Mathematical models of stored-grain ecosystems for management of stored grains.

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Globally, more than 3.1 billion tonnes of cereal grains, oil seeds and pulses (collectively referred to as grains) are produced annually, and stored at one or more points during their movement from the field to processors or to consumers. Grains are durable products, and at properly controlled conditions can be stored for a long time (more than one year). Conversely, improper storage conditions can result in physical, chemical, and biological conditions that spoil grain. The amount of spoilage can be up to 100% in a single unit of storage (e.g., a bin, bag, warehouse, or bunker). Therefore, the long-term vision of my research program is to reduce the qualitative and quantitative losses in stored grains. My research trainees and I will develop three-dimensional (3-D) mathematical models of stored-grain ecosystems and will validate these models using full-size bin experiments for use as innovative stored-grain management tools. The approach taken by my interdisciplinary research program has been to develop mathematical models of heat, moisture, and carbon dioxide (products of grain spoilage) transfer to enhance our understanding of the interactions among important abiotic factors (e.g., temperature, moisture content, and carbon dioxide concentration) and biotic factors (e.g., grain, insects, mites, fungi, and bacteria). Experimental studies will be conducted to determine: 1) the properties of grains required as coefficients in these models; 2) the changes in the insect populations at temperatures, moisture contents and carbon dioxide concentrations expected during long-term grain storage; and 3) insect movement parameters under gradients of temperature, moisture and carbon dioxide concentration occurring in stored grains. Experimental studies to develop such an understanding of a large number of biotic and abiotic factors for different types of storage structures around the world would be cost prohibitive and time consuming. These validated mathematical models are used as management tools to predict the locations of spoilage by insects and fungi. The models are used to pinpoint the locations in grain mass that must be sampled for detection of spoilage so that early preventive actions can be taken if necessary. The models are also used to determine the location and resolution of sensors, measuring carbon dioxide or off-odour volatiles, to detect incipient spoilage. These models are also used to develop guidelines for preserving grains to feed the increasing world population by analyzing many “what if” scenarios for different sizes and types of bins located in different climatic zones and filled with different types of grains. The value of Canada's annual grain crop is about $26.8 billion and the results of this research would help Canada to maintain its reputation as a marketer of high quality grain that is free of insects, pesticide residues, and mycotoxins to domestic and export buyers.