High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR.

Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR (r2 of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association (r2 = 0.92 and slope = 1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimized for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass (r2 = 0.93 and r2 = 0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new opportunities to deliver improved genotypes and agronomic interventions via more efficient and reliable phenotyping of these important traits in large experiments.

High-throughput chlorophyll fluorescence screening of Setaria viridis for mutants with altered CO2 compensation points.

To assist with efforts to engineer a C4 photosynthetic pathway into rice, forward-genetic approaches are being used to identify the genes modulating key C4 traits. Currently, a major challenge is how to screen for a variety of different traits in a high-throughput manner. Here we describe a method for identifying C4 mutant plants with increased CO2 compensation points. This is used as a signature for decreased photosynthetic efficiency associated with a loss of C4 function. By exposing plants to a CO2 concentration close to the CO2 compensation point of a wild-type plant, individuals can be identified from measurements of chlorophyll a fluorescence. We use this method to screen a mutant population of the C4 monocot Setaria viridis (L.)P.Beauv. generated using N-nitroso-N-methylurea (NMU). Mutants were identified at a frequency of 1 per 157 lines screened. Forty-six candidate lines were identified and one line with a heritable homozygous phenotype selected for further characterisation. The CO2 compensation point of this mutant was increased to a value similar to that of C3 rice. Photosynthesis and growth was significantly reduced under ambient conditions. These data indicate that the screen was capable of identifying mutants with decreased photosynthetic efficiency. Characterisation and next-generation sequencing of all the mutants identified in this screen may lead to the discovery of novel genes underpinning C4 photosynthesis. These can be used to engineer a C4 photosynthetic pathway into rice.

Phenomic Approaches and Tools for Phytopathologists.

Plant phenomics approaches aim to measure traits such as growth, performance, and composition of plants using a suite of noninvasive technologies. The goal is to link phenotypic traits to the genetic information for particular genotypes, thus creating the bridge between the phenome and genome. Application of sensing technologies for detecting specific phenotypic reactions occurring during plant-pathogen interaction offers new opportunities for elucidating the physiological mechanisms that link pathogen infection and disease symptoms in the host, and also provides a faster approach in the selection of genetic material that is resistant to specific pathogens or strains. Appropriate phenomics methods and tools may also allow presymptomatic detection of disease-related changes in plants or to identify changes that are not visually apparent. This review focuses on the use of sensor-based phenomics tools in plant pathology such as those related to digital imaging, chlorophyll fluorescence imaging, spectral imaging, and thermal imaging. A brief introduction is provided for less used approaches like magnetic resonance, soft x-ray imaging, ultrasound, and detection of volatile compounds. We hope that this concise review will stimulate further development and use of tools for automatic, nondestructive, and high-throughput phenotyping of plant-pathogen interaction.

TraitCapture: genomic and environment modelling of plant phenomic data.

Agriculture requires a second green revolution to provide increased food, fodder, fiber, fuel and soil fertility for a growing population while being more resilient to extreme weather on finite land, water, and nutrient resources. Advances in phenomics, genomics and environmental control/sensing can now be used to directly select yield and resilience traits from large collections of germplasm if software can integrate among the technologies. Traits could be Captured throughout development and across environments from multi-dimensional phenotypes, by applying Genome Wide Association Studies (GWAS) to identify causal genes and background variation and functional structural plant models (FSPMs) to predict plant growth and reproduction in target environments. TraitCapture should be applicable to both controlled and field environments and would allow breeders to simulate regional variety trials to pre-select for increased productivity under challenging environments.

Digital imaging approaches for phenotyping whole plant nitrogen and phosphorus response in Brachypodium distachyon.

This work evaluates the phenotypic response of the model grass (Brachypodium distachyon (L.) P. Beauv.) to nitrogen and phosphorus nutrition using a combination of imaging techniques and destructive harvest of shoots and roots. Reference line Bd21-3 was grown in pots using 11 phosphorus and 11 nitrogen concentrations to establish a dose-response curve. Shoot biovolume and biomass, root length and biomass, and tissue phosphorus and nitrogen concentrations increased with nutrient concentration. Shoot biovolume, estimated by imaging, was highly correlated with dry weight (R(2) > 0.92) and both biovolume and growth rate responded strongly to nutrient availability. Higher nutrient supply increased nodal root length more than other root types. Photochemical efficiency was strongly reduced by low phosphorus concentrations as early as 1 week after germination, suggesting that this measurement may be suitable for high throughput screening of phosphorus response. In contrast, nitrogen concentration had little effect on photochemical efficiency. Changes in biovolume over time were used to compare growth rates of four accessions in response to nitrogen and phosphorus supply. We demonstrate that a time series image-based approach coupled with mathematical modeling provides higher resolution of genotypic response to nutrient supply than traditional destructive techniques and shows promise for high throughput screening and determination of genomic regions associated with superior nutrient use efficiency.

Infrared thermography in plant phenotyping for salinity tolerance.

The recent advances made in the use of infrared thermal imaging (thermography) as a non-invasive, high-throughput technique for the screening of salinity tolerance in plants is reviewed. Taking wheat seedlings as an example, the methods and protocols used to impose a homogeneous salt stress to a large number of genotypes, as well as capturing infrared images of these genotypes and automatically processing the images are described in detail in this chapter. We also present the source code of the Matlab program applied to automatically identify plants and batch process IR images.

Growth of the C4 dicot Flaveria bidentis: photosynthetic acclimation to low light through shifts in leaf anatomy and biochemistry.

In C(4) plants, acclimation to growth at low irradiance by means of anatomical and biochemical changes to leaf tissue is considered to be limited by the need for a close interaction and coordination between bundle sheath and mesophyll cells. Here differences in relative growth rate (RGR), gas exchange, carbon isotope discrimination, photosynthetic enzyme activity, and leaf anatomy in the C(4) dicot Flaveria bidentis grown at a low (LI; 150 micromol quanta m(2) s(-1)) and medium (MI; 500 micromol quanta m(2) s(-1)) irradiance and with a 12 h photoperiod over 36 d were examined. RGRs measured using a 3D non-destructive imaging technique were consistently higher in MI plants. Rates of CO(2) assimilation per leaf area measured at 1500 micromol quanta m(2) s(-1) were higher for MI than LI plants but did not differ on a mass basis. LI plants had lower Rubisco and phosphoenolpyruvate carboxylase activities and chlorophyll content on a leaf area basis. Bundle sheath leakiness of CO(2) (phi) calculated from real-time carbon isotope discrimination was similar for MI and LI plants at high irradiance. phi increased at lower irradiances, but more so in MI plants, reflecting acclimation to low growth irradiance. Leaf thickness and vein density were greater in MI plants, and mesophyll surface area exposed to intercellular airspace (S(m)) and bundle sheath surface area per unit leaf area (S(b)) measured from leaf cross-sections were also both significantly greater in MI compared with LI leaves. Both mesophyll and bundle sheath conductance to CO(2) diffusion were greater in MI compared with LI plants. Despite being a C(4) species, F. bidentis is very plastic with respect to growth irradiance.

New phenotyping methods for screening wheat and barley for beneficial responses to water deficit.

This review considers stomatal conductance as an indicator of genotypic differences in the growth response to water stress. The benefits of using stomatal conductance are compared with photosynthetic rate and other indicators of genetic variation in water stress tolerance, along with the use of modern phenomics technologies. Various treatments for screening for genetic diversity in response to water deficit in controlled environments are considered. There is no perfect medium: there are pitfalls in using soil in pots, and in using hydroponics with ionic and non-ionic osmotica. Use of mixed salts or NaCl is recommended over non-ionic osmotica. Developments in infrared thermography provide new and feasible screening methods for detecting genetic variation in the stomatal response to water deficit in controlled environments and in the field.

A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography.

A high-throughput, automated image analysis protocol for the capture, identification and analysis of thermal images acquired with a long-wave infrared (IR) camera was developed to quantify the osmotic stress response of wheat and barley to salinity. There was a strong curvilinear relationship between direct measurements of stomatal conductance and leaf temperature of barley grown in a range of salt concentrations. This indicated that thermography accurately reflected the physiological status of salt-stressed barley seedlings. Leaf temperature differences between barley grown at 200 mM NaCl and 0 mM NaCl reached 1.6°C - the sensitivity of the IR signal increasing at higher salt concentrations. Seventeen durum wheat genotypes and one barley genotype, known to vary for osmotic stress tolerance, were grown in control (no salt) and 150 mM NaCl treatments to validate the newly-developed automated thermal imaging protocol. The ranking of the 18 genotypes based on both a growth study and the IR measurements was consistent with previous reports in the literature for these genotypes. This study shows the potential of IR thermal imaging for the screening of large numbers of genotypes varying for stomatal traits, specifically those related to salt tolerance.