Optimization Of Microbial Activity In Irvingia Gabonensis Seeds Fermentation During ‗Itugha' Production

ABSTRACT : Optimization of this process is meant to develop the design and unit processes of fermenting irvingia gabonensis seeds, in the production of a product considered more nutritious than the raw material from which it is produced. This study assesses the optimal conditions in which the microbes thrive and give the desired product quality. The parameters: pH, temperature, acidity of fermenting medium and the different organic acids produced during the fermentation process, were monitored on a daily basis. Bacterial isolates included Bacillus spp, Micrococcus spp, and streptococcus spp. Principally only one fungi Candida tropicalis DMB321 was involved in the entire process. Three stages were categorized in the process flow chart. The early stage fermentation caused by Bacillus spp, at pH 6-7, 30 O C and 1.8% acidity of extract; the intermediary stage microorganism, Micrococcus spp, and Streptococcus, at pH 5.6, 35-38 O C and 4.4% acidity of extract while the late stage showed drastic decrease in bacterial load and prolific increase in growth of Candida tropicallis, at pH 4.5-5.1, 70 O C and 5.4% acidity of extract. Organic acids in the fermenting substrate included citric acid 2.4% DM, glycolic acid 1.22% DM and oxalic acid 2.98% were quantified. Optimization of this fermentation process would enable itugha product development and commercialization. Thereby expanding the frontiers of irvingia gabonensis utilization

The influence of hidden researcher decisions in applied microeconomics

Researchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many-analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size. Statistical significance varied across replications, and for one of the studies the effect\u27s sign varied as well. The standard deviation of estimates across replications was 3-4 times the mean reported standard error

The influence of hidden researcher decisions in applied microeconomics

Researchers make hundreds of decisions about data collection, preparation, and analysis in their research. We use a many‐analysts approach to measure the extent and impact of these decisions. Two published causal empirical results are replicated by seven replicators each. We find large differences in data preparation and analysis decisions, many of which would not likely be reported in a publication. No two replicators reported the same sample size. Statistical significance varied across replications, and for one of the studies the effect's sign varied as well. The standard deviation of estimates across replications was 3-4 times the mean reported standard error