Experimental dissection of phenotypic variation for quantitative disease resistance in canola (Brassica napus) -
Luke G Barrett1, Mohamed Cm Zakeel1, Angela P Van der Wouw2
1CSIRO Agriculture and Food, Canberra, ACT, Australia.
Background:
Quantitative resistance (QR) underpins durable control of blackleg caused by Leptosphaeria maculans in canola (Brassica napus), yet its reliable measurement under field conditions remains difficult. Although disease severity is hypothesized to arise from interacting effects of host genotype, pathogen population, environment and experimental structure, the relative importance of these sources of variation has not been explicitly partitioned. Here, we quantified the components shaping QR expression in the B. napus-L. maculans interaction and evaluated how replication influences power to detect small-to-moderate differences in QR.
Results:
Highly replicated outdoor pot experiments were conducted at three locations in southeastern Australia during 2021. Three canola cultivars lacking effective major-gene resistance were inoculated with four stubble-derived pathogen treatments approximating natural infection. Crown canker severity (CCS) was analyzed using mixed-effects models that partitioned biological and experimental sources of variation. Host genotype (32%) and location (27%) were the dominant contributors to structured variance, followed by genotype × environment interactions (11%). All remaining interaction terms among host, inoculum source, and environment were statistically significant, although they varied in magnitude. Residual and blocking effects together accounted for ~27% of total variance. Dispersion analyses further showed that cultivar and environment influenced the stability of disease responses independently of mean severity. Power simulations indicated that detecting modest QR differences requires substantially greater replication than is typical of many field experiments.
Conclusions:
The QR expression in the B. napus-L. maculans pathosystem is context-dependent and embedded within considerable environmental and residual variation. Reliable estimation of QR therefore requires appropriately powered phenotyping designs that account for biological and experimental sources of variation, particularly when results are intended to generalize across environments. © 2026 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
