Research Articles

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Browsing Research Articles by Author "Annavaram, V."

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    Hydrothermal fabrication of MoS2/reduced graphene oxide nanohybrid composite for the electrochemical sensing of Hg (II) in green tea.
    (Materials Today: Proceedings, 2022) Annavaram, V.; Somala, A. R.; Chen, Q.; Kutsanedzie, F. Y.; Agyekum, A. A.; Zareef, M.; Hassan, M. M.
    Heavy metal contamination is a standout among the most genuine ecological issues: toxicity, persistence, bioaccumulation, and biomagnification through food chains. The present work aims at the synthesis of abundant, fast-sensing electrochemical sensors MoS2 and MoS2@rGO composite by the hydrothermal method to develop electrochemical sensors for the detection of Mercury (Hg-II). The synthesized material was characterized and conformed to a hierarchical spherical sponge-like structure with a high surface-to-volume ratio. The electrochemical sensor conditions were observed at ambient conditions to detect Hg (II) (0.5, 1, 1.5, 2, 2.5, 3, 3.5 µm L−1 was used) and the results showed very promisingly. The limit of detection (LOD) was found to be 2.0 × 10−7 µg/mL for MoS2, 1.22 × 10−8 µg/mL for composite. The heavy metals were spiked in green tea extract to observe the sensor ability of the material. The sensor ability for the material for real-time detection of green tea was found to be LOD-2.12 × 10−7 µg/mL (MoS2) and 1.21 × 10−9 µg/mL (MoS2@rGO).
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    Rapid and nondestructive quantification of trimethylamine by FT-NIR coupled with chemometric techniques
    (Food Analytical Methods, 2019) Agyekum, A. A.; Kutsanedzie, F. Y.; Mintah, B. K.; Annavaram, V.; Zareef, M.; Hassan, M. M.; Chen, Q.
    This paper focused on the quick and nondestructive evaluation of trimethylamine (TMA-N) in fish storage which is sequent to its freshness, the key for controlling the quality and safety of fish products by combining Fourier transform near-infrared (FT-NIR) and chemometric techniques. Calibration models of fish freshness were established using three multivariate chemometric methods—partial least square (PLS), synergy interval PLS (Si-PLS), and genetic algorithm PLS (GA-PLS) for quantitative prediction of TMA-N in fish. Results of the developed model were estimated using the correlation coefficients of the prediction (Rp) and calibration (Rc); root mean square error of prediction (RMSEP) and the ratio of sample standard deviation to RMSEP (RPD). The established model’s performance achieved 0.943 ≤ Rp ≤ 0.977 and 4.25 ≤ RPD ≤ 4.30. The model’s prediction strength improved in the order PLS < Si-PLS < GA-PLS. GA-PLS significantly improved the prediction of TMA-N prediction with RMSEC = 5.08 and Rc = 98.28 for the calibration data whereas the prediction set gave an RMSEP = 5.10 and Rp = 97.70. FT-NIR spectroscopy combined with GA-PLS technique may be employed for rapid and non-invasive quantification of TMA-N in fish for monitoring safety and quality.
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    Rapid Detection and Prediction of Norfloxacin in Fish Using Bimetallic Au@ Ag Nano-Based SERS Sensor Coupled Multivariate Calibration.
    (Food Analytical Methods, 2022) Agyekum, A. A.; Kutsanedzie, F. Y.; Mintah, B. K.; Annavaram, V.; Braimah, A. O.
    Norfloxacin is an antibiotic in the fluoroquinolone family licenced for use in animals. However, residues in animal products can have negative consequences for consumers. As a result, residue detection in various food matrices must be considered. Norfloxacin accumulates in animal-derived foods, causing deleterious consequences in humans such as foetal deformity, renal failure and drug resistance. A built-in SERS-Au@Ag nanosensor coupled with GA-PLS was used to rapidly detect norfloxacin in the specimen of the spiked fish muscles due to the threat to human lives. A detection limit of 2.36 × 10⁻⁵ μg/mL was realized in the spiked fish muscle sample for norfloxacin compared to the European Commission’s maximum threshold level of 100 μg/kg, indicating the sensor’s ability to detect and quantify norfloxacin at a relatively lower level. The recovery rates (RC) and coefficient of variation (CV) measured in the spiked fish muscle samples for norfloxacin analytes and their standard solutions were between 99.70–105.00% and 0.17–5.21%, respectively. The low CV values imply the reproducibility of the obtained data. The constructed model recorded residual predictive deviations (RPD) greater than three (3), demonstrating the robustness and resilience of the developed genetic algorithm-partial least squares (GA-PLS) model. GA-PLS-built models predicted all results within 4.07 s, which indicates the nanosensor’s ability to rapidly detect norfloxacin in fish to guarantee safety and public health. The SERS probe holds promise for rapid quantification of norfloxacin at microgram per milliliter level in fish to guarantee safety in commerce.