Nondestructive Phenomic Tools for the Prediction of Heat and Drought Tolerance at Anthesis in Brassica Species.

Oilseed Brassica species are vulnerable to heat and drought stress, especially in the early reproductive stage. We evaluated plant imaging of whole plant and flower tissue, leaf stomatal conductance, leaf and bud temperature, photochemical reflectance index, quantum yield of photosynthesis, and leaf gas exchange for their suitability to detect tolerance to heat (H) and/or drought (D) stress treatments in 12 Brassica genotypes (G). A replicated factorial experiment was set up with 7 d of stress treatment from the beginning of anthesis with various levels of three factors H, D, and G. Most phenomics tools detected plant stress as indicated by significant main effects of H, D, and H×D. Whole plant volume was highly correlated with fresh weight changes, suggesting that whole plant imaging may be a useful surrogate for fresh weight in future studies. Vcmax, the maximum carboxylation rate of photosynthesis, increased rapidly on day 1 in H and H+D treatments, and there were significant interactions of G×H and G×D. Vcmax of genotypes on day 1 in H and H+D treatments was positively correlated with their harvested seed yield. Vcmax on day 1 and day 3 were clustered with seed yield in H and H+D treatments as shown in the heatmaps of genotypic correlations. TPU, the rate of triose phosphate use, also showed significant positive genotypic correlations with seed yield in H+D treatments. Flower volume showed significant interactions of G×H and G×D on day 7, and flower volume of genotypes on day 7 in H was positively correlated with their harvested seed yield. There were few interactions of G×H or G×D for leaf stomatal conductance, leaf and bud temperature, photochemical reflectance index, and quantum yield of photosynthesis. Vcmax, TPU, and volume of flowers are potential nondestructive phenomic traits for heat or combined heat and drought stress tolerance screening in Brassica germplasm.

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.

Leaf Photosynthetic Parameters Related to Biomass Accumulation in a Global Rice Diversity Survey.

Mining natural variations is a major approach to identify new options to improve crop light use efficiency. So far, successes in identifying photosynthetic parameters positively related to crop biomass accumulation through this approach are scarce, possibly due to the earlier emphasis on properties related to leaf instead of canopy photosynthetic efficiency. This study aims to uncover rice (Oryza sativa) natural variations to identify leaf physiological parameters that are highly correlated with biomass accumulation, a surrogate of canopy photosynthesis. To do this, we systematically investigated 14 photosynthetic parameters and four morphological traits in a rice population, which consists of 204 U.S. Department of Agriculture-curated minicore accessions collected globally and 11 elite Chinese rice cultivars in both Beijing and Shanghai. To identify key components responsible for the variance of biomass accumulation, we applied a stepwise feature-selection approach based on linear regression models. Although there are large variations in photosynthetic parameters measured in different environments, we observed that photosynthetic rate under low light (Alow) was highly related to biomass accumulation and also exhibited high genomic inheritability in both environments, suggesting its great potential to be used as a target for future rice breeding programs. Large variations in Alow among modern rice cultivars further suggest the great potential of using this parameter in contemporary rice breeding for the improvement of biomass and, hence, yield potential.

Diurnal Solar Energy Conversion and Photoprotection in Rice Canopies.

Genetic improvement of photosynthetic performance of cereal crops and increasing the efficiency with which solar radiation is converted into biomass has recently become a major focus for crop physiologists and breeders. The pulse amplitude modulated chlorophyll fluorescence technique (PAM) allows quantitative leaf level monitoring of the utilization of energy for photochemical light conversion and photoprotection in natural environments, potentially over the entire crop lifecycle. Here, the diurnal relationship between electron transport rate (ETR) and irradiance was measured in five cultivars of rice (Oryza sativa) in canopy conditions with PAM fluorescence under natural solar radiation. This relationship differed substantially from that observed for conventional short term light response curves measured under controlled actinic light with the same leaves. This difference was characterized by a reduced curvature factor when curve fitting was used to model this diurnal response. The engagement of photoprotective processes in chloroplast electron transport in leaves under canopy solar radiation was shown to be a major contributor to this difference. Genotypic variation in the irradiance at which energy flux into photoprotective dissipation became greater than ETR was observed. Cultivars capable of higher ETR at midrange light intensities were shown to produce greater leaf area over time, estimated by noninvasive imaging.

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.

Using Phenomic Analysis of Photosynthetic Function for Abiotic Stress Response Gene Discovery.

Monitoring the photosynthetic performance of plants is a major key to understanding how plants adapt to their growth conditions. Stress tolerance traits have a high genetic complexity as plants are constantly, and unavoidably, exposed to numerous stress factors, which limits their growth rates in the natural environment. Arabidopsis thaliana, with its broad genetic diversity and wide climatic range, has been shown to successfully adapt to stressful conditions to ensure the completion of its life cycle. As a result, A. thaliana has become a robust and renowned plant model system for studying natural variation and conducting gene discovery studies. Genome wide association studies (GWAS) in restructured populations combining natural and recombinant lines is a particularly effective way to identify the genetic basis of complex traits. As most abiotic stresses affect photosynthetic activity, chlorophyll fluorescence measurements are a potential phenotyping technique for monitoring plant performance under stress conditions. This review focuses on the use of chlorophyll fluorescence as a tool to study genetic variation underlying the stress tolerance responses to abiotic stress in A. thaliana.

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.

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.

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.

Down-regulation of Glucan, Water-Dikinase activity in wheat endosperm increases vegetative biomass and yield.

A novel mechanism for increasing vegetative biomass and grain yield has been identified in wheat (Triticum aestivum). RNAi-mediated down-regulation of Glucan, Water-Dikinase (GWD), the primary enzyme required for starch phosphorylation, under the control of an endosperm-specific promoter, resulted in a decrease in starch phosphate content and an increase in grain size. Unexpectedly, consistent increases in vegetative biomass and grain yield were observed in subsequent generations. In lines where GWD expression was decreased, germination rate was slightly reduced. However, significant increases in vegetative growth from the two leaf stage were observed. In glasshouse pot trials, down-regulation of GWD led to a 29% increase in grain yield while in glasshouse tub trials simulating field row spacing and canopy development, GWD down-regulation resulted in a grain yield increase of 26%. The enhanced yield resulted from a combination of increases in seed weight, tiller number, spikelets per head and seed number per spike. In field trials, all vegetative phenotypes were reproduced with the exception of increased tiller number. The expression of the transgene and suppression of endogenous GWD RNA levels were demonstrated to be grain specific. In addition to the direct effects of GWD down-regulation, an increased level of α-amylase activity was present in the aleurone layer during grain maturation. These findings provide a potentially important novel mechanism to increase biomass and grain yield in crop improvement programmes.

A novel mesh processing based technique for 3D plant analysis.

BACKGROUND: In recent years, imaging based, automated, non-invasive, and non-destructive high-throughput plant phenotyping platforms have become popular tools for plant biology, underpinning the field of plant phenomics. Such platforms acquire and record large amounts of raw data that must be accurately and robustly calibrated, reconstructed, and analysed, requiring the development of sophisticated image understanding and quantification algorithms. The raw data can be processed in different ways, and the past few years have seen the emergence of two main approaches: 2D image processing and 3D mesh processing algorithms. Direct image quantification methods (usually 2D) dominate the current literature due to comparative simplicity. However, 3D mesh analysis provides the tremendous potential to accurately estimate specific morphological features cross-sectionally and monitor them over-time. RESULT: In this paper, we present a novel 3D mesh based technique developed for temporal high-throughput plant phenomics and perform initial tests for the analysis of Gossypium hirsutum vegetative growth. Based on plant meshes previously reconstructed from multi-view images, the methodology involves several stages, including morphological mesh segmentation, phenotypic parameters estimation, and plant organs tracking over time. The initial study focuses on presenting and validating the accuracy of the methodology on dicotyledons such as cotton but we believe the approach will be more broadly applicable. This study involved applying our technique to a set of six Gossypium hirsutum (cotton) plants studied over four time-points. Manual measurements, performed for each plant at every time-point, were used to assess the accuracy of our pipeline and quantify the error on the morphological parameters estimated. CONCLUSION: By directly comparing our automated mesh based quantitative data with manual measurements of individual stem height, leaf width and leaf length, we obtained the mean absolute errors of 9.34%, 5.75%, 8.78%, and correlation coefficients 0.88, 0.96, and 0.95 respectively. The temporal matching of leaves was accurate in 95% of the cases and the average execution time required to analyse a plant over four time-points was 4.9 minutes. The mesh processing based methodology is thus considered suitable for quantitative 4D monitoring of plant phenotypic features.

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.