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教授

刘小军

发布人:     发布日期: 2018-02-01    浏览次数:


姓       名:刘小军,教授,博士生导师

研究方向:作物模型、农作精确管理、智慧农业工程

电    话:025-84396804

电子邮箱:liuxj@njau.edu.cn


个人简介:

1998年起在南京农业大学攻读农学学士、作物栽培学与耕作学硕士及农业信息学博士学位。现任国家信息农业工程技术中心副主任、江苏省信息农业重点实验室常务副主任、智慧农业系副主任等。先后主持国家自然科学基金、国家863计划、国家重点研发专项、江苏省自然科学基金等20余项科研项目;受国家留学基金委项目资助,赴美国内布拉斯加州大学精确农业实验室开展了1年的合作研究。在国内外核心期刊发表论文130余篇,其中SCI论文70余篇;参编专著和教材4部;授权国家发明专利9项,登记国家计算机软件著作权20项;研发的2项技术入选国家重大引领性农业技术、2项技术入选农业农村部农业主推技术。先后获国家科技进步二等奖2项、部省级科技进步一等奖5项,并获国家粮丰工程优秀工作者、优秀教师、优秀共产党员及优秀班主任等荣誉称号,指导的博硕士研究生8人次获得国家奖学金、校长奖学金、省级优秀毕业论文等荣誉称号。

代表性论文:

1. Lu R, Zhang P, Fu Z, Jiang J, Wu J, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Improving the spatial and temporal estimation of ecosystem respiration using multi-source data and machine learning methods in a rainfed winter wheat cropland. Science of the Total Environment. 2023, 871: 161967.

2. Wu Y, Jiang J, Zhang X, Zhang J, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Combining machine learning algorithm and multi-temporal temperature indices to estimate the water status of rice. Agricultural Water Management, 2023, 289: 108521. 

3. Zhang J, Fu Z, Zhang K, Li J, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Optimizing rice in-season nitrogen topdressing by coupling experimental and modeling data with machine learning algorithms. Computers and Electronics in Agriculture. 2023, 209: 107858.

4. Jiang J, Atkinson M, Chen C, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Combining UAV and Sentinel-2 satellite multi-spectral images to diagnose crop growth and N status in winter wheat at the county scale. Field Crops Research. 2023, 294: 108860.

5. Fu Z, Zhang R, Zhang J, Zhang K, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Potential of establishing the universal critical nitrogen dilution curve for Japonica rice. Plant Phenomics. 2023, 5: 0036.

6. Zhang J, Pan Y, Tao X, Wang B, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. In-season mapping of rice yield potential at jointing stage using Sentinel-2 images integrated with high-precision UAS data. European Journal of Agronomy. 2023, 146: 126808.

7. Fu Z, Zhang K, Zhang J, Zhang Y, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Optimizing nitrogen application and sowing date can improve environmental sustainability and economic benefit in wheat-rice rotation. Agricultural Systems. 2023, 204: 103536.

8. Wang C, Zhang K, Jiang J, Liu Q, Wu J, Guo C, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Remotely assessing FIPAR of different vertical layers in field wheat. Field Crops Research. 2023, 297: 108932.

9. Jiang J, Wu Y, Liu Q, Liu Y, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Developing an efficiency and energy‑saving nitrogen management strategy for winter wheat based on the UAV multispectral imagery and machine learning algorithm. Precision Agriculture. 2023, 1-25.

10. Yao B, Wang X, Wang Y, Ye T, Wang E, Cao Q, Yao X, Zhu Y, Cao W, Liu X*, Tang L*. Interaction of genotype, environment, and management on organ-specific critical nitrogen dilution curve in wheat. Plant Phenomics. 2023, 5: 0078.

11. Jiang J, Atkinson M, Zhang J, Lu R, Zhou Y, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Combining fixed-wing UAV multispectral imagery and machine learning to diagnose winter wheat nitrogen status at the farm scale. European Journal of Agronomy. 2022, 138: 126537.

12. Zhang K, Ma J, Wang Y, Cao W, Zhu Y, Cao Q, Liu X*, Tian Y. Key variable for simulating critical nitrogen dilution curve of wheat: leaf area ratio-driven approach. Pedosphere. 2022, 32(3): 463-474.

13. Fu Z, Yu S, Zhang J, Xi H, Gao Y, Lu R, Zheng H, Zhu Y, Cao W, Liu X*. Combining UAV multispectral imagery and ecological factors to estimate leaf nitrogen and grain protein content of wheat. European Journal of Agronomy. 2022, 132: 126405.

14. Zhang J, Wang W, Krienke B, Cao Q, Zhu Y, Cao W, Liu X*. In‑season variable rate nitrogen recommendation for wheat precision production supported by fixed‑wing UAV imagery. Precision Agriculture. 2022, 23: 830-853.

15. Zhang J, Qiu X, Wu Y, Zhu Y, Cao Q, Liu X*, Cao W. Combining texture, color, and vegetation indices from fixed-wing UAS imagery to estimate wheat growth parameters using multivariate regression methods. Computers and Electronics in Agriculture. 2021, 185: 106138.

16. Zhang K, Liu X (Co-first author), Ma Y, Wang Y, Zhu Y, Cao W, Tian Y*. A new canopy chlorophyll index-based paddy rice critical nitrogen dilution curve in eastern China. Field Crops Research. 2021, 266: 108139.

17. Jiang J, Wang C, Wang H, Fu Z, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Evaluation of three portable optical sensors for non-destructive diagnosis of nitrogen status in winter wheat. Sensors. 2021, 21: 5579.

18. Fu Z, Jiang J, Gao Y, Krienke B, Wang M, Zhong K, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Wheat growth monitoring and yield estimation based on multi-rotor unmanned aerial vehicle. Remote Sensing. 2020, 12, 508.

19. Zhang K, Yuan Z, Yang T, Lu Z, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Chlorophyll meter–based nitrogen fertilizer optimization algorithm and nitrogen nutrition index for in-season fertilization of paddy rice. Agronomy Journal. 2020, 1-13.

20. Jiang J, Zhang Z, Cao Q, Liang Y, Krienke B, Tian Y, Zhu Y, Cao W, Liu X*. Use of an active canopy sensor mounted on an unmanned aerial vehicle to monitor the growth and nitrogen status of winter wheat. Remote Sensing. 2020, 12, 3684.

21. Wang Y, Zhang K, Tang C, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Estimation of rice growth parameters based on linear mixed-effect model using multispectral images from fixed-wing unmanned aerial vehicles. Remote Sensing. 2019, 11, 1371.

22. Zhang J, Liu X, Liang Y, Cao Q, Tian Y, Zhu Y, Cao W, Liu X*. Using a portable active sensor to monitor growth parameters and predict grain yield of winter wheat. Sensors. 2019, 19, 1108.

23. Liu X, Cao Q, Yuan Z, Liu X, Wang X, Tian Y, Cao W, Zhu Y*. Leaf area index based nitrogen diagnosis in irrigated lowland rice. Journal of Integrative Agriculture. 2018, 17(1): 60345-7.

24. Liu X, Ferguson R, Zheng H, Cao Q, Tian Y, Cao W, Zhu Y*. Using an active-optical sensor to develop an optimal NDVI dynamic model for high-yield rice production (Yangtze, China). Sensors. 2017, 17(4): 672.

25. Liu X, Zhang K, Zhang Z, Cao Q, Lv Z, Yuan Z, Tian Y, Cao W, Zhu Y*. Canopy chlorophyll density based index for estimating nitrogen status and predicting grain yield in rice. Frontiers in Plant Science. 2017, 8: 1829.

26. Yuan Z, Ata-Ul-Karim S, Cao Q, Lu Z, Cao W, Zhu Y, Liu X*. Indicators for diagnosing nitrogen status of rice based on chlorophyll meter readings. Field Crops Research, 2016, 185:12-20.

27. Lv Z, Liu X (Co-first author), Tang L, Liu L, Cao W, Zhu Y*. Estimation of ecotype-specific cultivar parameters in a wheat phenology model and uncertainty analysis. Agricultural and Forest Meteorology, 2016, 221: 219-229.

28. Yuan Z, Cao Q, Zhang K, Ata-Ul-Karim ST, Tian Y, Zhu Y, Cao W, Liu X*. Optimal leaf positions for SPAD meter measurement in rice. Frontiers in Plant Science, 2016, 7:719.

29. 刘小军, 张宇鸥, 陆震洲, 杨雪, 曹卫星, 朱艳*. 基于VRMap 的农区可视化仿真系统设计与实现. 南京农业大学学报, 2013, 36(6): 7-12.

30. 刘小军, 田永超, 姚霞, 曹卫星, 朱艳*. 基于高光谱的水稻叶片含水量监测研究. 中国农业科学, 2012, 45(3): 435-442.

31. 刘小军, 曹静, 汤亮, 曹卫星, 朱艳*. 基于模型和GIS的水稻生产管理决策支持系统构建与应用. 中国水稻科学, 2010, 24(3): 297-302.

32. 刘小军, 曹静, 李艳大, 张玉屏, 曹卫星, 朱艳*. 水稻水分精确管理的知识模型研究. 中国农业科学, 2010, 43(8): 1571-1576.

33. 刘小军, 邱小雷, 孙传范, 曹卫星, 朱艳*, 吴福官. 基于知识模型和PDA的精确农作系统设计及应用. 农业工程学报, 2010, 26(1): 210-215.

34. 刘小军, 朱艳*, 邱小雷, 姜海燕, 曹卫星. 便携式精确农作系统的构建与应用. 农业工程学报, 200925(S2): 104-109.

35. 刘小军, 朱艳*, 曹卫星, 田永超, 姚霞. 基于WebGIS和知识模型的精确农作决策支持系统. 南京农业大学学报, 2007, 30(4): 11-15.

36. 刘小军, 朱艳, 姚霞, 田永超, 曹卫星*. 基于WebGIS的农业空间信息管理及辅助决策系统. 农业工程学报, 2006, 22(5): 125-129.

37. 刘小军, 朱艳, 姚霞, 周治国, 田永超, 曹卫星*. 基于WebGIS的农田生产环境质量评价系统研究. 中国农业科学, 2005, 38(3): 551-557.

专著与教材:

1. 专著:作物生长光谱监测科学出版社,2020(参编)

2. 专著:数字农作技术科学出版社,2008(参编)

3. 教材:农学概论,中国农业出版社,2021(参编)

4. 教材:作物生理生态学实验,科学出版社,2021(参编)

主要科研项目:

1. 水稻全程绿色智慧施肥技术,农业农村部重大引领性技术项目,2023.5-2024.4

2. 稻-麦(油)周年种植智能化管理技术研发,国家重点研发专项任务课题,2022.11-2025.12

3. 多时相无人机图谱信息与临界氮稀释模型耦合的水稻氮素营养诊断研究,国家自然科学基金面上项目,2021.1-2024.12

4. 稻麦智慧化播栽与施肥关键技术及装备研发, 南京农业大学农学院科研培育项目, 2022.1-2024.12

5. 海南水稻长势立体化智能诊断技术与产品的开发应用,海南研究院引导资金重点项目,2021.11-2014.10

6. --地作物长势实时监测与智能诊断平台构建,江苏省农业科技自主创新项目,2020.8-2022.7

7. 高标准农田多种生产模式下的资源安全高效利用与地力提升关键技术集成与示范,江苏省重点研发专项任务课题,2019.7-2023.6

8. 农田感知与智慧管理技术服务,横向课题,2018.7-2020.12

9. 长江中下游小麦适宜指标动态模型及诊断调控,国家重点研发专项任务课题,2016.1-2020.12

10. 南方稻麦轮作区稻麦精准变量施肥管理模型研发,国家重点研发专项任务课题,2016.1-2020.12

11. 长江下游稻作区水稻临界氮浓度稀释模型及追氮调控方法研究,中央高校基本科研业务费重点项目,2016.1-2018.12

12. 作物精确管理技术在宜兴市的集成与示范,江苏省农业三新工程,2016.5-2018.4

13. 冬小麦植株适宜氮浓度模型及诊断指标研究,国家自然科学基金项目,2013.1-2015.12

14. 小麦适宜氮素指标动态模型及诊断方法研究,江苏省自然科学基金,2013.1-2015.12

15. 基于传感网的稻麦生长诊断与调控技术开发应用,江苏省农业三新工程,2013.8-2015.7

16. 麦稻精准农作平行管理系统实现关键技术,国家863计划,2012.1-2015.11

17. 基于Web服务的数字农作管理系统研究,江苏省科技支撑计划,2009.7-2012.7

18. 种植业生产过程信息化关键技术与产品研发,国家科技支撑计划子课题,2006.11-2009.10

主要科研奖励:

1. 稻麦生长指标光谱监测与定量诊断技术. 国家科技进步二等奖,2015

2. 基于模型的作物生长预测与精确管理技术. 国家科技进步二等奖,2008

3. 稻麦生长指标无损监测与精确诊断技术. 教育部科技进步一等奖,2014

4. 作物管理知识模型系统的构建与应用. 教育部科技进步一等奖,2008

5. 稻麦生长指标光谱监测与精确施肥技术的集成推广. 全国农牧渔业丰收奖一等奖,2022

6. 稻麦生长指标无损监测与精确诊断技术. 江苏省科技进步一等奖,2014

7. 稻麦精确管理技术的集成与推广. 江苏省农业技术推广一等奖,2017