Fiona Corke

Canopy application of film antitranspirants over the reproductive phase enhances yield and yield-related physiological traits of water-stressed oilseed rape (Brassica napus)

Abstract. Oilseed rape (Brassica napus L.) yield is strongly decreased by water deficit, and crop-management solutions are urgently required considering the emerging difficulties in breeding for drought-tolerant varieties. Film-forming antitranspirants (polymers) are agrochemicals that, applied to the crop canopy, mechanically block the stomata and decrease canopy transpiration. In this study, the drought-protection efficacy of an adaxial-surface application at the flowering stage of two film-forming treatments (poly-1-p-menthene and di-1-p-menthene) was investigated in pot-grown, droughted oilseed rape over two glasshouse experiments. Over the drought period, the two compounds reduced leaf stomatal conductance (P < 0.001), and as the soil moisture deficit increased, they sustained carbon assimilation and improved water-use efficiency with differing efficacy. Following the antitranspirant treatments, ABA concentration in leaves and reproductive organs was severely reduced and this was accompanied by significant improvements in leaf and flower–pod water potential. Drought significantly decreased the seed dry matter production of oilseed rape plants, by 39% on average. The treatments significantly increased seed dry matter by 13% (poly-1-p-menthene) and 17% (di-1-p-menthene), on average, compared with the unsprayed droughted plants, as a result of a significant increase in number of pods per plant, by 11% and 13%, respectively. The results suggest that film-forming compounds may be a useful crop-management tool to avoid severe drought-induced yield losses in oilseed rape by improving water-use efficiency and plant water status, thus alleviating ABA signalling under water deficit.

Natural Variation in Brachypodium Links Vernalization and Flowering Time Loci as Major Flowering Determinants

Standing genetic variation for flowering time in a nondomesticated grass encompasses known and novel regulators. The domestication of plants is underscored by the selection of agriculturally favorable developmental traits, including flowering time, which resulted in the creation of varieties with altered growth habits. Research into the pathways underlying these growth habits in cereals has highlighted the role of three main flowering regulators: VERNALIZATION1 (VRN1), VRN2, and FLOWERING LOCUS T (FT). Previous reverse genetic studies suggested that the roles of VRN1 and FT are conserved in Brachypodium distachyon yet identified considerable ambiguity surrounding the role of VRN2. To investigate the natural diversity governing flowering time pathways in a nondomesticated grass, the reference B. distachyon accession Bd21 was crossed with the vernalization-dependent accession ABR6. Resequencing of ABR6 allowed the creation of a single-nucleotide polymorphism-based genetic map at the F4 stage of the mapping population. Flowering time was evaluated in F4:5 families in five environmental conditions, and three major loci were found to govern flowering time. Interestingly, two of these loci colocalize with the B. distachyon homologs of the major flowering pathway genes VRN2 and FT, whereas no linkage was observed at VRN1. Characterization of these candidates identified sequence and expression variation between the two parental genotypes, which may explain the contrasting growth habits. However, the identification of additional quantitative trait loci suggests that greater complexity underlies flowering time in this nondomesticated system. Studying the interaction of these regulators in B. distachyon provides insights into the evolutionary context of flowering time regulation in the Poaceae as well as elucidates the way humans have utilized the natural variation present in grasses to create modern temperate cereals.

Determining Phenological Patterns Associated with the Onset of Senescence in a Wheat MAGIC Mapping Population

The appropriate timing of developmental transitions is critical for adapting many crops to their local climatic conditions. Therefore, understanding the genetic basis of different aspects of phenology could be useful in highlighting mechanisms underpinning adaptation, with implications in breeding for climate change. For bread wheat (Triticum aestivum), the transition from vegetative to reproductive growth, the start and rate of leaf senescence and the relative timing of different stages of flowering and grain filling all contribute to plant performance. In this study we screened under Smart house conditions a large, multi-founder “NIAB elite MAGIC” wheat population, to evaluate the genetic elements that influence the timing of developmental stages in European elite varieties. This panel of recombinant inbred lines was derived from eight parents that are or recently have been grown commercially in the UK and Northern Europe. We undertook a detailed temporal phenotypic analysis under Smart house conditions of the population and its parents, to try to identify known or novel Quantitative Trait Loci associated with variation in the timing of key phenological stages in senescence. This analysis resulted in the detection of QTL interactions with novel traits such the time between “half of ear emergence above flag leaf ligule” and the onset of senescence at the flag leaf as well as traits associated with plant morphology such as stem height. In addition, strong correlations between several traits and the onset of senescence of the flag leaf were identified. This work establishes the value of systematically phenotyping genetically unstructured populations to reveal the genetic architecture underlying morphological variation in commercial wheat.

Linking Dynamic Phenotyping with Metabolite Analysis to Study Natural Variation in Drought Responses of Brachypodium distachyon

Drought is an important environmental stress limiting the productivity of major crops worldwide. Understanding drought tolerance and possible mechanisms for improving drought resistance is therefore a prerequisite to develop drought-tolerant crops that produce significant yields with reduced amounts of water. Brachypodium distachyon (Brachypodium) is a key model species for cereals, forage grasses, and energy grasses. In this study, initial screening of a Brachypodium germplasm collection consisting of 138 different ecotypes exposed to progressive drought, highlighted the natural variation in morphology, biomass accumulation, and responses to drought stress. A core set of ten ecotypes, classified as being either tolerant, susceptible or intermediate, in response to drought stress, were exposed to mild or severe (respectively, 15 and 0% soil water content) drought stress and phenomic parameters linked to growth and color changes were assessed. When exposed to severe drought stress, phenotypic data and metabolite profiling combined with multivariate analysis revealed a remarkable consistency in separating the selected ecotypes into their different pre-defined drought tolerance groups. Increases in several metabolites, including for the phytohormones jasmonic acid and salicylic acid, and TCA-cycle intermediates, were positively correlated with biomass yield and with reduced yellow pixel counts; suggestive of delayed senescence, both key target traits for crop improvement to drought stress. While metabolite analysis also separated ecotypes into the distinct tolerance groupings after exposure to mild drought stress, similar analysis of the phenotypic data failed to do so, confirming the value of metabolomics to investigate early responses to drought stress. The results highlight the potential of combining the analyses of phenotypic and metabolic responses to identify key mechanisms and markers associated with drought tolerance in both the Brachypodium model plant as well as agronomically important crops.

Image-based estimation of oat panicle development using local texture patterns

Flowering time varies between and within species, profoundly influencing reproductive fitness in wild plants and productivity in crop plants. The time of flowering, therefore, is an important statistic that is regularly collected as part of breeding programs and phenotyping experiments to facilitate comparison of genotypes and treatments. Its automatic detection would be highly desirable. We present significant progress on an approach to this problem in oats (Avena sativa L.), an underdeveloped cereal crop of increasing importance. Making use of the many thousands of images of oat plants we have available, spanning different genotypes and treatments, we observe that during flowering, panicles (the flowering structures) betray particular intensity patterns that give an identifiable texture that is distinctive and discriminatory with respect to the main plant body and can be used to determine the time of flowering. This texture can be located by a filter, trained as a form of local pattern. This training phase identifies the best parameters of such a filter, which usefully discovers the scale of the panicle spikelets. The results demonstrate the success of the filter. We proceed to suggest and evaluate an approach to using the filter as a growth stage detector. Preliminary results show very good correspondence with hand-measured ground truth, and are amenable to improvement in several ways. Future work will build on this initial success and will go on to locate fully mature panicles, which have a different appearance, and assess whether this approach can be extended to a broader range of plants.

eIF4A RNA Helicase Associates with Cyclin-Dependent Protein Kinase A in Proliferating Cells and Is Modulated by Phosphorylation

CDKA phosphorylation of the RNA helicase, eIF4A, is restricted to proliferating cells and could provide a mechanism that inhibits translation and cell growth in a cell cycle-dependent manner. Eukaryotic initiation factor 4A (eIF4A) is a highly conserved RNA-stimulated ATPase and helicase involved in the initiation of messenger RNA translation. Previously, we found that eIF4A interacts with cyclin-dependent kinase A (CDKA), the plant ortholog of mammalian CDK1. Here, we show that this interaction occurs only in proliferating cells where the two proteins coassociate with 5′-cap-binding protein complexes, eIF4F or the plant-specific eIFiso4F. CDKA phosphorylates eIF4A on a conserved threonine residue (threonine-164) within the RNA-binding motif 1b TPGR. In vivo, a phospho-null (APGR) variant of the Arabidopsis (Arabidopsis thaliana) eIF4A1 protein retains the ability to functionally complement a mutant (eif4a1) plant line lacking eIF4A1, whereas a phosphomimetic (EPGR) variant fails to complement. The phospho-null variant (APGR) rescues the slow growth rate of roots and rosettes, together with the ovule-abortion and late-flowering phenotypes. In vitro, wild-type recombinant eIF4A1 and its phospho-null variant both support translation in cell-free wheat germ extracts dependent upon eIF4A, but the phosphomimetic variant does not support translation and also was deficient in ATP hydrolysis and helicase activity. These observations suggest a mechanism whereby CDK phosphorylation has the potential to down-regulate eIF4A activity and thereby affect translation.

Functional mapping of quantitative trait loci (QTLs) associated with plant performance in a wheat MAGIC mapping population

In crop genetic studies, the mapping of longitudinal data describing the spatio-temporal nature of agronomic traits can elucidate the factors influencing their formation and development. Here, we combine the mapping power and precision of a MAGIC wheat population with robust computational methods to track the spatio- temporal dynamics of traits associated with wheat performance. NIAB MAGIC lines were phenotyped throughout their lifecycle under smart house conditions. Growth models were fitted to the data describing growth trajectories of plant area, height, water use and senescence and fitted parameters were mapped as quantitative traits. Trait data from single time points were also mapped to determine when and how markers became and ceased to be significant. Assessment of temporal dynamics allowed the identification of marker-trait associations and tracking of trait development against the genetic contribution of key markers. We establish a data-driven approach for understanding complex agronomic traits and accelerate research in plant breeding.

Automated estimation of tiller number in wheat by ribbon detection

The advent of high-throughput phenotyping installations signals a need for plant biology to use pattern analysis and recognition techniques, especially when analysis is done via digital images. Such installations also provide an opportunity to computer vision. We describe one such application at the UK National Plant Phenomics Centre, in which historically measurements have been made in a labour-intensive manual manner. We develop an estimator of tiller number in growing wheat which, when exploiting per-day averaging, temporal interpolation and dynamic programming, delivers measurements of finer-grain and no less accuracy than manually, and provides observations on plant treatments hitherto difficult or impossible to obtain. The approach developed lends itself to reuse for any similar imaging setup, and plants with tillering characteristics similar to wheat. We consider the work a useful exemplar for co-operation between biologists and computer scientists in such installations.

Estimation of Branch Angle from 3D Point Cloud of Plants

Measuring geometric features in plant specimens either quantitatively or qualitatively, is crucial for plant phenotyping. However, traditional measurement methods tend to be manual and can be tedious, or employ coarse 2D imaging techniques. Emerging 3D imaging technologies show much promise in capturing architectural complexity. However, automated 3D acquisition and accurate estimation of plant morphology for the construction of quantitative plant models remain largely aspiration. In this paper, we propose an approach for segmentation and angle estimation directly from dense 3D plant point clouds. Experimental results show that the approach is efficient and reliable, and appears to be a promising 3D acquisition and measurement solution to plant phenotyping for structural analysis and for building Functional-Structural Plant Models (FSPM).

Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions

Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions. Firstly, RGB images of individual rice plants at different growth points were analyzed to derive 4 features that were influenced by imposition of drought. These include a feature related to the ability to stay green, which we termed greenness plant area ratio (GPAR) and 3 shape descriptors [total plant area/bounding rectangle area ratio (TBR), perimeter area ratio (PAR) and total plant area/convex hull area ratio (TCR)]. Experiments showed that these 4 features were capable of discriminating reliably between drought resistant and drought sensitive accessions, and dynamically quantifying the drought response under controlled conditions across time (at either daily or half hourly time intervals). We compared the 3 shape descriptors and concluded that PAR was more robust and sensitive to leaf-rolling than the other shape descriptors. In addition, PAR and GPAR proved to be effective in quantification of drought response in the field. Moreover, the values obtained in field experiments using the collection of rice varieties were correlated with those derived from pot-based experiments. The general applicability of the algorithms is demonstrated by their ability to probe archival Miscanthus data previously collected on an independent platform. In conclusion, this image-based technology is robust providing a platform-independent tool for quantifying drought response that should be of general utility for breeding and functional genomics in future.