高光谱评价植被叶绿素含量的研究进展

重点介绍利用便携式光谱仪获得的高光谱数据在评价植被叶绿素含量的研究状况。从叶绿素的光谱特性入手。通过和传统宽波段对比阐述高光谱数据在评价植被叶绿素中的特点。在此基础上简要介绍了高光谱遥感数据估计植被叶绿素含量两种方法的研究进展。一是利用光谱数据。植被指数，导数光谱评价植被叶绿素密度或浓度。二是利用红边光学参数评价植被叶绿素密度或浓度，并分析了研究中可能存在的问题。     

A broad-band leaf chlorophyll vegetation index at the canopy scale

An assessment of the sensitivity at the canopy scale to leaf chlorophyll concentration of the broad-band chlorophyll vegetation index (CVI) is carried out for a wide range of soils and crops conditions and for different sun zenith angles by the analysis of a large synthetic dataset obtained by using in the direct mode the coupled PROSPECT + SAILH leaf and canopy reflectance model. An optimized version (OCVI) of the CVI is proposed. A single correction factor is incorporated in the OCVI algorithm to take into account the different spectral behaviors due to crop and soil types, sensor spectral resolution and scene sun zenith angle. An estimate of the value of the correction factor and of the minimum leaf area index (LAI) value of applicability are given for each considered condition. The results of the analysis of the synthetic dataset indicated that the broad-band CVI index could be used as a leaf chlorophyll estimator for planophile crops in most soil conditions. Results indicated as well that, in principle, a single correction factor incorporated in the OCVI could take into account the different spectral behaviors due to crop and soil types, sensor spectral resolution and scene sun zenith angle.     

Comparing methods to estimate perennial ryegrass biomass: canopy height and spectral vegetation indices

Precision Agriculture - Pasture management is highly dependent on accurate biomass estimation. Usually, such activity is neglected as current methods are time-consuming and frequently perceived as...     

Development of an optical sensor for crop leaf chlorophyll content detection

Nitrogen content in crop leaf is an important indication for evaluating crop health and predicting crop yield. A normalized difference vegetation index (NDVI) is widely used as an indicator in estimating leaf nitrogen content in practice. How to effectively and accurately measure the NDVI value of crop leaves in the field is a challenge on in-field use instrument development. This paper reports the development of a hand-held spectroscopy-based optical sensing device for measuring crop leaf NDVI values under in-field natural light conditions. This optical sensing device could simultaneously measure the spectral reflectance of canopies and the solar intensity at two bands of 610 and 1220 nm, and calculate NDVI value in real-time based on measured spectral reflectance. This device was tested in tomato plants chlorophyll content measurement. A series of field tests were conducted to evaluate the performance of the sensor, and tomato leaf samples were collected for measuring chlorophyll contents as the reference for validation. Obtained results indicated that NDVI values measured with this sensing device had a close correlation with chlorophyll contents of the collected leaf samples measured in laboratory with a UV–vis spectrophotometer .     

Monitoring leaf potassium content using hyperspectral vegetation indices in rice leaves

Precision Agriculture - Potassium (K) is one of three main crop nutrients, and the high rate of potash fertilizer utilization (second only to nitrogen) leads to high prices. Therefore, efficient...     

基于高光谱植被指数的马铃薯叶片叶绿素含量估测模型

【目的】筛选相关性好的植被指数构建马铃薯叶片叶绿素a、叶绿素b估测模型,为科学、无损地进行马铃薯叶片叶绿素含量估算提供技术支撑。【方法】采用便携式高光谱地物波谱仪,获取不同施氮水平下不同生育时期的马铃薯植株叶片光谱反射率,提取植被指数,测定马铃薯叶片叶绿素a、叶绿素b含量,并研究叶绿素含量与植被指数的相关性。【结果】12个植被指数与叶绿素a、叶绿素b含量相关性较好,其中修正归一化差异指数(mND_(705))、修正简单比值指数(mSR_(705))、地面叶绿素指数(MTCI)、修改叶绿素吸收反射指数(MCARI)与叶绿素a、叶绿素b含量相关性最好。基于这4个植被指数建立的估测模型中,MTCI构建的乘幂模型估测叶绿素a含量的效果最佳,mND_(705)构建的指数模型估测叶绿素b含量的效果最佳。【结论】MTCI构建的乘幂模型能较为精确地估测叶绿素a含量,mND_(705)构建的指数模型能较为精确地估测叶绿素b含量;这2种模型可用于间接监测马铃薯植株的氮营养亏缺状态。     

水稻叶绿素变化与感光性和感温性关系分析

水稻叶绿素变化与叶片衰老紧密联系,影响叶绿素变化有高温、强光等因素,但叶绿素变化与感光性和感温性方面的研究很少,为试图分析这两者间的联系,同时分析叶绿素含量本底与叶绿素变化间的联系,分别通过35个、133个材料在广州和湖北荆州两地多组试验,研究始穗期在不同生态区的变化,即利用出穗促进率,反映水稻不同材料的感光性和感温性,进一步研究出穗促进率与叶绿素含量变化的关系.此外,对叶绿素含量本底不同的材料,按高低进行分类,探讨不同类型材料叶绿素的变化动态.结果表明,在始穗后的第14天到第18天叶片叶绿素含量(SPAD值)减少百分率与出穗促进率呈显著的正相关,35、133个材料分别对应的相关系数是0.5093、0.3036.同时试验还表明,叶绿素含量本底高的材料,在始穗后第9～13天其叶绿素降低幅度较本底低的材料小,而在第14～18天降低幅度反而大,差异达显著水平.叶绿素高低两组材料分开进行出穗促进率与叶绿素含量变化的相关分析,表明低SPAD值组的相关系数更高,达极显著水平.始穗后第14～18天叶绿素变化与感光性和感温性存在显著相关关系,此期叶绿素变化可以作为反映感光性和感温性的指标.     

Combining spatial and spectral information to estimate chlorophyll contents of crop leaves with a field imaging spectroscopy system

Imaging spectroscopy is widely used in weed recognition, pest monitoring, agricultural product quality control and other precision agricultural fields. In the present study, an in-house-designed/developed field imaging spectroscopy system (FISS, 380–870 nm) was used to obtain the imaging spectra of soybean leaves at 344 wavelengths. The spatial and spectral information including the entropy, mean reflectivity and standard deviation of the leaf images at different wavelengths were extracted; the chlorophyll content was retrieved using multiple linear regression (MLR) together with the spatial information and spectral information, and the results were compared with the results derived with the Analytical Spectral Devices (ASD, FieldSpecFR spectrometer, Analytical Spectral Devices Inc., USA) data that were generated using conventional single sensor spectrometers. The results demonstrated that the entropy, standard deviation and other features of the image were very good indicators of the leaf chlorophyll content, confirming the idea that spatial information can be used to retrieve chlorophyll content, with an accuracy equivalent to that of spectral information, and can provide information that spectral reflectivity cannot provide. Thus, integrating spatial information and spectral information can greatly improve the chlorophyll content retrieval accuracy and reduce the estimation errors by 20 %. Due to the unique measurement method and image-spectrum-in-one feature, the field imaging spectroscopy system (FISS) data can be conveniently used to achieve accurate chlorophyll content retrieval, and the retrieval error was reduced by 30–45 % compared with that for the ASD data. FISS data and the proposed method of integrating both spectral and spatial information of imaging spectroscopy have potential advantages in quantitative spectral analysis applied in agricultural biochemistry related fields.     

叶面喷施谷氨酸对柑桔叶绿素含量的影响

以柑桔为试验材料 ,研究了叶面喷施谷氨酸对其叶绿素的影响。结果表明 ,经过叶面喷施谷氨酸后 ,其叶绿素含量都有所提高 ,这一生理指标在一定程度上的提高 ,将会增强柑桔树的光合作用     

鲜食型甜玉米叶片叶绿素含量的遗传分析

以8个甜玉米亲本为研究对象,采用Griffing双列杂交法Ⅱ,对玉米叶片叶绿素含量的遗传特性进行了系统分析。结果表明,8个自交系叶绿素含量的一般配合力(GCA)值为T1T33T8T3T7T5T4T14,其中T1、T8和T33叶绿素含量的GCA较高,可以提高杂交组合的叶绿素含量,但特殊配合力存在明显的组合差异。自交系利用价值的综合评价表明,T8和T33是选育叶片高叶绿素含量的理想亲本。玉米叶片叶绿素含量性状的遗传符合加性-显性-上位性模型,以基因非加性效应为主,存在着显著的显性与上位性效应;控制玉米叶绿素含量遗传增效等位基因为隐性。广义遗传率为63.92%,狭义遗传率为15.90%。可见,在高光效育种工作中,对叶绿素含量选择宜在高代进行,同时利用叶绿素含量高的自交系作为亲本并广泛测配有利于叶片高叶绿素杂交种选育。     

Determination of differences in crop injury from aerial application of glyphosate using vegetation indices

Crop injury caused by off-target drift of herbicide can seriously reduce growth and yield and is of great concern to farmers and aerial applicators. Farmers can benefit from identifying an indirect method for assessing the level of crop injury. This study evaluates the combined use of statistical methods and vegetation indices (VIs) derived from multispectral images to assess the level of crop injury. An experiment was conducted in 2009 to determine glyphosate injury differences among the cotton, corn, and soybean crops. The crops were planted in eight rows spaced 102 cm apart and 80 m long with four replications. Seven VIs were calculated from multispectral images collected at 7 and 21 days after the glyphosate application (DAA). At each image collection date, visual injury estimates were assessed and data were collected for plant height, chlorophyll content, and shoot dry weight. From the seven VIs evaluated as surrogate for glyphosate injury identification using a canonical correlation analysis (CCA), the Chlorophyll Vegetation Index (CVI) showed the highest correlation with field-measured plant injury data. CVI image values were subtracted from the CVI average values of the non-injured area to generate CVI residual images (CVI_res). Frequency distribution histograms of CVI_res image values were calculated to assess the level of injury between crops. These data suggested that injury increased from 7DAA to 21DAA with corn exhibiting higher severity of injury than cotton or soybean, while only moderate injury was observed for cotton. The techniques evaluated in this study are promising for estimating the level of glyphosate herbicide drift, which can be used to make appropriate management decisions considering crop proximity.     

Comparison between vegetation indices for detecting spatial and temporal variabilities in soybean crop using canopy sensors

Precision Agriculture - Crop monitoring through remote sensing techniques enable greater knowledge of average variability in crop growth. Canopy sensors help provide information on the variability...     

不同光照度生境对海芋块茎形态、淀粉含量及叶绿素含量的影响

【目的】了解海芋Alocasia macrorrhiza对不同光照度生境的响应,明确在海芋试验中叶绿素仪测定叶绿素的精确度,以期为大面积的成龄胶园林荫下土地资源利用及叶绿素仪在海芋生理试验中正确应用提供理论依据和技术支持。【方法】采用SPAD-502叶绿素仪和乙醇-丙酮浸提法对不同光照度下海芋不同叶片的SPAD值、叶绿素a、叶绿素b和总叶绿素含量进行测定。【结果】与自然光照下的海芋相比,林荫下海芋的块茎长度增加了12.11%,茎围和淀粉含量则分别降低了15.08%和12.96%。自然光照下海芋的SPAD值、叶绿素a、叶绿素b及总叶绿素含量均比在林荫下生长的海芋低,但叶绿素a与叶绿素b含量的比值要高。自然光照下海芋叶片SPAD值呈现从倒1叶至倒5叶逐渐增加的趋势(倒3叶除外)。林荫下生长的海芋叶片SPAD值从倒1叶至倒2叶是增加的,从倒3叶至倒5叶逐渐降低,最大值在倒2叶。光照强度对不同叶片的叶绿素a、叶绿素b及总叶绿素含量的影响趋势与SPAD值的影响趋势一致,只是影响幅度不同。【结论】光照有利于海芋淀粉的合成。光照不足的情况下,海芋会通过增加叶片(特别是上层叶片)的SPAD值、叶绿素a、叶绿素b及总叶绿素含量来捕获光能。在自然光照下,利用海芋倒4叶的SPAD值更能准确地预测其叶绿素的绝对含量,而在林荫下生长的海芋倒5叶的SPAD值更能准确地预测其叶绿素的绝对含量。     

叶绿素仪CCM-200在测定茶树叶片叶绿素 和氮素含量上的应用

叶绿素仪是一种快速、无损地测定植物叶片叶绿素和氮素含量的有效工具。采用分光光度计法和凯氏定氮法分别测定茶树叶片叶绿素含量和氮素含量,并与叶绿素仪测定的CCI值进行相关性分析。结果表明,CCI值与叶绿素含量均呈显著正相关,其中单位面积叶绿素a(R2为0.972 8)、b(R2为0.858 6)及总量(R2为0.977 4)与CCI值的相关性均高于单位质量叶绿素含量与CCI值的相关性;不同品种茶树叶片叶绿素含量差异明显,但仍与其CCI值有良好的线性关系。研究还显示,CCI值和叶片全氮含量之间呈显著线相关性,其R2为0.982 8。说明叶绿素仪CCM-200在茶树叶片叶绿素和氮素含量估算上具较好的适用性。     

基于高光谱植被指数的西北玉米不同时期叶绿素含量估测

以陕西省扶风县马席村、巨良农场和杨凌区揉谷乡种植的大田玉米为试验材料,分别测定玉米抽雄期、灌浆期和乳熟期的冠层光谱反射率和叶片叶绿素含量,分析冠层各光谱植被指数与叶片叶绿素含量之间的相关关系,建立玉米叶绿素含量估测模型。结果表明,以单变量光谱植被指数估算叶绿素含量,抽雄期的最佳模型由修正叶绿素吸收反射率指数(Modified chlorophyll absorption reflectivity index,MCARI)建立,灌浆期最佳模型由垂直植被指数(Perpendicular vegetation index,PVI)建立,乳熟期最佳模型由植被衰老反射率指数(Plant senescence reflectance index,PSRI)建立。随着玉米生长期的推进,叶片衰老,用PSRI所建立的模型来监测玉米叶绿素含量的效果较好,可为高光谱遥感在玉米长势监测提供理论依据和技术支持。     

Mapping within-field leaf chlorophyll content in agricultural crops for nitrogen management using Landsat-8 imagery

Precision Agriculture - Spatial information on crop nutrient status is central for monitoring vegetation health, plant productivity and managing nutrient optimization programs in agricultural...     

植被冠层氨释放及其对草地氨挥发贡献与源解析

为原位监测不同植被的草地土壤与冠层氨挥发,并考察不同植被冠层氨释放的生理机制及其对草地氨挥发的贡献,本研究选择3个品种（麦冬、高羊茅和狗牙根）,每个品种设置3个施肥处理（不施氮、30 g·m-2缓释尿素和30 g·m-2尿素）。采用泵吸式便携氨气探测仪原位监测土壤和冠层氨挥发,采用酶联免疫法测定叶片的乙醇酸氧化酶（GO...     

基于物理模型与查找表策略的南繁水稻叶片叶绿素含量反演研究

【目的 】利用海南省中南部5市县采集的南繁水稻光谱、叶绿素等数据,研究物理模型与查找表策略对南繁水稻叶片叶绿素的反演,并对不同查找表进行比较分析。【方法 】文章先根据研究区调查与文献调研,利用辐射传输模型PROSAIL-PRO模拟2万条冠层光谱,分别构建波长400～1 000 nm区间的全波段查找表和双植被指数(Vegetation Index,VI)查找表,并使用实测的南繁水稻冠层光谱与叶绿素含量进行验证。其中,双VI查找表包括TCARI-OSAVI查找表、比值型植被指数(Ratio Vegetation Index,RVI)查找表和红边相对指数(Red Edge Relative Indices,RERI)查找表3种。【结果 】(1)传统的全波段查找表反演叶片叶绿素含量的精度较差,R值为0.46,均方根误差(Root Mean Squared Error,RMSE)为8.84μg/cm²,正规化均方根误差(Normalized Root Mean Squared Error,NRMSE)为0.32。(2)双VI查找表反演结果较传统查找表更好,TCARI-OSA...     

铁观音茶树不同叶位和氮肥用量对叶片叶绿素含量的影响

研究了铁观音茶树不同叶位和施氮量对叶片叶绿素含量的影响,结果表明：第2、3位叶,第5、6位叶和隔年老叶的叶绿素含量随叶片生长时间延长呈增加趋势;随着氮肥用量的增加,百芽重、芽头密度和茶青产量随之增加,叶绿素含量也呈增加趋势.