The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass...The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat yield.However,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale.Time-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter wheat.In this study,Fr equations were fitted for each organ of winter wheat using site-scale data.These equations were then coupled into a process-based and remote sensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),respectively.The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.展开更多
Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies.However,crop yield is influenced by multiple factors within complex growth environments.Previous r...Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies.However,crop yield is influenced by multiple factors within complex growth environments.Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat.Therefore,there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield,making precise yield prediction increasingly important.This study was based on four type of indicators including meteorological,crop growth status,environmental,and drought index,from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield.Using the sparrow search al-gorithm combined with random forest(SSA-RF)under different input indicators,accuracy of winter wheat yield estimation was calcu-lated.The estimation accuracy of SSA-RF was compared with partial least squares regression(PLSR),extreme gradient boosting(XG-Boost),and random forest(RF)models.Finally,the determined optimal yield estimation method was used to predict winter wheat yield in three typical years.Following are the findings:1)the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms.The best yield estimation method is achieved by four types indicators’composition with SSA-RF)(R^(2)=0.805,RRMSE=9.9%.2)Crops growth status and environmental indicators play significant roles in wheat yield estimation,accounting for 46%and 22%of the yield importance among all indicators,respectively.3)Selecting indicators from October to April of the follow-ing year yielded the highest accuracy in winter wheat yield estimation,with an R^(2)of 0.826 and an RMSE of 9.0%.Yield estimates can be completed two months before the winter wheat harvest in June.4)The predicted performance will be slightly affected by severe drought.Compared with severe drought year(2011)(R^(2)=0.680)and normal year(2017)(R^(2)=0.790),the SSA-RF model has higher prediction accuracy for wet year(2018)(R^(2)=0.820).This study could provide an innovative approach for remote sensing estimation of winter wheat yield.yield.展开更多
Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to ac...Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.Thus,we proposed a new approach to approximating irrigations of winter wheat over the North China Plain(NCP),where irrigation occurs extensively during the winter wheat growing season.This approach used irrigation pattern parameters(IPPs)to define the irrigation frequency and timing.Then,they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat(PRYM–Wheat),to improve the regional estimates of winter wheat over the NCP.The IPPs were determined using statistical yield data of reference years(2010–2015)over the NCP.Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield,with an increase and decrease in the correlation coefficient(R)and root mean square error(RMSE)of 0.15(about 37%)and 0.90 t ha–1(about 41%),respectively.The data in validation years(2001–2009 and 2016–2019)were used to validate PRYM–Wheat.In addition,our findings also showed R(RMSE)of 0.80(0.62 t ha–1)on a site level,0.61(0.91 t ha–1)for Hebei Province on a county level,0.73(0.97 t ha–1)for Henan Province on a county level,and 0.55(0.75 t ha–1)for Shandong Province on a city level.Overall,PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years,providing a scientific basis for ensuring regional food security.展开更多
The establishment of crop yield estimating model based on microwave and optical satellite images can conduct the mutual verification of the accuracy of the reported crop yield and the precision of the estimating model...The establishment of crop yield estimating model based on microwave and optical satellite images can conduct the mutual verification of the accuracy of the reported crop yield and the precision of the estimating model. With Shou County and Huaiyuan County of Anhui Province as the experimental fields of winter wheat producing areas, the linear winter wheat yield estimating models were established by adopting backscattering coefficient and Normalized Difference Vegetation Index（NDVI） based on images from the synthetic aperture radar（SAR）—RDARSAT-2 and HJ satellite photographed in mid-April and early May, 2014, and then comparisons were conducted on the accuracy of the yield estimating models. The accuracies of the yield estimating models established using co-polarized（HH） and cross-polarized（HV） modes of SAR in Jiangou Town, Shou County were 68.37% and 74.01%, respectively, while the accuracies in Longkang Town, Huaiyuan County were 63.10%and 69.10%, respectively. Accuracies of yield estimating models established by HJ satellite data were 69.52% and 66.43% in Shou County and Huaiyuan County, respectively. Accuracies of winter yield estimating model based on HJ satellite data and that based on SAR were closed, and the yield difference of winter wheat in the lodging region was analyzed in detail. The model results laid the foundation and accumulated experience for the verification, parameters correction and promotion of the winter wheat yield estimating model.展开更多
To accurately estimate winter wheat yields and analyze the uncertainty in crop model data assimilations, winter wheat yield estimates were obtained by assimilating measured or remotely sensed leaf area index （LAI） v...To accurately estimate winter wheat yields and analyze the uncertainty in crop model data assimilations, winter wheat yield estimates were obtained by assimilating measured or remotely sensed leaf area index （LAI） values. The performances of the calibrated crop environment resource synthesis for wheat （CERES-Wheat） model for two different assimilation scenarios were compared by employing ensemble Kalman filter （EnKF）-based strategies. The uncertainty factors of the crop model data assimilation was analyzed by considering the observation errors, assimilation stages and temporal-spatial scales. Overalll the results indicated a better yield estimate performance when the EnKF-based strategy was used to comprehen- sively consider several factors in the initial conditions and observations. When using this strategy, an adjusted coefficients of determination （R2） of 0.84, a root mean square error （RMSE） of 323 kg ha-1, and a relative errors （RE） of 4.15% were obtained at the field plot scale and an R2 of 0.81, an RMSE of 362 kg ha-1, and an RE of 4.52% were obtained at the pixel scale of 30 mx30 m. With increasing observation errors, the accuracy of the yield estimates obviously decreased, but an acceptable estimate was observed when the observation errors were within 20%. Winter wheat yield estimates could be improved significantly by assimilating observations from the middle to the end of the crop growing seasons. With decreasing assimilation frequency and pixel resolution, the accuracy of the crop yield estimates decreased; however, the computation time decreased. It is important to consider reasonable temporal-spatial scales and assimilation stages to obtain tradeoffs between accuracy and computation time, especially in operational systems used for regional crop yield estimates.展开更多
Accurate estimation of regional-scale crop yield under drought conditions allows farmers and agricultural agencies to make well-informed decisions and guide agronomic management. However, few studies have focused on u...Accurate estimation of regional-scale crop yield under drought conditions allows farmers and agricultural agencies to make well-informed decisions and guide agronomic management. However, few studies have focused on using the crop model data assimilation(CMDA) method for regional-scale winter wheat yield estimation under drought stress and partial-irrigation conditions. In this study, we developed a CMDA framework to integrate remotely sensed water stress factor(MOD16 ET PET) with the WOFOST model using an ensemble Kalman filter(En KF) for winter wheat yield estimation at the regional scale in the North China Plain(NCP) during 2008–2018. According to our results, integration of MOD16 ET PETwith the WOFOST model produced more accurate estimates of regional winter wheat yield than open-loop simulation. The correlation coefficient of simulated yield with statistical yield increased for each year and error decreased in most years, with r ranging from 0.28 to 0.65 and RMSE ranging from 700.08 to1966.12 kg ha. Yield estimation using the CMDA method was more suitable in drought years(r = 0.47, RMSE = 919.04 kg ha) than in normal years(r = 0.30, RMSE = 1215.51 kg ha). Our approach performed better in yield estimation under drought conditions than the conventional empirical correlation method using vegetation condition index(VCI). This research highlighted the potential of assimilating remotely sensed water stress factor, which can account for irrigation benefit, into crop model for improving the accuracy of winter wheat yield estimation at the regional scale especially under drought conditions, and this approach can be easily adapted to other regions and crops.展开更多
Sowing date and seeding rate are critical for productivity of winter wheat(Triticum aestivum L.).A three-year field experiment was conducted with three sowing dates(20 September(SD1),1 October(SD2),and 10 October(SD3)...Sowing date and seeding rate are critical for productivity of winter wheat(Triticum aestivum L.).A three-year field experiment was conducted with three sowing dates(20 September(SD1),1 October(SD2),and 10 October(SD3)) and three seeding rates(SR67.5,SR90,and SR112.5) to determine suitable sowing date and seeding rate for high wheat yield.A large seasonal variation in accumulated temperature from sowing to winter dormancy was observed among three growing seasons.Suitable sowing dates for strong seedlings before winter varied with the seasons,that was SD2 in 2012–2013,SD3 in 2013–2014,and SD2 as well as SD1 in 2014–2015.Seasonal variation in precipitation during summer fallow also had substantial effects on soil water storage,and consequently influenced grain yield through soil water consumption from winter dormancy to maturity stages.Lower consumption of soil water from winter dormancy to booting stages could make more water available for productive growth from anthesis to maturity stages,leading to higher grain yield.SD2 combined with SR90 had the lowest soil water consumption from winter dormancy to booting stages in 2012–2013 and 2014–2015; while in 2013–2014,it was close to that with SR67.5 or SR112.5.For productive growth from anthesis to maturity stages,SD2 with SR90 had the highest soil water consumption in all three seasons.The highest water consumption in the productive growth period resulted in the best grain yield in both low and high rainfall years.Ear number largely contributed to the seasonal variation in grain yield,while grain number per ear and 1 000-grain weight also contributed to grain yield,especially when soil water storage was high.Our results indicate that sowing date and seeding rate affect grain yield through seedling development before winter and also affect soil water consumption in different growth periods.By selecting the suitable sowing date(1 October) in combination with the proper seeding rate of 90 kg ha–1,the best yield was achieved.Based on these results,we recommend that the current sowing date be delayed from 22 or 23 September to 1 October.展开更多
This paper presents the applications of Landsat Thematic Mapper (TM) data and Advanced Very High Resolution Radiometer (AVHRR) time series data for winter wheat production estimation in North China Plain. The keytechn...This paper presents the applications of Landsat Thematic Mapper (TM) data and Advanced Very High Resolution Radiometer (AVHRR) time series data for winter wheat production estimation in North China Plain. The keytechniques are described systematically about winter wheat yield estimation system, including automatically extractingwheat area, simulating and monitoring wheat growth situation, building wheat unit yield model of large area and forecasting wheat production. Pattern recognition technique was applied to extract sown area using TM data. Temporal NDVI(Normal Division Vegetation Index) profiles were produced from 8 - 12 times AVHRR data during wheat growth dynamically. A remote sensing yield model for large area was developed based on greenness accumulation, temperature andgreenness change rate. On the basis of the solution of key problems, an operational system for winter wheat yield estimation in North China Plain using remotely sensed data was established and has operated since 1993, which consists of 4 subsystems, namely databases management, image processing, models bank management and production prediction system.The accuracy of wheat production prediction exceeded 96 per cent compared with on the spot measurement.展开更多
Based on split plot design method of field test,the impacts of supplemental irrigation based on soil moisture measurement and nitrogen use on winter wheat yield and nitrogen absorption and distribution were studied.Su...Based on split plot design method of field test,the impacts of supplemental irrigation based on soil moisture measurement and nitrogen use on winter wheat yield and nitrogen absorption and distribution were studied.Supplemental irrigation had three levels: 60%(W_1),70%(W_2) and 80%(W3) of the targeted relative water content at 0-40 cm of soil layer during jointing period of winter wheat.Nitrogen fertilization had three levels: not using nitrogen(N_0),using pure nitrogen of 195 kg/hm^2(N_(195)) and 255 kg/hm^2(N_(255)).Results showed that:(i)different supplemental irrigation and nitrogen fertilization significantly affected plant height and leaf area of winter wheat during key growth period.Under the same supplemental irrigation treatment,both plant height and leaf area of winter wheat showed as N_(255)> N_(195)> N_0(P <0.05).Plant height in N_(195) and N_(255)treatments was significantly higher than that in N_0 treatment,but there was not significant difference between N_(195) and N_(255)(P >0.05).Under the same nitrogen fertilization,plant height in W_2(569.4 m^3/hm^2) and W3(873.45 m^3/hm^2) treatments was significant higher than that in W_1(265.2 m^3/hm^2),but there was not significant difference between W_2 and W3(P >0.05).It illustrated that excessive nitrogen fertilization and supplemental irrigation did not significantly affect plant height and leaf area of winter wheat.(ii) Under the same nitrogen fertilization level,yield increase effect of winter wheat by supplemental irrigation showed a declining trend with nitrogen application amount increased.It illustrated that nitrogen fertilization and supplemental irrigation had certain critical values on the yield of winter wheat.When surpassing the critical value,the yield declined.When nitrogen fertilization amount was 195 kg/hm^2,and supplemental irrigation amount was 70% of field moisture capacity(569.4 m^3/hm^2),the highest yield 8500 kg/hm^2 could be obtained.(iii) During mature period of winter wheat,nitrogen accumulation amount of plant treated by nitrogen was significantly higher than that not treated by nitrogen(P <0.05).But under the treatments of W_2 and W3,nitrogen accumulation amount in N_(255) significantly declined when compared with N_(195)(P <0.05).Especially under W3(873.45 m^3/hm^2) level,nitrogen accumulation amount in N_(255) was even lower than N_0.Under the treatments of N_0 and N_(195),nitrogen accumulation amount of plant significantly increased with supplemental irrigation increased(P < 0.05).But under N_(255) treatment,there was not significant difference(P > 0.05).It illustrated that moderate supplemental irrigation and nitrogen fertilization could improve nitrogen absorption ability of winter wheat,but excessive supplemental irrigation and nitrogen fertilization were not favorable for plant's nitrogen absorption.(iv) Although the increase of supplemental irrigation during jointing period improved nitrogen absorption ability of winter wheat and promoted winter wheat absorbing more nitrogen,it inhibited nitrogen transferring and distributing to seed.Comprehensively considering growth condition of winter wheat and nitrogen risk condition,it is suggested that nitrogen application amount was 195 kg/hm^2,and supplemental irrigation reached 70% of field moisture capacity(569.4 m^3/hm^2),which could be as the suitable water and fertilizer use amounts in the region.展开更多
The combined effects of straw incorporation(SI)and polymer-coated urea(PCU)application on soil ammonia(NH_(3))and nitrous oxide(N_(2)O)emissions from agricultural fields have not been comprehensively evaluated in Nort...The combined effects of straw incorporation(SI)and polymer-coated urea(PCU)application on soil ammonia(NH_(3))and nitrous oxide(N_(2)O)emissions from agricultural fields have not been comprehensively evaluated in Northwest China.We conducted a two-year field experiment to assess the effects of combining SI with either uncoated urea(U)or PCU on soil NH_(3)emissions,N_(2)O emissions,winter wheat yields,yield-scaled NH_(3)(/NH_(3)),and yield-scaled N_(2)O(/N_(2)O).Five treatments were investigated,no nitrogen(N)fertilizer(N_(0)),U application at 150 kg N ha-1 with and without SI(SI+U and S_(0)+U),and PCU application at 150 kg N ha^(-1) with and without SI(SI+PCU and S_(0)+PCU).The results showed that the NH_(3);emissions increased by 20.98-34.35%following Sl compared to straw removal,mainly due to increases in soil ammonium(NH_(4)^(+)-N)content and water-flled pore space(WFPS).SI resulted in higher N_(2)O emissions than under the So scenario by 13.31-49.23%due to increases in soil inorganic N(SIN)contents,WFPS,and soil microbial biomass.In contrast,the PCU application reduced the SIN contents compared to the U application,reducing the NH_(3)and N_(2)O emissions by 45.99-58.07 and 18.08-53.04%,respectively.Moreover,no significant positive effects of the SI or PCU applications on the winter wheat yield were observed.The lowest /NH_(3) and /N_(2)O values were observed under the S_(0)+PCU and SI+PCU treatments.Our results suggest that single PCU applications and their combination with straw are the optimal agricultural strategies for mitigating gaseous N emissions and maintaining optimal winter wheat yields in Northwest China.展开更多
Excessive nitrogen (N) fertilizer application to winter wheat is a common problem on the North China Plain. To determine the optimum fertilizer N rate for winter wheat production while minimizing N losses, field exper...Excessive nitrogen (N) fertilizer application to winter wheat is a common problem on the North China Plain. To determine the optimum fertilizer N rate for winter wheat production while minimizing N losses, field experiments were conducted for two growing seasons at eight sites, in Huimin County, Shandong Province, from 2001 to 2003. The optimum N rate for maximum grain yield was inversely related to the initial soil mineral N content (Nmin) in the top 90 cm of the soil profile before sowing. There was no yield response to the applied N at the three sites with high initial soil mineral N levels (average 212 kg N ha-1). The average optimum N rate was 96 kg N ha-1 for the five sites with low initial soil Nmin (average 155 kg N ha-1) before sowing. Residual nitrate N in the top 90 cm of the soil profile after harvest increased with increasing fertilizer N application rate. The apparent N losses during the wheat-growing season also increased with increasing N application rate. The average apparent N losses with the optimum N rates were less than 15 kg N ha-1, whereas the farmers' conventional N application rate resulted in losses of more than 100 kg N ha-1. Therefore, optimizing N use for winter wheat considerably reduced N losses to the environment without compromising crop yields.展开更多
In order to promote the winter wheat yield and guarantee seeding quality in double-cropping system,no-tillage or reduced tillage planting modes with different row spacing have been implemented to result in different l...In order to promote the winter wheat yield and guarantee seeding quality in double-cropping system,no-tillage or reduced tillage planting modes with different row spacing have been implemented to result in different levels of yield.A three-year(2012-2015)field experiment was conducted on the experimental farm at Zhuozhou of Hebei Province in North China Plain to compare winter wheat yield from the two planting modes:wide-narrow row space planting mode(WN)and uniform row space planting mode(UR)Both planting modes were performed under reduced tillage conditions with straw mulching.The results showed that in North China Plain WN had positive impacts on crop yield,yield components,leaf area index(LAI)and intercepted photosynthetically active radiation(IPAR)index.Comparing with the UR,IPAR and LAI index for WN were enhanced by 4.8%and 5.2%,respectively.The average yield for WN was 7.2%,significantly greater than that of UR under the same quantity and density.In addition,for WN mode,machinery could pass through with less blocking under large amount of straw mulching,which largely improved tillage efficiency and potentially popularized the conservation tillage technology in North China plain.It is therefore recommended that wide-narrow row space planting mode(WN)combined with reduced tillage and straw mulching be more suitable for conservation tillage in double-cropping pattern areas in North China Plain.展开更多
North China is one of the main regions of irrigated winter wheat production in China. Climate warming is apparent in this region, especially during the growing season of winter wheat. To understand how the yield of ir...North China is one of the main regions of irrigated winter wheat production in China. Climate warming is apparent in this region, especially during the growing season of winter wheat. To understand how the yield of irrigated winter wheat in North China might be affected by climate warming and CO2 concentration enrichment in future, a set of manipulative field experiments was conducted in a site in the North China Plain under increased temperature and elevated CO2 concentration by using open top chambers and infrared radiator heaters. The results indicated that an average temperature increase of 1.7℃ in the growing season with CO2 concentration of 560 μmol mol-1 did not reduce the yield of irrigated winter wheat. The thousand- kernel weight of winter wheat did not change significantly despite improvement in the filling rate, because the increased temperature shortened the duration of grain filling. The number of effective panicles and the grain number per ear of winter wheat did not show significant changes. There was a large increase in the shoot biomass because of the increase in stem number and plant height. Consequently, under the prescribed scenario of asymmetric temperature increases and elevated CO2 concentration, the yield of irrigated winter wheat in North China is not likely to change significantly, but the harvest index of winter wheat is likely to be greatly reduced.展开更多
Agricultural drought threatens food security.Numerous remote-sensing drought indices have been developed,but their different principles,assumptions and physical quantities make it necessary to compare their suitabilit...Agricultural drought threatens food security.Numerous remote-sensing drought indices have been developed,but their different principles,assumptions and physical quantities make it necessary to compare their suitability for drought monitoring over large areas.Here,we analyzed the performance of three typical remote sensing-based drought indices for monitoring agricultural drought in two major agricultural production regions in Shaanxi and Henan provinces,northern China(predominantly rain-fed and irrigated agriculture,respectively):vegetation health index(VHI),temperature vegetation dryness index(TVDI)and drought severity index(DSI).We compared the agreement between these indices and the standardized precipitation index(SPI),soil moisture,winter wheat yield and National Meteorological Drought Monitoring(NMDM)maps.On average,DSI outperformed the other indices,with stronger correlations with SPI and soil moisture.DSI also corresponded better with soil moisture and NMDM maps.The jointing and grain-filling stages of winter wheat are more sensitive to water stress,indicating that winter wheat required more water during these stages.Moreover,the correlations between the drought indices and SPI,soil moisture,and winter wheat yield were generally stronger in Shaanxi province than in Henan province,suggesting that remote-sensing drought indices provide more accurate predictions of the impacts of drought in predominantly rain-fed agricultural areas.展开更多
<div style="text-align:justify;"> The fitting of water requirement and yield during the growth period of winter wheat can improve yield effectively and improve irrigation water use efficiency with a ce...<div style="text-align:justify;"> The fitting of water requirement and yield during the growth period of winter wheat can improve yield effectively and improve irrigation water use efficiency with a certain amount of resource input. This paper selects the irrigation amount, precipitation and yield of winter wheat at the Wuqiao Scientific Observation and Experimental Station. Fitting the water requirement and yield of winter wheat based on three types of artificial neural networks. This paper uses support vector machine (SVM), thought evolution algorithm to optimize BP neural network (MAE-BP) and generalized regression neural network (GRNN) to fit the water requirement and yield of two crops. The SVM is the model with the highest fitting accuracy among the three models, the RMSE, MAE, NS and R2 between predictive value and true value are 7.45 kg/hectares, 213.64 kg/hectares, 0.8086, 0.9409 respectively. </div>展开更多
Crop simulation models provide alternative, less time-consuming, and cost-effective means of deter- mining the sensitivity of crop yield to climate change. In this study, two dynamic mechanistic models, CERES （Crop E...Crop simulation models provide alternative, less time-consuming, and cost-effective means of deter- mining the sensitivity of crop yield to climate change. In this study, two dynamic mechanistic models, CERES （Crop Environment Resource Synthesis） and APSIM （Agricultural Production Systems Simulator）, were used to simulate the yield of wheat （Triticum aestivum L.） under well irrigated （CFG） and rain-fed （YY） conditions in relation to different climate variables in the North China Plain （NCP）. The study tested winter wheat yield sensitivity to different levels of temperature, radiation, precipitation, and atmospheric carbon dioxide （COa） concentration under CFG and YY conditions at Luancheng Agro-ecosystem Experimental Stations in the NCR The results from the CERES and APSIM wheat crop models were largely consistent and suggested that changes in climate variables influenced wheat grain yield in the NCR There was also significant variation in the sensitivity of winter wheat yield to climate variables under different water （CFG and YY） conditions. While a temperature increase of 2℃ was the threshold beyond which temperature negatively influenced wheat yield under CFG, a temperature rise exceeding 1℃ decreased winter wheat grain yield under YY. A decrease in solar radiation decreased wheat grain yield under both CFG and YY conditions. Although the sensitivity of winter wheat yield to precipitation was small under the CFG, yield decreased significantly with decreasing precipitation under the rain- fed YY treatment. The results also suggest that wheat yield under CFG linearly increased by ≈ 3.5% per 60 ppm （parts per million） increase in CO2 concentration from 380 to560ppm, and yield under YY increased linearly by ≈ 7.0% for the same increase in CO2 concentration.展开更多
Water shortage has threatened sustainable development of agriculture globally as well as in the North China Plain（NCP）.Irrigation,as the most effective way to increase food production in dry land,may not be readily ...Water shortage has threatened sustainable development of agriculture globally as well as in the North China Plain（NCP）.Irrigation,as the most effective way to increase food production in dry land,may not be readily available in the situation of drought.One of the alternatives is to supply plants with enough nutrients so that they can be more sustainable to the water stress.The objective of this study was to explore effects of irrigation and sulphur（S）application on water consumption,dry matter accumulation（DMA）,and grain yield of winter wheat in NCP.Three irrigation regimes including no irrigation（rainfed,I0）during the whole growth period,once irrigation only at jointing stage（90 mm,I1）,and twice respective irrigation at jointing and anthesis stages（90 mm plus 90 mm,I2）,and two levels of S application including 0S0and 60 kg ha^–1（S60）were designed in the field experiment in NCP.Results showed that increasing irrigation times significantly increased mean grain yield of wheat by 12.5–23.7%and nitrogen partial factor productivity（NPFP）by 21.2–45.0%in two wheat seasons,but markedly decreased crop water use efficiency（YWUE）.Furthermore,S supply 60 kg ha^–1 significantly increased mean grain yield,YWUE,IWUE and NPFP by 5.6,6.1,23.2,and 5.6%（across two wheat seasons）,respectively.However,we also found that role of soil moisture prior to S application was one of important greater factors on improving the absorption and utilization of storage water and nutrients of soil.Thus,water supply is still the most important factor to restrict the growth of wheat in the present case of NCP,supplying 60 kg ha^–1 S with once irrigation 90 mm at the jointing stage is a relatively appropriate recommended combination to improve grain yield and WUE of wheat when saving water resources is be considered in irrigated wheat farmlands of NCP.展开更多
An understanding of wheat yield and yield stability response to fertilization is important for sustainable wheat production. A 36-year long-term fertilization experiment was employed to evaluate the yield and yield st...An understanding of wheat yield and yield stability response to fertilization is important for sustainable wheat production. A 36-year long-term fertilization experiment was employed to evaluate the yield and yield stability of winter wheat. Five fertilization regimes were compared,including(1) CK, no fertilizer;(2) NPK, inorganic fertilizer only;(3) O, organic fertilizer only;(4)NPKO, 50% of NPK plus 50% of O, and(5) HNPKO, 80% of NPK plus 80% of O. The greatest yield increase was recorded in HNPKO, followed by NPKO, with O producing the lowest mean yield increase. Over the 36 years, the rate of wheat yield increase in fertilized plots ranged from95.31 kg ha-1 year-1 in the HNPKO to 138.65 kg ha-1 year-1 in the O. Yield stability analysis using the additive main effects and multiplicative interactions(AMMI) method assigned 62.3%, 26.3%,and 11.4% of sums of squares to fertilization effect, environmental effect, and fertilization ×environment interaction effect, respectively. The combination of inorganic and organic fertilization(NPKO and HNPKO) appeared to produce more stable yields than O or NPK, with lower coefficients of variation and AMMI stability value. However, wheat grown with O seemed to be the most susceptible to climate change and the least productive among the fertilized plots.Significant correlations of grain yield with soil properties and with mean air temperature were observed. These findings suggest that inorganic + organic fertilizer can increase wheat yield and its stability by improvement in soil fertility and reduction in variability to climate change.展开更多
Remote sensing can provide near real-time and dynamic monitoring of drought. The drought severity index(DSI), based on the normalized difference vegetation index(NDVI) and evapotranspiration/potential evapotranspirati...Remote sensing can provide near real-time and dynamic monitoring of drought. The drought severity index(DSI), based on the normalized difference vegetation index(NDVI) and evapotranspiration/potential evapotranspiration(ET/PET), has been used for drought monitoring. This study examined the relationship between the DSI and winter wheat yield for prefecture-level cities in five provinces of eastern China during 2001–2016. We first analyzed the spatial and temporal distribution of droughts in the study area. Then the correlation coefficient between drought-affected area and detrended yield of winter wheat was quantified and the impact of droughts of different intensities on winter wheat yield during different growth stages was investigated. The results show that incipient drought during the wintering period has no significant impact on the yield of winter wheat, while moderate drought in the same period can reduce yield. Drought affects winter wheat yield significantly during the flowering and filling stages. Droughts of higher intensity have more significant negative effects on the yield of winter wheat. Monitoring of droughts and irrigation is critical during these periods to ensure normal yield of winter wheat. This study has important practical implications for the planning of irrigation and food security.展开更多
Zinc（Zn） is an important essential microelement for wheat.In order to study the characteristics of Zn absorption,accumulation and distribution in highly-yielding winter wheat（with a grain yield of 9 000 kg ha-1）,f...Zinc（Zn） is an important essential microelement for wheat.In order to study the characteristics of Zn absorption,accumulation and distribution in highly-yielding winter wheat（with a grain yield of 9 000 kg ha-1）,field experiments were conducted in Gaocheng County of Hebei Province,China.Four winter wheat cultivars,i.e.,Shimai 14,Jifeng 703,Shimai 12,and Shixin 828,and four cultivars,i.e.,Temai 1,Shimai 12,Shixin 531,and Shixin 828,were used in the experiment,during 2004-2005 and 2005-2006,respectively.Plant samples were taken from the plots at each growing stage for Zn concentration analysis.The main results showed that the concentration of Zn in various above-ground organs of wheat was 9.5-112.5 mg kg-1 at different growing stages.The organ with the highest Zn concentration differed with the change of growth center at different growing stages.Accumulation of Zn in leaf blades was the highest among all the organs during early growing period,and more than 50% of the Zn accumulation was distributed to leaf blades before jointing,and higher than that to other organs.In late growing period,however,the accumulation of Zn in grains was the highest,and 58.1% of the Zn accumulation was distributed in grains at maturity.The total accumulation of Zn in wheat plant during its life span ranged from 384.9 to 475.9 g ha-1.The amount of Zn required for the formation of 100 kg grain yield ranged from 4.3 to 5.2 g.All the organs were ordered in such a sequence that leaf blades 〉 spikes 〉 leaf sheaths 〉 stems according to their net absorption and transportation of Zn as well as their contribution to Zn accumulation in grains.58.2-60.3% of the Zn accumulated in grains was redistributed from other organs,mostly from leaf blades.Concentration and accumulation of Zn in all the organs of wheat was high during early and middle growing periods,while accumulation of Zn in grains during late growing period mainly depended on the redistribution from other organs.According to these characteristics of Zn absorption and accumulation,Zn should be applied as seed dressing or basal fertilizer,so as to accelerate the early growth and Zn absorption of wheat.展开更多
基金supported by the National Natural Science Foundation of China(42101382 and 42201407)the Shandong Provincial Natural Science Foundation China(ZR2020QD016 and ZR2022QD120)。
文摘The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat yield.However,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale.Time-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter wheat.In this study,Fr equations were fitted for each organ of winter wheat using site-scale data.These equations were then coupled into a process-based and remote sensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),respectively.The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.
基金Under the auspices of National Natural Science Foundation of China(No.52079103)。
文摘Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies.However,crop yield is influenced by multiple factors within complex growth environments.Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat.Therefore,there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield,making precise yield prediction increasingly important.This study was based on four type of indicators including meteorological,crop growth status,environmental,and drought index,from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield.Using the sparrow search al-gorithm combined with random forest(SSA-RF)under different input indicators,accuracy of winter wheat yield estimation was calcu-lated.The estimation accuracy of SSA-RF was compared with partial least squares regression(PLSR),extreme gradient boosting(XG-Boost),and random forest(RF)models.Finally,the determined optimal yield estimation method was used to predict winter wheat yield in three typical years.Following are the findings:1)the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms.The best yield estimation method is achieved by four types indicators’composition with SSA-RF)(R^(2)=0.805,RRMSE=9.9%.2)Crops growth status and environmental indicators play significant roles in wheat yield estimation,accounting for 46%and 22%of the yield importance among all indicators,respectively.3)Selecting indicators from October to April of the follow-ing year yielded the highest accuracy in winter wheat yield estimation,with an R^(2)of 0.826 and an RMSE of 9.0%.Yield estimates can be completed two months before the winter wheat harvest in June.4)The predicted performance will be slightly affected by severe drought.Compared with severe drought year(2011)(R^(2)=0.680)and normal year(2017)(R^(2)=0.790),the SSA-RF model has higher prediction accuracy for wet year(2018)(R^(2)=0.820).This study could provide an innovative approach for remote sensing estimation of winter wheat yield.yield.
基金supported by the National Natural Science Foundation of China(42101382 and 41901342)the Shandong Provincial Natural Science Foundation(ZR2020QD016)the National Key Research and Development Program of China(2016YFD0300101).
文摘Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.Thus,we proposed a new approach to approximating irrigations of winter wheat over the North China Plain(NCP),where irrigation occurs extensively during the winter wheat growing season.This approach used irrigation pattern parameters(IPPs)to define the irrigation frequency and timing.Then,they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat(PRYM–Wheat),to improve the regional estimates of winter wheat over the NCP.The IPPs were determined using statistical yield data of reference years(2010–2015)over the NCP.Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield,with an increase and decrease in the correlation coefficient(R)and root mean square error(RMSE)of 0.15(about 37%)and 0.90 t ha–1(about 41%),respectively.The data in validation years(2001–2009 and 2016–2019)were used to validate PRYM–Wheat.In addition,our findings also showed R(RMSE)of 0.80(0.62 t ha–1)on a site level,0.61(0.91 t ha–1)for Hebei Province on a county level,0.73(0.97 t ha–1)for Henan Province on a county level,and 0.55(0.75 t ha–1)for Shandong Province on a city level.Overall,PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years,providing a scientific basis for ensuring regional food security.
基金Supported by the National Natural Science Foundation of China(41205126)the Discipline Construction and Macroscopic Agricultural Research Project of Anhui Academy of Agricultural Sciences(13A1424)+2 种基金the Fund for Youth Innovation of Anhui Academy of Agricultural Sciences(14B1460)the Innovative Research Team for Agricultural Disaster Risk Analysis in Anhui ProvinceAnhui Academy of Agricultural Sciences(14C1409)~~
文摘The establishment of crop yield estimating model based on microwave and optical satellite images can conduct the mutual verification of the accuracy of the reported crop yield and the precision of the estimating model. With Shou County and Huaiyuan County of Anhui Province as the experimental fields of winter wheat producing areas, the linear winter wheat yield estimating models were established by adopting backscattering coefficient and Normalized Difference Vegetation Index（NDVI） based on images from the synthetic aperture radar（SAR）—RDARSAT-2 and HJ satellite photographed in mid-April and early May, 2014, and then comparisons were conducted on the accuracy of the yield estimating models. The accuracies of the yield estimating models established using co-polarized（HH） and cross-polarized（HV） modes of SAR in Jiangou Town, Shou County were 68.37% and 74.01%, respectively, while the accuracies in Longkang Town, Huaiyuan County were 63.10%and 69.10%, respectively. Accuracies of yield estimating models established by HJ satellite data were 69.52% and 66.43% in Shou County and Huaiyuan County, respectively. Accuracies of winter yield estimating model based on HJ satellite data and that based on SAR were closed, and the yield difference of winter wheat in the lodging region was analyzed in detail. The model results laid the foundation and accumulated experience for the verification, parameters correction and promotion of the winter wheat yield estimating model.
基金supported by the National Natural Science Foundation of China (41401491,41371396,41301457,41471364)the Introduction of International Advanced Agricultural Science and Technology,Ministry of Agriculture,China (948 Program,2016-X38)+1 种基金the Agricultural Scientific Research Fund of Outstanding Talentsthe Open Fund for the Key Laboratory of Agri-informatics,Ministry of Agriculture,China (2013009)
文摘To accurately estimate winter wheat yields and analyze the uncertainty in crop model data assimilations, winter wheat yield estimates were obtained by assimilating measured or remotely sensed leaf area index （LAI） values. The performances of the calibrated crop environment resource synthesis for wheat （CERES-Wheat） model for two different assimilation scenarios were compared by employing ensemble Kalman filter （EnKF）-based strategies. The uncertainty factors of the crop model data assimilation was analyzed by considering the observation errors, assimilation stages and temporal-spatial scales. Overalll the results indicated a better yield estimate performance when the EnKF-based strategy was used to comprehen- sively consider several factors in the initial conditions and observations. When using this strategy, an adjusted coefficients of determination （R2） of 0.84, a root mean square error （RMSE） of 323 kg ha-1, and a relative errors （RE） of 4.15% were obtained at the field plot scale and an R2 of 0.81, an RMSE of 362 kg ha-1, and an RE of 4.52% were obtained at the pixel scale of 30 mx30 m. With increasing observation errors, the accuracy of the yield estimates obviously decreased, but an acceptable estimate was observed when the observation errors were within 20%. Winter wheat yield estimates could be improved significantly by assimilating observations from the middle to the end of the crop growing seasons. With decreasing assimilation frequency and pixel resolution, the accuracy of the crop yield estimates decreased; however, the computation time decreased. It is important to consider reasonable temporal-spatial scales and assimilation stages to obtain tradeoffs between accuracy and computation time, especially in operational systems used for regional crop yield estimates.
基金supported by Feng Yun Research Plan (FYAPP-2021.0301)National Key Research and Development Program of China (2019YFC1510205)National Natural Science Foundation of China (42075193)。
文摘Accurate estimation of regional-scale crop yield under drought conditions allows farmers and agricultural agencies to make well-informed decisions and guide agronomic management. However, few studies have focused on using the crop model data assimilation(CMDA) method for regional-scale winter wheat yield estimation under drought stress and partial-irrigation conditions. In this study, we developed a CMDA framework to integrate remotely sensed water stress factor(MOD16 ET PET) with the WOFOST model using an ensemble Kalman filter(En KF) for winter wheat yield estimation at the regional scale in the North China Plain(NCP) during 2008–2018. According to our results, integration of MOD16 ET PETwith the WOFOST model produced more accurate estimates of regional winter wheat yield than open-loop simulation. The correlation coefficient of simulated yield with statistical yield increased for each year and error decreased in most years, with r ranging from 0.28 to 0.65 and RMSE ranging from 700.08 to1966.12 kg ha. Yield estimation using the CMDA method was more suitable in drought years(r = 0.47, RMSE = 919.04 kg ha) than in normal years(r = 0.30, RMSE = 1215.51 kg ha). Our approach performed better in yield estimation under drought conditions than the conventional empirical correlation method using vegetation condition index(VCI). This research highlighted the potential of assimilating remotely sensed water stress factor, which can account for irrigation benefit, into crop model for improving the accuracy of winter wheat yield estimation at the regional scale especially under drought conditions, and this approach can be easily adapted to other regions and crops.
基金supported by the earmarked fund for China Agriculture Research System (CARS-0301-24)the National Natural Science Foundation of China (31771727)+5 种基金the National Key Technology R&D Program of China (2015BAD23B04-2)The research project was also supported by the Shanxi Scholarship Council,China (2015Key 4)the Shanxi Science and Technology Innovation Team Project,China (201605D131041)the Jinzhong Science and Technology Plan Project,China (Y172007-2)the Sanjin Scholar Support Special Funds,Chinathe Special Fund for Agro-scientific Research in the Public Interest,China (201503120)
文摘Sowing date and seeding rate are critical for productivity of winter wheat(Triticum aestivum L.).A three-year field experiment was conducted with three sowing dates(20 September(SD1),1 October(SD2),and 10 October(SD3)) and three seeding rates(SR67.5,SR90,and SR112.5) to determine suitable sowing date and seeding rate for high wheat yield.A large seasonal variation in accumulated temperature from sowing to winter dormancy was observed among three growing seasons.Suitable sowing dates for strong seedlings before winter varied with the seasons,that was SD2 in 2012–2013,SD3 in 2013–2014,and SD2 as well as SD1 in 2014–2015.Seasonal variation in precipitation during summer fallow also had substantial effects on soil water storage,and consequently influenced grain yield through soil water consumption from winter dormancy to maturity stages.Lower consumption of soil water from winter dormancy to booting stages could make more water available for productive growth from anthesis to maturity stages,leading to higher grain yield.SD2 combined with SR90 had the lowest soil water consumption from winter dormancy to booting stages in 2012–2013 and 2014–2015; while in 2013–2014,it was close to that with SR67.5 or SR112.5.For productive growth from anthesis to maturity stages,SD2 with SR90 had the highest soil water consumption in all three seasons.The highest water consumption in the productive growth period resulted in the best grain yield in both low and high rainfall years.Ear number largely contributed to the seasonal variation in grain yield,while grain number per ear and 1 000-grain weight also contributed to grain yield,especially when soil water storage was high.Our results indicate that sowing date and seeding rate affect grain yield through seedling development before winter and also affect soil water consumption in different growth periods.By selecting the suitable sowing date(1 October) in combination with the proper seeding rate of 90 kg ha–1,the best yield was achieved.Based on these results,we recommend that the current sowing date be delayed from 22 or 23 September to 1 October.
文摘This paper presents the applications of Landsat Thematic Mapper (TM) data and Advanced Very High Resolution Radiometer (AVHRR) time series data for winter wheat production estimation in North China Plain. The keytechniques are described systematically about winter wheat yield estimation system, including automatically extractingwheat area, simulating and monitoring wheat growth situation, building wheat unit yield model of large area and forecasting wheat production. Pattern recognition technique was applied to extract sown area using TM data. Temporal NDVI(Normal Division Vegetation Index) profiles were produced from 8 - 12 times AVHRR data during wheat growth dynamically. A remote sensing yield model for large area was developed based on greenness accumulation, temperature andgreenness change rate. On the basis of the solution of key problems, an operational system for winter wheat yield estimation in North China Plain using remotely sensed data was established and has operated since 1993, which consists of 4 subsystems, namely databases management, image processing, models bank management and production prediction system.The accuracy of wheat production prediction exceeded 96 per cent compared with on the spot measurement.
基金Supported by National Key Research Plan Project(2016YFD0801001,2016YFD0200103,2017YFD0800500)
文摘Based on split plot design method of field test,the impacts of supplemental irrigation based on soil moisture measurement and nitrogen use on winter wheat yield and nitrogen absorption and distribution were studied.Supplemental irrigation had three levels: 60%(W_1),70%(W_2) and 80%(W3) of the targeted relative water content at 0-40 cm of soil layer during jointing period of winter wheat.Nitrogen fertilization had three levels: not using nitrogen(N_0),using pure nitrogen of 195 kg/hm^2(N_(195)) and 255 kg/hm^2(N_(255)).Results showed that:(i)different supplemental irrigation and nitrogen fertilization significantly affected plant height and leaf area of winter wheat during key growth period.Under the same supplemental irrigation treatment,both plant height and leaf area of winter wheat showed as N_(255)> N_(195)> N_0(P <0.05).Plant height in N_(195) and N_(255)treatments was significantly higher than that in N_0 treatment,but there was not significant difference between N_(195) and N_(255)(P >0.05).Under the same nitrogen fertilization,plant height in W_2(569.4 m^3/hm^2) and W3(873.45 m^3/hm^2) treatments was significant higher than that in W_1(265.2 m^3/hm^2),but there was not significant difference between W_2 and W3(P >0.05).It illustrated that excessive nitrogen fertilization and supplemental irrigation did not significantly affect plant height and leaf area of winter wheat.(ii) Under the same nitrogen fertilization level,yield increase effect of winter wheat by supplemental irrigation showed a declining trend with nitrogen application amount increased.It illustrated that nitrogen fertilization and supplemental irrigation had certain critical values on the yield of winter wheat.When surpassing the critical value,the yield declined.When nitrogen fertilization amount was 195 kg/hm^2,and supplemental irrigation amount was 70% of field moisture capacity(569.4 m^3/hm^2),the highest yield 8500 kg/hm^2 could be obtained.(iii) During mature period of winter wheat,nitrogen accumulation amount of plant treated by nitrogen was significantly higher than that not treated by nitrogen(P <0.05).But under the treatments of W_2 and W3,nitrogen accumulation amount in N_(255) significantly declined when compared with N_(195)(P <0.05).Especially under W3(873.45 m^3/hm^2) level,nitrogen accumulation amount in N_(255) was even lower than N_0.Under the treatments of N_0 and N_(195),nitrogen accumulation amount of plant significantly increased with supplemental irrigation increased(P < 0.05).But under N_(255) treatment,there was not significant difference(P > 0.05).It illustrated that moderate supplemental irrigation and nitrogen fertilization could improve nitrogen absorption ability of winter wheat,but excessive supplemental irrigation and nitrogen fertilization were not favorable for plant's nitrogen absorption.(iv) Although the increase of supplemental irrigation during jointing period improved nitrogen absorption ability of winter wheat and promoted winter wheat absorbing more nitrogen,it inhibited nitrogen transferring and distributing to seed.Comprehensively considering growth condition of winter wheat and nitrogen risk condition,it is suggested that nitrogen application amount was 195 kg/hm^2,and supplemental irrigation reached 70% of field moisture capacity(569.4 m^3/hm^2),which could be as the suitable water and fertilizer use amounts in the region.
基金This work was supported by the National Key R&D Program of China(2021YFD1900700)the National Natural Science Foundation of China(52179046).
文摘The combined effects of straw incorporation(SI)and polymer-coated urea(PCU)application on soil ammonia(NH_(3))and nitrous oxide(N_(2)O)emissions from agricultural fields have not been comprehensively evaluated in Northwest China.We conducted a two-year field experiment to assess the effects of combining SI with either uncoated urea(U)or PCU on soil NH_(3)emissions,N_(2)O emissions,winter wheat yields,yield-scaled NH_(3)(/NH_(3)),and yield-scaled N_(2)O(/N_(2)O).Five treatments were investigated,no nitrogen(N)fertilizer(N_(0)),U application at 150 kg N ha-1 with and without SI(SI+U and S_(0)+U),and PCU application at 150 kg N ha^(-1) with and without SI(SI+PCU and S_(0)+PCU).The results showed that the NH_(3);emissions increased by 20.98-34.35%following Sl compared to straw removal,mainly due to increases in soil ammonium(NH_(4)^(+)-N)content and water-flled pore space(WFPS).SI resulted in higher N_(2)O emissions than under the So scenario by 13.31-49.23%due to increases in soil inorganic N(SIN)contents,WFPS,and soil microbial biomass.In contrast,the PCU application reduced the SIN contents compared to the U application,reducing the NH_(3)and N_(2)O emissions by 45.99-58.07 and 18.08-53.04%,respectively.Moreover,no significant positive effects of the SI or PCU applications on the winter wheat yield were observed.The lowest /NH_(3) and /N_(2)O values were observed under the S_(0)+PCU and SI+PCU treatments.Our results suggest that single PCU applications and their combination with straw are the optimal agricultural strategies for mitigating gaseous N emissions and maintaining optimal winter wheat yields in Northwest China.
基金Project supported by the National Natural Science Foundation of China (Nos. 30390084 and 30270772)the Natural Science Foundation of Beijing (No. 6010001)
文摘Excessive nitrogen (N) fertilizer application to winter wheat is a common problem on the North China Plain. To determine the optimum fertilizer N rate for winter wheat production while minimizing N losses, field experiments were conducted for two growing seasons at eight sites, in Huimin County, Shandong Province, from 2001 to 2003. The optimum N rate for maximum grain yield was inversely related to the initial soil mineral N content (Nmin) in the top 90 cm of the soil profile before sowing. There was no yield response to the applied N at the three sites with high initial soil mineral N levels (average 212 kg N ha-1). The average optimum N rate was 96 kg N ha-1 for the five sites with low initial soil Nmin (average 155 kg N ha-1) before sowing. Residual nitrate N in the top 90 cm of the soil profile after harvest increased with increasing fertilizer N application rate. The apparent N losses during the wheat-growing season also increased with increasing N application rate. The average apparent N losses with the optimum N rates were less than 15 kg N ha-1, whereas the farmers' conventional N application rate resulted in losses of more than 100 kg N ha-1. Therefore, optimizing N use for winter wheat considerably reduced N losses to the environment without compromising crop yields.
基金This study was financially supported by the Special Fund for Agro-scientific Research in the Public Interest from the Ministry of Agriculture,China(Grant No.201503136)Modern Agricultural Industry Technology System(Grant No.CARS-03)the Program for Changjiang Scholars and Innovative Research Team in University of China(Grant No.IRT13039).
文摘In order to promote the winter wheat yield and guarantee seeding quality in double-cropping system,no-tillage or reduced tillage planting modes with different row spacing have been implemented to result in different levels of yield.A three-year(2012-2015)field experiment was conducted on the experimental farm at Zhuozhou of Hebei Province in North China Plain to compare winter wheat yield from the two planting modes:wide-narrow row space planting mode(WN)and uniform row space planting mode(UR)Both planting modes were performed under reduced tillage conditions with straw mulching.The results showed that in North China Plain WN had positive impacts on crop yield,yield components,leaf area index(LAI)and intercepted photosynthetically active radiation(IPAR)index.Comparing with the UR,IPAR and LAI index for WN were enhanced by 4.8%and 5.2%,respectively.The average yield for WN was 7.2%,significantly greater than that of UR under the same quantity and density.In addition,for WN mode,machinery could pass through with less blocking under large amount of straw mulching,which largely improved tillage efficiency and potentially popularized the conservation tillage technology in North China plain.It is therefore recommended that wide-narrow row space planting mode(WN)combined with reduced tillage and straw mulching be more suitable for conservation tillage in double-cropping pattern areas in North China Plain.
基金Supported by the National Natural Science Foundation of China(41075085 and 41375118)National(Key)Basic Research and Development(973)Program of China(2010CB951303)
文摘North China is one of the main regions of irrigated winter wheat production in China. Climate warming is apparent in this region, especially during the growing season of winter wheat. To understand how the yield of irrigated winter wheat in North China might be affected by climate warming and CO2 concentration enrichment in future, a set of manipulative field experiments was conducted in a site in the North China Plain under increased temperature and elevated CO2 concentration by using open top chambers and infrared radiator heaters. The results indicated that an average temperature increase of 1.7℃ in the growing season with CO2 concentration of 560 μmol mol-1 did not reduce the yield of irrigated winter wheat. The thousand- kernel weight of winter wheat did not change significantly despite improvement in the filling rate, because the increased temperature shortened the duration of grain filling. The number of effective panicles and the grain number per ear of winter wheat did not show significant changes. There was a large increase in the shoot biomass because of the increase in stem number and plant height. Consequently, under the prescribed scenario of asymmetric temperature increases and elevated CO2 concentration, the yield of irrigated winter wheat in North China is not likely to change significantly, but the harvest index of winter wheat is likely to be greatly reduced.
基金This work was supported by National Natural Science Foundation of China:[grant numbers 41671418,41805090,61661136006]CMA/Henan Key Laboratory of Agrometeorological Support and Applied Technique:[grant numbers AMF201802,AMF201708]+1 种基金Science and Technology Facilities Council of UK–Newton Agritech Programme[Sentinles of Wheat]Foundation for Key Program of Beijing:[grant number D171100002317002].
文摘Agricultural drought threatens food security.Numerous remote-sensing drought indices have been developed,but their different principles,assumptions and physical quantities make it necessary to compare their suitability for drought monitoring over large areas.Here,we analyzed the performance of three typical remote sensing-based drought indices for monitoring agricultural drought in two major agricultural production regions in Shaanxi and Henan provinces,northern China(predominantly rain-fed and irrigated agriculture,respectively):vegetation health index(VHI),temperature vegetation dryness index(TVDI)and drought severity index(DSI).We compared the agreement between these indices and the standardized precipitation index(SPI),soil moisture,winter wheat yield and National Meteorological Drought Monitoring(NMDM)maps.On average,DSI outperformed the other indices,with stronger correlations with SPI and soil moisture.DSI also corresponded better with soil moisture and NMDM maps.The jointing and grain-filling stages of winter wheat are more sensitive to water stress,indicating that winter wheat required more water during these stages.Moreover,the correlations between the drought indices and SPI,soil moisture,and winter wheat yield were generally stronger in Shaanxi province than in Henan province,suggesting that remote-sensing drought indices provide more accurate predictions of the impacts of drought in predominantly rain-fed agricultural areas.
文摘<div style="text-align:justify;"> The fitting of water requirement and yield during the growth period of winter wheat can improve yield effectively and improve irrigation water use efficiency with a certain amount of resource input. This paper selects the irrigation amount, precipitation and yield of winter wheat at the Wuqiao Scientific Observation and Experimental Station. Fitting the water requirement and yield of winter wheat based on three types of artificial neural networks. This paper uses support vector machine (SVM), thought evolution algorithm to optimize BP neural network (MAE-BP) and generalized regression neural network (GRNN) to fit the water requirement and yield of two crops. The SVM is the model with the highest fitting accuracy among the three models, the RMSE, MAE, NS and R2 between predictive value and true value are 7.45 kg/hectares, 213.64 kg/hectares, 0.8086, 0.9409 respectively. </div>
基金This study was supported by the National Natural Science Foundation of China （Grant No. 41401104）, Natural Science Foundation of Hebei Province, China （D2015302017）, China Postdoctoral Science Foundation funded project （2015M570167）, and also supported by the Planning Subject of the ＂Twelfth five-year-plan＂ in National Science and Technology for the Rural Development in China （2013BAD11B03-2）, and Science and Technology Planning Project of Hebei Academy of Science （15101）. We are grateful to the editors and anonymous reviewers for their insightful inputs at the review phase of this work.
文摘Crop simulation models provide alternative, less time-consuming, and cost-effective means of deter- mining the sensitivity of crop yield to climate change. In this study, two dynamic mechanistic models, CERES （Crop Environment Resource Synthesis） and APSIM （Agricultural Production Systems Simulator）, were used to simulate the yield of wheat （Triticum aestivum L.） under well irrigated （CFG） and rain-fed （YY） conditions in relation to different climate variables in the North China Plain （NCP）. The study tested winter wheat yield sensitivity to different levels of temperature, radiation, precipitation, and atmospheric carbon dioxide （COa） concentration under CFG and YY conditions at Luancheng Agro-ecosystem Experimental Stations in the NCR The results from the CERES and APSIM wheat crop models were largely consistent and suggested that changes in climate variables influenced wheat grain yield in the NCR There was also significant variation in the sensitivity of winter wheat yield to climate variables under different water （CFG and YY） conditions. While a temperature increase of 2℃ was the threshold beyond which temperature negatively influenced wheat yield under CFG, a temperature rise exceeding 1℃ decreased winter wheat grain yield under YY. A decrease in solar radiation decreased wheat grain yield under both CFG and YY conditions. Although the sensitivity of winter wheat yield to precipitation was small under the CFG, yield decreased significantly with decreasing precipitation under the rain- fed YY treatment. The results also suggest that wheat yield under CFG linearly increased by ≈ 3.5% per 60 ppm （parts per million） increase in CO2 concentration from 380 to560ppm, and yield under YY increased linearly by ≈ 7.0% for the same increase in CO2 concentration.
基金supported by the National Natural Science Foundation of China (31272246)the National Key Technologies R&D Program of China during the 12th Five-Year Plan period (2013BAD07B00, 2011BAD16B07 and 2015BAD26B01)the Special Fund for Agroscientific Research in the Public Interest, China (201203096, 201203079 and 201203031)
文摘Water shortage has threatened sustainable development of agriculture globally as well as in the North China Plain（NCP）.Irrigation,as the most effective way to increase food production in dry land,may not be readily available in the situation of drought.One of the alternatives is to supply plants with enough nutrients so that they can be more sustainable to the water stress.The objective of this study was to explore effects of irrigation and sulphur（S）application on water consumption,dry matter accumulation（DMA）,and grain yield of winter wheat in NCP.Three irrigation regimes including no irrigation（rainfed,I0）during the whole growth period,once irrigation only at jointing stage（90 mm,I1）,and twice respective irrigation at jointing and anthesis stages（90 mm plus 90 mm,I2）,and two levels of S application including 0S0and 60 kg ha^–1（S60）were designed in the field experiment in NCP.Results showed that increasing irrigation times significantly increased mean grain yield of wheat by 12.5–23.7%and nitrogen partial factor productivity（NPFP）by 21.2–45.0%in two wheat seasons,but markedly decreased crop water use efficiency（YWUE）.Furthermore,S supply 60 kg ha^–1 significantly increased mean grain yield,YWUE,IWUE and NPFP by 5.6,6.1,23.2,and 5.6%（across two wheat seasons）,respectively.However,we also found that role of soil moisture prior to S application was one of important greater factors on improving the absorption and utilization of storage water and nutrients of soil.Thus,water supply is still the most important factor to restrict the growth of wheat in the present case of NCP,supplying 60 kg ha^–1 S with once irrigation 90 mm at the jointing stage is a relatively appropriate recommended combination to improve grain yield and WUE of wheat when saving water resources is be considered in irrigated wheat farmlands of NCP.
基金supported by the National Key Research and Development Program of China(2016YFD0300803)the Special Fund for Agro-scientific Research in the Public Interest(201503116-10)+1 种基金the Agricultural Science and Technology Innovation Program(CAAS-XTCX2016019-03 and Y2016XT01-03)the Science and Technology Major Project of Anhui Province(16030701099)
文摘An understanding of wheat yield and yield stability response to fertilization is important for sustainable wheat production. A 36-year long-term fertilization experiment was employed to evaluate the yield and yield stability of winter wheat. Five fertilization regimes were compared,including(1) CK, no fertilizer;(2) NPK, inorganic fertilizer only;(3) O, organic fertilizer only;(4)NPKO, 50% of NPK plus 50% of O, and(5) HNPKO, 80% of NPK plus 80% of O. The greatest yield increase was recorded in HNPKO, followed by NPKO, with O producing the lowest mean yield increase. Over the 36 years, the rate of wheat yield increase in fertilized plots ranged from95.31 kg ha-1 year-1 in the HNPKO to 138.65 kg ha-1 year-1 in the O. Yield stability analysis using the additive main effects and multiplicative interactions(AMMI) method assigned 62.3%, 26.3%,and 11.4% of sums of squares to fertilization effect, environmental effect, and fertilization ×environment interaction effect, respectively. The combination of inorganic and organic fertilization(NPKO and HNPKO) appeared to produce more stable yields than O or NPK, with lower coefficients of variation and AMMI stability value. However, wheat grown with O seemed to be the most susceptible to climate change and the least productive among the fertilized plots.Significant correlations of grain yield with soil properties and with mean air temperature were observed. These findings suggest that inorganic + organic fertilizer can increase wheat yield and its stability by improvement in soil fertility and reduction in variability to climate change.
文摘Remote sensing can provide near real-time and dynamic monitoring of drought. The drought severity index(DSI), based on the normalized difference vegetation index(NDVI) and evapotranspiration/potential evapotranspiration(ET/PET), has been used for drought monitoring. This study examined the relationship between the DSI and winter wheat yield for prefecture-level cities in five provinces of eastern China during 2001–2016. We first analyzed the spatial and temporal distribution of droughts in the study area. Then the correlation coefficient between drought-affected area and detrended yield of winter wheat was quantified and the impact of droughts of different intensities on winter wheat yield during different growth stages was investigated. The results show that incipient drought during the wintering period has no significant impact on the yield of winter wheat, while moderate drought in the same period can reduce yield. Drought affects winter wheat yield significantly during the flowering and filling stages. Droughts of higher intensity have more significant negative effects on the yield of winter wheat. Monitoring of droughts and irrigation is critical during these periods to ensure normal yield of winter wheat. This study has important practical implications for the planning of irrigation and food security.
基金supported by the Key Technologies R&D Program of China during the 11th Five-Year Plan period (2006BAD02A08)the Earmarked Fund for Modern Agro-Industry Technology Research System,China
文摘Zinc（Zn） is an important essential microelement for wheat.In order to study the characteristics of Zn absorption,accumulation and distribution in highly-yielding winter wheat（with a grain yield of 9 000 kg ha-1）,field experiments were conducted in Gaocheng County of Hebei Province,China.Four winter wheat cultivars,i.e.,Shimai 14,Jifeng 703,Shimai 12,and Shixin 828,and four cultivars,i.e.,Temai 1,Shimai 12,Shixin 531,and Shixin 828,were used in the experiment,during 2004-2005 and 2005-2006,respectively.Plant samples were taken from the plots at each growing stage for Zn concentration analysis.The main results showed that the concentration of Zn in various above-ground organs of wheat was 9.5-112.5 mg kg-1 at different growing stages.The organ with the highest Zn concentration differed with the change of growth center at different growing stages.Accumulation of Zn in leaf blades was the highest among all the organs during early growing period,and more than 50% of the Zn accumulation was distributed to leaf blades before jointing,and higher than that to other organs.In late growing period,however,the accumulation of Zn in grains was the highest,and 58.1% of the Zn accumulation was distributed in grains at maturity.The total accumulation of Zn in wheat plant during its life span ranged from 384.9 to 475.9 g ha-1.The amount of Zn required for the formation of 100 kg grain yield ranged from 4.3 to 5.2 g.All the organs were ordered in such a sequence that leaf blades 〉 spikes 〉 leaf sheaths 〉 stems according to their net absorption and transportation of Zn as well as their contribution to Zn accumulation in grains.58.2-60.3% of the Zn accumulated in grains was redistributed from other organs,mostly from leaf blades.Concentration and accumulation of Zn in all the organs of wheat was high during early and middle growing periods,while accumulation of Zn in grains during late growing period mainly depended on the redistribution from other organs.According to these characteristics of Zn absorption and accumulation,Zn should be applied as seed dressing or basal fertilizer,so as to accelerate the early growth and Zn absorption of wheat.
