基于正交信号校正和偏最小二乘(OSC/PLS)的苹果糖度近红外检测

采用正交信号校正法(OSC)对苹果的近红外光谱(1300nm～2100nm)进行预处理，并结合偏最小二乘法(PLS)建立了苹果光谱对糖度的预测模型。应用结果表明，经OSC法预处理后，光谱形状总体上与原始光谱没有差别，但光谱曲线变得更为光滑，排列更为整齐、紧密。这说明正交信号校正法(OSC)滤除了原始光谱中的部分噪声，但又保留了原光谱中的主要信息。苹果光谱对糖度的PLS校正模型采纳的最佳因予数会随着OSC因子的被逐个滤除而逐渐减少，甚至可减少至1(当然模型精度也有变化)。本研究中，校正模型的最佳性能产生于原始光谱被滤除10个OSC因了时，此时其采纳的最佳因了数为2，校正时的相关系数r2和标准偏差SEC分别为0．92644和0．40250，预测时的标准偏差SEP为0．50229。与OSC法处理前的PLS模型相比，其精度虽没有大幅提高，但由于采纳的因子数少，模型变得十分简洁。     

红外技术在食品工业中的应用

介绍了红外技术在食品工业应用及其原理，着重讲述了近红外的检测技术应用和远红外加热和杀菌技术应用，并分析了光波炉的工作原理、干燥原理以及近红外技术的特点。并给出了一些比较实例，指出了红外技术应用的发展趋势。     

静电复印废纸溶剂法脱墨机理初步研究

采用傅立叶变换红外光谱、图像扫描和显微分析等手段,研究了静电复印废纸溶剂法脱墨的机理.红外光谱分析表明,溶剂将油墨的连接料组分(如苯乙烯丙烯酸树脂等)溶出;油墨粒子的显微分析表明,随着抽提时间的延长,油墨粒子之间的结合越来越松散,从而在碎浆过程中油墨粒子更易被打散,同时,浮选后粘附在纤维上的油墨粒子粒径越来越小,数量也越来越少,但是抽提时间过长使得粒径较小(＜12μm)的油墨粒子数量增加,导致浮选效率有一定程度的下降.     

Study of the oxidative degradation of farmed salmon lipids by means of Fourier transform infrared spectroscopy. Influence of salting

Farmed salmon fillets were dry‐salted for 24 h. Both salted and unsalted samples were submitted to oxidative conditions at 50 °C in an oven with circulating air. Lipids of both samples were extracted daily from aliquots and studied by Fourier transform infrared spectroscopy. The infrared spectra of salmon lipids are similar to those of vegetable edible oils, with differences in the frequency and absorbance of some bands due to their different acyl group compositions. The infrared spectra of salted and unsalted fish lipid samples remain unchanged during a period of time, which is shorter for the salted salmon. After this period, changes in the frequency and absorbance of some bands of the spectrum are observed owing to the presence of oxidation products. Therefore the reduction in the oxidative stability of farmed salmon lipids caused by the dry‐salting process is proved and the usefulness of this technique for studying the oxidative stability of fish lipid samples as well as their oxidation degree is shown. Copyright © 2004 Society of Chemical Industry     

Confirmation of brand identity in foods by near infrared transflectance spectroscopy using classification and class-modelling chemometric techniques — The example of a Belgian beer

Food and beverage processors require tools to monitor conformance of finished goods to their defined specification; regulatory authorities need appropriate methods for detecting retail fraud. In this report, samples (n = 275) of Belgian and other European beers were collected and analysed using near infrared transflectance spectroscopy; three class-modelling techniques (soft independent modelling of class analogy, SIMCA; potential functions techniques, POTFUN; and unequal dispersed classes, UNEQ) were employed to characterise beer types (firstly Trappist and then Rochefort) while a classification method (partial least squares discriminant analysis, PLS-DA) was applied to discriminate between two final beer classes: Rochefort 8° and Rochefort 10°. The class-models and the classification rules developed were validated by means of an external prediction set. A discussion on the appropriate use of these chemometric approaches is included. Modelling of Trappist beers met with limited success while model efficiencies for Rochefort samples were highest for SIMCA and UNEQ applications i.e. 81.4% and 84.5% respectively. The classification of beers as Rochefort 8? or Rochefort 10? was possible with an average correct classification rate of 93.4%.     

一种红外图像超分辨率重构系统设计与应用

设计了一种基于FPGA和DSP架构的红外图像超分辨率重构系统。采用TI公司高性能DSP(TMS320DM6467)和Xilinx公司FPGA(VIRTEX-4)作为核心处理器。DSP模块承担目标图像重构算法运算,FPGA模块负责图像预处理及与主控计算机通信。通过合理的任务调度,充分发挥DSP并行运算的灵活与速度优势和FPGA实现的快速性与通用性,结合改进PCOS超分辨率算法,可稳定获得较高质量的重构红外图像。应用结果证明该重构系统设计合理,具备较强的实用性。     

近似稀疏正则化的红外图像超分辨率重建

针对红外图像分辨率低、受噪声影响严重等问题,引入近似稀疏正则化和K-奇异值分解（K-SVD）法,提出了基于近似稀疏表示模型的红外图像超分辨率重建方法。考虑到红外图像受到噪声污染,首先建立了稳健近似稀疏表示模型。针对已有字典训练方法时间消耗巨大问题,在假定低分辨率图像空间和高分辨率图像空间具有相似流形的前提下,联合近似稀疏表示模型和K-SVD方法,提出近似稀疏约束的基于K-SVD的高低分辨率字典对学习算法。最后,通过高分辨字典和对应的红外图像群稀疏表示系数重建得到高分辨率的红外图像。为了验证算法的性能,对提出的算法与稀疏性正则化的图像超分辨模型（SRSR）和Zeyde算法进行了实验比较。结果表明,本文方法能够较好地减少红外图像中的噪声,同时获得更好的超分辨率重建效果。     

Determination of starch and lipid in pea flour by near infrared reflectance analysis. the effect of pea genotype on starch and lipid content

Equations were derived for predicting starch and lipid content of pea varieties from near infrared data measured on a filter instrument (Technicon InfraAlyzer 400). The accuracy of the predictions were tested against separate data sets and were found to be better than ±2.6% for starch (range 20–45%) and ±0.3% for lipid (range 1.4–3.3%). Together with the previous work on the near infrared determination of protein it is possible to analyse rapidly for three components important to a plant breeding programme. The study has also demonstrated a clear-cut delineation between round and wrinkled pea genotypes.     

消防机器人火源单目探测方法研究

针对目前基于上位机的视频火焰探测技术成本高、体积大等缺点,提出了一种基于FPGA和ARM的嵌入式图像处理系统。通过分析火焰的红外特性,提出了选用合适的红外滤光片简化图像处理和火源探测算法,并详细介绍了系统构成、工作原理以及开发流程。此外,通过分析火焰的静态特征和动态特征,并结合红外图像的特点,提出了通过分析火焰的圆形度、面积改变率和尖角特性来判别疑似火焰。     

真丝织物化学接枝改性后的结构和热性能

利用红外光谱、扫描电镜、热重分析 ,对具有 β -乙烯砜硫酸酯基、磺酸基和三嗪环结构的接枝剂改性后真丝织物的结构和热性能进行研究表明 ,纤维表面发生明显改变 ,真丝织物热稳定性提高