|Year : 2017 | Volume
| Issue : 49 | Page : 193-198
Quality-by-Design: Multivariate model for multicomponent quantification in refining process of honey
Xiaoying Li, Zhisheng Wu, Xin Feng, Shanshan Liu, Xiaojie Yu, Qun Ma, Yanjiang Qiao
Department of Science and Technology Development of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, P.R. China
|Date of Submission||09-Sep-2014|
|Date of Acceptance||18-Mar-2015|
|Date of Web Publication||06-Jan-2017|
Dr. Qun Ma
No. 6, South of Wangjing Middle Ring Road, Chaoyang, Beijing
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Objective: A method for rapid analysis of the refining process of honey was developed based on near-infrared (NIR) spectroscopy. Methods: Partial least square calibration models were built for the four components after the selection of the optimal spectral pretreatment method and latent factors. Results: The models covered the samples of different temperatures and time pointstherefore the models were robust and universal. Conclusions: These results highlighted that the NIR technology could extract the information of critical process and provide essential process knowledge of the honey refining process.
Abbreviation used: NIR: Near-infrared; 5-HMF: 5-hydroxymethylfurfural; RMSEP: Root mean square error of prediction; R: correlation coefficients; PRESS: prediction residual error-sum squares; TCM: Traditional Chinese medicine; HPLC: High-performance liquid chromatography; HPLC-DAD: HPLC-diode array detector; PLS: Partial least square; MSC: multiplicative scatter correction; RMSECV: Root mean square error of cross validation; RPD: Residual predictive deviation; 1D: 1st order derivative; SG: Savitzky-Golay smooth; 2D: 2nd order derivative.
Keywords: Honey, near-infrared, partial least, squares, rapid analysis, refining process
|How to cite this article:|
Li X, Wu Z, Feng X, Liu S, Yu X, Ma Q, Qiao Y. Quality-by-Design: Multivariate model for multicomponent quantification in refining process of honey. Phcog Mag 2017;13:193-8
|How to cite this URL:|
Li X, Wu Z, Feng X, Liu S, Yu X, Ma Q, Qiao Y. Quality-by-Design: Multivariate model for multicomponent quantification in refining process of honey. Phcog Mag [serial online] 2017 [cited 2022 Aug 16];13:193-8. Available from: http://www.phcog.com/text.asp?2017/13/49/193/196310
Xiaoying Li, Zhisheng Wu
These authors contributed equally to this work
- A method for rapid analysis of the refining process of honey was developed based on near-infrared (NIR) spectroscopy.
| Introduction|| |
Honey has been used as food as well as traditional Chinese medicine (TCM). It has the effect of strengthening the middle warmermoistening the lung to suppress coughand moistening dryness of intestine and detoxification. Besideshoney has been used as auxiliary material during the process of Chinese medicinal herbs and the preparation of Chinese patent drug.
Honey has been used as adhesive and corrective after being processed in the honey pills. Honey pill is widely approved in China. There are lots of famous and effective prescriptions appeared in the form of honey pillsuch as Angong Niuhuang Pill., Though the refined honey plays an important role in the preparation of honey pillonce it is not well refinedhoney pills will be easily wrinkleddriedand cracked.
Refined honeywhich has been used in Chinese herbal medicine processingwas called honey-fried method. Raw drugs decocted by refining honey are widely used in clinical settings. Thousands of honey-fried crude drugs can be found in Chinese pharmacopeia and local standards.,,, The quality of the refined honey influences the quality of herbal medicine.
In the refining processthe quality of honey is affected by heating timetemperaturepressureevaporation intensitygas flowetc.Moisture has long been regarded as the test item of refined honeyand its content can indicate the rank of the refined honey. A previous study has explored the above-mentioned factors according to the index of moisture content., Howevermore components should be explored. 5-hydroxymethylfurfural (5-HMF) is bad for human health. Reports indicate that 5-HMF can cause the paralysis of nonstriated muscle and organ injury. Newly collected honey does not include 5-HMF. 5-HMF is produced during the storage and processing of honey and it is the degeneration product of monosaccharide such as glucose. Thereforeit must be strictly controlled.,, Fructose and glucose are the main contents of the honey. They are easily destroyed during the refining processand it is necessary to monitor both of them.
Near-infrared (NIR) spectroscopy is a newly emerging process analytical technologywhich is fastenvironmental friendlyfree of pretreatmentand able to detect different components at the same time. NIR spectroscopy is widely used in the analysis of TCM's manufacturing processsuch as the extraction processthe drying processand the blend process.,,,, Currentlythe application of the technique in honey is focused on the content determinationdistinction of different producing areas and floral resourcesand adulteration. There is no literature reporting the application of NIR in the process of refining honey.
Since the quality of the refining honey has profound effectsthe control of the refining process of the refining honey can not only guarantee the quality of the refining honeybut also make a meaningful exploration of the nature of the process. In this studywe studied the role of the temperature and time played in the refining process of honey according to the contents of moisture5-HMFfructoseand glucose. NIR technique was applied in the refining process of honey.
| Materials and Methods|| |
Honey was purchased from Tong Ren Tang Technologies Co.Ltd. (Beijing, China). 5-hydromethylfurfural (5-HMF) (lot number: 110777-201005) fructose (lot number: 100231-200904)and glucose (reference standards: 110833-200904) were supplied by the National Institute for Food and Drug control (Beijing, China). Methanol and acetonitrile of high-performance liquid chromatography (HPLC) grade were purchased from Fisher Scientific Co.Ltd. (New JerseyUSA). Distilled water was purchased from Watsons Co.Ltd. (Hong KongChina).
Amounts of honey in the two-necked round-bottomed flask were refined for 10 h in the oil-bathing of constant temperature of 100°C, 110°C, and 120°C, respectively. Samples were collected every 15 min from 0 min to 600 minand 123 kinds of samples were obtained.
The NIR spectra were collected by the transflective mode using the Antaris II NIR spectrophotometer (Thermo Electron Co.USA). Each spectrum was scanned 32 times with a resolution of 8/cm. The spectra range was from 4000/cm to 10,000/cm. Spectra of each sample were collected 3 times and the average result of three spectra was used for future analysis. Data analysis was performed with the TQ Analyst V8.0 software (Thermo Electron Co.USA).
Determination of water content
The moisture in the honey was measured by Abbe refractometer. The detail of the method can be found in the industry standard of Import and Export Inspection and Quarantine of China (SN/T0852-2000). The temperature of the water flowed through the refractometer was 40°C.
Determination of 5-hydroxymethylfurfural content
A 2.5 g sample of refining honey was dissolved by 10% methanol (v/v)and then transferred into a 25 mL volumetric flask10% methanol was added to the scale. After the sample solution was filtrated through a 0.45 μm filterthe filtrate was transferred into an HPLC vial before HPLC-diode array detector (HPLC-DAD) analysis.
A Shimadzu LC-20AT system consisting of two pumpsDAD detectora thermostat maintained at 30°Cand an auto sampler was adopted. The sample filtrate was separated and analyzed by an Agilent Eclipse XDB-C18 column (150 mm × 4.6 mm5 μm). The mobile phase consisted of 94% solvent A (water) and 6% solvent B (methanol). The flow rate was 0.8 mL/min. The absorbance was measured at a wavelength of 283 nm. The chromatographic peaks were identified by comparing their retention time against standards.
Determination of fructose and glucose contents
A 0.2 g sample of refining honey was dissolved by 10% methanol (v/v)and then transferred into a 100 mL volumetric flask10% methanol was added to the scale. After the sample solution was filtrated through a 0.45 μm filterthe filtrate was transferred into an HPLC vial before HPLC-DAD analysis.
An Agilent 1100 system equipped with Alltech 3300 ELSD detector was used in the determination of fructose and glucose. The samples were separated and analyzed by an APS-2 Hypersil NH2-column (250 × 4.6 mm5 μm)which was used as a reversed-phase column. The mobile phase was 25% solvent A (water) and 75% solvent B (acetonitrile)and its flow rate was 0.8 mL/min. The gas flow rate was 3.0 mL/min. The temperature of the drift tube was set at 80°C. The gain of the instrument was 1. The injection volume was 5 μL.
Software and basic theory
TQ Analyst V8.0 software related to the equipment was applied to process data. Partial least square (PLS) analysis can consider both variable matrix Y (data or property collected by traditional method) and matrix X (the spectra) at the same timethus PLS can solve problemswhich cannot be solved by common multiple regression. ThereforePLS was chosen to establish the regression model. Stratified sampling method was used to divide the calibration setand validation set for the data of 5-HMF showed skewed distributions. In other wordsone of every three samples is divided into the validation set. Finally82 samples were chosen as calibration set and 41 samples were chosen as validation set.
To evaluate the result of the models established by PLS5 indicators were introduced. They are root mean square error of prediction (RMSEP)root mean square error of cross validationprediction residual error-sum squares (PRESS)correlation coefficient (R)and standard deviation/SEP.
| Results and Discussion|| |
Result of moisture content by reference method
Moisture loss is an important characteristic of the refining process of honey. [Figure 1] shows how the content of moisture changed during the refining process. As we can see from the figureas the refining time goes onmoisture content declines apparently. The loss rate of the moisture exaggerates with the increasing temperature. That isthe loss rate was higher when the temperature was 120°C than 110°C and 100°C. The linear regression equations were calculatedand the slopes were - 0.15, -0.17 and -0.22, respectively.
|Figure 1: The change in the content of water during the refining process|
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The refining honey was divided into three grades according to traditional Chinese pharmaceutical theory for different purposes. In Grade Athe water content varies between 17% and 20%and after 10590and 120 min heating at 100110and 120°Cthe refining honey began to be Grade A. In Grade Bthe water content varies between 14% and 16%and after 435360and 195 min heating at 100110and 120°C the refining honey began to be Grade B. In Grade Cthe water content was < 10% and after 525 min heating at 120°C the refining honey began to be Grade C. After 10 h heatingthe final moisture content was 11.88%11.26% and 8.99% respectively.
Quantitative analysis of 5-hydroxymethylfurfural by high-performance liquid chromatography method
HPLC method was explored to determine 5-HMF. [Figure 2] shows the chromatograms of 5-HMF reference standard and the honey sample. 5-HMF in honey sample has the same retention time with the reference standard. The methodology study was investigated. The calibration curve exhibited good linearity (r = 0.9999)within the quantitative range from 3.76 to 188.00 μg. The methodology parameters were investigated before the realistic sample analyses such as the precisionstabilitythe average recoveryand repeatability test. It comes to the conclusion that HPLC method can satisfy all the demands of quantitative analysisand can provide accurate data for NIR calibration.
|Figure 2: The chromatograms of 5-hydroxymethylfurfural reference standard and honey sample|
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[Figure 3] reveals that the refining temperature and time had a great effect on the content of 5-HMF. 5-HMF content increases along with the time extension and temperature rise. The growth rate of 5-HMF also increases along with the temperature risein other wordsthe growth rate of 5-HMF was higher in 120°C than in 100°C and 110°C. After 12075and 60 min heating at 100110and 120°Cthe content of 5-HMF was higher than 0.04 mg/gwhich was the highest limit of European standard. The suitable curves were calculatedand the slopes were 0.0010.003and 0.011when the temperature was 100110and 120°C. The final content of 5-HMF were 0.74081.9039and 5.5721 mg/grespectively
|Figure 3: The content change of 5-hydroxymethylfurfural during the refining process|
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Quantitative analysis of fructose and glucose by high-performance liquid chromatography method
[Figure 4] shows the chromatograms of fructose reference standardglucose reference standardand the honey sample. Fructose and glucose in honey sample have the same retention time with the reference standards. The methodology studies were also investigated. The calibration curve of fructose and glucose exhibited good linearity (r = 0.9993 and r = 0.9996respectively)within the quantitative ranges from 1.3720 to 13.7200 μg and 1.2048 to 12.0480 μgrespectively. What is moreother tests such as the precisionstabilitythe average recovery ratioand repeatability test perform well. Henceit comes to the conclusion that HPLC method can satisfy all the demands of quantitative analysisand can provide accurate data for NIR calibration.
|Figure 4: The chromatograms of reference standards and honey sample. Peak 1 represents fructose and Peak 2 represents glucose|
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[Figure 5] shows the influence of the refining temperature and time on the content of fructose and glucose. The refining temperature and refining time do affect the content of fructose and glucose. Howeverthe change rule or trend is not clear. The content of fructose varied from 315.8933 to 374.6548349.8052 to 447.8220and 264.1140 to 418.3368 mg/g in 100110and 120°Crespectivelywhereas the content of glucose varied from 312.1638 to 350.9069305.4088 to 474.0710and 311.2195 to 405.1648 mg/g. Additional research should be conducted to thoroughly evaluate the change rules of fructose and glucose.
|Figure 5: The changes in the content of fructose and glucose during the refining process|
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The original NIR spectra may be affected by the physical properties of the samples and other environmental factors. Thereforethe pretreatment of the spectra is of great importance. Reducing the systematic noiseremoving the drift of the baselineand eliminating the effect of the lighting scattering will make it easier to get effective information. Preprocessing techniques such as 1st order derivative (1d)2nd order derivativeSavitzky-Golay smooth (SG92)multiplicative scatter correction (MSC)and their combinations are used to seek the optimal models. [Table 1] shows the result of different pretreatments. From [Table 1] it is obvious that for moisture model5-HMF modeland fructose model1d combined with SG smooth and MSC (1d-sg-MSC) method is superior to the other methods; for glucose model1d is the best method.
The selection of principal component number
Confirming the principal component number is another effective way to eliminate the noise and make the best use of the spectral data. If fewer principal component numbers are considered in the modelthe predictive ability of the model is not tenableand this is called under fitting. Howeverif too many principle component numbers are considered; for examplethe principal component number which represents the noise may be considered in the modelthe predictive ability of the model is not tenableeitherand it is called over fitting. The optimal latent factors were chosen based on the lowest PRESS. [Figure 6] shows how the numbers of latent factors affect the values of PRESS when determining all the components with different spectral pretreatments. The optimal numbers of latent factors were 71410and 8for moisture5-HMFfructoseand glucoserespectively.
|Figure 6: Effects of numbers of partial least squares latent factors on prediction residual error-sum squares values for moisture5-hydroxymethylfurfural, fructoseand glucose|
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Result of the near-infrared method
After the spectral preprocessing method and the number of latent factors were selectedthe PLS models were built to the determination of moisture5-HMFfructoseglucoseand the decrease of sugarsaccording to all the evaluation parameters. The RMSEP values in the established models for moisture 5-HMF fructoseand glucose were 0.155% (g/g)132 μg/ml18.4 mg/gand 20.1 mg/grespectively. The R values were 0.99950.99810.9367and 0.9049respectively. [Figure 7] shows the correlation of predictive value of NIR and actual value of reference method for moisture5-HMFfructoseand glucose. The calibration sets of the correction models covered samples that were got from different refining temperature and refining time. Thusthe models allowed the determination of the content of moisture5-HMFfructoseand glucose to be applied at a wide range rapidly and conveniently
|Figure 7: The correlation of predictive value of near-infrared and actual value of reference method for moisture5-hydroxymethylfurfural, fructoseand glucose|
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| Conclusions|| |
Honey refining is a typical case for process analysis. The technologies such as NIR spectroscopy used in process analysis can be applied in the refining process of honey. Our study explored the change of content of moisture 5-HMF fructoseand glucose in the refining process of honeyand investigated the influence of the refining time and temperature. MoreoverPLS models were built to analyze the refining process rapidly. The results exhibited that NIR spectroscopy is a good solution for the quality control of the refining process of honey. NIR spectroscopy avoids the time-consumingcostlyand destructive chemical analysisand guarantees the quality of the refining honey at the same time. Once there was homogeneous and stable refining honeythe quality and effect of the drugs or crude drugs were ensured. Thusit will bring tremendous economic and social benefits. This research is meaningful in illuminating the essence of honey refining project.
This research was carried out in the laboratory and had limitationsbut more work should be done in the manufacturing process to make sure that NIR technology can be used in monitoring the refining process of honey.
Financial support and sponsorship
This study was supported by the National Natural Science Foundation of China (No. 81303218)Doctoral Fund of Ministry of Education of China (20130013120006)Beijing University of Chinese Medicine Special Subject of Outstanding Young Teachersand Innovation Team Foundation.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Cano CB, Felsner ML, Matos JR, Bruns RE, Whatanabe HM, Almeida-Muradian LB, Comparison of methods for determining moisture content of citrus and eucalyptus Brazilian honeys by refractometry. J Food Compost Anal 2001;14:101-9.
Cavia MM, Fernández-Muiño MA, Gömez-Alonso E, Montes-Pérez MJ, Huidobro JF, Sancho MT, Evolution of fructose and glucose in honey over one year: Influence of induced granulation. Food Chem 2002;78:157-61.
Camara VC, Laux D, Moisture content in honey determination with a shear ultrasonic reflectometer. J Food Eng 2010;96:93-6.
Chernetsova ES, Morlock GE, Assessing the capabilities of direct analysis in real time mass spectrometry for 5-hydroxymethylfurfural quantitation in honey. Int J Mass Spectrom 2012;314:22-32.
Commission CP, Pharmacopeia of People's Republic of China 2010;Beijing, China Medical Science Press
Laux D, Camara VC, Rosenkrantz E, α-Relaxation in honey study versus moisture content: High frequency ultrasonic investigation around room temperature. J Food Eng 2011;103:165-9.
Lu YF, Wu Q, Liang SX, Miao JW, Shi JS, Liu J, Evaluation of hepatotoxicity potential of cinnabar-containing an-gong-niu-huang wan, a patent traditional Chinese medicine. Regul Toxicol Pharmacol 2011;60:206-11.
Lu YF, Yan JW, Wu Q, Shi JZ, Liu J, Shi JS, Realgar- and cinnabar-containing an-gong-niu-huang wan (AGNH) is much less acutely toxic than sodium arsenite and mercuric chloride. Chem Biol Interact 2011;189:134-40.
Nozal MJ, Bernal JL, Toribio L, Jiménez JJ, Martn T, High-performance liquid chromatographic determination of methyl anthranilate, hydroxymethylfurfural and related compounds in honey. J Chromatogr A 2001;917:95-103.
Rizelio VM, Gonzaga LV, Campelo Borges GS, Micke GA, Fett R, Costa AC, Development of a fast MECK method for determination of 5-HMF in honey samples. Food Chem 2012;133:1640-5.
Wu Z, Ma Q, Lin Z, Peng Y, Ai L, Shi X, et al
. Anovel model selection strategy using total error concept. Talanta 2013;107:248-54.
Wu Z, Sui C, Xu B, Ai L, Ma Q, Shi X, et al
. Multivariate detection limits of on-line NIR model for extraction process of chlorogenic acid from Lonicera japonica
. J Pharm Biomed Anal 2013;77:16-20.
Wu ZS, Du M, Sui CL, Shi XY, Qiao YJ, Development and validation of NIR model using low-concentration calibration range: Rapid analysis of Lonicera japonica
solution in ethanol precipitation process. Anal Methods 2012;4:1084-8.
Wu ZS, Du M, Xu B, Lin ZZ, Shi XY, Qiao YJ, Absorption characteristics and quantitative contribution of overtones and combination of NIR: Method development and validation. J Mol Struct 2012;1019:97-102.
Wu Z, Xu B, Du M, Sui C, Shi X, Qiao Y, Validation of a NIR quantification method for the determination of chlorogenic acid in Lonicera japonica
solution in ethanol precipitation process. J Pharm Biomed Anal 2012;62:1-6.
Xu B, Wu Z, Lin Z, Sui C, Shi X, Qiao Y, NIR analysis for batch process of ethanol precipitation coupled with a new calibration model updating strategy. Anal Chim Acta 2012;720:22-8.
Yanniotis S, Skaltsi S, Karaburnioti S, Effect of moisture content on the viscosity of honey at different temperatures. J Food Eng 2006;72:372-7.
Ye J, Zhang X, Dai W, Yan S, Huang H, Liang X, et al
. Chemical fingerprinting of Liuwei Dihuang Pill and simultaneous determination of its major bioactive constituents by HPLC coupled with multiple detections of DAD, ELSD and ESI-MS. J Pharm Biomed Anal 2009;49:638-45.
Zhang M, Wang MY, Liu YQ, Shi HM, Li XB, Quality analysis of raw and honey-processed licorice of Glycyrrhiza uralensis
Fisch and G. glabra
L. by simultaneous determination of five bioactive components using RPHPLC/DAD method. J Food Drug Anal 2011;9:131-8.
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