Message

In recent years, various information technologies (IT) have been widely applied in agriculture. By making full use of IT technologies, it is possible to quickly and non-destructively collect various information about the objects (soil, environment, crop, product, etc.) in agriculture. This makes it possible to predict, evaluate and visualize various information about the observed objects. These IT technologies are expected to make remarkable progress in various agricultural fields from basic research to practical application, including monitoring of soil environment, control of crop production and postharvest quality evaluation of agricultural products and foods.

Let’s enjoy research in this field together!

Research Theme

1）Applications of multi-platform, multi-sensor remote sensing technologies in agriculture

2) Development of nondestructive sensing techniques and mobile devices for crop growth monitoring and postharvest agro-products quality evaluation

Education & Appointments

1989.09-1993.07, Zhejiang University, China, B.Sc. in Agronomy

1993.09-1996.07, Zhejiang University, China, M.Sc. in Ecology

2002.10-2007.03, Tokyo University of Agriculture and Technology, Japan, PhD in Agricultural Engineering

1996.07–2003.09, Zhejiang University, China, Lecturer

2007.04–2008.07, The University of Tokyo, Japan, JSPS postdoctoral research fellow

2008.08–2013.3, Zhejiang University, China, Associate professor

2012.5-2013.3, Tokyo University of Agriculture and Technology, Japan, JSPS Visiting professor

2013.04-present, Hirosaki University, Associate professor

Publications

1. Xujun Ye, Kenshi Sakai (2013). Limited and time-delayed internal resource allocation generates oscillations and chaos in the dynamics of citrus crops. Chaos, 23: 043124. IF: 1.954. 
2. Xujun Ye, Jinmeng Li, K. Sakai, Tiejun Zhao (2013). Estimation and visualization of nitrogen content in citrus canopy using hyperspectral imagery. Proceedings of IEEE 5rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013.
3. Tiejun Zhao, K. Sakai, T. Higashi, M. Komatsuzaki, Xujun Ye (2013). Application of portable hyper-spectral camera in Andisol soils nitrogen assessment. Proceedings of IEEE 5rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013.
4. X. Ye, K. Sakai (2013). Limited and time-delayed internal resource allocation generates oscillations and chaos in the dynamics of citrus crops. Chaos, 23, 043124, 2013.
5. J. Li, X. Ye, Q. Wang, C. Zhang, Y. He (2014). Development of prediction models for determining N content in citrus leaves based on hyperspectral imaging technology. Spectroscopy and Spectral Analysis, 34(1): 212-216, 2014.
6. X. Ye, Y. Shi, M. Sun, S. Zhang (2014). Non-destructive Prediction of Hardness of Carrots using Hyperspectral Imaging. No. 2014-0870, 18th World Congress of CIGR, Beijing, September 2014.
7. D. Zhang, M. Sun, X. Ye, S. Zhang (2014). Study on the Optical Non-destructive Quality Detection Method of Mini-watermelon. No. 2014-1012, 18th World Congress of CIGR, Beijing, September 2014.
8. Wang Q., Ye X., Li J., Xiao Y., He Y. (2015). Estimation and visualization of nitrogen content in citrus canopy based on two band vegetation index (TBVI). Spectroscopy and Spectral Analysis, 35(3): 715-718, 2015. 
9. Ye X., Iino K., Zhang S., Oshita S. (2015). Nondestructive monitoring of chicken meat freshness using hyperspectral imaging technology. Proceedings of IEEE 7rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2-5 June 2015, Tokyo, Japan.
10. Xujun Ye, Kenshi Sakai (2015). Application of hyperspectral imaging in Agriculture. The Journal of The Institute of Image Information and Television Engineers, 69(5): 464-469.
11. Xujun Ye, Kenshi Sakai (2016). A new modified resource budget model for nonlinear dynamics in citrus production. Chaos, Solitons and Fractals, 87: 51-60. IF: 1.448.
12. Xujun Ye, Kanako Iino, Shuhuai Zhang (2016). Monitoring of bacterial contamination on chicken meat surface using a novel narrowband spectral index derived from hyperspectral imagery data. Meat Science, 122: 25–31. IF: 2.801.
13. Ye X., Y. Shi, S. Zhang (2016). Non-destructive prediction of hardness and carotenoid content of carrots using hyperspectral imaging. Agricultural Research Updates, Volume 12, Chapter 3, Pages 57–70, ISBN: 978-1-63483-967-9, Nova Science Publishers.
14. Ye, X., T. Izawa, S. Zhang (2016). Development of an Android Application for Determination of Lycopene Content in Tomato Fruit. International Symposium on Machinery and Mechatronics for Agricultural and Biosystems Engineering (ISMAB 2016), Niigata, Japan, 23-25 May 2016.
15. Xujun Ye, Kenshi Sakai (2016). Comparison of Resource Budget Models for Nonlinear Dynamics in Alternate Bearing of Tree Crops. 2016 International Symposium on Nonlinear Theory and Its Applications, NOLTA2016, Yugawara, Japan, November 27th-30th, 2016.
16. Xujun Ye, Shyota Ishioka, Shuhuai Zhang (2017). Estimation of the degree of red coloration in flesh of a red-fleshed apple cultivar 'Kurenai no Yume' with a UV-Vis-NIR interactance device. Postharvest Biology and Technology, 124: 128-136. IF: 2.618.
17. Zhou Li-ping, Zhao Yan-ru, Yu Ke-qiang, He Yong, Fang Hui, Ye Xu-jun (2017). Hyperspectral Technique for Estimating the Shelf-Lives of Fresh Spinach Leaves Covered with Film. Spectroscopy and Spectral Analysis, Vol. 37, No. 2, pp. 423-428.

Laboratory

Faculty member

Professor: ZHANG Shu-huai

Associate Professor: YE Xu-Jun

Main research interests:

• Smart agriculture technologies
• Crop nutrient diagnosis using multi- and hyper-spectral imaging devices
• Poultry/meat freshness and quality evaluation using hyper-spectral imaging
• Development of mobile apps for rapid fruit quality and maturity grading
• Development of mobile devices for fast crop health evaluation
• Development of new methods for fruit discrimination and yield prediction