A Practical Approach for Rapid Grading Cotton Verticillium Wilt Severity for Remote Sensing Monitoring

Abstract

Disease severity grading is a key prerequisite and major aspect of the integrated management of cotton Verticillium wilt (VW). However, the application of current VW severity grading methods requires an investigation into the disease status of all cotton leaves. It is time-consuming, unlinked to yield, and difficult to reflect the actual severity, especially when it comes to large-scale remote-sensing monitoring. We integrated the cotton VW progression mechanism exploring the potential of leaf VW severity in various leaf types at different layers of cotton to indicate yield loss. Based on all main stem leaves (MLs) in cotton leaf layers 1-3 and fruit branch leaves (FLs) in layers 1-5, we proposed a practical grading method for cotton VW linked to yield loss and suitable for remote sensing monitoring, termed the Eight-Position Grading method (EPG). The results indicated FL exhibited stronger correlation with yield compared to ML, and MLs in layers 1-3 and FLs in layers 1-5 effectively indicated yield loss due to VW. EPG was compared with the technical specifications for VW severity assessment in China (GB) and its associated grading methods, demonstrating performance with a 12% yield loss gradient while correcting overestimation in GB grading. The remote sensing applicability of EPG was theoretically validated using PROSPECT_D and mSCOPE. Field remote sensing experiment confirmed that EPG achieved preferable accuracies in estimating VW severity (R² = 0.76, RPD = 2.06) and demonstrated a strong correlation with yield (R² = 0.53). This study offers a simple and practical method for scientifically assessing VW severity and estimating yield loss.

Keywords: Cotton Verticillium wilt, Severity grading, Yield loss, remote sensing