Abstract
A semi-deterministic model that allows assessment of groundnut yields from NOAA AVHRR data has been developed for the Peanut Basin in Senegal. Linear regression, using yield as the dependent variable and integrated NDVI during the reproductive period of the groundnuts, minus integrated NDVI during a period before the growing season as the independent variable, allowed 64% of the groundnut yield variance to be explained. This is comparable to similar studies concerned with other crops. Variable integration periods were used to account for variation in the temporal location of the reproductive periods. Compared to models using fixed integration periods this significantly increased both the level of explained yield variance and the interannual stability of the model. Pathfinder data were used to fill gaps in the time series of LAC data, using a linear transformation of Pathfinder NDVI values.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
