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. Prélèvement des échantillons <ol><li> Décidez quels cultivars seront inclus dans la cible du modèle d&#39;étalonnage. </li><li> Collecter nombre suffisant et divers types de bleuets échantillons des cultivars cibles. <ol><li> Recueillir de préférence 100 bleuets pour la construction du modèle d&#39;étalonnage, et au moins 10 pour la validation du modèle construit. Afin de construire des modèles robustes, prélever des échantillons de divers types, soit avec différentes couleurs, tailles, et ...

<ol>
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Quelques commentaires supplémentaires sur le protocole sont décrits ici. Tout d&#39;abord, à l&#39;étape 1.1, il est mentionné pour décider les cultivars inclus dans la cible. Bien qu&#39;il soit possible de construire des modèles couvrant les bleuets de nombreux cultivars ou sans préciser les cultivars, les exactitudes de prédiction avec les modèles sont parfois bien inférieurs à ceux des modèles pour un seul cultivar et cultivars limités. Il convient également de noter que les modèles d&#39;étalonnage...

Proche infrarouge (NIR) est largement appliquée comme une technique non destructive pour analyser le contenu de fruits et légumes de toutes sortes. 1,2 Nondestructive analyse par spectroscopie NIR permettre à l&#39;expédition de seulement délicieux fruits et légumes avec des qualités garanties. La spectroscopie NIR a déjà été appliquée à l&#39;orange, pomme, melon, cerise, kiwi, mangue, papaye, pêche et ainsi de suite pour connaître leur Brix qui correspond à la teneur totale en sucre, acidité, TSC (solides totaux contenus), et ainsi de suite . Récemment, nous avons signalé l&#39;application de la spectroscopie NIR à l&#39;évaluation de la qualité des bleuets. 3 Nous mesurée non seulement la teneur totale en sucre et la teneur totale en acide organique correspondant à l&#39; acidité, mais aussi la teneur en anthocyanes totale. L&#39;anthocyanine est un composant bioactif qui est censé améliorer la santé humaine. Il est commode pour les consommateurs s&#39;ils peuvent acheter de délicieux bleuets avec une assurance de leur teneur en sucre, acidité et teneur en anthocyanes. Dans les spectres d&#39;absorption NIR de fruits et légumes, seules des bandes d&#39;absorption larges sont observés. Ils sont principalement les bandes dues à la fibre et de l&#39;humidité. Bien que de nombreuses bandes faibles en raison de divers ingrédients de la cible non-destructed sont observées en même temps, les bandes observées ne peuvent pas être attribués à des modes vibratoires spécifiques des composants spécifiques de la cible dans la plupart des cas. Par conséquent, la technique traditionnelle pour déterminer la teneur d&#39;un composant spécifique en utilisant la loi de Beer-Lambert est pas efficace pour les spectres NIR. Au lieu de cela, des modèles d&#39;étalonnage pour prédire la teneur des composants à partir des spectres observés cibles sont construits à l&#39; aide de la chimiométrie , en examinant la corrélation entre les spectres observés et le contenu de l&#39; ingrédient correspondant aux spectres 4,5. Ici, un protocole de construire et de valider les modèles pour la prédiction de la teneur totale en sucre, teneur totale en acide organique correspondant à Acidity, et la teneur en anthocyanes totale de bleuets de spectres NIR est présenté. La figure 1 montre l&#39;organigramme général pour construire des modèles d&#39;étalonnage fiables et robustes. Des échantillons de nombre suffisant sont collectés. Certains d&#39;entre eux sont utilisés pour la construction de modèles, tandis que les autres sont utilisés pour la validation des modèles construits. Pour chacun des échantillons prélevés, un spectre proche infrarouge est mesurée, et ensuite les composants cibles sont analysés quantitativement par des méthodes d&#39;analyse chimique destructive traditionnelles. Ici, la chromatographie liquide à haute performance (HPLC) est utilisée pour les analyses chimiques des sucres, des acides organiques et des anthocyanines. Moindres carrés partiels (PLS) regression est utilisé pour la construction de modèles d&#39;étalonnage, où la corrélation entre les spectres observés et les teneurs en ingrédients déterminée par des analyses chimiques est examinée. Afin de construire des modèles robustes avec la meilleure capacité de prédiction, les prétraitements de obserLes spectres vés et les régions de longueurs d&#39;onde utilisées pour la prédiction sont également examinés. Enfin, les modèles construits sont validés pour confirmer leur capacité de prédiction suffisante. La validation, le contenu prédit à partir du spectre observé par le modèle de construction (valeurs prédites) sont comparées aux teneurs déterminées par les analyses chimiques (valeurs observées). Si la corrélation suffisante ne peut pas être trouvé entre les valeurs prédites et observées, le modèle d&#39;étalonnage doit être à nouveau réalisée jusqu&#39;à ce que la corrélation suffisante soit obtenue. Bien qu&#39;il soit préférable d&#39;utiliser différents groupes d&#39;échantillons pour la construction et la validation d&#39;un modèle, comme indiqué sur cette figure (de validation externe), les échantillons d&#39;un même groupe sont utilisés aussi bien pour la construction et la validation (validation croisée) lorsque le nombre d&#39; échantillons ne sont pas assez grand. <img alt="Figure 1" src="/files/ftp_upload/53981/53981fig1.jpg" /> Figure 1. Diagramme pour la construction et la validation du modèle d&#39;étalonnage. Les procédures entourées par des lignes bleues et vertes correspondent, respectivement, à la construction d&#39;un modèle d&#39;étalonnage et sa validation. <a href="https://www.jove.com/files/ftp_upload/53981/53981fig1large.jpg" target="_blank">S&#39;il vous plaît cliquer ici pour voir une version plus grande de cette 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.

La figure 2 montre à titre d&#39;exemple un ensemble de spectres d&#39;absorption NIR de bleuets où les spectres de 70 bleuets sont présentés simultanément. Depuis les bandes définitivement assignables à des sucres, des acides organiques, ou les anthocyanes ne sont pas observées dans les spectres NIR, la loi traditionnelle de Beer-Lambert est sans objet pour quantifier le contenu des ingrédients. Par conséquent, la construction de modèles pour la prédiction d...

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.

Construction de modèles de prédiction non destructive des matières Ingrédient en Blueberries par spectroscopie proche infrarouge basée sur des mesures de CLHP

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

The overall goal of this procedure is to construct and validate models for nondestructive prediction of total sugar, total organic acid, and total anti-cyanine content in individual blueberries by near-infrared spectroscopy. This method will answer key problems in the field of evaluation of farm products, such as fruits and vegetables. To me, an advantage of this technique is that plenty of our products can be checked nondestructively by spectroscopy.And the models constructed through the procedure shown here. Near-infrared spectroscopy is a powerful tool for the nondestructive evaluation of farm products. Prediction models are constructed by examining the correlation between the spectrum and the contents determined by chemical analysis of each target.Demonstrating the procedure will be Yusuke Kimura, a graduated student from my laboratory and Jingai Che, from university and one of the authors of this protocol. Collect a sufficient number and various types of sample blueberries from the target cultivars. Collect preferably 100 blueberries for the construction of the calibration model.And at least 10 for the validation of the constructed model. To construct robust models, collect samples of various types, such as with various colors, sizes, and at various ripening conditions. Weigh each blueberry.The weights measured are used later for the calculation of content percent of ingredients of each blueberry. Next put a blueberry sample in the center of the window of the near-infrared spectrophotomoter for diffuse reflectance measurements. By using the sample single channel command, measure the spectra of each blueberry.Preferably at several points in the fruit. Keep the blueberries in a freezer, below minus 30 degrees celsius if they are not to be analyzed just after the spectrum measurements. To begin the pre-treatment, cut a blueberry into several pieces so it can be easily homogenized.Cutting the blueberry without defrosting when it is frozen. Put the pieces into a 50 milliliter beaker. Add approximately 10 milliliters of ultra pure water to the beaker.Heat the cut blueberry in ultra pure water in a microwave oven for 20 seconds to deactivate the enzymes that might decompose sugars during the analyses. Add approximately 10 milliliters of ultra pure water to the beaker. Homogenize the mixture for five minutes at 12, 000 RPM with a homogenizer equipped with a standard shaft and generator.Centrifuge the homogenized mixture for 10 minutes at 3, 000 RPM. Next collect the filtrate by vacuum filtration of the centrifuged sample using a five B paper filter. After repeating the homogenization steps twice, measure the pH of the filtrate and adjust it to seven with dilute hydrochloric acid and dilute aqueous solutions of sodium hydroxide.Dilute the filtrate to 50 milliliters with ultra pure water. Divide the sample into two. One for the analysis of sugars and the other for the analysis of organic acids.Pass the first sample solution through the columns connected in series to exclude pigments, cations, and anions. Throw away the first one milliliter of the sample solution from the columns. Then use the sample solution from the columns for the analysis of sugars by high performance liquid chromotography or HPLC.Centrifuge the solution at 6, 600 RPM for 10 minutes in a microtube equipped with a 0.445 micron filter with a mini-centrifuge before the analysis by HPLC. Arrange the HPLC system using a gel permeation column in the column oven at 40 degrees celsius. Use de-gassed ultra pure water with a flow rate of 0.1 milliliters per minute as the eluent.Also use a refractive index detector. Measure the HPLC spectrograms of standard solutions by injecting a 20 microliter aliquot for each measurement. Here packed solution software is used for the measurement.Get the area intensity of the band of sugar on the chromatogram of each standard solution by clicking re-analysis with the right button of the mouse. Then plug the area intensities against the corresponding concentrations to get the working curve for each sugar by linear regression. From the curve, the equation representing the relationship between the area intensity and the concentration is obtained for each sugar.After obtaining the standard curve, measure the HPLC spectrograms of sample solutions by injecting a 20 microliter aliquot for each measurement. Get the area intensities of the bands of sugars on the chromatogram of each sample solution as before. Refer to the text protocol for steps on performing HPLC measurements of organic acids.Keep the blueberries in a freezer below minus 80 degrees celsius if they are not to be analyzed for anthocyanins just after the spectrum measurements. To perform pre-treatment for HPLC measurements of anthocyanins, dry each frozen fruit with a vacuum lyophalyzer for 12 hours. Extract anthocyanin from the dried blueberry in a one percent methanol solution of trifluruocetic acid by leaving the mixture in a refrigerator at four degrees celsius for 12 hours.Centrifuge the extract for 15 minutes in a two milliliter microtube using an ultra-centrifuge at minus eight degrees celsius and 15, 000 RPM. Then filter the extract through 0.45 micron filter to get the sample for HPLC measurements. Arrange the HPLC system using a C18 reverse phase column in a column oven at 40 degrees celsius.Apply the gradient method using a 0.1 percent aqueous trifluroacetic acid as LUNA. And 0.5 percent trifluroacetic acid in acetonitrile as LUNB. Use a flow rate of 0.1 milliliters per minute where the ratio of LUNB increases from eight percent to 15%during zero to 50 minutes after the injection.And from 15%to 75%during 50 to 60 minutes after the injection. Use a photo diode array detector monitoring at 520 nanometers. Measure the HPLC spectrograms of standard solutions by injecting a 10 microliter aliquot through the auto-sampler for each measurement.Use the LC solution software for the measurement. Finally measure the HPLC spectrograms of sample solutions by injecting a 10 microliter aliquot through the auto-sampler for each measurement. At this point, the construction of calibration models for prediction of ingredient contents, followed by the validation of these constructed models, is performed as described in the text protocol.Prediction models are constructed using the observed spectra and the ingredient contents determined through the procedure shown here. An example of the result of cross validation of the model constructed for the prediction of total sugar content is shown here. The correlation between the values predicted by near-infrared spectroscopy and those determined by HPLC is satisfactory.A similar result is observed for the cross validation of the model for total anthocyanin content. Again the correlation between the predicted values and the observed ones is satisfactory. After watching this video, you should have a good understanding of how to get previous values of content of blueberries with HPLC.Different evaluation is possible only by using the models constructed properly based on the preset content measured by destructive chemical analysis. It means that previous chemical analysis of a target is mystery to construct high performance prediction models. Please refer to the text protocol for the procedure of the construction of prediction models that are not shown in this video.Once constructed properly, the models for prediction are applicable for the prediction of sugar, organic acids, and any contents of blueberries. Near-infrared spectroscopy, as shown here, is expected to be applicable for the correlation of many kinds of farm products. Don't forget that it is necessary to get preset barriers of content through chemical analysis for the construction of a good model when applying near-infrared spectroscopy to evaluation of any farm product.

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