Winter wheat yield improvement by genetic gain across different provinces in China

The replacement of winter wheat varieties has contributed significantly to yield improvement worldwide,with remarkable progress in China.Drawing on two sets of data,production yield from the National Bureau of Statistics of China and experimental yield from literature,this study aims to(1)illustrate the increasing patterns of production yield among different provinces from 1978 to 2018 in China,(2)explore the genetic gain in yield and yield relevant traits through the variety replacement based on experimental yield from 1937 to 2016 in China,and(3)compare the yield gap between experimental yield and production yield.The results show that both the production and experimental yields significantly increased along with the variety replacement.The national annual yield increase ratio for the production yield was 1.67%from 1978 to 2018,varying from 0.96%in Sichuan Province to 2.78%in Hebei Province;such ratio for the experimental yield was 1.13%from 1937 to 2016.The yield gap between experimental and production yields decreased from the 1970s to the 2010s.This study reveals significant increases in some yield components consequent to variety replacement,including thousand-grain weight,kernel number per spike,and grain number per square meter;however,no change is shown in spike number per square meter.The biomass and harvest index consistently and significantly increased,whereas the plant height decreased significantly.

Will the Globe Encounter the Warmest Winter after the Hottest Summer in 2023?

In the boreal summer and autumn of 2023,the globe experienced an extremely hot period across both oceans and continents.The consecutive record-breaking mean surface temperature has caused many to speculate upon how the global temperature will evolve in the coming 2023/24 boreal winter.In this report,as shown in the multi-model ensemble mean(MME)prediction released by the Institute of Atmospheric Physics at the Chinese Academy of Sciences,a medium-to-strong eastern Pacific El Niño event will reach its mature phase in the following 2−3 months,which tends to excite an anomalous anticyclone over the western North Pacific and the Pacific-North American teleconnection,thus serving to modulate the winter climate in East Asia and North America.Despite some uncertainty due to unpredictable internal atmospheric variability,the global mean surface temperature(GMST)in the 2023/24 winter will likely be the warmest in recorded history as a consequence of both the El Niño event and the long-term global warming trend.Specifically,the middle and low latitudes of Eurasia are expected to experience an anomalously warm winter,and the surface air temperature anomaly in China will likely exceed 2.4 standard deviations above climatology and subsequently be recorded as the warmest winter since 1991.Moreover,the necessary early warnings are still reliable in the timely updated mediumterm numerical weather forecasts and sub-seasonal-to-seasonal prediction.

The first factor affecting dryland winter wheat grain yield under various mulching measures: Spike number

Water is the key factor limiting dryland wheat grain yield.Mulching affects crop yield and yield components by affecting soil moisture.Further research is needed to determine the relationships between yield components and soil moisture with yield,and to identify the most important factor affecting grain yield under various mulching measures.A long-term 9-yearifeld experiment in the Loess Plateau of Northwest China was carried out with three treatments:no mulch (CK),plastic mulch (M_(P)) and straw mulch (M_(S)).Yield factors and soil moisture were measured,and the relationships between them were explored by correlation analysis,structural equation modeling and significance analysis.The results showed that compared with CK,the average grain yields of M_(P) and M_(S) increased by 13.0and 10.6%,respectively.The average annual grain yield of the M_(P) treatment was 134 kg ha^(–1) higher than the M_(S) treatment.There were no significant differences in yield components among the three treatments (P<0.05).Soil water storage of the M_(S) treatment was greater than the M_(P) treatment,although the differences were not statistically signifiant.Soil water storage during the summer fallow period (SWSSF) and soil water storage before sowing (SWSS) of M_(S) were significantly higher than in CK,which increased by 38.5 and 13.6%,respectively.The relationship between M_(P) and CK was not statistically significant for SWSSF,but the SWSS in M_(P) was significantly higher than in CK.In terms of soil water storage after harvest (SWSH) and water consumption in the growth period(ET),there were no signi?cant differences among the three treatments.Based on the three analysis methods,we found that spike number and ET were positively correlated with grain yield.However,the relative importance of spike number to yield was the greatest in the M_(P )and M_(S) treatments,while that of ET was the greatest in CK.Suifcient SWSSF could indirectly increase spike number and ET in the three treatments.Based on these results,mulch can improve yield and soil water storage.The most important factor affecting the grain yield of dryland wheat was spike number under mulching,and ET with CK.These findings may help us to understand the main factors influencing dryland wheat grain yield under mulching conditions compared to CK.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

创伤性冠状动脉血肿致de Winter综合征心电图动态演变1例

创伤性冠状动脉(冠脉)血肿临床罕见,de Winter综合征是一种特殊类型的急性冠脉综合征。本文报道新昌县人民医院诊治的创伤性冠脉血肿致de Winter综合征,且心电图呈动态演变1例,其冠脉病变经冠脉造影及血管内超声(IVUS)证实。

Different ENSO Impacts on Eastern China Precipitation Patterns in Early and Late Winter Associated with Seasonally-Varying Kuroshio Anticyclonic Anomalies

Winter precipitation over eastern China displays remarkable interannual variability,which has been suggested to be closely related to El Niño-Southern Oscillation(ENSO).This study finds that ENSO impacts on eastern China precipitation patterns exhibit obvious differences in early(November-December)and late(January-February)winter.In early winter,precipitation anomalies associated with ENSO are characterized by a monopole spatial distribution over eastern China.In contrast,the precipitation anomaly pattern in late winter remarkably changes,manifesting as a dipole spatial distribution.The noteworthy change in precipitation responses from early to late winter can be largely attributed to the seasonally varying Kuroshio anticyclonic anomalies.During the early winter of El Niño years,anticyclonic circulation anomalies appear both over the Philippine Sea and Kuroshio region,enhancing water vapor transport to the entirety of eastern China,thus contributing to more precipitation there.During the late winter of El Niño years,the anticyclone over the Philippine Sea is further strengthened,while the one over the Kuroshio dissipates,which could result in differing water vapor transport between northern and southern parts of eastern China and thus a dipole precipitation distribution.Roughly the opposite anomalies of circulation and precipitation are displayed during La Niña winters.Further analysis suggests that the seasonally-varying Kuroshio anticyclonic anomalies are possibly related to the enhancement of ENSO-related tropical central-eastern Pacific convection from early to late winter.These results have important implications for the seasonal-tointerannual predictability of winter precipitation over eastern China.

Wintertime ozone surges:The critical role of alkene ozonolysis

Ozone(O_(3))pollution is usually linked to warm weather and strong solar radiation,making it uncommon in cold winters.However,an unusual occurrence of four high O_(3)episode days(with maximum hourly concentrations exceeding 100 ppbv and peaking at 121 ppbv)was recorded in January 2018 in Lanzhou city,China.During these episodes,the average daytime concentration of total non-methane volatile organic compounds(TVOCs)reached 153.4±19.0 ppbv,with alkenes—largely emitted from the local petrochemical industry—comprising 82.3±13.1 ppbv.Here we show a photochemical box model coupled with a Master Chemical Mechanism to elucidate the mechanisms behind this unusual wintertime O_(3)pollution.We find that the typically low temperatures(−1.7±1.3°C)and weak solar radiation(263.6±60.7 W m^(-2))of those winter episode days had a minimal effect on the reactivity of VOCs with OH radicals.Instead,the ozonolysis of alkenes generated Criegee intermediates,which rapidly decomposed into substantial ROx radicals(OH,HO_(2),and RO_(2))without sunlight.This radical production led to the oxidation of VOCs,with alkene ozonolysis ultimately contributing to 89.6±8.7%of the O_(3)formation during these episodes.This mechanism did not activate at night due to the depletion of O_(3)by the NO titration effect.Furthermore,the findings indicate that a reduction of alkenes by 28.6%or NO_(x)by 27.7%in the early afternoon could significantly mitigate wintertime O_(3)pollution.Overall,this study unravels the unique mechanism of alkene-induced winter O_(3)pollution and offers a reference for winter O_(3)reduction strategies in the petrochemical industrial regions.

Geographical origin identification of winter jujube(Ziziphus jujuba Dongzao')by using multi-element fingerprinting with chemometrics

Winter jujube(Ziziphus jujuba'Dongzao')is greatly appreciated by consumers for its excellent quality,but brand infringement frequently occurs in the market.Here,we first determined a total of 38 elements in 167 winter jujube samples from the main winter jujube producing areas of China by inductively coupled plasma mass spectrometer(ICP-MS).As a result,16 elements(Mg,K,Mn,Cu,Zn,Mo,Ba,Be,As,Se,Cd,Sb,Ce,Er,Tl,and Pb)exhibited significant differences in samples from different producing areas.Supervised linear discriminant analysis(LDA)and orthogonal projection to latent structures discriminant analysis(OPLS-DA)showed better performance in identifying the origin of samples than unsupervised principal component analysis(PCA).LDA and OPLS-DA had a mean identification accuracy of 87.84 and 94.64%in the testing set,respectively.By using the multilayer perceptron(MLP)and C5.0,the prediction accuracy of the models could reach 96.36 and 91.06%,respectively.Based on the above four chemometric methods,Cd,Tl,Mo and Se were selected as the main variables and principal markers for the origin identification of winter jujube.Overall,this study demonstrates that it is practical and precise to identify the origin of winter jujube through multi-element fingerprint analysis with chemometrics,and may also provide reference for establishing the origin traceability system of other fruits.

Shallow sub-lakes are essential for sustaining the successful wintering of waterbirds in Poyang Lake,China

For migratory waterbirds,the quality of wintering habitat is related to spring migration and successful breeding in the next year.The availability of food resources in the habitat is critical and varies within water levels.Although the water-level fluctuations in Poyang Lake have been extremely variable interannually in recent years,the wintering waterbird populations have remained relatively stable.Hence,the mechanism of maintaining the stability is worth exploring.This study aimed to compare the distribution of vegetation and herbivorous wa-terbirds in 2015-2016 and 2016-2017,focusing on three shallow sub-lakes and one main lake are.The results showed that the emergence of tubers and the growth of Carex spp.provided a continuous food supply and habitat for wintering waterbirds with a gradual decline in the water level.Shallow sub-lakes supported almost all of the tuber-eating waterbirds(1.42-1.62×10^(5))and most geese(1.34-1.53×10^(6)).However,the main lake area,covered with Persicaria hydropiper,did not provide adequate and accessible food.This resulted in almost no distribution of tuber-eating waterbirds,with only a few geese congregating in early winter.Our results demonstrated that the shallow sub-lakes under human control provided a different environment from the main lake and are key to sustaining the successful wintering of hundreds of thousands of migratory waterbirds in Poyang Lake.Therefore,we recommend refining the anthropogenic management of the shallow sub-lakes to regulate the water level to ensure the carrying capacity of Poyang Lake.

Prediction of the potential distribution and analysis of the freezing injury risk of winter wheat on the Loess Plateau under climate change

Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat.We used an optimized Maximum Entropy(MaxEnt)Model to predict the potential distribution of winter wheat in the current period(1970-2020)and the future period(2021-2100)under four shared socioeconomic pathway scenarios(SSPs).We applied statistical downscaling methods to downscale future climate data,established a scientific and practical freezing injury index(FII)by considering the growth period of winter wheat,and analyzed the characteristics of abrupt changes in winter wheat freezing injury by using the Mann-Kendall(M-K)test.The results showed that the prediction accuracy AUC value of the MaxEnt Model reached 0.976.The minimum temperature in the coldest month,precipitation in the wettest season and annual precipitation were the main factors affecting the spatial distribution of winter wheat.The total suitable area of winter wheat was approximately 4.40×10^(7)ha in the current period.In the 2070s,the moderately suitable areas had the greatest increase by 9.02×10^(5)ha under SSP245 and the least increase by 6.53×10^(5)ha under SSP370.The centroid coordinates of the total suitable areas tended to move northward.The potential risks of freezing injury in the high-latitude and-altitude areas of the Loess Plateau,China increased significantly.The northern areas of Xinzhou in Shanxi Province,China suffered the most serious freezing injury,and the southern areas of the Loess Plateau suffered the least.Environmental factors such as temperature,precipitation and geographical location had important impacts on the suitable area distribution and freezing injury risk of winter wheat.In the future,greater attention should be paid to the northward boundaries of both the winter wheat planting areas and the areas of freezing injury risk to provide the early warning of freezing injury and implement corresponding management strategies.

Improved simulation of winter wheat yield in North China Plain by using PRYM-Wheat integrated dry matter distribution coefficient

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.

The Ice-Snow Industry Heated Up the Winter

This winter witnessed the popularity of cities in Northeast China,especially Harbin.People’s enthusiasm for the ice and snow grew,and more and more people started to focus on and engage in the ice-snow industry.At the ski resort,skiing enthusiasts from all over the country wear goggles and sprint down slopes on their snowboards.

River width and depth as key factors of diurnal activity energy expenditure allocation for wintering Spot-billed Ducks in the Xin'an River Basin

Rivers are important habitats for wintering waterbirds.However,they are easily influenced by natural and human activities.An important approach for waterbirds to adapt to habitats is adjusting the activity time and energy expenditure allocation of diurnal behavior.The compensatory foraging hypothesis predicts that increased energy expenditure leads to longer foraging time,which in turn increases food intake and helps maintain a constant energy balance.However,it is unclear whether human-disturbed habitats result in increased energy expenditure related to safety or foraging.In this study,the scan sample method was used to observe the diurnal behavior of the wintering Spot-billed Duck(Anas poecilorhyncha) in two rivers in the Xin’an River Basin from October 2021 to March 2022.The allocation of time and energy expenditure for activity in both normal and disturbed environments was calculated.The results showed that foraging accounted for the highest percentage of time and energy expenditure.Additionally,foraging decreased in the disturbed environment than that in the normal environment.Resting behavior showed the opposite trend,while other behaviors were similar in both environments.The total diurnal energy expenditure of ducks in the disturbed environment was greater than that in the normal environment,with decreased foraging and resting time percentage and increased behaviors related to immediate safety(swimming and alert) and comfort.These results oppose the compensatory foraging hypothesis in favor of increased security.The optimal diurnal energy expenditure model included river width and water depth,which had a positive relationship;an increase in either of these two factors resulted in an increase in energy expenditure.This study provides a better understanding of energy allocation strategies underlying the superficial time allocation of wintering waterbirds according to environmental conditions.Exploring these changes can help understand the maximum fitness of wintering waterbirds in response to nature and human influences.

Scientific Advances and Weather Services of the China Meteorological Administration’s National Forecasting Systems during the Beijing 2022 Winter Olympics

Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational techniques,and experience.This made providing meteorological services for this event particularly challenging.The China Meteorological Administration(CMA)Earth System Modeling and Prediction Centre,achieved breakthroughs in research on short-and medium-term deterministic and ensemble numerical predictions.Several key technologies crucial for precise winter weather services during the Winter Olympics were developed.A comprehensive framework,known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics,was established.Some of these advancements represent the highest level of capabilities currently available in China.The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality.This included achievements such as the“100-meter level,minute level”downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days.Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed,and many of these techniques have since been integrated into the CMA’s operational national forecasting systems.These accomplishments were facilitated by a dedicated weather forecasting and research initiative,in conjunction with the preexisting real-time operational forecasting systems of the CMA.This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project(SMART2022),and continues to play an important role in their Regional Association(RA)II Research Development Project(Hangzhou RDP).Therefore,the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming highimpact weather forecasting activities.This article provides an overview and assessment of this program and the operational national forecasting systems.

A combination of straw incorporation and polymer-coated urea offsets soil ammonia and nitrous oxide emissions in winter wheat fields

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.

National Image Construction from the Perspective of Multimodal Metaphor-A Case Study of the Opening Ceremony of the Beijing Winter Olympics

The national image is a comprehensive concept with a distinct political feature,including the international image presented to the outside world,and also encompassing the national identity of the people.With the development of globalization,international cultural communication has become a crucial part of shaping the national image,and the opening ceremony of the Beijing Winter Olympics has become an important opportunity for China to showcase its national image to the world in the post-pandemic era.Based on Forceville’s multimodal metaphor theory,this paper examines the metaphorical phenomena contained in the performance and their functions,effects,and purposes in the construction of the national image.It is found that there are many scenes,images,and narratives in the opening ceremony,including war metaphor,competition metaphor,personification metaphor,and other conceptual metaphors.The focus of this paper is on multimodal metaphor in a broad sense,mainly encompassing auditory and visual modes.Through the use of these multimodal metaphors,the opening ceremony of the Winter Olympics builds an image of a vibrant,peace-loving,and responsible country,which not only demonstrates China’s cultural self-confidence,but also expresses the Chinese people’s beautiful vision for the early reunification of the motherland.

Spatio-temporal Evolution Characteristics and Driving Forces of Winter Urban Heat Island:A Case Study of Rapid Urbanization Area of Fuzhou City,China

Under the influence of anthropogenic and climate change,the problems caused by urban heat island(UHI)has become increasingly prominent.In order to promote urban sustainable development and improve the quality of human settlements,it is significant for exploring the evolution characteristics of urban thermal environment and analyzing its driving forces.Taking the Landsat series images as the basic data sources,the winter land surface temperature(LST)of the rapid urbanization area of Fuzhou City in China was quantitatively retrieved from 2001 to 2021.Combing comprehensively the standard deviation ellipse model,profile analysis and GeoDetector model,the spatio-temporal evolution characteristics and influencing factors of the winter urban thermal environment were systematically analyzed.The results showed that the winter LST presented an increasing trend in the study area during 2001–2021,and the winter LST of the central urban regions was significantly higher than the suburbs.There was a strong UHI effect from 2001 to 2021with an expansion trend from the central urban regions to the suburbs and coastal areas in space scale.The LST of green lands and wetlands are significantly lower than croplands,artificial surface and unvegetated lands.Vegetation and water bodies had a significant mitigation effect on UHI,especially in the micro-scale.The winter UHI had been jointly driven by the underlying surface and socio-economic factors in a nonlinear or two-factor interactive enhancement mode,and socio-economic factors had played a leading role.This research could provide data support and decision-making references for rationally planning urban layout and promoting sustainable urban development.

Winter Wheat Yield Estimation Based on Sparrow Search Algorithm Combined with Random Forest:A Case Study in Henan Province,China

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.

My Winter Holiday Plan

The winter holiday is coming and I’m making a plan for it.First of all,I will finish my homework.My English is not very good,so I will go on practicing it hard.I hope I can make great progress in English.Secondly,I will do sports every day to keep healthy.

My Winter Vacation Plan

Winter vacation is coming and I've made the following winter vacation plan.First of all,I will read some classic literature work^(1)because I think reading them makes me wiser.Then I will try to spend more time help^(2)my parents to do some housework.Besides,I am going to take part in some social activities so that I can know more about society.What's more,I want to take up some forms of exercise,such as walking,running and swimming,keeping^(3)healthy.If possible,I'd like to go to Beijing to visit the Great Wall.