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.

Soil salinity is a major abiotic stress in Australian lentil-producing areas. It is therefore imperative to identify genetic variation for salt tolerance in order to develop lentil varieties suitable for saline soils. Conventional screening methods include the manual assessment of stress symptoms, which can be very laborious, time-consuming, and error-prone. Recent advances in image-based high-throughput phenotyping (HTP) technologies have provided unparalleled opportunities to screen plants for a range of stresses, such as salt toxicity. The current study describes the development and application of an HTP method for salt toxicity screening in lentils. In a pilot study, six lentil genotypes were evaluated to determine the optimal salt level and the growth stage for distinguishing lentil genotypes using red–green–blue (RGB) images on a LemnaTec Scanalyzer 3D phenomics platform. The optimized protocol was then applied to screen 276 accessions that were also assessed earlier in a conventional phenotypic screen. Detailed phenotypic trait assessments, including plant growth and green/non-green color pixels, were made and correlated to the conventional screen (r = 0.55; p < 0.0001). These findings demonstrated the improved efficacy of an image-based phenotyping approach that is high-throughput, efficient, and better suited to modern breeding programs.

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. 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. 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.

Seed-associated microbiomes represent an underexplored frontier in synthetic community (SynCom) design, particularly in forage legumes such as lucerne (Medicago sativa L.), where early microbial assembly can shape plant development. Crop wild relatives (CWRs) harbour more diverse seed microbiomes and may contain microbes with greater functional potential than domesticated lucerne. To test this, SynComs were constructed from seed-borne bacteria isolated from M. laciniata (drought-resilient) and M. littoralis (salt-tolerant). Two three-strain SynComs were assembled from taxa consistently shared across lucerne and its CWRs, and a third six-strain ‘Mix’ SynCom combined both sets. The aim of this study was to assess whether these SynComs exert phenotypic effects on lucerne growth when used as seed inocula alongside the native microbiome during early development and later vegetative stages under well-watered and drought conditions. Inoculation enhanced germination and early growth, with the Mix SynCom producing the strongest gains. Microbiome profiling at 24 days revealed treatment-specific restructuring, with enrichment of beneficial taxa and microbial coalescence. While early-stage benefits diminished at later stages, and drought ultimately reduced biomass across all treatments, the findings demonstrate that CWR-derived SynComs can enhance lucerne establishment and early growth while restructuring host microbiomes, providing a framework for seed-applied microbial solutions in sustainable agriculture.

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.

PlantCV is an open‐source Python project aimed at developing tools to address a range of image‐based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data, and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding experience through extensive example use‐case tutorials and simplified installation. In addition to usability, we document added functionality since the release of PlantCV v2, including support for more image types such as fluorescence, thermal, and hyperspectral data. Finally, we describe the development of a new subpackage focused on morphological trait measurements like leaf angle, and demonstrate its utility as compared to more manual methods of data collection.