Crop Models And Its Techniques
Agrometeoorological forecasting is also concerned with the assessment of current and expected crop performance. It utilizes the past and the present weather data and crop data to predict the crop performance in the future. These forecasts may be about the occurrence of some phonological events viz. Emergence, flowering, fruiting, maturity and harvesting etc or may be about the possible crop production. Of the agro meteorological forecasts in use. Probably the most important economically are the forecasts of crop yield. The impact of weather and climate on crop growth and yield can be represented by crop weather models.
A model in general is an equation or set of equations which represents the behavior of a system. There are many types of the models as follows.
1. Statistical empirical model: Actual mechanism of processes is not disclosed.
2. Mechanistic model: mechanism of the processes involved id discussed e.g. photosynthesis based model.
3. Static model: Time is not a factor.
4. Dynamic model:These models predict changes in crop status with time.
5. Deterministic model: In which a definite output is given e.g. NPK doses are applied and the definite yields are given out.
6. Stochastic model: The models are based on the probability of occurrence of some event or external variable. Probabilities are given out.
The statistical techniques used in designing the models are as follows:
1. Simple regression analysis
2. Simple correlation technique.
3. Curvilinear correlations techniques
4. Multiple regression analysis
5. Stepwise regression analysis
6. Fishers orthogonal polynomial techniques
7. Mallow’s Cp techniques.
8. Marko cham model.
Bar (1979) has tried to classify the basic types of crop weather models as follows:
1. Crop growth simulation models
2. Crop weather analysis models
3. Empirical statistical model