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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳秀熙 | zh_TW |
dc.contributor.advisor | Hsiu-Hsi Chen | en |
dc.contributor.author | 謝宜芳 | zh_TW |
dc.contributor.author | Yi-Fang Hsieh | en |
dc.date.accessioned | 2023-03-08T17:01:11Z | - |
dc.date.available | 2023-11-10 | - |
dc.date.copyright | 2023-03-01 | - |
dc.date.issued | 2023 | - |
dc.date.submitted | 2023-02-18 | - |
dc.identifier.citation | 1. 衛生福利部食品藥物管理署(2022)。食品藥物管理署年報。衛生福利部食品藥物管理署網站。https://www.fda.gov.tw/upload/ebook/AnnuaReport/2022/2022_C/ index.html#p=I
2. 楊安琪、鄭維智、蕭惠文、劉芳銘(2019)。我國食品安全衛生管理之中央年度後市場稽查專案規劃之簡介。食品藥物研究年報,10,382-391。https://doi.org/10.6945/ARFDR 3. 行政院農業委員會(2021)。糧食供需年報。行政院農業委員網站。https://agrstat.coa.gov.tw/sdweb/public/book/Book.aspx 4. Garg, N., Abdel-Aziz, S. M. & Aeron, A. (2016). Microbes in Food and Health. Springer. https://doi.org/10.1007/ 978-3-319-25277-3 5. 衛生福利部(2022)。市售包裝食品有效日期評估指引。衛生福利部食品藥物管理署網站。https://www.fda.gov.tw/TC/newsContent.aspx?cid=3&id=28422 6. Barbosa-Cánovas, G. V., Fontana Jr, A. J., Schmidt S. J. & Labuza, T. P. (2020). Water Activity in Foods: Fundamentals and Applications (2nd ed.). Wiley Blackwel. https://doi.org/10.1002/9780470376454 7. Li, M., Ma, M., Zhu, K. X., Guo, X. N. & Zhou, H. M. (2017). Food Chemistry. Food Chemistry, 216, 374-381. https://doi.org/10.1016/j.foodchem.2016.08.059 8. Schaechter, M. (2009). Encyclopedia of Microbiology. (3rd ed.). Elsevier. https://doi.org/10.1016/B978-012373944-5.00122-X 9. 衛生福利部(2015)。104年1到10月抽驗米麵濕製品1,295件,不合格率3.4%。衛生福利部網站。https://www.mohw.gov.tw/cp-2649-20003-1.html 10. 衛生福利部(2016)。食品藥物管理署公布米麵濕製品製造業者稽查結果。衛生福利部網站。https://www.mohw.gov.tw/cp-2629-18916-1.html 11. 衛生福利部(2018)。食安源頭勤把關,米麵製品安心呷! 食藥署啟動「107年度米麵濕製品製造業稽查專案」。衛生福利部網站。https://www.mohw.gov.tw/cp-3793-40782-1.html 12. Lee, J. Y., KIM, B. Y. NA B. J. & HA S. D. (2011). Temperature dependent growth characteristics and a predictive mathematical model of Bacillus cereus in wet noodles. Journal of Food Safety, 31(1), 382-391. 13. Lloyd, S. P. (1957). Least squares quantization in PCM. Technical Report, 14. MacQueen, J. B. (1967). Some methods for classification and analysis of multivariate observations. In L. M. Le Cam & J. Neyman (Eds.), Proceedings of the fifth Berkeley symposium on mathematical statistics and probability. California: University of California Press, 1, 281-297. 15. Wu, J. (2012). Advances in K-means Clustering: A Data Mining Thinking. Springer. https://doi.org/10.1007/978-3-642-29807-3 16. 臺中市食品藥物安全處(2018)。中市食安處查驗量能逐年倍增 抽驗數六都第一。臺中市食品藥物安全處網站。https://www.fds.taichung.gov.tw/1222699/post 17. 臺中市政府衛生局(2020)。臺中市政府衛生局109年度施政計畫。臺中市政府衛生局網站。https://www.health.taichung.gov.tw/media/480393/%E8%87%BA %E4%B8%AD%E5%B8%82%E6%94%BF%E5%BA%9C%E8%A1%9B%E7%94%9F%E5%B1%80109%E5%B9%B4%E5%BA%A6%E6%96%BD%E6%94%BF%E8%A8%88%E7%95%AB.pdf | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/83305 | - |
dc.description.abstract | 背景:米、麵製品為國人主食,為提升臺灣米麵製品之監管效益,本研究透過對米麵製品檢驗不合格事件之分析及探討,瞭解影響食品抽驗不合格之主要風險因子,作為衛生機關規劃抽驗米麵製品之參考依據。
方法: 本研究以食品藥物管理署108年1月1日至110年12月31日期間,登錄於產品通路管理資訊系統之米麵製品抽驗資料進行探討,以文獻探討作為檢驗不合格事件發生之變項,再以k-means演算法進行分類,分類後使用廣義線性模式-隨機布瓦松回歸模型,評估不合格事件發生之相關危險因素。 結果:自108至110年,臺灣米麵製品檢驗總項次數共計37,496次,其中「防腐劑類」檢驗占比最高,檢驗27,819項次(74.2%)。此3年間米麵製品檢驗不合格項次數為218次(不合格率0.58%),其中「食品微生物類」檢驗不合格率最高,檢驗1,193項次,不合格118項次(不合格率9.89%),其次為「殺菌劑類」檢驗2,602項次,不合格13項次(不合格率0.5%),第三為「防腐劑類」檢驗27,819項次,不合格86項次(不合格率0.31%),第四為「非法定物質類」檢驗4,726項次,不合格1項次(不合格率0.02%),另「漂白劑類」及「真菌毒素類」無不合格情形。108年米麵製品檢驗不合格率0.68%、109年之不合格率0.53%、110年之不合格率0.52%。 6大類檢驗項目中以「防腐劑類」檢驗項次數最多,共27,819項次,不合格率0.31%,其中「己二烯酸」檢驗占比最多,「苯甲酸」不合格率最高。「食品微生物類」檢驗1,193項次,不合格率9.89%,其中以「大腸桿菌群」檢驗不合格率最高。米麵製品抽驗不合格率以「涼麵」最高,不合格率為6.9%。 臺中市、臺北市及宜蘭市為檢驗項次數最多之前三縣市,其合計之檢驗項次數約占總檢驗項次數之50%,該三縣市檢驗最多之類別皆為「防腐劑」,檢驗不合格率最高之類別皆為「食品微生物」。米麵製品抽驗不合格率以「苗栗縣」最高,不合格率1.55%,其中不合格率最高之檢驗類別為「防腐劑類」;其次為「新北市」檢驗不合格率1.42%,第三為「臺北市」檢驗不合格率1.41%,不合格率最高之檢驗類別皆為「食品微生物」。 抽檢月份之分析,米麵製品以「3月」檢驗項次數最多,占比14.01%,其中「防腐劑類」檢驗占比最高比76.03%,檢驗不合格率0.3%。該月份不合格率最高之檢驗類別為「殺菌劑」,不合格率為0.56%。其次為「7月」占比13.35%,其中「防腐劑類」檢驗占比最高占比75.44%,檢驗不合格率0.61%。該月份不合格率最高之檢驗類別為「食品微生物」,不合格率是10.24%。第三為「6月」占比12.77%,其中「防腐劑類」檢驗占比最高占比76.99%,檢驗不合格率0.11%,該月份不合格率最高之檢驗類別為「食品微生物」,不合格率11.58%。 「麵製品製造販賣業」、「生鮮超市」及「小吃店」依序為檢驗項次數最多之前三場所,其合計之檢驗項次數約占總檢驗項次數之48.97%,該三個場所檢驗最多之類別皆為「防腐劑」,檢驗不合格率最高之類別為「防腐劑」、「殺菌劑」及「食品微生物」。檢驗不合格率最高之前三場所,分別為「小吃店」、「宴席餐廳(20桌以上)」及「便利商店」。 以隨機布瓦松回歸模型分析,在控制變項-「抽驗場所」、「抽驗縣市」與「抽驗月份」後,「檢驗項目」及「產品類別」與檢驗不合格事件呈現統計有意義之相關性。「檢驗項目」中之「生物類檢驗項目」及「產品類別」中之「生麵」為影響抽驗不合格發生次數最重要之風險因子。 結論:臺灣米麵製品監測,以「食品微生物」檢驗中之「大腸桿菌群」不合格率最高,「大腸桿菌群」為衛生指標菌,常用來監測食品於製造過程中是否遭受污染或是否符合衛生要求的一種指標。為保障國人飲食安全衛生,建議衛生機關除加強於小吃店抽驗外,應積極輔導業者落實食品良好規範準則之規定。 | zh_TW |
dc.description.abstract | Background: Rice and flour products are the staple food of the citizens. In order to improve the regulatory effectiveness of rice and flour products in Taiwan, this study analyzed and discussed the unqualified incidents of rice and flour products to understand the major risk factors affecting food random inspections. It is used as the sampling basis for the planning of rice noodle products by health authorities.
Methods: This study is based on the sampling data of rice and flour products registered in the Product Management Distribution System of the Food and Drug Administration from January 1, 2019 to December 31, 2021. In the way of literature review, as a variable for the occurrence of unqualified events, and then the k-means algorithm was used to classify. After classification, the generalized linear model –random effect Poisson regression model was used to evaluate the risk factors associated with the occurrence of unqualified events. Results: From 2019 to 2021, the total number of inspections for Taiwanese rice and noodle products was 37,496. "Preservatives" had the highest proportion of inspections, with 27,819 inspections (74.2%). Over the three years, there were 218 instances of non-compliance (0.58% non-compliance rate) in rice and noodle product inspections. "Food Microorganisms" had the highest non-compliance rate, with 118 non-compliant instances out of 1,193 inspections (9.89% non-compliance rate). "Sanitizing Agents" had 13 non-compliant instances out of 2,602 inspections (0.5% non-compliance rate), "Preservatives" had 86 non-compliant instances out of 27,819 inspections (0.31% non-compliance rate), and "Illegal Substances" had 1 non-compliant instance out of 4,726 inspections (0.02% non-compliance rate). "Bleaching Agents" and "Mycotoxins" had no instances of non-compliance. The non-compliance rates for rice and noodle product inspections were 0.68% in 2019, 0.53% in 2020, and 0.52% in 2021. Of the six categories of inspection items, preservatives had the most inspections with 27,819 inspections and a non-compliance rate of 0.31%. "Sorbic Acid" had the highest percentage of inspections. "Benzoic Acid" had the highest non-compliance rate. "Food Microorganisms" inspections had 1,193 inspections with a non-compliance rate of 9.89%. Among these, " Coliform Bacteria" had the highest non-compliance rate. For rice and noodle products, "Cold Noodles" had the highest non-compliance rate, with a non-compliance rate of 6.9%. The variables under consideration, namely "Test Items", "Sampling Place", "Sampling counties and cities", "Sampling Month", and "Product Category", exhibit a positive correlation with the incidence of unqualified events. Specifically, of all the variables, "Biological Test Items" in the "Test Items" category and "Fresh Noodles" in the "Product Category" category emerge as the most critical risk factors associated with unqualified events. The top three counties with the highest number of inspection items were Taichung City, Taipei City, and Yilan City, which accounted for approximately 50% of the total inspection items. The most frequently inspected category in these three counties was "preservatives", while the category with the highest non-compliance rate was "Food Microorganisms". For rice and noodle products, Miaoli County had the highest non-compliance rate of 1.55%, with "preservatives" being the category with the highest non-compliance rate, followed by New Taipei City with a non-compliance rate of 1.42%. In New Taipei City, the category with the highest non-compliance rate was "Food Microorganisms". Taipei City had the third highest non-compliance rate of 1.41%, with the highest non-compliance rate in the "Food Microorganisms" category. The analysis of the inspection data showed that rice and noodle products had the highest number of inspections in March, accounting for 14.01% of the total number of inspections. The category "preservatives" had the highest proportion of inspections with a non-compliance rate of 0.3%, while the category "Sanitizing Agents" had the highest non-compliance rate of 0.56%. In July, "Preservatives" was the most frequently inspected category with 75.44% of the total inspections and a non-compliance rate of 0.61%. The "Food Microorganisms" category had the highest non-compliance rate of 10.24%. In June, the "Preservatives" category had the highest percentage of inspections at 76.99% with a non-compliance rate of 0.11%, while the "Food Microorganisms" category had the highest non-compliance rate at 11.58%. Noodle Manufacturing and Retail Shop, Fresh Markets and Snack Shops were the top three locations with the most inspections. The total number of inspections from these three locations accounted for approximately 48.97% of the total number of inspections. The most frequently inspected category for all three locations was "Preservatives", while the categories with the highest non-compliance rates were "Preservatives", "Sanitizing Agents", and "Food Microorganisms". In the random effect Poisson regression model, after adjusting for the random effect of the variables, "Sampling Location," "Sampling Counties and Cities," "Sampling Month," "Test Items," and "Product Category" were significantly associated with unqualified events. The "Biological Test Items" in the "Test Items" and the "Fresh Noodles" in the "Product Category" were the most important risk factors affecting the occurrence of unqualified events. Conclusion: The highest non-compliance rate of "Food Microorganisms" was found from the monitoring of Taiwanese rice noodle wet products. In order to ensure food safety and hygiene in Taiwan, it is important to strengthen inspections at snack food outlets, and it is necessary to actively guide operators to comply with The Regulations on Good Hygiene Practice for Food (GHP). | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-03-08T17:01:11Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2023-03-08T17:01:11Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | 口試委員會審定書 I
謝辭 II 中文摘要 III 英文摘要 V 目次 IX 表目錄 XI 圖目錄 XI 第一章 導論 1 第一節 實習單位簡介 1 第二節 研究動機與目的 3 第三節 相關文獻探討 4 第二章 方法 8 第一節 研究資料 8 第二節 研究假設及研究架構 8 第三節 分析方法 9 第四節 資料處理 11 第五節 名詞解釋 11 第三章 結果 13 第一節 臺灣108至110年米麵製品之監測結果 13 第二節 市售米麵製品抽驗不合格之風險因子 30 第四章 討論與結論 33 第一節 研究發現 33 第二節 結果比較 33 第三節 研究限制與建議 35 第四節 結論 35 參考文獻 36 附錄 38 附錄一、各縣市米麵製品之抽驗結果 38 附錄二、各月份米麵製品之抽驗結果 43 附錄三、各場所米麵濕製品之抽驗結果 46 附錄四、各產品類別之抽驗結果 52 | - |
dc.language.iso | zh_TW | - |
dc.title | 臺灣米麵製品監測資料分析 | zh_TW |
dc.title | Data Analysis of Monitoring Products Made by Rice and Flour in Taiwan | en |
dc.title.alternative | Data Analysis of Monitoring Products Made by Rice and Flour in Taiwan | - |
dc.type | Thesis | - |
dc.date.schoolyear | 111-1 | - |
dc.description.degree | 碩士 | - |
dc.contributor.coadvisor | 賴昭智;林金富 | zh_TW |
dc.contributor.coadvisor | Chao-Chih Lai;King-Fu Lin | en |
dc.contributor.oralexamcommittee | 嚴明芳 | zh_TW |
dc.contributor.oralexamcommittee | Ming-Fang Yen | en |
dc.subject.keyword | 米麵製品監測,米麵濕製品,風險因子分析,廣義線性模式分析, | zh_TW |
dc.subject.keyword | Rice noodle product monitoring,Rice noodle wet product,Risk Factor Analysis,Generalized Linear Mode Analysis, | en |
dc.relation.page | 54 | - |
dc.identifier.doi | 10.6342/NTU202300608 | - |
dc.rights.note | 未授權 | - |
dc.date.accepted | 2023-02-18 | - |
dc.contributor.author-college | 公共衛生學院 | - |
dc.contributor.author-dept | 公共衛生碩士學位學程 | - |
顯示於系所單位: | 公共衛生碩士學位學程 |
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