Open Access
Issue
SHS Web Conf.
Volume 95, 2021
The 3rd International Conference on Resources Economics and Bioeconomy in Competitive Societies (RebCos’20) under the title Environmental Challenges, Innovative Technologies and Rural Areas in Digital Era
Article Number 01015
Number of page(s) 6
DOI https://doi.org/10.1051/shsconf/20219501015
Published online 03 February 2021
  1. A. A. Sawant, N. J. Thakor, S. B. Swami, A. D. Divate, and B. S. K. K. Vidyapeeth, “Physical and sensory characteristics of Ready-To-Eat food prepared from finger millet based composite mixer by extrusion,” Agric. Eng. Int. CIGR J., 2013. [Google Scholar]
  2. S. Balasubramanian, D. N. Yadav, J. Kaur, and T. Anand, “Development and shelf-Life evaluation of pearl millet based upma dry mix,” J. Food Sci. Technol., 2014, doi: 10.1007/s13197-012-0616-0. [Google Scholar]
  3. S. Shobana et al., “Development and evaluation of nutritional, sensory and glycemic properties of finger millet (Eleusine coracana L.) based food products,” Asia Pac. J. Clin. Nutr., 2018, doi: 10.6133/apjcn.032017.18. [Google Scholar]
  4. S. E. Kemp, T. Hollowood, and J. Hort, Sensory evaluation: A practical handbook. 2013. [Google Scholar]
  5. S. B. Solanke, R. V. Jaybhaye, and S. B. Jadhav, “Sensory Evaluation of Pearl Millet based Snack Food (Kharodi) using Fuzzy Logic,” Int. J. Curr. Microbiol. Appl. Sci., 2018, doi: 10.20546/ijcmas.2018.704.244. [Google Scholar]
  6. S. Vanishree, M. R. Kammar, and U. Nidoni, “Development and Evaluation of Pearl Millet Based Novel Health Drink,” Indian J. Nutr. Diet., 2016, doi: 10.21048/ijnd.2016.53.4.8404. [Google Scholar]
  7. S. Gaur, “Iron Bioavailability, Storability and Sensory Evaluation of Iron Fortified Extruded Snacks Intended to Alleviate Iron Deficiency in Indian Children,” Int. J. Nutr. Food Sci., 2015, doi: 10.11648/j.ijnfs.20150401.16. [Google Scholar]
  8. T. M. Aande, I. G. Agbidye, and C. A. Adah, “Formulation, Proximate Analysis and Sensory Evaluation of Mumu from Pearl Millet, Irish Potato and Sesame Seed Blend,” Agric. Sci., 2020, doi: 10.4236/as.2020.113015. [Google Scholar]
  9. Priya S S and Kowsalya S, “Formulation and evaluation and convenience food mixes from malted millets,” Int. J. Sci. Res., 2015, doi: https://www.theglobaljournals.com/ijsr/articles.php? [Google Scholar]
  10. A. Mehra and U. Singh, “Development, Organoleptic And Nutritional Evaluation Of Pearl Millet Based Mathri,” Int. J. Eng. Technol. Sci. Res., 2017. [Google Scholar]
  11. E. P. Köster, “Diversity in the determinants of food choice: A psychological perspective,” Food Qual. Prefer., 2009, doi: 10.1016/j.foodqual.2007.11.002. [Google Scholar]
  12. B. Dhillon, N. S. Sodhi, S. Gandotra, S. Kaur, and S. Jaiswal, “Physico-chemical and textural (sensorial and electromyographic) evaluation of idlis formulated with brown rice and pearl millet flours,” J. Food Meas. Charact., 2020, doi: 10.1007/s11694-020-00534-w. [Google Scholar]
  13. N. Kaushik, A. R. Gondi, R. Rana, and P. Srinivasa Rao, “Application of fuzzy logic technique for sensory evaluation of high pressure processed mango pulp and litchi juice and its comparison to thermal treatment,” Innov. Food Sci. Emerg. Technol., 2015, doi: 10.1016/j.ifset.2015.08.007. [Google Scholar]
  14. K. J. Shinde and I. L. Pardeshi, “Fuzzy Logic Model for Sensory Evaluation of Commercially Available Jam,” J. Ready to eat food, 2014. [Google Scholar]
  15. C. Ayca and K. Hasan, “An application of fuzzy analytic hierarchy process (FAHP) for evaluating students project,” Educ. Res. Rev., 2017, doi: 10.5897/err2016.3065. [Google Scholar]
  16. Y. Chen, X. Zeng, M. Happiette, P. Bruniaux, R. Ng, and W. Yu, “Optimisation of garment design using fuzzy logic and sensory evaluation techniques,” Eng. Appl. Artif. Intell., 2009, doi: 10.1016/j.engappai.2008.05.007. [Google Scholar]
  17. N. Perrot, I. Ioannou, I. Allais, C. Curt, J. Hossenlopp, and G. Trystram, “Fuzzy concepts applied to food product quality control: A review,” Fuzzy Sets Syst., 2006, doi: 10.1016/j.fss.2005.12.013. [Google Scholar]
  18. X. Wang, D. Li, and X. Shi, “A fuzzy model for aggregative food safety risk assessment in food supply chains,” Prod. Plan. Control, 2012, doi: 10.1080/09537287.2011.561812. [Google Scholar]
  19. C. J. Du and D. W. Sun, “Recent developments in the applications of image processing techniques for food quality evaluation,” Trends Food Sci. Technol., 2004, doi: 10.1016/j.tifs.2003.10.006. [Google Scholar]
  20. Y. P. Tsang, K. L. Choy, C. H. Wu, G. T. S. Ho, and H. Y. Lam, “Blockchain-Driven IoT for Food Traceability with an Integrated Consensus Mechanism,” IEEE Access, 2019, doi: 10.1109/ACCESS.2019.2940227. [Google Scholar]
  21. S. Khan, M. I. Khan, A. Haleem, and A. R. Jami, “Prioritising the risks in Halal food supply chain: an MCDM approach,” J. Islam. Mark., 2019, doi: 10.1108/JIMA-10-2018-0206. [Google Scholar]
  22. G. Egilmez, S. Gumus, M. Kucukvar, and O. Tatari, “A fuzzy data envelopment analysis framework for dealing with uncertainty impacts of input-output life cycle assessment models on eco-efficiency assessment,” J. Clean. Prod., 2016, doi: 10.1016/j.jclepro.2016.03.111. [Google Scholar]
  23. P. Morone, P. M. Falcone, and A. Lopolito, “How to promote a new and sustainable food consumption model: A fuzzy cognitive map study,” J. Clean. Prod., 2019, doi: 10.1016/j.jclepro.2018.10.075. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.