Jiwan Han

Accurate Multi-View Stereo 3D Reconstruction for Cost-Effective Plant Phenotyping

Phenotyping, which underpins much of plant biology and breeding, involves the measurement of characteristics or traits. Traditionally, this has been often destructive and/or subjective but the dynamic objective measurement of traits as they change in response to genetic mutation or environmental influences is an important goal. 3-D imaging technologies are increasingly incorporated into mass produced consumer goods (3D laser scanning, structured light and digital photography) and may represent a cost-effective alternative to current commercial phenotyping platforms. We evaluate their performance, cost and practicability for plant phenotyping and present a 3D reconstruction method for plants from multi-view images acquired with domestic quality cameras. We exploit an efficient Structure-From-Motion followed by stereo matching and depth-map merging processes. Experimental results show that the proposed method is flexible, adaptable and inexpensive, and promising as an generalized groundwork for phenotyping various plant species.

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.

A Cost-Effective Automatic 3D Reconstruction Pipeline for Plants Using Multi-view Images

Plant phenotyping involves the measurement, ideally objectively, of characteristics or traits. Traditionally, this is either limited to tedious and sparse manual measurements, often acquired destructively, or coarse image-based 2D measurements. 3D sensing technologies (3D laser scanning, structured light and digital photography) are increasingly incorporated into mass produced consumer goods and have the potential to automate the process, providing a cost-effective alternative to current commercial phenotyping platforms. We evaluate the performance, cost and practicability for plant phenotyping and present a 3D reconstruction method from multi-view images acquired with a domestic quality camera. This method consists of the following steps: (i) image acquisition using a digital camera and turntable; (ii) extraction of local invariant features and matching from overlapping image pairs; (iii) estimation of camera parameters and pose based on Structure from Motion(SFM); and (iv) employment of a patch based multi-view stereo technique to implement a dense 3D point cloud. We conclude that the proposed 3D reconstruction is a promising generalized technique for the non-destructive phenotyping of various plants during their whole growth cycles.

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.

An All-Solid-State Phosphate Electrode with H3PO4 Doped Polyaniline as the Sensitive Layer

We here describe the construction of a highly sensitive and selective all-solid-state phosphate electrode based on polyaniline and H3PO4 doped polyaniline. The polyaniline layer was electroplated on the gold substrate with Chronoamperometry method and was in-situ doped by H3PO4. The Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy (SEM, EDS) and contact angle measurement was taken to explain the difference of the two layers. This electrode can be used in both freshwater and seawater systems. In both of the two systems, the electrode exhibits linear response in the concentration range 10 -1 to 10 -6 M with detection limit of 10 -6 M. and response time of <1 seconds. The selectivity of the electrodes was also studied in 10 -1 -10 -5 M KH2PO4 solutions containing either 0.01 M sulfate, nitrate, chloride as the interference ions. During 12 hours continuous monitoring in 10 -3

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).

A novel chemical sensor with multiple all-solid-state electrodes and its application in freshwater environmental monitoring

Freshwater quality detection is important for pollution control. Three important components of water quality are pH, ammonia and dissolved H2S and there is an urgent need for a high-precision sensor for simultaneous and continuous measurement. In this study, all-solid-state electrodes of Eh, pH, NH4+ and S2- were manufactured and mounted to a wireless chemical sensor with multiple parameters. Calibration indicated that the pH electrode had a Nernst response with slope of 53.174 mV; the NH4+ electrode had a detection limit of 10-5 mol/L (Nernst response slope of 53.56 mV between 10-1 to 10-4 mol/L). Ag/Ag2S has a detection limit of 10-7 mol/L (Nernst response slope of 28.439 mV). The sensor was cylindrical and small with low power consumption and low storage demand to achieve continuous in-situ monitoring for long periods. The sensor was tested for 10 days in streams at Trawsgoed Dairy farm in Aberystwyth, UK. At the intensively farmed Trawsgoed, the concentration of NH4+ in the stream rose sharply after the application of slurry to adjacent fields. Further, the stream was overhung with extensive vegetation and exhibited changes in pH, which correlated with photosynthetic activity. Measurements of S2- were stable throughout the week. Our data demonstrate the applicability of our multiple electrode sensor.

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.

Nutrient and drought stress : implications for phenology and biomass quality in miscanthus

Abstract Background and Aims The cultivation of dedicated biomass crops, including miscanthus, on marginal land provides a promising approach to the reduction of dependency on fossil fuels. However, little is known about the impact of environmental stresses often experienced on lower-grade agricultural land on cell-wall quality traits in miscanthus biomass crops. In this study, three different miscanthus genotypes were exposed to drought stress and nutrient stress, both separately and in combination, with the aim of evaluating their impact on plant growth and cell-wall properties. Methods Automated imaging facilities at the National Plant Phenomics Centre (NPPC-Aberystwyth) were used for dynamic phenotyping to identify plant responses to separate and combinatorial stresses. Harvested leaf and stem samples of the three miscanthus genotypes (Miscanthus sinensis, Miscanthus sacchariflorus and Miscanthus × giganteus) were separately subjected to saccharification assays, to measure sugar release, and cell-wall composition analyses. Key Results Phenotyping showed that the M. sacchariflorus genotype Sac-5 and particularly the M. sinensis genotype Sin-11 coped better than the M. × giganteus genotype Gig-311 with drought stress when grown in nutrient-poor compost. Sugar release by enzymatic hydrolysis, used as a biomass quality measure, was significantly affected by the different environmental conditions in a stress-, genotype- and organ-dependent manner. A combination of abundant water and low nutrients resulted in the highest sugar release from leaves, while for stems this was generally associated with the combination of drought and nutrient-rich conditions. Cell-wall composition analyses suggest that changes in fine structure of cell-wall polysaccharides, including heteroxylans and pectins, possibly in association with lignin, contribute to the observed differences in cell-wall biomass sugar release. Conclusions The results highlight the importance of the assessment of miscanthus biomass quality measures in addition to biomass yield determinations and the requirement for selecting suitable miscanthus genotypes for different environmental conditions.