FT-NIRS Coupled with PLS Regression as a Complement to HPLC Routine Analysis of Caffeine in Tea Samples.

Daily consumption of caffeine in coffee, tea, chocolate, cocoa, and soft drinks has gained wide and plentiful public and scientific attention over the past few decades. The concentration of caffeine in vivo is a crucial indicator of some disorders-for example, kidney malfunction, heart disease, increase of blood pressure and alertness-and can cause some severe diseases including type 2 diabetes mellitus (DM), stroke risk, liver disease, and some cancers. In the present study, near-infrared spectroscopy (NIRS) coupled with partial least-squares regression (PLSR) was proposed as an alternative method for the quantification of caffeine in 25 commercially available tea samples consumed in Oman. This method is a fast, complementary technique to wet chemistry procedures as well as to high-performance liquid chromatography (HPLC) methods for the quantitative analysis of caffeine in tea samples because it is reagent-less and needs little or no pre-treatment of samples. In the current study, the partial least-squares (PLS) algorithm was built by using the near-infrared NIR spectra of caffeine standards prepared in tea samples scanned by a Frontier NIR spectrophotometer (L1280034) by PerkinElmer. Spectra were collected in the absorption mode in the wavenumber range of 10,000-4000 cm-1, using a 0.2 mm path length and CaF2 sealed cells with a resolution of 2 cm-1. The NIR results for the contents of caffeine in tea samples were also compared with results obtained by HPLC analysis. Both techniques provided good results for predicting the caffeine contents in commercially available tea samples. The results of the proposed study show that the suggested FT-NIRS coupled with PLS regression algorithun has a high potential to be routinely used for the quick and reproducible analysis of caffeine contents in tea samples. For the NIR method, the limit of quantification (LOQ) was estimated as 10 times the error of calibration (root mean square error of calibration (RMSECV)) of the model; thus, RMSEC was calculated as 0.03 ppm and the LOQ as 0.3 ppm.

Chemical, molecular and structural studies of Boswellia species: ß-Boswellic Aldehyde and 3-epi-11ß-Dihydroxy BA as precursors in biosynthesis of boswellic acids.

The distribution and biosynthesis of boswellic acids (BAs) is scarce in current literature. Present study aims to elucidate the BAs biosynthetic and its diversity in the resins of Boswellia sacra and Boswellia papyrifera. Results revealed the isolation of new (3ß, 11ß-dihydroxy BA) and recently known (as new source, ß-boswellic aldehyde) precursors from B. sacra resin along with α-amyrin. Following this, a detailed nomenclature of BAs was elucidated. The quantification and distribution of amyrins (3-epi-α-amyrin, ß-amyrin and α-amyrin) and BAs in different Boswellia resins showed highest amyrin and BAs in B. sacra as compared with B. serrata and B. papyrifera. Distribution of BAs significantly varied in the resin of B. sacra collected from dry mountains than coastal trees. In B. sacra, high content of α-amyrin was found in the roots but it lacked ß-amyrin and BAs. The leaf part showed traces of ß-ABA and AKBA but was deficient in amyrins. This was further confirmed by lack of transcript accumulation of amyrin-related biosynthesis gene in leaf part. In contrast, the stem showed presence of all six BAs which are attributed to existence of resin-secretory canals. In conclusion, the boswellic acids are genus-specific chemical constituents for Boswellia species albeit the variation of the amounts among different Boswellia species and grades.

Quantification of Incensole in Three Boswellia Species by NIR Spectroscopy Coupled with PLSR and Cross-Validation by HPLC.

INTRODUCTION: Incensole can be considered as a biomarker for Boswellia species which is a diterpene that has received remarkable pharmacological interest recently due to its potent anti-inflammatory and anti-depressant activity. OBJECTIVE: Near-infrared (NIR) spectroscopy coupled with PLSR (partial least squares regression) as a robust, rapid and alternative method was used to quantify the content of incensole in three species namely B. papyrifera, B. sacra and B. serrata and cross-validated by high-performance liquid chromatography (HPLC). MATERIALS AND METHODS: NIR spectrophotometer was used for the quantification of incensole standards and Boswellia species in absorption mode in the wavelength range between 700 and 2500 nm. A PLSR model was built from the obtained spectral data using 70% of the incensole working standard solutions (training set), ranging from 0.5 to 100 ppm. The PLSR model obtained has a R2 value of 98% with a correlationship of 0.99 and a good prediction with root mean square error for prediction (RMSEP) value of 3.2%. RESULTS: The results indicated that the methanol (MeOH) extract of B. papyrifera resin has the highest concentration of incensole (18.4%) followed by n-hexane (13.5%) and ethyl acetate (3.6%) while trace amounts was detected in the fractions of B. sacra and no incensole was detected in the fractions of B. serrata. CONCLUSION: The findings are in total agreement with the HPLC analysis suggesting that NIR spectroscopy coupled with PLSR is a robust, rapid and non-destructive alternate method for the quantification of incensole in B. papyrifera. Copyright © 2018 John Wiley & Sons, Ltd.

Quantification of AKBA in Boswellia sacra Using NIRS Coupled with PLSR as an Alternative Method and Cross-Validation by HPLC.

INTRODUCTION: 3-O-Acetyl-11-keto-ß-boswellic acid (AKBA), one of the pentacyclic triterpenoids, is the main biologically active constituent in the resin of Boswellia sacra and has received significant pharmacological interest in recent years. OBJECTIVE: It was aimed to develop a robust method to quantify the AKBA content in methanolic extracts of different parts of B. sacra plants and in various fractions of its resin exudates through near-infrared spectroscopy (NIRS) coupled with partial least squares regression (PLSR). MATERIAL AND METHODS: The near-infrared (NIR) spectra were used to measure the AKBA standards and B. sacra samples at a wavelength range between 700 and 2500 nm in absorption mode. A PLSR model was built from the obtained spectral data using 70% of the AKBA working standard solutions (training set), ranging from 0.1 ppm to 100 ppm. The final PLSR showed a R2 value of 99% with a root mean square error of cross-validation (RMSECV) value of 0.39% and a R2 value of 99%. RESULTS: The results showed that a 50% CHCl3 /n-hexane sub-fraction has the highest concentration of AKBA (14.8%), followed by 55% CHCl3 /n-hexane (13.6%), and 40% CHCl3 /n-hexane (6.1%). CONCLUSION: As the results achieved with the proposed NIRS methodology are in close agreement to the results of AKBA analysis using HPLC, we suggest that our proposed NIRS method is a fast alternative and non-destructive method for the analysis of AKBA in different samples of B. sacra. Copyright © 2017 John Wiley & Sons, Ltd.