Determinants of loan repayment performance of fishermen: empirical evidence from Ghana

This study investigated factors influencing loan repayment performance of fishermen. A survey of 67 randomly sampled fishermen was conducted using a standard questionnaire. An interview schedule was the main tool of data collection while descriptive statistics and multiple regression analysis were the main analytical techniques. The study showed that majority of the fishermen interviewed were in the productive age range, had high average annual income and were experienced fishermen. Empirical results indicated that 70.1% of the fishermen interviewed had delayed repayment and this was partly attributed to low catch and high debts from fishmongers. Regression estimation results reveals that loan repayment increased with years of education, fishing income, years of fishing experience and amount of loan whilst the age and investment made negatively influenced the amount of loan repaid. The regression analysis finds the fishing income, loan and amount of investment made as significant predictors of the amount of loan repaid. The covariates in the model explained 77% of the variation in the loan repaid. It is recommended that allocation of loans to fisheries sector be increased to stimulate fishing activities and improve repayment performance of fishermen

A sensitive method for the determination of gold and palladium based on dispersive liquid-liquid microextraction combined with flame atomic absorption spectrometric determination using N-(6-morpholin-4-ylpyridin-3-yl)-N '-phenylthiourea

Soylak, Mustafa/0000-0002-1017-0244WOS: 000369515500005A new method for the determination of gold and palladium was developed by dispersive liquid-liquid microextraction separation-preconcentration and flame atomic absorption spectrometry detection. In the proposed approach, N-(6-morpholin-4-ylpyridin-3-yl)-N'-phenylthiourea (MPPT) was synthesized as a complexing agent. The complexation ability of the MPPT was explored by examining the effect of a series of heavy metal ions, including Mn2+, Pd2+, Ni2+, Cd2+, Co2+, Cu2+, Au3+, Pb2+, Zn2+ and Fe3+, using the DLLME procedure. The MPPT exhibited pronounced selectivity toward Pd2+ and Au3+ ions at different pH levels. Factors influencing the extraction efficiency and complex formation were examined, i.e. the pH of the sample solution, the concentration of the chelating agent, the extraction and dispersive solvent type and volume, the sample volume, and foreign ions, etc. Optimal conditions for quantitative recoveries were pH 5.5 for gold and pH 1.5 for palladium, 125 mu L of % 0.4 MPPT, 1200 mu L of methanol and 125 mu L of carbon tetrachloride. The presented method showed a good linearity within a range of 30-230 and 25-200 mu g L-1 with the detection limits of 1.75 and 1.65 mu g L-1 for Au and Pd, respectively. The relative standard deviation (RSD) was below 2.8% at 50 mu g L-1 for both ions (n = 10). The developed method was simple, fast, cost efficient, and sensitive for the extraction and preconcentration of gold and palladium in samples of liquids (sea, stream water) and solids (stream sediment, ores, and electronic waste).Unit of the Scientific Research Projects of Karadeniz Technical University [1223]Financial support of the Unit of the Scientific Research Projects of Karadeniz Technical University (Project no: 1223) is gratefully acknowledged

Determinants of farmers’ adaptation to climate change: A micro level analysis in Ghana

ABSTRACT This study analyzed socio-economic factors that influence farmers’ adaptation to climate change in agriculture. Perceptions regarding long-term changes in climate variables and the rate of occurrence of weather extremes were also investigated. Additionally, farmers’ perceived barriers to the use of adaptation practices were identified and ranked. A total of 100 farm-households were randomly selected from four communities in the Lawra district of Ghana and data were collected through semi-structured questionnaires, focused group discussions and field observations. A logistic regression model and weighted average index were used to analyze the data. The results showed that 87 % of respondents perceived a decrease in rainfall amount, while 82 % perceived an increase in temperature over the past 10 years. Results of the weighted average index indicate that dry spell and drought have a higher annual rate of occurrence than flood. Empirical results of the logistic regression model showed that education, household size, annual household income, access to information, credit and membership of farmer-based organization are the most important factors that influence farmers’ adaptation to climate change. The main constraints on adaptation include unpredictability of weather, high farm input cost, lack of access to timely weather information and water resources. The policy implication of this study is that governments should mainstream barriers to, and choice factors of, adaptation practices to climate change related projects and programs