SBIR-STTR Award

Millions of dollars worth of grain are lost worldwide due to spoilage activity in stored grain. Our goal is to develop an electronic device that will integrate CO2 sensing and data processing into a single unit. It will be an `easy-to-install-and-use' device that will continuously monitor CO2 concentrations in grain storage structures and alert operators early about spoilage conditions. It will provide information throughout the storage season, and minimize the loss of grain due to insects and molds. Commercialization of this device could save the U.S. grain industry millions of dollars annually, reduce the need for spoilage mitigation, improve the grain grading process for federal inspectors, and enhance the quality and competitiveness of U.S. grain exports. OBJECTIVES: Our goal is to develop an electronic device that will integrate CO2 sensing and data processing into a single unit. It will be an easy-to-install-and-use device that will continuously monitor CO2 concentrations in grain storage structures and alert operators early about spoilage conditions. It will provide information throughout the storage season, and minimize the loss of grain due to insects and molds. Development and commercialization of this device will depend on the successful completion of all three project phases as outlined above. The technical objectives for Phase I are: (1) Conduct a full-scale CO2 monitoring trial in two 400,000 bu commercial steel storage tanks utilizing semi-wet (17.5% moisture) vs. dry (15% moisture) corn. (2) Explore the development of inexpensive and reliable CO2 sensor hardware that could withstand the harsh grain facility environment, and of intelligent data processing software. APPROACH: In Phase I, we will refine our efforts based on the experiences made during the preliminary trial involving the large commercial grain storage structures at the Delphi, IN facility of The Andersons. We have secured their cooperation for the installation of 20 Telaire 7001 CO2 sensors in two 400,000 bushel tanks that they plan to fill with dry corn (i.e., moisture content below 15%) vs. semi-wet corn (i.e., moisture content around 17.5%) during the fall 2004 harvest. The Purdue team will be responsible for the on-site set up and monitoring of the data collecting effort. The BinTech team will be responsible for quality control and completeness of the data gathering effort via the internet-connected computer. The BinTech team will explore the development of inexpensive and reliable CO2 sensor hardware that could withstand the harsh grain facility environment, and of intelligent data processing software that could tie in with a model of the processes involved. Our combined efforts will enrich our understanding of the various parameters that affect the generation and movement of CO2 in a grain mass and storage structure. The successful completion of our Phase I efforts will lay the foundation for Phase II of this project. PROGRESS: 2004/05 TO 2006/12 This research project utilized commercial NDIR based CO2 sensors installed in a large network on mulitple 500,000 bushel capacity vertical and multiple >1.5 million bushel capacity groundpile storage vessels. The monitoring was conducted over 2 storage seasons. The data was collected via wireless communication from the sensors to a base station and from the base station to Purdue University. The grain monitored was # 2 yellow corn of various qualities and moisture contents. The test site was an operational grain elevator similar to other grain elevators whose business is primarily receiving, conditioning, holding, blending and then selling/shipping commodity bulk grain. Considerable high-value research data was collected addressing CO2 detection efficacy, CO2 early detection, sensor placement, number of sensors necessary per grain bin, mycotoxic risk, etc. The research results appear to present clear indicators of the viability of using CO2 for the early detection and warning of the onset of grain condition degradation. Also, the research resulted in a number of viable sensor packaging concepts that are believed to comply with explosion proof requirements and are expected to be reliable ruggedized yet cost effective new products. At the heart of the new sensor is a MEMS(Micro-Electro-Mechanical-System) based state of the art detector. IMPACT: 2004/05 TO 2006/12 Results of the research confirm that CO2 detection is a viable advanced spoilage alarm for bulk stored cereal grain. The future development of a robust sensor based on this research will give all grain owners and managers a new tool for improving grain quality management at farms and at commercial grain handling facilities

Millions of dollars are lost worldwide due to insect and fungi caused spoilage in stored grain. The predominate method for spoilage detection at farms involves manual walking, smelling, sampling the grain inside the storage bin which is at best very time consuming and randomly effective and at worst life threatening. The predominate method for detection at elevators/processors is via temperature cables which have significant efficacy problems due to the insulation value of grain that hampers hot spot detection. We propose to develop new technology for early detection that takes advantage of the fact that small amounts of spoilage cause significant increases in CO2 concentration throughout the grain mass and storage structure. A sensor system designed to detect the early and progressive stages of spoilage before a human or temperature cable response. The new sensor will be designed for placement in stored grain structures to continuously monitor CO2. The readings will be processed intelligently to give users information about the characteristics and extent of the spoilage for their quality management decision making process. This will require the development of inexpensive, easy to install, easy to use, reliable sensor hardware to withstand the harsh grain facility environment. And software that accounts for dynamic factors such as grain type, grain quantity, storage structure architecture; to effectively alert the user about developing decay. OBJECTIVES: Our goal is to develop an electronic device that will integrate CO2 sensing and data processing into a single unit. It will be an easy-to-install-and-use device that will continuously monitor CO2 concentrations in grain storage structures and alert operators early about spoilage conditions. It will provide information throughout the storage season, minimize the loss of grain due to insects and molds, and stifle the opportunity for mycotoxic grain infection. The technical objectives for this Phase II are: (1) Continue the R&D of the CO2 sensor concepts. Specifically with the goal at the completion of the phase II project of a single front end sensor head and two complete sensor systems ready for commercial introduction. One sensor system application for on-farm grain storage bins and one for off-farm commercial grain storage vessels. (2) As part of the final R&D of the envisioned two sensor products, conduct a wide-scale farm bin and commercial storage vessel pilot test using the preproduction stage of the two versions of the CO2 sensor system. Including sampling, analysis, and documentation of the starting and ending quality of the grain being monitored. (3) Using the data from the pilot program (i.e. the CO2 readings, the grain quality correlation, the grain type, and perhaps the grain bins physical parameters), develop the first generation alarm model to be integrated into the CO2 sensors firmware that will aid the farmer or commercial operator in making spoilage mitigation decisions such as initiating aeration, coring, stirring, or early merchandising the problem grain. APPROACH: We will follow a well defined plan of research tasks for this project. Like in Phase I, BinTech will continue its strong collaboration with the Purdue University PHERC research team. In phase II, the BinTech team will design and build hardware prototypes of the CO2 sensor combined with data processing into a single unit. It will be an easy-to-install-and-use, reliable and rugged device that will withstand the harsh grain facility environment, continuously monitor CO2 concentrations in grain storage structures, and alert operators early about spoilage conditions. We will then conduct a moderate scale pilot field trial with the prototype design. Research data gathered from the pilot tests will be analyzed for trends and correlations between the CO2 measurements and the final spoilage. Also, using this data, the Purdue team will expand their existing Post-Harvest Aeration & Storage Simulation Tool (PHAST-FEM) to predict the generation and movement of CO2 throughout the grain mass and storage structure, as well as account for gas leakage from the structure. PHAST-FEM is based on the finite element method (FEM), currently incorporates the prediction of heat conduction and natural convection currents, and utilizes realistic boundary conditions for a range of grain types and storage structures. It has been validated using data collected in the two commercial tanks during Phase I. Results from these simulation studies is anticipated to generate a data base of grain quality maintenance vs. deterioration output, help to develop decision support software that will be incorporated into the final spoilage detection device, and aid in its commercialization