Verticillium wilt is one of the most critical cotton diseases, which is widely distributed in cotton-producing countries. However, the conventional method of verticillium wilt investigation is still manual, which has the disadvantages of subjectivity and low efficiency. In this research, an intelligent vision-based system was proposed to dynamically observe cotton verticillium wilt with high accuracy and high throughput. Firstly, a 3-coordinate motion platform was designed with the movement range 6,100 mm × 950 mm × 500 mm, and a specific control unit was adopted to achieve accurate movement and automatic imaging. Secondly, the verticillium wilt recognition was established based on 6 deep learning models, in which the VarifocalNet (VFNet) model had the best performance with a mean average precision (mAP) of 0.932. Meanwhile, deformable convolution, deformable region of interest pooling, and soft non-maximum suppression optimization methods were adopted to improve VFNet, and the mAP of the VFNet-Improved model improved by 1.8%. The precision–recall curves showed that VFNet-Improved was superior to VFNet for each category and had a better improvement effect on the ill leaf category than fine leaf. The regression results showed that the system measurement based on VFNet-Improved achieved high consistency with manual measurements. Finally, the user software was designed based on VFNet-Improved, and the dynamic observation results proved that this system was able to accurately investigate cotton verticillium wilt and quantify the prevalence rate of different resistant varieties. In conclusion, this study has demonstrated a novel intelligent system for the dynamic observation of cotton verticillium wilt on the seedbed, which provides a feasible and effective tool for cotton breeding and disease resistance research.

The severity of Verticillium wilt on cotton caused by defoliating strains of Verticillium dahliae has gradually increased and threatens production worldwide. Identification of the molecular components of leaf defoliation may increase cotton tolerance to V. dahliae. Ethylene, a major player in plant physiological processes, is often associated with senescence and defoliation of plants. We investigated the cotton–V. dahliae interaction with a focus on the role of ethylene in defoliation and defense against V. dahliae. Cotton plants inoculated with V. dahliae isolate V991, a defoliating strain, accumulated more ethylene and showed increased disease symptoms than those inoculated with a non-defoliating strain. In cotton with a transiently silenced ethylene synthesis gene (GhACOs) and signaling gene (GhEINs) during cotton–V. dahliae interaction, ethylene produced was derived from cotton and more ethylene increased cotton susceptibility and defoliation rate. Overexpression of AtCTR1, a negative regulator in ethylene signaling, in cotton reduced sensitivity to ethylene and increased plant resistance to V. dahliae. Collectively, the results indicated precise regulation of ethylene synthesis or signaling pathways improve cotton resistant to Verticillium wilt.

MicroRNAs (miRNAs) play essential roles in plant defense responses, although such roles have not been identified in cotton in response to the plant pathogenic fungus Verticillium dahliae. In this study, the functions of miR398b and its target genes in cotton-V. dahliae interaction were investigated. The transcript levels of miR398b were down-regulated by V. dahliae infection and miR398b overexpression in cotton made the plants more susceptible to V. dahliae. The results suggest that miR398b negatively regulates cotton resistance to V. dahliae. This may occur by miR398b repression of some CC-NBS-LRR genes via translational inhibition, interfering with defense responses and leading to cotton susceptibility to V. dahliae. Alternatively, miR398b may guide the cleavage of the mRNAs of GhCSD1, GhCSD2 and GhCCS, each of which functions in reactive oxygen species (ROS) regulation and homeostasis, thereby causing excessive ROS accumulation in miR398b-overexpressing plants in response to V. dahliae infection. This study suggests conserved and novel roles of miR398b in the cotton–V. dahliae interaction. These discoveries may be coupled with new strategies in cotton breeding programs to improve resistance to V. dahliae.