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Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy
Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Fo...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481643/ https://www.ncbi.nlm.nih.gov/pubmed/34603350 http://dx.doi.org/10.3389/fpls.2021.720022 |
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author | Ejaz, Irsa He, Siyang Li, Wei Hu, Naiyue Tang, Chaochen Li, Songbo Li, Meng Diallo, Boubacar Xie, Guanghui Yu, Kang |
author_facet | Ejaz, Irsa He, Siyang Li, Wei Hu, Naiyue Tang, Chaochen Li, Songbo Li, Meng Diallo, Boubacar Xie, Guanghui Yu, Kang |
author_sort | Ejaz, Irsa |
collection | PubMed |
description | Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Fourier-transform (FT) NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by FT-NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. This study aimed to provide a reference for the evaluation of sorghum grain biochemicals for food, feed, and fuel without destruction and complex chemical analysis. |
format | Online Article Text |
id | pubmed-8481643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84816432021-10-01 Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy Ejaz, Irsa He, Siyang Li, Wei Hu, Naiyue Tang, Chaochen Li, Songbo Li, Meng Diallo, Boubacar Xie, Guanghui Yu, Kang Front Plant Sci Plant Science Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Fourier-transform (FT) NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by FT-NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. This study aimed to provide a reference for the evaluation of sorghum grain biochemicals for food, feed, and fuel without destruction and complex chemical analysis. Frontiers Media S.A. 2021-09-16 /pmc/articles/PMC8481643/ /pubmed/34603350 http://dx.doi.org/10.3389/fpls.2021.720022 Text en Copyright © 2021 Ejaz, He, Li, Hu, Tang, Li, Li, Diallo, Xie and Yu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Ejaz, Irsa He, Siyang Li, Wei Hu, Naiyue Tang, Chaochen Li, Songbo Li, Meng Diallo, Boubacar Xie, Guanghui Yu, Kang Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy |
title | Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy |
title_full | Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy |
title_fullStr | Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy |
title_full_unstemmed | Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy |
title_short | Sorghum Grains Grading for Food, Feed, and Fuel Using NIR Spectroscopy |
title_sort | sorghum grains grading for food, feed, and fuel using nir spectroscopy |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481643/ https://www.ncbi.nlm.nih.gov/pubmed/34603350 http://dx.doi.org/10.3389/fpls.2021.720022 |
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