荒漠土壤有机质含量高光谱估算模型

为解决荒漠土壤有机质含量高光谱估算存在的困难,提高土壤有机质含量估算的精准性,该文对准噶尔盆地东部荒漠土壤进行采样、化验分析和光谱测量、处理,分析土壤光谱与有机质含量的相关性,确定敏感光谱波段,建立荒漠土壤有机质含量多种高光谱估算模型,旨在通过模型精度的比较,确定最优模型。结果表明：反射率、倒数对数光谱与荒漠土壤有机质含量相关性低,而经过一阶微分、二阶微分变换后,相关系数有所提高,部分波段的相关系数通过0.01显著水平的检验,可以用来荒漠土壤有机质含量的估算;一元线性回归建立的估算模型的精度低,不适用荒漠土壤有机质含量高光谱的估算。荒漠土壤有机质多元逐步回归模型的二阶微分、倒数对数二阶微分修正决定系数得到了较大提高,分别提高了0.22和0.31,均方根误差下降了0.66和0.80,建模精度高于一元线性回归模型。荒漠土壤有机质一阶微分、二阶微分光谱的最小偏二乘回归模型的决定系数比其多元逐步回归模型提高了0.07、0.04,一阶微分、二阶微分均方根误差都下降了0.11,二阶微分偏最小二乘法回归模型是该研究所建12个模型的最优估算模型。在多元逐步、偏最小二乘回归模型中,最优估算模型是二阶微分模型,因而用偏最小二乘法回归估算荒漠土壤有机质含量是个可行的方法。该研究的成果为荒漠土壤有机质高光谱遥感分析提供了支撑,实现荒漠土壤有机质监测的时效性、准确性,为区域生态环境的修复提供依据。     

应用可见/近红外高光谱成像测定鲑鱼片脂肪含量分布(英文)

脂肪作为一种重要的品质参数,在大西洋鲑鱼片中的分布很不均匀。为寻找一种能替代脂肪化学检测的快速无损的方法,该研究应用可见/近红外高光谱成像测定大西洋鲑鱼片的脂肪含量分布。分别采用可见/短波近红外(400-1100 nm)和近红外(900-1700 nm)系统获取大西洋鲑鱼片样本的高光谱图像。提取样本图像的平均光谱并与其相应的脂肪含量化学值采用偏最小二乘回归(partial least squares regression,PLSR)和最小二乘支持向量机(least-squares support vector machines,LS-SVM)建立相关性模型。为降低高光谱图像的共线性和冗余度,基于竞争性自适应重加权算法(competitive adaptive reweighted sampling,CARS)分别在可见/短波近红外和近红外光谱区间提取16个(468,479,728,734,785,822,863,890,895,899,920,978,1005,1033,1040,1051 nm)和15个(975,995,1023,1047,1095,1124,1167,1210,1273,1316,1354,1368,1575,1632,1661 nm)特征波长,并分别建立PLSR和LS-SVM模型。特征波长模型的性能优于全波段模型,且近红外区间的特征波长PLSR模型为最优,预测决定系数(R2p)为0.92,预测均方根误差(root mean square error of prediction,RMSEP)为0.92%,剩余预测偏差(residual predictive deviation,RPD)为3.50。最后,将最优模型用于预测高光谱图像上所有像素点的脂肪含量以展示样本上脂肪的分布。此外,还基于该技术对大西洋鲑整鱼片实现了脂肪分布可视化。结果表明高光谱成像技术结合化学计量学方法在大西洋鲑鱼片脂肪的定量和分布可视化上有一定的研究和应用前景。     

Ureolytic Activity of Soybean and Corn Residue Extracts

The enzyme urease is responsible for the rapid hydrolysis of urea in agroecosystems where more than 50% of the applied nitrogen (N) can be lost via ammonia volatilization. The objectives of the study were to (1) extract urease from corn (Zea mays L.) and soybean (Glycine max L.) and (2) compare the urease activity from soybean and corn residues to Jackbean (Canavalia ensiformis) urease using Fourier transform infrared spectroscopy (FTI-R). Concentrations of urea and sodium bicarbonate ranging from 0 to 200 mM were analyzed with FTI-R to determine the correlation to peak height. Bicarbonate produced the most responsive peaks to concentration at 1,362 cm^?1. Urease extracted from soybean residue was active, producing a bicarbonate peak at 1362 cm^?1, whereas no urease activity was observed in corn residue. Variation among urease activities in crop residues could suggest a need for more precise nitrogen management in conservation tillage agroecosystems to reduce ammonia volatilization.     

基于冠层光谱的锦橙叶片磷素营养监测研究

以盆栽蓬安100号锦橙施肥调控试验为基础,利用田间冠层光谱信息探索建立植株磷素营养监测技术与方法。通过采集蓬安100号锦橙95个单株样本的冠层光谱信息和室内检测分析叶片磷含量,随机选取76个作为建模样本,19个为检验样本,运用多种光谱预处理方法和偏最小二乘法(Partial least square method,PLS)及内部交叉验证方法建立校正模型与模型检验。结果表明,经多种光谱预处理方法的建模结果比较,冠层原始反射光谱经二阶求导和SNV处理后建立的蓬安100号锦橙叶片磷含量冠层光谱监测模型预测能力和稳健性最佳,其主成分数4个,能表达全波段63%的信息;校正模型相关系数为0.90,偏差Bias=2.45E-10,且RMSEC和RMSEP均最小。模型检验预测的决定系数R2=0.85。因此,利用二阶导数及标准归一化(Standard normal variate transformation,SNV)预处理的田间冠层光谱信息快速无损监测蓬安100号锦橙叶片磷含量具有一定的可行性。     

土壤有机质与水分反射光谱响应特征综合作用模拟

土壤有机质与水分均对土壤反射光谱特征有显著的影响,但其作用机理难以定量描述。通过对黑龙江省典型黑土区土壤野外高光谱反射率的测定,研究了该区土壤的光谱反射特征;利用BP神经网络方法,以土壤有机质与水分数据作为输入层,以土壤光谱反射率一阶微分作为输出层,建立黑土有机质与水分的高光谱预测模型,并对模型的稳定性和预测能力进行检验。结果表明:土壤有机质与土壤表层0~20 cm含水量之间具有显著的相关性,相关系数为0.59;1570 nm波段处的一阶微分为输出层的模型精度最高,RMES达到0.017,平均绝对误差为0.014,平均相对误差为0.110;模型检验结果表明建立的BP神经网络模型具有良好的稳定性;土壤有机质、含水量对土壤光谱反射率的综合作用得到较准确的描述,可以用于野外土壤有机质与水分的速测。     

Fractionation of soil humic acids by preparative polyacrylamide gel electrophoresis in the presence of concentrated urea

To separate soil humic acids (HAs) into their constituents and characterize them, polyacrylamide gel electrophoresis (PAGE) was carried out in the presence of 7 M urea using a preparative electrophoresis system. Two types of soil HAs were fractionated into nine fractions by PAGE. The dark-colored constituents were recovered from the electrophoretic fractions by precipitation on acidification, and the brown-colored constituents dissolved in the acidic solution of fast-moving fractions were recovered by adsorption onto DAX-8 resin. High-performance size-exclusion chromatography (HPSEC) confirmed that the constituents of the HAs were separated based on their molecular size by PAGE. The dark-colored constituents exhibited higher degrees of humification than did the corresponding unfractionated HAs, except for the constituents remaining in the electrophoretic gels at the end of electrophoresis. Diffuse reflectance infrared spectroscopy revealed that the chemical properties of the dark-colored constituents changed regularly: the content of carboxyl groups decreased and the proportions of proteinous, aliphatic and polysaccharide moieties increased with increasing molecular size. The humification degrees of the constituents adsorbed onto DAX-8 resin were considerably lower than those of the corresponding unfractionated HAs. The chemical properties of the DAX-8-adsorbed constituents were different from those of the dark-colored constituents. Observation of electrophoretic fractions under blue light (470 nm) and HPSEC with fluorescence detection at an excitation wavelength of 460 nm and an emission wavelength of 520 nm showed that green fluorescent substances were largely concentrated in the smallest molecular size fractions and were partitioned into both the dark-colored precipitates and DAX-8-adsorbed fractions. The proportion of organic carbon recovered by precipitation and adsorption onto DAX-8 resin was 45–63%, indicating that substantial parts of the HA constituents were missing. The unrecovered constituents were considered to be acid-soluble, nearly colorless substances. The dissociation of the acid-soluble constituents from the acid-insoluble dark-colored constituents during the preparative PAGE of soil HAs was ascribed to disruption of hydrogen bonding and hydrophobic interactions caused by concentrated urea.     

不同施肥情况下甘蔗叶片的光谱特征分析及叶绿素含量检测

In order to investigate the visible-NIR spectral features of the leaves of a sugarcane variety(ROC 22), the spectral reflectance and the chlorophyll content were measured in the laboratory, and their correlations were analyzed.Prediction models were built eventually.Results showed that the negative correlations with r greater than 0.8 was found in 527-578 nm and 701-731 nm between spectral reflectance and chlorophyll content.And the red edge position(REP) was also found having high correlation with chlorophyll content, with the highest r of 0.8442.In order to explore the most sensitive bands for normalized difference vegetation index(NDVI), 48471 NDVI values were computed with different wavebands for each sample and their correlations with chlorophyll were also analyzed.The distribution maps of NDVI and its correlations in a two-spectral-dimension space both indicated that the red bands had significant influence than the NIR bands.The suggested sensitive red range was 710-735 nm, especially 720-725 nm; and the sensitive NIR range was from 780-850 nm, which had the higher robustness.The chlorophyll predication model with NDVI(725 and 840 nm) in tillering stage had determination coefficients of 0.7386, and was recommended for guiding the subsequent ridging fertilization.     

基于多光谱与高光谱遥感数据的冬小麦叶面积指数反演比较

近年来,高光谱遥感数据广泛应用于农作物叶面积指数(LAI)反演。与常用的多光谱遥感数据相比,高光谱数据能否提高农作物LAI反演的精度和稳定性还存在争议。针对这一问题,该研究利用实测冬小麦冠层高光谱反射率数据,构造了不同光谱分辨率和波段组合的5种光谱数据。基于ACRM(a two-layer canopy reflectance model)模型、2套参数化方案及上述5种光谱数据,对冬小麦LAI进行反演,分析光谱分辨率、高光谱数据波段选择、模型参数不确定性3方面因素对LAI反演精度与稳定性的影响。研究结果表明:当波段选择适宜、模型参数不确定性较小且光谱数据分辨率较高时,LAI反演精度与稳定性更高,提高光谱分辨率对LAI反演精度的改进作用随光谱分辨率的升高而降低;反之,当高光谱数据波段选择不当或者模型参数不确定性较大时,提高光谱数据的分辨率并未提高LAI反演精度。该研究解释了"高光谱遥感数据能否提高植被参数反演精度"问题,为进一步发挥高光谱数据在农作物LAI反演中的潜力提供了科学参考。     

用核磁共振研究浸种方法对水稻种子吸水量的影响

为寻求较佳浸种方法,该文应用低场核磁共振检测技术,研究了不同的浸种方式及浸种溶剂对水稻种子吸水量的影响。试验利用横向弛豫时间 T2反演谱分析了水稻种子的水分状态变化及吸水特性,发现浸种过程改变了水稻种子内部的水分分布情况,水稻种子吸水量对初始含水率差异不显著(P>0.05),但对各种浸种方法差异显著(P<0.05)。研究表明,采用连续浸种4 h、浸种3 h-晾干1 h-浸种1 h、浸种2 h-晾干1 h-浸种2 h及浸种2 h-晾干2 h-浸种2 h这4种不同的浸种方式时,浸种2 h-晾干1 h-浸种2 h的间歇浸种方式吸水率较高;采用清水、强氯精300倍液、饱和澄清石灰水、质量分数为40%福尔马林的50倍液、100倍液及200倍液6种不同的浸种溶液时,应用质量分数为40%福尔马林50倍液药剂时吸水率较高。低场核磁共振检测技术揭示了水稻种子含水量的影响因素,为浸种过程中吸水量的测定提供了一种有效的方法。     

用低场核磁共振检测水稻浸种过程中种子水分的相态及分布特征

为研究水稻浸种过程中种子的水分相态及其分布特征,利用低场核磁共振快速、无损、准确的检测技术,通过硬脉冲回波序列CPMG(carr-purcell-meiboom-gill sequence)测量水稻种子横向弛豫时间T2,根据横向弛豫时间T2的差异区分种子内部的水分相态及其变化规律。试验结果表明:通过T2反演谱横向弛豫时间T2长短的差异,发现水稻浸种过程中种子内部水分存在结合水、自由水2种水分状态,同时可区分出内层水、中层水、外层水3种水分分层;二者均能通过回归方程合理的估测水稻在浸种过程中种子的吸水率情况;通过T2反演谱信号幅值大小的差异,发现水稻浸种过程中的种子总水含量不断上升,但由于判定依据及划分方式的不同,二者在水分的流动方式上略显差异。低场核磁共振技术对水稻浸种过程中种子内部的水分变化进行了直观的揭示,提供了一种高效的种子水分检测方法。