Main Article Content
Aim: The main aim of this study is to identify the factors affecting the big onion productivity of Hambantota district during the off-season. Moreover, we identify the average productivity per acre from Hambantota district and compare it with the other areas that cultivated the big onion. Further, identify the main issues encountered in big onion cultivation in Hambantota and identify the critical contributing factors for the big onion cultivation in this area.
Place and Duration of Study: During the off seasons in 2015 to 2016 in Hambantota District.
Methodology: Sample data was collected from 201 farmers in Hambantota district. Multiple linear regression model was used to identify the factors affecting the big onion productivity in Hambantota district during the off-season. The normality assumption of the regression model was checked using Kolmogorov–Smirnov test, Shapiro Wilk normality test and Skewness and Kurtosis test. Pearson, Spearman’s Rank and Partial correlation tests were used to check the correlations between variables. Mean absolute percentage error (MAPE) and Symmetrical Mean absolute percentage error (SMAPE) values were used to validate the fitted model.
Results: By the multiple linear regression model main factors affecting the productivity of big onion in Hambantota area were Seasonal Months, Monthly Income, Subsidies Fertilizer and Cultivated Quantity. And the R-squared value was most like to 80% and this means these independent variables were described 80% of the dependent variable. Model accuracies were reported as 98.48% and 98.49% from MAPE and SMAPE respectively. Therefore, this multiple linear regression model was suitable for this study. Further, the model determined the affected factors for the big onion cultivation in Hambantota district during the off-season.
Conclusion: Hambantota district average productivity was less than other areas. Big onion productivity of Matale is more than 2 times greater than big onion productivity of Hambantota. Off season big onion cultivation in Hambantota district is not very effective because of the average productivity is less than other areas in Sri Lanka.
Pattie PS, Wickramasinghe YM. Present status and future prospects of onion production in Sri Lanka. 1993;45.
P. T. F. O. N. F. Production. "www.agrimin.gov.lk," Divisions - Ministry of Agriculture - Sri Lanka, 2016 - 2018.
F. P. a. A. D. Marketing, "www.harti.gov.lk," Hector Kobbekaduwa Agrarian Research and Training Institute, January 2015.
C. A. Businesses, Cost of Production of selected Vegitables, Grains and Pulses, CIC Institute of Agri Businesses; 2010.
Matsuyama K. Agricultural productivity, comparative advantage, and economic growth. Journal of Economic Theory. 1992;58(2):317-334.
Thennakoon M, Silva D. Market window analysis: A case of tobacco paddy and big oinin farmers in Galewela, Sri Lanka. Sabaragamuwa University Journal. 2012;11(1):95-108.
Jayathissa R, Wickramasinghe W, Piyasena C. Food consumption patterns in Sri Lanka. Hector Kobbekaduwa Agrarian Research and Training Institute, Colombo; 2014.
Wijesinghe R, Wijesinghe I, Perera A. Socio economic factors affecting the productivity of green gram. Hector Kobbekaduwa Agrarian Research and Training Institute, Colombo; 2015.
Jin S, Huang J, Hu R, Rozelle S. The creation and spread of technology and total factor productivity in China's agriculture. American Journal of Agricultural Economics. 2002;84(4):916-930.
Gunawardena S. An overview of onion production in Sri Lanka, Department of Agriculture, Peradeniya.
Lesly W. Agronomic research on big onion, Field Crops Research and Development Institute, Mahailluppallama.