With salt stress presenting a major threat to global food production, attention has turned to the identification and breeding of crop cultivars with improved salt tolerance. For instance, some accessions of wild species with higher salt tolerance than commercial varieties are being investigated for their potential to expand food production into marginal areas or to use brackish waters for irrigation. However, assessment of individual plant responses to salt stress in field trials is time-consuming, limiting, for example, longitudinal assessment of large numbers of plants. Developments in Unmanned Aerial Vehicle (UAV) sensing technologies provide a means for extensive, repeated and consistent phenotyping and have significant advantages over standard approaches. In this study, 199 accessions of the wild tomato species, Solanum pimpinellifolium , were evaluated through a field assessment of 600 control and 600 salt-treated plants. UAV imagery was used to: (1) delineate tomato plants from a time-series of eight RGB and two multi-spectral datasets, using an automated object-based image analysis approach; (2) assess four traits, i.e., plant area, growth rates, condition and Plant Projective Cover (PPC) over the growing season; and (3) use the mapped traits to identify the best-performing accessions in terms of yield and salt tolerance. For the first five campaigns, >99% of all tomato plants were automatically detected. The omission rate increased to 2–5% for the last three campaigns because of the presence of dead and senescent plants. Salt-treated plants exhibited a significantly smaller plant area (average control and salt-treated plant areas of 0.55 and 0.29 m 2 , respectively), maximum growth rate (daily maximum growth rate of control and salt-treated plant of 0.034 and 0.013 m 2 , respectively) and PPC (5–16% difference) relative to control plants. Using mapped plant condition, area, growth rate and PPC, we show that it was possible to identify eight out of the top 10 highest yielding accessions and that only five accessions produced high yield under both treatments. Apart from showcasing multi-temporal UAV-based phenotyping capabilities for the assessment of plant performance, this research has implications for agronomic studies of plant salt tolerance and for optimizing agricultural production under saline conditions.

Thermal infrared cameras provide unique information on surface temperature that can benefit a range of environmental, industrial and agricultural applications. However, the use of uncooled thermal cameras for field and unmanned aerial vehicle (UAV) based data collection is often hampered by vignette effects, sensor drift, ambient temperature influences and measurement bias. Here, we develop and apply an ambient temperature-dependent radiometric calibration function that is evaluated against three thermal infrared sensors (Apogee SI-11(Apogee Electronics, Santa Monica, CA, USA), FLIR A655sc (FLIR Systems, Wilsonville, OR, USA), TeAx 640 (TeAx Technology, Wilnsdorf, Germany)). Upon calibration, all systems demonstrated significant improvement in measured surface temperatures when compared against a temperature modulated black body target. The laboratory calibration process used a series of calibrated resistance temperature detectors to measure the temperature of a black body at different ambient temperatures to derive calibration equations for the thermal data acquired by the three sensors. As a point-collecting device, the Apogee sensor was corrected for sensor bias and ambient temperature influences. For the 2D thermal cameras, each pixel was calibrated independently, with results showing that measurement bias and vignette effects were greatly reduced for the FLIR A655sc (from a root mean squared error (RMSE) of 6.219 to 0.815 degrees Celsius (℃)) and TeAx 640 (from an RMSE of 3.438 to 1.013 ℃) cameras. This relatively straightforward approach for the radiometric calibration of infrared thermal sensors can enable more accurate surface temperature retrievals to support field and UAV-based data collection efforts.

Low frequency electromagnetic induction (EMI) is becoming a useful tool for soil characterization due to its fast measurement capability and sensitivity to soil moisture and salinity. In this research, a new EMI system (the CMD mini-Explorer) is used for subsurface characterization of soil salinity in a drip irrigation system via a joint inversion approach of multiconfiguration EMI measurements. EMI measurements were conducted across a farm where Acacia trees are irrigated with brackish water. In situ measurements of vertical bulk electrical conductivity (r b ) were recorded in different pits along one of the transects to calibrate the EMI measurements and to compare with the modeled electrical conductivity (r) obtained by the joint inversion of multiconfiguration EMI measurements. Estimates of r were then converted into the universal standard of soil salinity measurement (i.e., electrical conductivity of a saturated soil paste extract -EC e ). Soil apparent electrical conductivity (EC a ) was repeatedly measured with the CMD mini-Explorer to investigate the temperature stability of the new system at a fixed location, where the ambient air temperature increased from 26 C to 46 C. Results indicate that the new EMI system is very stable in high temperature environments, especially above 40 C, where most other approaches give unstable measurements. In addition, the distribution pattern of soil salinity is well estimated quantitatively by the joint inversion of multicomponent EMI measurements. The approach of joint inversion of EMI measurements allows for the quantitative mapping of the soil salinity distribution pattern and can be utilized for the management of soil salinity.

Excessive evaporative loss of water from the topsoil in arid-land agriculture is compensated via irrigation, which exploits massive freshwater resources. The cumulative effects of decades of unsustainable freshwater consumption in many arid regions are now threatening food-water security. While plastic mulches can reduce evaporation from the topsoil, their cost and nonbiodegradability limit their utility. In response, we report on superhydrophobic sand (SHS), a bio-inspired enhancement of common sand with a nanoscale wax coating. When SHS was applied as a 5 mm-thick mulch over the soil, evaporation dramatically reduced and crop yields increased. Multi-year field trials of SHS application with tomato (Solanum lycopersicum), barley (Hordeum vulgare), and wheat (Triticum aestivum) under normal irrigation enhanced yields by 17%-73%. Under brackish water irrigation (5500 ppm NaCl), SHS mulching produced 53%-208% higher fruit yield and grain gains for tomato and barley. Thus, SHS could benefit agriculture and city-greening in arid regions.

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