Data from a three factor experiment carried out during two years were used to analyse the effects of drought, nitrogen and disease on light interception (IPAR) and radiation use efficiency (RUE) in winter wheat (Triticum aestivum L.). The factors in the experiment comprised four irrigation strategies including no irrigation, three nitrogen levels providing 67, 83 and 100% of the recommended nitrogen rate, and two strategies for control of leaf diseases (with and without fungicides). Light interception was estimated from weekly measurements of crop spectral reflectance. This method was compared with estimates derived from crop area index measured by plant samples or by using the LAI2000 instrument. There was a good correspondence between the different methods before anthesis, but an overestimation of light interception with the methods using crop area index after anthesis due to an increase in non-photosynthetic active leaf area. Irrigation increased both IPAR and RUE. The relative increase in IPAR for irrigation was greater than the relative increase in RUE in the first year, whereas they were of similar size in the second year. The differences between the years could be attributed to changes in timing of the drought relative to crop ontogenesis. Increasing nitrogen rate increased IPAR, but caused a small decrease in RUE in both years. This reduction in RUE with increasing nitrogen concentration in leaves was also found to be significant when disease levels and drought effects were included in a multiple linear regression. Fungicide application increased IPAR in both years, but RUE was only significantly reduced by disease in the first year, where mildew dominated the trial. The data were also used to estimate the coefficients of partitioning of dry matter to grains before and after anthesis. About 40% of dry matter produced before anthesis and about 60% after anthesis was estimated to contribute to grain yield. The low fraction after anthesis is probably due to the fact that it was not possible to estimate changes in RUE with time, which may lead to biases in the estimation of partitioning coefficients.