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| where b1 to b3 are the corresponding X coefficients. | where b1 to b3 are the corresponding X coefficients. | ||
| + | Using an example for Malawi, first it will be established which water balance parameters are good predictors for yield. Then the multiple linear regression will be performed. | ||
| {|"class=prettytable" cellpadding="15" border="1" style="border-collapse:collapse" | {|"class=prettytable" cellpadding="15" border="1" style="border-collapse:collapse" | ||
| - | |width="225"|Besides is a very simple example of a yield function in an area where yields are mainly conditioned by limited water supply, as is the case -by definition- in most semi-arid areas of the world. ||[[Image:graph80.jpg|400px|]] | + | |width="225"| ||[[Image:graph92.jpg|400px|]] |
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Revision as of 12:01, 15 September 2006
Calibrating Yield
The yield function is a statistically derived function relating the water balance parameters (which constitute the outputs of the water balance model) and the other factors (farm inputs, trend) or NDVI with station yield. Once this function has been established, it can be used for early crop yield forecasting.
Although many different equations are possible, the most widely used one is the outcome of a multiple linear regression procedure:
Y = a + b1X1 + b2X2 + b3X3where b1 to b3 are the corresponding X coefficients.
Using an example for Malawi, first it will be established which water balance parameters are good predictors for yield. Then the multiple linear regression will be performed.
