Browsing by Author "Vianney, John Mary"

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Development of Plant-Based Yoghurt Rich in Bioavailable Essential Nutrients and Bioactive Compounds from Ingredients Available in East Africa
(Enviro Research Publishers., 2022-03-25) Dusabe, Angelique; Chacha, Musa; Vianney, John Mary; Raymond, Jofrey
The main aim of the present study was to formulate a convenient plant based yoghurt (PBY) with essential nutrients and bioactive compounds comparable to that of cow's milk using locally available ingredients in East Africa. Linear programming (LP) was applied for ratios optimization. The fermentation technique was deployed using commercial yoghurt culture (Streptococcus thermophilus and Lactobacillus bulgaricus) to develop a palatable and functional yoghurt. Laboratory analysis was conducted to validate the nutritional and functional values calculated by LP, and their relative difference was also calculated. PBY was analyzed for lactic acid bacteria (LAB) viability and storage stability for the 1st, 7th, and 14th day of refrigeration storage (4°C). Results showed that LP-optimized PBY could be formulated at a low cost of USD 0.9/kg, which is 60% cheaper than Alpro natural PBY. The formulation contained 37.87% and 18.88% of total Monounsaturated Fatty acids (MUFAs) and total Polyunsaturated Fatty acids (PUFAs), respectively. PBY riches in essential nutrients and functional properties enough to meet the Recommended Daily Intake (RDI) for 2-10-year old children. Formulated PBY were microbiologically stable for 14 days of storage and were found within acceptable standards specified by the Food Standard Australia New Zealand (FSANZ) and the East African Standard for yoghurt (EAS33:2006). Plant-based yoghurt rich in nutrient bioavailability and bioactive compounds can be formulated using locally available ingredients and considered as an alternative to yoghurt.
Effects of sample preservation methods and duration of storage on the performance of mid-infrared spectroscopy for predicting the age of malaria vectors
(BMC, 2022-08-06) Mgaya, Jacqueline; Siria, Doreen; Makala, Faraja; Mgando, Joseph; Vianney, John Mary; Mwanga, Emmanuel; Okumu, Fredros
Background Monitoring the biological attributes of mosquitoes is critical for understanding pathogen transmission and estimating the impacts of vector control interventions on the survival of vector species. Infrared spectroscopy and machine learning techniques are increasingly being tested for this purpose and have been proven to accurately predict the age, species, blood-meal sources, and pathogen infections in Anopheles and Aedes mosquitoes. However, as these techniques are still in early-stage implementation, there are no standardized procedures for handling samples prior to the infrared scanning. This study investigated the effects of different preservation methods and storage duration on the performance of mid-infrared spectroscopy for age-grading females of the malaria vector, Anopheles arabiensis. Methods Laboratory-reared An. arabiensis (N = 3681) were collected at 5 and 17 days post-emergence, killed with ethanol, and then preserved using silica desiccant at 5 °C, freezing at − 20 °C, or absolute ethanol at room temperature. For each preservation method, the mosquitoes were divided into three groups, stored for 1, 4, or 8 weeks, and then scanned using a mid-infrared spectrometer. Supervised machine learning classifiers were trained with the infrared spectra, and the support vector machine (SVM) emerged as the best model for predicting the mosquito ages. Results The model trained using silica-preserved mosquitoes achieved 95% accuracy when predicting the ages of other silica-preserved mosquitoes, but declined to 72% and 66% when age-classifying mosquitoes preserved using ethanol and freezing, respectively. Prediction accuracies of models trained on samples preserved in ethanol and freezing also reduced when these models were applied to samples preserved by other methods. Similarly, models trained on 1-week stored samples had declining accuracies of 97%, 83%, and 72% when predicting the ages of mosquitoes stored for 1, 4, or 8 weeks respectively. Conclusions When using mid-infrared spectroscopy and supervised machine learning to age-grade mosquitoes, the highest accuracies are achieved when the training and test samples are preserved in the same way and stored for similar durations. However, when the test and training samples were handled differently, the classification accuracies declined significantly. Protocols for infrared-based entomological studies should therefore emphasize standardized sample-handling procedures and possibly additional statistical procedures such as transfer learning for greater accuracy.
Electrochemical Sensing Fabricated with TaO Nanoparticle-Electrochemically Reduced Graphene Oxide Nanocomposite for the Detection of Oxytetracycline.
(MDPI, 2020-01-08) Magesa, Felista; Wu, Yiyong; Dong, Shuai; Tian, Yaling; Li, Guangli; Vianney, John Mary; Buza, Joram; Liu, Jun; He, Quanguo
A novel tantalum pentoxide nanoparticle-electrochemically reduced graphene oxide nanocomposite-modified glassy carbon electrode (TaO-ErGO/GCE) was developed for the detection of oxytetracycline in milk. The composition, structure and morphology of GO, TaO, and TaO-ErGO were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). Oxytetracycline electrochemical behavior on the bare GCE, GO/GCE, ErGO/GCE, and TaO-ErGO/GCE was studied by cyclic voltammetry. The voltammetric conditions (including scan rate, pH, deposition potential, and deposition time) were systematically optimized. With the spacious electrochemical active area, the TaO-ErGO/GCE showed a great magnification of the oxidation signal of oxytetracycline, while that of the other electrodes (GCE, GO/GCE, ErGO/GCE) could not reach the same level. Under the optimum conditions, the currents were proportional to the oxytetracycline concentration in the range from 0.2 to 10 μM, and a low detection limit of 0.095 μM (S/N = 3) was detectable. Moreover, the proposed TaO-ErGO/GCE performed practically with satisfactory results. The preparation of TaO-ErGO/GCE in the current work provides a minor outlook of detecting trace oxytetracycline in milk.