Name: construction of models for nondestructive prediction of ingredient contents in blueberries by near-infrared spectroscopy based on hplc measurements
Uploaded: 2016-06-28T14:00:00
Description: Watch this Scientific Journal Video about Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements at JoVE.co

This work was partially supported by the project "A Scheme to Revitalize Agriculture and Fisheries in Disaster Area through Deploying Highly Advanced Technology" of Ministry of Agriculture, Forestry and Fisheries, Japan.

1. Collection of Samples
<ol>
	<li>Decide which cultivars will be included in the target of the calibration model.</li>
	<li>Collect sufficient number and various types of sample blueberries of the target cultivars.
	<ol>
		<li>Collect preferably 100 blueberries for the construction of the calibration model, and at least 10 for the validation of the constructed model. In order to construct robust models, collect samples of various types, i.e. with various colors, sizes, and at various ripening conditions.</li>...

<ol>
	<li>Ozaki, Y., McClure, W. F., Christy, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Near-infrared Spectroscopy in Food Science and Technology. , (2007).</li><li>Sun, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Infrared Spectroscopy for Food Quality Analysis and Control. , (2009).</li><li>Bai, W., Yoshimura, N., Takayanagi, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+analysis+of+ingredients+of+blueberry+fruits+by+near+infrared+spectroscopy.">Quantitative analysis of ingredients of blueberry fruits by near infrared spectroscopy.</a> J. Near Infrared Spectrosc. 22, 357-365 (2014).</li><li>Hasegawa, T., Tasumi, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Chemometrics in infrared spectroscopic analysis. In: Introduction to Experimental Infrared Spectroscopy. , 97-113 (2015).</li><li>Varmuza, K., Filzmoser, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Introduction to Multivariate Statistical Analysis in Chemometrics. , (2009).</li><li>Kubelka, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=New+contributions+to+the+optics+of+intensely+light-scattering+materials.+Part+I.">New contributions to the optics of intensely light-scattering materials. Part I.</a> J. Opt. Soc. Am. 38, 448-457 (1948).</li><li>Juang, R. H., Storey, D. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+determination+of+the+extent+of+neutralization+of+carboxylic+acid+functionality+in+carbopol+974P+NF+by+diffuse+reflectance+fourier+transform+infrared+spectrometry+using+Kubelka-Munk+function.">Quantitative determination of the extent of neutralization of carboxylic acid functionality in carbopol 974P NF by diffuse reflectance fourier transform infrared spectrometry using Kubelka-Munk function.</a> Pharm Res. 15, 1714-1720 (1998).</li><li>Ogiwara, I., Ohtsuka, Y., Yoneda, Y., Sakurai, K., Hakoda, N., Shimura, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Extraction+method+by+water+followed+by+microwave+heating+for+analyzing+sugars+in+strawberry+fruits.">Extraction method by water followed by microwave heating for analyzing sugars in strawberry fruits.</a> J. Jpn. Soc. Hort. Sci. 68, 949-953 (1999).</li><li>Che, J., Suzuki, S., Ishikawa, S., Koike, H., Ogiwara, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fruit+ripening+and+quality+profile+of+64+cultivars+in+three+species+of+blueberries+grown+in+Tokyo.">Fruit ripening and quality profile of 64 cultivars in three species of blueberries grown in Tokyo.</a> Hort. Res. (Japan). 8, 257-265 (2009).</li><li>Pomerantsev, A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Chemometrics in Excel. , (2014).</li><li>Jiang, H. J., Berry, R. J., Siesler, H. W., Ozaki, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wavelength+Interval+Selection+in+Multicomponent+spectral+analysis+by+moving+window+partial+least-squares+regression+with+applications+to+mid-infrared+and+near-infrared+spectroscopic+data.">Wavelength Interval Selection in Multicomponent spectral analysis by moving window partial least-squares regression with applications to mid-infrared and near-infrared spectroscopic data.</a> Anal. Chem. 74, 3555-3565 (2002).</li><li>Edney, M. J., Morgan, J. E., Williams, P. C., Campbell, L. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+feed+barley+by+near+infrared+reflectance+spectroscopy.">Analysis of feed barley by near infrared reflectance spectroscopy.</a> J. Near-Infrared Spectrosc. 2, 33-41 (1994).</li><li>Mathison, G. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prediction+of+composition+and+ruminal+degradability+characteristics+of+barley+straw+by+near+infrared+reflectance+spectroscopy.">Prediction of composition and ruminal degradability characteristics of barley straw by near infrared reflectance spectroscopy.</a> Can. J. Anim. Sci. 79, 519-523 (1999).</li><li>Chiara, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+anthocyanins+in+commercial+fruit+juices+by+using+nano-liquid+chromatography+electrospray-mass+spectrometry+and+high+performance+liquid+chromatography+with+UV-vis+detector.">Analysis of anthocyanins in commercial fruit juices by using nano-liquid chromatography electrospray-mass spectrometry and high performance liquid chromatography with UV-vis detector.</a> J. Separation Sci. 34, 150-159 (2011).</li><li>Li, Q., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antioxidant+anthocyanins+screening+through+spectrum-effect+relationships+and+DPPH-HPLC-DAD+analysis+on+nine+cultivars+of+introduced+rabbiteye+blueberry+in+China.">Antioxidant anthocyanins screening through spectrum-effect relationships and DPPH-HPLC-DAD analysis on nine cultivars of introduced rabbiteye blueberry in China.</a> Food Chemistry. 132, 759-765 (2013).</li><li>Sinelli, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+quality+and+nutraceutical+content+of+blueberries+(Vaccinium+corymbosum+L.)+by+near+and+mid-infrared+spectroscopy.">Evaluation of quality and nutraceutical content of blueberries (Vaccinium corymbosum L.) by near and mid-infrared spectroscopy.</a> Postharvest Biol. Technol. 50, 31-36 (2008).</li><li>Giusti, M. M., Wrolsted, R. E., Wrolstad, R. E., Schwartz, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anthocyanins:+characterization+and+measurement+with+UV-visible+spectroscopy.">Anthocyanins: characterization and measurement with UV-visible spectroscopy.</a> Current Protocols in Food Analytical Chemistry. , 1-13 (2001).</li></ol>

Some additional comments on the protocol are described here. Firstly, in step 1.1, it is mentioned to decide the cultivars included in the target. Although it is possible to construct models covering blueberries from many cultivars or without specifying cultivars, the prediction accuracies with the models are sometimes much lower than those with the models for a single cultivar and for limited cultivars. It should also be noted that the calibration models should be constructed for blueberries from each production site to...

Near-infrared (NIR) spectroscopy is widely applied as a nondestructive technique to analyze contents of fruits and vegetables of various kinds.1,2 Nondestructive analyses by NIR spectroscopy enable the shipping of only delicious fruits and vegetables with guaranteed qualities. NIR spectroscopy has already been applied to orange, apple, melon, cherry, kiwi fruit, mango, papaya, peach and so on to know their Brix that corresponds to the total sugar content, acidity, TSC (total solids contents), and so on. Recently, we have reported the application of NIR spectroscopy to the quality evaluation of blueberries.3 We measured not only the total sugar content and the total organic acid content corresponding to acidity, but also the total anthocyanin content. Anthocyanin is a bioactive component which is believed to improve human health. It is convenient for consumers if they can buy delicious blueberries with an assurance of their sugar content, acidity, and anthocyanin content.
In NIR absorption spectra of fruits and vegetables, only broad absorption bands are observed. They are mainly the bands due to fiber and moisture. Although many weak bands due to various ingredients of the non-destructed target are observed simultaneously, the observed bands cannot be assigned to specific vibrational modes of specific components of the target in most cases. Therefore, the traditional technique to determine the content of a specific component using the Lambert-Beer&#39;s law is not effective for NIR spectra. Instead, calibration models to predict the contents of the target components from the observed spectra are constructed using chemometrics by examining the correlation between the observed spectra and the ingredient contents corresponding to the spectra.4,5 Here, a protocol to construct and validate the models for prediction of total sugar content, total organic acid content corresponding to acidity, and total anthocyanin content of blueberries from NIR spectra is presented.
Figure 1 shows the general flow chart to construct reliable and robust calibration models. Samples of sufficient number are collected. Some of them are used for the construction of models while the others are used for the validation of the constructed models. For each of collected samples, an NIR spectrum is measured, and then the target components are analyzed quantitatively with traditional destructive chemical analysis methods. Here, high-performance liquid chromatography (HPLC) is used for the chemical analyses of sugars, organic acids, and anthocyanins. Partial least squares (PLS) regression is used for the construction of calibration models where the correlation between the observed spectra and the ingredient contents determined by chemical analyses is examined. In order to construct robust models with the best prediction ability, the pretreatments of observed spectra and the wavelength regions used for the prediction are also examined. Finally, the constructed models are validated to confirm their sufficient prediction ability. In the validation, the contents predicted from the observed spectrum by the constructed model (predicted values) are compared with the contents determined by the chemical analyses (observed values). If the sufficient correlation cannot be found between the predicted and observed values, the calibration model should be re-constructed until the sufficient correlation is obtained. Although it is preferable to use different groups of samples for the construction and validation of a model as shown in this figure (external validation), samples in a same group are used both for the construction and the validation (cross validation) when the number of samples is not large enough.
<img alt="Figure 1" src="/files/ftp_upload/53981/53981fig1.jpg" /> 
Figure 1. Flow chart for the construction and validation of the calibration model. The procedures surrounded by blue and green lines correspond, respectively, to the construction of a calibration model and its validation. <a href="https://www.jove.com/files/ftp_upload/53981/53981fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table border="0" cellpadding="0" cellspacing="0" width="1315">
	<tbody>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">FT-NIR spectrophotometer</td>
			<td style="width:320px;">Bruker Optics GmbH</td>
			<td style="width:355px;">MPA&#160;</td>
			<td style="width:320px;"></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">High-Performance Liquid Chromatography</td>
			<td style="width:320px;">Shimadzu Corporation</td>
			<td>228-45041-91, 228-45000-31, 228-45018-31,</td>
			<td>For sugar analysis</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;"></td>
			<td style="width:320px;"></td>
			<td>223-04500-31, 228-45010-31, 228-45095-31</td>
			<td>Refractive Index Detector</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">High-Performance Liquid Chromatography</td>
			<td style="width:320px;">Shimadzu Corporation</td>
			<td>228-45041-91, 228-45003-31, 228-45000-31,</td>
			<td>For organic acid analysis</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;"></td>
			<td style="width:320px;"></td>
			<td>228-45018-31, 228-45010-31, 223-04500-31</td>
			<td>Ultraviolet-Visible Detector</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">High-Performance Liquid Chromatography</td>
			<td style="width:320px;">Shimadzu Corporation</td>
			<td>228-45041-91, 228-45018-31, 228-45000-31,</td>
			<td style="width:320px;">For anthocyanin analysis</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;"></td>
			<td style="width:320px;"></td>
			<td>228-45012-31, 228-45119-31, 228-45005-31,</td>
			<td style="width:320px;">Photodiode Array Detector</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;"></td>
			<td style="width:320px;"></td>
			<td>228-45009-31</td>
			<td style="width:320px;"></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">pH meter</td>
			<td style="width:320px;">Mettler-Toledo</td>
			<td>30019028</td>
			<td style="width:320px;">S220, Automatic temperature compensation</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Ultra-pure water treatment equipment</td>
			<td style="width:320px;">ORGANO Corporation</td>
			<td style="width:355px;">ORG-ULXXXM1; PRA-0015-0V0</td>
			<td style="width:320px;">PURELAB ultra; PURELITE</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Biomedical Freezers&#160;</td>
			<td style="width:320px;">SANYO</td>
			<td style="width:355px;">2-6780-01</td>
			<td style="width:320px;">MDF-U338</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Ultra-Low Temperature Freezer</td>
			<td style="width:320px;">Panasonic healthcare Co.,Ltd.</td>
			<td style="width:355px;">KM-DU73Y1</td>
			<td style="width:320px;">-80&#176;C</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Vacuum lyophilizer</td>
			<td style="width:320px;">IWAKI GLASS Co.,Ltd</td>
			<td>119770</td>
			<td style="width:320px;">DRC-3L;FRD-82M</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Homoginizer</td>
			<td style="width:320px;">Microtec Co., Ltd.&#160;</td>
			<td>Physcotron</td>
			<td style="width:320px;"></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Ultracentrifuge</td>
			<td style="width:320px;">Hitachi Koki Co.,Ltd</td>
			<td style="width:355px;">S204567</td>
			<td>CF15RXII</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Mini-centrifuge</td>
			<td style="width:320px;">LMS CO.,LTD.</td>
			<td>KN3136572</td>
			<td>MCF-2360</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Centrifuge</td>
			<td style="width:320px;">Kokusan Co.,Ltd</td>
			<td style="width:355px;">2-5534-01</td>
			<td>H-103N</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Filter Paper&#160;</td>
			<td style="width:320px;">Advantec</td>
			<td style="width:355px;">1521070</td>
			<td>5B, Eqivalent to Whatman 40</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Sep-Pak C18 column</td>
			<td style="width:320px;">Waters Corporation Milford</td>
			<td style="width:355px;">WAT020515</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Sep-Pak CM column</td>
			<td style="width:320px;">Waters Corporation Milford</td>
			<td style="width:355px;">WAT020550</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Sep-Pak QMA column</td>
			<td style="width:320px;">Waters Corporation Milford</td>
			<td style="width:355px;">WAT020545</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Centrifugal Filter Unit</td>
			<td style="width:320px;">Merck Millipore Corporation</td>
			<td style="width:355px;">R2SA18503</td>
			<td>PVDF, 0.45 &#956;m</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Microtube</td>
			<td style="width:320px;">As One Corporation</td>
			<td style="width:355px;">1-1600-02</td>
			<td>PP, 2 mL</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Syringe Filter</td>
			<td style="width:320px;">GE Healthcare CO.,LTD.</td>
			<td style="width:355px;">6788-1304</td>
			<td>PP, 0.45 &#956;m</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Sucrose</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">194-00011</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Glucose</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">049-31165</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Fructose</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">123-02762</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Citric acid</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">036-05522</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Malic acid</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">355-17971</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Succinic acid&#160;</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">190-04332</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Quinic acid</td>
			<td style="width:320px;">Alfa Aesar, A Johnson Matthey Company</td>
			<td style="width:355px;">10176328</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;">Phosphoric acid</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">162-20492</td>
			<td>HPLC-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Trifluoroacetic acid</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">208-02746</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Methanol</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">131-01826</td>
			<td>Reagent-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Acetonitrile</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">015-08633</td>
			<td>HPLC-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Grade cyanidin-3-O-glucoside chloride</td>
			<td style="width:320px;">Wako Pure Chemical Industries,Ltd</td>
			<td style="width:355px;">306-37661</td>
			<td>HPLC-grade</td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Software for analyses</td>
			<td style="width:320px;">Bruker Optics GmbH</td>
			<td style="width:355px;">OPUS ver. 6.5</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Softoware for preprocessing</td>
			<td style="width:320px;">Microsoft</td>
			<td style="width:355px;">Excel powered by Visual Basic for Applications</td>
			<td></td>
		</tr>
		<tr height="33">
			<td height="33" style="height:33px;width:320px;">Software for construction of models</td>
			<td style="width:320px;"></td>
			<td style="width:355px;">Freemat 4.0</td>
			<td>http://freemat.sourceforge.net/</td>
		</tr>
	</tbody>
</table>

construction of models for nondestructive prediction of ingredient contents in blueberries by near-infrared spectroscopy based on hplc measurements

Nondestructive prediction of ingredient contents of farm products is useful to ship and sell the products with guaranteed qualities. Here, near-infrared spectroscopy is used to predict nondestructively total sugar, total organic acid, and total anthocyanin content in each blueberry. The technique is expected to enable the selection of only delicious blueberries from all harvested ones. The near-infrared absorption spectra of blueberries are measured with the diffuse reflectance mode at the positions not on the calyx. The ingredient contents of a blueberry determined by high-performance liquid chromatography are used to construct models to predict the ingredient contents from observed spectra. Partial least squares regression is used for the construction of the models. It is necessary to properly select the pretreatments for the observed spectra and the wavelength regions of the spectra used for analyses. Validations are necessary for the constructed models to confirm that the ingredient contents are predicted with practical accuracies. Here we present a protocol to construct and validate the models for nondestructive prediction of ingredient contents in blueberries by near-infrared spectroscopy.

Figure 2 shows as an example a set of NIR absorption spectra of blueberries where spectra of 70 blueberries are shown simultaneously. Since the bands definitely assignable to sugars, organic acids, or anthocyanins are not observed in the NIR spectra, traditional Lambert-Beer&#39;s law is not applicable to quantify the ingredient contents. Therefore, the construction of models for the prediction of ingredient contents is necessary.
<p class="jove_content" fo:keep-toget...

Watch this Scientific Journal Video about Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements at JoVE.co

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

We present here a protocol to construct and validate models for nondestructive prediction of total sugar, total organic acid, and total anthocyanin content in individual blueberries by near-infrared spectroscopy.

Nondestructive prediction of ingredient contents of farm products is useful to ship and sell the products with guaranteed qualities. Here, near-infrared ...

Research

JoVE Journal

Chemistry

Profiling the Triacylglyceride Contents in Bat Integumentary Lipids by Preparative Thin Layer Chromatography and MALDI-TOF Mass Spectrometry

The mammalian integument includes sebaceous glands that secrete an oily material onto the skin surface. Sebum production is part of the innate immune ...

Dissolution Dynamic Nuclear Polarization Instrumentation for Real-time Enzymatic Reaction Rate Measurements by NMR

The main limitation of NMR-based investigations is low sensitivity. This prompts for long acquisition times, thus preventing real-time NMR measurements of ...

HPLC-based Assay to Monitor Extracellular Nucleotide/Nucleoside Metabolism in Human Chronic Lymphocytic Leukemia Cells

This method describes a sensitive, specific, reliable and reproducible reverse phase high-performance liquid chromatography (RP-HPLC) assay developed and ...

Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

The precise details of the interaction of intense X-ray pulses with matter are a topic of intense interest to researchers attempting to interpret the ...

Detection and Quantification of Plasmodium falciparum in Aqueous Red Blood Cells by Attenuated Total Reflection Infrared Spectroscopy and Multivariate Data Analysis

Detection and Quantification of Plasmodium falciparum in Aqueous Red Blood Cells by Attenuated Total Reflection Infrared Spectroscopy and Multivariate Data Analysis

We demonstrate a method of quantification and detection of parasites in aqueous red blood cells (RBCs) by using a simple benchtop Attenuated Total ...

Pretargeted Radioimmunotherapy Based on the Inverse Electron Demand Diels-Alder Reaction

While radioimmunotherapy (RIT) is a promising approach for the treatment of cancer, the long pharmacokinetic half-life of radiolabeled antibodies can ...

Performing Spectroscopy on Plasmonic Nanoparticles with Transmission-Based Nomarski-Type Differential Interference Contrast Microscopy

Differential interference contrast (DIC) microscopy is a powerful imaging tool that is most commonly employed for imaging microscale objects using ...

Covalent Attachment of Single Molecules for AFM-based Force Spectroscopy

Atomic force microscopy (AFM)-based single molecule force spectroscopy is an ideal tool for investigating the interactions between a single polymer and ...

Crystallization of Proteins on Chip by Microdialysis for In Situ X-ray Diffraction Studies

Crystallization of Proteins on Chip by Microdialysis for In Situ X-ray Diffraction Studies

This protocol describes the manufacturing of reproducible and inexpensive microfluidic devices covering the whole pipeline for crystallizing proteins ...

Construction of Cyclic Cell-Penetrating Peptides for Enhanced Penetration of Biological Barriers

Cancer has been a grand challenge in global health. However, the complex tumor microenvironment generally limits the access of therapeutics to deeper ...