In-Season Estimation of Rice Nitrogen Status With an Active Crop Canopy Sensor. - Yinkun Yao; Yuxin Miao; Qiang Cao 002; Hongye Wang; Martin L. Gnyp; Georg Bareth; Rajiv Khosla; Wen Yang; Fengyan Liu; Cheng Liu (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014)

Active canopy sensing of winter wheat nitrogen status: An evaluation of two sensor systems. - Qiang Cao 002; Yuxin Miao; Guohui Feng; Xiaowei Gao; Fei Li; Bin Liu; Shanchao Yue; Shanshan Cheng; Susan L. Ustin; Rajiv Khosla (Comput. Electron. Agric., 2015)

Potential of RapidEye and WorldView-2 Satellite Data for Improving Rice Nitrogen Status Monitoring at Different Growth Stages. - Shanyu Huang; Yuxin Miao; Fei Yuan 004; Martin L. Gnyp; Yinkun Yao; Qiang Cao 002; Hongye Wang; Victoria I. S. Lenz-Wiedemann; Georg Bareth (Remote. Sens., 2017)

Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China). - Xiaojun Liu 003; Richard B. Ferguson; Hengbiao Zheng; Qiang Cao 002; Yongchao Tian; Weixing Cao; Yan Zhu 005 (Sensors, 2017)

Comparison RGB Digital Camera with Active Canopy Sensor Based on UAV for Rice Nitrogen Status Monitoring. - Songyang Li; Xiaojun Liu 003; Yongchao Tian; Yan Zhu 005; Qiang Cao 002 (Agro-Geoinformatics, 2018)

Detecting Rice Blast Disease Using Model Inverted Biochemical Variables from Close-Range Reflectance Imagery of Fresh Leaves. - Long Tian; Zefu Wan; Dong Li 003; Jiale Jiang; Xia Yao; Qiang Cao 002; Yongchao Tian; Yan Zhu 005; Weixing Cao; Tao Cheng 003 (IGARSS, 2018)

Evaluation of One-Class Support Vector Classification for Mapping the Paddy Rice Planting Area in Jiangsu Province of China from Landsat 8 OLI Imagery. - Xinjie Xu; Xusheng Ji; Jiale Jiang; Xia Yao; Yongchao Tian; Yan Zhu 005; Weixing Cao; Qiang Cao 002; Hongjian Yang; Zhongkui Shi; Tao Cheng 003 (Remote. Sens., 2018)

In-Season Diagnosis of Rice Nitrogen Status Using Proximal Fluorescence Canopy Sensor at Different Growth Stages. - Shanyu Huang; Yuxin Miao; Fei Yuan 004; Qiang Cao 002; Huichun Ye; Victoria I. S. Lenz-Wiedemann; Georg Bareth (Remote. Sens., 2019)

Combining Color Indices and Textures of UAV-Based Digital Imagery for Rice LAI Estimation. - Songyang Li; Fei Yuan 004; Syed Tahir Ata-UI-Karim; Hengbiao Zheng; Tao Cheng 003; Xiaojun Liu 003; Yongchao Tian; Yan Zhu 005; Weixing Cao; Qiang Cao 002 (Remote. Sens., 2019)

Estimation of Rice Growth Parameters Based on Linear Mixed-Effect Model Using Multispectral Images from Fixed-Wing Unmanned Aerial Vehicles. - Yanyu Wang; Ke Zhang; Chunlan Tang; Qiang Cao 002; Yongchao Tian; Yan Zhu 005; Weixing Cao; Xiaojun Liu 003 (Remote. Sens., 2019)

Predicting Rice Grain Yield Based on Dynamic Changes in Vegetation Indexes during Early to Mid-Growth Stages. - Ke Zhang; Xiaokang Ge; Pengcheng Shen; Wanyu Li; Xiaojun Liu 003; Qiang Cao 002; Yan Zhu 005; Weixing Cao; Yongchao Tian (Remote. Sens., 2019)

Using a Portable Active Sensor to Monitor Growth Parameters and Predict Grain Yield of Winter Wheat. - Jiayi Zhang; Xia Liu; Yan Liang; Qiang Cao 002; Yongchao Tian; Yan Zhu 005; Weixing Cao; Xiaojun Liu 003 (Sensors, 2019)

Wheat Growth Monitoring and Yield Estimation based on Multi-Rotor Unmanned Aerial Vehicle. - Zhaopeng Fu; Jie Jiang 006; Yang Gao; Brian Krienke; Meng Wang; Kaitai Zhong; Qiang Cao 002; Yongchao Tian; Yan Zhu 005; Weixing Cao; Xiaojun Liu 003 (Remote. Sens., 2020)

Use of an Active Canopy Sensor Mounted on an Unmanned Aerial Vehicle to Monitor the Growth and Nitrogen Status of Winter Wheat. - Jie Jiang 006; Zeyu Zhang; Qiang Cao 002; Yan Liang; Brian Krienke; Yongchao Tian; Yan Zhu 005; Weixing Cao; Xiaojun Liu 003 (Remote. Sens., 2020)

Using an Active Sensor to Develop New Critical Nitrogen Dilution Curve for Winter Wheat. - Jie Jiang 006; Cuicun Wang; Yu Wang; Qiang Cao 002; Yongchao Tian; Yan Zhu 005; Weixing Cao; Xiaojun Liu 003 (Sensors, 2020)

A Comparative Assessment of Measures of Leaf Nitrogen in Rice Using Two Leaf-Clip Meters. - Ke Zhang; Xiaojun Liu 003; Yong Ma; Rui Zhang; Qiang Cao 002; Yan Zhu 005; Weixing Cao; Yongchao Tian (Sensors, 2020)

AGTOC: A novel approach to winter wheat mapping by automatic generation of training samples and one-class classification on Google Earth Engine. - Gaoxiang Yang; Weiguo Yu; Xia Yao; Hengbiao Zheng; Qiang Cao 002; Yan Zhu 005; Weixing Cao; Tao Cheng 003 (Int. J. Appl. Earth Obs. Geoinformation, 2021)

Combining texture, color, and vegetation indices from fixed-wing UAS imagery to estimate wheat growth parameters using multivariate regression methods. - Jiayi Zhang; Xiaolei Qiu; Yueting Wu; Yan Zhu 005; Qiang Cao 002; Xiaojun Liu 003; Weixing Cao (Comput. Electron. Agric., 2021)

Evaluation of Three Portable Optical Sensors for Non-Destructive Diagnosis of Nitrogen Status in Winter Wheat. - Jie Jiang 006; Cuicun Wang; Hui Wang; Zhaopeng Fu; Qiang Cao 002; Yongchao Tian; Yan Zhu 005; Weixing Cao; Xiaojun Liu 003 (Sensors, 2021)

Advances in the estimations and applications of critical nitrogen dilution curve and nitrogen nutrition index of major cereal crops. A review. - Xinyu Li; Syed Tahir Ata-UI-Karim; Yue Li; Fei Yuan 004; Yuxin Miao; Kato Yoichiro; Tao Cheng 003; Liang Tang; Xingshuai Tian; Xiaojun Liu 003; Yongchao Tian; Yan Zhu 005; et al. (Comput. Electron. Agric., 2022)

Improving wheat yield prediction integrating proximal sensing and weather data with machine learning. - Guojie Ruan; Xinyu Li; Fei Yuan 004; Davide Cammarano; Syed Tahir Ata-UI-Karim; Xiaojun Liu 003; Yongchao Tian; Yan Zhu 005; Weixing Cao; Qiang Cao 002 (Comput. Electron. Agric., 2022)

Developing an Active Canopy Sensor-Based Integrated Precision Rice Management System for Improving Grain Yield and Quality, Nitrogen Use Efficiency, and Lodging Resistance. - Junjun Lu; Hongye Wang; Yuxin Miao; Liqin Zhao; Guangming Zhao; Qiang Cao 002; Krzysztof Kusnierek (Remote. Sens., 2022)

Optimizing rice in-season nitrogen topdressing by coupling experimental and modeling data with machine learning algorithms. - Jiayi Zhang; Zhaopeng Fu; Ke Zhang; Jiayu Li; Qiang Cao 002; Yongchao Tian; Yan Zhu 005; Weixing Cao; Xiaojun Liu 003 (Comput. Electron. Agric., 2023)

Improving yield prediction based on spatio-temporal deep learning approaches for winter wheat: A case study in Jiangsu Province, China. - Peipei Chen; Yue Li; Xiaojun Liu 003; Yongchao Tian; Yan Zhu 005; Weixing Cao; Qiang Cao 002 (Comput. Electron. Agric., 2023)

Multi-source data fusion improved the potential of proximal fluorescence sensors in predicting nitrogen nutrition status across winter wheat growth stages. - Qing Liu; Cuicun Wang; Jie Jiang 006; Jiancheng Wu; Xue Wang 012; Qiang Cao 002; Yongchao Tian; Yan Zhu 005; Weixing Cao; Xiaojun Liu 003 (Comput. Electron. Agric., 2024)

Investigating data-driven approaches to optimize nitrogen recommendations for winter wheat. - Guojie Ruan; Davide Cammarano; Syed Tahir Ata-UI-Karim; Xiaojun Liu 003; Yongchao Tian; Yan Zhu 005; Weixing Cao; Qiang Cao 002 (Comput. Electron. Agric., 2024)

Screening drought-resistant and water-saving winter wheat varieties by predicting yields with multi-source UAV remote sensing data. - Xu Liu; Han Yang; Syed Tahir Ata-UI-Karim; Urs Schmidhalter; Yunzhou Qiao; Baodi Dong; Xiaojun Liu 003; Yongchao Tian; Yan Zhu 005; Weixing Cao; Qiang Cao 002 (Comput. Electron. Agric., 2025)