Composition and functional properties of yam bean (Pachyrhizus spp.) seed flour

Open Access JournalYam bean (Pachyrhizus spp.) is legume crop that not only produces edible roots but also has a high yield of unutilized seeds. Although the yam bean seeds are rich in protein, they are not used due to a high content of toxic rotenone. In this study, yam bean seeds were detoxified and the nutritional and functional properties of their protein determined to assess the proteins’ potential for applications. Seeds of 10 accessions (2 accessions of P. erosus, 4 accessions of P. ahipa and 4 accessions of P. tuberosus) were analyzed for proximate composition, pasting and functional properties (bulk density, least gelation concentration, water absorption capacity, oil absorption capacity, emulsifying capacity, emulsion stability, foaming capacity, foam stability and protein solubility). The results showed that yam bean seeds contained: 29.2 - 32.1 g/100g proteins, 31.3 - 33.0 g/100 g carbohydrates, 24.1 - 25.6 g/100g total fat, 7.5 - 8.1 g/100g crude fiber and 3.4 - 4.1 g/100g ash. The defatted P. erosus seed flour contained 45.6 - 48.8 g/100g protein, 32.6 - 36.5 g/100g total carbohydrate, 6.7 - 7.1 g/100g crude fiber, 6.0 - 6.4 g/100g ash and 5.2/100 g crude fat. The defatted yam bean seed flour exhibited relatively high protein solubility (68.0% - 70.4%), least gelation concentration (14%), water absorption capacity (2.8% - 2.9%) and oil absorption capacity (1.5%). The defatted flour exhibited emulsifying capacity of 35.7% - 36.0%, emulsion stability of 33.2% - 33.5%, foaming capacities of 42% and foam stability of 25.1% - 25.8%. With respect to pasting properties, the defatted yam bean seed flours exhibited pasting temperature of 80.0˚C - 81.3˚C, peak viscosity of 145.5 - 146.7 RVU, trough viscosity of 95.1 - 102.0 RVU, break down of 43.5 - 51.6 RVU, set back of 252.9 - 258.1 RVU and final viscosity of 348 - 360 RVU. The results show that yam bean seed has potential for use in both food and nonfood applications

Impact of COVID-19 on routine malaria indicators in rural Uganda: an interrupted time series analysis.

BACKGROUND: In March 2020, the government of Uganda implemented a strict lockdown policy in response to the COVID-19 pandemic. Interrupted time series analysis (ITSA) was performed to assess whether major changes in outpatient attendance, malaria burden, and case management occurred after the onset of the COVID-19 epidemic in rural Uganda. METHODS: Individual level data from all outpatient visits collected from April 2017 to March 2021 at 17 facilities were analysed. Outcomes included total outpatient visits, malaria cases, non-malarial visits, proportion of patients with suspected malaria, proportion of patients tested using rapid diagnostic tests (RDTs), and proportion of malaria cases prescribed artemether-lumefantrine (AL). Poisson regression with generalized estimating equations and fractional regression was used to model count and proportion outcomes, respectively. Pre-COVID trends (April 2017-March 2020) were used to predict the'expected' trend in the absence of COVID-19 introduction. Effects of COVID-19 were estimated over two six-month COVID-19 time periods (April 2020-September 2020 and October 2020-March 2021) by dividing observed values by expected values, and expressed as ratios. RESULTS: A total of 1,442,737 outpatient visits were recorded. Malaria was suspected in 55.3% of visits and 98.8% of these had a malaria diagnostic test performed. ITSA showed no differences between observed and expected total outpatient visits, malaria cases, non-malarial visits, or proportion of visits with suspected malaria after COVID-19 onset. However, in the second six months of the COVID-19 time period, there was a smaller mean proportion of patients tested with RDTs compared to expected (relative prevalence ratio (RPR) = 0.87, CI (0.78-0.97)) and a smaller mean proportion of malaria cases prescribed AL (RPR = 0.94, CI (0.90-0.99)). CONCLUSIONS: In the first year after the COVID-19 pandemic arrived in Uganda, there were no major effects on malaria disease burden and indicators of case management at these 17 rural health facilities, except for a modest decrease in the proportion of RDTs used for malaria diagnosis and the mean proportion of malaria cases prescribed AL in the second half of the COVID-19 pandemic year. Continued surveillance will be essential to monitor for changes in trends in malaria indicators so that Uganda can quickly and flexibly respond to challenges imposed by COVID-19

The age-specific incidence of hospitalized paediatric malaria in Uganda

Background Understanding the relationship between malaria infection risk and disease outcomes represents a fundamental component of morbidity and mortality burden estimations. Contemporary data on severe malaria risks among populations of different parasite exposures are scarce. Using surveillance data, we compared rates of paediatric malaria hospitalisation in areas of varying parasite exposure levels. Methods Surveillance data at five public hospitals; Jinja, Mubende, Kabale, Tororo, and Apac were assembled among admissions aged 1 month to 14 years between 2017 and 2018. The address of each admission was used to define a local catchment population where national census data was used to define person-year-exposure to risk. Within each catchment, historical infection prevalence was assembled from previously published data and current infection prevalence defined using 33 population-based school surveys among 3400 children. Poisson regression was used to compute the overall and site-specific incidences with 95% confidence intervals. Results Both current and historical Plasmodium falciparum prevalence varied across the five sites. Current prevalence ranged from Conclusion Malaria hospitalisation rates remain high in Uganda particularly among young children. The incidence of hospitalized malaria in different locations in Uganda appears to be influenced by past parasite exposure, immune acquisition, and current risks of infection. Interruption of transmission through vector control could influence age-specific severe malaria risk.</p