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金秀良

 

姓  名:金秀良       性 别: 男 

职  称:研究员

联系电话:010-82105097      

电子邮箱:jinxiuliang@caas.cn       

个人网页:

课 题 组:作物表型

 

本人简历:

金秀良研究员, 中国农业科学院作物科学研究所作物栽培与耕作中心作物表型创新研究组组长。201512月至20192月,在法国农业科学院UMR-EMMAH, UMT-CAPTE从事博士后研究,20157月至201511月,在中国科学院东北地理与农业生态研究所从事农业遥感研究,任助理研究员,20119月至20156月,在扬州大学农学院作物栽培学与耕作学攻读博士学位,20089月至20116月,在石河子大学农学院作物栽培学与耕作学攻读硕士学位,20049月至20086月,在石河子大学农学院林学系攻读学士学位。

研究方向:

主要从事作物表型鉴定与精准农业研究,主要关注以下研究领域:(1)定量遥感在农业监测中的应用; 2)光学传感器的应用和开发; 3)作物表型平台的研究与应用; 4)作物模型和多源遥感的数据同化;5)多源图像数据的处理。

主要贡献:

  1. 首次提出利用无人机影像数据开展了小麦苗期植株密度估算研究
  2. 系统地开展了国内Aquacrop模型的模拟研究及其与多源遥感数据的数据同化研究
  3. 利用卫星和近地面影像数据对作物动态长势监测、产量和品质进行评估及应用研究
  4. 法国田间作物表型平台研发与应用

主要学术成就包括以第一作者或通讯作者共发表SCI文章23, 其中中科院SCI分区1区的文章8篇,2区的文章10篇,合作发表论文40余篇,文章主要发表在国际著名遥感杂志《Remote sensing of Environment》、《ISPRS Journal of Photogrammetry and Remote Sensing》和国际著名农业杂志《Agricultural and Forest Meteorology》、《European Journal of Agronomy》、《Field Crops Research》、《Agricultural Water Management》等,其中SCI高引和热点文章分别为2篇和1篇。

获奖成果和荣誉称号:

曾经获得过德国洪堡学者的资助,当前担任Agronomy journal 副主编(2019-2021/The Journal of Agricultural Science 副主编(2017-2020/Scientific Reports 编委(2017-2019/Remote Sensing-专刊 “Estimation of Crop Phenotyping Traits using Unmanned Ground Vehicle and Unmanned Aerial Vehicle Imagery” 客座编辑(2017-2018

在研的科研项目:

  1. 主持国家自然基金青年项目(2016-2019
  2. 主持中国农业科学院作物科学研究所青年英才项目(2019

主要代表论文:

  1. Jin, X. L.*, Li, Z. H. *, Nie, C. W., Xu, X. G., Feng, H. K., Wang, J. H., Guo, W. S.: Parameter sensitivity analysis of AquaCrop model based on the extended fourier amplitude sensitivity under different agro-meteorological conditions. Field Crops Research, 2018 226: 1-15.
  2. Liu, T., Li, R., Zhong, X.C.*, Jiang, M., Jin, X.L.*, Zhou, P., Liu, S.P., Sun, C.M.*, Guo, W.S*. Estimates of rice lodging using indices derived from UAV visible and thermal infrared images. Agricultural and Forest Meteorology, 2018, 252:144-154.
  3. Jin, X.L.*, Kumar, L., Li, Z. H., Feng, H. K., Xu, X. G., Yang, G. J., Wang, J. H. (2018): A review of data assimilation of remote sensing and crop models. European Journal of Agronomy, 2018, 92:141-152. (SCI 热点文章)
  4. Jin, X. L.*, Yang, G. J., Li, Z. H., Xu, X. G., Wang, J. H., Lan, Y. B. Estimation of water productivity in winter wheat using the AquaCrop model with field hyperspectral data. Precision Agriculture, 2018, 19: 1-17.
  5. Jin, X.L.*, Liu, S.Y., Baret, F., Hemerlé, M., Comar, A. Estimates of plant density of wheat crops at emergence from very low altitude UAV imagery. Remote Sensing of Environment, 2017, 198: 105-114. (SCI 高引文章)
  6. Jin, X. L., Song, K.S.*, Du, J., Liu, H.J., Wen, Z. D. Soil organic matter estimation based on simulated spectral configuration of different satellite sensors: optimal three band algorithms versus the PSO-SVM model. Agricultural and Forest Meteorology, 2017, 244-245:57-71.
  7. Jin, X. L.*, Yang, G. J*., Xue, X. Z., Li, Z. H., Xu, X. G., Feng, H. K. Validation of two Huanjing-1A/B satellite-based FAO-56 models for estimating winter wheat crop evapotranspiration during mid-season. Agricultural Water Management, 2017, 189: 27-38.
  8. Jin, X. L.*, Li, Z. H., Yang, G. J., Yang, H., Feng, H. K., Xu, X. G., Wang, J. H. Winter wheat yield estimation based on multi-source high-resolution optical and radar imagery and AquaCrop model using particle swarm optimization algorithm. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 126:24-37.
  9. Jin, X. L.*, Kumar, L., Li, Z. H., Xu, X. G., Yang, G. J., Wang, J. H. Estimation of Winter Wheat Biomass and Yield by Combining the AquaCrop Model and Field Hyperspectral Data. Remote Sensing, 2016, 8(12):1-15, DOI: 10.3390/rs8120972.
  10. Jin, X. L., Du, J., Liu, H. J., Wang, Z. M., Song, K. S. Remote estimation of soil organic matter content in the Sanjiang Plain, Northest China: the optimal band algorithm versus the GRA-ANN model. Agricultural and Forest Meteorology, 2016, 218-219: 250-260.
  11. Jin, X. L., Yang, G. J., Xu, X. G., Yang, H., Feng, H. H., Li, Z. H., Shen, J. X., Zhao, C. J., Lan, Y. B. (2015): Combined multi-temporal optical and radar parameters for estimating LAI and biomass in winter wheat using HJ and RADARSAR-2 data. Remote Sensing, 2015, 7: 13251-13272.
  12. Jin, X. L., Ma, J. H., Wen, Z. D., Song, K. S. Estimation of maize residue cover using Landsat-8 OLI image spectral information and textural features. Remote Sensing, 2015, 7: 14559 -14575.
  13. Jin, X. L., Yang, G. J., Tan, C. W., Zhao, C. J. Effects of nitrogen stress on the photosynthetic CO2 assimilation, chlorophyll fluorescence, and sugar-nitrogen ratio in corn.  Scientific Reports, 2015, 5: 9311.
  14. Jin, X. L., Diao, W. Y., Xiao, C. H., Wang, F. Y., Chen, B., Wang, K. R, Li, S. K. Estimation of wheat nitrogen status under drip irrigation with canopy spectral indices. Cambridge University Press Journal of Agricultural Science, 2015, 153:1281-1291.
  15. Jin, X. L., Feng, H. K., Li, Z. H., Song, S. N., Zhu, X. K., Song, X. Y., Yang, G. J., Xu, X. G., Guo, W. S. Assessment of the AquaCrop model for use in simulation of irrigated winter wheat canopy cover, biomass, and grain yield in the North China Plain. PLOS ONE, 2014, 9: e86938.
  16. Jin, X. L., Li, Z. H., Feng, H. K., Xu, X. G., Yang, G. J. Newly combined spectral indices to improve estimation of total leaf chlorophyll content in cotton.  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 4589-4600.
  17. Jin, X. L., Xu, X. G., Feng, H. K., Song, X. Y., Wang, Q., Wang, J. H., Guo, W. S. Estimating grain protein content in winter wheat by using three methods with hyperspectral data. International Journal of Agriculture and Biology, 2014, 16: 498-504. (SCI, IF=0.902, JCR=4)
  18. Jin, X. L., Diao, W. Y., Xiao, C. H., Wang, F. Y., Chen, B., Wang, K. R., Li, S. K. (2013): Estimation of wheat agronomic parameters using new spectral indices. PLoS ONE, 2013, 8: e72736.
  19. Jin, X. L., Xu, X. G., Song, X. Y., Li, Z. H., Wang, J. H., Guo, W. S. Estimation of leaf water content in winter wheat using grey relational analysis (GRA)-partial least squares (PLS) modeling with hyperspectral data. Agronomy journal, 2013, 105: 1385-1392.
  20. Jin, X. L., Wang, K. R., Xiao, C. H., Diao, W. Y., Wang, F. Y., Chen, B., Li, S. K. Comparison of two methods for estimation of leaf total chlorophyll content using remote sensing in wheat. Field Crops Research, 2012, 135: 24-29.
  21. Li, Z.H., Jin, X.L., Yang, G.J., Drummond, J., Yang, H., Clark, B., Li, Z.H., Zhao, C.J. (2018): Remote Sensing of Leaf and Canopy Nitrogen Status in Winter Wheat (Triticum aestivum L.) Based on N-PROSAIL Model. Remote Sensing, 2018, 10, 1463.
  22. Li, Z. H., Jin, X. L., Zhao, C. J., Wang, J. H., Xu, X. G., Yang, G. J., Li, C. J., Shen, J. X. Estimating wheat yield and quality by coupling the DSSAT-CERES model and proximal remote sensing. European Journal of Agronomy, 2015, 71: 53-62.
  23. Li, Z. H., Jin, X. L., Wang, J. H., Yang, G. J., Nie, C. W., Xu, X. G., Feng, H. K. Estimating winter wheat (Triticum aestivum) LAI and leaf chlorophyll content from canopy reflectance data by integrating agronomic prior knowledge with the PROSAIL model. International Journal of Remote Sensing, 2015, 36: 2634-2653.

 



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