A A Statistical Analysis on Paddy Crop Production in Southern Punjab, Pakistan
Keywords:
Paddy crop production; Forecasting; Multiple regression; Durbin Watson test; Mean square error; Punjab; PakistanAbstract
Background: Paddy is an important staple food crop of Pakistan and plays a vital role for the economy of Pakistan. Paddy provides more than two million tons for food requirements after wheat in Pakistan. Objectives: The main objective of current research was to identify the factors affecting the paddy crop yield in Lodhran district, Pakistan. Methods: The secondary data of paddy crop production of fifteen villages from 10 years (2005-2014) were collected from Crop Reporting Service, Lodhran district through simple random sampling. Multiple regression models and Durbin Watson (DW) test were used for data analysis. Results: The results showed ten independent variables were found statistically significant and had strong impact on paddy crop production. These were seed type, seed quantity, DAP used, Urea used, other fertilizers used, number of watering, number of ploughs, number of leveling) and average humidity. These all factors were having p-value 0.000 which is highly significant (p< 0.01) in terms of the influence they put on the crop production. Average temperature (p-value of 0.057) was also significant at p< 0.05 level of significance. Whereas crop area and average rainfall were not significant statistically. Moreover, the model applied is statistically significant as various statistical checks including R2, adjusted R2, Durbin Watson test, mean square error, P-value and VIF were applied to test the fitness of the model and for the multicollinearity. Conclusions: The study concluded that several factors such as seed type, seed quantity, DAP, urea and other fertilizers, number of watering, levelling, plough, average temperature and humidity have been a profound impact on the paddy crop yield of the study area. The subjective variables (average temperature and humidity) during cropping period were better in forecasting of paddy crop yield and the model is suitable to estimate the paddy crop yield in district Lodhran.