Skip to main navigation menu Skip to main content Skip to site footer

Research Articles

Vol. 10 No. 2 (2023)

Indigenous knowledge in traditional production of rice: Impact on food security in the upland households in Ifugao, Philippines

DOI
https://doi.org/10.14719/pst.1864
Submitted
28 April 2022
Published
15-01-2023 — Updated on 01-04-2023
Versions

Abstract

Indigenous knowledge is essential to the survival of highland farming across the world. In the Philippines, the Ifugao indigenous people have a long history of rice farming which is intertwined with their indigenous knowledge and cultural identity, particularly the Ifugao Rice Terraces (IRT). Their traditional practices of rice production entails the use of indigenous knowledge. The investigation included a number of conventional processes, ranging from land preparation through harvesting and even the planting season. It is clear that Ifugaos continue to grow native rice in the region in the customary manner. It is noteworthy because Ifugao is having food security challenges, thus 82 percent of people believe that there is a high risk of food insecurity, and 70.20 percent believe that rice output is insufficient based on yearly rice production. 51.2 percent felt that even though there is food insecurity, they would not go hungry.

References

  1. UNEP 2008 ANNUAL REPORT [Internet]. 2009 [cited 2021 Jun 9]. Available from: https://wedocs.unep.org/handle/20.500.11822/7742?show=full
  2. Ananayo Z. Tinawon: Ifugao Traditional Rice Production. Nurturing Indigenous Knowledge Experts. Nurtur Indig Knowl Expert. 2012;
  3. Koohafkan P. Conservation and Adaptive Management of Globally Important Agricultural Heritage Systems (GIAHS?. Resour Sci. 2009;31(1):4–9.
  4. Glover D, Stone GD. Heirloom rice in Ifugao: an ‘anti-commodity’ in the process of commodification. J Peasant Stud [Internet]. 2018;45(4):776–804. Available from: http://dx.doi.org/10.1080/03066150.2017.1284062
  5. Marasigan SB, Serrano J V. Indigenous Farming Families of Ifugao: Partners in Safeguarding the Sustainable Use of Natural Resources. IAMURE Int J Ecol Conserv. 2014;10(1).
  6. Dulawan M. Oral Literature of the Tuwali Ifugao in Kiangan [Internet]. 1982. Available from: https://ncca.gov.ph/about-ncca-3/subcommissions/subcommission-on-cultural-communities-and-traditional-arts-sccta/northern-cultural-communities/oral-literature-of-the-tuwali-ifugao-in-kiangan/
  7. Alon AS, Venal MCA, Militante S V., Hernandez MD, Acla HB. Lyco-frequency: A development of lycopersicon esculentum fruit classification for tomato catsup production using frequency sensing effect. Int J Adv Trends Comput Sci Eng. 2020;9(4):4690–5. https://doi.org/10.30534/ijatcse/2020/72942020
  8. Ponge A. Integrating Indigenous Knowledge for Food Security?: Perspectives from the Millennium Village Project at Bar-Sauri in Nyanza Province in Kenya . nternational Conf Enhancing Food Secur East Horn Africa Reg A Conf held Imp R Hotel Kampala, Uganda 16 – 17 Novemb 2011. 2013;43.
  9. Shepherd A. Sustainable rural development. New York City: St. Martin’s Press; 1998. 269–284 p.
  10. Dennis M. Warren, Leendert Jan Slikkerveer SOT. Indigenous Knowledge Systems: Implications for Agriculture and International Development. Washington: Technology and Social Change Program, Iowa State University; 1989. 186 p.
  11. Camacho LD, Gevaña DT, Carandang AP, Camacho SC. Indigenous knowledge and practices for the sustainable management of Ifugao forests in Cordillera, Philippines. Int J Biodivers Sci Ecosyst Serv Manag [Internet]. 2016;12(1–2):5–13. Available from: http://dx.doi.org/10.1080/21513732.2015.1124453
  12. Melgar-Quinonez, Hugo R., Zubieta, Ana C., MkNelly, Barbara, Nteziyaremye, Anastase, Gerardo, Maria Filipinas D., Dunford, Christopher, Household Food Insecurity and Food Expenditure in Bolivia, Burkina Faso, and the Philippines, The Journal of Nutrition, Volume 136, Issue 5, May 2006, Pages 1431S–1437S, https://doi.org/10.1093/jn/136.5.1431S
  13. Hernandez MD, Fajardo AC, Medina RP. A Hybrid Convolutional Neural Network-Gradient Boosted Classifier for Vehicle Classification. IJRTE J [Internet]. 2019;(2):213–6. Available from: https://www.ijrte.org/wp-content/uploads/papers/v8i2/B1016078219.pdf
  14. Hernandez MD, Fajardo AC, Medina RP, Hernandez JT, Dellosa RM. Implementation of data augmentation in convolutional neural network and gradient boosted classifier for vehicle classification. Int J Sci Technol Res [Internet]. 2019;8(12):185–9. Available from: http://www.ijstr.org/final-print/dec2019/Implementation-Of-Data-Augmentation-In-Convolutional-Neural-Network-And-Gradient-Boosted-Classifier-For-Vehicle-Classification.pdf

Downloads

Download data is not yet available.