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.

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). Electronic supplementary material The online version of this article (10.1186/s12870-019-1946-0) contains supplementary material, which is available to authorized users.

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The maximum biomass yield of switchgrass (Panicum virgatum L.) usually is achieved with one seasonal autumn harvest. However, information is limited on the influences of winter harvesting on annual biomass yield and on quality parameters impacting conversion into bioethanol. Accordingly, the objectives of this study were to assess: (i) yield of standing field cured biomass at monthly intervals through winter, (ii) year‐round elemental composition of biomass, and (iii) associated year‐round soil nutrient status. An unfertilized ‘Kanlow’ switchgrass planting established in 1998 was used for this study conducted from November 2007 to October 2010. The experimental treatment was monthly harvest from November to the following March and year‐round monthly sampling of biomass (except April) and soil for chemical analyses. The 3‐yr mean dry matter yield of winter harvests was 5.94Mg ha−1, ranging from 3.88 Mg ha−1 in the winter of 2007–2008 to 7.55 Mg ha−1 in 2009–2010. Monthly biomass yield differences were significant in Years 1 and 3 but not in Year 2. Concentrations of biomass elements and soil nutrients changed with various degrees over the 3 yr. Concentrations of ash, cell wall components, and mineral nutrients, except P, K, and S, did not change appreciably across winter months. Early winter harvests resulted in less yield loss compared to late winter harvests. These findings will be valuable in harvest management for switchgrass biomass production.

Plant tillering and related traits are morphologically important components contributing to switchgrass (Panicum virgatum L.) biomass yield. The objectives of this study were to estimate broadsense 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 highyielding cultivars through marker-assisted selection.

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Turfgrass varietal identification is critical and allows turfgrass professionals to manage the turf based on the cultural requirements of the variety. On the Oklahoma State University (OSU) Baseball Field (OSUBF) in Stillwater, OK, some bermudagrass (Cynodon sp.) plants exhibited desirable traits but their exact identities were unknown due to the installation of multiple varieties over time. Accordingly, the major objective of this study was to identify if the desirable bermudagrass plants were from commercially available known varieties. Recently, the OSU turf bermudagrass breeding program developed and entered three fairway-type clonal bermudagrasses in the 2013 National Turfgrass Evaluation Program (NTEP) bermudagrass trial: OKC 1131, OKC 1163, and OKC 1302. The secondary objective was to create molecular marker profiles for these three experimental lines. Five OSUBF samples were analyzed using simple sequence repeat (SSR) markers, along with 24 clonal, commercially available turf bermudagrass varieties widely used in Oklahoma, the three OSU experimental clones, six randomly selected single plants from ‘Riviera’, and two controls for common bermudagrass (Cynodon dactylon) and african bermudagrass (Cynodon transvaalensis). SSR marker genotyping data indicated that the five OSUBF plants were clones of an identical bermudagrass. The OSUBF bermudagrass had the same fingerprint as ‘Astro-DLM’ bermudagrass for 14 out of 16 SSRs genotyped. Fifteen out of 30 additional SSR markers also showed differences between the OSUBF bermudagrass and ‘Astro-DLM’. The three OSU experimental clones were different from each other and had different fingerprints from the other tested varieties based on SSR profiles, indicating they are new breeding lines. These four distinct lines have potential to be released as new varieties if they demonstrate superior turf quality traits and adaptation over time.

Timing of biomass removal from stands of switchgrass (Panicum virgatum L.) impacts the nutrient content of harvested material and fertilizer requirements for subsequent growing seasons. is study was conducted to determine the change in N, P, and K content of harvested switchgrass biomass as a function of the harvest date and to determine the economic consequences of an extended harvest window. Data were produced in a randomized complete block study conducted at the Oklahoma Agricultural Experiment Station, Stillwater, with six replications over three harvest seasons from November of 2007 to March of 2010. Treatments on the established stand of cultivar Kanlow consisted of ve harvest dates separated by about 30 d beginning in late November. Regression equations were used to t yield and N, P, and K concentration response to the harvest date. Delaying harvest beyond December resulted in an average 5.4% decline in harvested biomass per month. Delaying harvest beyond November did not result in a signi cant change in the N concentration in the harvested biomass. However, delaying harvest did result in a signi cant decrease in both P and K content in the harvested biomass. Point estimates from the response functions were used to estimate production cost for each of ve harvest dates beginning with 30 November and ending with 30 March. e quantities of P 2 O 5 and K 2 O fertilizer that would be required to replace the P and K removed with the biomass were used in the budgets. Biomass production cost was similar across harvest dates.