TY - JOUR
T1 - IDENTIFICATION AND AUTHENTICATION OF HONEY USING CHEMOMETRIC ANALYSIS BASED ON ATR-FTIR AND RAMAN SPECTROSCOPY
AU - Sahlan, Muhamad
AU - Ahlam, Nur Annisa Luthfiyah
AU - Agus, Ali
AU - Sabir, Ardo
AU - Pratami, Diah Kartika
N1 - Funding Information:
This research was funded by the Indonesian Ministry of Research and Technology/National Agency for Research and Innovation and Indonesian Ministry of Education and Culture under Program Penelitian Kolaborasi Indonesia (PPKI) 2021 managed by Universitas Indonesia, contract no. NKB-462/UN2. RST/HKP.05.00/ 2021. The author gratefully acknowledged the Basic Chemical Process Laboratory Faculty of Engineering University of Indonesia and the Integrated Laboratory and Research Center (ILRC) the University of Indonesia who has provided facilities for this research.
Funding Information:
This research was funded by the Indonesian Ministry of Research and Technology/National Agency for Research and Innovation and Indonesian Ministry of Education and Culture under Program Penelitian Kolaborasi Indonesia (PPKI) 2021 managed by Universitas Indonesia, contract no. NKB-462/UN2. RST/HKP.05.00/ 2021.
Publisher Copyright:
© 2022 The Authors. Published by Innovare Academic Sciences Pvt Ltd.
PY - 2022/6
Y1 - 2022/6
N2 - Objective: This study aims to develop a fast, fitted, and accurate classification method for authenticating honey. Methods: The authentic honey samples were obtained from local beekeepers and distributors, while most of the adulterated honey samples were made from a mixture of fructose syrup, authentic honey, sodium bicarbonate, and sweet soy sauce, while others were received from local distributors. To authenticate the honey, samples were divided into two classes, real honey, and adulterated honey. Similarly, to classify the honey, we categorized two classes, Apis spp. and stingless bee. ATR-FTIR spectra data were collected using Thermo Scientific’s OMNIC FTIR software and processed using Thermo Scientific’s TQ Analyst software by dividing the wavelengths into six regions between 550-4000 cm-1. and Raman spectra data were collected using HORIBA LabSpec 6 software and processed using CAMO’s Unscrambler X10.4 software by dividing the Raman shifts into five regions between 200-3350 cm-1. Results: Our methods effectively authenticate the honey-based on ATR-FTIR and Raman spectra. Based on ATR-FTIR spectra data, the best region of honey’s authenticity is Region 1,3,4,5,6 (2800-3000 cm-1; 1640-1760 cm-1; 1175-1455 cm-1; 950-1175 cm-1; 750-950 cm-1) and the best region for classification is 750-950 cm-1. Based on Raman spectra data, the best region of honey’s authenticity is 970-1150 cm-1 and the best region for classification are 1150-1480 cm-1 and 970-1480 cm-1. Conclusion: This study successfully demonstrated accurate methods based on ATR-FTIR and Raman spectral data to authenticate and classify the honey.
AB - Objective: This study aims to develop a fast, fitted, and accurate classification method for authenticating honey. Methods: The authentic honey samples were obtained from local beekeepers and distributors, while most of the adulterated honey samples were made from a mixture of fructose syrup, authentic honey, sodium bicarbonate, and sweet soy sauce, while others were received from local distributors. To authenticate the honey, samples were divided into two classes, real honey, and adulterated honey. Similarly, to classify the honey, we categorized two classes, Apis spp. and stingless bee. ATR-FTIR spectra data were collected using Thermo Scientific’s OMNIC FTIR software and processed using Thermo Scientific’s TQ Analyst software by dividing the wavelengths into six regions between 550-4000 cm-1. and Raman spectra data were collected using HORIBA LabSpec 6 software and processed using CAMO’s Unscrambler X10.4 software by dividing the Raman shifts into five regions between 200-3350 cm-1. Results: Our methods effectively authenticate the honey-based on ATR-FTIR and Raman spectra. Based on ATR-FTIR spectra data, the best region of honey’s authenticity is Region 1,3,4,5,6 (2800-3000 cm-1; 1640-1760 cm-1; 1175-1455 cm-1; 950-1175 cm-1; 750-950 cm-1) and the best region for classification is 750-950 cm-1. Based on Raman spectra data, the best region of honey’s authenticity is 970-1150 cm-1 and the best region for classification are 1150-1480 cm-1 and 970-1480 cm-1. Conclusion: This study successfully demonstrated accurate methods based on ATR-FTIR and Raman spectral data to authenticate and classify the honey.
KW - Apis spp
KW - ATR-FTIR
KW - Discriminant analysis
KW - Honey
KW - Raman
KW - Stingless bee
UR - http://www.scopus.com/inward/record.url?scp=85133955345&partnerID=8YFLogxK
U2 - 10.22159/ijap.2022.v14s3.08
DO - 10.22159/ijap.2022.v14s3.08
M3 - Article
AN - SCOPUS:85133955345
SN - 0975-7058
VL - 14
SP - 36
EP - 44
JO - International Journal of Applied Pharmaceutics
JF - International Journal of Applied Pharmaceutics
IS - Special Issue 3
ER -