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- Creators: Ahn, Gail-Joon
- Creators: Grgich, Traci
Description
The true number of food borne illness occurrences that stem from the home is largely unknown, but researchers believe the number is much greater than represented in national data. The focus on food safety has generally been directed at food service establishments, which have made great strides at improving the methods of how their food is prepared. However, that same drive for proper food safety education is lacking in home kitchens, where the majority of food is prepared. Young adults are among some of the riskiest food preparers, and limited research and education methods have been tested on this vulnerable population. This study examined the effect of a basic food safety intervention on consumer food safety knowledge in young adults in the United States (U.S.) over a week period. The study had a pre/post survey design, where participants answered a survey, watched a short 10-minute video, and then recompleted the same survey a week later. Ninety-one participants age 18-29 years completed the initial food safety knowledge questionnaire. Twenty-six of those participants completed both the pre- and post-intervention food safety knowledge questionnaires. A paired t-test was used to analyze changes in questionnaire scores pre/post intervention. The majority of participants were female (78.9%), Arizona State University (ASU) students (78.0%), did not have any formal food safety education (58.2%), prepared a minimum of one meal per week from home (96.7%), and had completed 0-1 college nutrition courses (64.8%). The average overall score for all participants who completed the initial questionnaire was 62.6%. For those that took both the initial questionnaire and the follow up questionnaire (n=26), their scores shifted from 66.8% to 65.5% after the intervention. Scores increased significantly only for one question post-intervention: 38.5% (n=10) to 53.8% (n=14) for the safest method for cooling a large pot of hot soup (p = 0.050). This was the first study of its kind to test a video intervention in attempts to increase food safety knowledge in young adults, and additional studies must be done to solidify the results of this study. Other means of education should be explored as well to determine the best way of reaching this population and others.
ContributorsClifford, Brooke (Author) / Johnston, Carol (Thesis advisor) / Grgich, Traci (Committee member) / Shepard, Christina (Committee member) / Arizona State University (Publisher)
Created2019
Description
Food safety is vital to the well-being of society; therefore, it is important to inspect food products to ensure minimal health risks are present. A crucial phase of food inspection is the identification of foreign particles found in the sample, such as insect body parts. The presence of certain species of insects, especially storage beetles, is a reliable indicator of possible contamination during storage and food processing. However, the current approach to identifying species is visual examination by human analysts; this method is rather subjective and time-consuming. Furthermore, confident identification requires extensive experience and training. To aid this inspection process, we have developed in collaboration with FDA analysts some image analysis-based machine intelligence to achieve species identification with up to 90% accuracy. The current project is a continuation of this development effort. Here we present an image analysis environment that allows practical deployment of the machine intelligence on computers with limited processing power and memory. Using this environment, users can prepare input sets by selecting images for analysis, and inspect these images through the integrated pan, zoom, and color analysis capabilities. After species analysis, the results panel allows the user to compare the analyzed images with referenced images of the proposed species. Further additions to this environment should include a log of previously analyzed images, and eventually extend to interaction with a central cloud repository of images through a web-based interface. Additional issues to address include standardization of image layout, extension of the feature-extraction algorithm, and utilizing image classification to build a central search engine for widespread usage.
ContributorsMartin, Daniel Luis (Author) / Ahn, Gail-Joon (Thesis director) / Doupé, Adam (Committee member) / Xu, Joshua (Committee member) / Computer Science and Engineering Program (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05