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At least 343 records · Page 19

Approximately 15% of Miscanthus yield is lost at current commercial cutting heights in Iowa

Various works have quantitatively characterized the effects of environmental and management factors on Miscanthus x giganteus Greef et Deu (mxg) yield and, therefore, anticipated land requirement per unit production. However, little work has addressed the effects of cutting height, which may significantly contribute to the difference between the standing aboveground biomass at harvest (i.e., biological yield) and harvested yield. This study quantitatively characterized the effect of cutting height using a replicated nitrogen trial of a 5-year-old mxg stand in southeast Iowa and related this information to observations of cutting height in nearby commercial fields. Nitrogen fertilizer did not significantly change the relationship of the stem segment mass to length, and overall, a 1-cm stem segment contributes 0.5% of the total stem biomass within the bottom 44 cm of the stem. This results in an average harvest loss of 15% of the aboveground standing biomass when cutting at 30 cm, typically seen in commercial mxg fields in eastern Iowa. Cutting height should be considered when accurately predicting commercial mxg harvest yields and changes in soil organic carbon in a commercial mxg agroecosystem.

60 APPLIED LIFE SCIENCES↗

Reductive catalytic fractionation of agricultural residue and energy crop lignin and application of lignin oil as antimicrobials

Cheap and abundant waste from bioethanol and agricultural processing industries are an alluring alternative feedstock for biorefineries. In this work, we employ reductive catalytic fractionation (RCF) to depolymerize, over Ru/C powder and Ru/Al 2 O 3 pellets, five herbaceous biomass feedstocks, namely corn stover, miscanthus, switchgrass, sugarcane bagasse, and wheat straw into phenolic monomers with high yields (~40 wt.% based on total (Klason + acid soluble) lignin and > 50 wt.% when stabilized using aldehydes), leaving behind a carbohydrate pulp residue. Interestingly, a polar solvent is sufficient to solubilize and fragment the lignin polymer into monomers without any catalyst. Here, contrary to woody biomass, where the monomer yields are positively correlated with the S-content of lignin, principal component analysis indicates that the monomer yields from herbaceous biomass depend on the content of lignin crosslinker – ferulate. Using NMR, we further identify α – 6 C-C linked oligomers formed from condensation reactions, explaining the unexpected low monomer yields of high β-O-4 herbaceous biomass. Recyclability experiments indicate that catalyst deactivation occurs through sintering, leaching, and fouling. Lignin oil from herbaceous biomass exhibits bacteriostatic effects against Staphylococcus aureus, highlighting a potential application in functional food development and as food or feed preservative.

09 BIOMASS FUELS↗

Photoperiod shift effects on yield characteristics of rice

Edible yield must be maximized for each crop species selected for inclusion in the Controlled Ecological Life-Support System (CELSS) proposed by NASA to support long-term manned space missions. In a greenhouse study aimed at increasing biomass partitioning to rice (Oryza sativa L.) grain, plants of the high yielding semi-dwarf rice cultivar Ai-Nan-Tsao were started in pots under 8-h photoperiods at a density of 212 plants m-2. After different periods of time under 8-h photoperiods, pots were switched to continuous light for the remainder of the cropping cycle. Continuous light did not delay time to first panicle emergence (60 d) or time to harvest (83 d). There was a positive correlation between the length of continuous light treatments and nongrain biomass. Grain yield (1.6 +/- 0.2 g plant-1) did not increase in continuous light. Yield-efficiency rate (grain weight per length of cropping cycle, canopy volume, and weight of nongrain shoot biomass) was used to compare treatments. Small Ai-Nan-Tsao rice canopies grown under 8-h photoperiods were more efficient producers of grain than canopies grown under continuous light for a portion of the rice cropping cycle.

Non-NASA Center↗

Plant productivity in controlled environments

To assess the cost and area/volume requirements of a farm in a space station or Lunar or Martian base, a few laboratories in the United States, the Soviet Union, France, and Japan are studying optimum controlled environments for the production of selected crops. Temperature, light, photoperiod, CO2, humidity, the root-zone environment, and cultivars are the primary factors being manipulated to increase yields and harvest index. Our best wheat yields on a time basis (24 g m-2 day-1 of edible biomass) are five times good field yields and twice the world record. Similar yields have been obtained in other laboratories with potatoes and lettuce; soybeans are also promising. These figures suggest that approximately 30 m2 under continuous production could support an astronaut with sufficient protein and about 2800 kcal day-1. Scientists under Iosif Gitelzon in Krasnoyarsk, Siberia, have lived in a closed system for up to 5 months, producing 80% of their own food. Thirty square meters for crops were allotted to each of the two men taking part in the experiment. A functional controlled-environment life-support system (CELSS) will require the refined application of several disciplines: controlled-environment agriculture, food preparation, waste disposal, and control-systems technology, to list only the broadest categories. It has seemed intuitively evident that ways could be found to prepare food, regenerate plant nutrients from wastes, and even control and integrate several subsystems of a CELSS. But could sufficient food be produced in the limited areas and with the limited energy that might be available? Clearly, detailed studies of food production were necessary.

NASA Discipline Life Support Systems↗

Roles of mineral matter in biomass processing to biofuels

Abstract Minerals in biomass have a significant impact on both biofuel quality and yield. This is especially true for current thermochemical biomass conversion processes. However, the roles of plant minerals in biochemical conversion have not been studied extensively, even though they are generally considered to lower the sugar yield because they reduce the feedstock proportion of carbohydrates. A successful strategic solution is thus necessary to overcome the challenges caused by the minerals in biomass, which include (1) decreased quality of biomass feedstocks; (2) reduction of process efficiency; and (3) reduction of the product quality and quantity from biomass conversion. This review summarizes the roles of plant minerals in a biorefinery, focusing on these key challenges. The discussion covers many issues related to plant minerals in biofuel production, including their sources, functions, and distribution in plant biomass, methods of characterizing them, their influence in a biorefinery, and the strategic handling required to manage their occurrence in biomass, based on reported studies. It could inspire better strategies to deal with the variance of mineral content in biomass feedstocks to increase process efficiency and reduce costs while supporting the concept of a circular bioeconomy. © 2023 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗

Itaconic acid production is regulated by LaeA in Aspergillus pseudoterreus

The global regulator LaeA controls secondary metabolism in diverse Aspergillus species. Here we explored its role in regulation of itaconic acid production in Aspergillus pseudoterreus. To understand its role in regulating metabolism, we deleted and overexpressed laeA, and assessed the transcriptome, proteome, and secreted metabolome prior to and during initiation of phosphate limitation induced itaconic acid production. We found that secondary metabolite clusters, including the itaconic acid biosynthetic gene cluster, are regulated by laeA and that laeA is required for high yield production of itaconic acid. Overexpression of laeA improves itaconic acid yield at the expense of biomass by increasing the expression of key biosynthetic pathway enzymes and attenuating the expression of genes involved in phosphate acquisition and scavenging. Increased yield was observed in optimized conditions as well as conditions containing excess nutrients that may be present in inexpensive sugar containing feedstocks such as excess phosphate or complex nutrient sources. This suggests that global regulators of metabolism may be useful targets for engineering metabolic flux that is robust to environmental heterogeneity.

59 BASIC BIOLOGICAL SCIENCES↗

Easier Access to Functional Furans

Traditional furan alkylation utilizes catalyst materials are unsafe, produce hazardous waste, and yield low reaction products. Researchers at Los Alamos National Laboratory have developed a new method to enable industries to produce valuable chemicals from biomass more safely with higher yields and less waste. This method has been successfully demonstrated on the benchtop, and is ready for testing to scale up for industrial synthesis applications. Los Alamos is seeking a licensee to scale this technology in-house, or a Cooperative Research and Development Agreement (CRADA) partner to scale the method within the Laboratory for a specific purpose.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Feedstock/pretreatment screening for bioconversion of sugar and lignin streams via deacetylated disc-refining

Recent publications have shown the benefits of deacetylation disc-refining (DDR) as a pretreatment process to deconstruct biomass into sugars and lignin residues. Major advantages of DDR pretreatment over steam and dilute acid pretreatment are the removal of acetyl and lignin during deacetylation. DDR does not generate hydroxymethylfurfural (HMF) and furfural which are commonly produced from steam and dilute acid pretreatments. Acetate, lignin, HMF, and furfural are known inhibitors during enzymatic hydrolysis and fermentation. Another advantage of deacetylation is the production of lignin-rich black liquor, which can be upgraded to other bioproducts. Furthermore, due to the lack of sugar degradation during deacetylation, DDR has significantly less sugar loss than other pretreatment methods. Previous studies for DDR have primarily focused on corn stover, but lacked the investigative studies of other feedstocks. This study was designed to screen various DDR process conditions at pilot scale using three different feedstocks, including corn stover, poplar, and switchgrass. The impact of the pretreatment conditions was evaluated by testing hydrolysates for bioconversion to 2,3-butanediol. Pretreatment of biomass by DDR showed high-conversion-yields and 2,3-BDO fermentation production yields. Techno-economic analysis (TEA) of the pretreatment for biomass to sugar was also developed based on NREL’s Aspen Model. This study shows that the cellulose and hemicellulose in poplar was more recalcitrant than herbaceous feedstocks which ultimately drove up the sugar cost. Switchgrass was also more recalcitrant than corn stover but less than poplar.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying yield-optimizing environments for two cowpea breeding lines by manipulating photoperiod and harvest scenario

Photoperiod and harvest scenario of cowpea (Vigna unguiculata L. Walp) canopies were manipulated to optimize productivity for use in future controlled ecological life-support systems. Productivity was measured by edible yield rate (EYR:g m-2 day-1), shoot harvest index (SHI: g edible biomass [g total shoot dry weight]), and yield-efficiency rate (YER:g edible biomass m-2 day-1 per[g nonedible shoot dry weight]). Breeding lines 'IT84S-2246' (S-2246) and "IT82D-889' (D-889) were grown in a greenhouse under 8-, 12-, or 24-h photoperiods. S-2246 was short-day and D-889 was day-neutral for flowering. Under each photoperiod, cowpeas were harvested either for leaves only, seeds only, or leaves plus seeds (mixed harvest). Photoperiod did not affect EYR of either breeding line for any harvest scenario tested. Averaged over both breeding lines, seed harvest gave the highest EYR at 6.7 g m-2 day-1. The highest SHI (65%) and YER (94 mg m-2 day-1 g-1) were achieved for leaf-only harvest of D-889 under an 8-h photoperiod. For leaf-only harvest of S-2246, both SHI and YER increased with increasing photoperiod, but declined for seed-only and mixed harvests. However, photoperiod had no effect on SHI or YER for D-889 for any harvest scenario. A second experiment utilized the short-day cowpea breeding line 'IT89KD-288' (D-288) and the day-neutral breeding line 'IT87D-941-1' (D-941) to compare yield parameters using photoperiod extension under differing lamp types. This experiment confirmed the photoperiod responses of D-889 and S-2246 to a mixed-harvest scenario and indicated that daylength extension with higher irradiance from high pressure sodium lamps further suppressed EYR, SHI, and YER of the short-day breeding line D-288.

Non-NASA Center↗

Engineering biology approaches for food and nutrient production by cyanobacteria

Here, as photoautotrophic organisms, cyanobacteria capture and store solar energy in the form of biomass. Cyanobacterial biomass has been an important component of diet and nutrition in several regions for centuries. Synthetic biology strategies are currently being applied to increase the yield and productivity of cyanobacterial biomass by optimizing solar energy utilization and CO 2 fixation rates for carbon storage. Likewise, engineering cyanobacteria as cellular factories to synthesize carbohydrates, amino acids, proteins, lipids and fatty acids is providing an attractive way to sustainably produce food and nutrients for human consumption. In this review, we have summarized recent progress in both aspects and prospective trends under development.

59 BASIC BIOLOGICAL SCIENCES↗

How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?

This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration [CO2] on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al. 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50 percent of models within a range of plus/minus 1 Mg ha(exp. -1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(exp. -1). However under water deficit in one of the two years, the models captured only 30 percent of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

grain number↗

Air Classification of Forestry Residues for Fast Pyrolysis

Understanding critical biomass attributes through efficient fractionation is crucial for advancing sustainable pyrolysis for renewable energy and chemical production. This study investigates the intricate relationship between biomass preprocessing and pyrolysis product yields, employing the air classification technique for the treatment of loblolly pine residues with varying moisture content. A comprehensive exploration of the physicochemical properties of air-classified loblolly pine informs a sophisticated pyrolysis simulation model. Given the complex and multifaceted nature of biomass pyrolysis, operating across diverse temporal and spatial scales, a pyrolysis kinetics-based CFD–DEM simulation method is employed to predict product yields. Results showed that the elevated moisture content amplifies particle adhesiveness, necessitating augmented air velocities for effective separation, thereby influencing the efficiency of the separation process. While carbon and hydrogen contents exhibit relative stability across diverse moisture contents and blower frequencies, the oxygen content undergoes noticeable changes. For example, the oxygen contents were measured as 29.2 and 38.6 wt% in the light fraction of 30% moisture content sample at blower frequencies of 10 and 20 Hz, respectively. An intriguing finding emerges from pyrolysis simulation, indicating that a lower blower frequency in air classification moderately enhances bio-oil yield and significantly improves its quality, particularly in terms of water content. For instance, the water content in the bio-oil was about 1.5% and 10% in the heavy and light fractions, respectively from 10% moisture sample under 15 Hz blower frequency.

09 - BIOMASS FUELS↗

Wavelet Analysis of GPR Data for Belowground Mass Assessment of Sorghum Hybrid for Soil Carbon Sequestration

Among many agricultural practices proposed to cut carbon emissions in the next 30 years is the deposition of carbon in soils as plant matter. Adding rooting traits as part of a sequestration strategy would result in significantly increased carbon sequestration. Integrating these traits into production agriculture requires a belowground phenotyping method compatible with high-throughput breeding (i.e., rapid, inexpensive, reliable, and non-destructive). However, methods that fulfill these criteria currently do not exist. We hypothesized that ground-penetrating radar (GPR) could fill this need as a phenotypic selection tool. In this study, we employed a prototype GPR antenna array to scan and discriminate the root and rhizome mass of the perennial sorghum hybrid PSH09TX15. B-scan level time/discrete frequency analyses using continuous wavelet transform were utilized to extract features of interest that could be correlated to the biomass of the subsurface roots and rhizome. Time frequency analysis yielded strong correlations between radar features and belowground biomass (max R −0.91 for roots and −0.78 rhizomes, respectively) These results demonstrate that continued refinement of GPR data analysis workflows should yield an applicable phenotyping tool for breeding efforts in contexts where selection is otherwise impractical.

Wolfe, Matthew↗

Machine Learning Reduced Order Model for Cost and Emission Assessment of a Pyrolysis System

Biomass pyrolysis is a promising approach for producing economic and environmentally-friendly fuels and bioproducts. Biomass pyrolysis experiments show that feedstock properties have a significant impact on product yields and composition. Scientists are developing detailed chemical reaction mechanisms to capture the relationships between biomass composition and pyrolysis yields. These mechanisms can be computationally intensive. In this study, we investigate the use of a machine learning reduced order model (ROM) for assessing the costs and emissions of a pyrolysis biorefinery. Here, we developed a Kriging-based ROM to predict pyrolysis yields of 314 feedstock samples based on the results of a detailed chemical kinetic pyrolysis mechanism. The ROM is integrated into a chemical process model for calculating mass and energy yields in a commercial-scale (2000 tonne/day) biorefinery. The ROM estimated biofuel yields of 65 to 130 gallons per ton of dry biomass. This results in biofuel minimum fuel-selling prices of $2.62 to $5.43 per gallon and emissions of -13.62 to 145 kg of CO 2 per MJ. The ROM achieved an average mean square error of 1.8e-20 and a mean absolute error of 0.53%. These results suggest that ROMs can facilitate rapid feedstock screening for biorefinery systems.

09 BIOMASS FUELS↗

A novel transfer learning framework for sorghum biomass prediction using UAV-based remote sensing data and genetic markers

Yield for biofuel crops is measured in terms of biomass, so measurements throughout the growing season are crucial in breeding programs, yet traditionally time- and labor-consuming since they involve destructive sampling. Modern remote sensing platforms, such as unmanned aerial vehicles (UAVs), can carry multiple sensors and collect numerous phenotypic traits with efficient, non-invasive field surveys. However, modeling the complex relationships between the observed phenotypic traits and biomass remains a challenging task, as the ground reference data are very limited for each genotype in the breeding experiment. In this study, a Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN) model is proposed for sorghum biomass prediction. The architecture is designed to exploit the time series remote sensing and weather data, as well as static genotypic information. As a large number of features have been derived from the remote sensing data, feature importance analysis is conducted to identify and remove redundant features. A strategy to extract representative information from high-dimensional genetic markers is proposed. To enhance generalization and minimize the need for ground reference data, transfer learning strategies are proposed for selecting the most informative training samples from the target domain. Consequently, a pre-trained model can be refined with limited training samples. Field experiments were conducted over a sorghum breeding trial planted in multiple years with more than 600 testcross hybrids. The results show that the proposed LSTM-based RNN model can achieve high accuracies for single year prediction. Further, with the proposed transfer learning strategies, a pre-trained model can be refined with limited training samples from the target domain and predict biomass with an accuracy comparable to that from a trained-from-scratch model for both multiple experiments within a given year and across multiple years.

36 MATERIALS SCIENCE↗

Detailed biomass fast pyrolysis kinetics integrated to computational fluid dynamic (CFD) and discrete element modeling framework: Predicting product yields at the bench-scale

Fast pyrolysis is an intricate process due to the variability and anisotropy of lignocellulosic biomass and the complicated chemistry and physics during conversion in a bubbling fluidized bed reactor (BFBR). The complexity of biomass fast pyrolysis lends itself well to computational fluid dynamics (CFD) and discrete element (DEM) analysis, which promises to reduce experimental time and its associated cost. This work investigated switchgrass fast pyrolysis simulated by computational fluid dynamics coupled with a discrete element method to track individual reacting biomass particles throughout a bench-scale BFBR reactor. We accounted for the fast pyrolysis chemistry through a comprehensive reaction scheme with secondary cracking reactions. We performed a three-step reduction for secondary cracking reactions to convert the full cracking scheme into a reduced scheme easily incorporated into our model. We assessed the impact of operational conditions on the steady-state yields of liquid bio-oil, non-condensable gases (NCG), at 550 °C over a range of fluidization numbers (2 – 6 Umf), reported as a ratio to the minimum fluidization velocity (Umf). At steady-state, the volatile bio-oil yield had a range of 49.3–50.4 wt%. Levoglucosan was the primary volatile component present with 21 wt% of the bio-oil while water was the second largest with 20 wt%. The reduction of the secondary reaction schemes did not appreciably affect the overall yields of switchgrass pyrolysis compared to the full secondary scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engineered Pseudomonas putida KT2440 co-utilizes galactose and glucose

Abstract Background Efficient conversion of plant biomass to commodity chemicals is an important challenge that needs to be solved to enable a sustainable bioeconomy. Deconstruction of biomass to sugars and lignin yields a wide variety of low molecular weight carbon substrates that need to be funneled to product. Pseudomonas putida KT2440 has emerged as a potential platform for bioconversion of lignin and the other components of plant biomass. However, P. putida is unable to natively utilize several of the common sugars in hydrolysate streams, including galactose. Results In this work, we integrated a De Ley–Doudoroff catabolic pathway for galactose catabolism into the chromosome of P. putida KT2440, using genes from several different organisms. We found that the galactonate catabolic pathway alone (DgoKAD) supported slow growth of P. putida on galactose. Further integration of genes to convert galactose to galactonate and to optimize the transporter expression level resulted in a growth rate of 0.371 h −1 . Additionally, the best-performing strain was demonstrated to co-utilize galactose with glucose. Conclusions We have engineered P. putida to catabolize galactose, which will allow future engineered strains to convert more plant biomass carbon to products of interest. Further, by demonstrating co-utilization of glucose and galactose, continuous bioconversion processes for mixed sugar streams are now possible.

09 BIOMASS FUELS↗

Data for A Chemical-Free Pretreatment for Biosynthesis of Bioethanol and Lipids from Lignocellulosic Biomass: An Industrially Relevant 2G Biorefinery Approach

A wide range of inorganic and organic chemicals are used during the pretreatment and enzymatic hydrolysis of lignocellulosic biomass to produce biofuels. Developing an industrially relevant 2G biorefinery process using such chemicals is challenging and requires more unit operations for downstream processing. A sustainable process has been developed to achieve industrially relevant titers of bioethanol with significant ethanol yield. The pretreatment of sorghum biomass was performed by a continuous pilot-scale hydrothermal reactor followed by disk milling. Enzymatic hydrolysis was performed without washing the pretreated biomass. Moreover, citrate buffer strength was reduced to 100-fold (50 mM to 0.5 mM) during the enzymatic hydrolysis. Enzymatic hydrolysis at 0.5 mM citrate buffer strength showed that significant sugar concentrations of 222 ± 2.3 to 241 ± 2.3 g/L (glucose + xylose) were attained at higher solids loadings of 50 to 60% (w/v). Furthermore, hydrolysates were fermented to produce bioethanol using two different xylose-fermenting Saccharomyces cerevisiae strains and a co-culture of xylose-fermenting and non-GMO yeast cultures. Bioethanol titer of 81.7 g/L was achieved with an ethanol yield of 0.48 gp/gs. Additionally, lipids were produced using the oleaginous yeast Rhodosporidium toruloides , yielding 13.2 g/L lipids with cellular lipid accumulation of 38.5% w/w from 100 g/L of sugar concentration. In summary, reducing the strength of the citrate buffer during enzymatic hydrolysis and omitting inorganic chemicals from the pretreatment process enhances the fermentability of hydrolysates and can also reduce operating costs.

Conversion↗