Feasibility study of near infrared spectroscopy to detect yellow stain on cork granulate
The aim of this study was to evaluate the viability of near infrared spectroscopy (NIRS) to detect the anomaly known as yellow stain on cork granulate. Detecting this anomaly is crucial to the cork granulate stopper industry, since it is associated with the presence of 2.4.6-Trichloroanisole (TCA),...
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Italian Society of Silviculture and Forest Ecology (SISEF)
2018-02-01
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Series: | iForest - Biogeosciences and Forestry |
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Online Access: | https://iforest.sisef.org/contents/?id=ifor2563-010 |
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author | Pérez-Terrazas D González-Adrados JR Sánchez-González M |
author_facet | Pérez-Terrazas D González-Adrados JR Sánchez-González M |
author_sort | Pérez-Terrazas D |
collection | DOAJ |
description | The aim of this study was to evaluate the viability of near infrared spectroscopy (NIRS) to detect the anomaly known as yellow stain on cork granulate. Detecting this anomaly is crucial to the cork granulate stopper industry, since it is associated with the presence of 2.4.6-Trichloroanisole (TCA), this compound having been identified as the main agent responsible for cork off-flavours. Samples for the NIRS spectra were prepared by mixing in different proportions cork granulate with high visual quality and cork granulate with yellow stain, obtaining 120 samples with 8 different percentages of yellow stain (0, 5, 10, 15, 25, 35, 50 and 100%). Two spectra per sample were collected using a Bruker MPA spectrophotometer and the partial least squares (PLS) method was used to obtain numerous equations. The best equation was obtained by utilizing the standard normal variate (SNV) spectral preprocessing, making use of only one specific part of the near infrared spectral range: 9400-4250 cm-1. This equation shows a coefficient of determination (R²) of 99.42%, a root mean square error of cross validation (RMSECV) of 2.34%, and a residual prediction deviation (RPD) of 13.10. The critical level and the limit of detection are 3.8% and 7.6%, respectively. The calculated receiver operating characteristic (ROC) curves show great discrimination capacity and the area under the ROC curve (AUC) is higher than 0.93 in any case. This study demonstrates that NIRS provides a viable technique for detecting yellow stain in cork granulate. |
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institution | Directory Open Access Journal |
issn | 1971-7458 1971-7458 |
language | English |
last_indexed | 2024-12-21T04:39:56Z |
publishDate | 2018-02-01 |
publisher | Italian Society of Silviculture and Forest Ecology (SISEF) |
record_format | Article |
series | iForest - Biogeosciences and Forestry |
spelling | doaj.art-30b2ce4ef06f428aa376b6267b9af8082022-12-21T19:15:44ZengItalian Society of Silviculture and Forest Ecology (SISEF)iForest - Biogeosciences and Forestry1971-74581971-74582018-02-0111111111710.3832/ifor2563-0102563Feasibility study of near infrared spectroscopy to detect yellow stain on cork granulatePérez-Terrazas D0González-Adrados JR1Sánchez-González M2INIA-CIFOR, Ctra. de La Coruña km 7.5, E-28040 Madrid (Spain)MONTES (School of Forest Engineering and Natural Environment), Universidad Politécnica de Madrid, C/ José Antonio Novais s/n, E-28040 Madrid (Spain)INIA-CIFOR, Ctra. de La Coruña km 7.5, E-28040 Madrid (Spain)The aim of this study was to evaluate the viability of near infrared spectroscopy (NIRS) to detect the anomaly known as yellow stain on cork granulate. Detecting this anomaly is crucial to the cork granulate stopper industry, since it is associated with the presence of 2.4.6-Trichloroanisole (TCA), this compound having been identified as the main agent responsible for cork off-flavours. Samples for the NIRS spectra were prepared by mixing in different proportions cork granulate with high visual quality and cork granulate with yellow stain, obtaining 120 samples with 8 different percentages of yellow stain (0, 5, 10, 15, 25, 35, 50 and 100%). Two spectra per sample were collected using a Bruker MPA spectrophotometer and the partial least squares (PLS) method was used to obtain numerous equations. The best equation was obtained by utilizing the standard normal variate (SNV) spectral preprocessing, making use of only one specific part of the near infrared spectral range: 9400-4250 cm-1. This equation shows a coefficient of determination (R²) of 99.42%, a root mean square error of cross validation (RMSECV) of 2.34%, and a residual prediction deviation (RPD) of 13.10. The critical level and the limit of detection are 3.8% and 7.6%, respectively. The calculated receiver operating characteristic (ROC) curves show great discrimination capacity and the area under the ROC curve (AUC) is higher than 0.93 in any case. This study demonstrates that NIRS provides a viable technique for detecting yellow stain in cork granulate.https://iforest.sisef.org/contents/?id=ifor2563-010CorkGranulateYellow Stain2,4,6-TrichloroanisoleTCANear Infrared SpectroscopyNIRS |
spellingShingle | Pérez-Terrazas D González-Adrados JR Sánchez-González M Feasibility study of near infrared spectroscopy to detect yellow stain on cork granulate iForest - Biogeosciences and Forestry Cork Granulate Yellow Stain 2,4,6-Trichloroanisole TCA Near Infrared Spectroscopy NIRS |
title | Feasibility study of near infrared spectroscopy to detect yellow stain on cork granulate |
title_full | Feasibility study of near infrared spectroscopy to detect yellow stain on cork granulate |
title_fullStr | Feasibility study of near infrared spectroscopy to detect yellow stain on cork granulate |
title_full_unstemmed | Feasibility study of near infrared spectroscopy to detect yellow stain on cork granulate |
title_short | Feasibility study of near infrared spectroscopy to detect yellow stain on cork granulate |
title_sort | feasibility study of near infrared spectroscopy to detect yellow stain on cork granulate |
topic | Cork Granulate Yellow Stain 2,4,6-Trichloroanisole TCA Near Infrared Spectroscopy NIRS |
url | https://iforest.sisef.org/contents/?id=ifor2563-010 |
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