Bioenergy Crops Research Articles

Water loss through evapotranspiration after precipitation events in bioenergy crops grown in similar climatic conditions

Water loss through evapotranspiration after precipitation events in bioenergy crops grown in similar climatic conditions

Integration of Renewable Energy Solutions in Agricultural Operations

The integration of renewable energy solutions in agricultural operations presents a transformative approach to enhancing sustainability, reducing greenhouse gas emissions, and improving the economic viability of farming practices and explores the various renewable energy technologies applicable to agriculture, including solar, wind, biomass, and biogas energy solutions. Each technology is examined for its specific applications within the agricultural sector, highlighting its potential benefits and the challenges faced in implementation. Solar energy, through photovoltaic and thermal systems, offers significant potential for powering irrigation, greenhouse operations, and processing facilities, thereby reducing reliance on fossil fuels and grid electricity. Wind energy, with its ability to generate electricity through turbines, is particularly valuable in regions with consistent wind patterns, contributing to both onfarm energy needs and grid supply. Biomass energy, utilizing agricultural residues and dedicated bioenergy crops, provides a sustainable solution for heating and energy generation, while also addressing waste management challenges. Biogas production, through anaerobic digestion of organic waste, presents a dual benefit of generating renewable energy and improving nutrient recycling in farming systems. Government subsidies, feedin tariffs, research funding, and technical support play pivotal roles in encouraging farmers to transition to renewable energy sources. Case studies from various regions illustrate the practical implementation of these technologies, demonstrating their impact on enhancing agricultural productivity, reducing environmental footprints, and fostering energy independence, including policymakers, researchers, and farmers, about the opportunities and challenges in adopting sustainable energy practices. The findings underscore the importance of continued innovation, supportive policies, and collaborative efforts to achieve a resilient and sustainable agricultural sector.

In silico Analysis and Characterization of the F5H Gene Family in Sorghum bicolor and Its Role in Lignin Production

Ferulate 5-hydroxylase (F5H), a cytochrome P450-dependent monooxygenase, catalyzes the hydroxylation of coniferaldehyde, a crucial step in the formation of syringyl lignin monomer (S). However, evolutionary divergence, expression patterns under abiotic stress conditions (ABA, PEG and NaOH) and lignin content-related features of the F5H gene family in Sorghum bicolor have not been explored. This study envisaged mining of Sorghum genomic data leading to the identification of 61 SbF5H genes. Bioinformatics analysis revealed the phylogenetic evolutionary relations, gene structures, conserved motifs, physicochemical properties, and promoter cis-acting elements related to these genes and their encoded proteins. Based on the gene structural and phylogenetic features, these 61 SbF5Hs were grouped into 4 subclasses. The in silico expression analysis revealed higher accumulation of SbF5H1 transcripts in embryo and in root under stress conditions. Similarly, Other SbF5H genes have shown expression in stem and root, thus indicating SbF5H genes involvement in Sorghum lignin biosynthesis. By exploring into the functional aspects of the F5H gene, our study sought to shed light on its significance in influencing not only the chemical makeup of lignin but also the resultant plant phenotypes. This insight into the molecular mechanisms governing lignin biosynthesis can have implications for bioenergy production and crop improvement.

A miniaturized feedstocks-to-fuels pipeline for screening the efficiency of deconstruction and microbial conversion of lignocellulosic biomass.

Sustainably grown biomass is a promising alternative to produce fuels and chemicals and reduce the dependency on fossil energy sources. However, the efficient conversion of lignocellulosic biomass into biofuels and bioproducts often requires extensive testing of components and reaction conditions used in the pretreatment, saccharification, and bioconversion steps. This restriction can result in a significant and unwieldy number of combinations of biomass types, solvents, microbial strains, and operational parameters that need to be characterized, turning these efforts into a daunting and time-consuming task. Here we developed a high-throughput feedstocks-to-fuels screening platform to address these challenges. The result is a miniaturized semi-automated platform that leverages the capabilities of a solid handling robot, a liquid handling robot, analytical instruments, and a centralized data repository, adapted to operate as an ionic-liquid-based biomass conversion pipeline. The pipeline was tested by using sorghum as feedstock, the biocompatible ionic liquid cholinium phosphate as pretreatment solvent, a "one-pot" process configuration that does not require ionic liquid removal after pretreatment, and an engineered strain of the yeast Rhodosporidium toruloides that produces the jet-fuel precursor bisabolene as a conversion microbe. By the simultaneous processing of 48 samples, we show that this configuration and reaction conditions result in sugar yields (~70%) and bisabolene titers (~1500 mg/L) that are comparable to the efficiencies observed at larger scales but require only a fraction of the time. We expect that this Feedstocks-to-Fuels pipeline will become an effective tool to screen thousands of bioenergy crop and feedstock samples and assist process optimization efforts and the development of predictive deconstruction approaches.

Mycorrhizal types determined the response of yield of woody bioenergy crops to environmental factors.

Meeting the demand for energy solely through fossil fuels has posed challenges. To mitigate the risk of energy shortage, woody bioenergy crops as a renewable energy feedstock have been the subject of many researchers. Also, mycorrhizas play an important role in crop productivity and inevitably affect the biomass yield of woody bioenergy crops. Based on a global synthesis of biomass yield of woody bioenergy crops, a framework for identifying and comparing bioenergy crop biomass in response to mycorrhizal type was developed. Our results found that the biomass yield of woody bioenergy crops in descending order was ectomycorrhizas (ECM) crops (10.2 ton DM ha-1year-1) > arbuscular mycorrhizas (AM)+ECM crops (8.8 ton DM ha-1year-1) > AM crops (8.0 ton DM ha-1year-1). In addition, our analysis revealed that the climate had the strongest effect on biomass yield in AM and ECM crops, whereas geography exerted the most significant influence on biomass yield in AM+ECM crops. Furthermore, there were differences in the biomass yield response of different mycorrhizal and plant types to geographic (latitude and elevation) and climatic factors (mean annual temperature (MAT) and mean annual precipitation (MAP)). When cultivating AM crops, we can focus more on temperature conditions-warmer locations, whereas for ECM crops, selecting regions with higher precipitation levels is advantageous. This study revealed the relationship between mycorrhizae and bioenergy crops. It provides data and theoretical support to rationalize differences in different woody bioenergy crops and their different responses to global change and increased production of bioenergy crops.

Blue in green: forestation turns blue water green, mitigating heat at the expense of water availability

Abstract In order to meet a stringent carbon budget, shared socioeconomic pathways (SSPs) aligned with the Paris Agreement typically require substantial land-use changes (LUC), such as large-scale forestation and bioenergy crop plantations. What if such a low-emission, intense-LUC scenario actually materialized? This paper quantifies the biophysical effects of LUC under SSP1-2.6 using an ensemble of regional climate simulations over Europe. We find that LUC projected over the 21st century, primarily broadleaf-tree forestation at the expense of grasslands, reduce summertime heat extremes significantly over large swaths of continental Europe. In fact, cooling from LUC trumps warming by greenhouse gas (GHG) emissions, resulting in milder heat extremes by 2100 for about half of the European population. Forestation brings heat relief by shifting the partition of turbulent energy fluxes away from sensible and towards latent heat fluxes. Impacts on the water cycle are then assessed. Forestation enhances precipitation recycling over continental Europe, but not enough to match the boost of evapotranspiration (green water flux). Run-off (blue water flux) is reduced as a consequence. Some regions experience severe drying in response. In other words, forestation turns blue water green, bringing heat relief but compromising water availability in some already-dry regions.

Regulatory Network of the Late-Recruited Primary Decarboxylase C4NADP-ME in Sugarcane.

In agronomically important C4 grasses, efficient CO2 delivery to Rubisco is facilitated by NADP-malic enzyme (C4NADP-ME), which decarboxylates malate in bundle sheath cells. However, understanding the molecular regulation of the C4NADP-ME gene in sugarcane (Saccharum spp.) is hindered by its complex genetic background. Enzymatic activity assays demonstrated that decarboxylation in sugarcane Saccharum spontaneum predominantly relies on the NADP-ME pathway, similar to sorghum (Sorghum bicolor) and maize (Zea mays). Comparative genomics analysis revealed the recruitment of eight core C4 shuttle genes, including C4NADP-ME (SsC4NADP-ME2), in the C4 pathway of sugarcane. Contrasting to sorghum and maize, the expression of SsC4NADP-ME2 in sugarcane is regulated by different transcription factors (TFs). We propose a gene regulatory network for SsC4NADP-ME2, involving candidate TFs identified through gene co-expression analysis and yeast one-hybrid experiment. Among these, ABA INSENSITIVE5 (ABI5) was validated as the predominant regulator of SsC4NADP-ME2 expression, binding to a G-box within its promoter region. Interestingly, the core element ACGT within the regulatory G-box was conserved in sugarcane, sorghum, maize, and rice (Oryza sativa), suggesting an ancient regulatory code utilized in C4 photosynthesis. This study offers insights into SsC4NADP-ME2 regulation, crucial for optimizing sugarcane as a bioenergy crop.

An EIL Family Transcription Factor From Switchgrass Affects Sulphur Assimilation and Root Development in Arabidopsis.

Sulphur limitation 1 (SLIM1), a member of ethylene-insensitive3-like (EIN3/EIL) protein family, is recognised as the pivotal transcription factor regulating sulphur assimilation, essential for maintaining sulphur homoeostasis in Arabidopsis. However, the function of its monocot homologues is largely unknown. In this study, we identified PvEIL3a, a homologous gene of AtSLIM1, from switchgrass (Panicum virgatum L.), a significant perennial bioenergy crop. Our results demonstrated that introducing PvEIL3a into Arabidopsis slim1 mutants significantly increased the expression of genes responsive to sulphur deficiency, and transgenic plants exhibited shortened root length and delayed development. Moreover, PvEIL3a activated the expression of AtAPR1, AtSULTR1;1 and AtBGLU30, which plays an important role in sulphur assimilation and glucosinolate metabolism. Results of transcriptome and metabonomic analysis further indicated a perturbation in the metabolic pathways of tryptophan-dependent indole glucosinolates (IGs), camalexin and auxin. In addition, PvEIL3a conservatively regulated sulphur assimilation and the biosynthesis of tryptophan pathway-derived secondary metabolites, which reduced the biosynthesis of indole-3-acetic acid (IAA) and inhibited the root elongation of transgenic Arabidopsis. In conclusion, this study highlights the functional difference of the ethylene-insensitive 3-like (EIL) family gene in monocot and dicot plants, thereby deepening the understanding of the specific biological roles of EIL3 in monocot plant species.

Understanding the chemical language mediating maize immunity and environmental adaptation.

Diverse networks of specialized metabolites promote plant fitness by mediating beneficial and antagonistic environmental interactions. In maize (Zea mays), constitutive and dynamically formed cocktails of terpenoids, benzoxazinoids, oxylipins, and phenylpropanoids contribute to plant defense and ecological adaptation. Recent research has highlighted the multifunctional nature of many specialized metabolites, serving not only as elaborate chemical defenses that safeguard against biotic and abiotic stress but also as regulators in adaptive developmental processes and microbiome interactions. Great strides have also been made in identifying the modular pathway networks that drive maize chemical diversity. Translating this knowledge into strategies for enhancing stress resilience traits has the potential to address climate-driven yield losses in one of the world's major food, feed, and bioenergy crops.

Land competition and its impact on decarbonized energy systems: A case study for Germany

In densely populated countries, land competition is a key challenge in light of a growing population and the land-intensive decarbonization of energy supply. We apply an energy system model using linear optimization to Germany as an example for a densely populated and industrialized nation with a high energy demand to show how land competition affects the economics of land-intensive renewable energies. Bioenergy crops are currently cultivated on 6.5% of Germany’s land area. We find that allocating only 6% of the total land to the future energy system, which is even less than the current allocation to bioenergy crops, allows for a system that is close to the cost-minimum that we calculate when not restricting the land area. This 6% of the land area is divided into 4% for photovoltaics (PV), 2% for onshore wind and 0% for bioenergy crops. This would save 15billion€/a (15.1%) relative to the system that matches current political targets for utility-scale PV. For areas exceeding this 6%, we find that the most cost-efficient utilization comes from bioenergy crops, but they only add value to the energy system if there is plenty of land available. The value of land to the energy system is at least twice as high for 0% remaining emissions when compared to the case of 10% remaining green house gas emissions, although both scenarios are separated by less than five years according to current German law. Both our findings underline that considering the value of land as early as possible is necessary when developing state policies that shall lead to cost-efficient renewable energy systems.

Physiological, Metabolome and Gene Expression Analyses Reveal the Accumulation and Biosynthesis Pathways of Soluble Sugars and Amino Acids in Sweet Sorghum under Osmotic Stresses.

Water scarcity is a major environmental constraint on plant growth in arid regions. Soluble sugars and amino acids are essential osmolytes for plants to cope with osmotic stresses. Sweet sorghum is an important bioenergy crop and forage with strong adaptabilities to adverse environments; however, the accumulation pattern and biosynthesis basis of soluble sugars and amino acids in this species under osmotic stresses remain elusive. Here, we investigated the physiological responses of a sweet sorghum cultivar to PEG-induced osmotic stresses, analyzed differentially accumulated soluble sugars and amino acids after 20% PEG treatment using metabolome profiling, and identified key genes involved in the biosynthesis pathways of soluble sugars and amino acids using transcriptome sequencing. The results showed that the growth and photosynthesis of sweet sorghum seedlings were significantly inhibited by more than 20% PEG. After PEG treatments, the leaf osmotic adjustment ability was strengthened, while the contents of major inorganic osmolytes, including K+ and NO3-, remained stable. After 20% PEG treatment, a total of 119 and 188 differentially accumulated metabolites were identified in the stems and leaves, respectively, and the accumulations of soluble sugars such as raffinose, trehalose, glucose, sucrose, and melibiose, as well as amino acids such as proline, leucine, valine, serine, and arginine were significantly increased, suggesting that these metabolites should play key roles in osmotic adjustment of sweet sorghum. The transcriptome sequencing identified 1711 and 4978 DEGs in the stems, as well as 2061 and 6596 DEGs in the leaves after 20% PEG treatment for 6 and 48 h, respectively, among which the expressions of genes involved in biosynthesis pathways of sucrose (such as SUS1, SUS2, etc.), trehalose (including TPS6), raffinose (such as RAFS2 and GOLS2, etc.), proline (such as P5CS2 and P5CR), leucine and valine (including BCAT2), and arginine (such as ASS and ASL) were significantly upregulated. These genes should be responsible for the large accumulation of soluble sugars and amino acids under osmotic stresses. This study deepens our understanding of the important roles of individual soluble sugars and amino acids in the adaptation of sweet sorghum to water scarcity.

Comparative phenotypic and transcriptomic analysis reveals genotypic differences in nitrogen use efficiency in sorghum

Sorghum (Sorghumbicolor L.), a model for C4 grass and an emerging biofuel crop, is known for its robust tolerance to low input field. However, the focus on enhancing nitrogen use efficiency (NUE) in sorghum under low nitrogen (N) conditions has been limited. This study conducted hydroponic experiments and field trials with two sorghum inbred lines, contrasting in their N efficiency: the N-efficient (398B) and the N-inefficient (CS3541) inbred lines. The aim was to analyze the key factors influencing NUE by integrating phenotypic, physiological, and multi-omics approaches under N deficiency conditions. The field experiments revealed that 398B displayed superior NUE and yield performance compared to CS3541. In hydroponic experiments, the growth of 398B outperformed CS3541 following N deficiency, attributing to its higher photosynthetic and sustaining activity of N metabolism-related enzymes. Genomic and transcriptomic integration highlighted fewer genomic diversities and alterations in global gene expression in 398B, which were likely contributor to its high NUE. Additionally, co-expression network analysis suggested the involvement of key genes which impact N uptake efficiency (NUpE) and N utilization efficiency (NUtE) in both lines, such as an N transporter, Sobic.003G371000.v3.2leaf(NPF5.10) and a transcription factor, Sobic.002G202800.v3.2leaf(WRKY) in bolstering NUE under low-N stress. The findings collectively suggested that 398B achieved higher NUpE and NUtE, effectively coordinating photosynthesis and N metabolism to enhance NUE. The candidate genes regulating N uptake and utilization efficiencies could provide valuable insights for developing sorghum breeds with improved NUE, contributing to sustainable agricultural practices and bioenergy crop development.

Upgraded cellulose and xylan digestions for synergistic enhancements of biomass enzymatic saccharification and bioethanol conversion using engineered Trichoderma reesei strains overproducing mushroom LeGH7 enzyme

Crop straws provide enormous lignocellulose resources transformable for sustainable biofuels and valuable bioproducts. However, lignocellulose recalcitrance basically restricts essential biomass enzymatic saccharification at large scale. In this study, the mushroom-derived cellobiohydrolase (LeGH7) was introduced into Trichoderma reesei (Rut-C30) to generate two desirable strains, namely GH7–5 and GH7–6. Compared to the Rut-C30 strain, both engineered strains exhibited significantly enhanced enzymatic activities, with β-glucosidases, endocellulases, cellobiohydrolases, and xylanase activities increasing by 113 %, 140 %, 241 %, and 196 %, respectively. By performing steam explosion and mild alkali pretreatments with mature straws of five bioenergy crops, diverse lignocellulose substrates were effectively digested by the crude enzymes secreted from the engineered strains, leading to the high-yield hexoses released for bioethanol production. Notably, the LeGH7 enzyme purified from engineered strain enabled to act as multiple cellulases and xylanase at higher activities, interpreting how synergistic enhancement of enzymatic saccharification was achieved for distinct lignocellulose substrates in major bioenergy crops. Therefore, this study has identified a novel enzyme that is active for simultaneous hydrolyses of cellulose and xylan, providing an applicable strategy for high biomass enzymatic saccharification and bioethanol conversion in bioenergy crops.

Chromosome-level scaffolding of haplotype-resolved assemblies using Hi-C data without reference genomes.

Scaffolding is crucial for constructing most chromosome-level genomes. The high-throughput chromatin conformation capture (Hi-C) technology has become the primary scaffolding strategy due to its convenience and cost-effectiveness. As sequencing technologies and assembly algorithms advance, constructing haplotype-resolved genomes is increasingly preferred because haplotypes can provide additional genetic information on allelic and non-allelic variations. ALLHiC is a widely used allele-aware scaffolding tool designed for this purpose. However, its dependence on chromosome-level reference genomes and a higher chromosome misassignment rate still impede the unravelling of haplotype-resolved genomes. Here we present HapHiC, a reference-independent allele-aware scaffolding tool with superior performance on chromosome assignment as well as contig ordering and orientation. In addition, we provide new insights into the challenges in allele-aware scaffolding by conducting comprehensive analyses on various adverse factors. Finally, with the help of HapHiC, we constructed the haplotype-resolved allotriploid genome for Miscanthus × giganteus, an important lignocellulosic bioenergy crop.

Nutrient and moisture limitations reveal keystone metabolites linking rhizosphere metabolomes and microbiomes

Plants release a wealth of metabolites into the rhizosphere that can shape the composition and activity of microbial communities in response to environmental stress. The connection between rhizodeposition and rhizosphere microbiome succession has been suggested, particularly under environmental stress conditions, yet definitive evidence is scarce. In this study, we investigated the relationship between rhizosphere chemistry, microbiome dynamics, and abiotic stress in the bioenergy crop switchgrass grown in a marginal soil under nutrient-limited, moisture-limited, and nitrogen (N)-replete, phosphorus (P)-replete, and NP-replete conditions. We combined 16S rRNA amplicon sequencing and LC-MS/MS-based metabolomics to link rhizosphere microbial communities and metabolites. We identified significant changes in rhizosphere metabolite profiles in response to abiotic stress and linked them to changes in microbial communities using network analysis. N-limitation amplified the abundance of aromatic acids, pentoses, and their derivatives in the rhizosphere, and their enhanced availability was linked to the abundance of bacterial lineages from Acidobacteria, Verrucomicrobia, Planctomycetes, and Alphaproteobacteria. Conversely, N-amended conditions increased the availability of N-rich rhizosphere compounds, which coincided with proliferation of Actinobacteria. Treatments with contrasting N availability differed greatly in the abundance of potential keystone metabolites; serotonin and ectoine were particularly abundant in N-replete soils, while chlorogenic, cinnamic, and glucuronic acids were enriched in N-limited soils. Serotonin, the keystone metabolite we identified with the largest number of links to microbial taxa, significantly affected root architecture and growth of rhizosphere microorganisms, highlighting its potential to shape microbial community and mediate rhizosphere plant-microbe interactions.

Deployment expectations of multi-gigatonne scale carbon removal could have adverse impacts on Asia’s energy-water-land nexus

Existing studies indicate that future global carbon dioxide (CO2) removal (CDR) efforts could largely be concentrated in Asia. However, there is limited understanding of how individual Asian countries and regions will respond to varying and uncertain scales of future CDR concerning their energy-land-water system. We address this gap by modeling various levels of CDR-reliant pathways under climate change ambitions in Asia. We find that high CDR reliance leads to residual fossil fuel and industry emissions of about 8 Gigatonnes CO2yr−1 (GtCO2yr−1) by 2050, compared to less than 1 GtCO2yr−1 under moderate-to-low CDR reliance. Moreover, expectations of multi-gigatonne CDR could delay the achievement of domestic net zero CO2 emissions for several Asian countries and regions, and lead to higher land allocation and fertilizer demand for bioenergy crop cultivation. Here, we show that Asian countries and regions should prioritize emission reduction strategies while capitalizing on the advantages of carbon removal when it is most viable.

Characterization of Wood, Leaves, Barks, and pod wastes from Prosopis africana biomass for biofuel production

One of the approaches for increasing the contribution of biomass to the renewable energy mix is the valorization of biomass to bioenergy. Evaluating the potential of unconventional biomass sources could significantly accelerate the assessment for suitability as feedstock for bioenergy production as a sustainable solution. The study aimed to characterize the Prosopis africana biomass of wood, barks, leaves, and pods towards providing valuable data for scaling up and incorporating these materials into the bioenergy crop database. Characterizations of wood, leaves, barks, and pod wastes from Prosopis africana biomass were investigated based on the proximate, ultimate, and compositional analysis of pulverized samples of the PA biomass to determine their physical, thermal, and chemical properties towards assessing their potential for valorization to bioenergy. The lignocellulosic materials were characterized by scanning electron microscopy, energy dispersive X-ray, Fourier transform infrared spectroscopy, thermogravimetric analysis, and X-ray diffraction. The results show that the pulverized sample wastes have porous structures with varying degrees of crystallinity (wood: 89.20 %, bark: 23.90 %, leaves: 32.48 %, pods: 23.08 %), suggesting different susceptibilities to conversion processes. Notably, the wood sample had the lowest moisture content (3.13 %), and the pod sample had the highest volatile matter content (75.83 %), indicating a high potential for biofuel production. The higher heating values (HHV) and lower heating values (LHV) of the samples ranged from 15.23 to 20.49 MJ/kg and 13.83 to 18.79 MJ/kg, respectively. These calorific values are competitive with established lignocellulosic bioenergy feedstocks, positioning PA biomass as promising candidates for solid biofuel applications.

Machine learning applications in forest and biomass supply chain management: a review

ABSTRACT Forest and biomass crops for bioenergy and bioproducts can promote a sustainable bioeconomy while effectively reducing greenhouse gas (GHG) emissions to mitigate global warming. One of the most concerning issues is selecting and using appropriate modeling and analytical technologies to optimize the benefits of multi-feedstock biomass supply chains, including logistics. Machine learning (ML) has been used to solve increasingly complex supply chain problems, providing powerful tools for sustainable forest management and biomass resource development. Existing research is extensive and spans many different ML techniques, but synthesis is needed to help guide the adoption of these rapidly evolving tools. This review summarizes ML applications in forest and biomass supply chain management in terms of data, algorithms, and process examples, with an emphasis on direct application to supply chain management. ML is a viable technique to support strategic, operational, and tactical planning and decision-making in this field and can enhance the environmental and economic performance of diverse forest and biomass supply chains.

Exploring the Evolutionary History and Phylogenetic Relationships of Giant Reed (Arundo donax) through Comprehensive Analysis of Its Chloroplast Genome.

Giant reed (Arundo donax) is widely distributed across the globe and is considered an important energy crop. This study presents the first comprehensive analysis of the chloroplast genome of giant reed, revealing detailed characteristics of this species' chloroplast genome. The chloroplast genome has a total length of 137,153 bp, containing 84 protein-coding genes, 38 tRNA genes, and 8 rRNA genes, with a GC content of 39%. Functional analysis indicates that a total of 45 photosynthesis-related genes and 78 self-replication-related genes were identified, which may be closely associated with its adaptability and growth characteristics. Phylogenetic analysis confirmed that Arundo donax cv. Lvzhou No.1 belongs to the Arundionideae clade and occupies a distinct evolutionary position compared to other Arundo species. The findings of this study not only enhance our understanding of the giant reed genome but also provide valuable genetic resources for its application in biotechnology, bioenergy crop development, and ecological restoration.

Soil Microbial Community Structures under Annual and Perennial Crops Treated with Different Nitrogen Fertilization Rates

Perennial bioenergy crops may enhance microbial community structures due to their extensive root system compared to annual crops. However, the long-term effect of perennial bioenergy crops receiving different N fertilization rates on microbial community structures is not well defined. We evaluated the 11-year effect of perennial bioenergy crops with various N fertilization rates as well as an annual crop with the recommended N rate on soil microbial properties in 2019 and 2020 in the US northern Great Plains. Perennial grasses were intermediate wheatgrass, IWG (Thinopyrum intermedium [Host] Barkworth and Dewey), and switchgrass, SG (Panicum virgatum L.), with N fertilization rates of 0, 28, 56, and 84 kg N ha−1, and the annual crop was spring wheat, WH (Triticum aestivum, L.) with 80 kg N ha−1. The total fungal phospholipid fatty acid (PLFA) proportion and fungal/bacterial ratio were significantly lower under annual spring wheat than perennial grass (SG). Increased N fertilization rate linearly increased Gram-positive bacterial PLFA proportions and the Gram-positive/Gram-negative bacterial ratio for IWG in 2020 but decreased the PLFA proportions of arbuscular mycorrhizal fungi (AMF) for both perennial bioenergy crops in all years. The proportions of AMF neutral lipid fatty acid and Gram-negative bacterial PLFA were greater for SG (0.432 and 0.271, respectively) than IWG (0.339 and 0.258, respectively), but actinomycetes and the Gram-positive/Gram-negative bacterial ratio were greater for IWG (0.160 and 1.532, respectively) compared to SG (0.152 and 1.437, respectively). Microbial community structures varied with perennial bioenergy crops, N fertilization rates, and perennial vs. annual crops. This study showed how perennial crops favored fungal growth and how annual crops enhanced bacterial growth impacting soil biological health.