Computing Hybrid Rotation Period of Cotton-Rice and Cotton-Others

Article Preview

Abstract:

The aim of this study was to investigate the use of a remote-sensing model to compute a hybrid rotation period of multi-crop rotation in large area. The model was constructed to compute the hybrid rotation period of cotton-rice and cotton-others of 38 towns in XingHua City, Jiangsu Province, China. The rotation periods for cotton-rice and cotton-others were computed as 2.09 and 3.38 years using the data from satellite remote sensing images. The results were shown to lead to a hybrid rotation period of cotton-rice and cotton-others of 1.24 years. This indicates that there is a possibility of managing multi-crop rotation in large area from hybrid rotation periods and suggests that it is possible to measure crop growth status in large area with hybrid rotation periods to make management decision for crop diseases.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

2975-2978

Citation:

Online since:

January 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] B. C. Ball, I. Bingham, R. M. Rees, C. A. Watson, The role of crop rotations in determining soil structure and crop growth conditions [J]. Can J Plant Sci. 2005, 85, 557–577.

DOI: 10.4141/s04-078

Google Scholar

[2] J. M. Krupinsky, K. L. Bailey, M. M. McMullen, et al., Managing plant disease risk in diversi fi ed cropping systems [J]. Agron J, 2002, 94, 198–209.

DOI: 10.2134/agronj2002.1980

Google Scholar

[3] R. P. Larkin, C. W. Honeycutt, O. M. Olanya, et al., Impacts of crop rotation and irrigation on soilborne diseases and soil microbial communities [M]. Sustainable potato production: global case studies. Springer Netherlands, 2012: 23-41.

DOI: 10.1007/978-94-007-4104-1_2

Google Scholar

[4] Y. Yamamoto, T. Oberthür, R. Lefroy, Spatial identification by satellite imagery of the crop–fallow rotation cycle in northern Laos [J]. Environment, Development and Sustainability, 2009, 11(3), 639-654.

DOI: 10.1007/s10668-007-9134-z

Google Scholar

[5] J. Dury, N. Schaller, F. Garcia, et al., Models to support cropping plan and crop rotation decisions. A review [J]. Agronomy for sustainable development, 2012, 32(2), 567-580.

DOI: 10.1007/s13593-011-0037-x

Google Scholar