Suppr超能文献

基于使用YOLOv11-HSECal实例分割模型估计叶面积和叶片生长速率的盐胁迫下秋葵幼苗活力的全时序列评估。

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.

作者信息

Cao Xiaowei, Li Yifan, Zhang Yaben, Zhong Zhibo, Bai Ruxiao, Yang Peng, Pan Feng, Fu Xiuqing

机构信息

College of Engineering, Nanjing Agricultural University, Nanjing, China.

Institute of Farmland Water Conservancy and Soil-Fertilizer, Xinjiang Academy of Agricultural Reclamation Science, Shihezi, Xinjiang, China.

出版信息

Front Plant Sci. 2025 Aug 14;16:1625154. doi: 10.3389/fpls.2025.1625154. eCollection 2025.

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.

摘要

引言

随着全球盐碱化问题日益严重,评估盐胁迫下植物的生长活力已成为农业研究的关键环节。

方法

本文提出一种基于YOLOv11-HSECal模型计算秋葵叶面积和叶片生长速率的方法,用于评估秋葵幼苗期的活性。开发了一种高通量、全时段序列作物发芽活力监测系统,以在保持稳定温度和光照条件的同时,自动采集从种子萌发到幼苗生长阶段的图像数据。为解决传统YOLOv11-seg模型的局限性,通过整合HGNetv2主干、Slim-Neck特征融合和EMAttention机制对YOLOv11-HSECal模型进行了优化。

结果

这些改进使mAP50提高了1.1%,FLOPs降低了0.6%,模型参数减少了14.1%。此外,还集成了合并和计算模块来计算秋葵幼苗的叶面积和生长速率。最后,通过盐胁迫实验,评估了不同NaCl浓度(CK、10 mmol/L、20 mmol/L、30 mmol/L、40 mmol/L、50 mmol/L和60 mmol/L)对秋葵幼苗叶面积和生长速率的影响,验证了盐胁迫对幼苗活力的抑制作用。

讨论

结果表明,YOLOv11-HSECal模型以全时段监测方式高效、准确地评估了盐胁迫下秋葵幼苗的生长活力,具有广阔的应用潜力。这项工作为智能农业中的全时段植物生长监测和活力评估提供了一种新的解决方案,并为盐胁迫对作物生长的影响提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f4/12391126/1201bcb2301e/fpls-16-1625154-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验