Assessing Spatio-Temporal Variability of Soil Phosphorus in Different Cotton-Based Cropping Systems Using Geo-Statistics-Reference-Cited by-同舟云学术

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Assessing Spatio-Temporal Variability of Soil Phosphorus in Different Cotton-Based Cropping Systems Using Geo-Statistics

Published:2023-06-12 Issue:3 Volume:23 Page:3271-3280
ISSN:0718-9508
Container-title:Journal of Soil Science and Plant Nutrition
language:en
Short-container-title:J Soil Sci Plant Nutr

Author:

Teng Li,Shiwu Xiong,Zhanbao Wang,Xiaofei Li,Yingchun Han,Guoping Wang,Yaping Lei,Lu Feng,Beifang Yang,Xiaoyu Zhi,Zhengyi Fan,Yabing Li

Publisher

Springer Science and Business Media LLC

Subject

Plant Science,Soil Science,Agronomy and Crop Science

Link

https://link.springer.com/content/pdf/10.1007/s42729-023-01241-3.pdf

Reference37 articles.

1. Arbia G (2014) Pairwise likelihood inference for spatial regressions estimated on very large datasets. Spat Stat 7:21–39. https://doi.org/10.1016/j.spasta.2013.10.001

2. Baroni G, Ortuani B, Facchi A, Gandolfi C (2013) The role of vegetation and soil properties on the spatio-temporal variability of the surface soil moisture in a maize-cropped field. J Hydrol 489:148–159. https://doi.org/10.1016/j.jhydrol.2013.03.007

3. Feng L, Wang GP, Han YC, Li YB, Zhu Y, Zhou ZG, Cao WX (2017) Effects of planting pattern on growth and yield and economic benefits of cotton in a wheat-cotton double cropping system versus monoculture cotton. Field Crops Res 213:100–108. https://doi.org/10.1016/j.fcr.2017.07.003

4. Fixen PE, Grove IA (1990) Testing soils for phosphorus. Madison WI ASA and SSSA

5. Fortin MJ, James PM, Mackenzie A, Melles SJ, Rayfield B (2012) Spatial statistics, spatial regression, and graph theory in ecology. Spat Stat 1:100–109

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