Economic and Sustainability Impacts of Yield and Composition Variation in Bioenergy Crops: Switchgrass (Panicum virgatum L.).

Economically viable production of biobased products and fuels requires high-yielding, high-quality, sustainable process-advantaged crops, developed using bioengineering or advanced breeding approaches. Understanding which crop phenotypic traits have the largest impact on biofuel economics and sustainability outcomes is important for the targeted feedstock crop development. Here, we evaluated biomass yield and cell-wall composition traits across a large natural variant population of switchgrass (Panicum virgatum L.) grown across three common garden sites. Samples from 331 switchgrass genotypes were collected and analyzed for carbohydrate and lignin components. Considering plant survival and biomass after multiple years of growth, we found that 84 of the genotypes analyzed may be suited for commercial production in the southeastern U.S. These genotypes show a range of growth and compositional traits across the population that are apparently independent of each other. We used these data to conduct techno-economic analyses and life cycle assessments evaluating the performance of each switchgrass genotype under a standard cellulosic ethanol process model with pretreatment, added enzymes, and fermentation. We find that switchgrass yield per area is the largest economic driver of the minimum fuel selling price (MSFP), ethanol yield per hectare, global warming potential (GWP), and cumulative energy demand (CED). At any yield, the carbohydrate content is significant but of secondary importance. Water use follows similar trends but has more variability due to an increased dependence on the biorefinery model. Analyses presented here highlight the primary importance of plant yield and the secondary importance of carbohydrate content when selecting a feedstock that is both economical and sustainable.

Mapping freezing tolerance QTL in alfalfa: based on indoor phenotyping.

BACKGROUND: Winter freezing temperature impacts alfalfa (Medicago sativa L.) persistence and seasonal yield and can lead to the death of the plant. Understanding the genetic mechanisms of alfalfa freezing tolerance (FT) using high-throughput phenotyping and genotyping is crucial to select suitable germplasm and develop winter-hardy cultivars. Several clones of an alfalfa F1 mapping population (3010 x CW 1010) were tested for FT using a cold chamber. The population was genotyped with SNP markers identified using genotyping-by-sequencing (GBS) and the quantitative trait loci (QTL) associated with FT were mapped on the parent-specific linkage maps. The ultimate goal is to develop non-dormant and winter-hardy alfalfa cultivars that can produce extended growth in the areas where winters are often mild. RESULTS: Alfalfa FT screening method optimized in this experiment comprises three major steps: clone preparation, acclimation, and freezing test. Twenty clones of each genotype were tested, where 10 samples were treated with freezing temperature, and 10 were used as controls. A moderate positive correlation (r ~ 0.36, P < 0.01) was observed between indoor FT and field-based winter hardiness (WH), suggesting that the indoor FT test is a useful indirect selection method for winter hardiness of alfalfa germplasm. We detected a total of 20 QTL associated with four traits; nine for visual rating-based FT, five for percentage survival (PS), four for treated to control regrowth ratio (RR), and two for treated to control biomass ratio (BR). Some QTL positions overlapped with WH QTL reported previously, suggesting a genetic relationship between FT and WH. Some favorable QTL from the winter-hardy parent (3010) were from the potential genic region for a cold tolerance gene CBF. The BLAST alignment of a CBF sequence of M. truncatula, a close relative of alfalfa, against the alfalfa reference showed that the gene's ortholog resides around 75 Mb on chromosome 6. CONCLUSIONS: The indoor freezing tolerance selection method reported is useful for alfalfa breeders to accelerate breeding cycles through indirect selection. The QTL and associated markers add to the genomic resources for the research community and can be used in marker-assisted selection (MAS) for alfalfa cold tolerance improvement.

Current Progress in Nitrogen Fixing Plants and Microbiome Research.

In agroecosystems, nitrogen is one of the major nutrients limiting plant growth. To meet the increased nitrogen demand in agriculture, synthetic fertilizers have been used extensively in the latter part of the twentieth century, which have led to environmental challenges such as nitrate pollution. Biological nitrogen fixation (BNF) in plants is an essential mechanism for sustainable agricultural production and healthy ecosystem functioning. BNF by legumes and associative, endosymbiotic, and endophytic nitrogen fixation in non-legumes play major roles in reducing the use of synthetic nitrogen fertilizer in agriculture, increased plant nutrient content, and soil health reclamation. This review discusses the process of nitrogen-fixation in plants, nodule formation, the genes involved in plant-rhizobia interaction, and nitrogen-fixing legume and non-legume plants. This review also elaborates on current research efforts involved in transferring nitrogen-fixing mechanisms from legumes to non-legumes, especially to economically important crops such as rice, maize, and wheat at the molecular level and relevant other techniques involving the manipulation of soil microbiome for plant benefits in the non-legume root environment.

Correction to: QTL mapping of flowering time and biomass yield in tetraploid alfalfa (Medicago sativa L.).

In the article [1], in 'Methods' section and 'G x E and heritability' subsection, there is an error in the formula of heritability (H2).

QTL mapping of flowering time and biomass yield in tetraploid alfalfa (Medicago sativa L.).

BACKGROUND: The genetic and genomic basis of flowering time and biomass yield in alfalfa (Medicago sativa L.) remains poorly understood mainly due to the autopolyploid nature of the species and the lack of adequate genomic resources. We constructed linkage maps using genotyping-by-sequencing (GBS) based single dose allele (SDA) SNP and mapped alfalfa timing of flowering (TOF), spring yield (SY), and cumulative summer biomass (CSB) in a pseudo-testcross F1 population derived from a fall dormant (3010) and a non-dormant (CW 1010) cultivars. We analyzed the quantitative trait loci (QTL) to identify conserved genomic regions and detected molecular markers and potential candidate genes associated with the traits to improve alfalfa and provide genomic resources for the future studies. RESULTS: This study showed that both fall dormant and non-dormant alfalfa cultivars harbored QTL for early and late flowering, suggesting that flowering time in alfalfa is not an indicator of its fall dormancy (FD) levels. A weak phenotypic correlation between the flowering time and fall dormancy (FD) in F1 and checks also corroborated that alfalfa FD and TOF are not the predictors of one another. The relationship between flowering time and alfalfa biomass yield was not strong, but the non-dormant had relatively more SY than dormant. Therefore, selecting superior alfalfa cultivars that are non-dormant, winter-hardy, and early flowering would allow for an early spring harvest with enhanced biomass. In this study, we found 25 QTL for TOF, 17 for SY and six QTL for CSB. Three TOF related QTL were stable and four TOF QTL were detected in the corresponding genomic locations of the flowering QTL of M. truncatula, an indication of possible evolutionarily conserved regions. The potential candidate genes for the SNP sequences of QTL regions were identified for all three traits and these genes would be potential targets for further molecular studies. CONCLUSIONS: This research showed that variation in alfalfa flowering time after spring green up has no association with dormancy levels. Here we reported QTL, markers, and potential candidate genes associated with spring flowering time and biomass yield of alfalfa, which constitute valuable genomic resources for improving these traits via marker-assisted selection (MAS).

Quantitative Trait Loci Mapping for Tillering-Related Traits in Two Switchgrass Populations.

Plant tillering and related traits are morphologically important components contributing to switchgrass ( L.) biomass yield. The objectives of this study were to estimate broad-sense heritabilities for tillering-related traits, to analyze correlations between biomass yield and the traits, and to identify quantitative trait loci (QTL) for them. A first-generation selfed population of NL94 plant and a hybrid population between NL94 and SL93 plants were field established in a randomized complete block design with three replications in Stillwater and Perkins, OK. Phenotypic data were collected in 2 yr and genotypic data were obtained by genotyping simple-sequence repeat (SSR) markers in the two populations on the basis of two preexisting genetic maps. Plant base size (PBS), plant girth (PG), tillering ability (TA), tiller diameter (TD), and tiller dry weight (TDW) were positively correlated with biomass yield in both populations. Consistently, PBS had the largest correlation coefficients for biomass yield, suggesting its value as an indirect selection criterion for biomass yield. Twenty and 26 QTL for six tillering-related traits were detected in the hybrid and selfed population, respectively. Among the QTL, one on linkage group (LG) 5a between sww-2387/PVCAG-2197/2198 and PVGA-1649/1650 for PBS, PG, and TA and another on LG 2a between sww-2640/sww-2545 and PVCA-765/766 for TD and TDW were stably detected in multiple environments in the two populations. The findings add to the knowledge base regarding the genetics of tillering-related traits that could be used in accelerating the development of high-yielding cultivars through marker-assisted selection.