Recipient Organization
PURDUE UNIVERSITY
(N/A)
WEST LAFAYETTE,IN 47907
Performing Department
Ag & Biological Engineering
Non Technical Summary
Spoilage of grain in on-farm storage is becoming a major problem on U.S. farms in the Cornbelt. This hurts farmers not just because of the discounts or dockage received when they deliver grain to the elevator, but more so when lives are lost in the process of trying to unload a silo that has caked up grain resulting from spoilage. A recent (March, 2013) NPR radio special series entitled "Buried in Grain" highlighted the fatalities that have occurred due to engulfments of workers in grain bins when grain is discharged. In an extensive database of 181 grain entrapment incidences reviewed in a study at Purdue by Kingman et al. (2001), victims entrapped in grain were involved in bin unloading activities in 76% of the cases, while in 53% of the cases, corn that had gone out of condition (spoilage) was the agent of injury. Unfortunately, since the NPR report of March 2013, there has been a fatal incident every month, with over 50% of the incidences related to farm or elevator workers trying to unload caked up grain. A lot of efforts to address the problem of grain engulfments is focused on training farm and elevator workers on safe bin entry procedures, awareness of the problem, and first responders on best pratices to rescue entrapped victims. However, little attention has been focused on addressing the root of the problem, which is best management practices to prevent grain spoilage in storage. With the increase in grain bin sizes for on-farm storage, it is most likely that farmers will continue to encounter more grain management challenges and possibly fatalities, if they are not appraised with new knowledge and technologies on how to manage large grain stocks.Adequate and safe monitoring of stored grain is obviously the best preventive approach to reduce the fatalities caused by engulfments during unloading of grain in both on-farm and off-farm (grain elevator, processing industries, etc.). In fact, the recommended management system, SLAM, which stands for sanitation, loading, aeration and monitoring, has monitoring of stored grain as one of the four important steps of best management practices for stored grain in silos. Monitoring is also the best approach to adequately secure all the investment in the harvested crop for the season stored in the bin. Adequately dried grain bulk that is kept secure from the elements in a bin is flowable, and can be easily discharged with conventional grain unloading equipment. But because grain is a biologically active material, it will deteriorate and possibly become unflowable under favorable conditions caused by environmental pressures of warm weather and high humidity, insect pest infestation and/or leakage of the silo. When grain begins to deteriorate, fungi mass grows on the grain surface gluing them together into a caked-up mass rendering the grain bulk non-flowable. Technologies that monitor the stored grain condition during storage and provide the farmer or stored grain manager with data to make an informed management decision will help prevent spoilage. Anedeoctal evidence suggest that less than 30% of grain bins on U.S. farms have some form of stored grain monitoring technology. Additionally, with the increased bin sizes, from an average of 30,000 bushels in the 1980s and 1990s to over 100,000 bushels today, it appears that farmers today are still trying to use management principles that they have successfully used to manage small grain stocks for managing large grain stocks. Likewise, Extension outreach materials in grain post-harvest handling and storage developed in the 1980s and 1990s need to be updated to reflect today's larger and high throughput grain handling and storage systems on-farm, especially on the use of stored grain monitoring technology.While technologies for stored grain monitoring are available today, they are quite limited in scope and not commonly used in on-farm storage. The most common stored grain monitoring technology are temperature sensors that are mounted along the length of a cable, which is installed hanging from the bin roof to the bin floor. The principle of using temperature sensors is based on the fact that when grain deteriorates heat is released from the break-down of carbohyrates by fungi producing heat, carbon dioxide and water. Heat is also released as insects metabolize carbohydrates when they feed on grain. The localized release of heat from these two biological processes which degrade corn quality can be sensed by a temperature sensors and thus used to indicate when grain is going out of condition in storage. Because grain is a good insulator and heat transfer from a hot spot in the grain to any temperature sensor at some distance from the hot spot will be slow, temperature sensors are not always reliable for detecting hot spots timely in silos. Ileleji et al (2006) showed that temperature cables alone might not be a reliable indicator of stored grain conditions, and CO2 sensors could be used as an additional more effective complimentary tool for stored grain management. Further development of the idea of monitoring CO2 in the bin headspace to determine biological activity in the stored grain was pursued with the industry (BinTech and GSI, Inc). This led to the development of a headspace CO2 sensor, BinspectorTM, marketed by GSI, Inc. (Assumption, IL) (FarmProgress.com, 2010). The current technology is not only quite expensive but has limitations on how well the data can be interpreted to make an informed management decision. The primary drawbacks in both the use of temperature sensors on cables and CO2 sensors mounted in the headspace is that the data of temperature and CO2 concentration over time need to be interpreted by the operator and most monitoring systems don't have a expert system that provides guidiance on how the data should be interpreted. Additionally, little research has been conducted on the use of stored grain temperature and CO2 data in quantifying the quality condition of the grain. In fact, no Extension publication exists to guide farmers and elevator managers on how stored grain monitoring data should be interpreted in making informed management decisions. The proposed research will develop an expert management system for stored grain by quantifying and coupling multiple parameters of stored grain monitored for use in making improved management decisions.
Animal Health Component
50%
Research Effort Categories
Basic
10%
Applied
50%
Developmental
40%
Goals / Objectives
The focus of this research is investigating new innovative technologies and management practices that will permit farmers, elevator managers and grain processors to safely and effectively manage stored grain in silos without entry (zero entry). Current strict regulations for confined space entry by the Occupational Safety and Health Administration (OSHA), necessitates a paradigm shift from current unsafe operational practices where workers enter grain bins to perform tasks such as sampling, dislodging grain, etc. to avoidance of bin entry. In order to develop a zero entry platform for stored grain systems, technologies and systems for the effective management of the stored grain that prevent spoilage, and thus avoid bin entry must be developed.The following specific objectives will be pursued toward this end: (1) develop a deep grain probe for localized sampling of CO2, temperature and relative humidity in bulk grain; (2) improve on current CO2 monitoring technology by using the probe in Objective 1 to quantify and differentiate biological activity in a stored grain mass due to grain respiration, fungi, and/or insect pests activities; (3) develop a CO2 evolution and movement model due to grain respiration, fungi activity and insect pest activity; (4) develop an expert management system with real-time grain quality tracking for improved management of large grain stocks in bins; (5) develop a zero entry platform that will use technologies developed in Objectives 1 to 5; and (6) incorporate knowledge from Objectives 1-5 in extension outreach efforts (workshops, extension publications, posters, etc.)
Project Methods
Objective 1.Develop a deep grain probe for localized sampling of CO2, temperature and relative humidity in bulk grain: A retractable telescopic probe that penetrates the grain will be a 6 ft PVC or aluminum probe that has three air sampling ports spaced 2 ft apart. Each sampling port will be connected with Nalgene polypropylene tubing routed through the PVC pipe to a CO2 sensor mounted at the top end of the probe. Temperature and relative humidity (RH) sensors will be mounted at each sampling port. The CO2 sensor will be equipped with an air pump. The pump and sampling scheme will be designed to pull air sequentially from each port. The ability for the probe to sample air from the bin headspace and multiple locations across the cross-section of the grain in a bin will provide data for the development of an expert algorithm to precisely pinpoint the location of biological activity within the grain. The expert system will determine if there is a localized hotspot of grain deterioration. All components (CO2 sensors, pump, temperature and relative humidity sensors) will be connected to a printed circuit board (PCB) and input/output data obtained via interface with a USB connector to a PC. The unit will be powered by 24V DC using a standard transformer commonly used in the industry. LabVIEW Development Systems for Windows (National Instruments, Austin, TX) will be used to design the data acquisition (DAC) and control system, so that data of CO2, temperature and relative humidity, can be logged at desired intervals and the equilibrium moisture content (EMC) of grain can be determined from the relative humidity data via EMC/RH model. The DAC software will allow the input of grain respiration, fungi and insect development models based on CO2 evolution.Objective 2.Improve on current CO2 monitoring technology by using the probe in Objective 1 to quantify and differentiate biological activity in a stored grain mass due to grain respiration, fungi, and/or insect pests activity:This experiment will monitor biological activity based on CO2, temperature and relative humidity in grain (No. 2 yellow dent corn) stored in 85 gallons steel drums (about 39"× 26.56") in an environmental controlled chamber. The drums will be equipped with a perforated false floor through which a fan could be used to aerate the stored grain. Corn will be freshly harvested/timely dried to 14-15% moisture content (MC), and subsequently disinfected by freezing at -20C for 7 days or fumigated with phosphine to ensure that all biological activity from insect pest of fungi is eliminated. Other temperature sensors and a headspace relative humidity sensor will be installed in each drum. In scenario 1 (control), biological activity primarily caused by grain respiration will be monitored. In one of the 85 gallon steel drums filled with corn at 14-15% MC, a 12" diameter PVC tubing perforated with large holes covered with mesh spanning the fill height of the grain will be embedded at the center of the grain mass, leaving an empty space through the length of the tubing. In scenario 2, biological activity primarily caused by fungi will be monitored. A range of moisture contents (18-25%) and quantities of grain will be investigated to determine CO2 production from a given quantity of high-moisture grain caused primarily by fungi deteriorating corn. In scenario 3, biological activity primarily caused by two insect pests will be investigated, e.g., the maize weevil, Sitophilus zeamais (whole grain feeder) and red flour beetle, Tribolium castaneum (secondary flour/bran feeder). Data of biological activity will be collected for various levels of infestation (numbers of insects) and ratios of species (mixture of S. zeamais and T. castaneum). The fourth scenario, will be a combination of biological activity caused by both fungi and insect pest activities, and levels of mechanical damage (broken corn and fines).Objective 3.Develop a CO2 evolution and movement model due to grain respiration, fungi activity and insect pest activity:We will utilize a comprehensive stored grain ecosystem model (PHAST) developed at Purdue University that accurately predicts the heat and mass transfer in upright corrugated steel structures as a function of historic weather conditions (Montross, 1999). Biological events such as dry matter loss, grain respiration, fungi and mycotoxin development, and insect development are in the model. The model will be modified to allow for the prediction of CO2 production due to biological activity of grain respiration, fungi, and insect activity, and CO2 movement from the point source (hot spot) throughout the grain.Several mathematical models that predict the movement of CO2 as a fumigant gas in grain have been solved (Jayas et al., 1988, Alagusundaram et al., 1996 and Smith and Jayas, 2001). They were based on the transient transport of miscible fluids in an anisotropic porous medium governed by the partial differential equation given by Bachmat and Bear (1964), Bear and Bachmat (1991) and Huyakorn et al., (1986). We propose to develop a model of CO2 production that would closely replicate the dynamics of hot spot development in stored grain caused by fungi, insects or both. The model will be solved using the computational fluid dynamics (CFD) module on COMSOL Multiphysics® software (COMSOL Inc., Burlington, MA). The model will take into account the gas loss from the bin due to leakage and exchange caused by ambient wind effects, and adsorption of CO2 by grain (Cofie-Agblor et al. 1993). This should enable us to quantify the amount of CO2 produced over time, and predict the movement of CO2 through the grain towards the headspace as well as leakage through the bin wall and other openings (vents, bolt holes, ducts, unsealed fans, etc.). If gas loss is determined, we will be able to determine correction coefficients for the bin that adjusts the values recorded by a CO2 sensor on a probe measured within the grain, thereby estimating the level of biological activity more accurately.Objective 4.Develop an expert management system with real-time grain quality tracking for improved management of large grain stocks in bins:An expert management system with real-time tracking of grain quality will be developed. We will explore the use of data from a fungal susceptibility measurement tool using the Solvita® kit developed at Purdue by Dr. Stroshine and his team (Moog, 2006). The quality parameters that will be used as indicators of grain quality will be CO2, temperature and moisture content and will be modeled using data of the initial grain condition. The expert system will alert management to a problem when deviations exceed a pre-determined threshold level.Objective 5.Develop a zero entry platform that will use technologies developed in Objectives 1 to 5:The zero entry platform concept will be based on a robotic telescopic probe that is mounted on the bin roof and capable of moving in the headspace to preprogrammed locations above the grain for deep probing of 12 ft or more. The penetration of the probe into the grain will be by vacuum suction. Flexible durable tubing will transfer sampled grain from the probe enabled by an electrical powered cyclone assist via the flexible tubing ducted along the side of the bin, which will be transferred down by gravity to a sampling collection port at the bin base. This concept eliminates workers from climbing up to very high elevations and entering the unsafe environment of a confined bin space.Objective 6.Incorporate knowledge from Objectives 1-5 in Extension outreach efforts (workshops, Extension publications, posters, etc.): Presentations will be made at professional conferences, Extension workshops, the Grain Elevators and Processing Society (GEAPS), Commodity Classic and farm equipment shows. Research and Extension publications on safe and effective management of stored grain will be distributed via Purdue's Extension website.