文献类型： 外文期刊

作者： Che, Yingpu ¹ ; Gu, Yongzhe ¹ ; Bai, Dong ¹ ; Li, Delin ¹ ; Li, Jindong ¹ ; Zhao, Chaosen ⁴ ; Wang, Qiang ⁵ ; Qiu, Hongmei ⁶ ; Huang, Wen ⁷ ; Yang, Chunyan ⁸ ; Zhao, Qingsong ⁸ ; Liu, Like ⁹ ; Wang, Xing ¹⁰ ; Xing, Guangnan ¹¹ ; Hu, Guoyu ¹² ; Shan, Zhihui ¹³ ; Wang, Ruizhen ⁴ ; Li, Ying-hui ¹ ; Jin, Xiuliang ¹ ; Qiu, Li-juan ¹ ;

作者机构： 1.Chinese Acad Agr Sci, State Key Lab Crop Gene Resources & Breeding,Inst, Key Lab Grain Crop Genet Resources Evaluat & Utili, Natl Key Facil Crop Gene Resources & Genet Improve, Beijing 100081, Peoples R China

2.Chinese Acad Agr Sci, Natl Nanfan Res Inst Sanya, Sanya 572024, Peoples R China

3.HainanYazhou Bay Seed Lab, Sanya 572025, Peoples R China

4.Jiangxi Acad Agr Sci, Crops Res Inst, Nanchang Branch,Natl Ctr Oil Crops Improvement, Jiangxi Prov Key Lab Oil Crops Biol, Nanchang 330200, Peoples R China

5.Heilongjiang Acad Agr Sci, Inst Crop Resources, Harbin 150086, Peoples R China

6.Jilin Acad Agr Sci, Natl Engn Res Ctr Soybean, Soybean Res Inst, Changchun 130033, Peoples R China

7.Tong Hua Acad Agr Sci, Meihekou 135007, Peoples R China

8.Hebei Acad Agr & Forestry Sci, Inst Cereal & Oil Crops, Key Lab Crop Genet & Breeding, Shijiazhuang Branch,Ctr Natl Ctr Soybean Improveme, Shijiazhuang 050031, Peoples R China

9.Liaocheng Univ, Sch Life Sci, Liaocheng 252059, Peoples R China

10.Xuzhou Inst Agr Sci XuHuai Reg Jiangsu, Xuzhou 221131, Peoples R China

11.Nanjing Agr Univ, Key Lab Biol & Genet Improvement Soybean Gen, Natl Key Lab Crop Genet & Germplasm Enhancement, Minist Agr,Soybean Res Inst,Natl Ctr Soybean Impro, Nanjing 210095, Peoples R China

12.Anhui Acad Agr Sci, Crop Inst, Anhui Key Lab Crops Qual Improving, Hefei 230031, Peoples R China

13.Chinese Acad Agr Sci, Minist Agr, Oil Crops Res Inst, Key Lab Biol & Genet Improvement Oil Crops, Wuhan 430062, Peoples R China

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.