@article{jones_gillette_cooper_salinas_hill_black_lew_canelas_2022, title={Cultivating PhD Aspirations during College}, volume={21}, ISSN={["1931-7913"]}, url={http://dx.doi.org/10.1187/cbe.20-06-0111}, DOI={10.1187/cbe.20-06-0111}, abstractNote={Science, technology, engineering, and mathematics (STEM) career barriers persist for individuals from marginalized communities due to financial and educational inequality, unconscious bias, and other disadvantaging factors. To evaluate differences in plans and interests between historically underrepresented (UR) and well-represented (WR) groups, we surveyed more than 3000 undergraduates enrolled in chemistry courses. Survey responses showed all groups arrived on campus with similar interests in learning more about science research. Over the 4 years of college, WR students maintained their interest levels, but UR students did not, creating a widening gap between the groups. Without intervention, UR students participated in lab research at lower rates than their WR peers. A case study pilot program, Biosciences Collaborative for Research Engagement (BioCoRE), encouraged STEM research exploration by undergraduates from marginalized communities. BioCoRE provided mentoring and programming that increased community cohesion and cultivated students' intrinsic scientific mindsets. Our data showed that there was no statistical significant difference between BioCoRE WR and UR students when surveyed about plans for a medical profession, graduate school, and laboratory scientific research. In addition, BioCoRE participants reported higher levels of confidence in conducting research than non-BioCoRE Scholars. We now have the highest annual number of UR students moving into PhD programs in our institution's history.}, number={2}, journal={CBE-LIFE SCIENCES EDUCATION}, publisher={American Society for Cell Biology (ASCB)}, author={Jones, Daniela S. and Gillette, Devyn D. and Cooper, Paige E. and Salinas, Raquel Y. and Hill, Jennifer L. and Black, Sherilynn J. and Lew, Daniel J. and Canelas, Dorian A.}, editor={Price, RebeccaEditor}, year={2022}, month={Jun} }
 @misc{jones_2022, title={Data-Driven Decisions for Food and Energy}, volume={8}, url={http://dx.doi.org/10.52750/564142}, DOI={10.52750/564142}, abstractNote={You might not realize sweet potatoes come in all sorts of cool shapes and sizes. So why when you go to the grocery store, do they look all alike? Did you know how much power there is in corn? Computer programming, food and farmers actually have a lot in common. Daniela Sofia Jones, Ph.D., shares how agriculture data analytics is our best path to more efficient, sustainable, and resilient farms, the farms of the future.}, publisher={North Carolina State University}, author={Jones, Daniela}, year={2022}, month={Aug} }
 @article{grieger_zarate_barnhill-dilling_hunt_jones_kuzma_2022, title={Fostering Responsible Innovation through Stakeholder Engagement: Case Study of North Carolina Sweetpotato Stakeholders}, volume={14}, ISSN={2071-1050}, url={http://dx.doi.org/10.3390/su14042274}, DOI={10.3390/su14042274}, abstractNote={Stakeholder and community engagement are critical for the successful development of new technologies that aim to be integrated into sustainable agriculture systems. This study reports on an approach used to engage stakeholders within the sweetpotato community in North Carolina to understand their preferences, needs, and concerns as they relate to a new sensing and diagnostic platform. This work also demonstrates an example of real-time technology assessment that also fosters responsible innovation through inclusivity and responsiveness. Through the conduction of 29 interviews with sweetpotato stakeholders in North Carolina, we found that participants found the most value in detecting external sweetpotato characteristics, as well as the ability to use or connect to a smartphone that can be used in field. They also found value in including environmental parameters and having a Spanish language module. Most participants indicated that they were comfortable with sharing data as long as it benefited the greater North Carolina sweetpotato industry, and were concerned with sharing these data with “outside” competitors. We also observed differences and variations between stakeholder groups. Overall, this work demonstrates a relatively simple, low-cost approach to eliciting stakeholder needs within a local agricultural context to improve sustainability, an approach that could be leveraged and transferred to other local agrifood systems.}, number={4}, journal={Sustainability}, publisher={MDPI AG}, author={Grieger, Khara and Zarate, Sebastian and Barnhill-Dilling, Sarah Kathleen and Hunt, Shelly and Jones, Daniela and Kuzma, Jennifer}, year={2022}, month={Feb}, pages={2274} }
 @article{hossain_jones_hartley_thompson_langholtz_davis_2022, title={Nth-plant scenario for forest resources and short rotation woody crops: Biorefineries and depots in the contiguous US}, volume={325}, ISSN={["1872-9118"]}, url={http://dx.doi.org/10.1016/j.apenergy.2022.119881}, DOI={10.1016/j.apenergy.2022.119881}, abstractNote={Estimating the US potential of woody material is of vital importance to ensure cost-effective supply logistics and develop a sustainable bioenergy and bioproducts industry. We analyzed a mature conversion technology for woody resources for the contiguous US that takes advantage of economies of scale: the nth-plant. We developed a database to quantify the total accessible woody biomass within a distributed network of preprocessing depots and biorefineries considering both quality specifications for conversion and a target cost to compete with fossil fuels. We considered two categories of woody biomass: 1) forest residues from trees, tops and limbs produced from conventional thinning and timber harvesting operations as well as non-timber tree removal; and 2) short rotation woody crops such as poplar, willow, pine, and eucalyptus. A mixed integer linear programming model was developed to analyze scenarios with woody feedstock blends at variable biomass ash contents and cost targets at the biorefinery. When considering a target cost of $85.51/dry ton (2016$) at the biorefinery, the maximum accessible biomass from forest residues in 2040 remained constant at 106 million dry tons regardless of ash targets. Including short rotation woody crops as part of the blend increased the total accessible biomass to 153 and 195 million dry tons at ash targets of 1% and 1.75%, respectively. We concluded from our analysis that woody resources could address about 55% of EPA’s (Environmental Protection Agency) target of 16 billion gallons of cellulosic biofuel.}, journal={APPLIED ENERGY}, publisher={Elsevier BV}, author={Hossain, Tasmin and Jones, Dniela S. and Hartley, Damon S. and Thompson, David N. and Langholtz, Matthew and Davis, Maggie}, year={2022}, month={Nov} }
 @article{langholtz_davis_eaton_hilliard_brandt_webb_hellwinckel_samu_hartley_jones_2021, title={Nth-plant supply: corn stover supplies and costs in a fleet of biorefineries}, volume={11}, ISSN={["1932-1031"]}, url={https://doi.org/10.1002/bbb.2305}, DOI={10.1002/bbb.2305}, abstractNote={Abstract Feedstock cost and cost variability is expected to increase with the number of biorefineries. To quantify this effect, this spatial‐economic analysis simulates feedstock cost and cost variability of an industry based on corn stover as a function of the number of biorefineries. Results are reported for nine scenarios (a base case and sensitivity analysis of four variables – harvest efficiency, sustainability constraints, opportunity cost, and corn grain yield) under deterministic and stochastic simulations, assuming biorefineries using 658 000 Mg (725 000 tons) year −1 of corn stover in 2019. The resulting supply curves are highly elastic (i.e. little change in cost) for the first 50 of the 121 biorefineries, with price increases in subsequent biorefineries depending on scenario. In the base‐case deterministic scenario, weighted‐average stover costs are $66 Mg −1 ($60 ton −1 ), $69 Mg −1 ($62 ton −1 ), and $156 Mg −1 ($142 ton −1 ), at the first, 60th, and 121st biorefineries, respectively. The stochastic simulations, subject to observed 30‐year corn yield variability, follow a similar pattern, with price distributions that vary by scenario. The base‐case stochastic simulations illustrate minimal cost variability for the first 60 biorefineries, but rapid increases in cost variability in the second half of potential biorefineries, with similar patterns observed in the other scenarios. Of the four variables explored, price was most sensitive to harvest efficiency, followed by sustainability constraints, corn yield, and opportunity cost. Results suggest that, under conventional logistics, about half of the US corn stover resource is reliably available with minimum cost increase and variability. Interactive visualization is available at https://doi.org/10.11578/1828779 . © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd}, journal={BIOFUELS BIOPRODUCTS & BIOREFINING-BIOFPR}, publisher={Wiley}, author={Langholtz, Matthew and Davis, Maggie and Eaton, Laurence and Hilliard, Michael and Brandt, Craig and Webb, Erin and Hellwinckel, Chad and Samu, Nicole and Hartley, Damon and Jones, Daniela}, year={2021}, month={Nov} }
 @article{forsberg_dale_jones_hossain_morais_wendt_2021, title={Replacing liquid fossil fuels and hydrocarbon chemical feedstocks with liquid biofuels from large-scale nuclear biorefineries}, volume={298}, ISSN={["1872-9118"]}, url={https://doi.org/10.1016/j.apenergy.2021.117225}, DOI={10.1016/j.apenergy.2021.117225}, abstractNote={Liquid fossil fuels (1) enable transportation and (2) provide energy for mobile work platforms and (3) supply dispatchable energy to highly variable demand (seasonal heating and peak electricity). We describe a system to replace liquid fossil fuels with drop-in biofuels including gasoline, diesel and jet fuel. Because growing biomass removes carbon dioxide from the air, there is no net addition of carbon dioxide to the atmosphere from burning biofuels. In addition, with proper management, biofuel systems can sequester large quantities of carbon as soil organic matter, improving soil fertility and providing other environmental services. In the United States liquid biofuels can potentially replace all liquid fossil fuels. The required system has two key features. First, the heat and hydrogen for conversion of biomass into high-quality liquid fuels is provided by external low-carbon energy sources--nuclear energy or fossil fuels with carbon capture and sequestration. Using external energy inputs can almost double the energy content of the liquid fuel per unit of biomass feedstock by fully converting the carbon in biomass into a hydrocarbon fuel. Second, competing effectively with fossil fuels requires very large biorefineries—the equivalent of a 250,000 barrel per day oil refinery. This requires commercializing methods for converting local biomass into high-density storable feedstocks that can be economically shipped to large-scale biorefineries.}, journal={APPLIED ENERGY}, publisher={Elsevier BV}, author={Forsberg, C. W. and Dale, B. E. and Jones, D. S. and Hossain, T. and Morais, A. R. C. and Wendt, L. M.}, year={2021}, month={Sep} }
 @article{hossain_jones_hartley_griffel_lin_burli_thompson_langholtz_davis_brandt_2021, title={The nth-plant scenario for blended feedstock conversion and preprocessing nationwide: Biorefineries and depots}, volume={294}, ISSN={["1872-9118"]}, url={http://dx.doi.org/10.1016/j.apenergy.2021.116946}, DOI={10.1016/j.apenergy.2021.116946}, abstractNote={The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Defining the future location and supply logistics of conversion plants is imperative to ultimately transform the nation’s renewable biomass resources into cost-competitive, high-performance feedstock for production of biofuels and bioproducts. Since the US has put restrictions on production levels of conventional biofuels from edible resources, the nation needs to plan for the widespread accessibility and development of the cellulosic biofuel scenario. Conventional feedstock supply systems will be unable to handle cellulosic biomass nationwide, making it essential to expand the industry with an advanced feedstock supply system incorporating a distributed network of preprocessing depots and conversion plants, or biorefineries. Current studies are mostly limited to designing supply systems for specific regions of the country. We developed a national database with potential locations for depots and biorefineries to meet the nation’s target demand of cellulosic biofuel. Blended feedstock with switchgrass and corn stover (harvested by either a two- or three-pass method) are considered in a Mixed Integer Linear Programming model to deliver on-spec biomass that considers both, a desired quantity and quality at the biorefinery. The model solves for a network of varying size depots that supply to biorefineries of 725,000 dry tons/year. A total delivered feedstock cost that is less than $79.07/dry tons (2016$) is evaluated for years 2022, 2030, and 2040. In 2022, 124 depots and 59 biorefineries could be supplied with 42.8 million dt of corn stover and switchgrass. In 2030 and 2040, the total accessible biomass could increase to 215% and 393% respectively when compared to 2022. However, an $8/dry tons reduction in targeted delivery cost could reduce total accessible biomass by 67%. Kansas, Nebraska, South Dakota and Texas were identified as potential states with a strong biofuel economy given that they had six or more biorefineries located in all scenarios. In some scenarios, Colorado, Alabama, Georgia, Minnesota, Mississippi and South Carolina would greatly benefit from a depot network as these could only deliver to a biorefinery in a nearby state. To elaborate the impact of a nationwide consideration, the findings were compared with existing literature for different US regions. We also present results for biorefinery capacities that are double, triple and quadruple in size.}, journal={APPLIED ENERGY}, publisher={Elsevier BV}, author={Hossain, Tasmin and Jones, Daniela and Hartley, Damon and Griffel, L. Michael and Lin, Yingqian and Burli, Pralhad and Thompson, David N. and Langholtz, Matthew and Davis, Maggie and Brandt, Craig}, year={2021}, month={Jul} }
 @article{jones_searcy_eaton_2018, title={Assessment of Perennial Grass Inventories Predicted in the Billion-Ton Studies}, volume={61}, ISSN={2151-0040}, url={http://dx.doi.org/10.13031/trans.12505}, DOI={10.13031/trans.12505}, abstractNote={Abstract. The U.S. Department of Energy (DOE) has estimated herbaceous biomass availability through simulations with the Policy Analysis System (POLYSYS) agricultural modeling framework. An operational assumption for POLYSYS limited conversion of pastureland to perennial grass crops to counties east of the 100th meridian as a proxy for precipitation sufficient for economically viable yield, but allowed cropland conversion regardless of location. Knowledge of local conditions raised questions about predicted biomass quantities for Texas counties in the 2011 assessment. POLYSYS was rerun with different assumptions, specifically replacing the 100th meridian boundary with annual average precipitation data and limiting cropland conversion in low-rainfall counties. Perennial grass production was found to be overestimated by 8% and 87% in the U.S. and Texas, respectively (at $66.14 DMg -1 ), when limiting all land conversion to regions with >635 mm precipitation. Total herbaceous biomass predicted was approximately the same as in the BT2, but the biomass geographical location changed across the nation. Texas’ biomass contribution decreased from 6% to 1% at $66.14 DMg -1 and from 16% to 11% at $88.18 DMg -1 . Subsequent to this research being conducted, the DOE released the 2016 biomass inventory assessment, and these results are compared to those newest estimates. Keywords: Billion-Ton Study, Biomass, Perennial grass, Precipitation, Switchgrass.}, number={2}, journal={Transactions of the ASABE}, publisher={American Society of Agricultural and Biological Engineers (ASABE)}, author={Jones, Daniela  Sofia and Searcy, Stephen   W. and Eaton, Laurence   M.}, year={2018}, pages={331–340} }
 @article{gonzales_searcy_2017, title={GIS-based allocation of herbaceous biomass in biorefineries and depots}, volume={97}, ISSN={0961-9534}, url={http://dx.doi.org/10.1016/j.biombioe.2016.12.009}, DOI={10.1016/j.biombioe.2016.12.009}, abstractNote={While sufficient biomass has been identified to meet the Renewable Fuel Standard (RFS2)1 targets by previous studies, availability does not equal access. Our objective was to quantify the potential accessible and stranded herbaceous biomass from different scenarios of predicted available biomass in both Texas and the US. The location and size of potential biorefineries and depots was determined using the geographic location of suitable lands for biomass, the transportation infrastructure and published economic constraints for minimum biomass supplied to a facility within a specified neighborhood. Our GIS-based heuristic addresses the capacitated facility location problem by distributing potential biomass along a county's suitable lands. Road and rail proximity optionally was included in the algorithm. The total stranded biomass in Texas was 28% of the total available biomass. Including the constraint of the transportation network accessibility (rail and appropriate roads) when determining facility location increased the total stranded biomass to 33%. Using county centroids as supply points and potential facilities led to an increase of 7% in total biomass captured by all facilities in Texas when compared to our raster-based heuristic. The nationwide accessible biomass is 90% of the available biomass, 78% of which is captured by biorefineries. In total, 77 biorefineries and 171 depots were identified in the US, which projects to 184 million Mg year−1 delivered to biorefineries and depots, or 65.3 billion liters of advanced biofuels, more than the targeted 60 billion liters of advanced cellulosic biofuel in the RFS2.}, journal={Biomass and Bioenergy}, publisher={Elsevier BV}, author={Gonzales, Daniela S. and Searcy, Stephen W.}, year={2017}, month={Feb}, pages={1–10} }
 @article{acharya_gonzales_eksioglu_arora_2014, title={An Excel-Based Decision Support System for Supply Chain Design and Management of Biofuels}, volume={5}, ISSN={1947-9328 1947-9336}, url={http://dx.doi.org/10.4018/ijoris.2014100102}, DOI={10.4018/ijoris.2014100102}, abstractNote={This article presents a Decision Support System (DSS) to aid managers with supply chain (SC) design and logistics management of biomass-for-biofuel production. These tools play a very important role in efficiently managing biomass-for-biofuel SCs and have the potential to reduce the cost of biofuels. The proposed model coordinates the long-term decisions of designing a SC with the medium term decisions of logistics management. This system has the ability to (a) identify locations and capacities for biorefineries, given the availability of biomass and costs; (b) estimate the minimum cost of delivering biofuels, which include transportation, investment, and processing costs; and (c) perform sensitivity analyses with respect to a number of parameters. Visual Basic for Applications (VBA) is used to create the interface of the DSS, and Excel's CPLEX Add-In is used to solve the mathematical models.}, number={4}, journal={International Journal of Operations Research and Information Systems}, publisher={IGI Global}, author={Acharya, Ambarish M. and Gonzales, Daniela S. and Eksioglu, Sandra D. and Arora, Sumesh}, year={2014}, month={Oct}, pages={26–43} }
 @inproceedings{acharya_gonzales_eksioglu_2013, title={A decision support system (DSS) for biomass-to-biofuel supply chain}, booktitle={Proceedings of the 1st International Symposium on Computing in Informatics and Mathematics}, author={Acharya, A. and Gonzales, D. and Eksioglu, S.}, year={2013} }
 @article{gonzales_searcy_ekşioğlu_2013, title={Cost analysis for high-volume and long-haul transportation of densified biomass feedstock}, volume={49}, ISSN={0965-8564}, url={http://dx.doi.org/10.1016/j.tra.2013.01.005}, DOI={10.1016/j.tra.2013.01.005}, abstractNote={Using densified biomass to produce biofuels has the potential to reduce the cost of delivering biomass to biorefineries. Densified biomass has physical properties similar to grain, and therefore, the transportation system in support of delivering densified biomass to a biorenery is expected to emulate the current grain transportation system. By analyzing transportation costs for products like grain and woodchips, this paper identifies the main factors that impact the delivery cost of densified biomass and quantifies those factors’ impact on transportation costs. This paper provides a transportation-cost analysis which will aid the design and management of biofuel supply chains. This evaluation is very important because the expensive logistics and transportation costs are one of the major barriers slowing development in this industry. Regression analysis indicates that transportation costs for densified biomass will be impacted by transportation distance, volume shipped, transportation mode used, and shipment destination, just to name a few. Since biomass production is concentrated in the Midwestern United States, a biorefinery’s shipments will probably come from that region. For shipments from the Midwest to the Southeast US, barge transportation, if available, is the least expensive transportation mode. If barge is not available, then unit trains are the least expensive mode for distances longer than 161 km (100 miles). For shipments from the Midwest to the West US, unit trains are the least expensive transportation mode for distances over 338 km (210 miles). For shorter distances, truck is the least expensive transportation mode for densified biomass.}, journal={Transportation Research Part A: Policy and Practice}, publisher={Elsevier BV}, author={Gonzales, Daniela and Searcy, Erin M. and Ekşioğlu, Sandra D.}, year={2013}, month={Mar}, pages={48–61} }