Biomass feedstock production (BFP) is a critical subsystem within the overall bio-based energy production and utilization system. It provides necessary materials input to the conversion process of biomass into fuel, power, and value-added materials.  This subsystem includes the operations of agronomic production of energy crops and physical handling/delivery of biomass, as well as other enabling logistics. On the technical side, biological, physical, and chemical sciences need to be integrated with engineering and technology to ensure effective and efficient production of biomass feedstock. The entire bio-based energy system is understandably complex. The focus of this program will be on the engineering solutions for its subsystem of biomass feed stock production while keeping in mind its “external” interactions and influencing factors, such as social/economic considerations, environmental impact, and policy/regulatory issues. 

The overall objective of this program is to develop effective and efficient engineering solutions and machinery for successful production of biomass feedstock. This program objective will be accomplished through five interrelated tasks of (1) Pre-Harvest Crop Production, (2) Harvesting, (3) Transport, (4) Storage, and (5) Systems Informatics and Analysis.  For each task, systematic approaches will be taken to evaluate existing technologies, characterize task features, identify information needs and researchable questions, develop prototypes and computer models, conduct experiments and computer simulations, and analyze experimental data and simulation output. Results will be delivered in the forms of operational machinery design and prototypes, informational databases, and decision support tools.

Pre-Harvest Crop Production (Tian, Grift, Zhang) – Objectives: Develop optimized instrumentation and data processing systems for crop growth, health and stress monitoring; and algorithms for field operation scheduling. Research questions: (1) What are the major crop sensing needs for energy crop health monitoring and productivity improvement? (2) Which sensor/platform should be used for the field data collection? And, (3) what is the best process for energy crop data-to-knowledge conversion?

Harvesting (Zhang, Tian) – Objectives: Develop sustainable and cost-effective processes and optimized equipment for harvesting and collecting biomass feedstock of both types (agronomic crop residuals and perennial grass straws) from the field.  Research questions: (1) What are the main obstacles in current processes and equipment that limit their application in biomass feedstock harvesting?   (2) What harvesting processes are capable of addressing these limitations?  (3) What functionalities should the harvesting equipment have for performing sustainable and cost-effective harvesting?

Transport (Grift, Hansen, Eckhoff) – Objectives:  Provide practical solutions to conveying biomass feedstock from the field to storage locations in sufficient quantities and at high enough delivery rates to sustain biomass-to-energy conversion facilities. Research questions: (1) What delivery rates, quantity, and quality of feedstock are required in order to sustain a biomass-to-energy conversion facility?  This research question will be addressed with input from the Systems Informatics and Analysis task group. (2)  What sustainable methods of conveying or transporting the biomass from field to storage or to biomass processing plant can be implemented that have sufficient capacity and rate of delivery, while maintaining quality as determined in (1)? (3)  What post-harvesting processes are necessary to facilitate the transport of the biomass via methods determined in (2)?

Storage (Eckhoff, Ting, Zhang, Tian) – Objectives:  Develop guidelines for locating and sizing storage facilities, as well as storage and preservation methods that will provide adequate supply of high quality biomass to processing plants. Research questions:  (1) What storage capacity is required taking into account location, biomass consumption rate by energy production plant, and seasonal variation in biomass production?  (2)  What  storage and preservation methods such as ensiling, chemical preservation, drying, or freezing are suitable for BFP?  (3) What effect do moisture content, composition and quality of  biomass material have on storability? 

Systems Informatics and Analysis (Hansen, Ting, Rodriguez, Zhang) – Objectives: Integrate information and knowledge from various sources related to the BFP system in a real-time fashion, perform systems analysis, evaluate systems level performance, and deliver the results of analysis based on the most current information, also in a real-time fashion. Research questions:  (1) What systems integration platform is required in order to establish communication in a real-time fashion among the contributors and users of information?  (2) What systems analysis methodologies and computerized tools/user interfaces need to be developed for timely and wide implementation?

2009 Program Update:
A stand-alone multispectral imaging tower remote sensing system and a reconfigurable ground reference data acquisition vehicle (DAV) have been developed and tested. These sensing systems have been used for monitoring energy crops in real-time. Data processing algorithms are being developed to explore the optimum harvesting window for quality assurance of different biomass feedstocks. A study of the biophysical properties of Miscanthus relevant to cutting has been completed and will be used for designing and testing new cutting subsystems to be evaluated on a completed laboratory-scale cutting system research platform. A test protocol has been formulated for application this upcoming harvesting season to enable comparisons among commercial harvesting systems. Bulk density, particle size, and energy efficiency of size reduction were determined under various moisture and screening conditions. Energy efficiencies of pelletization and densification are being measured. Speed impacts on compression efficiency have been studied. A bale-scale compressor and biomass “Elevator” scenario has been designed. Web-based biomass transportation management systems are being developed. Moisture isotherms were determined for Miscanthus at different temperatures using the standard saturated salt solutions to provide various relative humidities. Equilibrium moisture content was measured by oven and Karl Fischer titration method when equilibrium was reached. Isotherms were fit into the Chung–Pfost’s model. The construction of a biomass post-harvest conditioning and storage laboratory was scheduled for completion by the end of 2009. The Systems Informatics and Analysis(SIA) team has deployed an informatics infrastructure providing knowledge management, concurrent engineering, and decision support. The BioFeed model has been enhanced and applied for Miscanthus and switchgrass production in Illinois. Development of both an agent-based model to analyze dynamic behaviors among multiple agents and an interactive web-based decision support platform are ongoing.