Food Security: Quality and Safety Drivers

Chandrasekar Vuppalapati
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Chandrasekar Vuppalapati: San Jose State University

Chapter Chapter 5 in Artificial Intelligence and Heuristics for Enhanced Food Security, 2022, pp 283-394 from Springer

Abstract: Abstract The chapter introduces food security quality and safety drivers. It introduces the components of dietary diversity and key indicators of dietary diversity and provides in-depth analysis on Household Dietary Diversity Score (HDDS) and Food Consumption Score (FCS). Next, the chapter introduces the food security and nutrition data framework. As part of the framework, it analyzes macroeconomic drivers and its impact on nutrition. Next, the chapter introduces National Surveys of Dietary Intake and Nutritional Status and develops machine learning regression models using HDDS on Venezuela data to predict who is most at risk of future hunger. Finally, the chapter concludes with machine learning models that leverage the National Health and Nutrition Examination Survey (NHANES) data to learn national health profile and food security among surveyed populations.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-031-08743-1_5

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DOI: 10.1007/978-3-031-08743-1_5

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