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Analysis of apparent amylose content of market milled rice via digital image photometry using a smartphone camera
Apparent amylose content (AC) of market milled rice was analyzed through digital image photometry (DIP) utilizing a smartphone camera and a free-access software (ImageJ). The DIP-AC method was validated using seven test samples and applied to a set of 17 commercially available milled rices varying i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8645420/ https://www.ncbi.nlm.nih.gov/pubmed/34917945 http://dx.doi.org/10.1016/j.crfs.2021.11.011 |
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author | Tuaño, Arvin Paul P. Castrillo, Gabrielle A. Viola, Gabriel Angelo V. |
author_facet | Tuaño, Arvin Paul P. Castrillo, Gabrielle A. Viola, Gabriel Angelo V. |
author_sort | Tuaño, Arvin Paul P. |
collection | PubMed |
description | Apparent amylose content (AC) of market milled rice was analyzed through digital image photometry (DIP) utilizing a smartphone camera and a free-access software (ImageJ). The DIP-AC method was validated using seven test samples and applied to a set of 17 commercially available milled rices varying in AC. A light box was constructed to accommodate a cuvette and a smartphone while ImageJ was used for digital image analysis towards quantifying AC. Smartphone camera settings were also optimized using the red, green, and blue (RGB) values of the digital images of amylose-iodine blue solutions. ISO 100 combined with shutter speed 1/640 was the optimum and most suitable settings combination when B values were used to generate calibration curves yielding a high degree of linearity (r = 0.995–0.998). Validation showed the DIP-AC method to be accurate based on the conventional ultraviolet–visible (UV-vis) spectrophotometric AC assay. It was also found to be repeatable and precise for non-waxy rice samples only, yielding RSD values below 7% among all replications made within one day and across different days. With the optimized DIP-AC assay, limits of detection and quantitation of AC that is capable of iodine binding at alkaline pH and influencing cooked rice texture, were 0.2% and 0.4% (milled rice basis at 12–14% moisture), respectively. The reported DIP-AC method can be a reliable and accurate assay for determining AC of non-waxy milled rice alternative to UV–vis spectrophotometry. Further refinement of the DIP-AC method is warranted to improve precision in measuring AC of milled waxy rice. |
format | Online Article Text |
id | pubmed-8645420 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-86454202021-12-15 Analysis of apparent amylose content of market milled rice via digital image photometry using a smartphone camera Tuaño, Arvin Paul P. Castrillo, Gabrielle A. Viola, Gabriel Angelo V. Curr Res Food Sci Articles from the special issue: Modern food analysis, edited by Quancai Sun, Xiaodong Xia and Junli Xu Apparent amylose content (AC) of market milled rice was analyzed through digital image photometry (DIP) utilizing a smartphone camera and a free-access software (ImageJ). The DIP-AC method was validated using seven test samples and applied to a set of 17 commercially available milled rices varying in AC. A light box was constructed to accommodate a cuvette and a smartphone while ImageJ was used for digital image analysis towards quantifying AC. Smartphone camera settings were also optimized using the red, green, and blue (RGB) values of the digital images of amylose-iodine blue solutions. ISO 100 combined with shutter speed 1/640 was the optimum and most suitable settings combination when B values were used to generate calibration curves yielding a high degree of linearity (r = 0.995–0.998). Validation showed the DIP-AC method to be accurate based on the conventional ultraviolet–visible (UV-vis) spectrophotometric AC assay. It was also found to be repeatable and precise for non-waxy rice samples only, yielding RSD values below 7% among all replications made within one day and across different days. With the optimized DIP-AC assay, limits of detection and quantitation of AC that is capable of iodine binding at alkaline pH and influencing cooked rice texture, were 0.2% and 0.4% (milled rice basis at 12–14% moisture), respectively. The reported DIP-AC method can be a reliable and accurate assay for determining AC of non-waxy milled rice alternative to UV–vis spectrophotometry. Further refinement of the DIP-AC method is warranted to improve precision in measuring AC of milled waxy rice. Elsevier 2021-11-25 /pmc/articles/PMC8645420/ /pubmed/34917945 http://dx.doi.org/10.1016/j.crfs.2021.11.011 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Articles from the special issue: Modern food analysis, edited by Quancai Sun, Xiaodong Xia and Junli Xu Tuaño, Arvin Paul P. Castrillo, Gabrielle A. Viola, Gabriel Angelo V. Analysis of apparent amylose content of market milled rice via digital image photometry using a smartphone camera |
title | Analysis of apparent amylose content of market milled rice via digital image photometry using a smartphone camera |
title_full | Analysis of apparent amylose content of market milled rice via digital image photometry using a smartphone camera |
title_fullStr | Analysis of apparent amylose content of market milled rice via digital image photometry using a smartphone camera |
title_full_unstemmed | Analysis of apparent amylose content of market milled rice via digital image photometry using a smartphone camera |
title_short | Analysis of apparent amylose content of market milled rice via digital image photometry using a smartphone camera |
title_sort | analysis of apparent amylose content of market milled rice via digital image photometry using a smartphone camera |
topic | Articles from the special issue: Modern food analysis, edited by Quancai Sun, Xiaodong Xia and Junli Xu |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8645420/ https://www.ncbi.nlm.nih.gov/pubmed/34917945 http://dx.doi.org/10.1016/j.crfs.2021.11.011 |
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