Predicting soil ECe based on values of EC1:2.5 as an indicator of soil salinity at Magozi irrigation scheme, Iringa, Tanzania.
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Date
2021
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Sokoine University of Agriculture
Abstract
Soil salinity is one of the limitations to sustainable production of rice and other crops in many irrigation schemes in Tanzania. Soil salinity can be assessed from electrical conductivity (EC) measurements. Most soil laboratories in Tanzania appraise soil salinity from measurements of electrical conductivity of 1:2.5 soil:water suspensions (EC1:2.5) by virtue of their simplicity. However, the influence of soil salinity on plant growth is mainly based on electrical conductivity of saturated paste extract (ECe), so it is necessary to convert EC1:2.5 to ECe in order to assess plant response to salinity. This study was conducted at Magozi Irrigation Scheme in Iringa Region, Tanzania to establish regression model for predicting ECe from EC1:2.5 values. A total of 60 soil samples (45 samples for model training and 15 samples for model validation) were collected and analyzed for soil EC1:2.5, ECe and soil texture. Results showed that EC1:2.5 ranged from 0.1 to 4.2 dS m-1 with a mean value of 0.71 dS m-1. EC obtained ranged from 0.3 (non-saline) to 12 dS m-1 (very
e
saline) with a mean of 2.4 dS m-1 (slightly saline). In order of dominance, soil textural classes were
sandy clay loam, clay, sandy clay, sandy loam and clay loam. Strong linear relationships between ECe and EC1:2.5 were observed in the developed linear regression equations. After validation, the study selected equation ECe = 3.4954*EC1:2.5 with R2 of 0.956 for combined soil textures to be used for prediction of ECe from EC1:2.5 at Magozi Irrigation Scheme. This model can be tested for its applicability to other similar soils in Tanzania in further studies.
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Keywords
Soil salinity, ECe, EC1:2.5, Magozi Irrigation Scheme, soil salinity prediction