MEALINESS DETECTION IN APPLES USING TIME RESOLVED REFLECTANCE SPECTROSCOPY

Mealiness is a textural attribute related to internal fruit disorder that is characterized by the combination of abnormal softness of the fruit and absence of free juiciness in the mouth when eaten by the consumer. Time‐resolved laser reflectance spectroscopy was used as a tool to determine mealiness. This new technique in agrofood research may provide physical and chemical information independently and simultaneously, which is relevant to characterize mealiness. Using visible and near infrared lasers as light sources, time‐resolved laser reflectance spectroscopy was applied to Golden Delicious and Cox apples (n = 90), to characterize batches of untreated samples and samples that were stored under conditions that promote the development of mealiness (20C & 95% RH). The collected database was clustered into different groups according to their instrumental test values. The optical coefficients were used as explanatory variables to build discriminant functions for mealiness. The performance of the classification models created ranged from 47 to 100% of correctly identified mealy versus nonmealy apples.     

Monitoring the ripening attributes of Turkish white cheese using miniaturized vibrational spectrometers

Monitoring the ripening process by prevalent analytic methods is laborious, expensive, and time consuming. Our objective was to develop a rapid and simple method based on vibrational spectroscopic techniques to understand the biochemical changes occurring during the ripening process of Turkish white cheese and to generate predictive algorithms for the determination of the content of key cheese quality and ripening indicator compounds. Turkish white cheese samples were produced in a pilot plant scale and ripened for 100 d, and samples were analyzed at 20 d intervals during storage. The collected spectra (Fourier-transform infrared, Raman, and near-infrared) correlated with major composition characteristics (fat, protein, and moisture) and primary products of the ripening process and analyzed by pattern recognition to generate prediction (partial least squares regression) and classification (soft independent analysis of class analogy) models. The soft independent analysis of class analogy models classified cheese samples based on the unique biochemical changes taking place during the ripening process. partial least squares regression models showed good correlation (R_Pre = 0.87 to 0.98) between the predicted values by vibrational spectroscopy and the reference values, giving low standard errors of prediction (0.01 to 0.57). Portable and handheld vibrational spectroscopy units can be used as a rapid, simple, and in situ technique for monitoring the quality of cheese during aging and provide real-time tools for addressing deviations in manufacturing.     

基于多重光谱技术的木糖醇与牛乳酪蛋白相互作用及对酪蛋白结构的影响

综合利用荧光光谱法、傅里叶变换红外光谱法和圆二色谱法等多种先进光谱技术研究木糖醇与牛乳酪蛋白的相互作用以及对牛乳酪蛋白二级结构及功能性质的影响。荧光光谱表明,木糖醇对牛乳酪蛋白具有较强的荧光猝灭效应,猝灭机理属于静态猝灭,生成了新的复合物,二者在300、310 K和320 K时相互作用的结合常数分别为5.326×106、2.600×106 L/mol和2.160×106 L/mol,对应的结合位点数分别为1.513、1.452和1.422,主要作用力为静电引力,可能会有疏水作用力,结合距离为3.564 nm;同步荧光光谱和三维荧光光谱的结果表明,二者的相互作用位点更接近于色氨酸,其周围微环境的疏水性增强,使酪蛋白的分子构象发生改变;傅里叶变换红外光谱和圆二色谱的结果表明,木糖醇改变了牛乳酪蛋白的二级结构,使其α-螺旋结构相对含量增加,无规卷曲结构相对含量减少,结构变得更加紧密;结构的变化导致酪蛋白的乳化活性降低,乳化稳定性升高,表面疏水性降低。研究结果为功能性乳基料的开发提供了理论依据。     

多种光谱技术在食用油分析鉴别中的研究进展

随着快检技术的发展与普及,化学计量学分析工具与光谱技术相结合的策略逐步在食品的掺假鉴别和产地溯源等领域发挥独特的优势,成为品质鉴别及掺伪检测的重要发展方向,具有重要的研究意义和广阔的应用前景。该文综述红外光谱、拉曼光谱、核磁共振波谱、太赫兹时域等光谱技术的基本原理及其与化学计量学分析工具相结合在食用油脂品种鉴定、掺假分析、理化指标等方面的应用及研究进展,为食品快检技术研究提供参考和借鉴。     

Evaluation of freshness decay of minced beef stored in high-oxygen modified atmosphere packaged at different temperatures using NIR and MIR spectroscopy

Meat freshness has been monitored by various microbiological, chemical and sensorial indices. However, these methods are slow and not suited to automation. Infrared spectroscopy is one of the most convenient analytical tools which could be used to monitor the evolution of food quality. The aim of this work was to investigate the ability of both NIR (Near Infrared) and MIR (Mid Infrared) spectroscopy to follow meat freshness decay. The minced beef was packaged in high-oxygen modified atmosphere (30% CO₂ and 70% O₂) and stored at three temperatures. Spectra were collected by Fourier-Transformation (FT)-NIR and FT-IR instruments. PCA, applied to the data, was able to discriminate samples on the basis of storage time and temperature. The modelling of PC scores versus time allowed the setting of the time of initial freshness decay for the samples (6–7 days at 4.3 °C, 2–3 days at 8.1 °C and less than 1 day at 15.5 °C).     

优质小米三级中红外光谱研究（网络首发、推荐阅读）

采用中红外（MIR）光谱分别开展山东、山西和河北等地五种小米的光谱特征研究。结果表明：小米的红外吸收模式主要包括OH伸缩振动模式（νOH）、CH3不对称伸缩振动模式（νasCH3）、CH2不对称伸缩振动模式（νasCH2）、CH2对称伸缩振动模式（νsCH2）、CH伸缩振动模式（νCH）、C==O伸缩振动模式（νC==O）、酰胺Ⅰ带吸收模式（νamide-Ⅰ）、酰胺Ⅱ带吸收模式（νamide-Ⅱ）、酰胺Ⅲ带吸收模式（νamide-Ⅲ）及C—O伸缩振动模式（νC—O）;进一步以小米νasCH3-二维、νasCH2-二维、νsCH2-二维和νCH-二维为研究对象,小米相应的同步2D-MIR光谱存在着一定的差异性,可以快速准确地鉴别上述五种小米。研究拓展了三级MIR光谱技术在优质小米结构及快速鉴别的研究范围。     

茶多酚与大豆分离蛋白的相互作用

利用荧光光谱、紫外-可见光谱和傅里叶变换红外光谱法,研究茶多酚与大豆分离蛋白之间的相互作用。结果表明：茶多酚对大豆分离蛋白有较强的荧光猝灭作用且为静态猝灭,其中,茶多酚与大豆分离蛋白在291、298、310 K时相互作用的表观结合常数分别为4.571×105、2.955×105、2.672×105 L/mol,对应的结合位点数分别为1.316、1.299、1.286。热力学数据分析结果表明：茶多酚与大豆分离蛋白反应的作用力主要是范德华力和氢键作用;同步荧光光谱和紫外-可见光谱表明茶多酚改变了芳香氨基酸残基在空间结构中所处的微环境,使大豆分离蛋白的分子构象发生改变,且同步荧光光谱显示茶多酚与大豆分离蛋白中色氨酸残基发生相互作用,使其周围的疏水作用减少。傅里叶变换红外光谱表明茶多酚引起大豆分离蛋白的二级结构发生改变。     

食用植物油掺假鉴别方法研究进展

阐述了食用植物油掺伪的现状,综述了理化方法、色谱法、核磁共振波谱法、红外光谱法、拉曼光谱法的检测原理,以及在食用植物油掺假鉴别中的研究进展.着重介绍了应用最广泛的色谱法,它主要通过对脂肪酸、甾醇、生育酚等物质的测定来进行掺伪鉴别.同时,对核磁共振波谱法、红外光谱法、拉曼光谱法在油脂掺伪检测中的初步应用进行了归纳.对掺伪检测技术的研究方向进行了展望.     

超声预处理对麦胚蛋白结构的影响

采用超声波对麦胚蛋白进行不同时间的预处理,并利用荧光、拉曼光谱分析溶液中蛋白的结构,红外光谱分析冻干后蛋白结构。结果显示,超声预处理会影响酶解法制备降血糖肽的活性,30min时活性最高。荧光光谱分析提示超声预处理能够引起麦胚蛋白中色氨酸残基由疏水区向亲水区转移,但蛋白结构未发生重大破坏。拉曼光谱分析超声预处理30min时对蛋白结构的影响最大,β-折叠含量降低最多。红外光谱分析显示蛋白结构随时间变化,在35 min时变化最大,α-螺旋含量显著降低,无规则卷曲含量显著升高。拉曼和红外光谱提供的信息比荧光丰富,拉曼光谱能够提供更准确的水溶液酶催化体系中的底物结构,对于蛋白的酶解反应更有指导意义。     

不同年份陈酿湘西原香醋的光谱特性

通过分析湘西原香醋的紫外光谱、红外光谱和荧光光谱,探讨不同陈酿年份原香醋的光谱特性。结果表明:原香醋的紫外光谱主要在200～400nm间近紫外区存在特征吸收,随陈酿时间延长,紫外吸收增强、光谱曲线上移。不同年份陈酿湘西原香醋的红外光谱—OH对称伸缩振动峰υ(OH)随陈酿时间延长发生不规则变化,在2351cm-1处变化较明显。随陈酿年份延长,原香醋荧光光谱变化较大,总体荧光强度呈下降趋势,陈酿3年后总体荧光强度急剧降低,发射峰由3个减少至2个。陈酿期间原香醋发生的理化变化导致光谱特性改变,光谱分析法可为原香醋陈酿时间的鉴别提供可选方法。     

温度外扰的二维相关荧光谱鉴别4种食用植物油的研究

采用F97S荧光分光光度计结合温度扰动下的二维相关荧光光谱技术,对芝麻油、棕榈油、菜籽油和油茶籽油,进行了快速无损的识别方法的研究,并以市售4种植物油样品进行验证试验。结果表明,4种食用植物油样加热后的一维荧光发射光谱谱图在出峰数目、位置以及峰强度上都略有差别,而结合二维相关荧光光谱对其进行进一步的研究时,其谱图在自动峰和交叉峰的出峰数目、位置以及交叉峰正负情况上区别更为清晰直观。表明以温度为外扰,二维相关荧光光谱能够对食用植物油进行有效区分。     

机械活化木薯淀粉的光谱分析

采用机械活化的方法对木薯淀粉进行处理,利用X射线衍射、红外光谱及激光光谱等方法对处理后木薯淀粉的结晶结构、分子基团和粒径分布进行分析。研究结果表明,机械活化可以有效降低木薯淀粉颗粒的粒径,且粒径线性回归的趋势分布随活化时间不同而迁移,机械活化能破坏木薯淀粉的结晶结构,在X射线衍射图上表现为结晶衍射峰消失,机械活化可以增加木薯淀粉中反应基团游离羟基的数量,尤其使伯羟基的数量增加。     

Emerging Spectroscopic and Spectral Imaging Techniques for the Rapid Detection of Microorganisms: An Overview

Microorganism contamination and foodborne disease outbreaks are of public concern worldwide. As such, the food industry requires rapid and nondestructive methods to detect microorganisms and to control food quality. However, conventional methods such as culture and colony counting, polymerase chain reaction, and immunoassay approaches are laborious, time‐consuming and require trained personnel. Therefore, the emergence of rapid analytical methods is essential. This review introduces 6 spectroscopic and spectral imaging techniques that apply infrared spectroscopy, surface‐enhanced Raman spectroscopy, terahertz time‐domain spectroscopy, laser‐induced breakdown spectroscopy, hyperspectral imaging, and multispectral imaging for microorganism detection. Recent advances of these technologies from 2011 to 2017 are outlined. Challenges in the application of these technologies for microorganism detection in food matrices are addressed. These emerging spectroscopic and spectral imaging techniques have the potential to provide rapid and nondestructive detection of microorganisms. They should also provide complementary information to enhance the performance of conventional methods to prevent disease outbreaks and food safety problems.     

拉曼光谱与中红外光谱融合技术快速定量食用酒精的乙醇浓度

目的? 利用拉曼光谱与中红外光谱的数据融合技术实现对食用酒精乙醇浓度（酒精度）的快速定量检测。方法? 首先,分别采集不同浓度食用酒精水溶液的拉曼光谱与中红外光谱。其次,采用多元散射校正(multiplicative scatter correction, MSC)、卷积平滑(Savitzky-Golay, S-G)、一阶求导的方法对原始数据进行预处理。然后,基于自举软缩减法(bootstrapping soft shrinkage, BOSS)和无信息变量消除算法(uninformative variable elimination, UVE)分别对预处理后的光谱数据进行特征提取,并利用X-Y距离样本集划分法(sample set partitioning based on joint x-y distance, SPXY)将光谱数据划分为校正集和预测集。最后,建立基于拉曼光谱－中红外光谱数据融合的偏最小二乘（partial least squares regression,PLSR）食用酒精乙醇浓度预测模型,并利用麻雀搜寻算法优化的混合核极限学习机算法（SSA-HKELM）提升预测性能,实现对不同浓度食用酒精的快速、准确定量检测。结果? 与拉曼光谱数据、中红外光谱数据以及中红外与拉曼光谱的数据层融合构建的预测模型相比,中红外光谱与拉曼光谱特征层融合数据构建的预测模型具有更好的预测性能。其中,最优模型的校正集均方根误差(root mean squared error of calibration set, RMSEC)为0.98314,校正集决定系数(coefficient of determination of calibration set, Rc2)为0.99634,预测集均方根误差(root mean squared error of prediction set, RMSEP)为1.03256,预测集决定系数(coefficient of determination of prediction set, Rp2)为0.99036。结论? 中红外光谱与拉曼光谱特征层融合预测模型可以实现对不同浓度食用酒精的高效定量检测,为食用酒精的质量检测提供了有效的理论支持与技术保障。     

Fluorescence Spectroscopy for Characterization and Differentiation of Beers

Total luminescence and synchronous scanning fluorescence spectroscopic techniques were applied for characterization of the intrinsic fluorescence of eight different beers. Spectra were measured using different geometries to reveal the presence of similar fluorescent components. The total luminescence and synchronous fluorescence spectra exhibit a relatively intense short‐wavelength emission ascribed to aromatic amino acids and less intense emission in the long‐wavelength region, which may originate from B vitamins. Classification of beers based on their synchronous fluorescence spectra was performed using non‐parametrical k nearest neighbours method and linear discriminant analysis. Very good discrimination was obtained in both methods with a low classification error. The results demonstrate the potential of fluorescence techniques to characterize and differentiate beers.     

基于拉曼光谱法测定冷鲜牛肉中肌红蛋白相对含量

为研究4 ℃贮藏期间冷鲜牛肉3?种化学形式肌红蛋白相对含量变化,对采集的一维拉曼光谱,用2D-shige二维相关分析软件对其光谱数据进行二维相关分析,得出3?种化学形式肌红蛋白的相对含量最佳推导公式。结果表明：肌红蛋白、氧合肌红蛋白与高铁肌红蛋白相对含量的最佳推导公式分别为：脱氧肌红蛋白相对含量/%=（－0.305?5x＋19.570）×100;氧合肌红蛋白相对含量/%=（－2.933?9x＋154.17）×100;高铁肌红蛋白相对含量/%=（1.574?3x－14.369）×100。3?种化学形式的肌红蛋白相对含量的预测效果为高铁肌红蛋白＞脱氧肌红蛋白＞氧合肌红蛋白,其中波数为1?033～1?248?cm－1时,高铁肌红蛋白相对含量的误差值最小为4.76%。研究表明,基于拉曼光谱法无损检测冷鲜牛肉中肌红蛋白相对含量是可行的。?     

去折叠态β-乳球蛋白与表没食子儿茶素没食子酸酯的相互作用

通过微波处理β-乳球蛋白（β-lactoglobulin,β-LG）得到去折叠态β-乳球蛋白（unfolded-β-lactoglobulin,U-β-LG）,采用荧光光谱、紫外-可见光谱、圆二色光谱的方法研究表没食子儿茶素没食子酸酯（epigallocatechin gallate,EGCG）与U-β-LG的相互作用机制。结果表明,EGCG能与β-LG和U-β-LG相互作用形成复合物。它们相互之间均主要为疏水作用力。在298?K时,EGCG与β-LG和U-β-LG的结合距离分别为3.188?nm和2.875?nm。EGCG的结合使β-LG和U-β-LG的二、三级结构发生变化,表面疏水性降低。与天然β-LG相比,U-β-LG与EGCG具有更大的结合强度,结合后的U-β-LG发生更大的结构变化。     

Raman and mid-infrared spectroscopy to assess changes in Cheddar cheese with maturation

Infrared spectroscopy and Raman spectroscopy, when applied to food samples, have the unique ability to interrogate their chemical structure. In this research, Raman and mid-infrared (MIR) spectroscopy in conjunction with selected chemometrics approaches were used to investigate the effects of ageing on the protein structure in Cheddar cheese. The results illustrate the potential of Raman confocal imaging and MIR spectroscopy for an understanding of chemical changes in complex dairy matrices.     

Comparison of near-infrared and dielectric spectra for quantitative identification of bovine colostrum adulterated with mature milk

The nonhomogeneity of bovine colostrum leads to strong scattering effects for electromagnetic waves, which affects the application of electromagnetic spectroscopy in detecting colostrum. This work aimed to compare the performance of near-infrared spectroscopy (NIRS) and dielectric spectroscopy (DS) in quantitatively predicting the content of mature milk as an adulterant in colostrum. The near-infrared spectra in the range of 833 to 2,500 nm and the dielectric spectra in the range of 20 to 4,500 MHz of 150 adulterated colostrum samples containing 0 to 50% mature milk were analyzed. The different proportions of mature milk in colostrum significantly changed near-infrared and dielectric spectra. The principal component analysis score plot showed that both NIRS and DS could identify the proportion of mature milk in colostrum, but the 2 methods had different characteristics. Linear partial least squares regression and nonlinear least squares support vector machine (LSSVM) models based on near-infrared and dielectric spectra were established to identify doping proportions. The results showed that DS had better identification performance with a root-mean-square error of prediction of 4.9% and a residual prediction deviation of 3.441 by successive projection algorithm LSSVM, whereas NIRS was relatively weak with a root-mean-square error of prediction of 7.3% and a residual prediction deviation of 2.301 by full-spectra LSSVM. This work provides important insights for the quantitative prediction of nonhomogeneous liquid food by DS.