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基于卷积神经网络和合成数据集训练鉴定棉花种子萌发期的耐盐性

王勇攀 杨洋 高文伟 马君 李晨宇 姚梦瑶 王子轩 黄灵芝 朱海艳 刘皖蓉 李波

新疆农业科学2025,Vol.62Issue(2):261-269,9.
新疆农业科学2025,Vol.62Issue(2):261-269,9.DOI:10.6048/j.issn.1001-4330.2025.02.001

基于卷积神经网络和合成数据集训练鉴定棉花种子萌发期的耐盐性

Salt tolerance in germination period of cotton seeds based on convolutional neural network and synthetic dataset

王勇攀 1杨洋 2高文伟 3马君 4李晨宇 1姚梦瑶 1王子轩 1黄灵芝 3朱海艳 3刘皖蓉 2李波2

作者信息

  • 1. 新疆农业大学农学院,乌鲁木齐 830091||新疆农作物生物技术重点实验室/新疆农业科学院核技术生物技术研究所,乌鲁木齐 830091
  • 2. 新疆农作物生物技术重点实验室/新疆农业科学院核技术生物技术研究所,乌鲁木齐 830091
  • 3. 新疆农业大学农学院,乌鲁木齐 830091
  • 4. 新疆农业科学院经济作物研究所,乌鲁木齐 830091
  • 折叠

摘要

Abstract

[Objective]To establish a convenient and accurate non-destructive detection method for cot-ton seed germination phenotypes,so as to characterize the salt tolerance of different cotton germplasm at the germination stage.[Methods]A synthetic dataset was generated using 150 images of cotton seed germination at different stages and used to train the Mask R-CNN model.Using the trained model,we performed instance segmentation and feature extraction of seed shell and germ in real-world images of 60 cotton germplasm that germinated under 125 mmol/L NaCl treatment,and used them to infer the seed germination rate,germination potential,and germination length,so as to evaluate the salt tolerance of these 60 cotton germplasm in the ger-mination stage.[Results]The generated synthetic dataset contained 2,000 images and corresponding mask data.The accuracy of the Mask R-CNN model trained based on this dataset for the segmentation of seed shells and germs in real images was above 95%,and the phenotypic values that inferred by model were highly consistent with them measured by manual operation(R2>0.98,P<0.001),indicating that the phenotypes could be accurately obtained using the model.The cluster analysis of the salt tolerance index for each trait classified the 60 cotton materials into four levels;using the affiliation function method for a comprehensive e-valuation of the salt tolerance of the cotton varieties.Kezimian 4(0.95),MC-30(0.88),and Lu8zao(0.81)had a larger D-value and indicated high salt tolerance.[Conclusion]In this study,we have estab-lished a method for phenotyping cotton seed germination traits based on the convolutional neural network model that trained by using synthetic dataset.and using this method,we have identified the seed germination salt tol-erance of 60 cotton germplasm in a non-destructive,rapid and accurate manner.

关键词

棉花/卷积神经网络/图像分割/种子萌发

Key words

cotton/convolutional neural network/image segmentation/seed germination

引用本文复制引用

王勇攀,杨洋,高文伟,马君,李晨宇,姚梦瑶,王子轩,黄灵芝,朱海艳,刘皖蓉,李波..基于卷积神经网络和合成数据集训练鉴定棉花种子萌发期的耐盐性[J].新疆农业科学,2025,62(2):261-269,9.

基金项目

国家自然科学基金项目(32060497) Project of National Natural Science Foundation of China(32060497) (32060497)

新疆农业科学

OA北大核心

1001-4330

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