| 姓名: 马韫韬 |
| 性别: 女 | |
| 职称: 教授/博士生导师 | |
| 职务: 无 | |
| Email: yuntao.ma@cau.edu.cn | |
| 办公电话: 无 | |
| 办公地址: 太阳成集团tyc234cc楼375室 |
教育背景
1996.09-2000.07 中国农业大学 计算机及应用数学系 本科 理学学士
2000.09-2006.12 中国农业大学 资源与环境学院 土壤学 硕博连读 农学博士
工作履历
2007.02-2009.02 中国科学院自动化研究所信息化 博士后
2009.02-至今 中国农业大学资源与环境学院 讲师、副教授、教授
其中：2004.12-2005.02 法国国家计算机科学与控制研究所(INRIA) 访问学者
2007.03-2008.04 荷兰Wageningen大学 博士后
2008.01巴黎中央大学(ECP) 访问学者
2016.03-2017.03加州大学戴维斯分校 访问学者
2019.01-至今 农业人工智能与作物表型内蒙古自治区工程研究中心 副主任 首席科学家
学术兼职
现代农业产业技术体系北京市创新团队岗位科学家（2022-至今）
中国自动化学会智慧生态专委会（筹） 副主任（2022-至今）
国际植物生长建模、仿真与数字孪生（PMA/FSPM）委员会 常务理事（2020-至今）
中国农业生物技术学会植物表型组学专业委员会首批常务委员（2017-至今）
作物学会智慧农业专业委员会首批委员（2022-至今）
农业建模与仿真专业委员会首批委员（2019-至今）
CCF中国计算机学会数字农业分会首批委员（2021-至今）
研究领域
1. 植物三维仿真与数字孪生
2. 基于机器视觉的植物生长信息的数据挖掘与应用
3. 人工智能与智慧农业
4. 无人机大规模育种性状快速调查
5. 多源传感器的研发及数字农业应用
6. 大规模三维场景的快速获取与渲染
奖励与荣誉
植物生长的三维建模仿真及其在数字农业中的应用，教育部自然科学二等奖，2022
智慧农业全产业链关键共性技术研究与综合服务平台建设与示范，内蒙古自治区科学技术进步奖，2023，二等奖
北京农业科技大讲堂服务体系建设与应用，北京市农业技术推广奖，2022
北京市优秀研究生毕业生指导教师奖（2020）
中国农业大学优秀班主任（2013）
第十届北京青年学术演讲比赛（决赛）优秀奖（2010年）
中国农业大学十佳博士论文（2006年）
首届全国博士生学术论坛唯一农业院校代表（2003年）
北京市优秀毕业生（2000年）
主持项目
1. 国家自然科学基金项目 “基于三维激光多光谱时序数据的甜菜褐斑病精准监测与机理模型预测”(NO. 32271987，2023.1-2026.12) 项目主持
2. 现代农业产业技术体系北京市创新团队“植物体征数字化获取技术熟化与应用”岗位科学家项目 (NO. BAIC10-2023-E05，2022.1-2026.12) 项目主持
3. 科技部重点专项日"日光温室数字化管理及小型成套作业装备创制与应用"(2023.12-2028-11) 课题主持
4. 国家自然科学基金项目 "小麦灌浆特性光谱响应机理与多尺度遥感监测" (NO. 42271319， 2023.1-2026.12) 课题主持
5. 科技部重点专项 "大田环境作物信息传感器与表型平台创制" (NO. 2021YFD2000103， 2021.12-2026.11) 骨干
6. 中央引导地方科技发展资金 "呼伦贝尔地区主要农作物智慧种植系统应用与示范"(NO. 2022ZY0128-01，2022.7-2023.12) 项目主持
7. 省、市、自治区科技项目"黑土地指纹库与基于土地承载力的黑土健康与保育耕作模式"(NO. 2022YFDZ0093-01，2022.6-2025.6) 项目主持
8. 省、市、自治区科技重大项目"内蒙古地区主要农作物人工智能关键技术研究与产品应用示范" (NO. 2019ZD024，2019.01-2022.10) 项目主持
9. 省、市、自治区科技项目"基于营养诊断的减肥减药黑土地保护性耕作新模式" (2021.1-2023.12) 课题主持
10. 省、市、自治区科技项目"现代化农牧场智慧农业综合服务平台研究与应用" (NO. 2021GG0305-01，2021.1-2023.12) 课题主持
11. 省、市、自治区科技成果转化重大项目 "甜菜精准农业服务体系的应用、示范与推广"(NO. 2019CG093，2020.01-2022.12) 课题主持
12. 省、市、自治区科技项目"基于机器学习的马铃薯氮素实时管理技术研发与应用" (NO. 2020GG00038，2020.6-2023.05) 课题主持
13. 云南省烟草公司科技计划项目"2017YN07云南烟用有机肥养分资源利用研究" (2017.07-2019.12.31) 项目骨干
14. 国家重点研发计划"物种多样性和遗传多样性间套作地上和地下作物功能与结构模型" (2016YFD0300202，2016.01-2020.12) 项目骨干
15. 国土资源部公益性行业科研专项"内蒙古宜耕沙地调查和评价关键技术研究"(201411009，2014-2016) 20万 项目骨干
16. 国家自然科学基金-国际（地区）合作与交流项目"间套作增产和提高资源利用效率的机理" (31210103906，2013.01-2017.12.31) 项目骨干
17. 国家自然科学基金项目"间作系统潜在生产力差异的3D模型解析" (31000671，2011.01-2013.12) 20万 主持
学术成果
一、发表文章：
2023年:
1. Xiao SF, Ye YL, Fei SP, Chen HC, Zhang BY, Li Q, Cai ZB, Che YP, Wang Q, Ghafoor A, Bi KY, Shao K, Wang RL, Guo Y, Li BG, Zhang R, Chen Z, Ma YT*.High-throughput calculation of rgan-scale traits with reconstructed accurate 3D canopy structures using a UAV RGB camera with an advanced cross-circling oblique route. ISPRS Journal of Photogrammetry and Remote Sensing. 2023(201) :104–122(IF=12.2)
2. Fei SP, XU DM, Chen Z, Xiao YG*, Ma YT*. MLR-based feature splitting egression for estimating plant traits using high-dimensional hyperspectral reflectance data. Field Crops Research. 2023, https://doi.org/10.1016/j.fcr.2023.108855(IF=6.145)
3. Xiao SF, Fei SP, li Q, Zhang BY, Chen HC, Xu DM, Cai ZB, Bi KY, Guo Y, Li BG, Chen Z, Ma YT*. The importance of using realistic 3D canopy models to calculate light interception in the field. Plant Phenomics. 2023:5;0082.DOI:10.34133/plantphenomics.0082, (IF = 6.961)
4. Che YP, Wang Q, Xie ZW, Li SL, Zhu JY, Li BG, Ma YT*. High-quality images and data augmentation based on inverse projection transformation significantly improve the estimation accuracy of biomass and leaf area index. Computers and Electronics in Agriculture. 2023, 212: 108144. https://doi.org/10.1016/j.compag.2023.108144 (IF=8.3)
5. Shu MY, Zhu JY, Yang XH, Gu XH, Li BG, Ma YT. A spectral decomposition method for estimating leaf nitrogen status of maize by UAV-based hyperspectral imaging. Computers and Electronics in Agriculture, 2023, 212: 108100 (IF=8.3)
6. Shu MY, Li Q, Ghafoor A, Zhu JY, Li BG, Ma YT. Using the plant height and canopy coverage to estimation maize aboveground biomass with UAV digital images[J]. European Journal of Agronomy, 2023, 151: 126957.(IF= 5.722)
7. Shu MY, Bai K, Meng L, Yang XH, Li BG, Ma YT. Assessing maize lodging severity using multitemporal UAV-based digital images. European Journal of Agronomy, 2023, 144:126754
2022年：
1. Shu MY, Dong QZ, Fei SP, Yang XH, Zhu JY, Meng L, Li BG, Ma YT*. Improved estimation of canopy water status in maize using UAV-based digital and hyperspectral images. Computers and Electronics in Agriculture. 2022, https://doi.org/10.1016/j.compag.2022.106982(IF = 6.757)
2. Shu MY, Shen MY, Dong QZ, Yang XH, Li BG, Ma YT*. Estimating the maize above-ground biomass by constructing the tridimensional concept model based on UAV-based digital and multi-spectral images. Field Crops Research, 2022, 282, https://doi.org/10.1016/j.fcr.2022.108491 (IF：6.145)
3. Che YP, Wang Q, Zhou L, Wang XQ, Li BG, Ma YT*. The effect of growth stage and plant counting accuracy of maize inbred lines on LAI and biomass prediction. Precision Agriculture. 2022: 1-27. https://doi.org/10.1007/s11119-022-09915-1(IF = 5.767)
4. Xie ZW, Chen S, Gao GZ, Li H, Wu XM, Meng L, Ma YT*. Evaluation of rapeseed flowering dynamics for different genotypes with UAV platform and machine learning algorithm. Precision Agriculture. 2022: 1-19. https://doi.org/10.1007/s11119-022-09904-4(IF = 5.767)
5. Wang Q, Che YP, Shao K, Zhu JY, Wang RL, Sui Y, Guo Y, Li BG, Meng L, Ma YT*. Estimation of sugar content in sugar beet root based on UAV multi-sensor data. Computers and Electronics in Agriculture, 2022, 203.(IF = 6.757)
6. Shu MY, Fei SP, Zhang BY, Yang XH, Guo Y, Li BG, Ma YT*. Application of UAV Multisensor Data and Ensemble Approach for High-Throughput Estimation of Maize Phenotyping Traits. Plant Phenomics, 2022, https://doi.org/10.34133/2022/9802585(IF：6.961)
7. Shu MY, Zhou L, Chen HC, Wang XQ, Meng L, Ma YT*. Estimation of Amino Acid Content in Maize Leaves based on Hyperspectral Imaging. Frontiers in Plant Science. 2022, https://www.frontiersin.org/articles/10.3389/fpls.2022.885794/full(IF = 6.672)
8. Liu Y, Zhang G, Shao K, Xiao S, Wang Q, Zhu J, Wang R, Meng L, Ma YT*. Segmentation of Individual Leaves of Field Grown Sugar Beet Plant Based on 3D Point Cloud. Agronomy. 2022, 12, 893. https://doi.org/10.3390/ agronomy12040893
9. 钟培阁,周也莹,张彦,石屹,郭焱,李保国,马韫韬.基于标志点法的烟草叶形提取与判别[J].浙江大学学报(农业与生命科学版),2022,48(04):533-542.
10. 李双伟,朱俊奇,Jochem B.EVERS,Wopke VAN DER WERF,郭焱,李保国,马韫韬.基于植物功能-结构模型的玉米-大豆条带间作光截获行间差异研究[J].智慧农业(中英文),2022,4(01):97-109.
2021年:
11. Xiao SF, Chai HH, Wang Q, Shao K, Meng L, Wang RL, Li BG, Ma YT*. Estimating economic benefit of sugar beet based on three-dimensional computer vision: a case study in Inner Mongolia, China. European Journal of Agronomy. 2021. https://doi.org/10.1016/j.eja.2021.126378 (IF= 5.722)
12. Li SW, van der Werf W, Zhu JQ, Guo Y, Li BG, Ma YT*, Evers JB. Estimating the contribution of plant traits to light partitioning in simultaneous maize/soybean intercropping. Journal of Experimental Botany. 2021, 72(10) , doi.org/10.1093/jxb/erab077.(IF：7.298)
13. Shu MY, Shen MY, Zuo JY, Yin PF, Wang M, Xie ZW, Tang JH, Wang RL, Li BG, Yang XH, Ma YT*. The Application of UAV-Based Hyperspectral Imaging to Estimate Crop Traits in Maize Inbred Lines. Plant Phenomics. 2021. https://doi.org/10.34133/2021/9890745(IF：6.961)
14. Shu MY, Zuo JY, Shen MY, Yin PF, Wang M, Yang XH, Tang JH, Li BG, Ma YT*. Improving the estimation accuracy of SPAD values for maize leaves by removing UAV hyperspectral image backgrounds. International Journal of Remote Sensing, 2021. https://doi.org/10.1080/01431161.2021.1931539
15. Hui F, Xie ZW, Li HG, Guo Y, Li BG, Liu YL, Ma YT*. Image-based root phenotyping for field-grown crops: An example under maize/soybean intercropping. Journal of Integrative Agriculture. 2021, 20(0): 2-15
16. 束美艳, 李世林, 魏家玺, 车荧璞, 李保国, 马韫韬*. 基于无人机平台的柑橘树冠信息提取. 农业工程学报, 2021, 37(1): 68-76.
17. 束美艳, 陈向阳, 王喜庆*, 马韫韬*. 基于高光谱数据的玉米叶面积指数和生物量评估. 智慧农业. 2021(3): 29-39.
18. 车荧璞, 王庆, 李世林, 李保国, 马韫韬*. 基于超分辨率重建和多模态数据融合的玉米表型性状监测. 农业工程学报, 2021, 37(20): 169-178.
19. 王庆, 车荧璞, 柴宏红, 邵科, 于超, 李保国, 马韫韬*. 基于无人机影像的冠层光谱和结构特征监测甜菜长势. 农业工程学报, 2021, 37(20): 90-98.
20. 王庆, 车荧璞, 柴宏红, 邵科, 李保国, 马韫韬*. 基于无人机可见光与激光雷达的甜菜株高定量评估.农业机械学报,2021,52(3):178-184.
2020年:
1. Xiao SF, Chai HH, Shao K, Shen MY, Wang Q, Wang RL, Sui Y, Ma YT*. Image-Based Dynamic Quantification of Aboveground Structure of Sugar Beet in Field. Remote Sensing, 2020, 12: 269-285(IF：5.349)
2. Liu YL, Cen CJ, Che YP, Ke R, Ma Y, Ma YT*. Detection of Maize Tassels from UAV RGB Imagery with Faster R-CNN. Remote Sensing, 2020, 12: 338-350(IF：5.349)
3. Zhu BL, Liu FS, Xie ZW, Guo Y, Li BG, Ma YT*. Quantification of light interception within image-based 3D reconstruction of sole and intercropped canopies over the entire growth season. Annals of Botany, 2020, 126: 701-712(IF：5.040)
4. Che YP, Wang Q, Xie ZW, Zhou L, Li SW, Hui F, Wang XQ, Li BG, Ma YT*. Estimation of maize plant height andleaf area index dynamic using unmanned aerial vehicle with oblique and nadir photography. Annals of Botany, 2020, 126: 765-773(IF：5.040)
5. 柴宏红, 邵科, 于超, 邵金旺, 王瑞利, 随洋, 白凯, 刘云玲, 马韫韬*. 甜菜根三维表型参数提取与根型判别. 农业工程学报, 2020, 36(10) 181-188
6. Li SW, Evers JB, van der Werf W, Wang RL, Xu ZL, Guo Y, Li BG, Ma YT*. Plant architectural responses in simultaneous maize/soybean strip intercropping do not lead to a yield advantage. Annals of Applied Biology, 2020, 177, 195-210.(IF：2.766/Q2)
2019年：
1. Chai HH, Shao K, Hui F, Wang RL, Ma YT*. Revealing the relationship between biomass, sugar content and image-based phenotyping in beetroot. 6th International Plant Phenotyping Symposium (IPPS 2019). Oral
2018年:
1. Ma YT*, Chen YJ, Zhu JY, Meng L, Guo Y, Li BG, Hoogenboom G. Coupling individual kernel filling process with source-sink interactions into GREENLAB-MAIZE. Annals of Botany, 2018, 121(5): 961-973. (IF：5.040)
2. Hui F, Zhu JY*, Hu PC, Meng L, Zhu BL, Guo Y, Li BG, Ma YT*. Image-based dynamic quantification and high-accuracy 3D evaluation for of canopy structure of plant populations. Annals of Botany, 2018, 121(5): 1079-1088.(IF：5.040)
3. Zhu BL, Che YP, Hui F, Ma YT*. Three-Dimensional Quantification of Field Grown Crops by ground and aerial photography. 6th IEEE International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA18). 2018, Nov 4-8, in Hefei, Anhui province, China (EI)
4. Hui F, Guo Y, Ma YT*. Quantification of differences in root system architecture under maize/soybean interspecific interactions. 6th IEEE International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA18). 2018, Nov 4-8, in Hefei, Anhui province, China (EI).
5. 朱冰琳, 刘扶桑, 朱晋宇, 郭焱, 马韫韬*. 基于机器视觉的大田植株生长动态的三维定量化研究. 农业机械学报, 2018 (05):1-10.
2017年:
1. Cao BS，Shan H，Ma YT，Li BG, Sun CQ. Simulating Rice Growth of Different Genotypes at Two Latitudes. Agronomy Journal. 2017, 109(6). DOI:10.2134/agronj2017.03.0145
2016年：
1. 惠放, 马韫韬, 朱晋宇, 蒋卫杰. 利用多视角图像法分析番茄幼苗根构型对氮水平的响应. 植物营养与肥料学报, 2016, 22(5): 1418-1424.
2. 徐照丽, 孙艳, 吴茜, 惠放, 郭焱, 杨宇虹, 马韫韬*. 烟草功能-结构模型GreenLab-Tobacco的构建.中国烟草学报, 2016, 22(3): 52-59.
3. Li SW, Xu YF, Qiu C, Zhu JQ, Evers JB, Guo Y, Li BG, Ma YT*. Modelling the architectural responses of individual plants in maize/soybean intercropping system. International conferences on FSPMA, Oral. 2016.
4. Cao BS, Hua S, Ma YT, Sun CQ, Chen Y, Li BG*. Evaluation of ORYZA 2000 model for three rice cultivars with contrasting plant achitecture under two regions in china. International conference on functional-structural plant growth modeling, simulation, visualization and application(FSPMA), Poster. 2016.
5. Hui F, Hu PC, Guo Y, Zhu JY and Ma YT*. Dynamic capture of three-dimensional plant architecture based on multi-view photographed image sequences. International conferences on FSPMA, Poster. 2016.
2015年：
1. 朱晋宇, 惠放, 李苗, 马韫韬, 余宏军, 蒋卫杰. 氮水平对盆栽沙培番茄苗期根系三维构型与氮素利用的影响. 农业工程学报, 2015, (23): 131-137.
2. 胡鹏程, 郭焱, 李保国, 朱晋宇, 马韫韬*. 基于多视角立体视觉的植株三维重建与精度评估. 农业工程学报, 2015, 31(11): 209-214.
3. Ren ST, L XH, Li BG, Zhu JY, Ma YT*. Simulation and analysis of light availability difference for inter-rows of subordinate crop within strip-intercropping system. Transactions of the Chinese Society of Agricultural Engineering, 2015, S2: 246-255.
5. Chen YJ, Li SW, Hoogenboom G, Guo Y, Li BG, Ma YT*. Simulation of maize kernel growth using source-sink approach with priority function. Transactions of the Chinese Society of Agricultural Engineering, 2015, S2: 152-158.
2013年：
1. Chen YJ, Hoogenboom G, Ma YT, Li BG, Guo Y. Maize kernel growth at different floret positions of the ear. Field crop research, 2013, 149: 177-186.
2012年：
1. Wubs A M，Ma YT, Heuvelink E, Hemerik L, Marcelis LFM. Model selection for nondestructive quantification of fruit growth in pepper. Journal of the American Society for Horticultural Science. 2012. 137(2):71-79
2011年：
1. Ma YT*, Wubs A M, Mathieu A, Heuvelink E, Zhu JY, Hu BG, Courne`de P H and de Reffye P. Simulation of fruit-set and trophic competition and optimization of yield advantages in six Capsicum cultivars using functional-structural plant modelling. Annals of Botany, 2011, 107: 793-803.
2. 郑邦友, 马韫韬, 李保国, 郭焱, 邓启云. 基于三维模型评估全球变暗效应对水稻光合生产的影响. 中国科学, 2011, 41(3): 386-393.
3. Zheng BY, Ma YT, Li BG, Guo Y, Deng QY. Assessment of the influence of global dimming on the photosynthetic production of rice based on three-dimensional modeling. Science China Earth Sciences, 2011, 54, 290-297.
2010年:
1. 马韫韬, 朱晋宇, 胡包钢, Heuvelink E, de Reffye P.生态学报, 2010, 30(24): 7072-7078.
2. Qi R, Ma YT, Hu BG, de reffye P, COURNèDE PH. Optimization of source-sink dynamics in plant growth for ideotype breeding: a case study on maize. Computers and Electronics in Agriculture, 2010, 71(1): 96-105.
3. Ma YT, Wang CY, Zheng BY, Buck-Sorlin, GH, Li, BG, Wang, ZL. Assessment of light capture and carbon gain of two wheat canopies with 3-D modelling. In: Information Science and Technology (ICIST 2011) 2010, pp1312–1317. Nanjing, Jiangsu, China, IEEE.
4. Ma YT, Liu J, Zheng BY, Li BG, Guo Y. Assessment of light capture and carbon gain for maize/soybean intercropping with 3-D modelling. Proceedings of the 6th International Workshop on Functional-Structural Plant Models, 12-17, Nov, Davis USA. 2010. (Oral presentation).
5. Chen Y, Guo Y, Ma YT*. A source-sink model on individual kernel growth for field grown maize. Proceedings of the 6th International Workshop on Functional-Structural Plant Models, 12-17, Nov, Davis USA. 2010. (Oral presentation).
2009年:
1. Wubs AM, Ma YT*, Hemerik L, Heuvelink E. Fruit set and yield patterns in six Capsicum cultivars. Hort Science, 2009, 44(5): 1296-1301. (Corresponding author).
2. Wubs AM, Ma YT, Heuvelink E, Marcelis LFM. Genetic differences in fruit-set patterns are determined by differences in fruit sink strength and a source: sink threshold for fruit set. Annals of Botany, 2009, 104: 957-964.
3. 郑邦友, 石利娟, 马韫韬, 邓启云, 李保国, 郭焱.水稻冠层的原位三维数字化及虚拟层切法. 中国农业科学, 2009, 42(4): 1181-1189.
4. Ma YT, Mathieu A, Wubs AM, Heuvelink E, Zhu JY, Hu BG, Cournède PH, de Reffye P. Parameter Estimation and Growth Variation Analysis in Six Capsicum Cultivars with the Functional - Structural Model GreenLab. In: BG Li, M Jaeger and Y Guo (eds.). The third International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA09), 2009, 183-190.
5. Zheng BY, Ma YT, Li BG, Guo Y, Deng QY. Assessment of the effects of leaf angle combinations on potential photosynthesis capacity of rice with 3-D models using high performance computing. The third synposium on Plant Growth Modeling and Applications, 9-13, Nov, Beijing, China, 2009. (Oral).
2008年:
1. Ma YT, Wen MP, Guo Y, Li BG, Cournede PH. de Reffye P. Parameter optimization and field validation of the functional-structural model GREENLAB for maize at different population densities. Annals of Botany, 2008, 101: 1185-1194.
2. Zheng BY, Shi LJ, Ma YT, Deng QY, Li BG, Guo Y. Comparison of architecture among different cultivars of hybrid rice using spatial light model based on 3D digitizing. Functional Plant Biology, 2008, 35(9/10): 900-910.
3. Wang XP, Guo Y, Wang XY, Ma YT, and Li BG. Estimating photosynthetically active radiation distribution in maize canopies by a three-dimensional incident radiation model. Functional Plant Biology, 2008, 35(9/10): 867-875.
2007年:
1. Ma YT, Li BG, Zhan ZG, Guo Y, Luquet D, de Reffye P, Dingkuhn M. Parameter stability of the functional-structural plant model GREENLAB as affected by variation within populations, among seasons and among growth stages. Annals of Botany, 2007, 99: 61-73.
2. Zheng BY, Shi LJ, Ma YT, Deng QY, Li BG, Guo Y. Canopy architecture quantification and spatial direct light interception modeling of hybrid rice. Proceedings of the 5th International Workshop on Functional-Structural Plant Models, 2007, 37. 4-9, Nov, Napier, New Zealand (Oral).
3. 马韫韬, 文美平, 李保国, 王锡平, 郭焱. 器官尺度的玉米冠层直射光分布快速计算模型. 农业工程学报, 2007, 23(10): 151-155.
2006年:
1. Guo Y, Ma YT, Zhan ZG, Li BG, Dingkuhn M, Luquet D, de Reffye P. Parameter optimization and field validation of the functional-structural model GREENLAB for maize. Annals of Botany, 2006, 97: 217-230.
2. 马韫韬, 郭焱, 展志岗, 李保国, Philippe de Reffye.玉米生长虚拟模型GREENLAB-Maize的评估. 作物学报, 2006, 32(7): 956-963.
3. 马韫韬, 郭焱, 李保国. 应用三维数字化仪对玉米植株叶片方位分布的研究. 作物学报, 2006, 32(6): 791-798.
4. Wang XP, Guo Y, Li BG, Wang XY, Ma YT. Evaluating a three-dimensional model of diffuse photosynthetically active radiation in maize canopies. International Journal of Biometeorology, 2006, 50: 349-357.
5. Ma YT, Wen MP, Li BG, Guo Y, Cournede PH, de Reffye P. Calibration of GREENLAB model for maize with sparse experimental data. In: Thierry Fourcaud and Xiaopeng Zhang (eds.). The second International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA06). IEEE computer society, 2006, 188-193.
2005年及以前:
1. 马韫韬, 郭焱, 李保国, 展志岗, Philippe de Reffye. 基于GreenLab理论的玉米生长虚拟模型: 参数提取与模拟. 数字农业技术与标准研讨会文集(国家农业信息化工程技术研究中心编), 2005, 365-374. 3.19-20, 北京.
2. 王锡平, 郭焱, 李保国, 马韫韬. 玉米冠层内太阳直接辐射三维空间分布的模拟. 生态学报, 2005, 25 (1): 7-12.
3. 马韫韬, 郭焱, 李保国. 数字农作物的研究. 首届全国博士生学术论坛, 2003, 10.17-19, 清华大学, 北京.
4. 高祥照, 胡克林, 郭焱, 李保国, 马韫韬, 杜森, 王运华.土壤养分与作物产量的空间变异特征与精确施肥. 中国农业科学, 2002, 35(6): 660-666.
