44. Combining crop growth modeling, active sensing and machine learning to improve in-season nitrogen management of maize-Reference-Cited by-同舟云学术

44. Combining crop growth modeling, active sensing and machine learning to improve in-season nitrogen management of maize

Published:2023-07-02 Issue: Volume: Page:
ISSN:
Container-title:Precision agriculture ’23
language:
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Author:

Wang X.¹,Miao Y.²,Dong R.³,Mi G.⁴,Kusnierek K.⁵,Batchelor W.D.⁶

Affiliation:

1. Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Key Laboratory of Crop Physiology & Ecology, Ministry of Agriculture, Beijing, 100081, China.

2. Precision Agriculture Center, Department of Soil, Water and Climate, University of Minnesota, St. Paul., MN, 55108, USA.

3. Institute of Tobacco Research, Chinese Academy of Agricultural Sciences, Qingdao, 266101, China.

4. College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China.

5. Center for Precision Agriculture, Norwegian Institute of Bioeconomy Research (NIBIO), Nylinna 226, 2849 Kapp, Norway.

6. Biosystems Engineering Department, Auburn University, Auburn, AL, 36849, USA.

Publisher

Wageningen Academic Publishers

Link

https://www.wageningenacademic.com/doi/pdf/10.3920/978-90-8686-947-3_44

Reference20 articles.

1. Abraham, A., Pedregosa, F., Eickenberg, M., Gervais, P., Mueller, A., Kossaifi, J. et al. 2014. Machine learning for neuroimaging with scikit-learn. Frontiers in Neuroinformatics 8, 14.

2. Cassman, K.G., Dobermann, A., Walters, D.T. 2002. Agroecosystems, nitrogen-use efficiency, and nitrogen management. AMBIO: A Journal of the Human Environment 31(2), 132-140.

3. In-Season Diagnosis of Winter Wheat Nitrogen Status in Smallholder Farmer Fields Across a Village Using Unmanned Aerial Vehicle-Based Remote Sensing

4. Colwell, J.D. 1994. Estimating fertilizer requirements: A quantitative approach. Centre for Agriculture and Bioscience International: Wallingford, UK.

5. Cummings, C., Miao, Y., Kang, S. & Stueve, K. 2021. Developing a remote sensing and calibration strip-based in-season nitrogen management strategy for corn. In: Stafford, J.V. (ed.) Precision Agriculture’21: Proceedings of the 13th European Conference on Precision Agriculture. Wageningen, Netherlands: Wageningen Academic Publishers, pp. 535-541.