Crop Forecasting by using Crop-Yield Weather Regression Model*

Working Paper
Subtitle: 
[Workshop on Regression Model Hand Note]

Crop production in Bangladesh is largely governed by the vagaries of nature. Climate is one of the key components influencing agricultural productivity and has never been stable. The effect of climate variability on agriculture is very significant (Virmani, 1987). Several studies (O’Toole and Jones, 1987; Oldeman, 1980; Satake and Yoshida, 1978) indicate that weather during cropping season strongly influences the crop growth and account for two-third (67%) of the variation in productivity while other factors account for only one-third (33%). 
 
Rice is grown in more diverse environmental condition than any other major food crop in the world. The different stages of growth and yields of crops are affected by weather fluctuations that deviate from optimum. Growth and yield of rice are affected by climate factors such as temperature, rainfall, hours of bright sunshine, evapotranspiration and solar radiation (Curry et al., 1990; Yoshida, 1978; 1981). Models for estimating and predicting crop yields require precise knowledge of yield weather relationship.
 
In spite of the adaptation of modern agricultural practices and plant protection measures, favorable weather condition is essential for good harvest. Each phase of agricultural activity from preparatory tillage to plant growth and harvest does have strong dependence for weather (Rahman, 2000a, b; Ahmed et al. 2000).
 
 

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Crop Forecasting by using Crop-Yield Weather Regression Model*287.5 KB
Date and language
Jan 2002
English
Personal Author
Other information
Pagination: 
26
Form: 
Web resource

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