还田对小麦产量和N_(2)O排放影响的研究仍十分有限。为此,本研究基于2000—2022年发表的关于长江中下游流域氮肥和秸秆投入下小麦产量和N_(2)O排放变化的文献,运用随机森林建模,定量分析氮肥和秸秆还田对小麦产量和N_(2)O排放的影响,并结合情景设置进行了特定地点的小麦产量和N_(2)O排放模拟,同时评估了碳排放强度(CEE)和净生态系统经济效益(NEEB)。结果表明,建立的区域尺度小麦产量与N_(2)O排放对氮秸互作响应的随机森林模型,验证结果R^(2)分别为0.66和0.65,RMSE分别为0.70和1.11。结果表明施氮量和土壤有机质是影响小麦产量和N_(2)O排放的重要因素。综合来看,达到最大产量所需的氮肥量为208~212 kg hm^(-2),达到最小CEE所需的氮肥量为113~130 kg hm^(-2),达到最高的NEEB所需的氮肥量为202~205 kg hm^(-2),其中在6.75 t hm^(-2)的秸秆投入下施用202 kg hm^(-2)的氮肥可以获得最高的生态收益1.37万元。优化氮肥和秸秆投入具备减少作物碳排放强度并获得最大净生态环境效益的潜力。
