KRISHI
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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/13053
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | R. Pandiselvam | en_US |
dc.date.accessioned | 2018-11-24T07:50:44Z | - |
dc.date.available | 2018-11-24T07:50:44Z | - |
dc.date.issued | 2016-04-01 | - |
dc.identifier.citation | Pandiselvam, R., Sunoj, S. and Uma, D., 2016. Development of Multivariate Regression Model for Quantification of Proximate Content in Vigna Radiata Using Fourier Transform–NIR Spectroscopy. | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/13053 | - |
dc.description | Not Available | en_US |
dc.description.abstract | The Fourier Transform Near Infrared (FT-NIR) absorbance spectra (12800-3600 cm-1) of 222 green gram samples was used to build calibration models for the determination of the content of protein, fat and carbohydrate. The samples that comprised the dataset had an average composition of 22.18% of protein, 1.30% fat, and 50.72% carbohydrate. Multivariate regression was used to develop the quantitative models for protein, fat and carbohydrate compounds. The root mean square error of cross validation (RMSECV) was 0.191 (R2 = 91.52) for protein, 0.0271 (R2 = 88.54) for fat and 0.765 (R2 = 93.62) for carbohydrate. A fast, simple and accurate method to quantify the proximate content of green gram was developed by using FT-NIR spectroscopy. The results showed that FT-NIR spectroscopy could support chemical analysis methods. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | Not Available | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | FT-NIR | en_US |
dc.subject | Green gram | en_US |
dc.subject | Composition | en_US |
dc.title | DEVELOPMENT OF MULTIVARIATE REGRESSION MODEL FOR QUANTIFICATION OF PROXIMATE CONTENT IN VIGNA RADIATA USING FOURIER TRANSFORM –NIR SPECTROSCOPY | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Research Paper | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Scientific Journal Agricultural Engineering | en_US |
dc.publication.volumeno | Not Available | en_US |
dc.publication.pagenumber | 61-70 | en_US |
dc.publication.divisionUnit | Physiology, Biochemistry and Post Harvest Technology Division | en_US |
dc.publication.sourceUrl | Not Available | en_US |
dc.publication.authorAffiliation | Central Plantation Crops Research Institute (CPCRI) | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
Appears in Collections: | HS-CPCRI-Publication |
Files in This Item:
File | Description | Size | Format | |
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DEVELOPMENT OF MULTIVARIATE REGRESSION MODEL FOR QUANTIFICATION OF PROXIMATE CONTENT.pdf | 372.96 kB | Adobe PDF | View/Open |
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