Soil apparent conductivity measurements for planning and analysis of agricultural experiments: A case study from Western-Thailand

In experimental trials, the success or failure of agricultural improvements is commonly evaluated on the agronomic response of crops, using proper experimental designs with sufficient statistical power. Since fine-scale variability of the experimental site can reduce statistical power, efficiency gains in the experimental design can be achieved if this variation is known and used to design blocking, or some proxy variable is used as a covariate. Near-surface geophysical techniques such as electromagnetic induction (EMI), which describes subsurface properties non-invasively by measuring soil apparent conductivity (ECa), may be one source of this information. The motivation of our study was to investigate the effectiveness of EMI-derived ECa measurements for planning and analysis of agricultural experiments. ECa and plant height measurements (the response variable) were taken from an agroforestry experiment in Western Thailand, and their variability was quantified to simulate multiple realizations of ECa and the residuals of the response variable from treatment means. These were combined to produce simulated data from different experimental designs and treatment effects. The simulated data were then used to evaluate the statistical power by detecting three orthogonal contrasts among the treatments in the original experiment. We considered three experimental designs, a simple random design (SR), a complete randomized block design (CRB), and a complete randomized block design with spatially adjusted blocks on plot means of ECa (CRBECa). Using analysis of variance (ANOVA), the smallest effect sizes could be detected with the CRBECa design, which indicates that ECa measurements could be used in the planning phase of an experiment to achieve efficiencies by improved blocking. In contrast, analysis of covariance (ANCOVA) demonstrated that substantial power improvements could be gained when ECa was considered as a covariate in the analysis. We therefore recommend that ECa measurements should be used to characterize subsurface variability of experimental sites and to support the statistical analysis of agricultural experiments

Can we use electrical resistivity tomography to measure root zone dynamics in fields with multiple crops?

status: publishe

Non-invasive monitoring of soil water dynamics in mixed cropping systems: A case-study in Ratchaburi province, Thailand

Agriculture on shallow or steep soils in the humid tropics often leads to low resource use efficiency. Contour hedgerow intercropping systems have been proposed to reduce run-off and control soil erosion. However, competition for water and nutrients between crops and associated hedgerows may reduce the overall performance of contour hedgerow systems. Electrical resistivity tomography (ERT) is a valuable technique used to assess the distribution and dynamics of soil moisture noninvasively. In this study, we demonstrated its potential to measure soil water depletion in the field in distinct cropping patterns in Ratchaburi province, Thailand. The measurements showed that the soils of our experimental plots were very heterogeneous both along the slope as with depth. This observation highlighted some constraints of the ERT method for soil moisture monitoring in the field, such as the difficulty of defining a relationship between electrical conductivity and soil moisture in very heterogeneous soils. Nevertheless, spatial analysis of the data revealed contrasting water depletion patterns under monocropping and intercropping systems. In this way, ERT provides access to information about the vadose zone moisture dynamics that would be unavailable with classical soil moisture measurements