基于高光谱数据的盐荒地和耕地土壤盐分遥感反演优化

盐荒地作为研究区的\     

Quantification of exopolysaccharide, lactic acid, and lactose concentrations in culture broth by near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) was used for the simultaneous prediction of exopolysaccharide (EPS; 0-3 g/L) and lactic acid (0-59 g/L) productions as well as lactose (0-68 g/L) concentration in supernatant samples from pH-controlled batch cultures of Lactobacillus rhamnosus RW-9595M in supplemented whey permeate medium. To develop calibration equations, the correlation between the second derivative of 164 NIRS transmittance spectra and concentration data obtained with reference methods was calculated at the wavelength between 1653-1770 and 2041-2353 nm, using a partial least-squares method (PLS). The lactic acid and lactose concentrations were measured by HPLC, and the EPS concentration was estimated by a new ultrafiltration method. The PLS correlation coefficient (R(2)) and the standard error of cross-validation for the calibrations were 91% and 0.26 g/L for EPS, 99% and 2.54 g/L for lactic acid, and 98% and 3.32 g/L for lactose, respectively. The calibration equations were validated with 45 randomly selected culture samples from 6 cultures that were not used for calibration. A high agreement between data of the reference methods and those of NIRS was observed, with correlation coefficients and standard errors of prediction of 99% and 1.64 g/L for lactic acid, 99% and 4.5 g/L for lactose, and 91% and 0.32 g/L for EPS. The results suggest that NIRS could be a useful method for rapid monitoring and control of EPS lactic fermentations.     

Single Wheat Kernel Color Classification by Using Near-Infrared Reflectance Spectra

An optical radiation measurement system, which measured reflectance spectra, log (1/R), from 400 to 2,000 nm, was used to quantify single wheat kernel color. Six classes of wheat samples were used for this study, including red wheat that appears white and white wheat that appears red. Partial least squares regression and multiple linear regression were used to develop classification models with three wavelength regions, 500–750, 500–1,700, and 750–1,900 nm, and three data pretreatments, log (1/R), first derivative, and second derivative. For partial least squares models, the highest classification accuracy was 98.5% with the wavelength region of 500–1,700 nm. The log (1/R) and the first derivative yielded higher classification accuracy than the second derivative. For multiple linear regression models, the highest classification accuracy was 98.1% obtained from log (1/R) spectra from the visible and near-infrared wavelength regions.     

褐潮土的光谱特性及用土壤反射率估算有机质含量的研究

本文通过ASDFR便携式光谱仪对132个风干土壤样品的光谱反射率进行了实验室测定。根据土样光谱反射率变化,获得了褐潮土土壤剖面的不同诊断层反射光谱特征。结果表明,在400～1200nm范围之间,土壤有机质含量与土壤光谱反射率有较好的相关性。利用导数光谱方法建立了预测土壤有机质含量的方程,提出了预测北京地区褐潮土有机质光谱的最佳波段。在波长447nm处采用反射率和A值(反射率倒数的对数)所建立的预测方程的预测精度较高。采用反射率的一阶微分建立的预测方程的最佳波段在516nm处。而A值一阶微分光谱在615nm处相关性最好。作为一项参考指标用光谱分析法评价土壤中有机质含量,以期对精准农业中土壤养分或肥力的预测具有一定的指导作用。     

光谱特征变量和BP神经网络构建油用牡丹种子含水率估算模型

为了进一步提高种子含水率的高光谱估算精度,该研究测定了156份油用牡丹种子的近红外吸收光谱及其对应的含水率值,分析了近红外吸收光谱、一阶微分光谱、水分吸收特征参数与含水率的相关关系,构建了基于特征波长吸收光谱、特征波长一阶微分光谱、水分特征吸收参数和BP神经网络的油用牡丹种子含水率估算模型,并对模型进行了验证;再结合一元线性回归（SLR,Single Linear Regression）、逐步多元线性回归（SMLR,Stepwise MultipleLinear Regression）、偏最小二乘回归（PLSR,Partial Least Squares Regression）模型与BP神经网络（BPNN,BP Neural Network）模型进行比较。结果表明：1）油用牡丹种子含水率的吸收光谱特征波长位于1 410、1 900、1990 nm,一阶微分光谱特征波长位于1 150、1 950、2 080 nm;2）以DF2080和AD2140为自变量建立的一元线性回归模型预测效果较优,在能够满足水分估算精度的情况下,是最优的选择方法。3）将优选的特征参数作为输入,实测含水率值作为输出,构建BP神经网络模型,其建模与验模R2分别为0.978和0.973,RMSE分别为0.22%和0.242%,而RPD值分别为6.478和5.889,与其他模型相比,BP神经网络模型的建模及预测精度均最高,是估算油用牡丹种子含水率的最优模型,其次为逐步多元线性回归模型。研究结果表明BP神经网络模型对种子含水率具有更好的预测能力,是估算油用牡丹种子含水率的有效方法。     

Effect of phosphate and sulfate fertilizers on selenium uptake by wheat (Triticum aestivum)

The objective of this study was to investigate whether oxyanionic phosphate (P) and sulfate (S) fertilizer management could influence selenium (Se) uptake by wheat (Triticum aestivum) in medium and high Se areas. Field studies were established at two locations for two growing seasons in central South Dakota, USA. Phosphate fertilizer was applied using three different methods (banded with seed, surface-broadcasted in the fall, or surface-broadcasted in the spring) using six different P rates. Sulfate fertilizers were broadcasted at four rates in the fall. Selenium concentration in wheat grain was significantly influenced by the interaction of P application methods and rates, but it was dependent on location. Grain Se concentration decreased in high Se availability soil when P fertilizer was applied, due to the dilution effect. Grain Se concentration and uptake was significantly decreased as S applications increased due to the competition effect, but the depression was apparent in high Se availability soil. The results from this study showed that P and S fertilizer management can influence Se level in wheat grain grown in naturally high Se areas, even though overall grain Se level was strongly associated with location variation.     

不同土壤含水率、体积质量及光谱反射率的关系模型

为了准确、快速地检测湿胀干缩型土壤含水率,该文提出了基于近红外光谱技术的土壤含水率分析方法。该文以湖北省黄棕壤、潮土、水稻土为研究对象,利用美国Ocean Optic公司的NIR256-2.5微型光纤光谱仪在暗室环境下对不同含水率下的土壤样本进行光谱反射率的测定和特征分析,并同时测量相应的土壤体积质量,研究土壤含水率、体积质量、光谱反射率之间的相关关系,通过采用2种土壤含水率表示方法与3种土壤光谱反射率表示方法反映土壤含水率与光谱反射率之间关系的对比试验分析,消除土壤其它性状对土壤反射率反演土壤含水率的影响,得到较适宜地进行土壤光谱反射率反演土壤含水率的匹配表示方法,构建三者之间关系的曲面模型和体积质量变化的土壤体积含水率与土壤光谱反射率的关系指数模型。研究结果表明,构建的3种土壤的曲面回归模型,决定系数均大于0.977,F值均达极显著水平,光谱反射率与体积质量的偏回归系数检验亦达显著或极显著水平。采用指数模型表述1 400、1 900 nm波长处的归一化减土光谱反射率与体积质量变化的土壤体积含水率的关系,其决定系数均在0.9以上,对模型进行验证,其预测误差在0.3左右,精度较高,所建模型拟合效果好。该研究可为用近红外光谱检测体积质量变化的土壤含水率提供科学资料。     

Comparison of nosespace,headspace, and sensory intensity ratings for the evaluation of flavor absorption by fat

The goal of this study was to better understand the correspondence between sensory perception and in-nose compound concentration. Five aroma compounds at three different concentrations increasing by factors of 4 were added to four matrixes (water, skim milk, 2.7% fat milk, and 3.8% fat milk). These were evaluated by nosespace analysis with detection by proton transfer reaction mass spectrometry (PTR-MS), using five panelists. These same panelists evaluated the perceived intensity of each compound in the matrixes at the three concentrations. PTR-MS quantification found that the percent released from an aqueous solution swallowed immediately was between 0.1 and 0.6%, depending on the compound. The nosespace and sensory results showed the expected effect of fat on release, where lipophilic compounds showed reductions in release as fat content increases. The effect is less than that observed in headspace studies. A general correlation between nosespace concentration and sensory intensity ratings was found. However, examples of perceptual masking were found where higher fat milks showed reductions in aroma compound intensity ratings, even if the nosespace concentrations were the same.     

不同品种水稻糙米对Cd Cu Zn积累特性的研究

以酸性矿山废水污染的含有多种重金属的农田土壤为供试土壤,通过盆栽实验,研究不同水稻品种,不同类型、不同遗传背景水稻糙米重金属Cd、Cu、Zn的积累差异。结果表明,供试水稻糙米Cd含量为0.006～0.092mg·kg-1,最高值和最低值相差15倍;Cu含量为6.712～27.117mg·kg-1,最高值和最低值相差4倍;Zn含量为28.390～43.296mg·kg-1,最高值和最低值相差不到1倍。常规稻和杂交稻糙米的Cd、Cu、Zn含量差异不明显。三系杂交稻的糙米Cd、Cu含量极显著高于二系杂交稻,而二系杂交稻糙米中Zn含量则显著高于三系杂交稻。不同遗传背景水稻品种糙米Cd、Cu、Zn含量也存在明显差异。相关分析结果表明,糙米中Cu、Cd含量间呈极显著正相关,Cu、Zn含量之间存在显著负相关,而Cd、Zn含量间的相关性不明显。     

基于分数阶微分的盐渍土电导率高光谱估算研究

传统电导率的反演模型采用整数阶微分(1阶或2阶)的预处理方法,忽略位于分数阶微分处的高光谱反射率信息。因此,本研究提出一种基于分数阶微分的盐渍土电导率高光谱估算方法,以新疆昌吉回族自治州境内的盐渍化土壤为研究靶区,于2017年5月采集0～20 cm的表层土壤样品,利用FieldSpec?3 Hi-Res光谱仪测量盐渍土的野外高光谱,并在实验室化验土壤的电导率理化参数。在Matlab2019a软件中编程实现0阶-2.0阶的Grünwald-Letnikov分数阶微分计算(阶数间隔为0.1)。分析土壤高光谱与电导率的相关系数曲线在21种微分处的变化规律,选择每阶微分的最大相关系数大于0.5时对应的波长为敏感波长,采用逐步多元线性回归模型对电导率进行预测。结果表明:分数阶微分预处理方法能够把相关系数曲线位于不同分数阶时的变化细节呈现出来,在全波段范围内出现更多的波峰和波谷信息。电导率的8个敏感波长为400 nm、418 nm、567 nm、1 667 nm、2 132 nm、2 193 nm、2 257 nm和2 258 nm。估算电导率的最佳模型位于分数阶1.5阶,其验证集的RPD值为1.99, R~2为0.81, RMSE为1.08,该模型因RPD值大于1.8对电导率的估算能力好。本研究探索了电导率在不同分数阶微分处的差异信息,为电导率的估算提供一种新的研究思路,对新疆干旱区盐渍土的改良提供了科学可靠的依据。     

Comparison of experimental methods for measuring infinite dilution volatilities of aroma compounds in water/ethanol mixtures

Several experimental methodologies exist for measuring volatilities; however, results show great dispersion and sometimes lack of agreement between different methods. The aim of our study was to compare the performance of three static headspace methods (vapor phase calibration, VPC; phase ratio variation, PRV; and liquid calibration static headspace, LC-SH) for determining gas/liquid partition coefficients of two aroma compounds in hydroalcoholic multicomponent solutions at infinite dilution. Comparison with literature data based on static and dynamic methods showed that PRV is simpler than VPC and LC-SH and that VPC and PRV are more accurate than LC-SH, which presented a significant bias (50% lower values).     

基于BP神经网络的橡胶苗叶片磷含量高光谱预测

为验证高光谱技术在橡胶苗叶片磷素营养诊断方面的可行性,该文以砂培橡胶苗为研究对象,利用高光谱仪测得不同磷处理水平下橡胶苗叶片光谱反射率,并应用微分技术求取去噪后光谱反射率一阶和二阶导数,以叶片磷含量和光谱变量相关性分析为基础,选择出叶片磷含量敏感波段,最后以敏感波段为输入变量,结合多重线性回归、偏最小二乘回归和反向传播神经网络模型对叶片磷含量进行预测。结果表明:原始光谱反射率555和722 nm、一阶导数674、710、855、1 091、1 197、1 275、1 718、2 181和2 228 nm以及二阶导数816、890、1 339、1 357和2 201 nm为叶片磷含量敏感波段;反向传播神经网络模型预测精度最高,训练集和验证集中预测值和实测值之间的相关系数r分别为0.964和0.967,均方根误差RMSE分别为0.0139和0.00856,模型性能指数(ratio of performance to deviation,RPD)分别为3.71和3.23,证明高光谱技术可以快速、准确诊断橡胶苗叶片磷含量。     

柑橘黄龙病高光谱早期鉴别及病情分级

为实现柑橘黄龙病的早期、快速确诊,有效阻止病害蔓延,达到早期防治、保障柑橘生产的目的,该文研究基于高光谱成像的柑橘黄龙病早期无损检测及病情分级,并对多种预处理方法的建模结果进行探讨。试验获取370～1 000 nm健康、不同染病程度及缺锌共5类柑橘叶片的高光谱图像,用遥感图像处理平台(environment for visualizing images,ENVI)得到各类样本感兴趣区域的光谱反射率平均值。运用一阶微分、移动窗口拟和多项式平滑(savitzky-golay,SG)进行数据处理,结合偏最小二乘判别分析(partial least squares-discriminate analysis,PLS-DA)构建黄龙病的早期鉴别及病情分级模型。结果表明:建立的3个判别模型,验证集相关系数均不低于0.9548。其中,经SG平滑及一阶微分预处理所建立的模型分类效果最佳,总体预测准确率达96.4%,预测均方根误差0.1344。该研究为柑橘病害早期诊断和预警提供了新方法,也为黄龙病病害程度遥感监测提供了基础。     

Diurnal,shade, and hybrid effects on nitrate content of young corn stalks

Abstract

Significant correlations have been found between the nitrate concentration in young corn (Zea mays L.) stalks and available soi 1 N and relative grain yield when N availability is a yield limiting factor. To successfully use nitrate tissue testing as an indicator of the N status of plants, the effects of factors other than soil or fertilizer N on the nitrate concentration in the tested tissue must be understood. Diurnal effects on stalk nitrate content were studied in a greenhouse experiment, in which stalk samples were collected every two hours for 24 hours, and in a field study, where plants in an N‐fertilizer response experiment were sampled at sunrise and at mid‐day. A significant diurnal cycle was observed for stalk nitrate content in the greenhouse, with a peak at 0800 h and a low at 1400 h, but no diurnal effect was found in the field study, possibly due to plant stress from other environmental factors. In a second greenhouse study, stalk samples from seedlings in direct and 66% shaded natural light were collected for two consecutive days and measured for nitrate content to ascertain the consequences of sampling on overcast days. Significant accumulations of nitrate occurred in stalks of plants sampled after two consecutive days of shading. Stalk samples from three standard hybrid corn trials in central Pennsylvania were measured for nitrate content to determine if hybrid differences existed. Hybrid differences in stalk nitrate were significant in only one of the three sites studied, and the variation in that one may have been due to differences in drought tolerance as well as nitrate metabolism. The results suggest that sampling strategies should be designed to minimize the effects of irradiance level on nitrate accumulation, but that differences in nitrate accumulation among corn varieties may not be a major concern in using nitrate tissue tests to predict N availability.     

Description of Chemical Changes Implied During Bread Dough Mixing by FT‐ATR Mid‐Infrared Spectroscopy

The aim of the present study was to investigate the ability of mid‐infrared (MIR) spectroscopy to identify physicochemical changes in the French bread dough mixing process. An ATR FT‐MIR spectrometer at 4000–800 cm^–1 was used. The MIR spectra collections recorded during mixing were analyzed after standard normal variate using principal component analysis (PCA) and after second‐derivative treatment. The results were interpreted in terms of chemical changes involved in dough development and more particularly in terms of secondary structural protein changes (amide III). The loading spectrum associated with principal component 1 (PC1) allows three MIR wave number regions of variations (3500–3000, 1700–1200, and 1200–800 cm^–1) to be identified. The loading spectrum associated with PC1 describes an increase in the relative protein band intensities and a decrease in relative water and starch band intensities. The variation during bread dough mixing time of the different amide III bands identified after the second‐derivative show that α‐helical, β‐turn, and β‐sheet structures increase while random coil structure decreases, suggesting that the gluten structure is becoming a more ordered structure. The MIR mixing time identified as being the maximum scores value on the PC1 scores plots was associated with the time at which the dough apparent torque begin to collapse, suggesting that the MIR spectroscopy could monitor bread dough development.     

The analysis of vegetation for total mercury

Over four hundred vegetation samples were collected for total Hg determination as part of a biogeochemical survey in the Precambrian Shield region near Huntsville, Ontario. An objective of the survey was to obtain accurate data describing the spatial and temporal variation of Hg concentrations in vegetation. Five tree species, clubmosses, mosses, lichen and fungi were collected along three transects each 8 to 10 km long. The samples were digested using a hot H₂SO₄/HNO₃ mixture followed by cold-vapor AAS detection. Very low detection limits (less than 1.0 ng g⁻¹) were achieved by performing the analyses in a clean, Hg-free laboratory. The Hg concentration of coniferous needles did not vary significantly over eight weeks of the summer, but did vary significantly between first and second year growth. In all tree species examined, Hg concentrations in needles/leaves were two to three times as high (by dry weight) as that in twig tissue from the same branch. Differences in Hg content between tissues of different types and ages constituted a major source of within-site variation between plants of the same species.     

不同水分处理对烟草叶片高光谱及红边特征的影响

采用ASD Fieldspec HH光谱仪, 测定了不同水分处理下两个烟草品种叶片的光谱特性, 分析其红边特征参数的变化规律及其与烟叶生理指标的相关性。结果表明: 不同水分处理之间的烟草叶片光谱反射率差异明显, 但两个品种的变化规律一致。烟草伸根期和旺长期, 近红外光区的光谱反射率随土壤水分的增加而升高, 成熟期则呈相反趋势, 且光谱反射率在旺长期达到最高值。不同水分处理下烟草叶片一阶微分光谱趋势总体一致, 但红边一阶导数光谱差异显著。红边位置随土壤水分减少向长波方向移动, 发生“红移”现象。红边幅值和红边面积在伸根期和旺长期均随土壤含水量的增加而发生“红移”现象, 成熟期则发生“蓝移”现象。烟草叶片的红边位置同其生理指标的相关性要优于其他参数, 同叶绿素a含量、叶绿素b含量、类胡萝卜素含量、叶绿素总量、叶片鲜重、叶片干重、叶面积和叶片含水率均呈极显著相关关系; 红边幅值和红边面积与叶绿素a含量、叶绿素b含量、类胡萝卜素含量、叶绿素总量和叶片含水率之间均呈极显著性正相关, 红边面积同叶片干重呈极显著性负相关关系。     

Quantitation of indomethacin, naproxen, and ibuprofen in pharmaceutical dosage forms by first and second derivative ultraviolet spectrometry

First and second derivative ultraviolet spectrometric methods are described for the estimation of indomethacin, naproxen, and ibuprofen in pharmaceutical dosage forms. The proposed methods permit the rapid, precise, and accurate determination of indomethacin capsules BP, naproxen capsules, and ibuprofen tablets BP. Matrix interference is successfully corrected. The results obtained by first and second derivative techniques are in accord with those obtained by the official assay method.     

基于可见-近红外光谱识别氧乐果污染的脐橙

该文对喷施过不同浓度氧乐果农药的脐橙样品采集可见-近红外光谱进行识别。采用多元散射校正（MSC）、标准正交变量变换（SNV）、一阶导数（FD）和二阶导数（SD）4种不同光谱预处理方法时,分别选取430～1 000、1 000～1 800和430～1 800 nm 3种波谱范围建立偏最小二乘法（PLS）农药污染预测模型。比较实验结果表明：波谱范围取430～1 000 nm,采用一阶导数的预处理方法时应用建立的PLS预测模型最优,其验证组脐橙表面氧乐果污染程度的实际类别与预测类别的相关系数Rpred为0.9817,预测样本均方根误差RMSEP是0.1564。