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    2019, Vol. 18 Issue (02): 340-349     DOI:
Special focus: Digital mapping in agriculture and environment Current Issue | Next Issue | Archive | Adv Search  |   
Using proximal sensor data for soil salinity management and mapping
GUO Yan1, 2, ZHOU Yin2, ZHOU Lian-qing2, 3, LIU Ting1, WANG Lai-gang1, CHENG Yong-zheng1, HE Jia1, ZHENG Guo-qing
1 Institute of Agricultural Economics and Information, Henan Academy of Agricultural Sciences, Zhengzhou 450002, P.R.China
2 Department of Resource Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, P.R.China
3 Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture, Hangzhou 310058, P.R.China
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Over the past five decades, increased pressure caused by the rapidly growing population has resulted in a reclamation of agricultural and urban buffer zones along China’s coastline.  However, information about the spatio–temporal variation of soil salinity in these reclaimed regions is limited.  As such, obtaining this information is crucial for mapping the variation in saline areas and to identify suitable salinity management strategies.  In this study, we employed EM38 data to conduct digital soil mapping of spatio–temporal variation and map these variations of different site-specific zones.  The results indicated that the distribution of soil salinity was heterogeneous in the middle of, and that the leaching of salts was significant at the edges of, the study field.  Afterwards, fuzzy-k means algorithm was used to divide the site-specific management zones within the time series apparent soil electrical conductivity (ECa) data and the spatial correlations of variation.  We concluded that two management zones are optimal to guide precision management.  Zone A had an average salinity level of about 165 mS m–1, in which salt-tolerant crops, such as cotton and barley can grow normally, while crops such as soybean and cowpeas may be planted using leaching and increasing the mulching film methods to reduce the accumulation of salt in surface soil.  In Zone B, there was a low salinity level with a mean of 89 mS m–1 for ECa, which allows for rice, wheat, and a wide range of vegetables to be grown normally.  In such situations, measures such as an optimized combination of irrigation and drainage, as well as soil amendment can be taken to adjust and control the salt content.  Particularly, flattening the land with a large-scale machine was used to improve the ability of micro-topography to influence salt migration; rice and other dry, land crops were planted in rotation in combination with utilizing salt-leaching multiple times to speed up desalinization. 
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ZHOU Lian-qing
LIU Ting
WANG Lai-gang
CHENG Yong-zheng
HE Jia
ZHENG Guo-qing
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Fund: This material is based upon work funded by the National Natural Science Foundation of China (41601213), the National Key Research and Development Program of China (2017YFD0700501) and the Major Science and Technology Projects of Henan, China (171100110600).
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GUO Yan, ZHOU Yin, ZHOU Lian-qing, LIU Ting, WANG Lai-gang, CHENG Yong-zheng, HE Jia, ZHENG Guo-qing. 2019. Using proximal sensor data for soil salinity management and mapping. Journal of Integrative Agriculture, 18(02): 340-349.
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[1] Kishk Abdelmageed, CHANG Xu-hong, WANG De-mei, WANG Yan-jie, YANG Yu-shuang, ZHAO Guang-cai, TAO Zhi-qiang. Evolution of varieties and development of production technology in Egypt wheat: A review[J]. Journal of Integrative Agriculture, 2019, 18(3): 483-495.
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