Accurately estimate soybean growth stages from UAV imagery by accounting for spatial heterogeneity and climate factors across multiple environments

文献类型： 外文期刊

第一作者： Che, Yingpu

作者： Che, Yingpu;Gu, Yongzhe;Bai, Dong;Li, Delin;Li, Jindong;Li, Ying-hui;Jin, Xiuliang;Qiu, Li-juan;Che, Yingpu;Li, Jindong;Li, Ying-hui;Jin, Xiuliang;Qiu, Li-juan;Che, Yingpu;Zhao, Chaosen;Wang, Ruizhen;Wang, Qiang;Qiu, Hongmei;Huang, Wen;Yang, Chunyan;Zhao, Qingsong;Liu, Like;Wang, Xing;Xing, Guangnan;Hu, Guoyu;Shan, Zhihui

作者机构：

关键词： Soybean growth stages; Multi-environment trials; Photothermal accumulation area; Spatial heterogeneity; Unmanned aircraft vehicle

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：7.7； 五年影响因子：8.4 ）

ISSN： 0168-1699

年卷期： 2024 年 225 卷

页码：

收录情况： SCI

摘要： Multi-environment trials (METs) are widely used in soybean breeding to evaluate soybean cultivars' adaptability and performance in specific geographic regions. However, METs' reliability is affected by spatial and temporal variation in testing environments, requiring further knowledge to correct such changes. To improve METs' accuracy, the growth of 1303 soybean cultivars was accurately estimated by accounting for climatic effects and spatial heterogeneity using a linear mixed-effect model and a field spatial-correction model, respectively. The METs across 10 sites varied in climate and planting dates, spanning N16 degrees 41 ' 52 '' in latitude. A soybean growth and development monitoring algorithm was proposed based on the photothermal accumulation area (AUC(pt)) rather than using calendar dates to reduce the impact of planting dates variability and climate factors. The AUC(pt) correlates strongly with latitude of the above trial sites (r > 0.77). The proposed merit-based integrated filter decreases the influence of noise on photosynthetic vegetation (f(PV)) and non-photosynthetic vegetation (f(NPV)) more effectively than S-G filter and locally estimated scatterplot smoothing. The field spatial-correction model helped account for spatial heterogeneity with a better estimation accuracy (R-2 >= 0.62, RMSE <= 0.17). Broad-sense heritability (H-2) with the field spatial-correction model outperformed the models without the model by an average of 52 % across the entire aerial surveys. Model transferability was evaluated across Sanya and Nanchang. Rescaled shape models in Sanya (R-2 = 0.97) were consistent with the growth curve in Nanchang (R-2 = 0.89). Finally, the methodology's precision estimations of crop genotypes' growth dynamics under differing environments displayed potential applications in precision agriculture and selecting high-yielding and stable soybean germplasm resources in METs.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序