{"id":30138287,"url":"https://github.com/nodef/ifct2017","last_synced_at":"2025-10-14T20:12:21.030Z","repository":{"id":32511391,"uuid":"134217841","full_name":"nodef/ifct2017","owner":"nodef","description":"Detailed nutritional values for 542 key foods in India, based on direct measurements across six regions.","archived":false,"fork":false,"pushed_at":"2025-06-24T05:16:00.000Z","size":2461,"stargazers_count":43,"open_issues_count":0,"forks_count":26,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-09-30T15:50:05.387Z","etag":null,"topics":["2017","acids","amino","carbohydrates","composition","compositions","fats","food","ifct","indian","institute","minerals","national","nutrition","proteins","research","tables","vitamins"],"latest_commit_sha":null,"homepage":"https://jsr.io/@nodef/ifct2017","language":"TypeScript","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"agpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/nodef.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2018-05-21T04:28:22.000Z","updated_at":"2025-09-13T11:49:43.000Z","dependencies_parsed_at":"2024-06-19T05:27:25.107Z","dependency_job_id":"c66e9131-4896-4cb3-bfdc-b9008f67b8e8","html_url":"https://github.com/nodef/ifct2017","commit_stats":{"total_commits":73,"total_committers":2,"mean_commits":36.5,"dds":0.04109589041095896,"last_synced_commit":"2e082d22bbed3007018de820c476833b81975030"},"previous_names":["nodef/ifct2017","ifct2017/compositions","ifct2017/ifct2017"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/nodef/ifct2017","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nodef%2Fifct2017","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nodef%2Fifct2017/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nodef%2Fifct2017/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nodef%2Fifct2017/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nodef","download_url":"https://codeload.github.com/nodef/ifct2017/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nodef%2Fifct2017/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279021008,"owners_count":26086946,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-14T02:00:06.444Z","response_time":60,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["2017","acids","amino","carbohydrates","composition","compositions","fats","food","ifct","indian","institute","minerals","national","nutrition","proteins","research","tables","vitamins"],"created_at":"2025-08-11T01:06:00.058Z","updated_at":"2025-10-14T20:12:20.966Z","avatar_url":"https://github.com/nodef.png","language":"TypeScript","readme":"\u003c!-- Copyright (C) 2025 Subhajit Sahu --\u003e\n\u003c!-- SPDX-License-Identifier: AGPL-3.0-or-later --\u003e\n\u003c!-- See LICENSE for full terms --\u003e\n\nThis package provides detailed nutritional values for 542 key foods in India, based on direct measurements across six regions. Data was obtained from the book [Indian Food Composition Tables 2017], published by the [National Institute of Nutrition, Hyderabad].\n\n▌\n📦 [JSR](https://jsr.io/@nodef/ifct2017),\n📰 [Docs](https://jsr.io/@nodef/ifct2017/doc),\n🌐 [Website](https://ifct2017.github.io).\n\n\u003cbr\u003e\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n\n\nawait ifct2017.loadCompositions();\nawait ifct2017.loadColumns();\nawait ifct2017.loadIntakes();\n// Load corpus first\n\nifct2017.compositions('pineapple');\nifct2017.compositions('ananas comosus');\n// → [ { code: 'E053',\n// →     name: 'Pineapple',\n// →     scie: 'Ananas comosus',\n// →     lang: 'A. Ahnaros; B. Anarasa; G. Anenas; H. Ananas; Kan. Ananas; Kash. Punchitipul; Kh. Soh trun; Kon. Anas; Mal. Kayirha chakka; M. Kihom Ananas; O. Sapuri; P. Ananas; Tam. Annasi pazham; Tel. Anasa pandu; U. Ananas.',\n// →     ... } ]\n\nifct2017.columns('vitamin c');\nifct2017.columns('c-vitamin');\n// → [ { code: 'vitc',\n// →     name: 'Total Ascorbic acid',\n// →     tags: 'ascorbate water soluble vitamin c vitamin c essential' } ]\n\nifct2017.pictures.unpkg('A001');\n// → https://unpkg.com/@ifct2017/pictures/assets/A001.jpeg\n\nifct2017.intakes('his');\nifct2017.intakes('Histidine');\n// → [ { code: 'his',\n// →     whorda: -0.01,\n// →     usear: NaN,\n// →     usrdam: -0.014,\n// →     usrdaf: NaN,\n// →     euprim: NaN,\n// →     euprif: NaN,\n// →     ulus: NaN,\n// →     uleu: NaN,\n// →     uljapan: NaN } ]\n// Negative value indicates amount per kg of body weight.\n```\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n### Reference\n\n| Method                  | Action\n|-------------------------|-------\n| [compositions]          | Detailed nutrient composition of 542 key foods in India.\n| [columns]               | Codes and names of nutrients, and its components.\n| [pictures]              | Single representative photo of each foods (JPEG, 307x173).\n| [yieldFactors]          | Yield factors for conversion of raw to edible portion.\n| [intakes]               | Recommended daily intakes of nutrients.\n| [hierarchy]             | Tree-like hierarchy of nutrients, and its components.\n| [representations]       | Representations of columns (as factors and units).\n| [codes]                 | Uniquely identifiable codes for each food.\n| [groups]                | Categorization of food by their common names.\n| [descriptions]          | Names of each food in local languages, including scientific name.\n| [abbreviations]         | Full forms of abbreviations used in the original book.\n| [languages]             | Full form of language abbreviations.\n| [methods]               | Analytical methods of nutrient and bioactive components.\n| [energies]              | Metabolizable energy conversion factors.\n| [nutrients]             | Detailed description of various nutrients, and its components.\n| [jonesFactors]          | Jones factors for conversion of nitrogen to protein.\n| [carbohydrates]         | Conversion of carbohydrate weights to monosaccharide equivalents.\n| [regions]               | Categorization of the States/UTs into six different regions.\n| [samplingUnits]         | Number of primary sampling units in each State/UT.\n| [compositingCentres]    | Regional compositing centres and sample size of each region.\n| [frequencyDistribution] | Frequency distribution of States/UTs for fixing the number of districts to be sampled.\n| [about]                 | On the history of malnutrition, current status, and data details.\n| [contents]              | Contents in the original book.\n\n\u003e NOTE: `.pictures(code) -\u003e null` as it is not included locally.\u003cbr\u003e\n\u003e Use `.pictures.unpkg(code)`, or `.pictures.jsDelivr(code)` instead.\n\n[Indian Food Composition Tables 2017]: http://ifct2017.com/\n[National Institute of Nutrition, Hyderabad]: https://www.nin.res.in/\n[abbreviations]: https://jsr.io/@nodef/ifct2017/doc/~/abbreviations\n[about]: https://jsr.io/@nodef/ifct2017/doc/~/about\n[carbohydrates]: https://jsr.io/@nodef/ifct2017/doc/~/carbohydrates\n[codes]: https://jsr.io/@nodef/ifct2017/doc/~/codes\n[columns]: https://jsr.io/@nodef/ifct2017/doc/~/columns\n[compositingCentres]: https://jsr.io/@nodef/ifct2017/doc/~/compositingcentres\n[compositions]: https://jsr.io/@nodef/ifct2017/doc/~/compositions\n[contents]: https://jsr.io/@nodef/ifct2017/doc/~/contents\n[descriptions]: https://jsr.io/@nodef/ifct2017/doc/~/descriptions\n[energies]: https://jsr.io/@nodef/ifct2017/doc/~/energies\n[frequencyDistribution]: https://jsr.io/@nodef/ifct2017/doc/~/frequencydistribution\n[groups]: https://jsr.io/@nodef/ifct2017/doc/~/groups\n[hierarchy]: https://jsr.io/@nodef/ifct2017/doc/~/hierarchy\n[intakes]: https://jsr.io/@nodef/ifct2017/doc/~/intakes\n[jonesFactors]: https://jsr.io/@nodef/ifct2017/doc/~/jonesfactors\n[languages]: https://jsr.io/@nodef/ifct2017/doc/~/languages\n[methods]: https://jsr.io/@nodef/ifct2017/doc/~/methods\n[nutrients]: https://jsr.io/@nodef/ifct2017/doc/~/nutrients\n[pictures]: https://jsr.io/@nodef/ifct2017/doc/~/pictures\n[regions]: https://jsr.io/@nodef/ifct2017/doc/~/regions\n[representations]: https://jsr.io/@nodef/ifct2017/doc/~/representations\n[samplingUnits]: https://jsr.io/@nodef/ifct2017/doc/~/samplingunits\n[yieldFactors]: https://jsr.io/@nodef/ifct2017/doc/~/yieldfactors\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Abbreviations\n\nFull forms of *abbreviations* used in the original book.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadAbbreviations() → corpus\n// ifct2017.abbreviationsSql([table], [options]) → SQL statements\n// ifct2017.abbreviationsCsv() → Path of CSV file\n// ifct2017.abbreviations(query)\n// → {abbr, full} if found, null otherwise.\n\n\nawait ifct2017.loadAbbreviations();\n// Load corpus first\n\nifct2017.abbreviations('GLV');\nifct2017.abbreviations('g l v');\n// → { abbr: 'GLV', full: 'Green Leafy Vegetables' }\n\nifct2017.abbreviations('what is D.R.I.');\nifct2017.abbreviations('d. r. i. stands for?');\n// → { abbr: 'DRI', full: 'Dietary reference intake' }\n\n\n// Note:\n// Full stops must immediately follow character, if present.\n// For single character abbreviations, full stop is mandatory.\n```\n\n[abbreviations-csv]: https://github.com/ifct2017/abbreviations/blob/master/index.csv\n[abbreviations-doc]: https://docs.google.com/spreadsheets/d/1ZTzOOj827HhsUWhdISh1lOJsOh-dvh3ORbAPs9XHI1Q/edit?usp=sharing\n[abbreviations-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vSPLlUvSc4OuO8cHl7kBntXJvolVWxklwZrbyNX0YfOaMMQpAi6iwf47If6wE1UyCTiBHUcx-UwLdb9/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## About\n\nOn the history of malnutrition, current status, and data details.\n\n\u003e Supported *topics* include: 1937, 1951, 1963, 1971, 1989, 2017, challenge,\n\u003e column, credit, data, father, form, funder, group, interest, learn, limitation,\n\u003e publisher, source, supporter, use, user, what, when, why.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadAbout() → corpus\n// ifct2017.about(query)\n// → text if matched, null otherwise\n\n\nawait ifct2017.loadAbout();\n// Load corpus first\n\nifct2017.about('who is you publisher');\nifct2017.about('which organization issued you');\n// → Indian Food Composition Tables 2017 was published by:\n// → T. Longvah, R. Ananthan, K. Bhaskarachary and K. Venkaiah\n// → National Institute of Nutrition\n// → Indian Council of Medical Research\n// → Department of Health Research\n// → Ministry of Health and Family Welfare, Government of India\n// → Jamai Osmania (PO), Hyderabad – 500 007\n// → Telangana, India\n// → Phone: +91 40 27197334, Fax: +91 40 27000339, Email: nin@ap.nic.in\n\nifct2017.about('can i know the food groups');\nifct2017.about('i want to know what types of food are there');\n// → There are 20 food groups:\n// → - A: Cereals and Millets. 24 foods.\n// → - B: Grain Legumes. 25 foods.\n// → - C: Green Leafy Vegetables. 34 foods.\n// → - D: Other Vegetables. 78 foods.\n// → - E: Fruits. 68 foods.\n// → - F: Roots and Tubers. 19 foods.\n// → - G: Condiments and Spices. 33 foods.\n// → - H: Nuts and Oil Seeds. 21 foods.\n// → - I: Sugars. 2 foods.\n// → - J: Mushrooms. 4 foods.\n// → - K: Miscellaneous Foods. 2 foods.\n// → - L: Milk and Milk Products. 4 foods.\n// → - M: Egg and Egg Products. 15 foods.\n// → - N: Poultry. 19 foods.\n// → - O: Animal Meat. 63 foods.\n// → - P: Marine Fish. 92 foods.\n// → - Q; Marine Shellfish. 8 foods.\n// → - R: Marine Mollusks. 7 foods.\n// → - S: Fresh Water Fish and Shellfish. 10 foods.\n// → - T: Edible Oils and Fats. 9 foods.\n\nifct2017.about('what happened in 1951');\nifct2017.about('what was the situation in nineteen fifty');\n// → Between 1938 and 1951, there was a notable transition in the Indian nutrition\n// → scenario. Among tropical regions, India contributed substantially in the field\n// → of nutrition (Nicholls, 1945). The incidence of pellagra was noticed and the\n// → role of niacin in its cure was successfully demonstrated in India (Raman, 1940;\n// → Aykroyd \u0026 Swaminathan, 1940). The agricultural practices in India also underwent\n// → modifications with concomitant increase in the crop yields. However, the basic\n// → diet of individuals remained inadequate, devoid of animal fats and proteins,\n// → due to poor economic conditions (Day, 1944). The translation of nutrition research\n// → into sustained public health was hindered by obstacles of weak economy, ignorance\n// → and poverty (Aykroyd, 1941). Other deficiency diseases such as maternal anaemia,\n// → infant beriberi and osteomalacia continued to be rampant. Sustained nutritional\n// → issues prompted the revision of Indian FCT resulting in the publication of fourth\n// → edition of the Health Bulletin No. 23 by Aykroyd, Patwardhan, and Ranganathan (1951).\n\n\n// Note:\n// Can convert textual number to number.\n// 1950-1959 is considered for 1951 event.\n```\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Carbohydrates\n\nConversion of carbohydrate weights to monosaccharide equivalents.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadCarbohydrates() → corpus\n// ifct2017.carbohydratesSql([table], [options]) → SQL statements\n// ifct2017.carbohydratesCsv() → path of CSV file\n// ifct2017.carbohydrates(query)\n// → matches [{sno, carbohydrate, hydrolysis, monosaccharide}]\n\n\nawait ifct2017.loadCarbohydrates();\n// Load corpus first\n\nifct2017.carbohydrates('monosaccharide');\nifct2017.carbohydrates('Glucose');\n// → [ { sno: '1',\n// →     carbohydrate: 'Monosaccharides e.g. glucose',\n// →     hydrolysis: 100,\n// →     monosaccharide: 1 } ]\n\nifct2017.carbohydrates('what is carbohydrate conversion factor of disaccharides?');\nifct2017.carbohydrates('maltose conversion factor');\n// → [ { sno: '2',\n// →     carbohydrate: 'Disaccharides e.g. sucrose, lactose, maltose',\n// →     hydrolysis: 105,\n// →     monosaccharide: 1.05 } ]\n```\n\n[carbohydrates-doc]: https://docs.google.com/spreadsheets/d/1YoEVoQFR0co_bTHL3Xok1dQfuqxXZa7yQrlUKbYVve4/edit?usp=sharing\n[carbohydrates-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vQ4Ogyx4J5JWX3HQnHhoGt9HsmqNIZ5MFvDvHa2gkYSZg6vxtWeqPrzkyvh1_bmaXDgrsElNgAu1YKk/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Codes\n\nUniquely identifiable *codes* for each food.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadCodes() → corpus\n// ifct2017.codesSql([table], [options]) → SQL statements\n// ifct2017.codesCsv() → path of CSV file\n// ifct2017.codes(query)\n// → matches [{name, code}]\n\n\nawait ifct2017.loadCodes();\n// Load corpus first\n\nifct2017.codes('mango green');\nifct2017.codes('Raw mango');\n// → [ { name: 'Mango, green, raw (Common)', code: 'D057' } ]\n\nifct2017.codes('what is food code of atta?');\nifct2017.codes('atta code');\n// → [ { name: 'Atta (H., P.)', code: 'A019' },\n// →   { name: 'Gahama atta (O.)', code: 'A019' },\n// →   { name: 'Wheat flour, atta (Common)', code: 'A019' } ]\n```\n\n[codes-doc]: https://docs.google.com/spreadsheets/d/1Q-M1C3DAEhoA6y7X89M3Fl_zml__v0Mr-fJAYBJkLJc/edit?usp=sharing\n[codes-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vSZD-_xy9EvbEM2axafTL251gWsCPUYRZA8wAUvscy0MZmHS9bCOpbvqJQsbf5TujlOA8FmL91bOzF8/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Columns\n\n*Codes and names* of nutrients, and its components.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadColumns() → corpus\n// ifct2017.columnsSql([table], [options]) → SQL statements\n// ifct2017.columnsCsv() → path of CSV file\n// ifct2017.columns(query)\n// → matches [{code, name, tags}]\n\n\nifct2017.columns('vitamin c');\nifct2017.columns('c-vitamin');\n// → [ { code: 'vitc',\n// →     name: 'Ascorbic acids (C)',\n// →     tags: 'total ascorbate water soluble vitamin c vitamin c essential' } ]\n\nifct2017.columns('what is butyric acid?');\nifct2017.columns('c4:0 stands for?');\n// → [ { code: 'f4d0',\n// →     name: 'Butyric acid (C4:0)',\n// →     tags: 'c40 c 40 4 0 bta butanoic propanecarboxylic carboxylic saturated fatty fat triglyceride lipid colorless liquid unpleasant vomit body odor' } ]\n```\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Compositing centres\n\nRegional *compositing centres* and sample size of each region.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadCompositingCentres() → corpus\n// ifct2017.compositingCentresSql([table], [options]) → SQL statements\n// ifct2017.compositingCentresCsv() → path of CSV file\n// ifct2017.compositingCentres(query)\n// → matches [{region, centre, samples}]\n\n\nawait ifct2017.loadCompositingCentres();\n// Load corpus first\n\nifct2017.compositingCentres('west');\nifct2017.compositingCentres('Mumbai');\n// → [ { region: 'West', centre: 'Mumbai', samples: 12 } ]\n\nifct2017.compositingCentres('what is compositing centre of north east?');\nifct2017.compositingCentres('North East compositing centre');\n// → [ { region: 'North East', centre: 'Guwahati', samples: 11 } ]\n```\n\n[compositingcentres-doc]: https://docs.google.com/spreadsheets/d/1r9J5mC-Dus9YA1AMSE_8-cEsXJ-8eKm6tKZMz0m5xPw/edit?usp=sharing\n[compositingcentres-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vQQj5wg7oGpgHZSlmrysbeS7MB92bgyPPVYrM7e2JpP2dC2Csts9pVc_Dcf0iVcCbtXSaWKbvQr0Yib/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Compositions\n\nDetailed *nutrient composition* of 542 key foods in India.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadCompositions() → corpus\n// ifct2017.compositionsSql([table], [options]) → SQL statements\n// ifct2017.compositionsCsv() → path of CSV file\n// ifct2017.compositions(query)\n// → matches [{code, name, scie, lang, grup, regn, tags, ...}]\n\n\nawait ifct2017.loadCompositions();\n// Load corpus first\n\nifct2017.compositions('pineapple');\nifct2017.compositions('ananas comosus');\n// → [ { code: 'E053',\n// →     name: 'Pineapple',\n// →     scie: 'Ananas comosus',\n// →     lang: 'A. Ahnaros; B. Anarasa; G. Anenas; H. Ananas; Kan. Ananas; Kash. Punchitipul; Kh. Soh trun; Kon. Anas; Mal. Kayirha chakka; M. Kihom Ananas; O. Sapuri; P. Ananas; Tam. Annasi pazham; Tel. Anasa pandu; U. Ananas.',\n// →     ... } ]\n\nifct2017.compositions('tell me about cow milk.');\nifct2017.compositions('gai ka doodh details.');\n// → [ { code: 'L002',\n// →     name: 'Milk, Cow',\n// →     scie: '',\n// →     lang: 'A. Garoor gakhir; B. Doodh (garu); G. Gai nu dhudh; H. Gai ka doodh; Kan. Hasuvina halu; Kash. Doodh; Kh. Dud masi; M. San Sanghom; Mar. Doodh (gay); O. Gai dudha; P. Gaan da doodh; S. Gow kshiram; Tam. Pasumpaal; Tel. Aavu paalu.',\n// →     ... } ]\n```\n\n[compositions-doc]: https://docs.google.com/spreadsheets/d/19C2EB4PIMgyusqKOnBq4-aBQxLjCai1Zg45YcBNTzFo/edit?usp=sharing\n[compositions-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vRAWAh3wLrPjDfeZ2pmApbwnvJ11CxdWaPiJ4BPClyN9X1wbbCjvfyqYpBy-LoIBltsH7MKjtNATtAh/pubhtml\n[compositions-tabdoc]: https://docs.google.com/spreadsheets/d/1ejgqo6uwlKRF3QLUPJJzrTkd47GtVXgHHsgG-T27uGc/edit?usp=sharing\n[compositions-tabweb]: https://docs.google.com/spreadsheets/d/e/2PACX-1vTNaOhfRaF_DxH5yh4QtW2D3iJSM4MRIKB-P_cFRlHGhEzWo5NP5ADmAzrpXH2fsjmzJEOMbmaBFMgq/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Contents\n\n*Contents* in the original book.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadContents() → corpus\n// ifct2017.contentsSql([table], [options]) → SQL statements\n// ifct2017.contentsCsv() → path of CSV file\n// ifct2017.contents(query)\n// → matches [{sno, title, pagenos}]\n\n\nawait ifct2017.loadContents();\n// Load corpus first\n\nifct2017.contents('table 2');\nifct2017.contents('Water soluble vitamins');\n// → [ { sno: '6.2.',\n// →     title: 'Table 2:  Water Soluble Vitamins',\n// →     pagenos: '31' } ]\n\nifct2017.contents('what is page number of table 3?');\nifct2017.contents('fat soluble vitamin page number');\n// → [ { sno: '6.3.',\n// →     title: 'Table 3:  Fat Soluble Vitamins',\n// →     pagenos: '61' } ]\n```\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Descriptions\n\n*Names* of each food in local languages, including scientific name.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadDescriptions() → corpus\n// ifct2017.descriptionsSql([table], [options]) → SQL statements\n// ifct2017.descriptionsCsv() → path of CSV file\n// ifct2017.descriptions(query)\n// → matches [{code, name, scie, desc}]\n\n\nawait ifct2017.loadDescriptions();\n// Load corpus first\n\nifct2017.descriptions('pineapple');\nifct2017.descriptions('ananas comosus');\n// → [ { code: 'E053',\n// →     name: 'Pineapple',\n// →     scie: 'Ananas comosus',\n// →     grup: 'Fruits',\n// →     desc: 'A. Ahnaros; B. Anarasa; G. Anenas; H. Ananas; Kan. Ananas; Kash. Punchitipul; Kh. Soh trun; Kon. Anas; Mal. Kayirha chakka; M. Kihom Ananas; O. Sapuri; P. Ananas; Tam. Annasi pazham; Tel. Anasa pandu; U. Ananas.' } ]\n\nifct2017.descriptions('tell me about cow milk.');\nifct2017.descriptions('gai ka doodh details.');\n// → [ { code: 'L002',\n// →     name: 'Milk, Cow',\n// →     scie: '',\n// →     grup: 'Milk and Milk Products',\n// →     desc: 'A. Garoor gakhir; B. Doodh (garu); G. Gai nu dhudh; H. Gai ka doodh; Kan. Hasuvina halu; Kash. Doodh; Kh. Dud masi; M. San Sanghom; Mar. Doodh (gay); O. Gai dudha; P. Gaan da doodh; S. Gow kshiram; Tam. Pasumpaal; Tel. Aavu paalu.' } ]\n```\n\n[descriptions-doc]: https://docs.google.com/spreadsheets/d/1dRKW2HJyWxDJliONe_URNxM0gPBmgZKqoF5lBotxOT8/edit?usp=sharing\n[descriptions-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vSueRUdwru4BNvmLCK16cM8DYO3mum4c-g_8MILZvg6TsT3vaZChWOwN5cUS58GtrXMKqZHeHy0ajeG/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Energies\n\nMetabolizable *energy conversion factors*.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadEnergies() → corpus\n// ifct2017.energiesSql([table], [options]) → SQL statements\n// ifct2017.energiesCsv() → path of CSV file\n// ifct2017.energies(query)\n// → matches [{component, kj, kcal}]\n\n\nawait ifct2017.loadEnergies();\n// Load corpus first\n\nifct2017.energies('dietary fibre');\nifct2017.energies('Soluble fibre');\n// → [ { component: 'Fibre', kj: 8, kcal: 2 } ]\n\nifct2017.energies('what is energy conversion factor of fat?');\nifct2017.energies('conversion factor of fat');\n// → [ { component: 'Fat', kj: 37, kcal: 9 } ]\n```\n\n[energies-doc]: https://docs.google.com/spreadsheets/d/1Go_O1rv7gwDw9GFx5S9-eBOOEueyrSnqf2KmQmB5ZEw/edit?usp=sharing\n[energies-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vRbNMeTawz-rXs53C9NTcMkJVnLCzJ79kxbOahFhq49Q7qDFMApQ5fcFvUoTGs6nDyHshtwcIzXMLiM/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Frequency distribution\n\n*Frequency distribution* of States/UTs for fixing the number of districts to be sampled.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadFrequencyDistribution() → corpus\n// ifct2017.frequencyDistributionSql([table], [options]) → SQL statements\n// ifct2017.frequencyDistributionCsv() → path of CSV file\n// ifct2017.frequencyDistribution(districts)\n// → {districts, states, selected, sampled} if found, null otherwise\n\n\nawait ifct2017.loadFrequencyDistribution();\n// Load corpus first\n\nifct2017.frequencyDistribution(2);\nifct2017.frequencyDistribution(5);\n// → { districts: '1-5', states: 9, selected: 1, sampled: 9 }\n\nifct2017.frequencyDistribution(32);\nifct2017.frequencyDistribution(37);\n// → { districts: '31-40', states: 4, selected: 5, sampled: 20 }\n```\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Groups\n\n*Categorization* of food by their common names.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadGroups() → corpus\n// ifct2017.groupsSql([table], [options]) → SQL statements\n// ifct2017.groupsCsv() → path of CSV file\n// ifct2017.groups(query)\n// → matches [{code, group, entries, tags}]\n\n\nawait ifct2017.loadGroups();\n// Load corpus first\n\nifct2017.groups('cereals');\nifct2017.groups('Millet');\n// → [ { code: 'A',\n// →     group: 'Cereals and Millets',\n// →     entries: 24,\n// →     tags: 'vegetarian eggetarian fishetarian veg' } ]\n\nifct2017.groups('what is vegetable?');\nifct2017.groups('vegetable group code?');\n// → [ { code: 'D',\n// →     group: 'Other Vegetables',\n// →     entries: 78,\n// →     tags: 'vegetarian eggetarian fishetarian veg' },\n// →   { code: 'C',\n// →     group: 'Green Leafy Vegetables',\n// →     entries: 34,\n// →     tags: 'vegetarian eggetarian fishetarian veg' } ]\n```\n\n[groups-doc]: https://docs.google.com/spreadsheets/d/1PMR0TZLLYsS70lcC0Bap4oNrI1azgmuGx9ekfHJB_0Q/edit?usp=sharing\n[groups-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vSsXdKiSvWypa6aJlCfl_eKIzAOfESO_wHITJtPik3K1goIy81hciSjmTCqFjmFv1cqrLdnYhg1Q3O1/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Hierarchy\n\nTree-like *hierarchy* of nutrients, and its components.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadHierarchy() → corpus\n// ifct2017.hierarchySql([table], [options]) → SQL statements\n// ifct2017.hierarchyCsv() → path of CSV file\n// ifct2017.hierarchy(query)\n// → {parents, ancestry, children} if found, null otherwise\n\n\nawait ifct2017.loadHierarchy();\n// Load corpus first\n\nifct2017.hierarchy('soluble oxalic acid');\nifct2017.hierarchy('Soluble Oxalic Acid');\n// → { parents: 'oxalt', ancestry: 'oxalt orgac', children: '' }\n\nifct2017.hierarchy('what is ifct2017.hierarchy of total saturated fat?');\nifct2017.hierarchy('who are children of total saturated fat?');\n// → { parents: 'fatce',\n// →   ancestry: 'fatce',\n// →   children:\n// →    'f4d0 f6d0 f8d0 f10d0 f11d0 f12d0 f14d0 f15d0 f16d0 f18d0 f20d0 f22d0 f24d0' }\n```\n\n[hierarchy-doc]: https://docs.google.com/spreadsheets/d/174DDCwdVRZ0RQT8zfGFSciQltA2sIHIIRXkWiejU_JQ/edit?usp=sharing\n[hierarchy-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vR1C-FJ2driNzJ_rRVmftv_wYPo4Rz4SJKGEo-pFNccvbF3nsAFj2zmbiGHDGlX4YnozoqMydg0xBwZ/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Intakes\n\n*Recommended daily intakes* of nutrients.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadIntakes() → corpus\n// ifct2017.intakesSql([table], [options]) → SQL statements\n// ifct2017.intakesCsv() → path of CSV file\n// ifct2017.intakes(query)\n// → matches [{code, whorda, usear, usrdam, usrdaf, euprim, euprif, ulus, uleu, uljapan}]\n\n\nawait ifct2017.loadIntakes();\n// Load corpus first\n\nifct2017.intakes('his');\nifct2017.intakes('Histidine');\n// → [{ code: 'his',\n// →    whorda: -0.01,\n// →    usear: NaN,\n// →    usrdam: -0.014,\n// →    usrdaf: NaN,\n// →    euprim: NaN,\n// →    euprif: NaN,\n// →    ulus: NaN,\n// →    uleu: NaN,\n// →    uljapan: NaN }]\n\nifct2017.intakes('intake of total fibre?');\nifct2017.intakes('what is rda of total fiber?');\n// → [{ code: 'fibtg',\n// →    whorda: NaN,\n// →    usear: NaN,\n// →    usrdam: 38,\n// →    usrdaf: 25,\n// →    euprim: NaN,\n// →    euprif: NaN,\n// →    ulus: NaN,\n// →    uleu: NaN,\n// →    uljapan: NaN }]\n\n\n// Note:\n// +ve value indicates amount in grams.\n// -ve value indicates amount in grams per kg of body weight.\n// NaN indicates no recommentation given.\n\n// Note:\n// whorda: WHO Recommended Dietary Allowance\n// usear:  US Estimated Average Requirement\n// usrdam: US Recommended Dietary Allowance (Male)\n// usrdaf: US Recommended Dietary Allowance (Female)\n// euprim: EU Population Reference Intake (Male)\n// euprif: EU Population Reference Intake (Female)\n// ulus: Tolerable intake Upper Level (US)\n// uleu: Tolerable intake Upper Level (EU)\n// uljapan: Tolerable intake Upper Level (Japan)\n```\n\n[intakes-doc]: https://docs.google.com/spreadsheets/d/14rD34GjeJ6jx9-RXLa7zu4m_896CojCP4qSTPKeWLEU/edit?usp=sharing\n[intakes-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vShOB5MaBlnccsBXPGT1KbG3442fF7ZPChdJCm7Ez3C9ejVF6503gMY28dOOdBJRDpCLL9o0BfJO8Nj/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Jones factors\n\n*Jones factors* for conversion of nitrogen to protein.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadJonesFactors() → corpus\n// ifct2017.jonesFactorsSql([table], [options]) → SQL statements\n// ifct2017.jonesFactorsCsv() → path of CSV file\n// ifct2017.jonesFactors(query)\n// → matches [{food, factor}]\n\n\nawait ifct2017.loadJonesFactors();\n// Load corpus first\n\nifct2017.jonesFactors('maida');\nifct2017.jonesFactors('Refined wheat');\n// → [ { food: 'Refined wheat flour (Maida)', factor: '5.70' } ]\n\nifct2017.jonesFactors('what is jones factor of barley?');\nifct2017.jonesFactors('jones factor of oats');\n// → [ { food: 'Barley and its flour;Rye and its flour;Oats',\n// →     factor: '5.83' } ]\n```\n\n[jonesfactors-doc]: https://docs.google.com/spreadsheets/d/1OqV-MSaXH1ARXlyuyayyfj9NXoH1DvW5-n1oxOX4n0o/edit?usp=sharing\n[jonesfactors-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vSfqNhcPoEpx9TbXLhlyLFYpN-JtKM0J6YtZN7He6Ad4fNoVGcNI3ILaW7PJkgsoTg7-XJqr39HRQe1/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Languages\n\nFull form of *language abbreviations*.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadLanguages() → corpus\n// ifct2017.languagesSql([table], [options]) → SQL statements\n// ifct2017.languagesCsv() → path of CSV file\n// ifct2017.languages(query)\n// → {abbr, lang} if found, null otherwise.\n\n\nawait ifct2017.loadLanguages();\n// Load corpus first\n\nifct2017.languages('mal.');\nifct2017.languages('Mal');\n// → { abbr: 'Mal.', lang: 'Malayalam' }\n\nifct2017.languages('what is s.?');\nifct2017.languages('S. stands for?');\n// → { abbr: 'S.', lang: 'Sanskrit' }\n\n\n// Note:\n// Full stops must immediately follow character, if present.\n// For single character abbreviations, full stop is mandatory.\n```\n\n[languages-doc]: https://docs.google.com/spreadsheets/d/1NrdVtCYtmxooVtdGj9UQOPR7l4HIJc9qeI7BNoytGhI/edit?usp=sharing\n[languages-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vTrDSLb2ABbFM8v7QVXqVR0QV7ha58ZJS3Kw6RmtgcwaN6GjNv_hfEZ3K-NqACpT9sIyv7oFysY6z_p/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Methods\n\n*Analytical methods* of nutrient and bioactive components.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadMethods() → corpus\n// ifct2017.methodsSql([table], [options]) → SQL statements\n// ifct2017.methodsCsv() → path of CSV file\n// ifct2017.methods(query)\n// → {analyte, method, reference} if found, null otherwise\n\n\nawait ifct2017.loadMethods();\n// Load corpus first\n\nifct2017.methods('soluble oxalic acid');\nifct2017.methods('Insoluble Oxalic Acid');\n// → { analyte: 'Oxalic acid (Total), Soluble oxalic acid, Insoluble oxalic acid',\n// →   method: 'Fast- HPLC',\n// →   reference: 'Moreau \u0026 Savage (2009)' }\n\nifct2017.methods('what is analytical method of saponin?');\nifct2017.methods('how is total saponin measured?');\n// → { analyte: 'Total Saponin',\n// →   method: 'Colorimetry',\n// →   reference: 'Dini et al. (2009)' }\n```\n\n[methods-doc]: https://docs.google.com/spreadsheets/d/11nJ7RfjgcTUz1bPmI7EWWOZSAxvwvXseG4AFqtLU3-o/edit?usp=sharing\n[methods-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vShqmhmDcwBNV1Qz-uAed412gfPQBHbO0--NkS7EwuEWjNI3trjMy0Widnqx8eM05B9a-PQLssOzLcj/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n\u003c!-- ## Nutrients\n\nDetailed description of various *nutrients*, and its components.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadNutrients() // → corpus\n// ifct2017.nutrients(query)\n// → nutrient description if found, null otherwise\n\n\nawait ifct2017.loadNutrients();\n// Load corpus first\n\nifct2017.nutrients('his');\nifct2017.nutrients('Histidine');\n// → Amino acid profile of each food is determined by three different analyses.\n// → Tryptophan is determined by alkaline hydrolysis, methionine and cystine by\n// → performic oxidation and the rest of the amino acids by acid hydrolysis. The\n// → amino acid profile of each food is expressed as g/100 g protein.\n\nifct2017.nutrients('what is soluble oxalate?');\nifct2017.nutrients('are organic acids useful?');\n// → Organic acids is naturally present in a wide variety of foods especially fruits,\n// → berries and vegetables. Organic acids cis-aconitic acid, citric acid, fumaric\n// → acid, mallic acid, quinic acid, succinic acid and tartaric acid were determined\n// → in single liquid chromatographic run. Soluble, insoluble and total oxalates were\n// → determined separately by HPLC method. The organic acids are energy contributing\n// → components, although it varies between the different organic acids. According to\n// → the Codex Alimentarius Commission’s Guidelines for Nutrition Labeling, the energy\n// → conversion factor for organic acids is 13 kJ/g. However, organic acids have not\n// → been included in the total energy of foods given in the IFCT.\n```\n\n\u003cbr\u003e\n\u003cbr\u003e --\u003e\n\n\n## Pictures\n\nSingle representative *photo* of each foods (JPEG, 307x173).\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.picturesUnpkg(code) → UNPKG URL | null\n// ifct2017.picturesJsDelivr(code) → jsDelivr URL | null\n// ifct2017.pictures(code)\n// → path is present, null otherwise\n\n\nifct2017.pictures('A001');\n// C:\\Documents\\pictures\\A001.jpeg\n\nifct2017.picturesUnpkg('A001');\n// https://unpkg.com/@ifct2017/pictures/assets/A001.jpeg\n\nifct2017.picturesJsDelivr('A001');\n// https://cdn.jsdelivr.net/npm/@ifct2017/pictures/assets/A001.jpeg\n```\n\n[pictures-doc]: https://docs.google.com/document/d/1UVWVh-wPOR80M2sTy5naIJvR5DUNtf7lbOaPgCNQ9t4/edit?usp=sharing\n[pictures-web]: https://docs.google.com/document/d/e/2PACX-1vSyo24GtsTF0wuhKUndF6w5KZa1gZU7kDyDun-6-QZvsO-Hy7Zn2chxxyYa3gSp5kzy-4AQrfHqF0N0/pub\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Regions\n\nCategorization of the States/UTs into six different regions.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadRegions() → corpus\n// ifct2017.regionsSql([table], [options]) → SQL statements\n// ifct2017.regionsCsv() → path of CSV file\n// ifct2017.regions(query)\n// → matches [{region, states}]\n\n\nawait ifct2017.loadRegions();\n// Load corpus first\n\nifct2017.regions('central');\nifct2017.regions('Uttaranchal');\n// → [ { region: 'Central',\n// →     states: 'Chhattisgarh;Madhya Pradesh;Uttar Pradesh;Uttaranchal' } ]\n\nifct2017.regions('which region andhra pradesh belongs to?');\nifct2017.regions('details of south region');\n// → [ { region: 'South',\n// →     states: 'Andaman \u0026 Nicobar Islands;Andhra Pradesh;Karnataka;Kerala;Lakshadweep;Pondicherry;Telangana;Tamil Nadu' } ]\n```\n\n[regions-doc]: https://docs.google.com/spreadsheets/d/1a01-O3cex87z9My2hF3ByoUMVMLZtMYKuRFGTbmcIzQ/edit?usp=sharing\n[regions-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vRXTC_URrQPaVbgG0tyMvJGkuaZgTjaQ9UZivesdtVBgpJXWHQldR9ps8C04HVDcZmEuKjCX2LhjUNA/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Representations\n\n*Representations* of columns (as factors and units).\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadRepresentations() → corpus\n// ifct2017.representationsSql([table], [options]) → sql statements\n// ifct2017.representationsCsv() → path of csv file\n// ifct2017.representations(query)\n// → {type, factor, unit} if found, null otherwise\n\n\nawait ifct2017.loadRepresentations();\n// Load corpus first\n\nifct2017.representations('his');\nifct2017.representations('Histidine');\n// → { type: 'mass', factor: 1000, unit: 'mg' }\n\nifct2017.representations('representation of vitamin d?');\nifct2017.representations('what is unit of ergocalciferol?');\n// → { type: 'mass', factor: 1000000000, unit: 'ng' }\n\n\n// Note:\n// type:   Type of physical quantity\n// factor: Multiplication factor\n// unit:   Unit symbol\n```\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Sampling units\n\nNumber of primary *sampling units* in each State/UT.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadSamplingUnits() → corpus\n// ifct2017.samplingUnitsSql([table], [options]) → SQL staments\n// ifct2017.samplingUnitsCsv() → path of CSV file\n// ifct2017.samplingUnits(query)\n// → matches [{sno, state, districts, selected}]\n\n\nawait ifct2017.loadSamplingUnits();\n// Load corpus first\n\nifct2017.samplingUnits('andaman');\nifct2017.samplingUnits('Nicobar');\n// → [ { sno: 'A',\n// →     state: 'Andaman \u0026 Nicobar',\n// →     districts: 3,\n// →     selected: 1 } ]\n\nifct2017.samplingUnits('sampling units in orissa?');\nifct2017.samplingUnits('orissa\\'s sampling units');\n// → [ { sno: '20', state: 'Orissa', districts: 30, selected: 4 } ]\n```\n\n[samplingunits-doc]: https://docs.google.com/spreadsheets/d/1Wm6eqy0TRwUItBHrU-OU4jVBRuYm162y2viZlP8JyuM/edit?usp=sharing\n[samplingunits-web]: https://docs.google.com/spreadsheets/d/e/2PACX-1vTL7Qe0f_MEe_6JtxiiROTb-mVewlGjrYlj2u3jPaRkz7mOgUjwOpsrTIPYUSAaKXD781_dCewAIiE9/pubhtml\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Yield Factors\n\n*Yield factors* for conversion of raw food to edible portion.\n\n\u003cbr\u003e\n\n```javascript\nimport * as ifct2017 from \"jsr:@nodef/ifct2017\";\n// ifct2017.loadYieldFactors() → corpus\n// ifct2017.yieldFactorsSql([table], [options]) → SQL staments\n// ifct2017.yieldFactorsCsv() → path of CSV file\n// ifct2017.yieldFactors(query)\n// → matches [{code, name, scie, yield, preparation}]\n\n\nawait ifct2017.loadYieldFactors();\n// Load corpus first\n\n\n\nifct2017.yieldFactors('mango');\nifct2017.yieldFactors('Mangifera indica');\n// → [ { code: 'D057',\n// →     name: 'Mango, green, raw',\n// →     scie: 'Mangifera indica',\n// →     lang: 'A. Keasa aam; B. Aam (kancha); G. Ambo; H. Katcha Aam; Kan. Mavinakayi; Kash. Kach Aamb; Kh. Soh pieng im; Mal. Manga; M. Heinou Ashangba; Mar. Amba; O. Ambu (kacha); P. Kaccha aam; Tam. Mangai; Tel. Mamidikaya; U. Kaccha aam.',\n// →     grup: 'Other Vegetables',\n// →     regn: 6,\n// →     tags: 'vegetarian eggetarian fishetarian veg',\n// →     yield: 0.6833333333,\n// →     preparation: 'Washing, Peeling, Seed removal' } ]\n\nifct2017.yieldFactors('yield factor of cow milk?');\nifct2017.yieldFactors('gai ka doodh');\n// → [ { code: 'L002',\n// →     name: 'Milk, Cow',\n// →     scie: '',\n// →     lang: 'A. Garoor gakhir; B. Doodh (garu); G. Gai nu dhudh; H. Gai ka doodh; Kan. Hasuvina halu; Kash. Doodh; Kh. Dud masi; M. San Sanghom; Mar. Doodh (gay); O. Gai dudha; P. Gaan da doodh; S. Gow kshiram; Tam. Pasumpaal; Tel. Aavu paalu.',\n// →     grup: 'Milk and Milk Products',\n// →     regn: 6,\n// →     tags: 'vegetarian eggetarian fishetarian veg',\n// →     yield: 1,\n// →     preparation: 'None' } ]\n```\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## License\n\nAs of 18 April 2025, this project is licensed under AGPL-3.0. Previous versions remain under MIT.\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n[![](https://raw.githubusercontent.com/qb40/designs/gh-pages/0/image/11.png)](https://wolfram77.github.io)\u003cbr\u003e\n[![ORG](https://img.shields.io/badge/org-nodef-green?logo=Org)](https://nodef.github.io)\n![](https://ga-beacon.deno.dev/G-RC63DPBH3P:SH3Eq-NoQ9mwgYeHWxu7cw/github.com/nodef/ifct2017)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnodef%2Fifct2017","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnodef%2Fifct2017","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnodef%2Fifct2017/lists"}