Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains
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| Formato: | Artículo |
| Lenguaje: | inglés |
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2018
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| _version_ | 1881508832234962944 |
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| author | Wilson Castro José Manuel Prieto Roenfi Guerra Tony Chuquizuta Wenceslao T. Medina Brenda Acevedo-Juárez Himer Ávila-George |
| author_browse | Brenda Acevedo-Juárez Himer Ávila-George José Manuel Prieto Roenfi Guerra Tony Chuquizuta Wenceslao T. Medina Wilson Castro |
| author_facet | Wilson Castro José Manuel Prieto Roenfi Guerra Tony Chuquizuta Wenceslao T. Medina Brenda Acevedo-Juárez Himer Ávila-George |
| author_sort | Wilson Castro |
| collection | Producción científica |
| format | Article |
| id | oai:cris.upeu.edu.pe:20.500.15037/654 |
| institution | UPeU |
| language | English |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| record_format | dspace |
| spelling | oai:cris.upeu.edu.pe:20.500.15037/6542026-10-30T16:14:45ZFeasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grainsWilson CastroJosé Manuel PrietoRoenfi GuerraTony ChuquizutaWenceslao T. MedinaBrenda Acevedo-JuárezHimer Ávila-GeorgeChenopodium quinoaWater activityHyperspectral imagingPartial least squares regressionMathematicsLinear regressionCoefficient of determinationFood scienceChemistryAnalytical Chemistry (journal)StatisticsWater contentRemote sensingEnvironmental chemistryGeographyEngineeringGeotechnical engineeringChenopodium quinoaWater activityHyperspectral imagingPartial least squares regressionMathematicsLinear regressionCoefficient of determinationFood scienceChemistryAnalytical Chemistry (journal)StatisticsWater contentRemote sensingEnvironmental chemistryGeographyLife Sciences Agricultural and Biological Sciences Food Science Seed and Plant BiochemistryPhysical Sciences Chemistry Analytical Chemistry Spectroscopy and Chemometric AnalysesLife Sciences Agricultural and Biological Sciences Food Science Sensory Analysis and Statistical MethodsArticle10.1016/j.jfoodeng.2018.06.012https://hdl.handle.net/20.500.15037/654W2808488807enJournal of Food Engineering0260-87741873-57702018-06-132026-06-13T09:29:08Z2026-06-13T09:29:08Z |
| spellingShingle | Chenopodium quinoa Water activity Hyperspectral imaging Partial least squares regression Mathematics Linear regression Coefficient of determination Food science Chemistry Analytical Chemistry (journal) Statistics Water content Remote sensing Environmental chemistry Geography Engineering Geotechnical engineering Chenopodium quinoa Water activity Hyperspectral imaging Partial least squares regression Mathematics Linear regression Coefficient of determination Food science Chemistry Analytical Chemistry (journal) Statistics Water content Remote sensing Environmental chemistry Geography Life Sciences Agricultural and Biological Sciences Food Science Seed and Plant Biochemistry Physical Sciences Chemistry Analytical Chemistry Spectroscopy and Chemometric Analyses Life Sciences Agricultural and Biological Sciences Food Science Sensory Analysis and Statistical Methods Wilson Castro José Manuel Prieto Roenfi Guerra Tony Chuquizuta Wenceslao T. Medina Brenda Acevedo-Juárez Himer Ávila-George Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains |
| title | Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains |
| title_full | Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains |
| title_fullStr | Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains |
| title_full_unstemmed | Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains |
| title_short | Feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains |
| title_sort | feasibility of using spectral profiles for modeling water activity in five varieties of white quinoa grains |
| topic | Chenopodium quinoa Water activity Hyperspectral imaging Partial least squares regression Mathematics Linear regression Coefficient of determination Food science Chemistry Analytical Chemistry (journal) Statistics Water content Remote sensing Environmental chemistry Geography Engineering Geotechnical engineering Chenopodium quinoa Water activity Hyperspectral imaging Partial least squares regression Mathematics Linear regression Coefficient of determination Food science Chemistry Analytical Chemistry (journal) Statistics Water content Remote sensing Environmental chemistry Geography Life Sciences Agricultural and Biological Sciences Food Science Seed and Plant Biochemistry Physical Sciences Chemistry Analytical Chemistry Spectroscopy and Chemometric Analyses Life Sciences Agricultural and Biological Sciences Food Science Sensory Analysis and Statistical Methods |
| topic_facet | Chenopodium quinoa Water activity Hyperspectral imaging Partial least squares regression Mathematics Linear regression Coefficient of determination Food science Chemistry Analytical Chemistry (journal) Statistics Water content Remote sensing Environmental chemistry Geography Engineering Geotechnical engineering Chenopodium quinoa Water activity Hyperspectral imaging Partial least squares regression Mathematics Linear regression Coefficient of determination Food science Chemistry Analytical Chemistry (journal) Statistics Water content Remote sensing Environmental chemistry Geography Life Sciences Agricultural and Biological Sciences Food Science Seed and Plant Biochemistry Physical Sciences Chemistry Analytical Chemistry Spectroscopy and Chemometric Analyses Life Sciences Agricultural and Biological Sciences Food Science Sensory Analysis and Statistical Methods |
| url | https://hdl.handle.net/20.500.15037/654 |
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