为无损探究种子成分分布与种子活力变化的内在关系, 以玉米种子主要成分淀粉为研究对象, 将太赫兹时域反射成像技术与移动窗口相关系数法相结合, 无损可视化构建不同活力程度的玉米种子淀粉空间分布图。 以郑单958玉米品种为例, 实验通过人工老化方式(40 ℃, 100%RH)制备老化0、 18、 36、 54、 72 h的种子样本, 采用Terapluse 4000太赫兹时域光谱仪及反射成像附件扫描获取不同老化程度的样本和纯玉米淀粉样品的太赫兹光谱图像。 以16.35 cm-1下THz图像为基准, 采用阈值分割法精确提取种子胚乳、 种胚区域, 通过对比不同组织区域内THz平均吸光度可得胚乳和种胚光谱明显差异, 且胚乳和淀粉纯物质在51.96 cm-1附近存在明显的共同吸收峰。 应用移动窗口相关系数法(窗口宽度为20, 移动步长为10), 逐像素点计算种子太赫兹时域光谱与纯玉米淀粉光谱的-相关系数, 并根据相关系数值以及坐标信息绘制伪彩色热力图, 可视化构建玉米种子淀粉分布图。 实验统计5个老化阶段、 6个谱区窗口的淀粉分布图中相关系数>0.8的像素点占比可得: 在29.83～67.36 cm-1区间内, 种子胚乳和种子区域内的淀粉含量在种子活力下降过程中呈现总体下降趋势, 即种子淀粉含量与活力呈现正相关关系。 实验结果表明: 太赫兹时域光谱反射成像技术结合移动窗口相关系数伪彩色成像分析方法可以初步实现种子活力变化过程中玉米种子淀粉空间分布特性的无损探测, 该技术可为深入研究种子化学成分与其自身活力之间的制约关系, 无损解析种子生命活动与自身生理生态规律变化提供崭新的视角和方法。

为进一步提高城市生态监测的精确度，在前人开展的城市生态遥感监测研究的基础上引入“区域尺度”的概念，充分考虑小区域范围内不同地物间的交互作用，并利用移动窗口模型(Moving Window-Remote Sensing Ecology Index, MW-RSEI)对沈阳市浑南区的遥感影像进行逐像元分析。实验结果表明，MW-RSEI模型和生态遥感监测模型（Remote Sensing Ecology Index, RSEI)在整体生态评价趋势上表现出一致性。但MW-RSEI模型对城市生态中的细节区域表征更明显。考虑到建筑及裸地周围植被的影响，其较差生态区域的占比仅为6%，生态评价为优的区域占比为11%。研究区生态评价结果表现得较为连续，并未出现明显的断层现象。该结果具有现实意义且与实际生态分布更为符合。MW-RSEI模型在城市生态监测中更为适用，可为相关部门提供一定的技术参考。

对近红外光谱(NIRS)分析技术结合化学计量学方法定量检测混合溶液中鲜味物质浓度及其鲜味强度的可行性进行探讨。以谷氨酸钠与肌苷酸二钠所构成的鲜味物质混合溶液为研究对象,获取不同鲜味强度的样本并采集其近红外光谱数据。基于偏最小二乘回归法结合竞争性自适应移动窗口区间组合(CMIC)新算法,以及多种常用变量优化算法分别建立混合溶液中鲜味物质浓度和混合溶液鲜味强度的检测模型。实验结果表明,最优的混合溶液中鲜味物质浓度和混合溶液鲜味强度检测模型均是基于CMIC算法建立的简化模型,预测决定系数分别为0.8886、0.9182和0.8097。因此,NIRS分析技术结合化学计量学方法可应用于定量检测混合溶液中鲜味物质浓度及其鲜味强度。

光纤法布里-珀罗可调滤波器(FFP-TF)是组成光纤布拉格光栅(FBG)传感器解调系统的核心器件之一,其稳定性对解调精度的提高至关重要,而温度漂移是影响其稳定性的关键因素之一。针对实际应用中遇到的FFP-TF在变温环境下产生的透射波长漂移问题,提出了一种基于集成移动窗口的温度漂移补偿方法。利用最小二乘支持向量机对透射波长和温度之间的非线性关系进行了建模,并在训练样本中建立了移动窗口。此外,为了挖掘更多的训练样本过程信息,提出了采用神经网络对各个移动窗口的补偿结果进行加权集成的方法。实验结果表明,当未引入集成移动窗口时,解调值的最大测量误差为±13.5 pm。在引入集成移动窗口后,解调值的最大测量误差为±0.82 pm,即所提方法有效提高了光纤光栅传感中可调滤波器解调的温度稳定性。

The moving-window bis-correlation coe±cients (MW-BiCC) was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and --thalassemia with visible and nearinfrared (Vis–NIR) spectroscopy. The well-performed moving-window principal component analysis linear discriminant analysis (MW-PCA–LDA) was also conducted for comparison. A total of 306 transgenic (positive) and 150 nontransgenic (negative) leave samples of sugarcane were collected and divided to calibration, prediction, and validation. The diffuse reflection spectra were corrected using Savitzky–Golay (SG) smoothing with first-order derivative (d=1), third-degree polynomial (p=3) and 25 smoothing points (m=25). The selected waveband was 736–1054 nm with MW-BiCC, and the positive and negative validation recognition rates (V REC+, V REC-T were 100%, 98.0%, which achieved the same effect as MW-PCA–LDA. Another example, the 93 --thalassemia (positive) and 148 nonthalassemia (negative) of human hemolytic samples were collected. The transmission spectra were corrected using SG smoothing with d=1, p=3 and m=53. Using MW-BiCC, many best wavebands were selected (e.g., 1116–1146, 1794–1848 and 2284–2342nm). The V REC+ and V REC- were both 100%, which achieved the same effect as MW-PCA–LDA. Importantly, the BiCC only required calculating correlation coe±cients between the spectrum of prediction sample and the average spectra of two types of calibration samples. Thus, BiCC was very simple in algorithm, and expected to obtain more applications. The results first confirmed the feasibility of distinguishing --thalassemia and normal control samples by NIR spectroscopy, and provided a promising simple tool for large population thalassemia screening.

Teicoplanin (TCP) is an important lipoglycopeptide antibiotic produced by fermenting Acti-noplanes teichomyceticus. The change in TCP concentration is important to measure in the fermentation process. In this study, a reagent-free and rapid quantification method for TCP in the TCP–Tris–HCl mixture samples was developed using near-infrared (NIR) spectroscopy by focusing our attention on the fermentation process for TCP. The absorbance optimization (AO) partial least squares (PLS) was proposed and integrated with the moving window (MW) PLS, which is called AO–MW–PLS method, to select appropriate wavebands. A model set that includes various wavebands that were equivalent to the optimal AO–MW–PLS waveband was proposed based on statistical considerations. The public region of all equivalent wavebands was just one of the equivalent wavebands. The obtained public regions were 1540–1868 nm for TCP and 1114–1310 nm for Tris. The root-mean-square error and correlation coefficient for leave-one-out cross validation were 0.046 mg mL 1 and 0.9998 mg mL 1 for TCP, and 0.235 mg mL 1 and 0.9986 mg mL 1 for Tris, respectively. All the models achieved highly accurate prediction effects, and the selected wavebands provided valuable references for designing specialized spectrometers. This study provided a valuable reference for further application of the proposed methods to TCP fermentation broth and to other spectroscopic analysis fields.

为满足白酒品牌判别领域快速检测的迫切需求, 提出了一种以紫外光谱为输入, 移动窗口相关系数法为手段的白酒品牌快速判别新方法。 研究以海之蓝酒作为对象品牌, 实验结果显示各批次海之蓝酒在实验波长区间存在较高的吻合一致性, 基于紫外光谱原始谱图的相关系数值和基于移动窗口光谱计算所得的相关系数值均达到0.99以上。 由于其他洋河系列白酒与海之蓝酒均属于洋河酒厂生产, 原料来源、 生产制备工艺等存在较高的相似性, 此时若仅使用紫外光谱原始谱图数据结合相似度算法进行品牌判别, 则定量化的判别区分存在一定困难。 移动窗口法可有效提高谱图细节差异, 突出光谱在特征谱段的形状、 强度、 变化趋势差异, 提高实验谱图在细节结构差异辨认分析能力。 经过研究筛选, 发现以移动窗口相关系数结合紫外光谱特征谱段(270～295 nm)可提高洋河系列酒间的谱图差异, 实现这种有较高相似性白酒品牌的判别区分。 此外, 市售六种其他品牌白酒及乙醇作为对照组, 进一步论证了该方案的可行性。 该研究的创新之处在于提出了一种移动窗口相关系数光谱法进行白酒品牌快速判别分析的新思路, 该方法同时具备速度快, 操作简便等优点, 具有较高的实际应用潜在价值, 并可为其他食品的质量安全判别分析研究提供借鉴。

将移动窗口偏最小二乘(MWPLS)应用于脐橙中重金属Cd含量的激光诱导击穿光谱(LIBS)定量分析模型中, 通过改变MWPLS窗口宽度并结合标准归一化处理、一阶导数、二阶导数、中心化处理和多元散射校正等5种数据前处理方法, 优选与脐橙中Cd元素相关性高的光谱区间, 并与传统偏最小二乘法进行对比分析。模型评价及验证结果显示, 当优选移动窗口为61个波长宽度、优选区域为218.61~222.55 nm时, 结合一阶导数数据前处理方法所构建的模型效果最佳, 验证集决定系数、预测均方根误差、主因子数、平均预测相对误差分别为0.9953, 15.10×10-6, 12, 7.43%。MWPLS结合合适的数据前处理方法可以筛选出脐橙中Cd元素的LIBS光谱区域, 提高定量分析模型的预测能力。