Genetic susceptibility to late maturity alpha-amylase (LMA) in wheat (Triticum aestivum L.) results in increased alpha-amylase activity in mature grain when cool conditions occur during late grain maturation. Farmers are forced to sell wheat grain with elevated alpha-amylase at a discount because it has an increased risk of poor end-product quality. This problem can result from either LMA or preharvest sprouting, grain germination on the mother plant when rain occurs before harvest. Whereas preharvest sprouting is a well-understood problem, little is known about the risk LMA poses to North American wheat crops. To examine this, LMA susceptibility was characterized in a panel of 251 North American hard spring wheat lines, representing ten geographical areas. It appears that there is substantial LMA susceptibility in North American wheat since only 27% of the lines showed reproducible LMA resistance following cold-induction experiments. A preliminary genome-wide association study detected six significant marker-trait associations. LMA in North American wheat may result from genetic mechanisms similar to those previously observed in Australian and International Maize and Wheat Improvement Center (CIMMYT) germplasm since two of the detected QTLs, QLMA.wsu.7B and QLMA.wsu.6B, co-localized with previously reported loci. The Reduced height (Rht) loci also influenced LMA. Elevated alpha-amylase levels were significantly associated with the presence of both wild-type and tall height, rht-B1a and rht-D1a, loci in both cold-treated and untreated samples.

Alfalfa is the most widely cultivated forage legume, with approximately 30 million hectares planted worldwide. Genetic improvements in alfalfa have been highly successful in developing cultivars with exceptional winter hardiness and disease resistance traits. However, genetic improvements have been limited for complex economically important traits such as biomass. One of the major bottlenecks is the labor-intensive phenotyping burden for biomass selection. In this study, we employed two alfalfa fields to pave a path to overcome the challenge by using UAV images with fully automatic field plot segmentation for high-throughput phenotyping. The first field was used to develop the prediction model and the second field to validate the predictions. The first and second fields had 808 and 1025 plots, respectively. The first field had three harvests with biomass measured in May, July, and September of 2019. The second had one harvest with biomass measured in September of 2019. These two fields were imaged one day before harvesting with a DJI Phantom 4 pro UAV carrying an additional Sentera multispectral camera. Alfalfa plot images were extracted by GRID software to quantify vegetative area based on the Normalized Difference Vegetation Index. The prediction model developed from the first field explained 50–70% (R Square) of biomass variation in the second field by incorporating four features from UAV images: vegetative area, plant height, Normalized Green–Red Difference Index, and Normalized Difference Red Edge Index. This result suggests that UAV-based, high-throughput phenotyping could be used to improve the efficiency of the biomass selection process in alfalfa breeding programs.

Quantification of variation for phenotypic traits within and among weed populations facilitate understanding of invasion mechanisms and management tactics. In the Pacific Northwest (PNW), USA, in response to climate change and to improve sustainability, producers are increasingly adopting broadleaf crops and cover crops, but Mayweed chamomile (Anthemis cotula L.) is a significant barrier to diversifying cropping systems because of its abundance and lack of herbicide options for its control. To quantify within-population phenotypic trait variation and heritability, plants (n = 300) from six half-sib families (i.e., seed source plants or mother plants) from each of 10 A. cotula populations (infested farms or sites) in the PNW were grown from seed through the flowering stage in the greenhouse common garden experiment. We measured percent seedling emergence, the initial date of flowering, flowering duration, plant biomass, number of flower heads, floral scent profiles, and other traits on individual plants. Trait variation was high among half-sib families within each population. For example, in two of the populations, percent seedling emergence within 30 days of planting ranged from 5 to 41% and 3 to 53%, respectively. As another example, initial date of flowering in two other populations ranged from 61 to 93 days and 58 to 92 days, respectively. Differences among half-sib families were greatest for flowering period, which differed by a month in most populations, and floral scent profiles. Heritability estimates were higher than 1.0 for most phenotypic traits, indicating that the study plants were more closely related than half-sibs (i.e., included full-sibs or products of selfing). These patterns of phenotypic trait variation are potentially caused by local edaphoclimatic factors and within-field farm management practices, suggesting that management of A. cotula might be challenging and differ within and across farms.

Bromus tectorum L. is arguably the most successful invasive weed in the world. It has fundamentally altered arid ecosystems of the western United States, where it now found on an excess of 20 million hectares and costs land managers and growers through lost yield, land utility, and increased incidence of fire. Invasion success is often related to avoidance of abiotic stress and human management. Early flowering is a complex but heritable trait utilized by B. tectorum that enables the species to temporally monopolize limited resources and thus outcompete native plant community. Thus, understanding the genetic underpinning of flowering time is critical for the design of integrated management strategies – regardless of the invaded ecosystem. To study flowering time traits in B. tectorum, we assembled the first chromosome scale reference genome using PacBio long reads, assembled using the Canu assembler, and scaffolded using Omni-C chromatin contact mapping technology. The final assembly spanned 2.482 Gb in length and has an N50 and L50 of 357 Mb and 4, respectively. To assess the utility of the assembled genome for trait discovery, 121 diverse B. tectorum accessions were phenotyped in replicated greenhouse trials, genotyped by sequencing and subjected to a genome wide association study (GWAS). Significantly (q < 0.05) associated QTLs were identified for height, days to first joint (J1), days to first visible panicle (VPN), and days to first ripe seed (FRS). Overlap between significant QTLs was present between traits, suggesting pleiotropy or closely linked QTLs for life cycle related traits. Candidate genes, representing homologs of an array of genes that have been previously associated with plant height or flowering phenology traits in related species, were located near significant QTLs. The GWAS, combined with a well annotated genome, is a viable method for identifying candidate genes associated with weedy characteristics in invasive weeds. This is the first study using high-resolution GWAS to identify phenology related genes in a weedy species and represents a significant step forward in our understanding of the mechanisms underlying genetic plasticity in one of the most successful invasive weed species in the world.

Winter wheat (Triticum aestivum L.) undergoes a period of cold acclimation in order to survive the ensuing winter, which can bring freezing temperatures and snow mold infection. Tolerance of these stresses is conferred in part by accumulation of carbohydrates in the crown region. This study investigates the contributions of carbohydrate accumulation during a cold treatment among wheat lines that differ in their snow mold tolerance (SMT) or susceptibility (SMS) and freezing tolerance (FrT) or susceptibility (FrS). Two parent varieties and eight recombinant inbred lines (RILs) were analyzed. The selected RILs represent four combinations of tolerance: SMT/FrT, SMT/FrS, SMS/FrT, and SMS/FrS. It is hypothesized that carbohydrate accumulation and transcript expression will differ between sets of RILs. Liquid chromatography with a refractive index detector was used to quantify carbohydrate content at eight time points over the cold treatment period. Polysaccharide and sucrose content differed between SMT and SMS RILs at various time points, although there were no significant differences in glucose or fructose content. Glucose and fructose content differed between FrT and FrS RILs in this study, but no significant differences in polysaccharide or sucrose content. RNAseq was used to investigate differential transcript expression, followed by modular enrichment analysis, to reveal potential candidates for other mechanisms of tolerance, which included expected pathways such as oxidative stress, chitinase activity, and unexpected transcriptional pathways. These differences in carbohydrate accumulation and differential transcript expression begin to give insight into the differences of wheat lines when exposed to cold temperatures.