Quantification of the effects of Septoria tritici blotch on wheat leaf gas exchange with respect to lesion age, leaf number, and leaf nitrogen status

Quantification of the damaging effects of pathogens on diseased plants and inclusion of these damaging functions in crop simulation models is of great importance for a more complete understanding of yield response to diseases. In this study, the effect of Septoria tritici blotch (STB) on net photosynthetic and dark respiration rates of wheat flag leaves was quantified. Bastiaans' model: Y=(1-x)[superscript {szligbeta}] was used to characterize the relationship between relative leaf photosynthesis (Y, considering Y[subscript net] and Y[subscript gross]) and STB severity (with x the proportion of the diseased area). The value of {szligbeta} indicates whether the effect of disease on photosynthesis is larger ({szligbeta} >1), lower ({szligbeta} <1), or equal ({szligbeta} =1) to the proportion of visible diseased area. In the experimental conditions used here, leaf nitrogen content (in a range from 0.18 to 0.24 mg cm⁻²), and leaf number (flag and second leaves) did not significantly influence the effect of STB on leaf gas exchange. By contrast, damage depended strongly on the developmental stages of the STB lesions. STB lesions had no effect on inoculated leaves before visible symptoms appeared. Chlorotic symptoms had less effect on leaf net photosynthetic rate than could be accounted for by the visible diseased area ({szligbeta}[subscript net]=0.81). The effect of necrotic lesions on the leaf net photosynthetic capacity was slightly greater than that accounted for by visible symptoms ({szligbeta}[subscript net]=1.35). Our results suggest that the effect of the necrotic symptoms on the net photosynthesis expressed by {szligbeta}[subscript net] >1 is due to a combination of a decrease in the gross photosynthesis ({szligbeta}[subscript gross] still >1) and to an increase in the dark respiration rate ({szligbeta}[subscript gross]<{szligbeta}[subscript net]). Finally, it is discussed how the results could improve the prediction of crop loss caused by an STB epidemic in wheat fields.