Analysis of meteorological and climatic data allows
to provide near real-time information about the crop state, in quality
and quantity, with the possibility of early warning on alarm/alert
situations so that timely interventions can be planned and undertaken.
Crop forecasting philosophy is based on various kind of data collected
from different sources: meteorological data, agrometeorological
(phenology, yield), soil (water holding capacity), remotely sensed,
agricultural statistics. Based on meteorological and agronomic data,
several indices are derived which are deemed to be relevant variables
in determining crop yield, for instance crop water satisfaction,
surplus and excess moisture, average soil moisture, etc.
Crop forecasting is the art of predicting crop yields (tons/ha)
and production before the harvest actually takes place, typically
a couple of months in advance. Crop forecasting relies on computer
programmes that describe the plant-environment interactions in quantitative
terms. Such programmes are called "models",
and they attempt to simulate plant-weather-soil interactions. They
need, therefore, information and data on the most important factors
that affect crop yields - the model inputs. After
passing "through" the model, the inputs are converted
to a number of outputs, such as maps of crop conditions
Security Information for Action Programme|
This website provides access to Food Security related
information and resources produced by the EC-FAO Food Security
Information for Action Programme..
CROP FORECASTING is the art of predicting crop yields
(tons/ha) and production before the harvest actually takes place,
typically a couple of months in advance..
conditions by Region|
Conditions during various seasons. Yeald and precipitations
are mapped for different years. Data sources are NOAA and FAO. Maps are prepared
by FAO/NRCB, Agrometeorology Group.
Length of the
growing season by Region|
The length of the "growing season" or "growing period"
(LGS or LGP) is the period (in days) during a year when precipitation exceeds
half the potential evapotranspiration.
Weather and Crop Situation (GIEWS)|
food and agriculture for Africa (GIEWS)|
2006 - Remote
Sensing Support to Crop Yield Forecast and Area Estimates [PDF, 1,899 kb]|
Slide show on "An illustration of some non-parametric
yield forecasting applications in Zimbabwe".
2006 - Non-parametric
Crop Yield Forecasting, a Didactic case Study for Zimbabwe [PDF, 596 kb]|
Paper presented at the EU/JRC meeting on Remote Sensing
Support to Crop Yield Forecast and Area Estimates.
2006 - INSAM,
Agrometeorological forecasting [PDF, 1,387 kb]|
Agrometeorological forecasting covers all aspects of
forecasting in agrometeorology. Therefore, the scope of agrometeorological
forecasting very largely coincides with the scope of agrometeorology itself..
||2003 - Non-parametric
crop yield forecasting [345 kb]|
||2001 - Coordinating
role of FAO in developing tools and methods to support food-security activities in
National Agrometeorological Services [192 kb]|
||2001 - An
Introduction to the Art of Agrometeorological Crop Yield Forecasting
using Multiple Regression [408 kb]|
||2000 - Handbook for
defining and setting up a Food Security Information and Early Warning System [935 kb]|
||1998 - FAO
Crop Yield Forecasting Philosophy in National Food Early Warning Systems [166 kb]|
||1998 - Agrometeorological
Crop Yield Forecasting Methods [114 kb]|
||1998 - Agrometeorological
Models and Remote Sensing for crop Monitoring and Forecasting in Asia and
the Pacific [114 kb]|
||1996 - Crops
Weather and Satellites: Interfacing in the Jungle [116 kb]|
Weather Modelling [670 kb]|