University of Reading
Continuous, large-scale, dynamic soil moisture mapping to capture root growth and dynamic water use traits in field conditions
Total Funds Requested
Water use efficiency is a key trait that the crop science community must address to be able to breed crops capable of coping with a warming climate, and ever more extreme and uncertain variable precipitation and drought events. Nowadays, the transpirative and photosynthetic demand of a plant or crop stand can readily be estimated via a series of direct and indirect phenotyping methods. However, the extent to which the plant or crop root system utilises and/or conserves soil moisture available to it through a season is not currently something which can be measured easily. The gambit of this proposal is that we have identified Active Distributed Temperature Sensing (Active DTS) as a technology that has the capability to turn whole fields into virtual lysimeter arrays, allowing high temporal and spatial resolution by mapping of water use across many hundreds of plots through the whole season under field conditions, on undisturbed soil and under actual agronomic practices. We propose that automated dynamic soil moisture mapping can be used as a powerful new below-ground field phenotyping tool to move plant and crop research on from its current reliance on a combination of low-to-moderate throughput imaging (e.g., shovelomics, rhizotrons, X-ray computed tomography) and physical measures (e.g., lysimeters) to actually capture season-long continuous water use on undisturbed soil reflecting root growth and water use dynamics. Challenges this pilot project will address include system parameter optimization, validation of robust calibration routines, and multiscale data management and analysis. The proposed work will support an early career researcher at Reading and the results from this study will advance the capabilities and knowledge in field phenotyping, plant physiology and crop breeding.
Water use strategies and availability are important under water limiting conditions, but they are traits that also present strong interactions with the cross-tolerance to most abiotic and biotic stressors. As a well-studied example, water limitations on UK wheat production on an average year cause losses of 1-2 t / ha (equivalent to 12-20% of potential production) with a loss of c.£72 million (Foulkes et al, 2007, Ober et al, 2014). However, there are considerably more losses in severe drought years or when the timing of water limitations matches sensitive stages of crop development. Indeed, climate-crop modelling indicates that the likelihood of drought affecting wheat reproductive development is on an increasing trajectory across large parts of Europe (Senapati et al, 2019), making drought tolerance and water use efficiency key breeding targets to secure robust yields. As the ability of roots to extract soil moisture is critical for maintaining yields during drought, selection for genotypes that can better access soil water should improve yield stability in increasingly variable rainfall environments (Ober et al, 2014). Crop breeding programmes therefore urgently require high-throughput phenotyping tools which sensitively and specifically measure crop water use traits, and which can be validated within real-life production environments.
Current water use phenotyping relies on low-to-moderate throughput measures of root system architecture (by imaging techniques) or punctual physical quantification of water in soil (lysimeters, soil water potential and content sensors). Other functional measures of water use efficiency are indirect, expensive and/or have limited temporal resolution (e.g., isotopic discrimination, gas-exchange, canopy temperature, spectral emission, root system capacitance). Notably (other than few very low throughput very large scale lysimeters), no current technique can provide non-invasive continuous direct measures of Soil Water Content (SWC) with a dense enough spatial sampling to capture both the dynamics of water extraction by actively growing plant root systems, and to measure and compensate for the high variability of undisturbed soil in the field. Validation of the phenotypes targeted by crop breeding programmes within real-life production environments is essential. For example, there is a lack of detailed studies of the real SWC distribution during recharge events (irrigation and precipitation) and their interaction with root system architecture, mainly due to the difficulties to gather SWC measurements with high spatial and temporal resolution (Rodríguez-Sinobas et al, 2021). A phenotyping tool with this capacity would open the opportunity to not only study and breed more efficiently for water use traits, but to also evaluate the impact of any combination of crop, soil and cropping system management practices and techniques (e.g., crop cover, rotations, irrigation systems).
Distributed Temperature Sensing (DTS) systems for soil water content determination
DTS systems are distributed optoelectronic devices that work by sending a laser light pulse down the optical fibre and collecting the temperature-dependant backscattered light (Fig 1). Combined with time-of-flight of the signal, the DTS receptor provides many spatially distributed precise temperature readings thorough the fibre length in milliseconds. Temperatures are recorded along the optical sensor cable, thus not at points, but as a continuous profile with a high accuracy. Typically, the DTS systems can locate the temperature to a decimetre spatial resolution with accuracy to within ±1°C at a resolution of 0.01°C in fibres of up to many kilometres in length.
Figure 1. Distributed Temperature Sensing principles. A: XT-DTS extreme DTS for remote environments supplied by Silixa, UK and installed at the University of Reading; B: DTS principle (adapted from Murphy 2015).
In A-DTS systems, embedded heating elements generate controlled pulses of heat through the optical fibre. By monitoring the heating and cooling dynamics through time, one can monitor the thermal conductivity of the immediate environment around the fibre. These changes in thermal conductivity of the soil are directly correlated to SWC. The sensing cable and heating system have no moving parts and design lives of at least 30 years. Thus, maintenance and operation costs are considerably less than for arrays of conventional sensors. Once installed and calibrated it only needs an electrical supply. These features make A-DTS an ideal, yet untested technology for continuous long-term crop monitoring.
Recent studies report optimization of heating pulse parameters under controlled conditions for SWC determination (Abesser et al, 2020; Vidana Gamage et al, 2018, 2021). Based on these, recent works have shown efforts for developing multiscaling and inference analysis of SWC from A-DTS pilot systems implemented in the field, focused on spatial variability of brief irrigation events (Rodríguez-Sinobas et al, 2021; Zubelzu et al, 2019) or the dynamics of a forested slope (Abesser et al, 2020). However, the ability to capture and characterise the impact of functional water use traits in a rainfed crop via A-DTS systems is so far unrealised, most likely because of the first non-obvious technical challenge of inserting a long cable run deep into the soil without disturbing the soil profile.
We have solved this technical hurdle and installed a pilot system consisting of almost 1 km of a state-of-the-art DTS cable inserted with minimum disturbance of soil profile at the University of Reading experimental farm in Sonning (Berkshire, UK). Thanks to the long agricultural engineering experience and fabrication skills of the University of Reading Crop Research Unit staff, we were able to modify a subsoiler/paraplow to make a narrow, angled cut into the soil profile to a depth of 50 cm with a spooled cable feed running behind the fresh cut inserting the cable to a constant depth below the soil surface (Fig 2A,C). By digging out trenches at opposite ends of each cable run, we were able to lift the subsoiler, turn and reinsert the unbroken cable into further parallel runs 5 m apart in a looped arrangement – resembling underfloor heating – and to demonstrate that the 1 km optic path was unbroken after laying was complete and row-end trenches filled back in (Fig 2B). If this pilot project is successful, future installations could involve simultaneous laying of cables at multiple depths e.g., 30 + 45 + 60cm. Cable laying was accomplished in September 2020, leaving an entire winter for any minimal disturbance of the soil to settle back. In March 2021, a uniform spring oat crop was drilled over the 0.36 ha A-DTS array. In total, the system consists of 14 x 52 m runs permitting us to have a length of 2 m cable run across the centre of (14 x 26 =) 364 plots measuring 5 x 2 m (which is the standard size of plot used at University of Reading to evaluate yield of annual combinable crops), setting the scene for this pilot project to explore how functional water use traits can be inferred from plot-level SWC dynamics. Sonning experimental farm is a well-established and highly instrumented field site combining large-scale irrigation, rainout shelters, mobile above-ground phenotyping, and environmental sensing; as well as a hosting a meteorological station within 100 m of the A-DTS cable termination. The exact parcel into which the A-DTS array has been installed has previously been used in 2014/15 to map QTL for wheat root length density in the field (Clarke et al, 2019), and it presents a free-draining deep sandy loam soil where previous irrigated trials in a neighbouring field have shown a strong discrimination between genotypes and limited spatial effects (Amer, 2020).
Figure 2. Active Distributed Temperature Sensing installation in Sonning experimental farm (Berkshire, UK). A: installation with minimal disturbance of soil profile using a tractor-mounted modified paraplow; B: A-DTS cable route marked out in red over an aerial image of the field during installation showing excavated row-end trenches allowing turning and reinsertion of the cable every 5m; white dashed boxes show how a row of 14 plots sits with 2 m of cable running transversally across the centre of each plot; C: schematic diagram showing how the optic fibre cable is inserted with an intact soil profile above.
During the current 2021 spring cropping season, a uniform oat crop was planted to assess baseline spatial heterogeneity. From Autumn 2021, the system will be ready to accommodate plot experiments required to screen for genotypic variation and effect of treatments. We have identified three immediate use cases that would greatly benefit from high-throughput continuous phenotyping of water use in the field. In the first two use cases, QTL for response to water limitation/drought tolerance have been recently identified in: (i) the NIAB elite winter wheat 8-parent MAGIC RIL population (work conducted at University of Reading in the O’Sullivan group – see Amer, 2020); and (ii) the Paragon x Garcia mapping population of UK spring wheat (work conducted as part of the Defra Wheat Genetic Improvement Network; see also supporting statement from Prof Simon Griffiths, JIC). In use case (iii), cloning of a gene – Enhanced Gravitropism 2 – controlling cereal lateral root angle through modulation of the gravity sensing mechanism has given rise to a well-characterised set of isogenic tetraploid wheat accessions with defined differences in root angle due to a known mechanism (Kirschner et al, 2021; see also supporting statement from Prof Silvio Salvi, University of Bologna).
This pilot project will focus on use case (i), with use cases (ii) and (iii) representing further examples of how the platform will be opened up to the research community but which cannot be executed or reported on in the funded timeframe.