Mathematical modeling of stored-grain ecosytems: a tool for preserving grain quality

储粮生态系统的数学模型：保持粮食质量的工具

• 批准号: 2219-2013
• 负责人: Jayas, Digvir
• 金额: $ 2.04万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Group
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=520458
• 关键词: Mathematical; modeling; stored; grain; ecosytems

Globally, about 2.7 billion tonnes of grains are produced annually and stored on farms or at storage facilities. Under ideal storage conditions, grains can be stored safely for several years as grains are durable products; however, improper interactions of physical, chemical and biological factors can spoil grains. 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 objective of our research program is to reduce the qualitative and quantitative losses in stored grains by developing and validating mathematical models of stored-grain ecosystems as innovative stored-grain management tools for supplying safe food for consumers and for increasing income of farmers. To achieve this objective, we will conduct experimental studies and solve partial differentials equations of heat and mass transfer as well as insect movement. Our experiments will focus on filling the data gap where almost no data are available in the literature related to the impact of sub-optimal conditions on the population dynamics of insects and respiration of grains and insects. Experiments also will be conducted on movement of rusty grain beetles and red flour beetles, two most common insects found in Canadian grain, at several gradients of temperature, moisture, and carbon dioxide for determination of coefficients of insect movement to solve the three-dimensional partial differential equation of insect movement using the finite element method. This will helps us integrate our insect movement model with heat and mass transfer models. Full-size bin experiments will be conducted to validate our models. Our research will lead to major advancements towards the understanding of stored-grain ecosystems, allowing prediction and prevention of grain spoilage. This would help in preserving the value of Canada's annual grain crop (worth about15.4 billion dollars) and in maintaining its reputation for marketing high quality grain free of insects, pesticide residues, and mycotoxins to domestic and export buyers. Our results will be applicable globally and will help in enhancing food safety and security.

全球每年生产约27亿吨谷物，并储存在农场或储存设施中。在理想的储存条件下，粮食可以安全储存几年，因为粮食是耐用的产品；然而，物理、化学和生物因素的不当相互作用可能会使粮食变质。单个存储单元(例如，垃圾箱、袋子、仓库或掩体)中的腐败量可能高达100%。因此，我们研究计划的长期目标是通过开发和验证储粮生态系统的数学模型来减少储粮的质量和数量损失，这些数学模型是为消费者提供安全食品和增加农民收入的创新储粮管理工具。为了实现这一目标，我们将进行实验研究，并求解热质传递和昆虫运动的偏微分方程组。我们的实验将专注于填补数据空白，因为文献中几乎没有关于次优条件对昆虫种群动态和谷物和昆虫呼吸的影响的数据。此外，还将对加拿大谷物中最常见的两种昆虫--锈粒甲虫和红粉甲虫在温度、水分和二氧化碳的不同梯度下的运动进行实验，以确定昆虫运动系数，用有限元方法求解昆虫运动的三维偏微分方程组。这将有助于我们将昆虫运动模型与热量和质量传输模型相结合。为了验证我们的模型，我们将进行全尺寸的仓储实验。我们的研究将导致对储藏粮食生态系统的理解取得重大进展，从而能够预测和防止粮食腐败。这将有助于保护加拿大年度谷物作物的价值(价值约154亿美元)，并保持其向国内和出口买家销售不含昆虫、农药残留和真菌毒素的高质量谷物的声誉。我们的成果将适用于全球，并将有助于加强食品安全和保障。