Use of apparent soil electrical conductivity to improve sugarcane nutrient management in Florida

被引:0
作者
Sandhu, Hardev S. [1 ]
Singh, Maninder P. [1 ]
McCray, James M. [1 ]
机构
[1] Univ Florida, Everglades Res & Educ Ctr, Belle Glade, FL 33430 USA
来源
INTERNATIONAL SUGAR JOURNAL | 2018年 / 120卷 / 1439期
关键词
precision agriculture; soil EC; soil variables; Pearson correlation; soil pH; sugarcane; ELECTROMAGNETIC INDUCTION; VARIABILITY;
D O I
暂无
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Precision agriculture is considered to be one of the most promising approaches for sustainable farming, but it requires efficient methods for accurately measuring within-field variations in soil physical and chemical properties. Apparent soil electrical conductivity (ECa) is a quick indirect measurement of soil EC with a sensor (e.g. EM-38), and the latter is used to determine spatial variations of this parameter in the field without extensive soil sampling. Correlation of ECa values with different soil nutrients in organic and mineral soils in southern Florida can help in determining its potential use to improve nutrient management in sugarcane. Data on ECa and different soil variables were collected from several 5-15 ha fallow sugarcane fields in Palm Beach (organic soil, Histosols) and Hendry (mineral soil, Entisols) counties of Florida in 2014 and 2015. Soil samples were analyzed for pH, P, Ca, Mg, S and Si in soil testing lab at the Everglades Research and Education Centre, Belle Glade. In organic soils, the bulked soil data showed significant correlations between ECa and each of soil pH (r=0.72), Mg (r=0.62), Si (r=0.52) and Ca (r=0.35). In mineral soils, there were significant correlations between ECa and each of pH (r=0.75), PMehlich-3 (r=0.73), Ca (r=0.58), and Si (r=0.46). Grouping the fields into different zones based on their location changed the correlations for the tested variables. PC-stepwise regression analysis indicated that soil pH was the major contributor to the variability in soil ECa in both soil types. Results showed that the correlations between ECa and the measured soil parameters were not consistent through all the tested zones or the fields. Therefore, ECa may be more precisely used in management of these parameters at zonal or field level. In bulk soil, the correlations between ECa and soil pH were highest in both soils and that supports the need of further exploration of ECa maps in soil pH management across a wide range of sugarcane fields in Florida. Alternatively, ECa may be used in conjunction with soil sampling to determine the spatial variability of the soil variables and thereafter be used for precise management of different nutrients. Further research is needed to determine the relationship between ECa and sugarcane yield, and for the use of yield maps in ECa map calibrations.
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页码:868 / 873
页数:6
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