Classification of Italian honeys by mid-infrared diffuse reflectance spectroscopy (DRIFTS)

Diffuse reflectance mid-infrared Fourier transform spectroscopy (DRIFTS) and multivariate statistical analysis methods were used for the identification and classification of honey from different floral sources. The 82 honey samples (robinia, chestnut, citrus, polyfloral) were scanned by DRIFTS in the region 4000–600 cm⁻¹ and also transformed in 1st and 2nd derivatives. Spectral data were analyzed by principal component analysis, general discriminant analysis and classification tree analysis. Classification accuracy near 100% was obtained by discriminant and classification tree analyses. Classification models were successfully validated with one-third leave out method and a classification of about 100% were achieved.     

基于傅里叶变换红外光谱法的红花药材质量分析

目的 建立傅里叶变换红外光谱法分析评价红花药材质量的分析方法。方法 采用傅立叶变换红外光谱法(Fourier transform infrared spectrometry, FTIR)对采集自新疆不同产地的20批红花药材进行测量, 建立指纹图谱; 运用聚类分析与主成分分析等统计学及化学模式识别技术, 对不同来源的红花药材进行红外光谱数据比较分析。结果 筛选出12个波数段, 形成了红花药材FTIR红外光谱指纹图谱共有模式; 精密度、稳定性和重复性实验结果表明, 共有峰波数的相对标准偏差(relative standard deviation, RSD)分别为0.00%~0.1%、0.00%~4.56%、0.32%~7.5%, 符合指纹图谱的要求; 20批样品相似度均大于95%, 大致可以分为3大类, 区域间差异较为明显。结论 本研究建立的方法简单、易行、快速, 不污染、样品耗量低, 为不同来源红花药材的鉴定、内在质量评价与质量控制提供了依据、奠定了基础。     

Differentiation of Greek red wines on the basis of grape variety using attenuated total reflectance Fourier transform infrared spectroscopy

Mid-infrared spectroscopy combined with appropriate software was used in an attempt to differentiate Greek red wines of different varietals origin, including the cultivars Agiorgitiko (Nemea-Peloponnesus), Xinomavro (Naousa-Central Macedonia) and Merlot from Greece. Extract of wine phenolic components were investigated by attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy. The wine extracts were obtained by solid-phase extraction with C-18 columns and elution by methanol containing 0.01% hydrochloric acid. Libraries of spectra were created using sample from each wine variety. Spectra of unknown wine extracts were recorded and compared with those of the wine libraries and the rate of affinity (the match value) was measured automatically using the appropriate software (OMNIC ver. 7.3). The spectral region 1800–900 cm⁻¹ was used to ‘fingerprint’ wine on the basis of grape variety. This simple and fast method of analysis showed that wines from different grape varieties can be differentiated between them.     

Chemical and discriminant analysis of bovine meat by near infrared reflectance spectroscopy (NIRS)

Near infrared reflectance spectroscopy (NIRS) was evaluated as a tool to segregate different types of bovine meat and predict several chemical fractions on samples from two breeds, three muscles and six grading (Chilean system) categories. Samples previously minced, frozen and thawed, were scanned (400–2500 nm) and then analyzed for dry matter, crude protein, ether extract, total ash and collagen content, after freeze drying. Discriminant analysis using a partial least squares regression technique and cross validation, correctly identified breed and muscle type for most samples, but carcass grades, with the exception of samples from calves, were not successfully predicted. Best calibrations for chemical composition tested by cross-validation, showed R² and standard errors of cross validation of 0.77 and 0.58% (dry matter), 0.82 and 0.48% (crude protein), 0.82 and 0.44% (ether extract). Calibrations for total ash showed a poor, and for collagen, a very poor prediction ability.     

Direct determination of lactulose in heat‐treated milk using diffuse reflectance infrared Fourier transform spectroscopy and partial least squares regression

The aim of this work was the direct determination of lactulose (LCT) concentration in freeze‐dried heat‐treated milks using diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) without any chemical pretreatment of the milk. The ‘actual’ lactulose concentrations estimated by means of high‐performance liquid chromatography (HPLC) were correlated with the spectral region 1286–754 cm^?1 of DRIFTS spectra in the second‐derivative form of the milk samples using partial least squares (PLS) regression. A linear relationship was established between the ‘actual’ and the concentrations recalculated using the built model. The proposed DRIFTS method is simple, rapid and low cost.     

Characterization of Pinus pinaster bark and its alkaline extracts by diffuse reflectance Fourier transform infrared (DRIFT) spectroscopy

bark and of the raffinates obtained after an alkaline extraction, and also the Stiasny number of the corresponding extracts. By means of a stepwise regression analysis a selection of the DRIFT spectra bands which allow to correlate satisfactorily the experimental results has been made.     

Characterization of Pinus pinaster bark and its alkaline extracts by diffuse reflectance Fourier transform infrared (DRIFT) spectroscopy

Pinus pinaster bark and of the raffinates obtained after an alkaline extraction, and also the Stiasny number of the corresponding extracts. By means of a stepwise regression analysis a selection of the DRIFT spectra bands which allow to correlate satisfactorily the experimental results has been made.

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Rapid recognition of marine fish surimi by one-step discriminant analysis based on near-infrared diffuse reflectance spectroscopy

A rapid and nondestructive near-infrared diffuse reflectance spectroscopy method combined with multivariate analysis was developed to discriminate different species and grades of marine fish surimi. Principal component analysis and discriminant analysis were applied to classify the species and quality grades of surimi. The results showed that excellent classification was obtained after optimizing spectral pretreatment. For the discrimination of three species of surimi, the correct classification rate of the calibration as well as the validation datasets were 98.5% and 100%, respectively, using the discriminant analysis method after multiplicative scatter correction pretreatment. For four grades of surimi, discriminant analysis provided 98.9% and 100% correct classification rate for calibration and validation datasets, respectively, after multiplicative scatter correction pretreatment. It was demonstrated that near-infrared diffuse reflectance spectroscopy integrated with discriminant analysis had significant potential as a rapid and accurate approach for rapid discrimination of surimi species and grades.     

Effect of homogenisation on detection of milk protein content based on NIR diffuse reflectance spectroscopy

Investigating the effect of homogenisation on the prediction performance of protein content by using near-infrared (NIR) spectroscopy is helpful to improve protein determination precision. For this purpose, the influence of homogenisation on milk fat globules and NIR spectra was analysed firstly. Then, NIR spectra of eighty-seven cow milk samples before and after homogenisation were obtained. Multiplicative scatter correction was used to do spectral pretreatment. Uninformative variable elimination based on partial least squares (UVE-PLS) and successive projection algorithm was used to extract characteristic variables. Partial least squares regression (PLSR) and least squares support vector machine models were established. The results showed that homogenisation made milk fat globules be distributed evenly, decreased the size of fat globules and improved NIR spectral repeatability and prediction precision on protein content. The best model was PLSR-UVE-PLS, having good and excellent protein prediction ability for un-homogenised milk (RMSEP = 0.06 g/100 g, RPD = 2.69) and homogenised milk (RMSEP = 0.04 g/100 g, RPD = 3.59), respectively.     

不同胎次奶牛乳中乳蛋白含量的近红外光谱定量分析

对不同胎次奶牛的牛奶样品进行近红外光谱扫描,并用多功能乳制品分析仪对牛奶样品中蛋白质的含量进行测定。利用正交实验设计,分别采用主成分回归法(PCR)、偏最小二乘法(PLS)、改进偏最小二乘法(MPLS)三种定量校正方法和多种光谱预处理方法建立模型,利用目标函数法对模型进行评定,结果表明:一胎、二胎奶牛乳样中乳蛋白的最优模型相同,其校正相关系数(R2)、定标标准差(SEC)和预测标准差(SEP)分别为:0.9626、0.0531、0.0630和0.9377、0.0810、0.1100;建立了三胎及以上奶牛乳样中乳蛋白的最优模型,R2、SEC和SEP分别为:0.9406、0.0461和0.0500;同时,建立了所有乳样中乳蛋白的最优模型,R2、SEC和SEP分别为:0.9351、0.0687和0.0790。所建模型对于快速、准确、无损、定量检测原料奶中乳蛋白的含量是可行的,该方法为快速检测混合原料奶中乳蛋白含量提供了理论依据。      

Effect of heat and transglutaminase on solubility of goat milk protein‐based films

The effect of heat, transglutaminase and combination of heat and transglutaminase treatments on the solubility of films prepared from goat milk casein, goat milk whey proteins and whole goat milk proteins was investigated. Goat milk casein films were less soluble when treated with transglutaminase and combination of heat with transglutaminase compare with heat‐treated caseins alone. Heat treatment was more effective at decreasing the solubility of whey protein films. SDS‐PAGE patterns demonstrated that goat milk caseins were better cross‐linked by transglutaminase, whereas whey proteins were better cross‐linked by heat. The extent of cross‐linking was further enhanced when a combination of heat and transglutaminase was used.     

应用傅立叶变换近红外光谱检测婴幼儿配方奶粉中的乳糖含量

利用傅立叶变换近红外光谱（FT-NIR）技术结合偏最小二乘法（PLS）对婴幼儿配方奶粉中的乳糖进行快速检测分析。搜集 94个不同产地、不同品牌的婴幼儿配方奶粉中乳糖的实验室数据,并采集婴幼儿配方奶粉的近红外光谱图,选择最优的光谱预处理方法,优化、验证和建立模型,并预测6个未知品牌的婴幼儿配方奶粉样品的乳糖含量。结果表明,不同阶段的婴幼儿配方奶粉有非常相似 的近红外特征图谱,图谱处理后的方差为95.423 5%,该模型测定的乳糖值与高效液相色谱（HPLC）法测定的乳糖值之间的平均相对误 差均≤0.67%,相对标准偏差（RSD）均≤0.88%,均符合误差范围。该方法可以无损、快速、高效地测定婴幼儿配方奶粉中的乳糖含量。     

Rapid characterization and identification of fatty acids in margarines using horizontal attenuate total reflectance Fourier transform infrared spectroscopy (HATR-FTIR)

Fourier transform infrared spectroscopy (FTIR) with horizontal attenuated total reflectance (HATR) coupled to multivariate analysis was used to predict chemical composition, fatty acid profile, nutritional relationships between fatty acids, and to identify trans fatty acids (TFA) of margarines. For model building and validation, a set of 42 margarines samples were analyzed in terms of fatty acid profile, total fat, moisture, and salt content. The quantitative models were based on incorporating the above chemical parameters of the different margarines and HATR-FTIR spectral information into the calibration model using chemometric analysis. Chemical parameters for total fat, moisture, and salt content ranged 39–84.5%, 14.5–59%, and 0.3–2.6%, respectively. Regarding fatty acids, the concentration of TFA, saturated fatty acid (SFA), monounsaturated fatty acid (MUFA), and polyunsaturated fatty acid (PUFA) ranged 0–34.06%, 17.17–54.20%, 15.26–34.49%, and 4.02–53.89% (g/100 g margarine), respectively. Principal components regression (PCR) and partial least square analysis (PLS) were used to inspect the variation within the sample set. The best model to predict the chemical composition was obtained using the algorithm partial least squares (PLS) with a R ² greater than 0.933 and SEC and SEP less than 1.294 and 1.406, respectively. The optimized SIMCA model used to identify high or low TFA content showed 100% correct classification rate of both margarines with less than 2.0 g TFA/100 g fat as more than 2.0 g TFA/100 g fat. Compared with traditional chemical analysis, the FTIR-HATR models analyzed margarines in minutes and directly in their neat form.     

Predicting bovine milk fat composition using infrared spectroscopy based on milk samples collected in winter and summer

It has recently been shown that Fourier transform infrared spectroscopy has potential for the prediction of detailed milk fat composition, even based on a limited number of observations. Therefore, there seems to be an opportunity for improvement by means of using more observations. The objective of this study was to verify whether the use of more data would add to the accuracy of predicting milk fat composition. In addition, the effect of season on modeling was quantified because large differences in milk fat composition between winter and summer samples exist. We concluded that the use of 3,622 observations does increase predictability of milk fat composition based on infrared spectroscopy. However, for fatty acids with low concentrations, the use of many observations does not increase predictability to a level at which application of the model becomes obvious. Furthermore, the effect of season on validation r-square was limited but was occasionally large on prediction bias. For fatty acids that show large differences in level and standard deviation between winter and summer, a representative sample that includes observations collected in various seasons is critical for unbiased prediction. This research shows that all major fatty acids, combined groups of fatty acids, and the ratio of saturated to unsaturated fatty acids can be predicted accurately.     

Analysis of wood surfaces and ground wood by diffuse reflectance (DRIFT) and photoacoustic (PAS) Fourier transform infrared spectroscopic techniques

Infrared diffuse reflectance and photoacoustle spectra were measured from wood powder and solid wood blocks and compared with the corresponding transmission spectra measured from thin wood sections. Studies indicated that high quality spectra could be obtained from either solid wood blocks or powder by diffuse reflectance (DRIFT) and photoacoustic (PAS) techniques. Positions of IR bands measured from different hardwood species by DRIFT and PAS technique are approximately same. However, the relative intensities of IR bands vary among species. For obtaining reproducible DRIFT spectra from the solid wood surfaces, roughness and structure of the cut (tangential, radial or transverse) must be identical. Whereas, for wood powder, smallest particle size results in best resolved spectrum. Specular reflection causes distortions in the intensities of the bands in the range 1150-950 cm^?1, which can be minimised either by diluting sample powder in KBr (concentration <2%) or by increasing the surface roughness of the solid block. FTIR-PAS spectra measured from wood powder are quite similar to spectra obtained by transmission and/or DRIFT techniques. Relative intensity and position of various IR bands measured by photoacoustic technique are independent of size of the particle and its concentration. These results indicate the usefulness of PAS technique over other solid sampling techniques.     

基于近红外光谱定量分析牛奶中掺假的动物水解蛋白含量

动物水解蛋白含有大量重金属离子,摄入人体危害人体健康,因其蛋白质含量高,被不法商贩作为廉价蛋白质添加在牛奶中以提高蛋白质含量。本研究自行配制不同浓度的动物水解蛋白掺假牛奶,应用近红外光谱仪浸入式光纤扫描样品,考察建模方法、预处理方法、建模范围、主成分数及样品的异常点分析对定量分析模型的影响。结果表明:使用SG平滑处理、主成分数4、在10000⁵000 cm^-1使用PLS法建立了最优动物水解蛋白定量分析模型。该模型的校正均方差（RMSEC）、预测均方差（RMSEP）、相关系数（r）分别为0.115、0.305、0.983,平均回收率为104.44%。该分析模型可以用于牛奶中动物水解蛋白的快速定量分析,为牛奶的品质控制和快速定量提供参考。      

Analysis of pork adulteration in beef meatball using Fourier transform infrared (FTIR) spectroscopy

Meatball is one of the favorite foods in Indonesia. The adulteration of pork in beef meatball is frequently occurring. This study was aimed to develop a fast and non destructive technique for the detection and quantification of pork in beef meatball using Fourier transform infrared (FTIR) spectroscopy and partial least square (PLS) calibration. The spectral bands associated with pork fat (PF), beef fat (BF), and their mixtures in meatball formulation were scanned, interpreted, and identified by relating them to those spectroscopically representative to pure PF and BF. For quantitative analysis, PLS regression was used to develop a calibration model at the selected fingerprint regions of 1200-1000 cm(-1). The equation obtained for the relationship between actual PF value and FTIR predicted values in PLS calibration model was y = 0.999x + 0.004, with coefficient of determination (R(2)) and root mean square error of calibration are 0.999 and 0.442, respectively. The PLS calibration model was subsequently used for the prediction of independent samples using laboratory made meatball samples containing the mixtures of BF and PF. Using 4 principal components, root mean square error of prediction is 0.742. The results showed that FTIR spectroscopy can be used for the detection and quantification of pork in beef meatball formulation for Halal verification purposes.     

Quantitative determination of fatty acid compositions in micro-encapsulated fish-oil supplements using Fourier transform infrared (FTIR) spectroscopy

The research describes a rapid method for the determination of fatty acid (FA) contents in a micro-encapsulated fish-oil (μEFO) supplement by using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic technique and partial least square regression (PLSR) analysis. Using the ATR-FTIR technique, the μEFO powder samples can be directly analysed without any pre-treatment required, and our developed PLSR strategic approach based on the acquired spectral data led to production of a good linear calibration with R(2)=0.99. In addition, the subsequent predictions acquired from an independent validation set for the target FA compositions (i.e., total oil, total omega-3 fatty acids, EPA and DHA) were highly accurate when compared to the actual values obtained from standard GC-based technique, with plots between predicted versus actual values resulting in excellent linear fitting (R(2)≥0.96) in all cases. The study therefore demonstrated not only the substantial advantage of the ATR-FTIR technique in terms of rapidness and cost effectiveness, but also its potential application as a rapid, potentially automated, online monitoring technique for the routine analysis of FA composition in industrial processes when used together with the multivariate data analysis modelling.