Mapping and quantifying unique branching structures in lentil (Lens culinaris Medik.).

BACKGROUND: Lentil (Lens culinaris Medik.) is a globally-significant agricultural crop used to feed millions of people. Lentils have been cultivated in the Australian states of Victoria and South Australia for several decades, but efforts are now being made to expand their cultivation into Western Australia and New South Wales. Plant architecture plays a pivotal role in adaptation, leading to improved and stable yields especially in new expansion regions. Image-based high-throughput phenomics technologies provide opportunities for an improved understanding of plant development, architecture, and trait genetics. This paper describes a novel method for mapping and quantifying individual branch structures on immature glasshouse-grown lentil plants grown using a LemnaTec Scanalyser 3D high-throughput phenomics platform, which collected side-view RGB images at regular intervals under controlled photographic conditions throughout the experiment. A queue and distance-based algorithm that analysed morphological skeletons generated from images of lentil plants was developed in Python. This code was incorporated into an image analysis pipeline using open-source software (PlantCV) to measure the number, angle, and length of individual branches on lentil plants. RESULTS: Branching structures could be accurately identified and quantified in immature plants, which is sufficient for calculating early vigour traits, however the accuracy declined as the plants matured. Absolute accuracy for branch counts was 77.9% for plants at 22 days after sowing (DAS), 57.9% at 29 DAS and 51.9% at 36 DAS. Allowing for an error of ± 1 branch, the associated accuracies for the same time periods were 97.6%, 90.8% and 79.2% respectively. Occlusion in more mature plants made the mapping of branches less accurate, but the information collected could still be useful for trait estimation. For branch length calculations, the amount of variance explained by linear mixed-effects models was 82% for geodesic length and 87% for Euclidean branch lengths. Within these models, both the mean geodesic and Euclidean distance measurements of branches were found to be significantly affected by genotype, DAS and their interaction. Two informative metrices were derived from the calculations of branch angle; 'splay' is a measure of how far a branch angle deviates from being fully upright whilst 'angle-difference' is the difference between the smallest and largest recorded branch angle on each plant. The amount of variance explained by linear mixed-effects models was 38% for splay and 50% for angle difference. These lower R2 values are likely due to the inherent difficulties in measuring these parameters, nevertheless both splay and angle difference were found to be significantly affected by cultivar, DAS and their interaction. When 276 diverse lentil genotypes with varying degrees of salt tolerance were grown in a glasshouse-based experiment where a portion were subjected to a salt treatment, the branching algorithm was able to distinguish between salt-treated and untreated lentil lines based on differences in branch counts. Likewise, the mean geodesic and Euclidean distance measurements of branches were both found to be significantly affected by cultivar, DAS and salt treatment. The amount of variance explained by the linear mixed-effects models was 57.8% for geodesic branch length and 46.5% for Euclidean branch length. CONCLUSION: The methodology enabled the accurate quantification of the number, angle, and length of individual branches on glasshouse-grown lentil plants. This methodology could be applied to other dicotyledonous species.

Haplotype-Based Genome-Wide Association Analysis Using Exome Capture Assay and Digital Phenotyping Identifies Genetic Loci Underlying Salt Tolerance Mechanisms in Wheat.

Soil salinity can impose substantial stress on plant growth and cause significant yield losses. Crop varieties tolerant to salinity stress are needed to sustain yields in saline soils. This requires effective genotyping and phenotyping of germplasm pools to identify novel genes and QTL conferring salt tolerance that can be utilised in crop breeding schemes. We investigated a globally diverse collection of 580 wheat accessions for their growth response to salinity using automated digital phenotyping performed under controlled environmental conditions. The results show that digitally collected plant traits, including digital shoot growth rate and digital senescence rate, can be used as proxy traits for selecting salinity-tolerant accessions. A haplotype-based genome-wide association study was conducted using 58,502 linkage disequilibrium-based haplotype blocks derived from 883,300 genome-wide SNPs and identified 95 QTL for salinity tolerance component traits, of which 54 were novel and 41 overlapped with previously reported QTL. Gene ontology analysis identified a suite of candidate genes for salinity tolerance, some of which are already known to play a role in stress tolerance in other plant species. This study identified wheat accessions that utilise different tolerance mechanisms and which can be used in future studies to investigate the genetic and genic basis of salinity tolerance. Our results suggest salinity tolerance has not arisen from or been bred into accessions from specific regions or groups. Rather, they suggest salinity tolerance is widespread, with small-effect genetic variants contributing to different levels of tolerance in diverse, locally adapted germplasm.

An image dataset of diverse safflower (Carthamus tinctorius L.) genotypes for salt response phenotyping.

This article describes a dataset of high-resolution visible-spectrum images of safflower (Carthamus tinctorius L.) plants obtained from a LemnaTec Scanalyser automated phenomics platform along with the associated image analysis output and manually acquired biomass data. This series contains 1832 images of 200 diverse safflower genotypes, acquired at the Plant Phenomics Victoria, Horsham, Victoria, Australia. Two Prosilica GT RGB (red-green-blue) cameras were used to generate 6576 × 4384 pixel portable network graphic (PNG) images. Safflower genotypes were either subjected to a salt treatment (250 mM NaCl) or grown as a control (0 mM NaCl) and imaged daily from 15 to 36 days after sowing. Each snapshot consists of four images collected at a point in time; one of which is taken from above (top-view) and the remainder from the side at either 0°, 120° or 240°. The dataset also includes analysis output quantifying traits and describing phenotypes, as well as manually collected biomass and leaf ion content data. The usage of the dataset is already demonstrated in Thoday-Kennedy et al. (2021) [1]. This dataset describes the early growth differences of diverse safflower genotypes and identified genotypes tolerant or susceptible to salinity stress. This dataset provides detailed image analysis parameters for phenotyping a large population of safflower that can be used for the training of image-based trait identification pipelines for a wide range of crop species.

Rapid Screening of Nitrogen Use Efficiency in Perennial Ryegrass (Lolium perenne L.) Using Automated Image-Based Phenotyping.

Perennial ryegrass (Lolium perenne L.) is a dominant species in temperate Australian pastures. Currently, nitrogenous fertilizers are used to support herbage production for pasture and fodder. Increasing the nitrogen use efficiency (NUE) of pasture grasses could decrease the amount of fertilizer application and reduce nitrogen (N) leaching into the environment. NUE, defined as units of dry matter production per unit of supplied nitrogen, is a complex trait in which genomic selection may provide a promising strategy in breeding. Our objective was to develop a rapid, high-throughput screening method to enable genomic selection for y -60NUE in perennial ryegrass. NUE of 76 genotypes of perennial ryegrass from a breeding population were screened in a greenhouse using an automated image-based phenomics platform under low (0.5 mM) and moderate (5 mM) N levels over 3 consecutive harvests. Significant (p < 0.05) genotype, treatment, and genotype by treatment interactions for dry matter yield and NUE were observed. NUE under low and moderate N treatments was significantly correlated. Of the seven plant architecture features directly extracted from image analysis and four secondarily derived measures, mean projected plant area (MPPA) from the two side view images had the highest correlation with dry matter yield (r = 0.94). Automated digital image-based phenotyping enables temporal plant growth responses to N to be measured efficiently and non-destructively. The method developed in this study would be suitable for screening large populations of perennial ryegrass growth in response to N for genomic selection purposes.

Optical and physical mapping with local finishing enables megabase-scale resolution of agronomically important regions in the wheat genome.

BACKGROUND: Numerous scaffold-level sequences for wheat are now being released and, in this context, we report on a strategy for improving the overall assembly to a level comparable to that of the human genome. RESULTS: Using chromosome 7A of wheat as a model, sequence-finished megabase-scale sections of this chromosome were established by combining a new independent assembly using a bacterial artificial chromosome (BAC)-based physical map, BAC pool paired-end sequencing, chromosome-arm-specific mate-pair sequencing and Bionano optical mapping with the International Wheat Genome Sequencing Consortium RefSeq v1.0 sequence and its underlying raw data. The combined assembly results in 18 super-scaffolds across the chromosome. The value of finished genome regions is demonstrated for two approximately 2.5 Mb regions associated with yield and the grain quality phenotype of fructan carbohydrate grain levels. In addition, the 50 Mb centromere region analysis incorporates cytological data highlighting the importance of non-sequence data in the assembly of this complex genome region. CONCLUSIONS: Sufficient genome sequence information is shown to now be available for the wheat community to produce sequence-finished releases of each chromosome of the reference genome. The high-level completion identified that an array of seven fructosyl transferase genes underpins grain quality and that yield attributes are affected by five F-box-only-protein-ubiquitin ligase domain and four root-specific lipid transfer domain genes. The completed sequence also includes the centromere.

Reduced lignin content and altered lignin composition in the warm season forage grass Paspalum dilatatum by down-regulation of a Cinnamoyl CoA reductase gene.

C4 grasses are favoured as forage crops in warm, humid climates. The use of C4 grasses in pastures is expected to increase because the tropical belt is widening due to global climate change. While the forage quality of Paspalum dilatatum (dallisgrass) is higher than that of other C4 forage grass species, digestibility of warm-season grasses is, in general, poor compared with most temperate grasses. The presence of thick-walled parenchyma bundle-sheath cells around the vascular bundles found in the C4 forage grasses are associated with the deposition of lignin polymers in cell walls. High lignin content correlates negatively with digestibility, which is further reduced by a high ratio of syringyl (S) to guaiacyl (G) lignin subunits. Cinnamoyl-CoA reductase (CCR) catalyses the conversion of cinnamoyl CoA to cinnemaldehyde in the monolignol biosynthetic pathway and is considered to be the first step in the lignin-specific branch of the phenylpropanoid pathway. We have isolated three putative CCR1 cDNAs from P. dilatatum and demonstrated that their spatio-temporal expression pattern correlates with the developmental profile of lignin deposition. Further, transgenic P. dilatatum plants were produced in which a sense-suppression gene cassette, delivered free of vector backbone and integrated separately to the selectable marker, reduced CCR1 transcript levels. This resulted in the reduction of lignin, largely attributable to a decrease in G lignin.