| |
|
Use of airborne digital imaging to assess within-paddock variability in rice production Research Supervisor: Research Staff: Funding: Duration: Project Summary: Models used to estimate crop yield potential
and nutrient requirements often fail because they do
not account for "transient" causes of variability due
to, for example pests, competition with weeds and unexpected seasonal changes. Timely data
concerning crop variability is potentially useful for maintaining
the veracity of model predictions throughout the
season and for extending these models into predicting
the spatial variability of yield within a given field.
This project will examine the usefulness of
airborne multispectral imaging as a support tool for rice
crop management and for enhancing the predictive
utility of existing crop models |