Optimal waveband identification for estimation of leaf area index of paddy rice

The objectives of the study were to select suitable wavebands for rice leaf area index （LAI） estimation using the data acquired over a whole growing season, and to test the efficiency of the selected wavebands by comparing them with feature positions of rice canopy spectra. In this study, the field experiment in 2002 growing season was conducted at the experimental farm of Zhejiang University, Hangzhou, China. Measurements of hyperspectral reflectance （350-2500 nm） and corresponding LAI were made for a paddy rice canopy throughout the growing season. And three methods were employed to identify the optimal wavebands for paddy rice LAI estimation： correlation coefficient-based method, vegetation index-based method, and stepwise regression method. This research selected 15 wavebands in the region of 350-2500 nm, which appeared to be the optimal wavebands for the paddy rice LAI estimation. Of the selected wavebands, the most frequently occurring wavebands were centered around 554, 675, 723, and 1633 rim. They were followed by 444, 524, 576, 594, 804, 849, 974, 1074, 1219, 1510, and 2194 rim. Most of them made physical sense and had their counterparts in spectral known feature positions, which indicates the promising potential of the 15 selected wavebands for the retrieval of paddy rice LAI.

Discriminant Analysis of Liquor Brands Based on Moving-Window Waveband Screening Using Near-Infrared Spectroscopy

Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.

Waveband Selection with Equivalent Prediction Performance for FTIR/ATR Spectroscopic Analysis of COD in Sugar Refinery Waste Water

The level of chemical oxygen demand(COD)is an important index to evaluate whether sewage meets the discharge requirements,so corresponding tests should be carried out before discharge.Fourier transform infrared spectroscopy(FTIR)and attenuated total reflectance(ATR)can detect COD in sewage effectively,which has advantages over conventional chemical analysis methods.And the selection of characteristic bands was one of the key links in the application of FTIR/ATR spectroscopy.In this work,based on the moving window partial least-squares(MWPLS)regression to select a characteristic wavelength,a method of equivalent wavelength selection was proposed combining with paired t-test equivalent concept.The results showed that the prediction effect of the selected wavelength was very close to that of the MWPLS method,while the number of wavelength points was much smaller.SEPAve,RP,Ave,SEPStd,and RP,Std which characterized the modeling effect were 26.3 mg L^-1,0.969,3.49 mg L^-1,and 0.006,respectively.The validation effect V-SEP and V-RP were 28.64 mg L^-1 and 0.960,respectively.The selected waveband was between 1809 cm^-1 and 1568 cm^-1.The method was of more reference value for the design of FTIR/ATR spectral instrument for COD detection.

A Sensitive Wavebands Identification System for Smart Farming

Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture.It helps the farmers in the optimal use of fertilizers.It reduces the cost of food production and also the negative environmentalimpacts on atmosphere and water bodies due to indiscriminate dosageof fertilizers.The traditional chemical-based laboratory soil analysis methodsdo not serve the purpose as they are hardly suitable for site specific soil management.Moreover,the spectral range used in the chemical-based laboratory soil analysismay be of 350-2500 nm,which leads to redundancy and confusion.Developing sensors based on the discovery of spectral wavebands that respondto soil macronutrient concentrations,on the other hand,is an innovative and successfultechnology since the results are dependable and timely.The goal of thisarticle is to use a supervised neuro-fuzzy based dimensionality reduction approachin the sensor development process to determine sensitive wavebands of soilmacronutrients.Accordingly,the spectral signatures of the soil are collected inan outdoor environment and mapped with its macronutrient concentrations.In thisspectral analysis,the spectral reflectance of 424 wavelengths has been obtainedand these wavelengths are evaluated through combined and individual modesas well.Appropriate wavelengths are selected in each case by minimizing the fuzzy reflectance assessment index.The effectiveness of these selected wavelengthsin each mode is validated by modeling the relation between the reduced reflectancespace and each macronutrient concentration using Partial Least Squares Multi Variable Regression(PLS-MVR)method.Set of optimal wavebands areidentified and the results are compared with the existing systems.

High power tunable Raman fiber laser at 1.2μm waveband

Development of a high power fiber laser at special waveband,which is difficult to achieve by conventional rare-earth-doped fibers,is a significant challenge.One of the most common methods for achieving lasing at special wavelength is Raman conversion.Phosphorus-doped fiber(PDF),due to the phosphorus-related large frequency shift Raman peak at 40 THz,is a great choice for large frequency shift Raman conversion.Here,by adopting 150 m large mode area triple-clad PDF as Raman gain medium,and a novel wavelength-selective feedback mechanism to suppress the silica-related Raman emission,we build a high power cladding-pumped Raman fiber laser at 1.2μm waveband.A Raman signal with power up to 735.8 W at 1252.7 nm is obtained.To the best of our knowledge,this is the highest output power ever reported for fiber lasers at 1.2μm waveband.Moreover,by tuning the wavelength of the pump source,a tunable Raman output of more than 450 W over a wavelength range of 1240.6–1252.7 nm is demonstrated.This work proves PDF’s advantage in high power large frequency shift Raman conversion with a cladding pump scheme,thus providing a good solution for a high power laser source at special waveband.

Silicon-based four-mode division multiplexing for chip-scale optical data transmission in the 2 μm waveband

Based on a silicon platform, we design and fabricate a four-mode division(de)multiplexer for chip-scale optical data transmission in the 2 μm waveband for the first time, to the best of our knowledge. The(de)multiplexer is composed of three tapered directional couplers for both mode multiplexing and demultiplexing processes. In the experiment, the average crosstalk for four channels is measured to be less than-18 dB over a wide wavelength range(70 nm) from 1950 to 2020 nm, and the insertion losses are also assessed. Moreover, we further demonstrate stable 5 Gbit/s direct modulation data transmission through the fabricated silicon photonic devices with nonreturn-to-zero on–off keying signals. The experimental results show clear eye diagrams, and the penalties at a bit error rate of 3.8 × 10-3 are all less than 2.5 dB after on-chip data transmission. The obtained results indicate that the presented silicon four-mode division multiplexer in the mid-infrared wavelength band might be a promising candidate facilitating chip-scale high-speed optical interconnects.

Efficient Design of Multi-stage Cascade Waveband Separator

We propose a cascade system of filters for realizing a non-uniform waveband separation for optical networks. The use of such separation is required at the DEMUX stage in a optical OXC switching wavebands. The design of the system is based on optimized balanced tree, which minimizes the overall optical loss.

带壳板栗含水率的可见/近红外与中短波近红外光谱检测对比研究

为实现带壳板栗含水率的无损快速检测与评价,利用可见/近红外和中短波近红外光谱技术进行定量预测方法探索与对比研究。应用不同光谱预处理方法在波段Ⅰ和波段Ⅱ建立全光谱PLSR模型,结果显示,标准正态变量变换预处理的波段Ⅰ模型及归一化预处理的波段Ⅱ模型为优选,预测集相关系数分别达0.882和0.856,预测均方根误差为1.389%和1.665%。进一步对优选预处理光谱应用iPLSR,BiPLSR和SiPLSR建模预测并对比,研究结果表明,波段Ⅰ总体优于波段Ⅱ,且iPLSR模型的预测效果最优,Rp和RMSEP分别可达0.910及1.180%,明确了近红外光谱检测带壳板栗含水率的优选波段、预处理及建模方法。研究为后续板栗含水率高通量在线快检提供技术与方法支撑。

超表面在微测辐射热计中的应用

超表面突破了传统自然材料的电磁特性限制,同时也解决了三维超材料难以加工实现等瓶颈问题,使器件朝着集成化,小型化,低成本,可调谐的方向不断发展。目前超表面已在许多领域得到了较为广泛的应用,在探测器领域也越来越受到人们的重视,通过独特的材料、结构设计,超表面可有效完成电磁波各项特性的精确调控,通过超表面的集成,微测辐射热计在光吸收增强,器件波段选择改善等方面有了更多的可能性。本文针对超表面及其在微测辐射热计上的应用研究进行了阐述,展现了超表面在这一领域的发展趋势和广阔前景。

2.0~25.0μm波段低限制损耗光子晶体光纤的设计

针对2.0~25.0μm波段传输的限制损耗问题,文章采用数值模拟方法研究影响碲基硫系光子晶体光纤(photonic crystal fiber,PCF)限制损耗的主要因素。光纤纤芯和包层材料采用Ge 20 As 20 Se 15 Te 45玻璃,通过改变纤芯直径、空气孔直径和空气孔层数等参数进行2.0~25.0μm波段限制损耗的计算,结果表明,影响限制损耗的最大因素是纤芯直径,限制损耗随着纤芯直径和空气孔直径的增大而显著降低,随着空气孔层数的增加而降低;优化设计出一种低限制损耗的PCF,结果表明,当纤芯直径和节距为8.0μm、空气孔直径为7.2μm、包层空气孔层数为4时,该PCF在2.0~25.0μm波长范围的限制损耗低于1.4×10^(-6) dB/m,满足低损耗传输要求。文章研究结果对2.0~25.0μm波段光信号的传输具有一定的意义。

自驱动α-Ga_(2)O_(3)/Cu_(2)O双波段光电探测器的研究性实验教学设计

为培养创新型人才,结合电子科学与技术专业的教学内容,设计了内容为“自驱动α-Ga_(2)O_(3)/Cu_(2)O双波段光电探测器”的研究性实验。采用水热法和光沉积法分别制备α-Ga_(2)O_(3)纳米线和Cu_(2)O纳米颗粒,采用X射线衍射仪和扫描电子显微镜对纳米线进行了表征,通过合理设计器件的能带结构,所制备的α-Ga_(2)O_(3)/Cu_(2)O异质结光电探测器具备对深紫外和近紫外分辨探测的能力,并深入分析了其中的物理机制。将学术研究的探索精神融入实验中不仅可以提升实验的趣味性,还可以锻炼学生的自主学习能力、创新实践能力和科研探索能力。

基于信杂比的高超声速飞行器红外探测谱段分析

以典型吸气巡航式和助推滑翔式两类高超声速飞行器为研究对象,采用纳维-斯托克斯(Navier-Stokes,N-S)方程和流固耦合模型计算流场分布,采用逆向蒙特卡罗方法计算高超声速飞行器本体光谱辐射特性;进一步考虑探测场景中的海面背景和临边大气背景辐射特性以及大气传输特性,基于探测信杂比分析高超声速飞行器的最优红外探测谱段。分析结果表明:在采用对地模式探测吸气巡航式高超声速飞行器时,建议选择(2.5~3.1)μm、(4.2~4.4)μm、(5.2~7.8)μm谱段;在采用临边模式探测吸气巡航式高超声速飞行器时,建议选择(3~5)μm谱段;在采用对地模式探测助推滑翔式高超声速飞行器时,建议选择(2.5~3.2)μm、(4.2~4.6)μm、(5.4~7.5)μm谱段;在采用临边模式探测助推滑翔式高超声速飞行器时,建议选择(2.7~5.0)μm谱段。

小麦叶层氮含量估测的最佳高光谱参数研究

【目的】作物体内氮素状况是评价长势和预测产量的重要指标。小麦植株氮素营养的快速监测和无损诊断对于精确氮素管理具有重要作用。本文旨在通过对高光谱信息的精细分析和信息提取,探索建立小麦叶片氮含量(LNC,leaf nitrogen content)估算的最佳波段、光谱参数及监测模型。【方法】利用连续4年的系统观测资料,采用精细采样法,详细分析350～2500nm波段范围内原始光谱反射率及其一阶导数光谱的任意两两波段组合而成的主要高光谱指数与小麦冠层叶片氮含量的定量关系。【结果】发现小麦叶片氮含量的最佳波段为位于红边的690、691、700和711nm以及近红外波段的1350nm;基于归一化光谱指数NDSI(R1350,R700)和NDSI(FD700,FD690)、比值光谱指数RSI(R700,R1350)和RSI(FD691,FD711)、土壤调节光谱指数SASI(R1350,R700)(L=0.09)和SASI(FD700,FD690)(L=-0.01)构建氮含量监测模型,决定系数(R2)分别为0.851和0.857、0.842和0.893、0.860和0.866。利用独立试验资料对模型检验的结果显示,模型测试的精度(R2)均大于0.758,RRMSE均小于0.266,尤其是高光谱参数RSI(FD691,FD711)和SASI(FD700,FD690)表现最好。【结论】总体上,利用精细采样法确定最佳波段,构建植被指数和氮含量监测模型,可显著提高模型的精确度和可靠性,从而为快速无损诊断小麦叶层的氮素状况提供新的波段选择和技术途径。

基于光谱成像技术的温室黄瓜识别方法

为实现温室环境下近色系果蔬的采摘识别,提出了一种基于统计方差结合人工神经网络的光谱选择方法对黄瓜敏感波段进行分析验证,并将选定的光谱组合作为温室黄瓜识别中光谱图像获取的参考依据。结果表明,利用所摄敏感波段的图像信息可有效地解决黄瓜目标与背景的区分问题。综合比较黄瓜作物(果实、叶、花)在不同光谱域的分光反射特性差异,利用方差分解方法获取果实信息的敏感波段,在敏感区域内进行主成分分析,将前4个主成分作为网络输入、作物器官类别作为输出,建立3层BP-ANN验证模型。将160个样本数据按比例分为建模集和预测集,模型对建模集120个样本的正确判别率为100%,对预测集40个样本的正确判别率为95%。说明敏感波段的选择能较好地反映黄瓜作物不同器官间的特性差异。

基于无人机遥感可见光影像的北疆主要农作物分类方法

作物类型准确分类是大田作业和管理的基础。该文通过无人机遥感试验获取的可见光影像,利用色彩空间转换和纹理滤波构建了色调、饱和度和亮度的27项纹理和低通滤波特征;然后采用Relief F-Pearson特征降维方法,剔除分类能力弱且相关性高的冗余特征;最后,基于优选特征训练分类模型,并结合人工分类结果对各模型进行精度比较和效果验证。结果表明:特征选择得到的H-CLP、H-Ent、I-Cor、I-CLP、I-Ent、S-CLP和I-Var是利用可见光影像进行北疆主要农作物分类的最佳特征,可在充分表征影像特征的同时降低数据冗余。支持向量机(support vector machine,SVM)分类方法精度最高,整体分类准确率达83.77%,ANN和KNN分类精度次之。通过在验证区进行像素级别作物分类,发现SVM分类方法效果最好,棉花、玉米、苜蓿和西葫芦作物分类精度均达到了80%以上。该研究可为基于无人机可见光影像的农作物种植信息普查提供参考。

应用近红外漫反射光谱快速测定土壤锌含量

采用近红外漫反射光谱和偏最小二乘法（PLS）建立了土壤锌快速分析的定量模型，并进行了波段优选。首先，基于单波长模型预测效果将全体样品划分为定标集和预测集；然后，采用多元散射校正（MSC）和Savitzky-Golay（SG）平滑方法对光谱进行预处理。选取全谱400～2500nm，400～1100nm，1100～1900nm，1900～2500nm，580～900nm等5个波段，每个波段分别采用原谱、一阶导数谱、二阶导数谱，共建立了15个定标模型。同时调整SG平滑点数和PLS因子数，每个模型分别进行PLS数值实验，按照预测效果进行优选。结果显示，采用1900-2500nm波段一阶导数谱的模型效果最好，预测相关系数（RP）、RMSEP、RRMSEP分别为0．806，31．0mg／kg和19．96％。这些结果表明，1900-2500nm波段可以代替全谱波段得到更好的预测效果，可为设计专用土壤近红外光谱仪提供依据。

双波段比色精确测温技术

非接触红外辐射测温具有响应速度快、准确、便捷等优势。为实现中低温（50-400℃）物体温度的精确测量，根据双波段比色测温原理，搭建了双波段比色测温试验系统。首先对试验系统所用的试验器件进行精确标定，得到拟合曲线，用多种插值算法对曲线进行校正。然后，用设定温度的面源黑体作为试验目标来进行试验温度数据采集。实验结果表明：搭建的双波段试验系统不需要知道目标发射率，也能较为精确地得到中低温物体的真实温度。当系统标定置信度为0.95时，物体的标准偏差在3℃以内。验证了搭建测温系统的正确性，实验装置的搭建对中低温物体真实温度的精确测量具有重要的研究意义。

基于高光谱特征的土壤有机质含量估测研究

在室内条件下,利用ASD2500高光谱仪测定了潮土和水稻土自然风干土壤样品的光谱。通过系统分析两种不同类型土壤的高光谱特征差异及其有机质含量的敏感波段区位,建立了土壤有机质含量的光谱估测模型。结果表明,具有相同有机质含量的两种类型土壤整体光谱变化趋势无明显差别,但反射率表现出明显差异,一阶导数变换能较好地显现谱图中的肩峰。潮土和水稻土有机质的敏感波段集中在相同区域,原始反射率在685 nm处相关性最高,而一阶导数光谱在554 nm处相关性最高。通过对整体样本的多元逐步回归分析,筛选出两种土壤有机质相同的敏感波段为800 nm、1 398 nm和546 nm。进一步以一阶导数为自变量,基于1 400nm和554 nm两个波段构建了土壤有机质差值指数SOMDI及估测模型,即Y=4.19 12.85×(R_FD554 R_FD1 400)。利用独立的样本对建立的光谱模型进行了检验,预测决定系数均达0.79以上。上述结果表明,利用高光谱技术可实现土壤有机质的快速监测与诊断。

岩石的红外波段辐射特性研究

提出了波段辐射特性这一物理概念，并对岩石的红外波段辐射特性进行了测量和研究．得到的结果对于选取遥感波段、建立遥感信息的判读标志、建立由岩石应力变化引起岩石红外辐射能量的变化量与相应应力的定量关系等具有重要的意义．

土壤总氮近红外光谱分析的波段优选

利用移动窗口偏最小二乘(MWPLS)和Savitzky-Golay(SG)平滑方法优选土壤总氮的近红外(NIR)光谱分析模型。从全部97个土壤样品中随机选出35个样品作为检验集;基于偏最小二乘交叉检验预测偏差(PLSPB),将余下62个样品划分为具有相似性的建模定标集(37个样品)、建模预测集(25个样品)。最优波段为1692～2138 nm,SG平滑的导数阶数(OD)、多项式次数(DP)、平滑点数(NSP)分别为0,6,69,PLS因子数为11,建模预测均方根偏差(M-RMSEP)、建模预测相关系数(M-RP)分别为0.015%,0.931,检验预测均方根偏差(V-RMSEP)、检验预测相关系数(V-RP)分别为0.018%,0.882。其结果可为设计专用NIR仪器提供有价值的参考。