Nutritional profile and yield of oyster mushroom cultivated on selected agricultural wastes

Research on mushroom production and products is gaining more grounds globally and in particular Nigeria. This study was carried out to determine nutritional relationship between the substrate used for cultivation and the fruiting body on each of the substrates. Agro-wastes, namely: palm ( Elaeis guineensis ) fruit shaft, plantain ( Musa paradisiaca ) leaves, sawdust and kenaf ( Hibiscus cannabinus ) stem, were assessed for suitability as substrates for cultivation of oyster mushroom ( Pleurotus floridanus Singer ). The spawn of the mushroom was used to inoculate each of the substrates, using a complete randomised design, with five replicates for each substrate. Results showed that all the substrates supported mycelia growth and development of fruiting bodies of the fungus. There were significant differences (P<0.05) among substrates in terms of number of days to complete mycelia run, with the least recorded in palm fruit shaft (25.20), and the highest in kenaf (32.40). Total yield also differed significantly (P<0.05), with the highest in palm fruit shaft (51.4 g 100 g-1) and lowest in plantain leaves (6.0 g 100 g-1). There was also significant difference (P<0.05) in the nutritional content of fruiting bodies, the highest fat content being on plantain leaves (1.72 g 100 g-1) and the lowest on palm fruit shaft (0.55 g 100 g-1). The trend was similar for mushroom substrates, plantain leaves having (2.55 g 100 g-1) and palm fruit shaft, (0.41g 100 g-1). Starch content for fruiting bodies was highest on sawdust (5.31 g 100 g-1) and lowest on kenaf (2.66 g 100 g-1), while for mushroom substrates, kenaf was (0.33g 100 g-1) and palm fruit shaft was (4.45g 100 g-1). There was a positive correlation (r = 0.24) between the nutrient of fruiting bodies and that of the substrate on which it was cultivated.

Selecting candidate predictor variables for the modelling of post-discharge mortality from sepsis: a protocol development project.

Background: Post-discharge mortality is a frequent but poorly recognized contributor to child mortality in resource limited countries. The identification of children at high risk for post-discharge mortality is a critically important first step in addressing this problem. Objectives: The objective of this project was to determine the variables most likely to be associated with post-discharge mortality which are to be included in a prediction modelling study. Methods: A two-round modified Delphi process was completed for the review of a priori selected variables and selection of new variables. Variables were evaluated on relevance according to (1) prediction (2) availability (3) cost and (4) time required for measurement. Participants included experts in a variety of relevant fields. Results: During the first round of the modified Delphi process, 23 experts evaluated 17 variables. Forty further variables were suggested and were reviewed during the second round by 12 experts. During the second round 16 additional variables were evaluated. Thirty unique variables were compiled for use in the prediction modelling study. Conclusion: A systematic approach was utilized to generate an optimal list of candidate predictor variables for the incorporation into a study on prediction of pediatric post-discharge mortality in a resource poor setting.