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2009 - 200912010 - 20161
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Subject: Agricultural Statistics × Author: KAU × Start date: 2000 ×
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    ThesisItemOpen Access
    Price forecast models for coconut and coconut oil
    (College of Horticulture, Vellanikkara, 2016) Indraji, K N; KAU; Laly, John C
    The study on “Price forecast models for coconut and coconut oil” was conducted to estimate seasonal variations in prices of coconut oil, copra and coconut, to evaluate different time series forecast models for prices of coconut oil, copra and coconut and to suggest suitable forecast models for Alappuzha, Kochi and Kozhikode markets. Time series data on monthly average prices of coconut oil and copra for Alappuzha, Kochi and Kozhikode markets from January 1990 to December 2015 and for coconut price at Alappuzha market from January 1998 to December 2015 were collected from Coconut Development Board (CDB), Kochi formed the database.Analysis of price pattern revealed that wide fluctuation exists in the prices of coconut oil and copra at Alappuzha, Kochi and Kozhikode markets and price of coconut at Alappuzha market. For coconut oil and copra price, the coefficient of variation was around 50 per cent indicating the instability in prices and a coefficient of variation of 37 per cent for coconut price showed that variability in price is lower than that of coconut oil and copra. Seasonal indices for the 12 months from January to December showed that December is the peak price month for coconut oil at Alappuzha and Kozhikode markets, whereas it is in January at Kochi. Lowest price is observed in May at Alappuzha and Kozhikode market, whereas, at Kochi it is in July. In all the three markets, September – February is the buoyant phase and price depression is during March - August. For copra, peak price is in December at Alappuzha and Kochi markets, whereas, it is in November at Kozhikode. Trough price for copra is in May in all the three markets. October to February is favourable for copra price in all the three markets, whereas, depressed phase is from March to September. For coconut, peak price at Alappuzha market is in December and the buoyant phase is from November to February. April is the low price month with depressed phase from March to October. During the summer months from March to May, harvest the coconuts as tender and increase the production of neera. Also, during March- September, where the price of coconut oil and copra is low, steps are to be taken to convert coconut into other value added products like desiccated coconut powder, virgin coconut oil, activated carbon etc. and to identify regular markets in major cities of India as also outside India. Different forecast models were fitted viz., Auto regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and exponential smoothing models (single, double, Holt-Winters’ additive and multiplicative) were fitted and compared for prices of coconut, coconut oil and copra in different market. Holt-Winters’ Multiplicative Seasonal (HWMS) model is the appropriate forecast model for price of coconut oil at Alappuzha and Kochi markets. At Kozhikode market, SARIMA(1,1,1)(1,0,1)12 and HWMS can be used. HWMS model is selected as the suitable forecast model for copra at all markets. ARIMA (0,1,1) model is suitable for forecasting price of coconut at Alappuzha market
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    ThesisItemOpen Access
    Yield prediction in cocoa (Theobrama cacao L)
    (College of Horticulture, Vellanikkara, 2009) Jayasree, K; KAU; Laly, john C
    The present investigation, “Yield prediction in Cocoa (Theobroma cacao L.)” was undertaken to determine the age at yield stabilization, to identify the optimum range for growth characters and early yield and to identify yield prediction models, if any, based on the growth characters and early yield of cocoa. For this purpose, the data were collected from a progeny trial of the Cadbury-KAU Co-operative Cocoa Research Project, Vellanikkara, pertaining to Forastero variety of cocoa, planted in 1989 under the shade of rubber. Individual plant data on girth (13 years), height (three years), spread (one year) and pod yield (12 years) of 660 plants were analyzed. Graphical method, correlation and regression analyses, analysis of variance, frequency distribution and 95% confidence interval were used. From graphical analyses, it was found that stabilized yield for the plant was obtained from sixth year after planting. Correlation studies established that girth is an important determining factor of yield potential of cocoa. Height in the early years has significant association with girth and yield of the plant. HD2 in the initial year of planting has clear influence on the yield of the plant upto age at yield stabilization. HD2 in the first and second year after planting have clear influence on the yield after stabilization year. Precocity has significant influence on total yield. No model could be obtained for predicting total yield of cocoa based on growth characters with reasonable predictability. There exists optimum for girth at different stages of plant growth and was derived from planting to 12 years after planting, for maximizing yield. The optimum ranges for seedling height and precocity, optimum combination of girth and height of seedlings and optimum combination of initial girth, initial height and precocity was derived, for maximizing yield.