Curriculum Vitae
Xia YAO (姚霞), Ph.D.
Professor, College of Agriculture, National
Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University (NAU)
Vice Dean, NAU Institute of Smart
Agriculture
Rm. A4009, Biology Building, 1 Weigang Rd, Nanjing, Jiangsu 210095, P. R. China
Tel:
+86-25-84396565, Fax: +86-25-84396672, Mobile:
13952028787
Email: yaoxia@njau.edu.cn,
Web: http://web.netcia.org.cn/XiaYao.html; http://web.netcia.org.cn/XiaYao_cn.html
Research Interests
n
Hyperspectral
remote sensing of vegetation
n
Crop
growth/biotic/abiotic stress/senescence monitoring based on SIF
n
Active
remote sensing (LiDAR) of vegetation
n
Unmanned
aerial vehicles (UAVs) of vegetation
n
Acquisition
of High Throughput Crop Phenotype
n
Crop-land
use change
n
Vegetation
mapping
Education
n
1997, 9- 2001,
7 BS of Agronomy, NAU, China
n
2001, 9- 2004,
7 MS
of Ecology,
NAU, China
n
2006, 9- 2009, 9
PhD of
Crop Informatics, NAU, China
Work Experience
n
2017, 1– 2017,
12 Visiting professor, Dep. Of Geography, UH., USA
n 2015, 1 – Now
Professor, College
of Agriculture, NAU, China
n 2010, 1 – 2014,12
Associate Professor, College
of Agriculture, NAU, China
n 2007, 1 –
2009, 12 Lecturer,
College of Agriculture, NAU, China
n
2004, 7 – 2006, 12 Teaching Assistant, College of Agriculture,
NAU, China
Publications (* note the
correspond author)
2025
1.
Li,
W., Li, D., Timothy, A. W., Liu, S., Frédéric, B., Yang, P., Jiang, J., Dong,
M., Cheng, T., Zhu, Y*., Cao, W., Yao, X.*, 2025. Improved generality of
wheat green LAI models through mitigation of the effect of leaf chlorophyll
content variation with red edge vegetation indices. Remote Sensing of
Environment. 318: 114589.
2.
Zhou,
M., Zhu, J., Ai, H., Zhang, Y., Timothy, A. W., Zheng, H., Jiang, C., Cheng,
T., Zhu, Y., Cao, W., Zhang, X., Yao, X.*, 2025. A in-seasonal phenology monitoring approach for wheat
breeding accessions with time-series RGB imagery by using a combination
KNN-CNN-RF model. ISPRS Journal of Photogrammetry and Remote Sensing.
227:297-315.
3.
Guo,
T., Wang, Y., Gu, Y., Fang, Y., Zheng, H., Zhang, X.*, Zhou, D, Jiang， C, Cheng, T, Zhu,
Y, Cao, W, Yao, X.*, 2025. MSCVI: An improved algorithm for mitigating
LiDAR noise and occlusion effects in field wheat tiller number calculation.
Computers and Electronics in Agriculture. 229: 109757.
4.
Guo,
T., Mathias, D., Wang, Y., Zheng, H., Zhou, D., Jiang, C.*, Cheng, T., Zhu, Y.,
Cao, W., Yao, X.*, 2025. Evaluating the effects of sampling design and
voxel size on wheat green area index estimation using 3D radiative transfer
simulations and TLS measurements. IEEE Transactions on Geoscience and Remote
Sensing. 15:23-38
2024
5.
Gu,
Y., Wang, Y., Wu, Y., Timothy, A. W., Guo, T., Ai, H., Zheng, H., Cheng, T.,
Zhu, Y., Cao, W., Yao, X.*, 2024. Novel 3D photosynthetic traits derived
from the fusion of UAV LiDAR point cloud and multispectral imager yin wheat.
Remote Sensing of Environment. 311: 114244.
6.
Gu,
Y., Wang, Y., Guo, T., Guo, C., Wang, X., Jiang, C., Cheng, T., Zhu, Y.*, Cao,
W., Chen, Q.*, Yao X.*, 2024. Assessment of the influence of
UAV-borne LiDAR scan angle and flight altitude on the estimation of wheat
structural metrics with different leaf angle distributions. Computers and
Electronics in Agriculture. 220:
108858.
7.
Mustafa,
G., Zheng, H., Imran, H. Khan., Zhu, J., Yamg, T., Wang, A., Xue, B., He, C.,
Jia, H., Li, G., Cheng, T., Cao, W., Zhu, Y., Yao X.*, 2024. Enhancing
fusarium head blight detection in wheat crops using hyperspectral indices and
machine learning classifiers. Computers and Electronics in Agriculture. 218:
108663.
8.
Mustafa,
G., Zheng, H., Liu, Y., Yang, S., Imran, H. Khan., Sarfraz, H., Liu, J., Wu,
W., Chen, M., Cheng, T., Zhu, Y., Yao, X.*, 2024. Leveraging machine
learning to discriminate wheat scab infection levels through hyperspectral
reflectance and feature selection methods. European Journal of Agronomy. 161:
127372.
9.
Yuan,
J., Li, X., Zhou, M., Zheng, H., Yao, Xia.*, 2024. Rapidly count crop
seedling emergence based on waveform Method(WM) using drone imagery at the
early stage. Computers and Electronics in Agriculture. 220: 108867.
10.
Han,
X., Zhou, M., Guo, C., Ai, H., Li, T., Li, W., Zhang, X., Chen, Q., Jiang, C.,
Cheng, T., Zhu, Y., Cao, W., Yao, X.*, 2024. A fully convolutional
neural network model combined with a Hough transform to extract crop breeding
field plots from UAV images. International Journal of Applied Earth Observation
and Geoinformation. 132: 104057.
11.
Wang,
Y., Gu, Y., Tang, J., Timothy, A.W., Guo, C., Zheng, H., Fumiki, H., Cheng, T.,
Zhu, Y., Cao, W., Yao, X.*, 2024. Quantify wheat canopy leaf angle
distribution using terrestrial laser scanning data. IEEE Transactions on
Geoscience and Remote Sensing. 62:1-15.
12.
Zheng,
H., Tang, W., Yang, T., Zhou, M., Guo, C., Cheng, T., Cao, W., Zhu, Y., Zhang,
Y., Yao, X.*, 2024. Grain protein content phenotyping in rice via
hyperspectral imaging technology and a genome-wide association study. Plant
Phenomics. 6: 0200.
2023
13.
Gu,
Y., Ai, H., Guo, T., Liu, P., Wang, Y., Zheng, H., Cheng, T., Zhu, Y.*, Cao,
W., Yao, X.*, 2023. Comparison of two novel methods for counting wheat
ears in the field with terrestrial LiDAR. Plant Methods. 19: 134.
14.
Zhu,
J., Yin, Y., Lu, J., Timothy, A.W., Xu, X., Lyu, M., Wang, X., Guo C., Cheng,
T., Zhu, Y., Cao, W., Yao, X.*, Zhang, Y., Liu, L., 2023. The relationship
between wheat yield and sun-induced chlorophyll fluorescence from continuous
measurements over the growing season. Remote Sensing of Environment. 298:
113791.
15.
Li,
W., Li, D., Liu, S., Frédéric, B., Ma, Z., He, C., Timothy, A.W., Guo, C.,
Cheng, T., Zhu, Y.*, Cao, W., Yao, X.*, 2023. RSARE: A physically-based
vegetation index for estimating wheat green LAI to mitigate the impact of leaf
chlorophyll content and residue-soil background. ISPRS Journal of
Photogrammetry and Remote Sensing. 200:138-152.
16.
Zhu,
J., Lu, J., Li, W., Wang, Y., Jiang, J., Cheng, T., Zhu, Y., Cao, W., Yao,
X.*, 2023. Estimation of canopy water content for wheat through combining
radiative transfer model and machine learning. Field Crop Research. 302:109077.
17.
Ma,
Z., Li, W., Timothy, A.W., He, C., Wang, X., Zhang, Y., Guo, C., Cheng, T.,
Zhu, Y., Cao, W., Yao, X.*. 2023. A framework combined stacking ensemble
algorithm to classify crop in complex agricultural landscape of high altitude
regions with Gaofen-6 imagery and elevation data. International Journal of
Applied Earth Observation and Geoinformation. 122:103386.
18.
Mustafa,
G., Zheng, H., Li, W., Yin, Y., Wang, Y., Zhou, M., Liu, P., Bilal, M., Jia,
H., Li, G., Cheng, T., Tian, Y., Cao, W., Zhu, Y.*, Yao, X.*, 2023.
Fusarium head blight monitoring in wheat ears using machine learning and
multimodal data from asymptomatic to symptomatic periods. Frontiers in Plant
Science. 13:1102341.
19.
Zhou,
M., Zheng, H., He, C., Liu, P., Mustafa, G., Wang, X., Cheng, T., Zhu, Y., Cao,
W., Yao, X.*, 2023. Wheat phenology detection with the methodology of
classification based on the time-series UAV images. Field Crops Research. 292:
108798.
20.
Wang,
K., Zhu, J., Xu, X., Li, T., Wang, X., Timothy, A.W., Cheng, T., Zhu, Y*., Cao,
W., Yao, X.*, Zhang, Z., 2023. Quantitative monitoring of salt
stress in rice with solar-induced chlorophyll fluorescence. European Journal of
Agronomy. 150: 126954.
21. Yin, Y., Zhu, J., Xu, X., Jia, M.,
Timothy, A.W., Wang, X., Li, T., Cheng, T., Zhu, Y., Cao, W., Yao, X.*,
2023. Tracing the nitrogen nutrient status of crop based on solar-induced
chlorophyll fluorescence. European Journal of Agronomy. 149: 126924.
2022
22.
Mustafa,
G., Zheng, H., Khan, I. H., Tian, L., Jia, H., Li, G., Cheng, T., Tian, Y.,
Cao, W., Zhu, Y., Yao, X., 2022. Hyperspectral reflectance proxies to
diagnose in-field fusarium head blight in wheat with machine learning. Remote
Sensing. 14(12): 2784.
23.
Jiang,
J., Liu, H., Zhao, C., He, C., Ma, J., Cheng, T., Zhu, Y., Cao, W., Yao, X.*,
2022. Evaluation of diverse convolutional neural networks and training
strategies for wheat leaf disease identification with field-acquired
photographs. Remote Sensing. 14(14): 3446.
2021
24.
Khan,
I. H., Liu, H., Li, W., Cao, A., Wang, X., Liu, H., Cheng, T., Tian, Y., Zhu,
Y., Cao, W., Yao, X.*, 2021. Early detection of powdery mildew disease
and accurate quantification of its severity using hyperspectral images in
Wheat. Remote Sensing. 13: 3612.
25.
Jia,
M., Colombo, R., Rossini, M., Celesti, M., Zhu, J., Cogliati, S., Cheng, T., Tian,
Y., Zhu, Y., Cao, W., Yao, X.*, 2021. Remote estimation of nitrogen
content and photosynthetic nitrogen use efficiency in wheat leaf using
sun-induced chlorophyll fluorescence at the leaf and canopy scales. European
Journal of Agronomy. 126: 126192.
2020
26.
Fang,
Y., Qiu, X., Guo, T., Wang, Y., Cheng, T., Zhu, Y., Chen, Q., Cao, W., Yao,
X.*, Niu, Q., Hu, Y., Gui, L., 2020. An automatic method for counting wheat
tiller number in the field with terrestrial LiDAR. Plant Methods. 16(1): 132.
27.
Zhou,
M., Ma, X., Wang, K., Cheng, T., Tian, Y., Wang, J., Zhu, Y., Hu, Y., Niu, Q.,
Gui, L., Yue, C., Yao, X., 2020. Detection of phenology using an improved shape
model on time-series vegetation index in wheat. Computers and Electronics in
Agriculture. 173: 105398.
2019
28.
邱小雷, 方圆, 郭泰, 程涛, 朱艳, 姚霞*, 2019. 基于地基LiDAR高度指标的小麦生物量监测研究. 农业机械学报. 50(10):
159-166.
29.
Jia,
M., Li, D., Colombo, R., Wang, Y., Wang, X., Cheng, T., Zhu, Y., Yao, X.*,
Xu, C., Ouer, G., Li, H., Zhang, C., 2019. Quantifying Chlorophyll Fluorescence
Parameters from Hyperspectral Reflectance at the Leaf Scale under Various
Nitrogen Treatment Regimes in Winter Wheat. Remote Sensing. 11: 2838.
30.
Jia,
M., Li, W., Wang, K., Zhou, C., Cheng, T., Tian, Y., Zhu, Y., Cao, W., Yao,
X.*, 2019. A newly developed method to extract the optimal hyperspectral
feature for monitoring leaf biomass in wheat. Computers and Electronics in
Agriculture. 165: 104942.
31.
Jiang,
J., Cai, W., Zheng, H., Cheng, T., Tian, Y., Zhu, Y., Ehsani, R., Hu, Y., Niu,
Q., Gui, L., Yao, X.*, 2019. Using Digital Cameras on an Unmanned Aerial
Vehicle to Derive Optimum Color Vegetation Indices for Leaf Nitrogen
Concentration Monitoring in Winter Wheat. Remote Sensing. 11: 2667.
32.
Jiang,
J., Zheng, H., Ji, X., Cheng, T., Tian, Y., Zhu, Y., Cao, W., Ehsani, R., Yao,
X.*, 2019. Analysis and evaluation of the image preprocessing process of a
Six-band multispectral camera mounted on an unmanned aerial vehicle for winter
wheat monitoring. Sensors. 19: 747.
33.
Guo,
T., Fang, Y., Cheng, T., Tian, Y., Zhu, Y., Chen, Q., Qiu, X., Yao, X.*,
2019. Detection of wheat height using optimized multi-scan mode of LiDAR during
the entire growth stages. Computers and Electronics in Agriculture. 165:
104959.
34.
Li,
W., Jiang, J., Guo, T., Zhou, M., Tang, Y., Wang, Y., Zhang, Y., Cheng, T.,
Zhu, Y., Cao, W., Yao, X.*, 2019. Generating red-edge images at 3 m
spatial resolution by fusing Sentinel-2 and Planet satellite products. Remote
Sensing. 11(12): 1422.
35.
Cao,
Z., Yao, X., Liu, H., Liu, B., Cheng, T., Tian, Y., Cao, W., Zhu, Y.*,
2019. Comparison of the abilities of vegetation indices and photosynthetic
parameters to detect heat stress in wheat. Agricultural and Forest Meteorology.
265: 121-136.
2018
36.
Jia,
M., Zhu, J., Ma, C., Alonso, L., Li, D., Cheng, T., Tian, Y., Zhu, Y., Yao,
X.*, Cao, W., 2018. Difference and Potential of the Upward and Downward
Sun-Induced Chlorophyll Fluorescence on Detecting Leaf Nitrogen Concentration
in Wheat. Remote Sensing. 10: 1315.
37.
Yao,
X., Si, H., Cheng, T.,
Liu, Y., Jia, M., Tian, Y., Chen, C., Liu, S., Chen, Q., Zhu, Y.*, 2018.
Spectroscopic estimation of leaf dry weight per ground area using vegetation
indices and continuous wavelet analysis in wheat. Frontiers in Plant Science.
9: 1360.
2017
38.
Yao,
X., Wang, N., Liu, Y.,
Cheng, T., Tian, Y., Chen, Q., Zhu, Y.*, 2017. Accurate Estimation of LAI with
Multispectral Imagery on Unmanned Aerial Vehicle (UAV) in Wheat. Remote
Sensing. 9: 1304.
39.
Cao,
Z., Cheng, T., Ma, X., Tian, Y., Zhu, Y., Yao, X.*, Chen, Q., Liu, S.,
Guo, Z., Zhen, Q., 2017. A new three-band spectral index for mitigating the
saturation in the estimation of leaf area index in wheat. International Journal
of Remote Sensing. 38(13): 3865-3885.
2016
40.
Chen,
J., Yao, X., Huang, F.*, Liu, Y., Yu, Q., Wang, N., Xu, H., Zhu, Y.,
2016. N status monitoring model in winter wheat based on image processing.
Transactions of the Chinese Society of Agricultural Engineering. 32(4):
163-170.
2015
41.
Yao,
X., Huang, Y., Shang, G.,
Zhou, C., Cheng, T., Tian, Y., Cao, W., Zhu, Y.*, 2015. Evaluation of Six
Algorithms to Monitor Wheat Leaf Nitrogen Concentration. Remote Sensing. 7:
14939-14966.
2014
42.
Yao,
X., Ren, H., Cao, Z.,
Tian, Y., Cao, W., Zhu, Y.*, Chen, T., 2014. Detecting leaf nitrogen content in
wheat with canopy hyperspectrum under different soil backgrounds. International
Journal of Applied Earth Observation and Geoinformation. 32: 114-124.
43.
Yao,
X., Jia, W., Si, H., Guo,
Z., Tian, Y., Liu, X., Cao, W., Zhu, Y.*, 2014. Monitoring leaf equivalent
water thickness based on hyperspectrum in wheat under different water and
nitrogen treatments. PLOS ONE. 9(6): e99789.
44.
Yao,
X., Ata-Ul-Karim, S. T.,
Zhu, Y., Tian, Y., Liu, X., Cao, W.*, 2014. Development of critical nitrogen
dilution curve in rice based on leaf dry matter. European Journal of Agronomy.
55: 20-28.
45.
Yao, X., Zhao, B., Tian, Y., Liu, X., Ni, J., Cao, W., Zhu,
Y.*, 2014. Using leaf dry
matter to quantify the critical nitrogen dilution curve for winter wheat in
eastern China. Field Crops Research. 159: 33-42.
46.
Zhao,
B., Yao, X., Tian, Y., Liu, X., Ata-Ul-Karim, S. T., Ni, J., Cao, W.,
Zhu, Y.*, 2014. New critical nitrogen curve based on leaf area index for winter
wheat. Agronomy Journal. 106(2): 379-389.
47.
Ata-Ul-Karim,
S. T., Yao, X., Liu, X., Cao, W., Zhu, Y.*, 2014. Development of critical
nitrogen dilution curve of japonica rice in yangtze river reaches. Field Crops
Research. 149: 149-158.
48.
Chen,
Q., Tian, Y., Yao, X., Cao, W., Zhu, Y.*, 2014. Comparison of nitrogen
dressing approaches to optimize rice growth. Plant Production Science. 17(1):
66-80.
2013
49.
Yao,
X., Zhu, Y., Tian, Y.,
Feng, W., Cao, W.*, 2013. Research of the optimum hyperspectral vegetation
indices on monitoring the nitrogen content in wheat leaves. Scientia Agricultura
Sinica. 42(8): 2716-2725.
50.
Tian,
Y., Zhang, J., Yao, X., Cao, W., Zhu, Y.*, 2013. Laboratory assessment
of three quantitative methods for estimating the organic matter content of
soils in China based on visible/near-infrared reflectance spectra. Geoderma.
202-203: 161-170.
51.
Ni, J., Yao, X., Tian, Y., Cao, W., Zhu, Y.*,
2013. Design and experiments of
portable apparatus for plant growth monitoring and diagnosis. Transactions of
the Chinese Society of Agricultural Engineering. 29(6): 150-156.
52.
Ni,
J., Wang, T., Yao, X., Cao, W., Zhu, Y.*, 2013. Design and experiments
of multi-spectral sensor for rice and wheat growth information. Transactions of
the Chinese Society for Agricultural Machinery. 44(5): 207-212.
53.
Yao,
XF., Yao, X., Jia, W., Tian, Y., Ni, J., Cao, W., Zhu, Y.*, 2013.
Comparison and inter calibration of vegetation indices from different sensors
for monitoring plant nitrogen uptake in wheat. Sensors. 13(3): 3109-3130.
54.
Yao, XF., Yao, X., Tian, Y., Ni, J., Cao, W., Zhu,
Y.*, 2013. A new method to
determine central wavelength and optimal bandwidth for predicting plant
nitrogen uptake in wheat. Journal of Integrative Agriculture. 12(5): 788-802.
2012
55.
Wang, W., Yao, X., Liu, X., Tian, Y., Ni, J., Cao,
W., Zhu, Y.*, 2012. Common spectral
bands and optimum vegetation indices for monitoring leaf nitrogen accumulation
in rice and wheat. Agricultural Sciences in China. 11(12): 2001-2008.
56.
Wang,
W., Yao, X., Yao, X. F., Tian, Y., Liu, X., Ni, J., Cao, W., Zhu, Y.*,
2012. Estimating leaf nitrogen concentration with three-band vegetation indices
in rice and wheat. Field Crops Research. 129: 90-98.
57.
Yao, X., Yao, X. F., Tian, Y., Ni, J., Cao, W., Zhu, Y.*, 2012.
Estimation of leaf
pigment concentration in rice by near infrared reflectance spectroscopy. Chinese
Journal of Analytical Chemistry. 40(4): 589-595.
58.
Tian,
Y., Zhang, J., Yao, X., Cao, W., Zhu, Y.*, 2012. Quantitative modeling
method of soil organic matter content based on near-infrared photo acoustic
spectroscopy. Transactions of the Chinese Society of Agricultural Engineering.
28(1): 145-152.
2011
59.
Tian,
Y., Yao, X., Yang, J., Cao, W., Hannaway, D. B., Zhu, Y., 2011.
Assessing newly developed and published vegetation indices for estimating rice leaf
nitrogen concentration with ground- and space-based hyperspectral reflectance.
Field Crops Research. 120: 299-310.
60.
Tian,
Y., Yao, X., Yang, J., Cao, W., Zhu, Y.*, 2011. Extracting red edge
position parameters from ground-and space-based hyperspectral data for
estimation of canopy leaf nitrogen concentration in rice. Plant Production
Science. 14(3): 270-281.
61.
Yao,
X., Liu, X., Wang, W., Ni,
J., Cao, W., Zhu, Y.*, 2011. Optimal bandwidths of sensitive bands for portable
nitrogen monitoring instrument in wheat. Transactions of the Chinese Society
for Agricultural Machinery. 42(2): 162-167.
62.
Yao,
X., Tang, S., Cao, W.,
Tian, Y., Zhu, Y.*, 2011. Estimating the nitrogen content in wheat leaves by
near-infrared reflectance spectroscopy. Chinese Journal of Plant Ecology.
35(8): 844-852.
2010
63.
Yao,
X., Zhu, Y., Tian, Y., Liu,
X., Cao, W.*, 2010. Exploring hyperspectral bands and estimation indices for
leaf nitrogen accumulation in wheat. International Journal of Applied Earth
Observation and Geoinformation. 12(2): 89-100.
64.
Yao,
X., Tian, Y., Liu, X., Cao,
W., Zhu, Y.*, 2010. Comparative study on monitoring canopy leaf nitrogen status
on red edge position with different algorithms in wheat. Scientia Agricultura
Sinica. 43(13): 2661-2667.
65.
Yao,
X., Liu, X., Wang, W., Tian,
Y., Cao, W., Zhu, Y.*, 2010. Estimation of optimum normalized difference
spectral index for nitrogen accumulation in wheat leaf based on reduced precise
sampling method. Chinese Journal of Applied Ecology. 21(12): 3175-3182.
66.
Zhang,
Y., Yao, X., Tian, Y., Cao, W., Zhu, Y.*, 2010. Estimating leaf nitrogen
content with near infrared reflectance spectroscopy in rice. Chinese Journal of
Plant Ecology. 34(6): 704-712.
2009
67.
Yao,
X., Zhu, Y., Feng, W.,
Tian, Y., Cao, W.*, 2009. Exploring novel hyperspectral band and key index for
leaf nitrogen accumulation in wheat. Spectroscopy and Spectral Analysis. 29(8):
2191-2195.
2008
68.
Feng,
W., Yao, X., Zhu, Y., Tian, Y., Cao, W., 2008. Monitoring leaf nitrogen
status with hyperspectral reflectance in wheat. European Journal of Agronomy.
28(3): 394-404.
69.
Feng,
W., Yao, X., Tian, Y., Cao, W., Zhu, Y., 2008. Monitoring leaf pigment
status with hyperspectral remote sensing in wheat. Australian Journal of
Agricultural Research. 59(9): 748-760.
70.
Zhu,
Y., Yao, X., Tian, Y., Liu, X., Cao, W., 2008. Analysis of common canopy
vegetation indices for indicating leaf nitrogen accumulations in wheat and
rice. International Journal of Applied Earth Observation and Geoinformation.
10(1): 1-10.
71.
Feng,
W., Yao, X., Tian, Y., Zhu, Y., Li, Y., Cao, W.*, 2008. Monitoring the
sugar to nitrogen ratio in wheat leaves with hyperspectral remote sensing.
Scientia Agricultura Sinica. 41(6): 1630-1639.
72.
Feng,
W., Yao, X., Tian, Y., Zhu, Y., Liu, X., Cao, W.*, 2008. Predicting
grain protein content with canopy hyperspectral remote sensing in wheat. Acta
Agronomica Sinica. 33(12): 1935-1942.
2007
73.
Yao,
X., Wu, H., Zhu, Y., Tian,
Y., Zhou, Z., Cao, W.*, 2007. Relationship between pigment concentrations and hyperspectral
parameters in functional leaves of cotton. Cotton Science. 19(4): 267-272.
74.
Yao,
X., Feng, W., Zhu, Y.,
Tian, Y., Cao, W.*, 2007. A non-destructive and real-time method of monitoring
leaf nitrogen status in wheat. New Zealand Journal of Agricultural Research.
50(5): 935-942.
75.
Yao,
X., Bian, X., Peng, H.,
Cao, W., Zhu, Y., Zhang, W.*, 2007. ARIMA time series modeling and applying on
fresh agricultural products. System Sciences and Comprehensive Studies in
Agriculture. 23(1): 89-94.
2006
76.
Zhu,
Y., Yao, X., Tian, Y., Zhou, D., Li, Y., Cao, W.*, 2006. Quantitative
relationship between leaf nitrogen accumulation and canopy reflectance spectra
in rice and wheat. Journal of Plant Ecology. 30(6): 983-990.
Monograph
& Textbook
(1). Monograph: Spectral Sensing of Crop Growth. Science Press.
2020. (Co-editor)
(2). Monograph: Estimating leaf nitrogen concentration of
cereal crops with hyperspectral data. In: Prasad ST, John GL, Alfredo H. (eds.)
Hyperspectral Remote Sensing of Vegetation. CRC Press, FL, USA. 2011.187-206. (One chapter)
(3). Textbook: An Introduction to Agricultural Information Technology. Agricultural Science and Technology Press. China. 2009. (Co-editor)
(4). Monograph: Digital Farming Technology. Science Press. 2008. (Co-editor)
Teaching
Experience
n 2018, 1-present Professor,
College of Agriculture, NAU
Ø Courses teaching
u Agricultural Remote Sensing
(Graduate,
Teaching in English)
u Agricultural Remote Sensing
(Undergraduate)
n 2016, 1-present Professor,
College of Agriculture, NAU
Ø Courses teaching
u Agricultural Remote Sensing
(Graduate)
u Crop High Yield Theory and
Technology (Graduate)
u Introduction to Information
Agriculture (Undergraduate)
n 2015, 1-present Professor,
College of Agriculture, NAU
Ø Courses teaching
u Agricultural Remote Sensing
(Graduate)
u Crop High Yield Theory and
Technology (Graduate)
Ø Supervisor
of 7 MS students and 1 PhD students
n 2010, 1-2014, 12 Associate Professor,
College of Agriculture, NAU
Ø Courses taught
u
Agricultural Remote Sensing (Graduate)
u
Crop High Yield Theory and Technology (Graduate)
u
Advanced
Crop Informatics (Graduate)
u
Research Progress on Information
Agriculture (Graduate)
u
Introduction to Information
Agriculture (Undergraduate)
Ø Supervisor
of 11 MS students and 3 PhD students
n 2007, 1- 2009, 12
Lecturer, College of
Agriculture, NAU
Ø Courses
taught
u
Introduction
to Information Agriculture (Undergraduate)
u
Crop
High Yield Theory and Technology
(Graduate)
u
Advanced
Crop Informatics (Graduate)
Ø Supervisor
of 2 MS students
n
2004, 7 -2006, 12 Teaching Assistant, College of
Agriculture, NAU
Ø Courses
taught
u
Introduction
to Information Agriculture (Undergraduate)
Ø Supervisor
of 1 MS student
Research Experience
n Principal investigator
Ø
National
Key Research and Development Program of China, Research on advanced remote
sensing monitoring method of agricultural conditions under GEOGLAM framework
Ø
National
Natural Science Foundation, Mechanism and method for estimating the
productivity with solar-induced chlorophyll fluorescence under the stress of
high temperature and drought in wheat
Ø
Key
Research and Development Program of Jiangsu Provincial, Research and
development of high-throughput acquisition technology and system in rice and
wheat crop phenotypes
Ø
National
Natural Science Foundation, Detecting leaf nitrogen status on the sun-induced
chlorophyll fluorescence (SIF) in wheat
Ø
National
Natural Science Foundation, Spectral monitoring mechanism and estimating model
for post-heading leaf senescence in wheat
Ø
Natural
Science Foundation of Jiangsu Province, Study on non-destructive monitoring of
water status in wheat using hyperspectra
Ø
Natural
Science Foundation of Jiangsu Province, Detection of wheat senescence under
heat stress at heading stage from leaf reflectance spectra
Ø
National
Science and Technology Support Plan, Development and application of new sensors
for diagnosis of crop nutrition
Ø
National
High-tech R&D (863) Plan, Development and application of smart management
technology for safe crop production
n Co-investigator
Ø
Science
and Technology Support Plan of Jiangsu Province, Research and development of
rice growth sensing and smart management technology
n Joint investigator
Ø
National Natural Science Foundation of China: Monitoring mechanism and estimation model of
nitrogen nutrition in wheat based on hyperspectra; Monitoring mechanism of nitrogen nutrition in
rice based on reflectance spectra
Ø
PhD Program Grant of
China: The non-destructive monitoring mechanism of
nitrogen nutrition in wheat based on hyperspectra
Ø
Natural Science Foundation of Jiangsu Province: The mechanism of monitoring and diagnosis of crop nitrogen nutrition by
non-destructive method
Ø
High Technology Program
of Jiangsu Province: Monitoring growth status and forecasting productivity in rice
Invention
Patents
(1). A method for
constructing estimation model of leaf area index with three-band vegetation
index in wheat (1/8)
(2). A method for establish
quantitative model of leaf dry weight with continuous wavelet analysis in wheat
(1/10)
(3). A method for crop
growth monitoring with remote sensing images space-time fusion in field scale
(4/7)
(4). A method for
estimation above-ground biomass with unmanned aerial vehicle multi-spectral
image in rice (4/6)
(5). Field crop phenotype
monitoring robot (6/9)
(6). Crop growth sensing apparatus
and method supporting agricultural machinery variable quantity fertilization
operations (6/9)
(7). A model and method for
monitoring water content with different PNC levels in wheat plants (2/7)
(8). A model for monitoring
leaf nitrogen content with canopy hyperspectra as influenced by soil background
in wheat (1/7)
(9).
A method for determining the core band of the shoot uptake nitrogen with
hyperspectra in wheat (1/7)
(10). A method for
monitoring leaf equivalent water thickness with hyperspectrum in wheat (1/7)
(11). A method for
monitoring sugar nitrogen ratio with near infrared spectrum in wheat (2/7)
(12). A method for estimating leaf nitrogen concentration with three-bands vegetation index in rice and wheat (2/7)
(13). A method for estimating plant water content
with hyperspectrum in wheat leaves (2/8)
(14). A method for estimating plant water content
under different nitrogen treatments in wheat (2/7)
Presentations & Poster
l Poster Presentation:
Estimating canopy nitrogen status from hyperspectral parameters of single
leaves in wheat. Annual Meeting of the ASA, CSSA, SSA, Oct. 31 - Nov. 3, 2010. Long
Beach, CA.
l Oral Presentation: Estimating leaf nitrogen
concentration with three-band vegetation indices in rice and wheat. The 5th
High Level Forum of the International Agricultural Science. Nov. 30th,
2012. Beijing, China.
l Poster Presentation:
A new
method
to determine
central
wavelength
and optimal
bandwidth
for predicting
plant
nitrogen
uptake
in wheat.
Annual Meeting of the ASA, CSSA, SSA, Oct. 21 - 24, 2012, Cincinnati, OH.
l Poster Presentation:
Using the leaf area index to quantify the critical nitrogen dilution curve for
winter wheat in eastern China; Monitoring leaf nitrogen content in wheat with
canopy hyperspectra. Annual Meeting of the ASA, CSSA, SSA, Nov 3-6, 2013. Tampa, FL.
l Poster Presentation:
Estimation of leaf
dry
weight
using hyperspectral vegetation indices and continuous wavelet analysis for wheat canopies. Annual Meeting
of the ASA, CSSA, SSA, Nov. 2-5, 2014, Long Beach, CA.
l Poster Presentation: Estimating leaf area index in rice and wheat with continuous wavelet analysis. 2015 IGARSS, July.
26 - 31, 2015, Milan, Italy.
l Poster Presentation: Monitoring Chlorophyll Fluorescence Parameters at
Canopy and Leaf Scales on Hyperspectral Reflectance in Wheat.
IGARSS,
2016. June.
10 - 14, Beijing, China.
l Oral
Presentation:
Estimation of
Wheat LAI at Middle to High Levels using Unmanned Aerial Vehicle Narrowband
Multispectral Imagery. APPPcon, 2018. March.24-26, Nanjing, China
l Oral
Presentation:
Estimation of
Crop growth phenotype on LiDAR. Precision Agriculture Aeronautics International
conference, 2018. June, Shenzhen, China
l Poster Presentation: Monitoring Leaf Nitrogen Content on Chlorophyll
Fluorescence Parameters in Wheat. IGARSS, 2018. June,
Valencia, Spain.
Award
& Honors
l
2021
International
Des Inventions Geneve, - silver award (3th)
l
2018
National Outstand1ing Returned Overseas
Chinese Talents, NAU
l
2016
Outstanding Award of Jiangsu Geography
Union, Jiangsu, China
l
2015
Second Class Award of National Science
and Technology Advancement (4th participant), State Counsel of
China, Number: 2015-J-R04
l
2014
First Class
Award of Science and Technology Advancement for Chinese Universities (4nd
participant), Ministry of Education of China, Number: 2014-04
l
2008 Second Class Award of National Science
and Technology Advancement (9th participant), State Counsel of
China, Number: 2008-J-251-1-22-R09
l
2007 First Class Award of Science and Technology
Advancement for Chinese Universities (8nd participant), Ministry of
Education of China, Number: 2007-173
Memberships
l
Editorial Committee
of International Journal of Precision Agriculture Aeronautics IEEE
l
Editorial
Board Member of Journal of Remote Sensing
l
Geoscience
and Remote Sensing Society
l
Union
of RS and GIS in Jiangsu province, China