Biomass production represents a fundamental biological process of both ecological and agricultural significance. The genetic basis of biomass production is unknown but asssumed to be complex. We developed a full sib, F1 mapping population of autotetraploid Medicago sativa (alfalfa) derived from an intersubspecific cross that was known to produce heterosis for biomass production. We evaluated the population for biomass production over several years at three locations (Ames, IA, Nashua, IA, and Ithaca, NY) and concurrently developed a genetic linkage map using restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR) molecular markers. Transgressive segregants, many of which exhibited high levels of heterosis, were identified in each environment. Despite the complexities of mapping within autotetraploid populations, single‐marker analysis of variance identified 41 marker alleles, many on linkage groups 5 and 7, associated with biomass production in at least one of the sampling periods. Seven alleles were associated with biomass production in more than one of the sampling periods. Favorable alleles were contributed by both parents, one of which is from the M. sativa subsp. falcata germplasm. Thus, increased biomass production alleles can be gleaned from unadapted germplasm. Further, the positive quantitative trait locus (QTL) alleles from the parents are partially complementary, suggesting these loci may play a role in biomass production heterosis.

Hemp (Cannabis sativa L.) is an emerging dioecious crop grown primarily for grain, fiber, and cannabinoids. There is good evidence for medicinal benefits of the most abundant cannabinoid in hemp, cannabidiol (CBD). For CBD production, female plants producing CBD but not tetrahydrocannabinol (THC) are desired. We developed and validated high‐throughput PACE (PCR Allele Competitive Extension) assays for C. sativa plant sex and cannabinoid chemotype. The sex assay was validated across a wide range of germplasm and resolved male plants from female and monoecious plants. The cannabinoid chemotype assay revealed segregation in hemp populations, and resolved plants producing predominantly THC, predominantly CBD, and roughly equal amounts of THC and CBD. Cultivar populations that were thought to be stabilized for CBD production were found to be segregating phenotypically and genotypically. Many plants predominantly producing CBD accumulated more than the current US legal limit of 0.3% THC by dry weight. These assays and data provide potentially useful tools for breeding and early selection of hemp.

Alfalfa (Medicago sativa L.), an important forage crop that is also a potential biofuel crop, has advantages of high yield, high lignocellulose concentration in stems, and has low input costs. In this study, we investigated population structure and linkage disequilibrium (LD) patterns in a tetraploid alfalfa breeding population using genome-wide simple sequence repeat (SSR) markers and identifi ed markers related to yield and cell wall composition by association mapping. No obvious population structure was found in our alfalfa breeding population, which could be due to the relatively narrow genetic base of the founders and/or due to two generations of random mating. We found signifi cant LD (p < 0.001) between 61.5% of SSR marker pairs separated by less than 1 Mbp. The observed large extent of LD could be explained by the effect of bottlenecking and selection or the high mutation rates of SSR markers. Total marker heterozygosity was positively related to biomass yield in each of fi ve environments, but no relationship was noted for stem composition traits. Of a total of 312 nonrare (frequency >10%) alleles across the 71 SSR markers, 15 showed strong association (p < 0.005) with yield in at least one of fi ve environments, and most of the 15 alleles were identifi ed in multiple environments. Only one allele showed strong association with acid detergent fi ber (ADF) and one allele with acid detergent lignin (ADL). Alleles associated with traits could be directly applied in a breeding program using marker-assisted selection. However, based on our estimated LD level, we would need about 1000 markers to explore the whole alfalfa genome for association between markers and traits.

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Current knowledge of yield potential and best agronomic management practices for perennial bioenergy grasses is primarily derived from small-scale and short-term studies, yet these studies inform policy at the national scale. In an effort to learn more about how bioenergy grasses perform across multiple locations and years, the U.S. Department of Energy (US DOE)/Sun Grant Initiative Regional Feedstock Partnership was initiated in 2008. The objectives of the Feedstock Partnership were to (1) provide a wide range of information for feedstock selection (species choice) and management practice options for a variety of regions and (2) develop national maps of potential feedstock yield for each of the herbaceous species evaluated. The Feedstock Partnership expands our previous understanding of the bioenergy potential of switchgrass, Miscanthus, sorghum, energycane, and prairie mixtures on Conservation Reserve Program land by conducting long-term, replicated trials of each species at diverse environments in the U.S. Trials were initiated between 2008 and 2010 and completed between 2012 and 2015 depending on species. Field-scale plots were utilized for switchgrass and Conservation Reserve Program trials to use traditional agricultural machinery. This is important as we know that the smaller scale studies often overestimated yield potential of some of these species. Insufficient vegetative propagules of energycane and Miscanthus prohibited farm-scale trials of these species. The Feedstock Partnership studies also confirmed that environmental differences across years and across sites had a large impact on biomass production. Nitrogen application had variable effects across feedstocks, but some nitrogen fertilizer generally had a positive effect. National yield potential maps were developed using PRISM-ELM for each species in the Feedstock Partnership. This manuscript, with the accompanying supplemental data, will be useful in making decisions about feedstock selection as well as agronomic practices across a wide region of the country.

Alfalfa (Medicago sativa L.) is a widely planted perennial forage legume grown throughout temperate and dry subtropical regions in the world. Long breeding cycles limit genetic improvement of alfalfa, particularly for complex traits such as biomass yield. Genomic selection (GS), based on predicted breeding values obtained using genome-wide molecular markers, could enhance breeding efficiency in terms of gain per unit time and cost. In this study, we genotyped tetraploid alfalfa plants that had previously been evaluated for yield during two cycles of phenotypic selection using genotyping-by-sequencing (GBS). We then developed prediction equations using yield data from three locations. Approximately 10,000 single nucleotide polymorphism (SNP) markers were used for GS modeling. The genomic prediction accuracy of total biomass yield ranged from 0.34 to 0.51 for the Cycle 0 population and from 0.21 to 0.66 for the Cycle 1 population, depending on the location. The GS model developed using Cycle 0 as the training population in predicting total biomass yield in Cycle 1 resulted in accuracies up to 0.40. Both genotype  environment interaction and the number of harvests and years used to generate yield phenotypes had effects on prediction accuracy across generations and locations, Based on our results, the selection efficiency per unit time for GS is higher than phenotypic selection, although accuracies will likely decline across multiple selection cycles. This study provided evidence that GS can accelerate genetic gain in alfalfa for biomass yield.

The Regional Feedstock Partnership is a collaborative effort between the Sun Grant Initiative (through Land Grant Universities), the US Department of Energy, and the US Department of Agriculture. One segment of this partnership is the field-scale evaluation of switchgrass (Panicum virgatum L.) in diverse sites across the USA. Switchgrass was planted (11.2 kg PLS ha −1 ) in replicated plots in New York, Oklahoma, South Dakota, and Virginia in 2008 and in Iowa in 2009. Adapted switchgrass cultivars were selected for each location and baseline soil samples collected before planting. Nitrogen fertilizer (0, 56, and 112 kg N ha −1 ) was applied each spring beginning the year after planting, and switchgrass was harvested once annually after senescence. Establishment, management, and harvest operations were completed using fieldscale equipment. Switchgrass production ranged from 2 to 11.5 Mg ha −1 across locations and years. Yields were lowest the first year after establishment. Switchgrass responded positively to N in 6 of 19 location/year combinations and there was one location/year combination (NY in Year 2) where a significant negative response was noted. Initial soil N levels were lowest in SD and VA (significant N response) and highest at the other three locations (no N response). Although N rate affected some measures of biomass quality (N and hemicellulose), location and year had greater overall effects on all quality parameters evaluated. These results demonstrate the importance of local field-scale research and of proper N management in order to reduce unnecessary expense and potential environmental impacts of switchgrass grown for bioenergy.

Switchgrass (Panicum virgatum L.) has been the principal perennial herbaceous crop investigated for bioenergy production in North America given its high production potential, relatively low input requirements, and potential suitability for use on marginal lands. Few large trials have determined switchgrass yields at field scale on marginal lands, including analysis of production costs. Thus, a field-scale study was conducted to develop realistic yield and cost estimates for diverse regions of the USA. Objectives included measuring switchgrass response to fertility treatments (0, 56, and 112 kg N ha À1 ) and generating corresponding estimates of production costs for sites with diverse soil and climatic conditions. Trials occurred in Iowa, New York, Oklahoma, South Dakota, and Virginia, USA. Cultivars and management practices were site specific, and field-scale equipment was used for all management practices. Input costs were estimated using final harvest-year (2015) prices, and equipment operation costs were estimated with the MachData model ($2015). Switchgrass yields generally were below those reported elsewhere, averaging 6.3 Mg ha À1 across sites and treatments. Establishment stand percent ranged from 28% to 76% and was linked to initial year production. No response to N was observed at any site in the first production year. In subsequent seasons, N generally increased yields on well-drained soils; however, responses to N were nil or negative on less well-drained soils. Greatest percent increases in response to 112 kg N ha À1 were 57% and 76% on well-drained South Dakota and Virginia sites, where breakeven prices to justify N applications were over $70 and $63 Mg À1 , respectively. For some sites, typically promoted N application rates may be economically unjustified; it remains unknown whether a bioenergy industry can support the breakeven prices estimated for sites where N inputs had positive effects on switchgrass yield.