Infection Rate Thresholds Reveals Instability in Resistance to Sheath Rot Caused by Sarocladium oryzae in Rice Genotypes

Sheath rot caused by Sarocladium oryzae has emerged as a serious threat to rice production, and host resistance remains the most sustainable management strategy. However, whether moderately resistant genotypes maintain their stability under increasing disease pressure is not well understood. The present study was undertaken to identify resistant genotypes, quantify the effect of infection rate on resistance behavior in moderately resistant genotypes, and develop a binary classification model for predicting stable versus unstable resistance. One hundred three rice genotypes were evaluated under field conditions during the kharif seasons of 2019 and 2020, with disease severity recorded weekly to calculate area under the disease progress curve (AUDPC) and infection rate (r). Residual maximum likelihood (REML) analysis gave significant genotypic variance (σ²g = 120.42) and high heritability (H² = 97.78%). Of the 103 genotypes screened, four (TMRH-2110, UPLRH-179510, RRX-805, and Rasi) were resistant (R), 35 were moderately resistant (MR), 62 were susceptible (S), and two (IIRRH-146 and Pusa Basmati 1121) were highly susceptible (HS). MR genotypes had r like those of S genotypes. Binomial logistic regression identified a critical infection rate threshold (r = 0.073). Above this value, the probability of moving from MR to S exceeded 50%. The model had an area under the ROC (receiver operating characteristic) curve (AUC) of 0.63 (95% CI = 0.551 to 0.710). Sensitivity and specificity were 0.476 and 0.714, respectively. Several MR genotypes had r greater than threshold, were classified as potentially unstable. 'r' can signal resistance instability early. This study demonstrates that r may be serve as a quantitative predictor of resistance stability to sheath rot in rice and provides a preliminary threshold-based framework for identifying MR genotypes that are likely to remain stable or unstable under disease pressure. Adding this component to breeding programs improves selection over severity-based methods.