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Manikanta, V.
- Regional Food Diversity of Traditional Indian Cuisines-A Perspective based on the Database of Indian Cuisines
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Authors
Affiliations
1 Department of Human Resource Development, CSIR-CFTRl, Mysore 570020, IN
2 Department of Planning Monitoring and Coordination, CSIR-CFTRI, Mysore- 570020, IN
1 Department of Human Resource Development, CSIR-CFTRl, Mysore 570020, IN
2 Department of Planning Monitoring and Coordination, CSIR-CFTRI, Mysore- 570020, IN
Source
Information Studies, Vol 18, No 3 (2012), Pagination: 177-188Abstract
Indian traditional foods are non-spatially mapped to different states and regions of the country. The mapping of region-wise cuisines on major food ingredient groups was carried out. Analysis was made towards exploring the dominant shared cuisines based on selected major ingredients in the intra- - regional states. The study shows the diverse nature of the origin or existence of cuisine traditions in the country.Keywords
Traditional Foods, Shared Cuisines, Food Diversity.References
- Srinivasan K. (2010). Traditional Indian functional foods. In: Functional foods of the East/. Edited by John Shi et al.: CRC Press.
- Larissa S.; Dresher, Silic Thiele; Gert B. M.; and Mensink (2007). A new index to measure healthy food diversity better reflects a healthy diet than traditional measures. J. Nutrition, 137; p. 647-651.
- krahn, Juta (2005). Upland food security and nutritional diversity. In; Improving the livelihoods in the uplands of Lao PDR/ Edited by : Nafri,Nafes and Nudol, p. 107-112.
- Naska A.; Fouskakis D.; Oikonomou E.; Almeida M.D.V.; Berg M.A. et al. Dietary patterns and their socio-demographic determinants in 10 European countries: data from DAFNE databank. European J. Clinical Nutrition, 60; p. 181-190.
- Maria Jose Soto-Mendez B.S.; Raquel Campos B.S.; Liza Hernandez B.S.; Monica Orozco; and Marieke Vossenaar (2011). Food vaiety, dietary diversity, and food characteristics among convenience samples of Guatemalan women. Salud publico de niexico, 53(4); p. 288-298.. http://www.foodvision.gov.uk (last accessed on 20 Nov. 2011
- Manikanta V.; Kumara S.S.; Harsha P.; and Manilal P. (2012). Mapping of shared traditional foods in Southern states using Geographical Information System (GIS) & MATLAB, International Conference on Food Web - A Global Connect, Chennai, India, 17-18th Feb.
- Parpia H.A.B., (2004). Multi-cultural heritage of traditional Indian foods. Indian Food Industry, 23(3): May-June, p. 10-14.
- Arjun Appadurai. (1998). How to make a national cuisine: Cookbooks in contemporary India. Comparative studies in Society and History, 30(1); p. 3-24
- Classification and Regression Tree-Based Analysis for Forecasting and Mapping of Funding Pattern
Abstract Views :148 |
PDF Views:0
Authors
Affiliations
1 Department of Human Resource Development, Central Food Technological Research Institute (CSIR), Mysore- 20, IN
2 Department of Planning Monitoring and Coordination, Central Food Technological Research Institute (CSIR), Mysore- 20, IN
1 Department of Human Resource Development, Central Food Technological Research Institute (CSIR), Mysore- 20, IN
2 Department of Planning Monitoring and Coordination, Central Food Technological Research Institute (CSIR), Mysore- 20, IN
Source
Information Studies, Vol 17, No 1 (2011), Pagination: 39-46Abstract
In public research and development institutions, project proposals are submitted by research groups to various government funded bodies for external financial support. The pattern of funding of various research groups was analyzed using classification and regression tree (C&RT) technique. The study was aimed at exploring and forging an effective networking with funding agencies to supplement the ongoing research programmes of the Institute.Keywords
Research, Funding, Classification and Regression Tree, Data Mining, Funding Agencies.References
- Qijia Tian: Jian Ma; Cleve J. Liang, Ron C.W. Kwok, Ou Liu. Quan Zhang (2002). An Organizational decision .support approach to R&D project selection, In.' Proceedings of the 35th Hawaii International Conference on System Sciences, 2002.
- Ravichandra Rao, I..K. (2003). Data mining and clustering techniques, DRTC Workshop on Semantic Web. 8-10 December.
- Clementine II Manual. (2005). SPSS Inc., Chicago, p. 313-325
- StatSoft Electronic Statistics Textbook. http://www.statsoft.com/TEXTBOOK/stcart.html, (accessed on 3 Feb 2010)
- Massimo, Bertolini, (2006). Oil pipeline spill cause analysis: A classification tree approach, J. Quality Maint. Eng. 12(2); p. 186-198
- Thamaraiselvi, G; Kaliammal, A. (2004). Data mining : Concepts and techniques, SRELS J. Information Management. 41(4); p. 339-348
- Manying Qiu (2007). Selecting classification and clustering tools for academic support. Issues in Information System. 8(2); p. 265-272
- http://themeasurementgroup.com/definitions/cart.htm, (accessed on 27 Aug 2009)
- Wen-Shuan Tseng; Hang Nguyen; Leibowitz, Jay; Agresti, William. (2005). Distractions and motor vehicle accidents: Data mining application on fatality analysis reporting system (PARS) data files, Industrial Management and Data Systems. 105(9); p. 1188-1205