Short basal internodes are important for lodging resistance of rice(Oryza sativa L.).Several canopy indices affect the elongation of basal internodes,but uncertainty as to the key factors determining elongation of bas...Short basal internodes are important for lodging resistance of rice(Oryza sativa L.).Several canopy indices affect the elongation of basal internodes,but uncertainty as to the key factors determining elongation of basal internodes persists.The objectives of this study were(1)to identify key factors affecting the elongation of basal internodes and(2)to establish a quantitative relationship between basal internode length and canopy indices.An inbred rice cultivar,Yinjingruanzhan,was grown in two split-plot field experiments with three N rates(0,75,and 150 kg N ha−1 in early season and 0,90,and 180 kg N ha−1 in late season)as main plots,three seedling densities(16.7,75.0,and 187.5 seedlings m−2)as subplots,and three replications in the 2015 early and late seasons in Guangzhou,China.Light intensity at base of canopy(Lb),light quality as determined from red/far-red light ratio(R/FR),light transmission ratio(LTR),leaf area index(LAI),leaf N concentration(NLV)and final length of second internode(counted from soil surface upward)(FIL)were recorded.Higher N rate and seedling density resulted in significantly longer FIL.FIL was negatively correlated with Lb,LTR,and R/FR(P<0.01)and positively correlated with LAI(P<0.01),but not correlated with NLV(P>0.05).Stepwise linear regression analysis showed that FIL was strongly associated with Lb and LAI(R2=0.82).Heavy N application to pot-grown rice at the beginning of first internode elongation did not change FIL.We conclude that FIL is determined mainly by Lb and LAI at jointing stage.NLV has no direct effect on the elongation of basal internodes.N application indirectly affects FIL by changing LAI and light conditions in the rice canopy.Reducing LAI and improving canopy light transmission at jointing stage can shorten the basal internodes and increase the lodging resistance of rice.展开更多
Since the reform and opening-up program started in 1978,the level of urbanization has increased rapidly in China.Rapid urban expansion and restructuring have had significant impacts on the ecological environment espec...Since the reform and opening-up program started in 1978,the level of urbanization has increased rapidly in China.Rapid urban expansion and restructuring have had significant impacts on the ecological environment especially within built-up areas.In this study,ArcGIS 10,ENVI 4.5,and Visual FoxPro 6.0 were used to analyze the human impacts on vegetation in the built-up areas of 656Chinese cities from 1992 to 2010.Firstly,an existing algorithm was refined to extract the boundaries of the built-up areas based on the Defense Meteorological Satellite Program Operational Linescan System(DMSP_OLS)nighttime light data.This improved algorithm has the advantages of high accuracy and speed.Secondly,a mathematical model(Human impacts(HI))was constructed to measure the impacts of human factors on vegetation during rapid urbanization based on Advanced Very High Resolution Radiometer(AVHRR)Normalized Difference Vegetation Index(NDVI)and Moderate Resolution Imaging Spectroradiometer(MODIS)NDVI.HI values greater than zero indicate relatively beneficial effects while values less than zero indicate proportionally adverse effects.The results were analyzed from four aspects:the size of cities(metropolises,large cities,medium-sized cities,and small cities),large regions(the eastern,central,western,and northeastern China),administrative divisions of China(provinces,autonomous regions,and municipalities)and vegetation zones(humid and semi-humid forest zone,semi-arid steppe zone,and arid desert zone).Finally,we discussed how human factors impacted on vegetation changes in the built-up areas.We found that urban planning policies and developmental stages impacted on vegetation changes in the built-up areas.The negative human impacts followed an inverted′U′shape,first rising and then falling with increase of urban scales.China′s national policies,social and economic development affected vegetation changes in the built-up areas.The findings can provide a scientific basis for municipal planning departments,a decision-making reference for government,and scientific guidance for sustainable development in China.展开更多
株高和叶面积指数(Leaf Area Index,LAI)反映着作物的生长发育状况。为了探究基于无人机可见光遥感提取冬小麦株高的可靠性,以及利用株高和可见光植被指数估算LAI的精度,本文获取了拔节期、抽穗期、灌浆期的无人机影像,提取了冬小麦株...株高和叶面积指数(Leaf Area Index,LAI)反映着作物的生长发育状况。为了探究基于无人机可见光遥感提取冬小麦株高的可靠性,以及利用株高和可见光植被指数估算LAI的精度,本文获取了拔节期、抽穗期、灌浆期的无人机影像,提取了冬小麦株高与可见光植被指数,使用逐步回归、偏最小二乘、随机森林、人工神经网络四种方法建立LAI估测模型,并对株高提取及LAI估测情况进行精度评价。结果显示:(1)株高提取值Hc与实测值Hd高度拟合(R^(2)=0.894,RMSE=6.695,NRMSE=9.63%),株高提取效果好;(2)与仅用可见光植被指数相比,基于株高与可见光植被指数构建的LAI估测模型精度更高,且随机森林为最优建模方法,当其决策树个数为50时模型估测效果最好(R^(2)=0.809,RMSE=0.497,NRMSE=13.85%,RPD=2.336)。利用无人机可见光遥感方法,高效、准确、无损地实现冬小麦株高及LAI提取估测可行性较高,该研究结果可为农情遥感监测提供参考。展开更多
为了揭示不同径阶油松Pinus tabulaeformis林群落内光辐射状况,以北京市妙峰山实验林场内人工油松林为研究对象,运用WinSCANOPY For Canopy Analysis冠层分析仪采集数据,并结合实地调查,实测了5种不同径阶的油松林群落内光辐射特征及冠...为了揭示不同径阶油松Pinus tabulaeformis林群落内光辐射状况,以北京市妙峰山实验林场内人工油松林为研究对象,运用WinSCANOPY For Canopy Analysis冠层分析仪采集数据,并结合实地调查,实测了5种不同径阶的油松林群落内光辐射特征及冠层结构参数。结果表明:立地条件相同的情况下,油松林内光辐射随胸径增加呈下降趋势,为14.64～22.43 MJ.m-2.d-1,平均约占冠上总辐射的64.59%。林分开阔度为24.91%～43.77%,并且不同径阶群落之间有明显差别。叶面积指数为2.23～4.50,平均约为3.67。冠层消光系数小于0.20,较小的消光系数对林内灌木层和草本层生长更新具有重要意义。展开更多
基金supported by the Natural Science Foundation of Guangdong Province,China(S2012020011043)the National High Technology Research and Development Program of China(2014AA10A605)+2 种基金the Special Fund for Agro-scientific Research in the Public Interest(201503106)Modern Agriculture Industry Technology System for Rice in Guangdong Province(2016LM1066,2017LM1066,2018LM1066)the Swiss Agency for Development and Cooperation through its funding of “Closing Rice Yield Gaps in Asia” Project(CORIGAP)
文摘Short basal internodes are important for lodging resistance of rice(Oryza sativa L.).Several canopy indices affect the elongation of basal internodes,but uncertainty as to the key factors determining elongation of basal internodes persists.The objectives of this study were(1)to identify key factors affecting the elongation of basal internodes and(2)to establish a quantitative relationship between basal internode length and canopy indices.An inbred rice cultivar,Yinjingruanzhan,was grown in two split-plot field experiments with three N rates(0,75,and 150 kg N ha−1 in early season and 0,90,and 180 kg N ha−1 in late season)as main plots,three seedling densities(16.7,75.0,and 187.5 seedlings m−2)as subplots,and three replications in the 2015 early and late seasons in Guangzhou,China.Light intensity at base of canopy(Lb),light quality as determined from red/far-red light ratio(R/FR),light transmission ratio(LTR),leaf area index(LAI),leaf N concentration(NLV)and final length of second internode(counted from soil surface upward)(FIL)were recorded.Higher N rate and seedling density resulted in significantly longer FIL.FIL was negatively correlated with Lb,LTR,and R/FR(P<0.01)and positively correlated with LAI(P<0.01),but not correlated with NLV(P>0.05).Stepwise linear regression analysis showed that FIL was strongly associated with Lb and LAI(R2=0.82).Heavy N application to pot-grown rice at the beginning of first internode elongation did not change FIL.We conclude that FIL is determined mainly by Lb and LAI at jointing stage.NLV has no direct effect on the elongation of basal internodes.N application indirectly affects FIL by changing LAI and light conditions in the rice canopy.Reducing LAI and improving canopy light transmission at jointing stage can shorten the basal internodes and increase the lodging resistance of rice.
基金Under the auspices of National Natural Science Foundation of China(No.41171143,40771064)Program for New Century Excellent Talents in University(No.NCET-07-0398)Fundamental Research Funds for the Central Universities(No.lzu-jbky-2012-k35)
文摘Since the reform and opening-up program started in 1978,the level of urbanization has increased rapidly in China.Rapid urban expansion and restructuring have had significant impacts on the ecological environment especially within built-up areas.In this study,ArcGIS 10,ENVI 4.5,and Visual FoxPro 6.0 were used to analyze the human impacts on vegetation in the built-up areas of 656Chinese cities from 1992 to 2010.Firstly,an existing algorithm was refined to extract the boundaries of the built-up areas based on the Defense Meteorological Satellite Program Operational Linescan System(DMSP_OLS)nighttime light data.This improved algorithm has the advantages of high accuracy and speed.Secondly,a mathematical model(Human impacts(HI))was constructed to measure the impacts of human factors on vegetation during rapid urbanization based on Advanced Very High Resolution Radiometer(AVHRR)Normalized Difference Vegetation Index(NDVI)and Moderate Resolution Imaging Spectroradiometer(MODIS)NDVI.HI values greater than zero indicate relatively beneficial effects while values less than zero indicate proportionally adverse effects.The results were analyzed from four aspects:the size of cities(metropolises,large cities,medium-sized cities,and small cities),large regions(the eastern,central,western,and northeastern China),administrative divisions of China(provinces,autonomous regions,and municipalities)and vegetation zones(humid and semi-humid forest zone,semi-arid steppe zone,and arid desert zone).Finally,we discussed how human factors impacted on vegetation changes in the built-up areas.We found that urban planning policies and developmental stages impacted on vegetation changes in the built-up areas.The negative human impacts followed an inverted′U′shape,first rising and then falling with increase of urban scales.China′s national policies,social and economic development affected vegetation changes in the built-up areas.The findings can provide a scientific basis for municipal planning departments,a decision-making reference for government,and scientific guidance for sustainable development in China.
文摘株高和叶面积指数(Leaf Area Index,LAI)反映着作物的生长发育状况。为了探究基于无人机可见光遥感提取冬小麦株高的可靠性,以及利用株高和可见光植被指数估算LAI的精度,本文获取了拔节期、抽穗期、灌浆期的无人机影像,提取了冬小麦株高与可见光植被指数,使用逐步回归、偏最小二乘、随机森林、人工神经网络四种方法建立LAI估测模型,并对株高提取及LAI估测情况进行精度评价。结果显示:(1)株高提取值Hc与实测值Hd高度拟合(R^(2)=0.894,RMSE=6.695,NRMSE=9.63%),株高提取效果好;(2)与仅用可见光植被指数相比,基于株高与可见光植被指数构建的LAI估测模型精度更高,且随机森林为最优建模方法,当其决策树个数为50时模型估测效果最好(R^(2)=0.809,RMSE=0.497,NRMSE=13.85%,RPD=2.336)。利用无人机可见光遥感方法,高效、准确、无损地实现冬小麦株高及LAI提取估测可行性较高,该研究结果可为农情遥感监测提供参考。
