TY - JOUR

T1 - Fast spectroscopic and multisensor methods for analysis of glucosamine and hyaluronic acid in dietary supplements

AU - Lang, Fabienne

AU - Adels, Klaudia

AU - Gaponova, Anna

AU - Panchuk, Vitaly

AU - Kirsanov, Dmitry

AU - Monakhova, Yulia

PY - 2024/12/1

Y1 - 2024/12/1

N2 - There is a lack of fast and inexpensive analytical methods for quantification of key ingredients in dietary supplements. Here we explore the potential of near infrared (NIR) spectrometry, attenuated total reflection infrared (ATR-IR) spectrometry and potentiometric multisensor system (MSS) in quantitative determination of glucosamine and hyaluronic acid in commercial samples of dietary supplements. All three methods have demonstrated their applicability for this task when combined with chemometric data processing. Principal Component Analysis (PCA) revealed similarities across the three techniques, indicating the presence of distinct sample composition. Partial least squares (PLS) models were constructed for glucosamine and hyaluronic acid quantification. The root mean square error of cross validation (RMSECV) for glucosamine quantification varied between 7.7 wt% and 8.9 wt%. NIR spectrometry has demonstrated the best accuracy for hyaluronic acid (RMSECV = 9.9 wt%), while ATR-IR and MSS yielded somewhat worse performance with RMSECV values of 12.1 and 11.3 wt%, respectively. The findings of this study indicated that NIR, ATR-IR and MSS exhibit reduced accuracy in comparison to complex and high-precision analytical techniques. However, they can be employed for the rapid, semi-quantitative evaluation of glucosamine and hyaluronic acid in dietary supplements, with the possibility of integration into routine quality control procedures.

AB - There is a lack of fast and inexpensive analytical methods for quantification of key ingredients in dietary supplements. Here we explore the potential of near infrared (NIR) spectrometry, attenuated total reflection infrared (ATR-IR) spectrometry and potentiometric multisensor system (MSS) in quantitative determination of glucosamine and hyaluronic acid in commercial samples of dietary supplements. All three methods have demonstrated their applicability for this task when combined with chemometric data processing. Principal Component Analysis (PCA) revealed similarities across the three techniques, indicating the presence of distinct sample composition. Partial least squares (PLS) models were constructed for glucosamine and hyaluronic acid quantification. The root mean square error of cross validation (RMSECV) for glucosamine quantification varied between 7.7 wt% and 8.9 wt%. NIR spectrometry has demonstrated the best accuracy for hyaluronic acid (RMSECV = 9.9 wt%), while ATR-IR and MSS yielded somewhat worse performance with RMSECV values of 12.1 and 11.3 wt%, respectively. The findings of this study indicated that NIR, ATR-IR and MSS exhibit reduced accuracy in comparison to complex and high-precision analytical techniques. However, they can be employed for the rapid, semi-quantitative evaluation of glucosamine and hyaluronic acid in dietary supplements, with the possibility of integration into routine quality control procedures.

KW - Dietary supplements

KW - Glucosamine

KW - Hyaluronic acid

KW - IR

KW - NIR

KW - Partial least squares

KW - Sensors

UR - https://www.mendeley.com/catalogue/880acda6-0658-3bba-b905-bf7e8573e240/

U2 - 10.1016/j.microc.2024.112116

DO - 10.1016/j.microc.2024.112116

M3 - Article

VL - 207

JO - Microchemical Journal

JF - Microchemical Journal

SN - 0026-265X

M1 - 112116

ER -