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.

Brachypodium distachyon (Brachypodium) is a non-domesticated model grass species that can be used to test if variation in genetic sequence or methylation are linked to environmental differences. To assess this, we collected seeds from 12 sites within five climatically distinct regions of Turkey. Seeds from each region were grown under standardized growth conditions in the UK to preserve methylated sequence variation. At six weeks following germination, leaves were sampled and assessed for genomic and DNA methylation variation. In a follow-up experiment, phenomic approaches were used to describe plant growth and drought responses. Genome sequencing and population structure analysis suggested three ancestral clusters across the Mediterranean, two of which were geographically separated in Turkey into coastal and central subpopulations. Phenotypic analyses showed that the coastal subpopulation tended to exhibit relatively delayed flowering and the central, increased drought tolerance as indicated by reduced yellowing. Genome-wide methylation analyses in GpC, CHG and CHH contexts also showed variation which aligned with the separation into coastal and central subpopulations. The climate niche modelling of both subpopulations showed a significant influence from the "Precipitation in the Driest Quarter" on the central subpopulation and "Temperature of the Coldest Month" on the coastal subpopulation. Our work demonstrates genetic diversity and variation in DNA methylation in Turkish accessions of Brachypodium that may be associated with climate variables and the molecular basis of which will feature in ongoing analyses.

Mechanical stimulation, including exposure to wind, is a common environmental variable for plants. However, knowledge about the morphogenetic response of the grasses (Poaceae) to mechanical stimulation and impact on relevant agronomic traits is very limited. Two natural accessions of Brachypodium distachyon were exposed to wind and mechanical treatments. We surveyed a wide range of stem-related traits to determine the effect of the two treatments on plant growth, development, and stem biomass properties. Both treatments induced significant quantitative changes across multiple scales, from the whole plant down to cellular level. The two treatments resulted in shorter stems, reduced biomass, increased tissue rigidity, delayed flowering, and reduced seed yield in both accessions. Among changes in cell wall-related features, a substantial increase in lignin content and pectin methylesterase activity was most notable. Mechanical stimulation also reduced the enzymatic sugar release from the cell wall, thus increasing biomass recalcitrance. Notably, treatments had a distinct and opposite effect on vascular bundle area in the two accessions, suggesting genetic variation in modulating these responses to mechanical stimulation. Our findings highlight that exposure of grasses to mechanical stimulation is a relevant environmental factor affecting multiple traits important for their utilization in food, feed, and bioenergy applications.

Many plants can modify their leaf profile rapidly in response to environmental stress. Image-based data are increasingly used to retrieve reliable information on plant water status in a non-contact manner that has the potential to be scaled to high-throughput and repeated through time. This paper examined the variation of leaf angle as measured by both 3D images and goniometer in progressively drought stressed grapevine. Grapevines, grown in pots, were subjected to a 21-day period of drought stress receiving 100% (CTRL), 60% (IRR 60%) and 30% (IRR 30%) of maximum soil available water capacity. Leaf angle was (i) measured manually (goniometer) and (ii) computed by a 3D reconstruction method (multi-view stereo and structure from motion). Stomatal conductance, leaf water potential, fluorescence (F v /F m ), leaf area and 2D RGB data were simultaneously collected during drought imposition. Throughout the experiment, values of leaf water potential ranged from -0.4 (CTRL) to -1.1 MPa (IRR 30%) and it linearly influenced the leaf angle when measured manually (R 2 = 0.86) and with 3D image (R 2 = 0.73). Drought was negatively related to stomatal conductance and leaf area growth particularly in IRR 30% while photosynthetic parameters (i.e., F v /F m ) were not impaired by water restriction. A model for leaf area estimation based on the number of pixels of 2D RGB images developed at a different phenotyping robotized platform in a closely related experiment was successfully employed (R 2 = 0.78). At the end of the experiment, top view 2D RGB images showed a ∼50% reduction of greener fraction (GGF) in CTRL and IRR 60% vines compared to initial values, while GGF in IRR 30% increased by approximately 20%.

Drought resistance (DR) is a complex trait that is regulated by a variety of genes. Without comprehensive profiling of DR-related traits, the knowledge of the genetic architecture for DR in cotton remains limited. Thus, there is a need to bridge the gap between genomics and phenomics. In this study, an automatic phenotyping platform (APP) was systematically applied to examine 119 image-based digital traits (i-traits) during drought stress at the seedling stage, across a natural population of 200 representative upland cotton accessions. Some novel i-traits, as well as some traditional i-traits, were used to evaluate the DR in cotton. The phenomics data allowed us to identify 390 genetic loci by genome-wide association study (GWAS) using 56 morphological and 63 texture i-traits. DR-related genes, including GhRD2, GhNAC4, GhHAT22 and GhDREB2, were identified as candidate genes by some digital traits. Further analysis of candidate genes showed that Gh_A04G0377 and Gh_A04G0378 functioned as negative regulators for cotton drought response. Based on the combined digital phenotyping, GWAS analysis and transcriptome data, we conclude that the phenomics dataset provides an excellent resource to characterize key genetic loci with an unprecedented resolution which can inform future genome-based breeding for improved DR in cotton.

Sphagnum peatmosses play an important part in water table management of many peatland ecosystems. Keeping the ecosystem saturated, they slow the breakdown of organic matter and release of greenhouse gases, facilitating peatland's function as a carbon sink rather than a carbon source. Although peatland monitoring and restoration programs have increased recently, there are few tools to quantify traits that Sphagnum species display in their ecosystems. Colony density is often described as an important determinant in the establishment and performance in Sphagnum but detailed evidence for this is limited. In this study, we describe an image analysis pipeline that accurately annotates Sphagnum capitula and estimates plant density using open access computer vision packages. The pipeline was validated using images of different Sphagnum species growing in different habitats, taken on different days and with different smartphones. The developed pipeline achieves high accuracy scores, and we demonstrate its utility by estimating colony densities in the field and detecting intra and inter-specific colony densities and their relationship with habitat. This tool will enable ecologists and conservationists to rapidly acquire accurate estimates of Sphagnum density in the field without the need of specialised equipment.

Seed germination is a complex process during which a mature seed resumes metabolic activity to prepare for seedling growth. In this study, we performed a comparative metabolomic analysis of the embryo and endosperm using the community standard lines of three annual Brachypodium species, i.e., B. distachyon (Bd) and B. stacei (Bs) and their natural allotetraploid B. hybridum (BdBs) that has wider ecological range than the other two species. We explored how far the metabolomic impact of allotetraploidization would be observable as over-lapping changes at 4, 12, and 24 h after imbibition (HAI) with water when germination was initiated. Metabolic changes during germination were more prominent in Brachypodium embryos than in the endosperm. The embryo and endosperm metabolomes of Bs and BdBs were similar, and those of Bd were distinctive. The Bs and BdBs embryos showed increased levels of sugars and the tricarboxylic acid cycle compared to Bd, which could have been indicative of better nutrient mobilization from the endosperm. Bs and BdBs also showed higher oxalate levels that could aid nutrient transfer through altered cellular events. In Brachypodium endosperm, the thick cell wall, in addition to starch, has been suggested to be a source of nutrients to the embryo. Metabolites indicative of sugar metabolism in the endosperm of all three species were not prominent, suggesting that mobilization mostly occurred prior to 4 HAI. Hydroxycinnamic and monolignol changes in Bs and BdBs were consistent with cell wall remodeling that arose following the release of nutrients to the respective embryos. Amino acid changes in both the embryo and endosperm were broadly consistent across the species. Taking our data together, the formation of BdBs may have maintained much of the Bs metabolome in both the embryo and endosperm during the early stages of germination. In the embryo, this conserved Bs metabolome appeared to include an elevated sugar metabolism that played a vital role in germination. If these observations are confirmed in the future with more Brachypodium accessions, it would substantiate the dominance of the Bs metabolome in BdBs allotetraploidization and the use of metabolomics to suggest important adaptive changes.

Histone acetylation is directly related to gene expression. In yeast, the acetyltransferase general control nonderepressible-5 (GCN5) targets histone H3 and associates with transcriptional co-activators alteration/deficiency in activation-2 (ADA2) and alteration/deficiency in activation-3 (ADA3) in complexes like SAGA. Arabidopsis thaliana has two genes encoding proteins, designated ADA3a and ADA3b, that correspond to yeast ADA3. We investigated the role of ADA3a and ADA3b in regulating gene expression during flowering time. Specifically, we found that knock out mutants ada3a-2 and the double mutant ada3a-2 ada3b-2 lead to early flowering compared to the wild type plants under long day (LD) conditions and after moving plants from short days to LD. Consistent with ADA3a being a repressor of floral initiation, FLOWERING LOCUS T (FT) expression was increased in ada3a mutants. In contrast, other genes involved in multiple pathways leading to floral transition, including FT repressors, players in GA signaling, and members of the SPL transcriptional factors, displayed reduced expression. Chromatin immunoprecipitation analysis revealed that ADA3a affects the histone H3K14 acetylation levels in SPL3, SPL5, RGA, GAI, and SMZ loci. In conclusion, ADA3a is involved in floral induction through a GCN5-containing complex that acetylates histone H3 in the chromatin of flowering related genes.

China is the largest producer and consumer of rice, and the classification of filled/unfilled rice grains is of great significance for rice breeding and genetic analysis. The traditional method for filled/unfilled rice grain identification was generally manual, which had the disadvantages of low efficiency, poor repeatability, and low precision. In this study, we have proposed a novel method for filled/unfilled grain classification based on structured light imaging and Improved PointNet++. Firstly, the 3D point cloud data of rice grains were obtained by structured light imaging. And then the specified processing algorithms were developed for the single grain segmentation, and data enhancement with normal vector. Finally, the PointNet++ network was improved by adding an additional Set Abstraction layer and combining the maximum pooling of normal vectors to realize filled/unfilled rice grain point cloud classification. To verify the model performance, the Improved PointNet++ was compared with six machine learning methods, PointNet and PointConv. The results showed that the optimal machine learning model is XGboost, with a classification accuracy of 91.99%, while the classification accuracy of Improved PointNet++ was 98.50% outperforming the PointNet 93.75% and PointConv 92.25%. In conclusion, this study has demonstrated a novel and effective method for filled/unfilled grain recognition.

The plant hormone auxin is thought to provide positional information for patterning during development. It is still unclear, however, precisely how auxin is distributed across tissues and how the hormone is sensed in space and time. The control of gene expression in response to auxin involves a complex network of over 50 potentially interacting transcriptional activators and repressors, the auxin response factors (ARFs) and Aux/IAAs. Here, we perform a large-scale analysis of the Aux/IAA-ARF pathway in the shoot apex of Arabidopsis, where dynamic auxin-based patterning controls organogenesis. A comprehensive expression map and full interactome uncovered an unexpectedly simple distribution and structure of this pathway in the shoot apex. A mathematical model of the Aux/IAA-ARF network predicted a strong buffering capacity along with spatial differences in auxin sensitivity. We then tested and confirmed these predictions using a novel auxin signalling sensor that reports input into the signalling pathway, in conjunction with the published DR5 transcriptional output reporter. Our results provide evidence that the auxin signalling network is essential to create robust patterns at the shoot apex.

The incorporation of new sophisticated phenotyping technologies within a crop improvement program allows for a plant breeding strategy that can include selections for major root traits previously inaccessible due to the challenges in their phenotype assessment. High-throughput precision phenotyping technology is employed to evaluate root ontogeny and progressive changes to root architecture of both novel amphiploid and introgression lines of Festulolium over four consecutive months of the growing season and these compared under the same time frame to that of closely related perennial ryegrass (L. perenne) varieties. Root imaging using conventional photography and assembled multiple merged images was used to compare frequencies in root number, their distribution within 0-20 and 20-40 cm depths within soil columns, and progressive changes over time. The Festulolium hybrids had more extensive root systems in comparison with L. perenne, and this was especially evident at depth. It was shown that the acquisition of extensive root systems in Festulolium hybrids was not dependent on the presence of an entire Festuca genome. On the contrary, the most pronounced effect on root development within the four Festulolium populations studied was observed in the introgression line Bx509, where a single small genome sequence from F. arundinacea had been previously transferred onto its homoeologous site on the long arm of chromosome 3 of an otherwise complete L. perenne genome. This demonstrates that a targeted introgression-breeding approach may be sufficient to confer a significant improvement in the root morphology in Lolium without a significant compromise to its genome integrity. The forage production of Bx509 was either higher (months 1-3) or equivalent to (month 4) that of its L. perenne parent control demonstrating that the enhanced root development achieved by the introgression line was without compromise to its agronomic performance.

Understanding how plants respond to drought can benefit drought resistance (DR) breeding. Using a non-destructive phenotyping facility, 51 image-based traits (i-traits) for 507 rice accessions were extracted. These i-traits can be used to monitor drought responses and evaluate DR. High heritability and large variation of these traits was observed under drought stress in the natural population. A genome-wide association study (GWAS) of i-traits and traditional DR traits identified 470 association loci, some containing known DR-related genes. Of these 470 loci, 443 loci (94%) were identified using i-traits, 437 loci (93%) co-localized with previously reported DR-related quantitative trait loci, and 313 loci (66.6%) were reproducibly identified by GWAS in different years. Association networks, established based on GWAS results, revealed hub i-traits and hub loci. This demonstrates the feasibility and necessity of dissecting the complex DR trait into heritable and simple i-traits. As proof of principle, we illustrated the power of this integrated approach to identify previously unreported DR-related genes. OsPP15 was associated with a hub i-trait, and its role in DR was confirmed by genetic transformation experiments. Furthermore, i-traits can be used for DR linkage analyses, and 69 i-trait locus associations were identified by both GWAS and linkage analysis of a recombinant inbred line population. Finally, we confirmed the relevance of i-traits to DR in the field. Our study provides a promising novel approach for the genetic dissection and discovery of causal genes for DR.

In situ hybridisation can provide cellular, and in some cases sub-cellular, resolution of mRNA levels within multicellular organisms and is widely used to provide spatial and temporal information on gene expression. However, standard protocols are complex and laborious to implement, restricting analysis to one or a few genes at any one time. Whole-mount and reverse transcriptase-PCR (RT-PCR) based protocols increase throughput, but can compromise both specificity and resolution. With the advent of genome-wide analysis of gene expression, there is an urgent need to develop high-throughput in situ methods that also provide high resolution.

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.

Lodging is a common problem in rice, reducing its yield and mechanical harvesting efficiency. Rice architecture is a key aspect of its domestication and a major factor that limits its high productivity. The ideal rice culm structure, including major_axis_culm, minor axis_culm, and wall thickness_culm, is critical for improving lodging resistance. However, the traditional method of measuring rice culms is destructive, time consuming, and labor intensive. In this study, we used a high-throughput micro-CT-RGB imaging system and deep learning (SegNet) to develop a high-throughput micro-CT image analysis pipeline that can extract 24 rice culm morphological traits and lodging resistance-related traits. When manual and automatic measurements were compared at the mature stage, the mean absolute percentage errors for major_axis_culm, minor_axis_culm, and wall_thickness_culm in 104 indica rice accessions were 6.03%, 5.60%, and 9.85%, respectively, and the R2 values were 0.799, 0.818, and 0.623. We also built models of bending stress using culm traits at the mature and tillering stages, and the R2 values were 0.722 and 0.544, respectively. The modeling results indicated that this method can quantify lodging resistance nondestructively, even at an early growth stage. In addition, we also evaluated the relationships of bending stress to shoot dry weight, culm density, and drought-related traits and found that plants with greater resistance to bending stress had slightly higher biomass, culm density, and culm area but poorer drought resistance. In conclusion, we developed a deep learning-integrated micro-CT image analysis pipeline to accurately quantify the phenotypic traits of rice culms in ∼4.6 min per plant; this pipeline will assist in future high-throughput screening of large rice populations for lodging resistance.

The ability to sense environmental temperature and to coordinate growth and development accordingly, is critical to the reproductive success of plants. Flowering time is regulated at the level of gene expression by a complex network of factors that integrate environmental and developmental cues. One of the main players, involved in modulating flowering time in response to changes in ambient temperature is FLOWERING LOCUS M (FLM). FLM transcripts can undergo extensive alternative splicing producing multiple variants, of which FLM-β and FLM-δ are the most representative. While FLM-β codes for the flowering repressor FLM protein, translation of FLM-δ has the opposite effect on flowering. Here we show that the cyclin-dependent kinase G2 (CDKG2), together with its cognate cyclin, CYCLYN L1 (CYCL1) affects the alternative splicing of FLM, balancing the levels of FLM-β and FLM-δ across the ambient temperature range. In the absence of the CDKG2/CYCL1 complex, FLM-β expression is reduced while FLM-δ is increased in a temperature dependent manner and these changes are associated with an early flowering phenotype in the cdkg2 mutant lines. In addition, we found that transcript variants retaining the full FLM intron 1 are sequestered in the cell nucleus. Strikingly, FLM intron 1 splicing is also regulated by CDKG2/CYCL1. Our results provide evidence that temperature and CDKs regulate the alternative splicing of FLM, contributing to flowering time definition.

Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.

The augmin complex plays an essential role in microtubule (MT)-dependent MT nucleation by recruiting the γ-tubulin complex to MT walls to generate new MTs [1]. The complex contains eight subunits (designated AUG) including AUG8, which is an MT-associated protein (MAP). When this complex is isolated from etiolated seedlings consisting of primarily interphase cells in Arabidopsis thaliana, AUG8 is an integral component [2]. EDE1 (Endosperm DEfective 1) is homologous to AUG8 [3]. Here, we demonstrate that EDE1, but not AUG8, is associated with acentrosomal spindle and phragmoplast MT arrays in patterns indistinguishable from those of the AUG1-7 subunits and the γ-tubulin complex proteins (GCPs) that exhibit biased localization toward MT minus ends. Consistent with this colocalization, EDE1 directly interacts with AUG6 in vivo. Moreover, a partial loss-of-function mutation, ede1-1, compromises the localization of augmin and γ-tubulin on the spindle and phragmoplast MT arrays and leads to serious distortions in spindle MT remodeling during mitosis. However, mitosis continues even when kinetochore fibers are not obviously discernable, and cytokinesis takes place following the formation of elongated bipolar phragmoplast MT arrays in the mutant. Hence, we conclude that the mitotic function of augmin is dependent on its MAP subunit EDE1, which cannot be replaced by AUG8, and that the cell-cycle-dependent function of augmin can be differentially regulated by employing distinct MAP subunits. Our results also illustrate that plant cells can respond flexibly to serious challenges of compromised MT-dependent MT nucleation to complete mitosis and cytokinesis.

Rice panicle phenotyping is important in rice breeding, and rice panicle segmentation is the first and key step for image-based panicle phenotyping. Because of the challenge of illumination differentials, panicle shape deformations, rice accession variations, different reproductive stages and the field's complex background, rice panicle segmentation in the field is a very large challenge.

With progress of genetic sequencing technology, plant genomics has experienced rapid development and subsequently triggered the progress of plant phenomics. In this study, a high-throughput hyperspectral imaging system (HHIS) was developed to obtain 1,540 hyperspectral indices at whole-plant level during tillering, heading, and ripening stages. These indices were used to quantify traditional agronomic traits and to explore genetic variation. We performed genome-wide association study (GWAS) of these indices and traditional agronomic traits in a global rice collection of 529 accessions. With the genome-level suggestive P-value threshold, 989 loci were identified. Of the 1,540 indices, we detected 502 significant indices (designated as hyper-traits) that exhibited phenotypic and genetic relationship with traditional agronomic traits and had high heritability. Many hyper-trait-associated loci could not be detected using traditional agronomic traits. For example, we identified a candidate gene controlling chlorophyll content (Chl). This gene, which was not identified based on Chl, was significantly associated with a chlorophyll-related hyper-trait in GWAS and was demonstrated to control Chl. Moreover, our study demonstrates that red edge (680-760 nm) is vital for rice research for phenotypic and genetic insights. Thus, combination of HHIS and GWAS provides a novel platform for dissection of complex traits and for crop breeding.