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Liu, P
Qian, J
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Authors
Sun, C
Ji, Z
Qian, J
Li, M
Zhao, L
Li, W
Zhou, C
Du, X
Xie, J
Wu, T
Qu, L
Hao, L
Yang, X
Yang, X
Sun, C
Qian, J
Ji, Z
Qiao, S
Chen, M
Zhao, C
Li, M
Yang, X
Li, M
Sun, C
Qian, J
Ji, Z
Chen, M
Li, M
Qian, J
Li, W
Wang, Y
Zhang, Y
Yang, X
Zhen, X
Miao, Y
Feng, G
Huang, Y
Yang, Z
Liu, P
Bindish, R
Topics
Information Management and Traceability
Precision Crop Protection
Information Management and Traceability
Precision Horticulture
Weather and Models for Precision Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2024
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Authors

Filter results5 paper(s) found.

1. Towards a Multi-Source Record Keeping System for Agricultural Product Traceability

Agricultural production record keeping is the basis of traceability system. To resolve the problem including single method of information acquisition, weak ability of real-time monitoring and low credibility of history information in agricultural production process, the... C. Sun, Z. Ji, J. Qian, M. Li, L. Zhao, W. Li, C. Zhou, X. Du, J. Xie, T. Wu, L. Qu, L. Hao, X. Yang

2. Modeling and Decision Support System for Precision Cucumber Protection in Greenhouses

The plant disease... X. Yang, C. Sun, J. Qian, Z. Ji, S. Qiao, M. Chen, C. Zhao, M. Li

3. Traceability And Management Information System Of Agricultural Product Quality Safety In China

Agricultural product quality safety is the hot topic in the world. From the technical view, the agricultural production management and traceability are the key measurement for insuring the quality safety. From 2005 until now, we have been investigating... X. Yang, M. Li, C. Sun, J. Qian, Z. Ji

4. Study On The Automatic Monitoring Technology For Fuji Fruit Color Based On Machine Vision

  Fruit color is one of the important indicators of quality and commodities. Three kinds of the traditional methods are used to evaluate fruit color, including artificial visual identification, fruit standard color cards and color measurement instrument. These methods are needed to be conducted in the field by persons, which are time-consuming and labored, and also difficult to obtain the dynamic color information of the target fruits in the growth process. This study developed... M. Chen, M. Li, J. Qian, W. Li, Y. Wang, Y. Zhang, X. Yang

5. Evaluating the Potential of In-season Spatial Prediction of Corn Yield and Responses to Nitrogen by Combining Crop Growth Modeling, Satellite Remote Sensing and Machine Learning

Nitrogen (N) is a critical yield-limiting factor for corn (Zea mays L.). However, over-application of N fertilizers is a common problem in the US Midwest, leading to many environmental problems. It is crucial to develop efficient precision N management (PNM) strategies to improve corn N management. Different PNM strategies have been developed using proximal and remote sensing, crop growth modeling and machine learning. These strategies have both advantages and disadvantages. There is... X. Zhen, Y. Miao, K. Mizuta, S. Folle, J. Lu, R.P. Negrini, G. Feng, Y. Huang