Estimating total leaf nitrogen concentration in winter wheat by canopy hyperspectral data and nitrogen vertical distribution

The use of remote sensing to monitor nitrogen(N) in crops is important for obtaining both economic benefit and ecological value because it helps to improve the efficiency of fertilization and reduces the ecological and environmental burden. In this study, we model the total leaf N concentration(TLNC) in winter wheat constructed from hyperspectral data by considering the vertical N distribution(VND). The field hyperspectral data of winter wheat acquired during the 2013–2014 growing season were used to construct and validate the model. The results show that:(1) the vertical distribution law of LNC was distinct, presenting a quadratic polynomial tendency from the top layer to the bottom layer.(2) The effective layer for remote sensing detection varied at different growth stages. The entire canopy, the three upper layers, the three upper layers, and the top layer are the effective layers at the jointing stage, flag leaf stage, flowering stages, and filling stage, respectively.(3) The TLNC model considering the VND has high predicting accuracy and stability. For models based on the greenness index(GI), mND705(modified normalized difference 705), and normalized difference vegetation index(NDVI), the values for the determining coefficient(R2), and normalized root mean square error(nRMSE) are 0.61 and 8.84%, 0.59 and 8.89%, and 0.53 and 9.37%, respectively. Therefore, the LNC model with VND provides an accurate and non-destructive method to monitor N levels in the field.     

冬小麦冠层水平叶绿素含量的高光谱估测

【目的】利用高光谱数据对抽穗期冬小麦冠层叶绿素含量进行估测,旨在为叶绿素含量快速准确估测提供参考。【方法】利用ASD便携式野外光谱仪和SPAD-502叶绿素仪实测了冬小麦抽穗期冠层光谱反射率及叶绿素含量,并对原始光谱反射率及其一阶导数光谱与叶绿素相对含量进行了相关分析,建立了基于敏感波段、红边位置、原始光谱峰度和偏度、一阶导数光谱峰度和偏度的叶绿素估算模型,并进行检验,从中筛选出精度最高的模型。【结果】冬小麦冠层光谱曲线特征与叶绿素含量之间有着密切联系。基于原始光谱一阶导数偏度和峰度的冬小麦(抽穗期)叶绿素含量估算模型拟合精度优于其他4种估算模型,决定系数R2分别为0.847和0.572,均方根误差RMSE分别为0.397和0.697,相对误差RE分别为61.0%和119.0%,拟合精度优于其他4种估算模型。【结论】原始光谱一阶导数的偏度和峰度作为自变量能很好地估测抽穗期小麦冠层叶绿素含量。     

条锈病影响下冬小麦叶绿素含量的高光谱估计

叶绿素含量是在小麦长势监测中是非常重要的评估内容,尤其是在小麦受到病害影响的情况下,准确估计其叶绿素含量,有助于合理进行灾害评价。遥感高光谱技术为获取植物的生理参数提供了丰富的数据来源。笔者使用襄樊地区实测获取的受条锈病影响的小麦高光谱数据,利用回归分析的方法建立了受条锈病影响的小麦叶绿素含量与其高光谱的关系模型。经验证,模型有较好的精度。     

Comparative analysis of three chemometric techniques for the spectroradiometric assessment of canopy chlorophyll content in winter wheat

Hyperspectral data sets contain useful information for characterizing vegetation canopies not previously available from multi-spectral data sources. However, to make full use of the information content one has to find ways for coping with the strong multi-collinearity in the data. The redundancy directly results from the fact that only a few variables effectively control the vegetation signature. This low dimensionality strongly contrasts with the often more than 100 spectral channels provided by modern spectroradiometers and through imaging spectroscopy. With this study we evaluated three different chemometric techniques specifically designed to deal with redundant (and small) data sets. In addition, a widely used 2-band vegetation index was chosen (NDVI) as a baseline approach. A multi-site and multi-date field campaign was conducted to acquire the necessary reference observations. On small subplots the total canopy chlorophyll content was measured and the corresponding canopy signature (450-2500 nm) was recorded (n_obs = 42). Using this data set we investigated the predictive power and noise sensitivity of stepwise multiple linear regression (SMLR) and two ‘full spectrum’ methods: principal component regression (PCR) and partial least squares regression (PLSR). The NDVI was fitted to the canopy chlorophyll content using an exponential relation. For all techniques, a jackknife approach was used to obtain cross-validated statistics. The PLSR clearly outperformed all other techniques. PLSR gave a cross-validated RMSE of 51 mg m⁻² for canopy chlorophyll contents ranging between 38 and 475 mg m⁻² (0.99 ≤ LAI ≤ 8.74 m² m⁻²). The lowest accuracy was achieved using PCR (RMSE_cv = 82 mg m⁻² and ). The NDVI, even using chlorophyll optimized band settings, could not reach the accuracy of PLSR. Regarding the sensitivity to artificially created (white) noise, PCR showed some advantages, whereas SMLR was the most sensitive chemometric technique. For relatively small, highly multi-collinear data sets the use of partial least square regression is recommended. PLSR makes full use of the rich spectral information while being relatively insensitive to sensor noise. PLSR provides a regression model where the entire spectral information is taken - in a weighted form - into account. This method seems therefore much better adapted to deal with potentially confounding factors compared to any 2-band vegetation index which can only avoid the most harmful factor of variation.     

施氮水平对冬小麦冠层氨挥发的影响

为探索冬小麦全生育期冠层氨挥发规律、主要影响因素及其对麦田氨挥发的贡献率,设置0、90、180 kg N·hm~(-2)三种氮素水平,利用改进型通气式氨气捕获装置,原位分析冬小麦冠层氨挥发速率及其与叶片氮素生理指标的关系。结果表明:麦田氨挥发主要发生在施肥后2~3周,全生育期累积挥发量为3.773~8.704 kg N·hm~(-2),施氮显著提高了麦田氨挥发累积量(P0.05),土壤与冠层氨挥发累积量分别为3.289~7.773 kg N·hm~(-2)和0.750~1.461 kg N·hm~(-2),对麦田氨挥发的贡献率分别为87.2%~89.3%和15.4%~19.9%。不施氮条件下,冠层无氨气吸收;低施氮(90 kg N·hm~(-2))下,冠层氨气吸收主要发生在苗期;高施氮(180 kg N·hm~(-2))下,苗期、返青期和灌浆前期冠层均有氨气吸收发生。冠层氨挥发主要发生在开花期、灌浆末期至枯死期,分别占冠层氨挥发的4.5%~9.3%和79.1%~99.0%;冠层氨挥发速率与叶片氨气补偿点、质外体NH+4浓度显著正相关(P0.05),与谷氨酰胺合成酶(GS)活性、质外体溶液pH相关关系不显著(P0.05)。总之,开花前,不施肥条件下冬小麦冠层向大气中释放氨,施肥后,冠层从大气中吸收氨。冬小麦开花后,不论施肥与否,冠层都向大气层释放氨。     

不同水分处理下冬小麦叶片光谱特征及 氮素垂直分布情况分析

【目的】为了研究不同水分处理下冬小麦冠层叶片氮素的分布情况。【方法】文章以2014年北京市农林科学院试验田的冬小麦为研究对象,在野外观测实验的支持下,分析不同水分处理下冬小麦氮素垂直分布规律及冠层光谱变化规律,并对不同水分处理下冠层不同叶位光谱指数与叶片氮素进行相关性分析。【结果 /结论】在挑旗期W2水分处理下叶片氮素含量最大,而W1、W3、W4、W5随着灌水量增加叶片氮素含量降低,在拔节期上2叶的氮素含量高于上1叶,而到了抽穗期和灌浆期随着叶位的升高氮素含量逐渐升高;对于拔节期未做水分处理时光谱反射率差异性表现为W2W3W4W5W1。除拔节期外其他生育期随灌水量增加冠层叶片光谱反射率降低;拔节期上1叶在W1、W2水分处理下氮素与光谱指数相关性达显著性水平,最大相关性为0.87,挑旗期上1叶、上3叶、上5叶氮素与光谱指数相关性达显著性水平,最大相关性为0.90,抽穗期上1叶、上2叶、上3叶、上4叶氮素与光谱指数达显著性水平,最大相关性为0.92,灌浆期、上2叶氮素与光谱指数相关性达显著性水平其最大相关性为0.96。     

基于光谱指数的冬小麦变量施肥冠层光谱特征研究及产量分析

 【目的】由适时获得的高光谱数据代替传统繁琐的实验室土壤养分测定数据来进行变量施肥，实现冬小麦高产优质的目标。【方法】本研究利用冬小麦起身期和拔节期冠层光谱数据，选用反映冬小麦长势信息的优化土壤调节植被指数（OSAVI，optimization of soil-adjusted vegetation index）和变量施肥模型进行变量施肥管理（变量区），以相邻地块常规非变量（均一）施肥区（对照区）为对照，研究了不同氮肥处理冬小麦冠层光谱特征及其施肥效应。【结果】变量施肥之后两种氮肥处理在敏感波段670 nm和760～900 nm处反射率差异明显，而670nm和760～900nm是氮素和冠层的敏感波段，说明进行变量施肥时，利用基于这两个波段组合的光谱指数OSAVI优于其它波段组合的光谱指数；SAVI不同生育时期的变化情况，反映了变量施肥在调控作物长势及群体结构上的优势；与对照区相比变量区提高产量达378.72 kg•ha-1，并降低了各小区产量之间的变异,变量区土壤硝态氮浓度降低，氮肥利用率提高，生态效益较为明显。【结论】该技术通过改善冬小麦群体质量，延缓了植株衰老，促进干物质和氮积累，增加冬小麦产量和氮肥利用率。     

夏玉米LAI与冠层反射光谱的定量关系

从不同角度研究夏玉米LAI与其对应冠层反射光谱的相关性.结果表明,夏玉米LAI与冠层反射光谱的定量关系以由多个单波段建立的多元线性回归模型为最优,其次是由DVI(900,730)建立的三次多项式回归模型,再次是由SAVI(950,600)建立的幂函数回归模型.     

Estimation of bioenergy crop yield and N status by hyperspectral canopy reflectance and partial least square regression

The objective of this study was to compare performance of partial least square regression (PLSR) and best narrowband normalize nitrogen vegetation index (NNVI) linear regression models for predicting N concentration and best narrowband normalize different vegetation index (NDVI) for end of season biomass yield in bioenergy crop production systems. Canopy hyperspectral data was collected using an ASD FieldSpec FR spectroradiometer (350–2500 nm) at monthly intervals in 2012 and 2013. The cropping systems evaluated in the study were perennial grass {mixed grass [50 % switchgrass (Panicum virgatum L.), 25 % Indian grass “Cheyenne” (Sorghastrum nutans (L.) Nash) and 25 % big bluestem “Kaw” (Andropogon gerardii Vitman)] and switchgrass “Alamo”} and high biomass sorghum “Blade 5200” (Sorghum bicolor (L.) Moench) grown under variable N applications rates to estimate biomass yield and quality. The NNVI was computed with the wavebands pair of 400 and 510 nm for the high biomass sorghum and 1500 and 2260 nm for the perennial grass that were strongly correlated to N concentration for both years. Wavebands used in computing best narrowband NDVI were highly variable, but the wavebands from the red edge region (710–740 nm) provided the best correlation. Narrowband NDVI was weakly correlated with final biomass yield of perennial grass (r² = 0.30 and RMSE = 1.6 Mg ha^?1 in 2012 and r² = 0.37 and RMSE = 4.0 Mg ha^?1, but was strongly correlated for the high biomass sorghum in 2013 (r² = 0.72 and RMSE = 4.6 Mg ha^?1). Compared to the best narrowband VI, the RMSE of the PLSR model was 19–41 % lower for estimating N concentration and 4.2–100 % lower for final biomass. These results indicates that PLSR might be best for predicting the final biomass yield using spectral sample obtained in June to July, but narrowband NNVI was more robust and useful in predicting N concentration.     

夏、冬季苏北近岸海域悬沙浓度垂直分布特征

通过将2012年8月、12月在苏北黄海海域野外调查获得的声学多普勒流速剖面仪(ADCP)后向散射强度数据与悬沙浓度进行拟合,得知两者的相关系数在0.8以上,反演结果较理想。并结合同步观测的温度、盐度等水文要素资料,对该区域夏、冬季两季悬浮泥沙的垂直分布特征、形成原因及输运进行了研究,结果表明苏北近岸海域悬浮泥沙分布的典型性季节变化明显,冬季悬沙浓度普遍高于夏季。悬浮泥沙分布及输运受苏北沿岸水、黄海西部沿岸流、长江冲淡水、黄海暖流、黄海冷水团等影响,其中黄海西部沿岸流的季节变化为主要的影响因素。苏北沿岸水携带废黄河口的再悬浮泥沙和近岸悬沙向东南外海扩散,冬季的搬运量和扩散范围显著大于夏季。黄海暖流阻碍悬沙向外海扩散,使其在近岸被大量捕集下来。夏季长江冲淡水的东北方向偏转,使得苏北南部海域悬沙分布出现层化现象。     

增水和施肥对苜蓿-冬小麦轮作系统冬小麦叶片光合速率和叶绿素含量的影响

[目的]黄土高原面临着严重的水土流失和土壤肥力下降等问题,将苜蓿引入小麦的作物体系形成草田轮作系统,以缓解过量化肥使用造成的环境问题,同时提高农作物产量。[方法]本研究采用野外控制实验,利用山西农业大学已经建立3年的紫花苜蓿实验平台,翻耕后种植冬小麦,进行增水和施肥处理,监测其叶片光合生理特征和叶绿素含量的变化。[结果]在2017年(10月29日-12月2日),即冬小麦出苗后到越冬期初期,增水和施肥仅提高叶绿素含量2.7%和8.2%;2018年(3月14日-6月4日),即冬小麦从越冬期末期至成熟期,增水提高光合速率20.3%、气孔导度43.8%、蒸腾速率31.4%和叶绿素含量2.3%,但降低叶面饱和蒸气压差6.5%;施肥显著提高叶绿素含量2.0%,但降低气孔导度8.2%。在冬小麦的整个生长季,增水和施肥对以上各指标的影响不存在交互作用。[结论]增水和施肥可以提高小麦叶绿素含量,但随着时间的推移,增水和施肥的作用减弱;增水提高冬小麦叶片光合速率但施肥作用不显著,说明将苜蓿引入小麦的作物体系形成草田轮作系统,小麦可以利用苜蓿固定的氮源,降低肥料的施用,增加经济效益和环境效应。未来草田轮作是绿色农业发展的重点方向,也是可持续农业发展的必要途径。     

基于HJ小卫星影像的北京市冬小麦测产研究

粮食产量的估测对制定粮食政策和调整种植结构具有重要的意义。本研究以北京市为例,利用2013年4月30日、5月12日和5月29日三期冬小麦抽穗、灌浆时期的HJ小卫星NDVI数据,结合北京市实产地块数据建立了北京市冬小麦估产回归模型,并对北京市各区县和北京全市的冬小麦单产进行了估算。结果显示:分区县地块回归的北京市冬小麦主产区大兴、房山、通州和顺义的小麦单产分别为5148.96 kg/hm2、4849.30 kg/hm2、5350.64kg/hm2和5108.84 kg/hm2,P值分别为0.000、0.000、0.000和0.001;北京市全市的冬小麦单产为5049.24 kg/hm2,精度验证的结果显示实测单产和预测单产具有良好的对应关系,其R2=0.92,RE=2.18%,RMSE=154.61 kg/hm2。以上研究结果表明利用HJ小卫星的NDVI数据可以快速、准确的估算北京市及其各区县的冬小麦单产。     

Influence of time of day on measurement with chlorophyll meters and canopy reflectance sensors of different crop N status

Precision Agriculture - Optical sensors are a promising approach for assessing nitrogen (N) status of vegetable crops. However, their potential may be undermined if time of day influences...     

Inversion of a canopy reflectance model using hyperspectral imagery for monitoring wheat growth and estimating yield

Applications of hyperspectral remote sensing data to derive relevant properties for precision agriculture are described. Green leaf area index, fraction of senescent material and grain yield are retrieved from the hyperspectral data. Two sensors were used to obtain these data; the airborne visible/infrared imaging spectrometer AVIS and the space-borne compact high-resolution imaging spectrometer CHRIS; they show the applicability of the methods to different spatial scales. In addition, the bi-directional observation capability of the CHRIS sensor is used to derive information about the average leaf angle of the canopies which are used to link canopy structure with phenological development. Derivation of the canopy properties, green leaf area index and fraction of senescent material was done with the radiative transfer model, SLC (soil–leaf–canopy). The results were used as input into the crop growth model PROMET-V to calculate grain yield. Two years of data from the German research project preagro are presented.     

冬小麦冠层叶色变化节奏及其与栽培措施的关系

以美制光谱辐射计EXOTECH 100BX的光谱指标，定量地监测到冬小麦扬麦158冠层叶色“三黑三黄”的变化节奏：出苗至分蘖末期为“第一黑”，拔节期至孕穗期为“第二黑”，始穗期至灌浆初期为“第三黑”；分蘖末期至拔节期为“第一黄”，孕穗期至始穗期为“第二黄”，灌浆初期至成熟为“第三黄”。经过长期栽培试验，人们的栽培措施与冬小麦冠层叶色变化节奏已基本统一。     

融合光谱反射率与时频特征的坡垒叶绿素含量估测模型研究

【目的】研究估测坡垒叶绿素含量的高光谱模型,探讨融合光谱反射率与时频特征估测叶绿素含量的可行性,为坡垒叶绿素含量的快速无损检测提供参考。【方法】以2年生坡垒为研究对象,设置N0（0 kg/hm²）、N1（35 kg/hm²）、N2（70 kg/hm²）3个氮肥水平,测定不同氮肥水平下坡垒冠层叶绿素含量和光谱曲线,采用离散傅里叶变换（DFT）和短时傅里叶变换（STFT）方法提取光谱时频特征,采用偏最小二乘回归（PLSR）算法,构建基于光谱反射率、时频特征及其二者融合特征的不同氮水平的分区模型以及全氮肥水平下的综合模型,估测不同氮肥水平下坡垒叶绿素含量,并以决定系数（R²）、平均绝对百分比误差（MAPE）、相对均方根误差（RRMSE）作为评价指标比较各模型精度,确定最优估测模型。【结果】（1）不同叶绿素含量下坡垒冠层光谱反射特征的整体变化趋势相似,在可见光波段（380~750 nm）内,光谱反射率随着叶绿素含量的增加而降低。（2）在构建的分区模型中,基于光谱反射率和时频特征构建的模型均能较好地估测坡垒叶绿素含量,检验R²分别为0.626~0.816,0.662~0.797,检验MAPE分别为4.966％~9.269％,6.029％~8.181％,检验RRMSE分别为6.827％~11.593％,8.247％~9.792％;基于融合光谱反射率与时频特征（融合特征）构建的分区模型检验R²为0.913~0.951,检验MAPE和RRMSE均低于10％。（3）在构建的综合模型中,当引入哑变量时,基于融合光谱反射率与时频特征（融合特征）构建模型的检验R²为0.814,MAPE和RRMSE分别为7.212％和8.578%,二者较基于光谱反射率构建的模型分别降低了37％和36％,较基于时频特征构建的模型分别降低了47％和45％。【结论】基于融合光谱反射率和时频特征（融合特征）构建的模型能够提高坡垒叶绿素含量估测的精度,对于不同氮肥水平下坡垒叶绿素含量有较好的估测效果,可作为估测坡垒叶绿素含量的优选方法。     

施氮量对新疆滴灌冬小麦冠层结构及其小气候特征的影响

为明确不同施氮量对新疆冬小麦冠层结构特征及其群体内部光、温变化的影响,于2013—2015年连续2个冬小麦生长周期,在大田滴灌条件下,采用单因素随机区组试验设计,共设置了0(N_0),94.5(N_1),180(N_2),240(N_3),300(N_4)和360kg/hm~2(N_5)6个施氮肥处理,研究了施氮量对冬小麦茎型特征,叶垂直分布及其形态特征,冠层光、温变化规律的影响。结果表明:与N_0处理相比,增施氮肥冬小麦叶片的长、宽及叶片总面积均显著增加。随着施氮量的增加,各叶层LAI、各节间长度和节间粗度均呈"先增后减"的趋势,株高变幅为71.83~85.88cm(2014年)和70.56~85.18cm(2015年);冠层中、下部的透光率和冠层温度均呈"先降后增"的趋势。各处理冠层温度日变化呈"凸"型曲线,均在15:00左右达到峰值,其值以N_3处理最低。2年试验产量均以N_3处理最高,为8 653.22(2013年)和8 415.20kg/hm~2(2014年),分别较同年N_0、N_1、N_2、N_4和N_5处理增产68.01%、32.39%、17.92%、5.34%、10.69%和67.39%、30.81%、19.31%、4.20%、11.49%。本试验条件下,施氮量控制在240kg/hm~2左右,滴灌冬小麦叶型、株型特征良好,冠层光、温适宜,有利于获得高产。     

两种筋型冬小麦品种旗叶叶绿素含量和衰老生理性状比较

以黄淮流域大面积推广的强筋型冬小麦品种郑麦366和中筋型冬小麦品种矮抗58为试验材料,分别测定其旗叶中叶绿素和丙二醛的含量.结果表明:随着小麦生育期的推进,叶绿素a、叶绿素b和总叶绿素含量的变化规律大体一致,均呈现先上升后下降的趋势,花期达到最大值;在生育前期,郑麦366的3种色素含量均高于矮抗58,而到生育后期则相反;花后20 d,两个品种旗叶中丙二醛含量均急剧增加,但郑麦366增加得更快.     

含沙量变化对U型渠道垂线流速分布的影响

【目的】探索含沙量变化对U型渠道挟沙水流垂线流速分布的影响,进而从理论上完善挟沙水流流速分布规律。【方法】通过U型渠道水槽试验,测定水流中含沙量为1.12～500kg/m3时,最大流速所在位置的变化,同时引入卡门常数κ,来反映含沙量对垂线流速分布的影响。【结果】当水流含沙量s<300kg/m3时,随着含沙量的增加,最大流速点的位置逐渐下降,在主流区、底流区和表面区,挟沙水流均遵循对数流速分布规律,但κ的变化规律不同;当含沙量s≥300kg/m3时,水流的流型发生了变化,表面区、主流区水流不再遵循对数流速分布规律,底流区虽仍遵循对数流速分布规律,但κ的变化规律与s<300kg/m3时不同,κ的变化趋势总体随着含沙量的增大而减小。【结论】U型渠道挟沙水流遵循对数流速分布规律,κ的变化规律与普通明渠不同,应该分别对待。