• <tr id="yyy80"></tr>
  • <sup id="yyy80"></sup>
  • <tfoot id="yyy80"><noscript id="yyy80"></noscript></tfoot>
  • 99热精品在线国产_美女午夜性视频免费_国产精品国产高清国产av_av欧美777_自拍偷自拍亚洲精品老妇_亚洲熟女精品中文字幕_www日本黄色视频网_国产精品野战在线观看 ?

    Determination of Geographical Origin and Protein Content of Acacia Gums Using Infrared Spectroscopy and Chemometrics

    2017-10-11 11:36:34ZOUXiaoboAlaaKamalMohmmedKHAIRKHOGLYSHIJiyongMelHOLMES
    食品科學(xué) 2017年20期
    關(guān)鍵詞:阿拉伯膠計量學(xué)基金項目

    ZOU Xiaobo, Alaa Kamal Mohmmed KHAIR KHOGLY, SHI Jiyong, Mel HOLMES

    (1. School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China;2. School of Food Science and Nutrition, the University of Leeds, Leeds LS1 3AB, United Kingdom)

    Determination of Geographical Origin and Protein Content of Acacia Gums Using Infrared Spectroscopy and Chemometrics

    ZOU Xiaobo1, Alaa Kamal Mohmmed KHAIR KHOGLY1, SHI Jiyong1, Mel HOLMES2

    (1. School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China;2. School of Food Science and Nutrition, the University of Leeds, Leeds LS1 3AB, United Kingdom)

    The feasibility of using Fourier transform infrared (FTIR) spectroscopy and chemometrics as a rapid and noninvasive technique to determine the geographical origin and protein content of Sudanese Acacia gums was investigated.Seventy-two samples of Acacia gums were collected from six different regions (12 samples from each region). Linear discriminant analysis (LDA) was used to discriminate the geographical origin of Acacia gums, and backward in terval partial least squares (Bi-PLS) was applied to build a prediction model for the protein content of Acacia gums. The results showed that the recognition rates of LDA for calibration set (48 samples) and prediction set (24 samples) were both 100% when the fi rst 6 principal components were used. In addition, Bi-PLS yielded a good prediction model (RP= 0.937 3 and RMSEP =0.173%) for protein content by using the optimal combination of 4 out of 20 spectral intervals. Hence, FTIR spectroscopy coupled with chemometrics can be considered as a valid approach for the determination of the geographical origin and protein content of Acacia gums.

    Acacia gums; Fourier transform infrared (FTIR) spectroscopy; geographical origin; protein content;linear discriminant analysis (LDA); backward interval partial least squares (Bi-PLS)

    Acacia gums, also called gums Arabic, are the dried exudates extracted from the stem and branches of Acacia trees. They are often used as non-digestible food ingredients in the foodstuffs, such as an emulsifier in the manufacture of soft drinks and a stabilizer in fermentation milk[1]. The chemical composition of gum Arabic is complex and consists of a group of macromolecules characterized by a high proportion of carbohydrates (-97%), which are predominantly composed of D-galactose and L-arabinose units and a low proportion of proteins (<3%)[2]. Acacia gums from different Acacia species exhibited different characteristics, and even gums in the same species bear some difference because of their geographical origin. For example, Acacia senegal(A. senegal) has a higher degree of branching and better emulsifying properties than Acacia seyal (A. seyal), gum does[3]. This is because their biochemical composition and molecular characteristics can vary, depending on internal and external factors (Acacia specie, tree location, or weather conditions) and postharvesting processes (storage conditions,filtration, spray drying, irradiation, or heat treatments)[4].Hence, recognition of these Acacia gums is of great signifi cance for the market and the end use.

    Traditionally, the identifi cation of the speices or quality of Acacia gums can be conducted by sensory analysis, such as observing the color and smelling, which are unfortunately impeded the subjectivity of human. Other physicochemical methods, such as detection of the sugar and nitrogen content[5], and component analysis by using combined gel permeation chromatography and multi-angle laser light scattering (GPC-MALLS)[6], are either destructive to samples or time-consuming. Nuclear magnetic resonance(NMR) was also regarded as an effective technology to identify A. senegal and A. seyal, but it may be inaccessible for industrial high throughput screening purposes[7]. As a result, a rapid, non-invasive and economical method for distinguishing the speices or the quality of Acacia gums is highly desired.

    Fourier transform infrared (FTIR) spectroscopy, which keeps the advantages of being robust, cost-effective and nondestructive to sample, has been widely used as an effective identifi cation and quantitative analysis technique[8]. In recent years, many studies have shown the feasibility of using FTIR spectroscopy in discriminating similar foodstuffs and medicines, such as walnut oil[9], Cortex Eucommiae[10],minced beef[11], and detecting specific components, such as free acids, invertase, moisture, hydroxymethyl furfural,polyphenol oxidase and electrical conductivity[12-14].Quantification of gums is another interesting issue for determining the quality of the gums. For A. senegal and A. seyal gums, one of the most signifi cant difference is their protein content (-2.5% for A. senegal, -1% for A. seyal gums)[15]. Accordingly, the protein content can be used as an imporatant quality index of these Acacia gums.

    Sudan is a dominant leader in Acacia gum production in the world[16]. The aim of the present work is discriminating the A. senegal and A. seyal gums collected from Sudan,and predicting their total protein content by using FTIR spectroscopy and chemometrics.

    1 Materials and Methods

    1.1 Materials

    Two categories of Acacia gum samples (n=72) were collected from different regions in Sudan, namely A. senegal(n=36) (Group (A), n=12∶ West Bara Locality in North Kordofan State; Group (B), n=12∶ Ennuhud Locality in West Kordofan State; Group (D), n=12∶ Acacia gum Ltd., Sudan)and Acacia sayal (n=24) (Group (C), n=12∶ South Kordofan State; Group (E), n=12∶ Acacia gum Ltd., Sudan). One other Acacia gum sample was obtained from China (Group (F),n=12∶ Siyuan Biology Ltd., Henan, China). All other reagents are of analytical grade purchased from Sinopharm Chemical Reagent Co. Ltd., Shanghai, China.

    1.2 Methods

    1.2.1 Determination of total protein content

    Firstly, all raw Acacia gum samples were dried ina forced draught oven (Shanghai Yi-Heng Machine Co.,Shanghai, China) at 50 ℃ for 24 h and then mashed into powder by using a cyclone mill. The total protein contents of the gums were measured by using the Kjeldahl method[17].

    1.2.2 FTIR spectroscopy

    FTIR spectra of gum powders were collected by using a FTIR spectrometer (Thermo Scientifi c Nicolet iS50, Thermo Fisher, USA). The spectra were obtained at reflectance mode from 650–4 000 cm?1at a resolution of 4 cm?1and the total number of scans was 32. Three spectra were recorded for each sample and the average spectrum was used for subsequent data analysis.

    1.2.3 Chemometrics

    Pri nciple component analysis (PCA) is a statistical procedure which is able to reduce the dimensions of the data set by using an orthogonal transformation[18]. After PCA, the useful information can be extracted from the original spectral data by eliminating overlapping information and the remained dimensions are defined by principal components (PCs).It is able to provide the visual graphical information for determining differences within and between cluster trends[19].

    Lin ear discriminant analysis (LDA) is a c lassical statistical approach for feature extraction and dimension reduction[20]. LDA can classify the objects into groups by estimating the distance between each observation form all group centers[21]. It manages to find out the optimal transformation (projection) that minimizes the intraclass distance and maximizes the inter-class distance simultaneously in order to achieve the maximum discrimination.

    Partial least squares (PLS) regression is one of the multiple linear regression methods[22]. PLS is useful when number of predictors (i.e. spectral peaks) is much higher than number of samples in data set[23]. Backward interval partial least squares (Bi-PLS) regression is an extension of PLS. The basic principle of Bi-PLS is as follows[24]∶ The fullspectrum region is split into a number of equidistant spectral subintervals. Then, PLS models are calculated with each subinterval left out. The fi rst left out interval is the one that when it gives the poorest performing model with respect to the root mean square error of cross-validation (RMSECV).

    A cross-validation process was used in model validation with leave-one-out method. The performance of the regression models was evaluated according to the correlation coefficient of calibration set (Rc) and prediction set (RP), RMSECV and root mean standard error of prediction set (RMSEP). Gen erally, a good model should have high correlation coefficients along with low RMSECV and RMSEP[25].

    1.3 Data analysis

    Matlab V7.0 (MathWorks, USA) was used for data processing under Windows 7.

    2 Results and Analysis

    2.1 The total protein content of Aca cia gums

    All 72 samples were randomly separated into two subsets, including the calibration set (48 samples) used to build models and the prediction set (24 samples) used to test the robustness of models. The total protein content in Acacia gums is shown in Table 1. It can be seen that the total protein contents of A. senegal (Groups (A), (B), and (D)) and A. sayal (Groups (C) and (E)) were in the range of 1.53%–2.22% and 0.56%–1.87%, respectively. These results are close to the Sud anese Standards and Metrology Organization (SSMO) in which the protein contents for A. senegal and A. sayal gums are recorded to be in the range of 1.50%–2.70% and 0.7%–1.0%, respectively. In comparison,the Acacia gums obtained from Group (D) had the highest protein content, while the Acacia gums obtained from China had the lowest protein content. These difference were closely associated with the species of the Acacia gums and also with the gum origin, age, storage conditions, and so forth[26].

    Table 1 Protein content of Acacia gums

    2.2 Spectra investigation

    The FTIR spectra for the Acacia gum samples acquired in the range of 650–4 000 cm–1are shown in Fig. 1. In order to avoid the strong absorption of water, especially in the amide I band region (1 720–1 580 cm–1)[17], Acacia gums were fully dried before spectra collection. For all of the Acacia gums, there are four main characteristic spectral bands. No significant difference can be observed between the FTIRspectra of different groups. This is because all of them consist of similar kinds of chemical components. Table 2 shows the wavenumbers and attribution of the characteristic spectral bands of these Acacia gums.

    Fig. 1 FTIR spectra of Acacia gums

    Table 2 Wavenumbers and ttribution of the characteristic spectral bands in FTIR spectra of Acacia gums

    2.3 Principle component analysis of FTIR spectra of Acacia gum

    Prior to regression analysis, an exploratory analysis was performed in order to investigate any trend of discrimination among the Acacia gums from different regions. PCA is the most widely applied linear projection method for unsupervised exploratory multivariate data analysis to visualize the similarities and differences between the spectra[29]. Before PCA, the raw mean spectra were preprocessed by using standard normal variate (SNV). Fig. 2a shows the score plot of the two-dimensional component space of six categories of Acacia gum samples. The accumulated variance contribution rates were 99.33% for the top two PCs.The classifi cation trend of these six categories of Acacia gum samples can be also observed from the score plot. The Acacia gum samples obtained from China were clearly separated from that obtained from Sudan, indicating the obvious difference of the chemical constituents between the Acacia gum from different geographical origins. In order to furtherly visualize the difference between Acacia gum collected from Sudan, PCA was conducted for the Acacia gum regardless of Group (F) and the score plot of the two-dimensional was shown in Fig. 2b. It can be seen that the five categories of Acacia gum from Sudan are clearly distinguished from each other, demonstrating their intrinsic difference. Nevertheless,PCA is not able to defi ne the boundaries of the six categories to discriminate the Acacia gum samples so that further analysis was carried out in the next sections.

    Fig. 2 S core cluster plot of top two principal components (PCs) for Acacia gum samples

    2.4 Determination of geographical of Ac acia gum by LDA

    LDA focus on finding the optimal boundaries between the classes[30]. The number of PCs is crucial to the performance of the LDA discrimination model. The discrimination rates by cross-validation were used to optimize the number of PCs. Fig. 3 shows the discrimination rates of LDA model according to different PCs by cross-validation.The optimal LDA models were achieved when the number of PCs was 6, and meanwhile the discrimination rate was up to 100% for both calibration set and prediction set. These results indicated that an ideal separation can be achieved for these six categories of Acacia gum. On the basis of LDA,a cluster analysis was conducted. Samples were grouped in clusters based on their nearness or similarity. Fig. 4 shows the dendrogram of Acacia gum samples. All the Acacia gums in the same group gathered together and were distinguished from other groups. In addition, when all the Acacia gum were clustered into two big groups, Group (E) and Group (F) were defi ned into the same group. This may be due to the reason that Group (E) and (F) had similar protein contents, which were much lower than those of other groups.

    Fig. 3 Rec ognition rates of LDA models

    Fig. 4 Dendrogram of Acacia gum samples

    2.5 Prediction of the total protein content in Acacia gum by Bi-PLS

    Fig. 5 Spectral interval selected by Bi-PLS (a) and actual versus predicted protein contents (b) in calibration set and prediction set

    In this study, the Bi-PLS approach was applied for the quantification of the total protein contents in Acacia gums.Bi-PLS aimed to select the most important subintervals in the whole data matrix. The spectra data set was split into some subintervals, and then PLS models were calculated when each subinterval left out. When the whole spectrum region was split into 20 subintervals, the optimal Bi-PLS model for the total protein content was obtained with the combination of four subintervals, resulting in the lowest RMSECV of 0.155%.As shown in Fig. 5a, the optimal subintervals are [1 4 7 19],which correspond to 650–817, 1 152–1 319, 1 652–1 819 and 3 666–3 833 cm–1, respectively. Fig. 5b presents the performance of the Bi-PLS model on the calibration and prediction set. For the prediction set, RPwas 0.937 3 and RMSEP was 0.173%,demonstrating that the Bi-PLS model can be used to predict the total protein content of Acacia gums.

    3 Conclusion

    FTIR spectroscopy technique combined with chemometrics was successfully established and employed to distinguish the geographical origins and predict the total protein contents of Acacia gums. The results showed that the optimal LDA model was achieved in determining the geographic origins with 100% of discrimination rate for both the calibration and prediction set when the number of PCs was 6. The Bi-PLS model showed a good performance in predicting the total protein content (RP= 0.937 3 and RMSEP = 0.173%) by using the optimal combination of 4 spectral subintervals among 20 subintervals. FTIR spectroscopy coupled with chemometrics can be considered as a valid approach for determination of the geographical origin and protein content of Acacia gums.

    [1] DA UQAN E, ABDULLAH A. Utiliz ation of gum Arabic for industries and human health[J]. American Journal of Applied Sciences, 2013,10(10)∶ 1270-1279. DOI∶10.3844/ajassp.2013.1270.1279.

    [2] IS LAM A M, PHILLIPS G O, SLJIVO A, et al. A review of recent developments on the regulatory, structural and functional aspects of gum arabic[J]. Food Hydrocolloids, 1997, 11(4)∶ 493-505.DOI∶10.1016/S0268-005X(97)80048-3.

    [3] EL MANAN M, AL-ASSAF S, PHILLIPS G O, et al. Studies on Acacia exudate gums∶ Part Ⅵ. Interfacial rheology of Acacia senegal and Acacia seyal[J]. Food Hydrocolloids, 2008, 22(4)∶ 682-689.DOI∶10.1016/j.foodhyd.2007.02.008.

    [4] LO PEZ-TORREZ L, NIGEN M, WILLIAMS P, et al. Acacia senegal vs. Acacia seyal gums-Part 1∶ composition and structure of hyperbranched plant exudates[J]. Food Hydrocolloids, 2015, 51∶41-53. DOI∶10.1016/j.foodhyd.2015.04.019.

    [5] DA OUB R M A, ELMUBARAK A H, MISRAN M, et al.Characterization and functional properties of some natural Acacia gums[J]. Journal of the Saudi Society of Agricultural Sciences, 2016.DOI∶10.1016/j.jssas.2016.05.002.

    [6] AL ASSAF S, PHILLIPS G, WILLIAMS P. Studies on Acacia exudate gums∶ part Ⅱ. Molecular weight comparison of the Vulgares and Gummiferae series of Acacia gums[J]. Food Hydrocolloids, 2005,19(4)∶ 661-667. DOI∶10.1016/j.foodhyd.2004.09.003.

    [7] NIE S P, WANG C, CUI S W, et al. The core carbohydrate structure of Acacia seyal var. seyal (gum Arabic)[J]. Food Hydrocolloids, 2013,32(2)∶ 221-227. DOI∶10.1016/j.foodhyd.2012.12.027.

    [8] SI NELLI N, SPINARDI A, EGIDIO V D, et al. Evaluation of quality and nutraceutical content of blueberries (Vaccinium corymbosum L.)by near and mid-infrared spectroscopy[J]. Postharvest Biology and Technology, 2008, 50(1)∶ 31-36. DOI∶10.1016/j.postharvbio.2008.03.013.

    [9] LI B, WANG H, ZHAO Q, et al. Rapid detection of authenticity and adulteration of walnut oil by FTIR and fluorescence spectroscopy∶a comparative study[J]. Food Chemistry, 2015, 181∶ 25-30.DOI∶10.1016/j.foodchem.2015.02.079.

    [10] W ANG X, SHENG D, ZHU Z, et al. Identification of Cortex Eucommiae from different producing areas by FTIR microspectroscopy[J].Spectrochimica Acta Part A Molecular & Biomolecular Spectroscopy,2015, 141∶ 94-98. DOI∶10.1016/j.lwt.2013.01.027.

    [11] A LAMPRESE C, CASALE M, SINELLI N, et al. Detection of minced beef adulteration with turkey meat by UV-vis, NIR and MIR spectroscopy[J]. LWT-Food Science and Technology, 2013, 53(1)∶225-232. DOI∶10.1016/j.lwt.2013.01.027.

    [12] P RADO B M, KIM S, ?ZEN B F, et al. Differentiation of carbohydrate gums and mixtures using Fourier transform infrared spectroscopy and chemometrics[J]. Journal of Agricultural and Food Chemistry, 2005, 53(8)∶ 2823-2829. DOI∶10.1021/jf0485537.

    [13] KO NG J, YU S. Fourier transform infrared spectroscopic analysis of protein secondary structures[J]. Acta Biochimica et Biophysica Sinica,2007, 39(8)∶ 549-559. DOI∶10.1111/j.1745-7270.2007.00320.x.

    [14] BALTACIOGLU H, BAYINDIRLI A, SEVERCAN F. Secondary structure and conformational change of mushroom polyphenol oxidase during thermosonication treatment by using FTIR spectroscopy[J]. Food Chemistry, 2017, 214∶ 507-514. DOI∶10.1016/j.foodchem.2016.07.021.

    [15] GA SHUA I B, WILLIAMS P A, BALDWIN T C. Molecular characteristics, association and interfacial properties of gum Arabic harvested from both Acacia senegal and Acacia seyal[J]. Food Hydrocolloids, 2016, 61∶ 514-522. DOI∶10.1016/j.foodhyd.2016.06.005.

    [16] OL AWALE A B H, OKEGBILE J, MOHAMMED A, et al. Effect of starch and gum arabic binders in the combustion characteristics of briquette prepared from sawdust[J]. International Journal of Scientifi c &Engineering Research, 2014, 5(3)∶ 1005-1009.

    [17] RE NARD D, LAVENANT-GOURGEON L, RALET M C, et al. Acacia senegal∶ continuum of molecular species differing by their protein to sugar ratio, molecular weight, and charges[J].Biomacromolecules, 2006, 7(9)∶ 2637-2649. DOI∶10.1021/bm060145j.

    [18] TAN ASKOVI? I, GOLOBOCANIN D, MILJEVI? N. Multivariate statistical analysis of hydrochemical and radiological data of Serbian spa waters[J]. Journal of Geochemical Exploration, 2012, 112(1)∶ 226-234.DOI∶10.1016/j.gexplo.2011.08.014.

    [19] TEYE E, HUANG X, DAI H, et al. Rapid differentiation of Ghana cocoa beans by FT-NIR spectroscopy coupled with multivariate classifi cation[J].Spectrochimica Acta Part A∶ Molecular and Biomolecular Spectroscopy,2013, 114(10)∶ 183-189. DOI∶10.1016/j.saa.2013.05.063.

    [20] JIA S Q, YANG L G, AN D, et al. Feasibility of analyzing frostdamaged and non-viable maize kernels based on near infrared spectroscopy and chemometrics[J]. Journal of Cereal Science, 2016,69∶ 145-150. DOI∶10.1016/j.jcs.2016.02.018.

    [21] MARQU ES A S, CASTRO J N, COSTA F J, et al. Near-infrared spectroscopy and variable selection techniques to discriminate Pseudomonas aeruginosa strains in clinical samples[J]. Microchemical Journal, 2016, 124∶ 306-310. DOI∶10.1016/j.microc.2015.09.006.

    [22] WOLD S, SJOSTROM M, ERIKSSON L. PLS-regression∶ a basic tool of chemometrics[J]. Chemometrics and Intelligent Laboratory Systems, 2001, 58(2)∶ 109-130. DOI∶10.1016/S0169-7439(01)00155-1.

    [23] OLESZ KO A, HARTWICH J, WOJTOWICZ A, et al. Comparison of FTIR-ATR and Raman spectroscopy in determination of VLDL triglycerides in blood serum with PLS regression[J]. Spectrochimica Acta Part A Molecular & Biomolecular Spectroscopy, 2017, 183∶239-246. DOI∶10.1016/j.saa.2017.04.020.

    [24] ZOU X B, ZHAO J W, LI Y X. Selection of the effi cient wavelength regions in FT-NIR spectroscopy for determination of SSC of ‘Fuji’apple based on BiPLS and FiPLS models[J]. Vibrational Spectroscopy,2007, 44(2)∶ 220-227. DOI∶10.1016/j.vibspec.2006.11.005.

    [25] WU D, SUN D W, HE Y. Application of long-wave near infrared hyperspectral imaging for measurement of color distribution in salmon fillet[J]. Innovative Food Science & Emerging Technologies, 2012,16(39)∶ 361-372. DOI∶10.1016/j.ifset.2012.08.003.

    [26] ALASS AF S, ANDRESBRULL M, CIRRE J, et al. Structural changes following industrial processing of Acacia gums[M]//KENNEDY J F, PHILLIPS G O, WILLIAMS P A. Gum Arabic.Special publication∶ Royal Society of Chemistry, 2011∶ 153-168.DOI∶10.1039/9781849733106-00153.

    [27] BHUSHETTE P R, ANNAPURE U S. Comparative study of Acacia nilotica exudate gum and Acacia gum[J]. International Journal of Biological Macromolecules, 2017, 102∶ 266-271. DOI∶10.1016/j.ijbiomac.2017.03.178.

    [28] ADERIBIGBE B A, VARAPRASAD K, SADIKU E R, et al.Kinetic release studies of nitrogen-containing bisphosphonate from gum acacia crosslinked hydrogels[J]. International Journal of Biological Macromolecules, 2015, 73∶ 115-123. DOI∶10.1016/j.ijbiomac.2014.10.064.

    [29] DONG Y J, SRENSEN K M, HE S, et al. Gum Arabic authentication and mixture quantification by near infrared spectroscopy[J]. Food Control, 2017, 78∶ 144-149. DOI∶10.1016/j.foodcont.2017.02.002.

    [30] CHEN Q S, ZHAO J W, LIN H. Study on discrimination of Roast green tea (Camellia sinensis L.) according to geographical origin by FT-NIR spectroscopy and supervised pattern recognition[J].Spectrochimica Acta Part A∶ Molecular and Biomolecular Spectroscopy, 2009, 72(4)∶ 845-850. DOI∶10.1016/j.saa.2008.12.002.

    應(yīng)用紅外光譜結(jié)合化學(xué)計量學(xué)方法檢測阿拉伯膠產(chǎn)地和蛋白質(zhì)含量

    鄒小波1,Alaa Kamal Mohmmed KHAIR KHOGLY1,石吉勇1,Mel HOLMES2
    (1.江蘇大學(xué)食品與生物工程學(xué)院,江蘇 鎮(zhèn)江 212013;2.利茲大學(xué)食品科學(xué)與營養(yǎng)學(xué)院,英國 利茲 LS1 3AB)

    研究利用傅里葉紅外光譜結(jié)合化學(xué)計量學(xué)方法來實現(xiàn)對蘇丹阿拉伯膠的產(chǎn)地和蛋白質(zhì)含量的快速無損檢測的可行性。采集自6 個不同的產(chǎn)地,每個產(chǎn)地12 個,總計72 個阿拉伯膠樣本,作為研究對象,運用線性判別分析(linear discriminant analysis,LDA)和反向區(qū)間偏最小二乘(backward interval partial least squares,Bi-PLS)法分別實現(xiàn)對蘇丹阿拉伯膠的產(chǎn)地區(qū)分和蛋白質(zhì)含量檢測。結(jié)果表明,當(dāng)主成分?jǐn)?shù)為6時,LDA對樣本的訓(xùn)練集(48 個樣本)和預(yù)測集(24 個樣本)的識別率都為100%。Bi-PLS法回歸聯(lián)合20 個光譜子區(qū)間中的4 個子區(qū)間得到最佳的蛋白質(zhì)預(yù)測模型,其預(yù)測集相關(guān)系數(shù)為0.937 3,均方根誤差為0.173%。因此,利用傅里葉紅外光譜結(jié)合化學(xué)計量學(xué)方法可實現(xiàn)對蘇丹阿拉伯膠的產(chǎn)地以及蛋白質(zhì)的含量的快速無損檢測。

    阿拉伯膠;傅里葉紅外光譜;產(chǎn)地;蛋白質(zhì)含量;線性判別分析;反向區(qū)間偏最小二乘法

    TS201.1

    A

    1002-6630(2017)20-0229-06

    nces:

    2017-05-08

    “十二五”國家科技支撐計劃項目(2015BAD17B04);“十三五”國家重點研發(fā)計劃重點專項(2016YFD0401104);

    鄒小波(1974—),男,教授,博士,研究方向為食品與農(nóng)產(chǎn)品無損檢測。E-mail:zou_xiaobo@ujs.edu.cn

    國家自然科學(xué)基金面上項目(31671844);國家自然科學(xué)基金青年科學(xué)基金項目(31601543);

    中國博士后科學(xué)基金項目(2014T70483;2016M590422);江蘇省自然科學(xué)基金項目(BK20160506;BE2016306);

    江蘇省國際科技合作項目(BZ2016013);蘇州市科技發(fā)展計劃項目(SNG201503);

    江蘇高校優(yōu)勢學(xué)科建設(shè)工程資助項目(PAPD)

    ZOU Xiaobo, KHAIR KHOGLY A K M, SHI Jiyong, et al. Determination of geographical origin and protein content of Acacia gums using infrared spectroscopy and chemometrics[J]. 食品科學(xué), 2017, 38(20)∶ 229-234. DOI∶10.7506/spkx1002-6630-201720033. http∶//www.spkx.net.cn

    ZOU Xiaobo, KHAIR KHOGLY A K M, SHI Jiyong, et al. Determination of geographical origin and protein content of Acacia gums using infrared spectroscopy and chemometrics[J]. Food Science, 2017, 38(20)∶ 229-234. DOI∶10.7506/spkx1002-6630-201720033. http∶//www.spkx.net.cn

    DOI∶10.7506/spkx1002-6630-201720033

    猜你喜歡
    阿拉伯膠計量學(xué)基金項目
    阿拉伯膠,食品添加劑里的“魔術(shù)師”
    生物化學(xué)計量學(xué)原理在離散生物動力系統(tǒng)的應(yīng)用
    云南化工(2021年5期)2021-12-21 07:41:34
    針刺治療失眠癥的文獻(xiàn)計量學(xué)分析
    常見基金項目的英文名稱(二)
    常見基金項目的英文名稱(一)
    維吾爾藥阿拉伯膠和乳香藥材摻偽的鑒別研究
    基于科學(xué)計量學(xué)的公安院??蒲信c評價
    2004-2013年中醫(yī)藥治療性早熟的文獻(xiàn)計量學(xué)分析
    阿拉伯膠的性質(zhì)和研究進(jìn)展
    河南科技(2014年12期)2014-02-27 14:10:29
    阿拉伯膠和羧甲基纖維素鈉對蕎麥面團(tuán)發(fā)酵流變學(xué)及烘焙特性的影響
    最近在线观看免费完整版| 一a级毛片在线观看| 男女边吃奶边做爰视频| 欧美色视频一区免费| 晚上一个人看的免费电影| 人人妻人人看人人澡| 三级国产精品欧美在线观看| 亚洲综合色惰| 最后的刺客免费高清国语| 午夜精品国产一区二区电影 | 中文在线观看免费www的网站| 亚洲欧美日韩东京热| 日产精品乱码卡一卡2卡三| 哪里可以看免费的av片| 亚洲国产色片| 日日摸夜夜添夜夜添小说| 精品一区二区三区视频在线观看免费| 国产精品久久久久久精品电影| 岛国在线免费视频观看| 中文字幕免费在线视频6| 熟妇人妻久久中文字幕3abv| av天堂在线播放| 国产成人福利小说| 国产片特级美女逼逼视频| 国产高清三级在线| 99久久久亚洲精品蜜臀av| 日韩三级伦理在线观看| 最近在线观看免费完整版| 精品久久久久久久久久免费视频| 国产一级毛片七仙女欲春2| 亚洲综合色惰| 禁无遮挡网站| 免费人成在线观看视频色| 成年女人看的毛片在线观看| 精品午夜福利在线看| 国产精华一区二区三区| 国产精品电影一区二区三区| 大型黄色视频在线免费观看| 黄色视频,在线免费观看| 国产真实乱freesex| 99热这里只有是精品50| 国产女主播在线喷水免费视频网站 | 麻豆国产av国片精品| 十八禁国产超污无遮挡网站| av在线蜜桃| 九九久久精品国产亚洲av麻豆| av视频在线观看入口| 99久国产av精品| 两性午夜刺激爽爽歪歪视频在线观看| 男人舔女人下体高潮全视频| 欧美成人一区二区免费高清观看| 天堂影院成人在线观看| 女同久久另类99精品国产91| 十八禁网站免费在线| 国产亚洲精品久久久com| 老女人水多毛片| 欧美区成人在线视频| 国产高清激情床上av| 亚洲国产精品成人综合色| 99久国产av精品| 又黄又爽又免费观看的视频| 高清日韩中文字幕在线| 麻豆成人午夜福利视频| 在线播放无遮挡| 波多野结衣高清无吗| 国产精品爽爽va在线观看网站| 午夜激情福利司机影院| 内射极品少妇av片p| 国产午夜精品久久久久久一区二区三区 | 精品人妻熟女av久视频| 国产伦在线观看视频一区| 国产男靠女视频免费网站| 最近视频中文字幕2019在线8| 精品无人区乱码1区二区| 在线国产一区二区在线| 97人妻精品一区二区三区麻豆| 欧美日韩乱码在线| 久久精品国产鲁丝片午夜精品| 亚洲精品一卡2卡三卡4卡5卡| 国产精品久久久久久精品电影| 日韩高清综合在线| 国产欧美日韩精品一区二区| 亚洲成人精品中文字幕电影| av视频在线观看入口| 内地一区二区视频在线| 身体一侧抽搐| 免费高清视频大片| 狂野欧美白嫩少妇大欣赏| 亚洲精品乱码久久久v下载方式| 少妇高潮的动态图| 久久中文看片网| 毛片女人毛片| 91在线观看av| 搡女人真爽免费视频火全软件 | 特级一级黄色大片| 香蕉av资源在线| 久久国内精品自在自线图片| 午夜免费男女啪啪视频观看 | 国产精品伦人一区二区| 免费av不卡在线播放| 99久久中文字幕三级久久日本| 一本一本综合久久| 欧美激情国产日韩精品一区| av免费在线看不卡| 国产黄色视频一区二区在线观看 | 人妻丰满熟妇av一区二区三区| 老熟妇仑乱视频hdxx| a级毛片免费高清观看在线播放| 久久99热6这里只有精品| 国产伦在线观看视频一区| 3wmmmm亚洲av在线观看| 亚洲四区av| 成人欧美大片| 又粗又爽又猛毛片免费看| 欧美性猛交╳xxx乱大交人| 一级av片app| 亚洲av五月六月丁香网| АⅤ资源中文在线天堂| 非洲黑人性xxxx精品又粗又长| 亚洲国产日韩欧美精品在线观看| 日韩中字成人| 亚洲婷婷狠狠爱综合网| 午夜视频国产福利| 深夜a级毛片| 色播亚洲综合网| 精品久久久久久久久久久久久| 亚洲中文字幕日韩| 激情 狠狠 欧美| 国产精品久久久久久久久免| 国产极品精品免费视频能看的| 少妇的逼好多水| 中文字幕精品亚洲无线码一区| 尾随美女入室| 久久99热这里只有精品18| 午夜精品在线福利| 18+在线观看网站| 亚洲精品成人久久久久久| 欧美成人a在线观看| 国产又黄又爽又无遮挡在线| 欧美又色又爽又黄视频| 两个人视频免费观看高清| 色尼玛亚洲综合影院| 亚洲欧美精品自产自拍| 观看美女的网站| 亚洲国产精品久久男人天堂| 不卡一级毛片| 午夜亚洲福利在线播放| 国产乱人偷精品视频| 我的老师免费观看完整版| 乱人视频在线观看| 亚洲人成网站高清观看| 国产一区二区三区av在线 | 天堂影院成人在线观看| 2021天堂中文幕一二区在线观| 91久久精品国产一区二区成人| av在线老鸭窝| 无遮挡黄片免费观看| 亚洲五月天丁香| 亚洲在线自拍视频| 少妇丰满av| 一本久久中文字幕| 99久久精品一区二区三区| 国产 一区精品| 成人无遮挡网站| 青春草视频在线免费观看| 国产精品久久久久久亚洲av鲁大| 一边摸一边抽搐一进一小说| 国产成人一区二区在线| 亚洲av成人av| 校园春色视频在线观看| 欧美一区二区精品小视频在线| 18禁在线播放成人免费| 尤物成人国产欧美一区二区三区| av天堂在线播放| 毛片一级片免费看久久久久| 日韩欧美在线乱码| 精品一区二区免费观看| 99热这里只有是精品在线观看| 国语自产精品视频在线第100页| 亚洲熟妇中文字幕五十中出| 亚洲av电影不卡..在线观看| 男人舔奶头视频| 女人十人毛片免费观看3o分钟| 国产成人a区在线观看| 久久久午夜欧美精品| 国产精品久久久久久av不卡| 日韩欧美在线乱码| 亚洲av免费在线观看| 少妇熟女欧美另类| 亚洲一区二区三区色噜噜| 成人漫画全彩无遮挡| 国产乱人偷精品视频| 国产乱人视频| 国产亚洲精品久久久com| 色5月婷婷丁香| 丰满的人妻完整版| 久99久视频精品免费| 日韩,欧美,国产一区二区三区 | 搡女人真爽免费视频火全软件 | 欧美日韩一区二区视频在线观看视频在线 | 99热只有精品国产| 蜜桃亚洲精品一区二区三区| 又粗又爽又猛毛片免费看| 国产成人a∨麻豆精品| 成人欧美大片| 精品乱码久久久久久99久播| 校园春色视频在线观看| 一区二区三区高清视频在线| 一级毛片我不卡| 久久久久久久久中文| 久久婷婷人人爽人人干人人爱| 51国产日韩欧美| 三级经典国产精品| 综合色丁香网| 波多野结衣巨乳人妻| 九九久久精品国产亚洲av麻豆| 亚洲人与动物交配视频| 免费观看在线日韩| 91久久精品国产一区二区成人| 可以在线观看毛片的网站| 少妇被粗大猛烈的视频| 人妻少妇偷人精品九色| 在线观看免费视频日本深夜| 国产高清有码在线观看视频| 久久亚洲国产成人精品v| 久久精品国产清高在天天线| 亚洲av不卡在线观看| 两个人的视频大全免费| 午夜老司机福利剧场| 91在线观看av| 久久久久久国产a免费观看| 精品久久久久久成人av| 亚洲欧美日韩无卡精品| 非洲黑人性xxxx精品又粗又长| 小说图片视频综合网站| 欧美色视频一区免费| 国产精品国产高清国产av| 色哟哟·www| 高清毛片免费看| 嫩草影视91久久| 亚洲五月天丁香| 国产精品不卡视频一区二区| 97超视频在线观看视频| 成人二区视频| 亚洲精品一区av在线观看| 男人的好看免费观看在线视频| 国产精品亚洲美女久久久| 黑人高潮一二区| 成人亚洲精品av一区二区| 天天躁夜夜躁狠狠久久av| 美女内射精品一级片tv| 日韩精品中文字幕看吧| 久久综合国产亚洲精品| 国产伦精品一区二区三区四那| 精品一区二区免费观看| 中文字幕免费在线视频6| 久久久午夜欧美精品| 给我免费播放毛片高清在线观看| 三级经典国产精品| 一区二区三区四区激情视频 | 老熟妇仑乱视频hdxx| 国产精品久久视频播放| 成年版毛片免费区| а√天堂www在线а√下载| 免费人成在线观看视频色| 九九久久精品国产亚洲av麻豆| 色视频www国产| 国产午夜福利久久久久久| 亚洲av熟女| 在线播放无遮挡| АⅤ资源中文在线天堂| 精品久久久久久久久久免费视频| 香蕉av资源在线| 99久国产av精品| 亚洲精品日韩在线中文字幕 | 青春草视频在线免费观看| 久久99热这里只有精品18| 久久久国产成人精品二区| 1000部很黄的大片| 午夜精品在线福利| 亚洲第一区二区三区不卡| 亚洲av熟女| 尾随美女入室| 嫩草影院精品99| 精品久久久噜噜| 精品国产三级普通话版| 午夜精品国产一区二区电影 | 日日撸夜夜添| 亚洲美女搞黄在线观看 | 中文字幕人妻熟人妻熟丝袜美| 国产 一区精品| 中文字幕精品亚洲无线码一区| 国产极品精品免费视频能看的| 天天躁日日操中文字幕| 又黄又爽又免费观看的视频| 狠狠狠狠99中文字幕| 97超碰精品成人国产| 免费高清视频大片| 黄色欧美视频在线观看| 国产精品国产三级国产av玫瑰| 老司机福利观看| 欧美日本亚洲视频在线播放| 日本撒尿小便嘘嘘汇集6| av在线蜜桃| 高清毛片免费观看视频网站| 波野结衣二区三区在线| av卡一久久| 熟妇人妻久久中文字幕3abv| 欧美日韩乱码在线| 搞女人的毛片| 免费观看人在逋| 人人妻人人看人人澡| 麻豆国产97在线/欧美| 国产 一区 欧美 日韩| 少妇丰满av| 又爽又黄无遮挡网站| 久久久午夜欧美精品| 国产精品一区www在线观看| 国产精品久久久久久久电影| 日韩欧美精品免费久久| 亚洲成人av在线免费| 欧美在线一区亚洲| 色综合色国产| 日日摸夜夜添夜夜爱| 欧美绝顶高潮抽搐喷水| 久久综合国产亚洲精品| 伦精品一区二区三区| 嫩草影院精品99| 波多野结衣巨乳人妻| АⅤ资源中文在线天堂| 欧美潮喷喷水| 国国产精品蜜臀av免费| 精品国内亚洲2022精品成人| 久久人人爽人人爽人人片va| 欧美最黄视频在线播放免费| 国产一区二区激情短视频| 日韩大尺度精品在线看网址| 国产av不卡久久| 真实男女啪啪啪动态图| 黑人高潮一二区| 国产 一区 欧美 日韩| 色综合亚洲欧美另类图片| 欧美另类亚洲清纯唯美| 国产伦精品一区二区三区视频9| 中文字幕免费在线视频6| 亚洲精品成人久久久久久| 亚洲精品456在线播放app| 日产精品乱码卡一卡2卡三| 少妇人妻精品综合一区二区 | 欧美bdsm另类| 亚洲av电影不卡..在线观看| 草草在线视频免费看| 九九爱精品视频在线观看| 少妇丰满av| 人妻久久中文字幕网| 搡老岳熟女国产| 亚洲精品456在线播放app| 无遮挡黄片免费观看| 美女高潮的动态| 国产精品福利在线免费观看| 欧美中文日本在线观看视频| 精品人妻视频免费看| 国产视频内射| av国产免费在线观看| 晚上一个人看的免费电影| 精华霜和精华液先用哪个| 国产精品伦人一区二区| 久久精品久久久久久噜噜老黄 | 在线看三级毛片| 97碰自拍视频| 久久精品国产亚洲网站| 日本与韩国留学比较| 麻豆av噜噜一区二区三区| 午夜福利18| 久久精品国产99精品国产亚洲性色| 最好的美女福利视频网| 久久草成人影院| 婷婷色综合大香蕉| 色尼玛亚洲综合影院| 色综合亚洲欧美另类图片| 99久久成人亚洲精品观看| 久久久成人免费电影| 国产久久久一区二区三区| avwww免费| 中文字幕免费在线视频6| 成人国产麻豆网| 日本三级黄在线观看| 热99在线观看视频| 老师上课跳d突然被开到最大视频| 亚洲av.av天堂| 国产色爽女视频免费观看| 亚洲av美国av| 免费人成在线观看视频色| 女生性感内裤真人,穿戴方法视频| 国产精品野战在线观看| 欧美性感艳星| 又黄又爽又免费观看的视频| 日韩欧美精品免费久久| 1000部很黄的大片| 免费在线观看成人毛片| 欧美日韩在线观看h| 最新在线观看一区二区三区| 男女下面进入的视频免费午夜| 午夜精品国产一区二区电影 | 国产精品日韩av在线免费观看| 亚洲人成网站在线观看播放| 欧美一区二区亚洲| 亚洲国产精品合色在线| 一级毛片我不卡| 亚洲中文字幕一区二区三区有码在线看| 国产欧美日韩一区二区精品| 日韩一本色道免费dvd| 麻豆精品久久久久久蜜桃| 深夜a级毛片| 午夜精品国产一区二区电影 | 天美传媒精品一区二区| 亚洲经典国产精华液单| 日韩欧美精品免费久久| 国产高潮美女av| 日韩 亚洲 欧美在线| 日韩精品青青久久久久久| 日本黄色片子视频| 热99在线观看视频| 久久久精品大字幕| 欧美性猛交黑人性爽| 亚洲精华国产精华液的使用体验 | 如何舔出高潮| 久久精品国产清高在天天线| 可以在线观看毛片的网站| 噜噜噜噜噜久久久久久91| 精品少妇黑人巨大在线播放 | 校园人妻丝袜中文字幕| 网址你懂的国产日韩在线| 97热精品久久久久久| 你懂的网址亚洲精品在线观看 | 男人的好看免费观看在线视频| 熟女电影av网| 国产麻豆成人av免费视频| 自拍偷自拍亚洲精品老妇| 成熟少妇高潮喷水视频| 亚洲av美国av| 午夜日韩欧美国产| 亚洲七黄色美女视频| 在线观看66精品国产| 99久久精品国产国产毛片| ponron亚洲| 成年免费大片在线观看| 国产高清激情床上av| 国产精品一区二区免费欧美| 国国产精品蜜臀av免费| 亚洲国产色片| 大型黄色视频在线免费观看| 精品午夜福利视频在线观看一区| 国产精品免费一区二区三区在线| 天堂av国产一区二区熟女人妻| 日韩欧美免费精品| 一级黄色大片毛片| 国产欧美日韩一区二区精品| 色在线成人网| av黄色大香蕉| 男女边吃奶边做爰视频| 日韩,欧美,国产一区二区三区 | 成人午夜高清在线视频| 欧美三级亚洲精品| aaaaa片日本免费| 精华霜和精华液先用哪个| av黄色大香蕉| 久久久久久大精品| 看免费成人av毛片| 18禁裸乳无遮挡免费网站照片| 色哟哟哟哟哟哟| 99热这里只有是精品在线观看| avwww免费| 午夜精品一区二区三区免费看| 亚洲最大成人av| 欧美激情久久久久久爽电影| 亚洲最大成人手机在线| 欧美日本亚洲视频在线播放| 久久久久精品国产欧美久久久| 国产成人福利小说| 成人高潮视频无遮挡免费网站| 97热精品久久久久久| 成人毛片a级毛片在线播放| 成人鲁丝片一二三区免费| 精品一区二区免费观看| 亚洲av中文字字幕乱码综合| 欧美在线一区亚洲| 免费在线观看影片大全网站| 干丝袜人妻中文字幕| 99久久精品热视频| 亚洲av中文字字幕乱码综合| 亚洲aⅴ乱码一区二区在线播放| 精品熟女少妇av免费看| 最新在线观看一区二区三区| 99久久中文字幕三级久久日本| 成人精品一区二区免费| 日韩av在线大香蕉| 精品一区二区三区人妻视频| 国产单亲对白刺激| 久久中文看片网| 国产亚洲精品综合一区在线观看| 国产精品美女特级片免费视频播放器| 国产男靠女视频免费网站| 国产精品永久免费网站| 国产精品日韩av在线免费观看| 少妇熟女aⅴ在线视频| 18禁裸乳无遮挡免费网站照片| 此物有八面人人有两片| 欧美国产日韩亚洲一区| 97在线视频观看| 欧美不卡视频在线免费观看| 乱系列少妇在线播放| 成人三级黄色视频| 真实男女啪啪啪动态图| 免费看美女性在线毛片视频| 成人特级黄色片久久久久久久| 99热全是精品| 精品一区二区免费观看| 免费av观看视频| 一区二区三区免费毛片| 久久久午夜欧美精品| 日本在线视频免费播放| 欧美性猛交黑人性爽| 一个人看的www免费观看视频| 熟女人妻精品中文字幕| 在线观看一区二区三区| 欧美最黄视频在线播放免费| 69av精品久久久久久| 成人毛片a级毛片在线播放| 老司机福利观看| АⅤ资源中文在线天堂| 国产精品国产高清国产av| 在线免费十八禁| 日本色播在线视频| 大又大粗又爽又黄少妇毛片口| 少妇裸体淫交视频免费看高清| 久久精品91蜜桃| 欧美中文日本在线观看视频| 国产精品人妻久久久影院| 两性午夜刺激爽爽歪歪视频在线观看| 一本一本综合久久| 国产一区二区在线观看日韩| 99久久精品一区二区三区| 少妇猛男粗大的猛烈进出视频 | 中国国产av一级| 熟女电影av网| 成人二区视频| 国产国拍精品亚洲av在线观看| 国内精品一区二区在线观看| 麻豆成人午夜福利视频| 一区福利在线观看| 亚洲中文日韩欧美视频| 一级毛片我不卡| 午夜福利18| 欧美一级a爱片免费观看看| 日日干狠狠操夜夜爽| 我的老师免费观看完整版| 成熟少妇高潮喷水视频| 97在线视频观看| 成人亚洲欧美一区二区av| 久久99热6这里只有精品| 黑人高潮一二区| 黄色配什么色好看| 人妻少妇偷人精品九色| 99久久精品热视频| 欧美日本视频| 男插女下体视频免费在线播放| 色在线成人网| 联通29元200g的流量卡| 毛片一级片免费看久久久久| 人人妻,人人澡人人爽秒播| 丝袜喷水一区| 日本a在线网址| 国内少妇人妻偷人精品xxx网站| 国产精品永久免费网站| 国产精品女同一区二区软件| 麻豆久久精品国产亚洲av| 蜜桃久久精品国产亚洲av| 嫩草影院精品99| 国产极品精品免费视频能看的| 成熟少妇高潮喷水视频| a级毛片a级免费在线| 精品不卡国产一区二区三区| 成人二区视频| 久久久久久国产a免费观看| 精品不卡国产一区二区三区| 男人狂女人下面高潮的视频| 床上黄色一级片| 亚洲经典国产精华液单| 色视频www国产| 变态另类丝袜制服| 网址你懂的国产日韩在线| 亚洲成a人片在线一区二区| 国产高清视频在线观看网站| 白带黄色成豆腐渣| 亚洲成人久久爱视频| 色吧在线观看| 又黄又爽又免费观看的视频| 99热全是精品| 国产精品一区二区三区四区久久| 国产白丝娇喘喷水9色精品| 国产精品一二三区在线看| 国产国拍精品亚洲av在线观看| 亚洲专区国产一区二区| 欧美3d第一页| 有码 亚洲区| 插逼视频在线观看| 成年女人毛片免费观看观看9| 久久久久久久午夜电影| av.在线天堂| 国产精品久久电影中文字幕| 欧美一区二区亚洲| 午夜福利高清视频| 丝袜喷水一区| 99久久无色码亚洲精品果冻|