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| ==Analyzing trends== | ==Analyzing trends== | ||
| - | The method uses historical data on crop area and production for up to 30 years to fit a linear regression model with area or production of the crop as dependent variable and time as the independent variable. | + | An increase in crop yield from year to year may be explained by gradual improvements in technology, while other variables such as weather conditions, pests and diseases, input availability are all fairly constant or “under control”. |
| - | What this means basically is that the average yearly increase which was found over previous years is assumed to continue for future years. | + | |
| - | + | ||
| - | An increase in crop yield from year to year may be explained by gradual improvements in technology, while other variables such as weather conditions, pests and diseases, input availability are all fairly constant or “under control”. A gradual increase in crop area may be explained by new land clearing or a gradual replacement of one crop by an other (for example sorghum/ maize in East Africa). This very simple model does not take into consideration any specific events of the current year, either physical or economic factors. | + | |
| + | The factors which affect the variability of agricultural yields can roughly be grouped in three categories according to their variations over time: | ||
| + | * growing smoothly, such as more or less regular technology and management trends (i.e. mechanization, varieties, irrigation, and the farmers know-how), but growing more abruptly for several years in succession in the case of innovations. A typical innovation would be the new introduction of irrigation; | ||
| + | * discontinuous, like extreme factors of various origins and policy decisions which affect management (for instance, farmers may decide to use less fertilizer if it is no longer subsidized) or infrastructure, such as the construction of a road which provides access to new markets; | ||
| + | * pseudo-cyclic, like weather. The result may be a complex curve where it is often rather difficult to separate weather from other factors, particularly if weather itself is affected by a trend... In addition, the figure assumes that the function linking yield and the factors is known (a simple addition in this case). | ||
| + | {|"class=prettytable" cellpadding="15" border="1" style="border-collapse:collapse" | ||
| + | |width="225"| Some of the factors affecting agricultural yields (represented by a heavy red line: technology and management trends, innovation, policy, extreme factors and weather) | ||
| + | ||[[Image:graph54.jpg|400px|]] | ||
| + | |} | ||
Revision as of 10:47, 24 August 2006
Analyzing trends
An increase in crop yield from year to year may be explained by gradual improvements in technology, while other variables such as weather conditions, pests and diseases, input availability are all fairly constant or “under control”.
The factors which affect the variability of agricultural yields can roughly be grouped in three categories according to their variations over time:
- growing smoothly, such as more or less regular technology and management trends (i.e. mechanization, varieties, irrigation, and the farmers know-how), but growing more abruptly for several years in succession in the case of innovations. A typical innovation would be the new introduction of irrigation;
- discontinuous, like extreme factors of various origins and policy decisions which affect management (for instance, farmers may decide to use less fertilizer if it is no longer subsidized) or infrastructure, such as the construction of a road which provides access to new markets;
- pseudo-cyclic, like weather. The result may be a complex curve where it is often rather difficult to separate weather from other factors, particularly if weather itself is affected by a trend... In addition, the figure assumes that the function linking yield and the factors is known (a simple addition in this case).
Some of the factors affecting agricultural yields (represented by a heavy red line: technology and management trends, innovation, policy, extreme factors and weather) 
