Search NASA⌕ Search

SEARCH · Search NASA

Results for “pine”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49

Rare Taxa Maintain Microbial Diversity and Contribute to Terrestrial Community Dynamics throughout Bark Beetle Infestation

A global phenomenon of increasing bark beetle-induced tree mortality has heightened concerns regarding ecosystem response and biogeochemical implications. Here, we explore microbial dynamics under lodgepole pines through the analysis of bulk (16S rRNA gene) and potentially active (16S rRNA) communities to understand the terrestrial ecosystem responses that are associated with this form of large-scale tree mortality. Here, we found that the relative abundances of bulk and potentially active taxa were correlated across taxonomic levels, but at lower levels, cladal differences became more apparent. Despite this correlation, there was a strong differentiation of community composition between bulk and potentially active taxa, with further clustering associated with the stages of tree mortality. Surprisingly, community clustering as a function of tree phase had limited correlation to soil water content and total nitrogen concentrations, which were the only two measured edaphic parameters to differ in association with tree phase. Bacterial clustering is more readily explained by the observed decrease in the abundance of active, rare microorganisms after tree death in conjunction with stable alpha diversity measurements. This enables the rare fraction of the terrestrial microbial community to maintain metabolic diversity by transitioning between metabolically active and dormant states during this ecosystem disturbance and contributes disproportionately to community dynamics and archived metabolic capabilities. Here, these results suggest that analyzing bulk and potentially active communities after beetle infestation may be a more sensitive indicator of disruption than measuring local edaphic parameters. Forests around the world are experiencing unprecedented mortality due to insect infestations that are fueled in part by a changing climate. While aboveground processes have been explored, changes at the terrestrial interface that are relevant to microbial biogeochemical cycling remain largely unknown. Here in this study, we investigated the changing bulk and potentially active microbial communities beneath healthy and beetle-killed trees. We found that, even though few edaphic parameters were altered from beetle infestation, the rare microbes were more likely to be active and fluctuate between dormancy and metabolic activity. Finally, this indicates that rare as opposed to abundant taxa contribute disproportionately to microbial community dynamics and presumably biogeochemical cycling within these types of perturbed ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Ecosystem Resilience and Limitations Revealed by Soil Bacterial Community Dynamics in a Bark Beetle-Impacted Forest

ABSTRACT Forested ecosystems throughout the world are experiencing increases in the incidence and magnitude of insect-induced tree mortality with large ecologic ramifications. Interestingly, correlations between water quality and the extent of tree mortality in Colorado montane ecosystems suggest compensatory effects from adjacent live vegetation that mute responses in less severely impacted forests. To this end, we investigated whether the composition of the soil bacterial community and associated functionality beneath beetle-killed lodgepole pine was influenced by the extent of surrounding tree mortality. The most pronounced changes were observed in the potentially active bacterial community, where alpha diversity increased in concert with surrounding tree mortality until mortality exceeded a tipping point of ~30 to 40%, after which diversity stabilized and decreased. Community structure also clustered in association with the extent of surrounding tree mortality with compositional trends best explained by differences in NH 4 + concentrations and C/N ratios. C/N ratios, which were lower in soils under beetle-killed trees, further correlated with the relative abundance of putative nitrifiers and exoenzyme activity. Collectively, the response of soil microorganisms that drive heterotrophic respiration and decay supports observations of broader macroscale threshold effects on water quality in heavily infested forests and could be utilized as a predictive mechanism during analogous ecosystem disruptions. IMPORTANCE Forests around the world are succumbing to insect infestation with repercussions for local soil biogeochemistry and downstream water quality and quantity. This study utilized microbial community dynamics to address why we are observing watershed scale biogeochemical impacts from forest mortality in some impacted areas but not others. Through a unique “tree-centric” approach, we were able to delineate plots with various tree mortality levels within the same watershed to see if surviving surrounding vegetation altered microbial and biogeochemical responses. Our results suggest that forests with lower overall tree mortality levels are able to maintain “normal” ecosystem function, as the bacterial community appears resistant to tree death. However, surrounding tree mortality influences this mitigating effect with various linear and threshold responses whereupon the bacterial community and its function are altered. Our study lends insight into how microscale responses propagate upward into larger-scale observations, which may be useful for future predictions during analogous disruptions.

16S DNA↗

Microbial Drivers of Plant Performance during Drought Depend upon Community Composition and the Greater Soil Environment

The increasing occurrence of drought is a global challenge that threatens food security through direct impacts to both plants and their interacting soil microorganisms. Plant growth promoting microbes are increasingly being harnessed to improve plant performance under stress. However, the magnitude of microbiome impacts on both structural and physiological plant traits under water limited and water replete conditions are not well-characterized. Using two microbiomes sourced from a ponderosa pine forest and an agricultural field, we performed a greenhouse experiment that used a crossed design to test the individual and combined effects of the water availability and the soil microbiome composition on plant performance. Specifically, we studied the structural and leaf functional traits of maize that are relevant to drought tolerance. We further examined how microbial relationships with plant phenotypes varied under different combinations of microbial composition and water availability. We found that water availability and microbial composition affected plant structural traits. Surprisingly, they did not alter leaf function. Maize grown in the forest-soil microbiome produced larger plants under well-watered and water-limited conditions, compared to an agricultural soil community. Although leaf functional traits were not significantly different between the watering and microbiome treatments, the bacterial composition and abundance explained significant variability in both plant structure and leaf function within individual treatments, especially water-limited plants. Our results suggest that bacteria-plant interactions that promote plant performance under stress depend upon the greater community composition and the abiotic environment.

59 BASIC BIOLOGICAL SCIENCES↗

Inelastic Neutrino Scattering on Hot Nuclei of Supernova Matter within the Theory of Finite Fermi Systems

The Nozières–Pines method for describing neutron scattering on a heated Fermi liquid (liquid {sup 3}He) is used to calculate cross sections for inelastic neutrino scattering on the isotope {sup 54}Fe, which is an element that plays a key role in the cooling of supernovae. The calculation in question is performed on the basis of the the theory of finite Fermi systems with the aid of the DF3-a Fayans energy density functional.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhanced degradation of softwood versus hardwood by the white-rot fungus Pycnoporus coccineus

White-rot basidiomycete fungi are potent degraders of plant biomass, with the ability to mineralize all lignocellulose components. Recent comparative genomics studies showed that these fungi use a wide diversity of enzymes for wood degradation. Deeper functional analyses are however necessary to understand the enzymatic mechanisms leading to lignocellulose breakdown. The Polyporale fungus Pycnoporus coccineus BRFM310 grows well on both coniferous and deciduous wood. In the present study, we analyzed the early response of the fungus to softwood (pine) and hardwood (aspen) feedstocks and tested the effect of the secreted enzymes on lignocellulose deconstruction.

Biotechnology & Applied Microbiology↗

Comparison of methodologies used to determine aromatic lignin unit ratios in lignocellulosic biomass

Abstract Background Multiple analytical methods have been developed to determine the ratios of aromatic lignin units, particularly the syringyl/guaiacyl (S/G) ratio, of lignin biopolymers in plant cell walls. Chemical degradation methods such as thioacidolysis produce aromatic lignin units that are released from certain linkages and may induce chemical changes rendering it difficult to distinguish and determine the source of specific aromatic lignin units released, as is the case with nitrobenzene oxidation methodology. NMR methods provide powerful tools used to analyze cell walls for lignin composition and linkage information. Pyrolysis-mass spectrometry methods are also widely used, particularly as high-throughput methodologies. However, the different techniques used to analyze aromatic lignin unit ratios frequently yield different results within and across particular studies, making it difficult to interpret and compare results. This also makes it difficult to obtain meaningful insights relating these measurements to other characteristics of plant cell walls that may impact biomass sustainability and conversion metrics for the production of bio-derived fuels and chemicals. Results The authors compared the S/G lignin unit ratios obtained from thioacidolysis, pyrolysis-molecular beam mass spectrometry (py-MBMS), HSQC liquid-state NMR and solid-state (ss) NMR methodologies of pine, several genotypes of poplar, and corn stover biomass. An underutilized approach to deconvolute ssNMR spectra was implemented to derive S/G ratios. The S/G ratios obtained for the samples did not agree across the different methods, but trends were similar with the most agreement among the py-MBMS, HSQC NMR and deconvoluted ssNMR methods. The relationship between S/G, thioacidolysis yields, and linkage analysis determined by HSQC is also addressed. Conclusions This work demonstrates that different methods using chemical, thermal, and non-destructive NMR techniques to determine native lignin S/G ratios in plant cell walls may yield different results depending on species and linkage abundances. Spectral deconvolution can be applied to many hardwoods with lignin dominated by S and G units, but the results may not be reliable for some woody and grassy species of more diverse lignin composition. HSQC may be a better method for analyzing lignin in those species given the wealth of information provided on additional aromatic moieties and bond linkages. Additionally, trends or correlations in lignin characteristics such as S/G ratios and lignin linkages within the same species such as poplar may not necessarily exhibit the same trends or correlations made across different biomass types. Careful consideration is required when choosing a method to measure S/G ratios and the benefits and shortcomings of each method discussed here are summarized.

09 BIOMASS FUELS↗

Draft genome sequence of the cellulolytic endophyte Chitinophaga costaii A37T2T

Abstract Here we report the draft genome sequence of Chitinophaga costai A37T2 T (=CIP 110584 T , =LMG 27458 T ), which was isolated from the endophytic community of Pinus pinaster tree. The total genome size of C. costaii A37T2 T is 5.07 Mbp, containing 4204 coding sequences. Strain A37T2 T encoded multiple genes likely involved in cellulolytic, chitinolytic and lipolytic activities. This genome showed 1145 unique genes assigned into 109 Cluster of Orthologous Groups in comparison with the complete genome of C. pinensis DSM 2588 T . The genomic information suggests the potential of the strain A37T2 T to interact with the plant metabolism. As there are only a few bacterial genomes related to Pine Wilt Disease, this work provides a contribution to the field.

Genetics & Heredity↗

Machine learning enables reconstruction of past fire regimes from charcoal-derived fire intensity and fuel composition

Background Fire is a foundational ecological process that shapes ecosystem structure, diversity, and resilience. Quantifying paleofire regime attributes such as frequency, severity, and intensity is essential for understanding the historical range of variability in fire behavior and its ecological effects. While frequency and severity are often reconstructed in paleofire studies, quantitative reconstructions of fire intensity remain limited. Recent work has shown that maximum pyrolysis temperature—a proxy for fire intensity—and plant species type can be inferred from charcoal using transmission Fourier-transform infrared (FTIR) spectroscopy. However, the sample preparation for transmission FTIR is destructive and time-consuming, limiting application and reuse of materials for other analyses. We evaluated reflectance FTIR spectroscopy as a non-destructive alternative for reconstructing combustion temperature and plant species from laboratory-generated charcoal. We also examined the influence of contrasting airflow environments (ambient air versus nitrogen-rich) on pyrolysis temperature and plant species reconstruction prediction accuracies and compared predictive performance between a novel, neural network–based deep learning model with the traditional modern analogue technique (MAT) using k-nearest neighbor functions. As proof of concept, we apply our enhanced methodology to ancient charcoal to demonstrate applicability at improving long-term fire regime reconstructions and the ability to link paleofire records with contemporary fire ecology. Results Our analysis shows that transmission and reflectance FTIR spectra yield comparable spectral profiles. However, sample preparation for reflectance FTIR is minimal and non-destructive, unlike transmission FTIR which is destructive. We demonstrate that oxygen environments improved reconstruction accuracy relative to nitrogen-rich conditions. Finally, our deep learning neural network (DL) achieved testing accuracies of 98.7% for temperature and 96.2% for species identification, outperforming MAT’s k-NN approach (89.8% and 65.9%, respectively). A Shapley importance analysis identified 5 key spectral regions that greatly influenced the model’s temperature or species categorization. When applied to ancient charcoal, our results show historic fires from the most recent past primarily burned at low intensities (400–500 °C), reflective of natural fire regimes in ponderosa pine forests. Our results corroborate charcoal morphology data that suggests all ancient charcoal originated from burned woody plant types. Conclusions By combining reflectance FTIR spectroscopy with a deep learning approach, we provide the first accuracies high enough to confidently identify both species and temperature from laboratory-produced charcoal, improving quantitative reconstructions of fire intensity and fuel composition from paleofire records. This opens a wide range of research into the link between fire and larger drivers (i.e., climate or human) and greater ecological understanding of fire regimes beyond that of burn scars or recent observations. These methodological improvements have direct relevance for fire management by improving interpretation of historical fire behavior, informing fuel–fire relationships, and providing a scalable analytical framework applicable to both long-term ecological studies and contemporary fire science.

54 ENVIRONMENTAL SCIENCES↗

Chapter 4: "Waste"-to-Energy for Decarbonization - Transforming Nut Shells Into Carbon-Negative Electricity

This chapter presents a study demonstrating waste pistachio nut shells as a renewable feedstock for climate-friendly electricity generation via industrial gasification technology. The study includes biomass feedstock characterization (i.e., pistachio waste critical material attributes), process variability (i.e., bulk material handling), and overall operational reliability and conversion performance through extended testing. Additionally, techno-economic analysis (TEA) and life cycle assessment (LCA) were performed to assess the economic feasibility and environmental impact of the technology to transform agricultural waste to biopower. For processing pistachio waste material, among critical material attributes, fines content in the biomass (<1/4") had the largest potential to reduce the operating time of the gasifiers due to plugging. Pelletizing fines and co-feeding them with the mixed pistachio waste increased the average feed density, feed rate, and biochar production. Compared to pine wood chips, mixed pistachio waste yielded higher biochar quantity but slightly reduced quality. In general, a systematic Quality by Design methodology is the preferred approach for designing preprocessing and material conveyance systems, where a downstream technology (end user) for the produced intermediate is specified at the outset. TEA results show that the biochar production rate and selling price had an overwhelming impact on the modeled Minimum Electricity Selling Price (MESP), which ranged from 35.5 to 39.9 cents/kWh for the cases studied (16 h/day operational basis). Moreover, LCA results show that the valorization of pistachio shells for biopower generation is a "carbon negative" process that can help decarbonize the U.S. electricity grid. The specific carbon intensity was -0.29 to -0.71 kg CO2e/kWh, compared to 0.45 kg CO2e/kWh for the average U.S. electricity mix. Biochar production from pistachio waste as a potential means for carbon sequestration was a significant driver for the LCA. The highly stable biochar permanently sequesters a considerable fraction of biochar carbon in the ground, more than enough to offset the life cycle emissions, and can be a complementary climate change mitigation strategy.

bio-char↗

Chapter 24: The Compound Middle Lamella as a Target for Improved Deconstruction of Woody Biomass

The compound middle lamella (CML) of woody angiosperm species, such as poplar (Populus spp.), birch (Betula spp.), and alder (Alnus spp.), and gymnosperm species, such as pine (Pinus spp.), Douglas fir (Pseudotsuga menziesii), and spruce (Picea spp.), is an amalgam of lignin, hemicellulosic xylans, and pectic polysaccharides that is the major site of cell-cell adhesion of fibre cells and tracheary elements. In grass species, such as sorghum (Sorghum bicolor), switchgrass (Panicum virgatum), and sugarcane (Saccharum officinarum), a phenylpropanoid network deposited in xylan-rich primary walls extends into the lignified CML. This review traces the early history of discovery of the molecular components of the CML and presents the current state of knowledge on the development of the CML in bioenergy-relevant woody species and grasses. This chapter emphasises the role of the CML in the recalcitrance of biomass to deconstruction by mechanical and enzymatic means for conversion to biofuels and valuable bioproducts. The use of genetic engineering to alter CML composition and structure to facilitate biomass deconstruction and to redesign wood to generate materials with novel properties is discussed.

BIOMASS FUELS↗

Data for Robust Paths to Net Greenhouse Gas Mitigation and Negative Emissions via Advanced Biofuels

This zip file contains a UNIX-format DayCent model executable, input files, automation code, and associated directory structure necessary to re-produce the DayCent analysis underlying the manuscript. The main script “autodaycent.py” (written for Python 2.7) opens an interactive command line routine that facilitates: Calibrating the DayCent pine growth model; Initializing DayCent for a set of case studies sites; Executing an ensemble of model runs representing case study site reforestation, grassland restoration, or conversion to switchgrass cultivation; and Results analysis & generation of manuscript Fig. 3. Note that the interactive analysis code requires that all input files to be contained in the directory structure as uploaded, without modification. Executable versions of the DayCent model compatible with other operating systems are available upon request.

Feedstock Production↗

Wear and Why? How Ash Elements Can Help Define Wear Profiles of Biomass Feedstocks

Biomass feedstocks have been shown to cause high wear rates on biomass processing equipment, including grinders, pneumatic conveyance systems, and screw feeders. Previously, wear rates were positively correlated with ash concentrations. Physical and chemical properties, including ash content, vary across the anatomy of plants in biomass feedstocks. To better understand biomass tissues that cause the most wear, anatomical fractions of pine forest residues were tested for wear properties. Fractions were tested in the Accelerated Wear Testing Apparatus using steel coupon mass loss to evaluate wear rates. Extrinsic ash was extracted and characterized. Total ash content of the forest residue was 0.80wt%. Anatomical fractions showed varied amounts of ash with highest concentrations in bark and needles (2.33wt%, 3.52wt%, respectively). The wear rate of the forest residue was 2.36mg loss per kg biomass. Low ash fractions, including whitewood and cambium, caused little wear. Bark had lower ash than the needles but resulted in more wear (8.63 vs 5.57mg loss per kg biomass). Bark contained the most extrinsic ash and largest ash particle size, while needles contained the least extrinsic ash and smallest ash particle size. These findings indicate that total ash content (intrinsic plus extrinsic), soil contamination, and elemental analysis can provide information related to wear properties of biomass materials; however, these analyses do not fully explain the differences observed in the wear rates of bark and needles. Additional testing is to determine other parameters of importance.

Lacey, Jeffrey A.↗

Development of a size reduction equation for woody biomass: The influence of branch wood properties on Rittinger's constant

Size reduction is an essential but energy-intensive process for preparing biomass for conversion processes. Three well-known scaling equations (Bond, Kick, and Rittinger) are used to estimate energy input for grinding minerals and food particles. Previous studies have shown that the Rittinger equation has the best fit to predict energy input for grinding cellulosic biomass. In the Rittinger equation, Rittinger's constant (k R ) is independent of the size of ground particles, yet we noted large variations in k R among similar particle size ranges. In this research, the dependence of k R on the physical structure and chemical composition of a number of woody materials was explored. Branches from two softwood species (Douglas fir and pine) and two hardwood species (aspen and poplar) were ground in a laboratory knife mill. The recorded data included power input, mass flow rate, and particle size before and after grinding. Nine material properties were determined: particle density, solid density (pycnometer and x-ray diffraction methods), microfibril angle, fiber coarseness, fiber length, and composition (lignin and cellulose glucan contents). The correlation matrix among the nine properties revealed high degrees of interdependence between properties. The k R value had the largest positive correlation (+0.60) with particle porosity across the species tested. As a result, particle density was strongly correlated with lignin content (0.85), microfibril angle (0.71), fiber length (0.87), and fiber coarseness (0.78). An empirical model relating k R to particle density was developed.

09 BIOMASS FUELS↗

Thermal images collected during 3D printing with Cincinnati BAAM

This data set contains images produced to test the performance of anomaly and fault detection methods in the context of additive manufacturing. A total of 10 print jobs were executed using a Cincinnati BAAM (model 606) with a Cincinnati medium compression screw. The material used was compounded polylactic acid (PLA) with wood flour as a filler produced by Jabil (80% NatureWorks Ingeo 6060D amorphous PLA, % 100 mesh pine flour from American Wood Fiber). Print sheets were 1/4in polycarbonate.

36 MATERIALS SCIENCE↗

Analysis of the Phlebiopsis gigantea Genome, Transcriptome and Secretome Provides Insight into Its Pioneer Colonization Strategies of Wood

Collectively classified as white-rot fungi, certain basidiomycetes efficiently degrade the major structural polymers of wood cell walls. A small subset of these Agaricomycetes, exemplified by Phlebiopsis gigantea, is capable of colonizing freshly exposed conifer sapwood despite its high content of extractives, which retards the establishment of other fungal species. The mechanism(s) by which P. gigantea tolerates and metabolizes resinous compounds have not been explored. Here, we report the annotated P. gigantea genome and compare profiles of its transcriptome and secretome when cultured on freshcut versus solvent-extracted loblolly pine wood. The P. gigantea genome contains a conventional repertoire of hydrolase genes involved in cellulose/hemicellulose degradation, whose patterns of expression were relatively unperturbed by the absence of extractives. The expression of genes typically ascribed to lignin degradation was also largely unaffected. In contrast, genes likely involved in the transformation and detoxification of wood extractives were highly induced in its presence. Their products included an ABC transporter, lipases, cytochrome P450s, glutathione S-transferase and aldehyde dehydrogenase. Other regulated genes of unknown function and several constitutively expressed genes are also likely involved in P. gigantea’s extractives metabolism. These results contribute to our fundamental understanding of pioneer colonization of conifer wood and provide insight into the diverse chemistries employed by fungi in carbon cycling processes.

59 BASIC BIOLOGICAL SCIENCES↗

From lapis lazuli to ultramarine blue: investigating Cennino Cennini’s recipe using sulfur K-edge XANES

As one of the most desired and expensive artists’ materials throughout history, there has long been interest in studying natural lapis lazuli. The traditional method of extracting the blue component, lazurite, from lapis lazuli, as outlined in Cennini’s Il Libro dell’Arte , involves a lengthy purification process: (1) finely grind the rock; (2) mix with pine rosin, gum mastic, and beeswax; (3) massage in water to collect the lazurite. Repeating the process produces several grades of the pigment, typically referred to as ultramarine blue. Here, we investigate the sulfur environment within the aluminosilicate framework of lazurite during its extraction from lapis lazuli. The sulfur XANES fingerprint from samples taken at the different stages in Cennini’s extraction method were examined. All spectra contain a strong absorption peak at 2483 eV, attributable to sulfate present in the lazurite structure. However, intensity variations appear in the broad envelope of peaks between 2470 and 2475 eV and the pre-peak at 2469.1 eV, indicating a variation in the content of trisulfur (S 3 –˙ ) radicals. By studying the effect of each step of Cennini’s process, this study elucidates the changes occurring during the extraction and the variability within different grades of the precious coloring material. The increasing application of XANES to the study of artist’s materials and works of art motivated extending the research to assess the possibility of X-ray induced damage. Direct comparison of micro-focused and unfocused beam experiments suggests an increase of the S 3 –˙ radicals with prolonged exposure. Furthermore, analysis indicates that induced damage follows first-order kinetics, providing a first assessment on the acceptable amount of radiation exposure to define the optimal acquisition parameters to allow safe analyses of lapis lazuli and ultramarine pigments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microbial extracellular enzyme activity with simulated climate change

It is critical to understand the consequences of environmental change for the microbial regulation of carbon and nutrient cycling. Specifically, understanding microbial community traits, such as extracellular enzyme activity, can help inform nutrient cycling models and address knowledge gaps. We analyzed data on extracellular enzyme activities and litter decomposition from an 18-month experiment in which microbial communities were reciprocally transplanted along a climate gradient in Southern California. Communities were from desert, scrubland, grassland, pine–oak, and subalpine ecosystems. We aimed to test how enzyme activities responded to climate change following transplantation and how those responses related to decomposition rates. We hypothesized that microbial communities would specialize on their native climate conditions, resulting in higher enzyme activities when transplanted back into their native climate. We investigated the relationship between extracellular enzyme Vmax values, substrate mass loss, and microbial biomass as well as variation in these variables across the climate gradient. We found little evidence for climate specialization, and there was rarely a reduction in enzyme functioning after microbial communities were transplanted into new climate conditions. Moreover, observed differences in decomposition were not related to changes in extracellular enzyme potential, although there were significant differences in enzyme activities and decomposition rates across sites. These results suggest that direct, physiological impacts of climate are likely to be important for enzyme-mediated decomposition, but climate specialization will not constrain the microbial response to climate change in our system.

54 ENVIRONMENTAL SCIENCES↗

Accurately estimating and minimizing costs for the cellulosic biomass supply chain with statistical process control and the Taguchi Loss Function

This research focuses on the statistical evaluation of the feedstock attributes of the biomass supply chain and the estimation of attribute costs as a function of the feedstock variability. Challenges of using cellulosic feedstocks include the variability of feedstock quality (e.g., ash content and moisture content), which impacts the final cost of the manufactured product. Statistical Process Control (SPC), Taguchi Loss Function, and components of variance techniques were illustrated for quantifying cumulative variance in the biomass supply chain. Costs in the presence of cumulative variance were estimated for switchgrass (Panicum virgatum L.) and loblolly pine residues (Pinus taeda L.). Findings of the study indicated that additional costs from ash content variability in switchgrass increased the net cost by $\$19.15$ per dry tonne. Additional costs from densification due to particle size variation increased net cost by $\$11.59$ per dry tonne. Moisture content variation increased costs by $\$14.86$ per dry tonne. This would represent a 50 to 100% increase in costs due to variation based on a $\$60$ to $\$70$ per dry tonne manufactured product cost. This study illustrates that total costs may be considerably underestimated if the influence of variance for key factors in the supply chain and associated costs are not estimated.

59 BASIC BIOLOGICAL SCIENCES↗