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1.
The potential of Fourier transform mid-infrared spectroscopy (FT-MIR) using an attenuated total reflectance (ATR) cell was evaluated for the authentication of 11 unifloral (acacia, alpine rose, chestnut, dandelion, heather, lime, rape, fir honeydew, metcalfa honeydew, oak honeydew) and polyfloral honey types (n = 411 samples) previously classified with traditional methods such as chemical, pollen, and sensory analysis. Chemometric evaluation of the spectra was carried out by applying principal component analysis and linear discriminant analysis, the error rates of the discriminant models being calculated by using Bayes' theorem. The error rates ranged from <0.1% (polyfloral and heather honeys as well as honeydew honeys from metcalfa, oak, and fir) to 8.3% (alpine rose honey) in both jackknife classification and validation, depending on the honey type considered. This study indicates that ATR-MIR spectroscopy is a valuable tool for the authentication of the botanical origin and quality control and may also be useful for the determination of the geographical origin of honey.  相似文献   

2.
The saccharide profiles of 5 different botanical species in 86 Italian honey samples were investigated by 1H and 1H-13C NMR spectroscopy. Nineteen saccharides were identified in the aqueous extracts, namely, fructose, glucose, gentiobiose, isomaltose, kojibiose, maltose, maltulose, melibiose, nigerose, palatinose, sucrose, turanose, erlose, isomaltotriose, kestose, maltotriose, melezitose, raffinose, and maltotetraose. PCA performed on NMR spectral regions, in particular between 4.400 and 5.700 ppm and the fructose signal at 4.050 ppm, revealed a partial sample grouping. The score contribution plots derived from PCA performed using the mean values for the buckets of the anomeric region for each floral source allowed the identification of saccharides characterizing different honeys. OPLS-DA models were further evaluated to confirm the previous findings. OPLS-DA models were also built to highlight differences between polyfloral and high mountain polyfloral honeys and between high mountain polyfloral and rhododendron honeys, both collected at high altitude; S-plots highlighted the characteristic saccharides.  相似文献   

3.
Front-face fluorescence spectroscopy, directly applied on honey samples, was used for the authentication of 11 unifloral and polyfloral honey types (n = 371 samples) previously classified using traditional methods such as chemical, pollen, and sensory analysis. Excitation spectra (220-400 nm) were recorded with the emission measured at 420 nm. In addition, emission spectra were recorded between 290 and 500 nm (excitation at 270 nm) as well as between 330 and 550 nm (excitation at 310 nm). A total of four different spectral data sets were considered for data analysis. Chemometric evaluation of the spectra included principal component analysis and linear discriminant analysis; the error rates of the discriminant models were calculated by using Bayes' theorem. They ranged from <0.1% (polyfloral and chestnut honeys) to 9.9% (fir honeydew honey) by using single spectral data sets and from <0.1% (metcalfa honeydew, polyfloral, and chestnut honeys) to 7.5% (lime honey) by combining two data sets. This study indicates that front-face fluorescence spectroscopy is a promising technique for the authentication of the botanical origin of honey and may also be useful for the determination of the geographical origin within the same unifloral honey type.  相似文献   

4.
The importance of honey has been recently increased because of its nutrient and therapeutic effects, but the adulteration of honey in terms of botanical origin has increased, too. The floral origin of honeys is usually determined using melisso-palynological analysis and organoleptic characteristics, but the application of these techniques requires some expertise. A number of papers have confirmed the possibility of characterizing honey samples by selected chemical parameters. In this study high-resolution nuclear magnetic resonance (HR-NMR) and multivariate statistical analysis methods were used to identify and classify honeys of five different floral sources. The 71 honey samples (robinia, chestnut, citrus, eucalyptus, polyfloral) were analyzed by HR-NMR using both 1H NMR and heteronuclear multiple bond correlation spectroscopy (HMBC). Spectral data were analyzed by application of unsupervised and supervised pattern recognition and multivariate statistical techniques such as principal component analysis (PCA) and general discriminant analysis (GDA). The use of 1H-(13)C HMBC coupled with appropriate statistical analysis seems to be an efficient technique for the classification of honeys.  相似文献   

5.
The potential of front-face fluorescence spectroscopy for the authentication of unifloral and polyfloral honey types (n = 57 samples) previously classified using traditional methods such as chemical, pollen, and sensory analysis was evaluated. Emission spectra were recorded between 280 and 480 nm (excit: 250 nm), 305 and 500 nm (excit: 290 nm), and 380 and 600 nm (excit: 373 nm) directly on honey samples. In addition, excitation spectra (290-440 nm) were recorded with the emission measured at 450 nm. A total of four different spectral data sets were considered for data analysis. After normalization of the spectra, chemometric evaluation of the spectral data was carried out using principal component analysis (PCA) and linear discriminant analysis (LDA). The rate of correct classification ranged from 36% to 100% by using single spectral data sets (250, 290, 373, 450 nm) and from 73% to 100% by combining these four data sets. For alpine polyfloral honey and the unifloral varieties investigated (acacia, alpine rose, honeydew, chestnut, and rape), correct classification ranged from 96% to 100%. This preliminary study indicates that front-face fluorescence spectroscopy is a promising technique for the authentication of the botanical origin of honey. It is nondestructive, rapid, easy to use, and inexpensive. The use of additional excitation wavelengths between 320 and 440 nm could increase the correct classification of the less characteristic fluorescent varieties.  相似文献   

6.
Proton high‐resolution magic angle spinning nuclear magnetic resonance (1H HR‐MAS NMR) has been applied for the analysis of two cultivars of durum wheat produced in different Italian geographical areas. Furthermore, on the same samples, isotopic ratios were measured by mass spectrometry (IRMS). The application of chemometrics to these results permitted the discrimination of semolina by cultivar and geographical origin. A similar approach has been applied to the results obtained from chemical analyses. The comparison showed that NMR spectroscopy can provide a faster method for the detection of differences among the durum wheat semolina according to geographical and varietal origin. Furthermore, IRMS data are suitable to provide information about the geographical origin of samples. This present investigation is part of an extensive research project to find a scientific method capable of classifying wheat foods for the assignment of a “denomination of origin” trademark.  相似文献   

7.
Proton nuclear magnetic resonance spectroscopy ((1)H NMR) and multivariate analysis techniques have been used to classify honey into two groups by geographical origin. Honey from Corsica (Miel de Corse) was used as an example of a protected designation of origin product. Mathematical models were constructed to determine the feasibility of distinguishing between honey from Corsica and that from other geographical locations in Europe, using (1)H NMR spectroscopy. Honey from 10 different regions within five countries was analyzed. (1)H NMR spectra were used as input variables for projection to latent structures (PLS) followed by linear discriminant analysis (LDA) and genetic programming (GP). Models were generated using three methods, PLS-LDA, two-stage GP, and a combination of PLS and GP (PLS-GP). The PLS-GP model used variables selected by PLS for subsequent GP calculations. All models were generated using Venetian blind cross-validation. Overall classification rates for the discrimination of Corsican and non-Corsican honey of 75.8, 94.5, and 96.2% were determined using PLS-LDA, two-stage GP, and PLS-GP, respectively. The variables utilized by PLS-GP were related to their (1)H NMR chemical shifts, and this led to the identification of trigonelline in honey for the first time.  相似文献   

8.
Fourier transform near-infrared spectroscopy (FT-NIR) was evaluated for the authentication of eight unifloral and polyfloral honey types (n = 364 samples) previously classified using traditional methods such as chemical, pollen, and sensory analysis. Chemometric evaluation of the spectra was carried out by applying principal component analysis and linear discriminant analysis. The corresponding error rates were calculated according to Bayes' theorem. NIR spectroscopy enabled a reliable discrimination of acacia, chestnut, and fir honeydew honey from the other unifloral and polyfloral honey types studied. The error rates ranged from <0.1 to 6.3% depending on the honey type. NIR proved also to be useful for the classification of blossom and honeydew honeys. The results demonstrate that near-infrared spectrometry is a valuable, rapid, and nondestructive tool for the authentication of the above-mentioned honeys, but not for all varieties studied.  相似文献   

9.
Isotope parameters (δ(13)C(honey), δ(13)C(protein), δ(15)N) were determined for 271 honey samples of 7 types (black locust, multifloral, lime, chestnut, forest, spruce, and fir honeys) from 4 natural geographical regions of Slovenia. Carbon and nitrogen stable isotope ratios were measured to elucidate the applicability of this method in the identification of the botanical and geographical origin of honey and in honey adulteration. Only 2.2% of the samples were adulterated according to the internal standard carbon isotope ratio analysis method. Botanical origin did not have any major influence on the honey isotope profiles; only black locust honey showed higher δ(13)C values. Some differences were seen across different production years, indicating that the influence of season should be further tested. Statistical and multivariate analyses demonstrated differences among honeys of various geographical origins. Those from the Alpine region had low δ(13)C (-26.0‰) and δ(15)N values (1.1‰); those from the Mediterranean region, high δ(13)C (-24.6‰) and medium δ(15)N values (2.2‰); those from the Pannonian region, medium δ(13)C (-25.6‰) and high δ(15)N value (3.0‰); and those from the Dinaric region, medium δ(13)C (-25.7‰) and low δ(15)N values (1.4‰).  相似文献   

10.
近红外光谱结合化学计量学方法检测蜂蜜产地   总被引：8，自引：4，他引：4  
为了实现蜂蜜产地的快速判别,应用近红外光谱结合化学计量学方法对蜂蜜产地进行了判别分析。kennard-Stone法划分训练集和预测集。光谱用一阶导数加自归一化预处理后,再用小波变换（WT）进行压缩和滤噪。结合滤波后光谱信息,分别用径向基神经网络（RBFNN）和偏最小二乘-线性判别分析（PLS-LDA）建立了苹果蜜产地和油菜蜜产地的判别模型。对不同小波基和分解尺度进行了讨论。对苹果蜜,WT-RBFNN模型和WT-PLS-LDA模型都是小波基为db1、分解尺度为2时的预测精度较好,都为96.2%。对油菜蜜：WT-RBFNN模型在小波基为db4和分解尺度为1时,预测精度较好,为85.7%;WT-PLS-LDA模型在小波基为db9、分解尺度也为1时,预测精度较好,为90.5%。研究表明：WT结合线性的PLS-LDA建模比WT结合非线性的RBFNN建模更适于蜂蜜产地判别;近红外光谱技术具有快速判别蜂蜜产地的潜力。  相似文献   

11.
应用近红外光谱结合化学计量学方法对蜂蜜产地进行了判别分析。kennard-Stone法划分训练集和预测集。光谱用一阶导数加自归一化预处理后,再用小波变换（WT）进行压缩和滤噪。结合滤波后光谱信息,分别用径向基神经网络（RBFNN）和偏最小二乘-线性判别分析（PLS-LDA）建立了苹果蜜产地和油菜蜜产地判别模型。对不同小波基和分解尺度进行了详细讨论。对苹果蜜,WT-RBFNN模型和WT-PLS-LDA模型都是小波基为db1、分解尺度为2时的预测精度最好,都为96.2%。对油菜蜜：WT-RBFNN模型在小波基为db4和分解尺度为1时,预测精度最好;WT-PLS-LDA模型在小波基为db9、分解尺度也为1时,预测精度最好,为90.5%;预测精度WT-PLS-LDA模型优于WT-RBFNN模型。研究表明：WT结合线性的PLS-LDA建模比WT结合非线性的RBFNN建模更适于蜂蜜产地鉴别;近红外光谱结合WT-PLS-LDA可实现对蜂蜜产地的快速无损检测,为蜂蜜产地鉴别提供了一种新方法。  相似文献   

12.
We tested the potential of High-Resolution MAS NMR spectroscopy to study 20 samples of Emmental cheeses from 7 different geographical regions. Principal component analysis (PCA) and discriminant analysis (DA) were used to analyze the data set of 1H HRMAS NMR spectra and succeeded in grouping the studied samples according to their geographical origins.  相似文献   

13.
With the objective of finding floral markers for the determination of the botanical origin of acacia (robinia) honey, the phytochemicals present in nectar collected from Robinia pseudacacia flowers were analyzed by high-performance liquid chromatography-tandem mass spectrometry. Eight flavonoid glycosides were detected and characterized as kaempferol combinations with rhamnose and hexose. Acacia honey produced in the same location where the nectar was collected contained nectar-derived kaempferol rhamnosides. This is the first time that flavonoid glycosides have been found as honey constituents. Differences in the stability of nectar flavonoids during honey elaboration and ripening in the hive were shown to be due to hydrolytic enzymatic activity and to oxidation probably related to hydrogen peroxide (glucose-oxidase) activity. Acacia honeys contained propolis-derived flavonoid aglycones (468-4348 microg/100 g) and hydroxycinnamic acid derivatives (281-3249 microg/100 g). In addition, nectar-derived kaempferol glycosides were detected in all of the acacia honey samples analyzed (100-800 microg/100 g). These flavonoids were not detected in any of the different honey samples analyzed previously from different floral origins other than acacia. Finding flavonoid glycosides in honey related to floral origin is particularly relevant as it considerably enlarges the number of possible suitable markers to be used for the determination of the floral origin of honeys.  相似文献   

14.
The free amino acid content of 61 honey samples from Estonia has been determined by HPLC-UV with precolumn derivatization with diethyl ethoxymethylenemalonate. Analyzed samples were seven types of unifloral honeys and polyfloral honeys. The main amino acids found in Estonian honeys were proline and phenylalanine. The resulting data have been analyzed by t test and principal component analysis (PCA). t Test revealed that some amino acids (alpha-alanine, beta-alanine, asparagine, gamma-aminobutyric acid, glutamine, glycine, histidine, ornithine, phenylalanine, proline, serine, and tryptophan) are more potent for assigning honey botanical origin than others. PCA enabled differentiation of some honey types by their botanical origin. In the space of the two first principal components, heather honeys form a cluster that is clearly separable from, for example, polyfloral honeys. It is concluded that analysis of the free amino acid profile may serve as a useful tool to assess the botanical origin of Estonian honeys.  相似文献   

15.
1H high-field nuclear magnetic resonance (NMR) was used to analyze 216 extra virgin olive oils collected in three years (1996, 1997, and 1998) in different Italian areas in order to evaluate the potential contribution of this technique to the geographical characterization of olive oils. A statistical procedure performed on the intensity of selected NMR peaks has been proposed. Tree clustering analysis of NMR data performed without any a priori hypothesis showed the existence of reliable parameters able to group the olive oils according to the location of olive oil production. Linear discriminant analysis applied to selected NMR parameters of olive oils of the same year of production allowed the grouping of samples according to their geographical origin with only very few errors. Moreover, a satisfactory grouping is reached by combining the NMR data of olive oils from two different years (1996 and 1997). Operating on appropriate sampling, a careful analysis of data yielded the conclusion that the place of olive production could be singled out as a discriminating factor regardless of the cultivars from which the olive oils are derived.  相似文献   

16.
Ingrid Kgel-Knabner 《Geoderma》1997,80(3-4):243-270
Nuclear magnetic resonance (NMR) is a valuable tool for the characterization of soil organic matter and humification processes in soils. This review highlights soil organic matter studies based mainly on solid-state 13C and 15N NMR spectroscopy and some emerging applications, that may provide significant progress in our knowledge on soil organic matter. A major advantage of Nmr spectroscopy is that it can be used as a non-invasive method for solid soil samples or soil fractions. Although resolution is limited, one can obtain an overview on the organic matter structures present in the soil sample. Application of 13C and 15N NMR to soils has, for a long time, been confined to the study of bulk soils or humic extracts for structural characterization. The transformations of soil organic C and N are now being investigated after addition of 13C- and 15N-labelled parent materials to the soil and following their evolution in different C and N pools. With labelling techniques it is also possible to study the interaction of organic pollutants with soil organic matter. Contamination of a soil with man-made additives, such as soot or brown coal dust, can also be detected in soils or individual soil fractions.  相似文献   

17.
Nuclear magnetic resonance (NMR) spectroscopy combined with multivariate data analysis (MVA) was used to investigate the molecular components of the aqueous extract of samples of bottarga, that is, salted and dried mullet (Mugil cephalus) roe, manufactured in Sardinia (Italy) from mullets of known and unknown geographical provenience. Principal component analysis (PCA) applied to the processed (1)H NMR spectra indicated that samples tend to cluster according to their geographical origin and also on the basis of storage and manufacturing procedures. The most important metabolites that characterized grouping of samples are the free amino acids methionine (Met), glutamate (Glu), histidine (His), phenylalanine (Phe), tyrosine (Tyr), and isoleucine (Ile); trimethylamine (TMA) and dimethylamine (DMA), both biomarkers of degradation; nucleotides and derivatives; choline (Cho) and phosphorylcholine (P-cho); and lactate (Lac).  相似文献   

18.
The potential of near-infrared (NIR) spectroscopy to determine the geographical origin of honey samples was evaluated. In total, 167 unfiltered honey samples (88 Irish, 54 Mexican, and 25 Spanish) and 125 filtered honey samples (25 Irish, 25 Argentinean, 50 Czech, and 25 Hungarian) were collected. Spectra were recorded in transflectance mode. Following preliminary examination by principal component analysis (PCA), modeling methods applied to the spectral data set were partial least-squares (PLS) regression and soft independent modeling of class analogy (SIMCA); various pretreatments were investigated. For unfiltered honey, best SIMCA models gave correct classification rates of 95.5, 94.4, and 96% for the Irish, Mexican, and Spanish samples, respectively; PLS2 discriminant analysis produced a 100% correct classification for each of these honey classes. In the case of filtered honey, best SIMCA models produced correct classification rates of 91.7, 100, 100, and 96% for the Argentinean, Czech, Hungarian, and Irish samples, respectively, using the standard normal variate (SNV) data pretreatment. PLS2 discriminant analysis produced 96, 100, 100, and 100% correct classifications for the Argentinean, Czech, Hungarian, and Irish honey samples, respectively, using a second-derivative data pretreatment. Overall, while both SIMCA and PLS gave encouraging results, better correct classification rates were found using PLS regression.  相似文献   

19.
In this study, various organic compounds in commercial whole milk were quantified simultaneously by 1H 1D and 1H - 13C HSQC 2D NMR spectra without any pretreatment. 2D NMR spectroscopy was applied to quantification of milk compounds for the first time. Milk fat content was easily determined to be 3.6 +/- 0.1%, and the lactose content was 47.8 +/- 1.0 mg/mL by 1H NMR spectra. From 1H-13C HSQC spectra, the concentrations of citrate, N-acetylcarbohydrates, and trimethylamine were determined to be 3.2 +/- 0.2, 2.9 +/- 0.1, and 4.0 +/- 0.6 mM, respectively. The latter two compounds were quantified in milk for the first time. Butyric acid, total monounsaturated fatty acids, and total polyunsaturated fatty acids of triacylglycerols were 6.2 +/- 0.5, 9.1 +/- 0.9, and 2.9 +/- 0.3 mM, respectively. The fatty acid compositions (mol %) of triacylglycerols were then calculated and were observed to be in good agreement with reference values. The results indicated that 1H 1D and 1H-13C HSQC 2D NMR spectroscopy is useful for the rapid and nondestructive determination of various compounds in milk.  相似文献   

20.
Multielemental (C, N, H, S) stable isotope ratio analysis was used as an analytical tool to verify the geographical origin of beef from several European and non-European countries. Beef samples were collected from nine different countries, and the (13)C/(12)C, (15)N/(14)N, (2)H/(1)H, and (34)S/(32)S ratios of defatted beef were measured using isotope ratio mass spectrometry (IRMS). There were highly significant differences in the mean isotopic values of the beef from different countries. The results of discriminant analysis showed that the four isotope ratios were significant for the discrimination of geographical origin and that 84.9% of the samples were correctly assigned to the country of origin (82.2% when cross-validated). Beef was also classified according to geographical origin when additional information on different feeding regimens used in Ireland was included, with 85.0% of the samples correctly allocated and 82.9% cross-validated using the isotopic signatures. All of the Irish beef samples verifiable as pasture-fed beef were correctly classified and then cross-validated.  相似文献   

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