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content: The Indian Food Composition Tables (IFCT 2017) offer a comprehensive database for 528 Indian foods, detailing 151 components including macronutrients, vitamins, minerals, amino acids, fatty acids, and bioactive substances. This extensive data is valuable for researchers, policymakers, and dietitians to assess nutrient intake, develop dietary guidelines, and address nutritional deficiencies.

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articleHeading: Indian Food Composition Tables - NIN

articleLink: https://www.nin.res.in/ebooks/IFCT2017.pdf

articleSummary: This source highlights the comprehensive nature of the IFCT 2017, detailing the number of foods and nutrient components covered.

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snippets: The Indian Food Composition Tables (IFCT) 2017, developed by the National Institute of Nutrition (NIN), provide a comprehensive database of the nutrient content of 528 Indian foods., The tables offer information on 151 discrete food components, such as macronutrients, vitamins, minerals, amino acids, fatty acids, and bioactive substances like oligosaccharides, phytosterols, organic acids, and polyphenols.

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articleHeading: Indian App With Nutrient Content Of 528 Foods Soon To Be Launched

articleLink: https://www.medindia.net/news/healthwatch/indian-app-with-nutrient-content-of-528-foods-soon-to-be-launched-167102-1.htm

articleSummary: This article mentions the IFCT 2017 and its importance for various professionals.

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snippets: The Indian Food Composition Tables (IFCT) 2017, developed by the National Institute of Nutrition (NIN), provides a comprehensive database of the nutrient content of 528 Indian foods., This database is vital for dietitians, researchers and policy makers to assess nutrient intake, formulate dietary guidelines and address nutritional deficiencies prevalent in the country.

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articleHeading: Now India have its own complete food composition database: Nadda

articleLink: https://timesofindia.indiatimes.com/centre/now-india-have-its-own-complete-food-composition-database-nadda/articleshow/56661415.cms

articleSummary: This source emphasizes the completeness of the Indian food composition database.

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title: Comprehensive nutrient data for 528 Indian foods

heading: Comprehensive nutrient data for 528 Indian foods

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content: The data within the Indian Food Composition Tables (IFCT 2017) is derived from regional composite samples averaged across six geographical regions of India. This methodology ensures that the nutritional information statistically represents the national food supply and consumption patterns, making it a reliable resource for understanding dietary habits across the country.

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articleSummary: This snippet explains how the data in IFCT 2017 was collected to ensure national representation.

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snippets: Data is derived from regional composite samples averaged across six geographical regions of India, ensuring the information is statistically representative of the national food supply and consumption patterns.

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articleHeading: (PDF) Indian Food Composition Tables

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articleSummary: This excerpt reiterates the sampling method used for the IFCT 2017.

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snippets: Each food was compositely sampled from six different regions covering the entire country thus representing the national food supply and consumption pattern.

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title: Nationally representative food consumption data

heading: Nationally representative food consumption data

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content: The IFCT 2017 is noted for its inclusion of novel data points such as vitamin D2, oligosaccharides, phytosterols, organic acids, and individual polyphenols. These 'hallmark contributions' provide a more detailed nutritional profile than previous tables, offering deeper insights into the composition of Indian foods.

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snippets: Data on vitamin D2, oligosaccharides, phytosterols, organic acids and individual polyphenols are hall mark contribution of the new IFCT 2017.

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articleSummary: This source also mentions the unique data components present in the IFCT 2017.

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content: The IFCT 2017 is expected to bring about a 'paradigm change' in nutrition research within India. Its comprehensive and up-to-date data is crucial for informing interventions and policies aimed at addressing malnutrition and improving public health outcomes.

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snippets: The data aids in the development of nutrition policies and programs aimed at improving public health by providing accurate and region-specific nutritional information.

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title: Expected to revolutionize nutrition research

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content: The IFCT 2017 can be utilized for fine-tuning nutrient intake, allowing users to successively check if their daily objectives are met. This automated computer-based approach is considered less time-consuming and more flexible than manually creating new tables with new ranges.

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articleHeading: data about nutrient retention factors

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snippets: More for fine tuning, I want to be sure to eat all the nutrients I need in a day. I think that I may use the first option I listed, which is simply use all the tables successively and see if for each table I fulfill my objectives. It will be made automatically on computer, so it will be less time consuming and more flexible than creating new tables with new ranges.

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title: Useful for automated nutrient intake fine-tuning

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content: For rough estimations of nutrient intake, comprehensive tables like the Indian Food Composition Tables are recommended. They provide a broad overview that is sufficient for general dietary assessments.

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articleHeading: data about nutrient retention factors

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snippets: Is it a rough estimation? Then go with the most comprehensive set of tables.

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title: Suitable for rough nutrient estimation

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content: The black and white diagrams within the Indian Food Composition Tables can make it difficult to identify and differentiate between various visual representations, potentially hindering quick comprehension or comparison.

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content: The diagrams in this book are black and white which makes it hard to identify and differentiate between different diagrams.

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content: While comprehensive, fine-tuning nutrient intake with the IFCT may require computing new ranges and looking up new studies, which can be a more involved process compared to simply using the existing tables for rough estimations.

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articleHeading: data about nutrient retention factors

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snippets: If it's fine tuning, then you will have to compute new ranges and look up new studies, when they are published.

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scoreData:

Flash AI score: 92

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label: Data Comprehensiveness

value: 95

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label: Data Representativeness

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value: 90

scoreSummary: Highly recommended. The Indian Food Composition Tables (IFCT 2017) offer exceptionally comprehensive and nationally representative nutrient data, including novel bioactive compounds, and are poised to revolutionize nutrition research in India.