Full-time sequence assessment of okra seedling vigor under salt stress based on leaf area and leaf growth rate estimation using the YOLOv11-HSECal instance segmentation model

基于YOLOv11-HSECal实例分割模型,通过叶面积和叶片生长速率估算,对盐胁迫下秋葵幼苗活力进行全时序列评估

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Abstract

INTRODUCTION: With the growing severity of global salinization, assessing plant growth vitality under salt stress has become a critical aspect in agricultural research. METHODS: In this paper, a method for calculating the leaf area and leaf growth rate of okra based on the YOLOv11-HSECal model is proposed, which is used to evaluate the activity of okra at the seedling stage. A high-throughput, Full-Time Sequence Crop Germination Vigor Monitoring System was developed to automatically capture image data from seed germination to seedling growth stage, while maintaining stable temperature and lighting conditions. To address the limitations of the traditional YOLOv11-seg model, the YOLOv11-HSECal model was optimized by incorporating the HGNetv2 backbone, Slim-Neck feature fusion, and EMAttention mechanisms. RESULTS: These improvements led to a 1.1% increase in mAP50, a 0.6% reduction in FLOPs, and a 14.1% decrease in model parameters. Additionally, Merge and Cal modules were integrated for calculating the leaf area and growth rate of okra seedlings. Finally, through salt stress experiments, we assessed the effects of varying NaCl concentrations (CK, 10 mmol/L, 20 mmol/L, 30 mmol/L, 40 mmol/L, 50 mmol/L, and 60 mmol/L) on the leaf area and growth rate of okra seedlings, verifying the inhibitory effects of salt stress on seedling vitality. DISCUSSION: The results demonstrate that the YOLOv11-HSECal model efficiently and accurately evaluates okra seedling growth vitality under salt stress in a full-time monitoring manner, offering significant potential for broader applications. This work provides a novel solution for full-time plant growth monitoring and vitality assessment in smart agriculture and offers valuable insights into the impact of salt stress on crop growth.

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