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: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=544020
• 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，粮食可以安全储存数年，因为粮食是耐用品;然而，物理，化学和生物因素的不当相互作用会破坏粮食。在单个存储单元中，腐败的量可以高达100%（例如，箱、袋、仓库或掩体）。因此，我们的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定性和定量损失，作为创新的储粮管理工具，为消费者提供安全的食品，增加农民的收入。 为了实现这一目标，我们将进行实验研究，并解决偏微分方程的热量和质量传递以及昆虫运动。 我们的实验将集中在填补数据空白，几乎没有数据可在文献中的影响，次优条件下的昆虫种群动态和谷物和昆虫的呼吸。 还将对加拿大谷物中发现的两种最常见的昆虫--锈粒甲虫和红粉甲虫在温度、湿度和二氧化碳的几个梯度下的运动进行实验，以确定昆虫运动的系数，从而使用有限元法求解昆虫运动的三维偏微分方程。这将有助于我们整合我们的昆虫运动模型与传热传质模型。将进行全尺寸箱实验来验证我们的模型。我们的研究将导致对储藏谷物生态系统的理解取得重大进展，从而预测和预防谷物腐败。这将有助于保持加拿大每年粮食作物的价值（价值约154亿美元），并保持其向国内和出口买家销售无昆虫，农药残留和真菌毒素的高质量谷物的声誉。 我们的研究结果将适用于全球，并将有助于加强食品安全和保障。