Assessment of the effects of environmental factors on yield of coconut (Cocos nucifera L.)

The long term nut yield data and climate data of eight variables (1976-1992) were analyzed to understand the effects of climate and weather on the yield variability between picks. The yield variation over the years had no systematic pattern. The order of contribution of the picks to total yield is not significantly consistent between years. Explanatory models were developed at monthly lag periods prior to harvest of each pick. The most and least influential picks in respect of climate variability are picks 5 and 2 respectively. The critical period with respect to climate and weather variability of picks 1-6 are February , June July, Septermber, December and February respectively. The climatic models fitted at these periods explain the yield variability between picks. The influence of climatic variables during these periods vary from pick to pick. Maximum air temperature and relative humidity in the afternoon are the two most significant environmental variables influencing yield irrespective of picks

An empirical analysis of stochastic behavior of Sri Lanka exchange rate changes.

The main purpose of this study was to explore the main characteristics of stochastic behaviour of Sri Lankan exchange rate aginst to US dollar,(LKR/US$). This study used daily spot exchange rate time series collected from Central Bank, Sri Lanka web site. The study covers the time period from 2008 to 2010, which represents 722 trading days. The sample period was divided into two. One period was from January 1, 2008 to May 19, 2009 and the other period from May 30, 2009 to December 31, 2010. Graphical techniques, Kernel density function, autocorrelation function, and GARCH models were used to analyse the behaviour of the exchange rate in this study. The results show that basic statistical properties of Sri Lankan exchange rate series was a nonlinear, asymetric shape ,nonstationary series with stochastic trend, I(1). The change in the logarithm of the daily exchange rate (Exchange rate return) series has fatter tails, serial dependence, volatility clustering and ARCH effects in both sample periods. During the period I, the exchange rate was depreciating, distribution was positively skewed , larger volatility (SD=3.4) , non normal and nonstationary. During the period II, exchange rate was appreciating, high persistent and skewed negatively. The changes of log exchange rate behave as normal with an autoregressive conditional heteroscedasticity process for innovations. The characteristics of the exchange rate changes indicates the presence of heterogeneity among market participants as well as changing parameters over time. Standard deviation of this distribution dominates the mean value. variance was also time varying. The results of this study has important implications for exchange rate determination, balance of payments, risk modeling and management, forecasting, market efficiency, statistical inference in empirical work and for the economy, as whole

Alternative methods to determine plot sizes for tree crops. a case study from coconut data

Two methodologies are pooposed to determine the most efficient plot size for tree crops using data from experiments based on randomized complete block designs. Both methods can be generalized for data from any balanced design. The merits and demerits of these methods are discussed. The methods are illustrated using the data sets of long-term field ecperiments at the Coconut Research Institute, Sri Lanka. The results show that efficient plot size in field experiments for coconut for a wide range of agroecological regions is four or six palms

An alternative model to estimate solar radiation

Solar radiation is extremely useful in modelling many agricultural applications, but is hardly used due to the difficulty in obtaining data, and the time consuming process in estimating it by the angstrom (1924) formula which uses world geographical relationships. To estimate solar radiation at the Coconut Research institute, Lunuwila (7o 20'N;71o 53'E;30.5m) an alternative model was developed from measured sunshine hours data only. The model had good fit (R2=0.90,P0.001) and was found to have agreement with the estimates obtained from the Angstrom model. The alternative model is more flexible and useful in estimating crop evapotranspiration, and for crop-weather modelling. The mean daily solar radiation at Lunuwila was estimated to be 18.3 MJ m-2d-1 and the total annual solar radiation receipts is 6680 MJ m-2 (66.8 TJ ha-1). The monthly solar radiation was highest in March (21.7MJ m-2 d-1) and the estimated 75 per cent probability value was 22.5 June had the lowest (16.1 MJ m-2 d-1) value and the estimated 75 per cent probability value was 17.8