Anupma Sharma

Coupling of chromatographic analyses with pretreatment for the determination of bioactive compounds in Emblica officinalis juice

A simple and new method for the simultaneous detection and quantification of vitamin C (ascorbic acid), phenolic acids (gallic acid and ellagic acid), hydroxycinnamic acid (chlorogenic acid) and flavonoids (myricetin, quercetin and kaempferol) in Emblica juice is developed. The compounds are separated in 18 minutes by an intangible curved gradient of 0.1% ortho-phosphoric acid in water (v/v) and acetonitrile, as mobile phase A and B, respectively, using Zorbax SB RP C-18 column at a wavelength of 254 nm. The assay was optimized by varying the mobile phase, gradient type, pretreatment method (thermal and non-thermal) and detection wavelength. The method was validated in terms of linearity, precision, detection limits and quantification limits. Good linear response was observed over the range specified for all the analytes, as confirmed by the correlation coefficient which ranged from 0.991 and 0.995. The limit of detection (LOD) and limit of quantification (LOQ) were found to be in the range of 0.129–0.685 μg ml−1 and 0.43–2.883 μg ml−1 respectively. Pulsed electric field (PEF) was used as the non-thermal pretreatment sample technique. HPLC-PDA showed increased levels of phenolic acids, as gallic and ellagic acid, and flavonoid, as quercetin, in PEF treated Emblica juice with respect to the untreated and thermally treated juice samples (p < 0.05). The overall precision values obtained for standards and samples were within the range 0.01–0.2 and 0.15–0.23 respectively. Further, total polyphenolic content and free radical scavenging capacity of the untreated, thermally and PEF treated Emblica juice were corroborated by HPLC.

Towards biological plausibility of electronic noses

The paper presents a novel encoding scheme for neuronal code generation for odour recognition using an electronic nose (EN). This scheme is based on channel encoding using multiple Gaussian receptive fields superimposed over the temporal EN responses. The encoded data is further applied to a spiking neural network (SNN) for pattern classification. Two forms of SNN, a back-propagation based SpikeProp and a dynamic evolving SNN are used to learn the encoded responses. The effects of information encoding on the performance of SNNs have been investigated. Statistical tests have been performed to determine the contribution of the SNN and the encoding scheme to overall odour discrimination. The approach has been implemented in odour classification of orthodox black tea (Kangra-Himachal Pradesh Region) thereby demonstrating a biomimetic approach for EN data analysis.

Rapid HPLC Method for Determination of Vitamin C, Phenolic Acids, Hydroxycinnamic Acid, and Flavonoids in Seasonal Samples of Emblica officinalis Juice

The work proposes a simple method for simultaneous detection and quantification of vitamin C (ascorbic acid), phenolic acids (gallic acid and ellagic acid), hydroxycinnamic acid (chlorogenic acid), and flavonoids (myricetin, quercetin, and kaempferol) in seasonal samples of emblica juice. The compounds were separated by an intangible curved gradient of 0.1% orthophosphoric acid in water (v/v) and acetonitrile as mobile phase A and B using Zorbax SB RP C-18 column at a wavelength of 254 nm in 18 min. The assay was optimized by varying the mobile phase, gradient type, and detection wavelength. The method was validated in terms of linearity, precision, detection limits, and quantification limits. Good linear response was observed over the range specified for all the analytes, as confirmed by the correlation coefficient which ranged from 0.991 and 0.995. The limit of detection and limit of quantification were found to be in the range of 0.129–0.685 µg mL−1 and 0.43–2.883 µg mL−1, respectively. Complete resolution of the phenolic compounds was achieved without the need of pre-analysis processes. The overall precision values obtained for standards and samples were within the range of 0.01–0.2 and 0.15–0.23, respectively.

DEVELOPMENT AND OPTIMIZATION OF AN HPLC METHOD FOR THE ROUTINE ANALYSIS OF CATECHINS, CAFFEINE, AND GALLIC ACID IN TEA (CAMELLIA SINENSIS)

An efficient and rapid high performance liquid chromatographic (HPLC) assay was developed for the quantification of catechins [(+) – catechin, (−) – epigallocatechin, (−) – epigallocatechingallate, (−) – epicatechin, and (−) – epicatechingallate], caffeine, and gallic acid in tea (Camellia Sinesis var. sinesis). The assay was optimized by varying sample strength, column temperature, gradient type, and detection wavelength. A curved gradient using a Thermo Hypersil ODS column with 0.05% orthophosphoric acid and methanol as mobile phase A and B, respectively, and UV detection at 277.5 nm was employed. It was observed that a curved gradient along with an optimal temperature, dramatically improves the signal to noise ratio and separation profile. The limit of detection (LOD) and limit of quantification (LOQ) were found to be in the range of 1.04–22.81 µg mL−1 and 3.47–76.05 µg mL−1 respectively. The overall precision values obtained from the analysis of Kangra and Darjeeling orthodox tea samples were within the range of 0–0.34 (standard error).

A Rapid High-Performance Liquid Chromatography Photodiode Array Detection Method to Determine Phenolic Compounds in Mung Bean (Vigna radiata L.)

A fast method was developed for simultaneous detection and quantification of 12 phenolic compounds in mung bean, using reversed phase high-performance liquid chromatography. The method was optimized for mobile phase combination, elution gradient, detection wavelength, and solvent extraction. All the phenolic compounds (gallic acid, neochlorogenic acid, catechin, chlorogenic acid, caffeic acid, p-coumaric acid, t-ferulic acid, vitexin, isovitexin, myricetin, quercetin, and kaempferol) were eluted for 18 min and recovered within a limit as per International Council for Harmonization guidelines. The method showed good linearity with correlation coefficient of 0.998. The limit of detection and quantification of all the compounds ranges from 0.27 ± 0.01 to 3.65 ± 0.3µg/mL and 0.91 ± 0.1 to 12.17 ± 0.9µg/mL, respectively. Vitexin (28.10 ± 0.20 to 29.60 ± 0.6 mg/100 g raw material) and isovitexin (34.09 ± 0.14 to 36.83 ± 0.82 mg/100 g raw material) were the major phenolic compounds along with other phenolic compounds found in mung beans.

Bacteriorhodopsin–ZnO hybrid as a potential sensing element for low-temperature detection of ethanol vapour

Summary Zinc oxide (ZnO) and bacteriorhodopsin (bR) hybrid nanostructures were fabricated by immobilizing bR on ZnO thin films and ZnO nanorods. The morphological and spectroscopic analysis of the hybrid structures confirmed the ZnO thin film/nanorod growth and functional properties of bR. The photoactivity results of the bR protein further corroborated the sustainability of its charge transport property and biological activity. When exposed to ethanol vapour (reducing gas) at low temperature (70 °C), the fabricated sensing elements showed a significant increase in resistivity, as opposed to the conventional n-type behaviour of bare ZnO nanostructures. This work opens up avenues towards the fabrication of low temperature, photoactivated, nanomaterial–biomolecule hybrid gas sensors.

Quality assessment of engine oil: An impedance spectroscopy based approach

A.C impedance spectroscopy is a very popular and decisive method to determine certain physicochemical properties of samples. In this work we use classification algorithms to identify the used or fresh class of engine oils, based on their impedance spectra. A proposed equivalent circuit, with multiple combination of resistors, capacitors and constant phase element (CPE), along with raw impedance data constituted the input feature matrix for the classifiers. Classifiers, based on Support Vector Machine (SVM) and Artificial Neural Network applied separately, were able to identify between used samples and fresh samples with an accuracy of about 98 to 100 percent. The qualitative performance of the method was defined by false positive rate, false negative rate, sensitivity rate and specificity rate.

Chemometric assisted RP-HPLC for fingerprinting of Indian orthodox black tea

In view of the large variation in tea quality, this study aims to fingerprint the best quality of Indian orthodox black tea depending upon the production region, variation of seasons, mechanical grading and processing with different fermentation times. A HPLC method reported by us earlier has been adapted to separate biochemical constituents in various tea samples, in which Thermo Hypersil ODS column has been found to be more efficient in terms of resolution and retention time. Even black tea processed from the same region but processed in different seasons or mechanically graded resulted in significant compositional changes. The average data from HPLC was subjected to chemometric analysis i.e. principal component analysis (PCA). Different clusters were obtained for each type of tea which can act as a fingerprint for further analysis and interpretation of tea quality for its ranking. Thus, HPLC integrated with chemometrics can be explored as a routine diagnostic tool for online monitoring of black tea quality.