Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy

Detalles Bibliográficos
Autores principales: Kaur, Simardeep, Singh, Naseeb, Dagar, Preety, Kumar, Amit, Jaiswal, Sandeep, Singh, Binay K., Bhardwaj, Rakesh, Chand Rana, Jai, Riar, Amritbir
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2024
Materias:
Acceso en línea:https://hdl.handle.net/10568/155341
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author Kaur, Simardeep
Singh, Naseeb
Dagar, Preety
Kumar, Amit
Jaiswal, Sandeep
Singh, Binay K.
Bhardwaj, Rakesh
Chand Rana, Jai
Riar, Amritbir
author_browse Bhardwaj, Rakesh
Chand Rana, Jai
Dagar, Preety
Jaiswal, Sandeep
Kaur, Simardeep
Kumar, Amit
Riar, Amritbir
Singh, Binay K.
Singh, Naseeb
author_facet Kaur, Simardeep
Singh, Naseeb
Dagar, Preety
Kumar, Amit
Jaiswal, Sandeep
Singh, Binay K.
Bhardwaj, Rakesh
Chand Rana, Jai
Riar, Amritbir
author_sort Kaur, Simardeep
collection Repository of Agricultural Research Outputs (CGSpace)
format Journal Article
id CGSpace155341
institution CGIAR Consortium
language Inglés
publishDate 2024
publishDateRange 2024
publishDateSort 2024
publisher Elsevier
publisherStr Elsevier
record_format dspace
spelling CGSpace1553412025-10-26T12:50:35Z Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy Kaur, Simardeep Singh, Naseeb Dagar, Preety Kumar, Amit Jaiswal, Sandeep Singh, Binay K. Bhardwaj, Rakesh Chand Rana, Jai Riar, Amritbir protein content perilla infrared spectrophotometry neural networks 2024-10 2024-10-14T14:15:34Z 2024-10-14T14:15:34Z Journal Article https://hdl.handle.net/10568/155341 en Limited Access Elsevier Kaur, S.; Singh, N.; Dagar, P.; Kumar, A.; Jaiswal, S.; Singh, B.K.; Bhardwaj, R.; Chand Rana, J.; Riar, A. (2024) Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR Spectroscopy. Food Bioscience 61: 104821. ISSN: 2212-4292
spellingShingle protein content
perilla
infrared spectrophotometry
neural networks
Kaur, Simardeep
Singh, Naseeb
Dagar, Preety
Kumar, Amit
Jaiswal, Sandeep
Singh, Binay K.
Bhardwaj, Rakesh
Chand Rana, Jai
Riar, Amritbir
Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
title Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
title_full Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
title_fullStr Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
title_full_unstemmed Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
title_short Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
title_sort comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in perilla perilla frutescens l seed meal using nir spectroscopy
topic protein content
perilla
infrared spectrophotometry
neural networks
url https://hdl.handle.net/10568/155341
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