Accounting for heterogeneity in the θ–σ relationship: Application to wheat phenotyping using EMI

Blanchy, Guillaume; Watts, C. W.; Ashton, R. W.; Webster, Collin A.; Hawkesford, Malcolm J.; Whalley, W. R.; Binley, Andrew

doi:10.1002/vzj2.20037

Cited by 13 publications

(7 citation statements)

References 41 publications

(61 reference statements)

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“…Similar spatial heterogeneities of the EC a (θ v ) relationship at the field scale related to crop varieties have been found by Blanchy et al. (2020), who suggested using plot‐specific parameters that can be estimated from baseline measurements. In our case, the variability in EC a was much greater compared with the crop‐specific θ v predictions.…”

Section: Discussionsupporting

confidence: 78%

“…Researchers have begun to exploit time-lapse EMI to study intraseason soil water use within-and across plant species such as chickpeas (Cicer arietinum L.; Huang, Purushothaman, McBratney, & Bramley, 2018) and wheat (Triticum aestivum L.; Shanahan, Binley, Whalley, & Watts, 2015). Time-lapse measurements of EC a have further been used to quantify root activity in wheat, as demonstrated by Whalley et al (2017) and Blanchy et al (2020). Other examples of the use of EMI in crop water use studies include Cassiani et al (2012), who demonstrated positive feedbacks in EC a between soil and root development, as well as water uptake; Yao et al (2016), who suggested the need for long-range EMI surveys and data collection to capture the spatial and temporal variability of soil and crop yield; and Moghadas, Jadoon, and McCabe (2017), who used EMI to study temporal root zone soil moisture variations with depth.…”

Section: Core Ideasmentioning

confidence: 99%

“…(2017) and Blanchy et al. (2020). Other examples of the use of EMI in crop water use studies include Cassiani et al.…”

Section: Introductionmentioning

confidence: 96%

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Time‐lapse mapping of crop and tillage interactions with soil water using electromagnetic induction

Brown

Heinse

Johnson‐Maynard

et al. 2021

Vadose Zone Journal

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Assessing spatiotemporal variations in soil water is critical to many decisions in precision agriculture. In dryland crop production regions with marginal precipitation, growers use crop rotations and surface preparation practices to build soil water natural capital over preceding seasons for cash crop production. However, significant gaps exist in quantifying linkages between topography, soil properties, and sitespecific agronomic practices to crop water use, and to predict temporal changes in soil water storage. In this study, we used time-lapse electromagnetic induction to measure apparent electrical conductivity (EC a ) to infer spatiotemporal variability of soil water while comparing crop (winter wheat [Triticum aestivum L.], spring peas [Pisum sativum L.], and spring barley [Hordeum vulgare L.]) as well as tillage (no till and chisel plow) on a split-plot design in the Palouse region of northern Idaho. Weekly measurements of EC a were converted to soil water content using multiple linear regression with the help of principal component analysis. Separating factors of temporal stability and variability allowed us to derive crop-specific calibrated relationships between soil water content and the additional variables growing degree days, elevation, clay content, and silt content. Results suggest that spring peas retained the highest water content, followed by spring barley and winter wheat. Resultant maps show highly structured and consistent patterns in EC a being driven primarily by crop type that are apparent even in uncalibrated imagery. Although soil EC a tended to be greater in no-tillage compared with chisel plow treatments, we found no significant differences in soil water content between the two. This may be partially due to the limited number of years of no-till practice at this site.

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Section: Discussionsupporting

confidence: 78%

Section: Core Ideasmentioning

confidence: 99%

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Time‐lapse mapping of crop and tillage interactions with soil water using electromagnetic induction

Brown

Heinse

Johnson‐Maynard

et al. 2021

Vadose Zone Journal

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“…In this study, ECa values were corrected using

E {normalC}_{25} = \frac{E {normalC}_{normalT}}{1 + 0.02 (T - 25)}

where EC 25 is the temperature corrected EC (at 25 °C), and T is the soil temperature (°C). When soil temperature profiles were available (all studies except the compaction case), a depth‐weighted temperature was computed using the cumulative sensitivity function of the EMI instrument (Blanchy, Watts, et al., 2020). This “apparent” temperature was then used in Equation to correct the ECa values.…”

Section: Methodsmentioning

confidence: 99%

Time‐lapse geophysical assessment of agricultural practices on soil moisture dynamics

Blanchy

Watts

Richards

et al. 2020

Vadose Zone Journal

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Geophysical surveys are now commonly used in agriculture for mapping applications. High-throughput collection of geophysical properties such as electrical conductivity (inverse of resistivity) can be used as a proxy for soil properties of interest (e.g., moisture, texture, salinity). Most applications only rely on a single geophysical survey at a given time. However, time-lapse geophysical surveys have greater capabilities to characterize the dynamics of the system, which is the focus of this work. Assessing the impact of agricultural practices through the growth season can reveal important information for the crop production. In this work, we demonstrate the use of time-lapse electrical resistivity tomography (ERT) and electromagnetic induction (EMI) surveys through a series of three case studies illustrating common agricultural practices (cover crops, compaction with irrigation, and tillage with N fertilization). In the first case study, time-lapse EMI reveals the initial effect of cover crops on soil drying and the absence of effect on the subsequent main crop. In the second case study, compaction leading to a shallower drying depth for potatoes (Solanum tuberosum L.) was imaged by timelapse ERT. In the third case study, larger changes in electrical conductivity over time were observed in conventional tillage compared with direct drill using timelapse EMI. In addition, different N application rates had a significant effect on the yield and leaf area index but only ephemeral effects on the dynamics of electrical conductivity, mainly after the first application. Overall, time-lapse geophysical surveys show great potential for monitoring the impact of different agricultural practices that can influence crop yield.

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“…Surface based geophysics is an alternative that offers a wide range of tools based on different physical principles (electrical, electromagnetic, seismic, gravimetric, and magnetic), [19]. In agronomy and soil sciences, geophysics has entered the list of commonly used tools [20][21][22]. Garré et al [23] define the term agrogeophysics.…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic Induction Is a Fast and Non-Destructive Approach to Estimate the Influence of Subsurface Heterogeneity on Forest Canopy Structure

Carrière

Martin‐StPaul

Doussan

et al. 2021

Water

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The spatial forest structure that drives the functioning of these ecosystems and their response to global change is closely linked to edaphic conditions. However, the latter properties are particularly difficult to characterize in forest areas developed on karst, where soil is highly rocky and heterogeneous. In this work, we investigated whether geophysics, and more specifically electromagnetic induction (EMI), can provide a better understanding of forest structure. We use EMI (EM31, Geonics Limited, Ontario, Canada) to study the spatial variability of ground properties in two different Mediterranean forests. A naturally post-fire regenerated forest composed of Aleppo pines and Holm oaks and a monospecific plantation of Altlas cedar. To better interpret EMI results, we used electrical resistivity tomography (ERT), soil depth surveys, and field observations. Vegetation was also characterized using hemispherical photographs that allowed to calculate plant area index (PAI). Our results show that the variability of ground properties contribute to explaining the variability in the vegetation cover development (plant area index). Vegetation density is higher in areas where the soil is deeper. We showed a significant correlation between edaphic conditions and tree development in the naturally regenerated forest, but this relationship is clearly weaker in the cedar plantation. We hypothesized that regular planting after subsoiling, as well as sylvicultural practices (thinning and pruning) influenced the expected relationship between vegetation structure and soil conditions measured by EMI. This work opens up new research avenues to better understand the interplay between soil and subsoil variability and forest response to climate change.

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Accounting for heterogeneity in the θ–σ relationship: Application to wheat phenotyping using EMI

Cited by 13 publications

References 41 publications

Time‐lapse mapping of crop and tillage interactions with soil water using electromagnetic induction

Time‐lapse mapping of crop and tillage interactions with soil water using electromagnetic induction

Time‐lapse geophysical assessment of agricultural practices on soil moisture dynamics

Electromagnetic Induction Is a Fast and Non-Destructive Approach to Estimate the Influence of Subsurface Heterogeneity on Forest Canopy Structure

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