Go Green Paddy App: A Mobile Application for Rice Cultivation

Abstract

This is crucial to the industry of agriculture that accurate performance projections are made during the growing season. The expected yields can be easily attained through the use of fertilizer on a consistent basis (using fertilizer in a smart way), as well as through the decrease of crop pests. This study's objective is to improve agricultural productivity by providing farmers with the technological tools necessary to do their jobs better. The discussion will focus on four crucial aspects that influence performance. The level of nitrogen in the soil should be evaluated so that a suitable amount of urea may be recommended. The process of forecasting future yield based on historical data collected from a particular area. A disease and four different kinds of agricultural pests were identified. The color of the leaf color indicator is used to calculate the quantity of nitrogen present in the plant. For the purpose of this screening, two grant parameters are considered. To measure this parameter, the colors palette API is used to confirm the color, and the decision tree method is used to confirm the age of the tree. This parameter is determined by the color of the leaves and the age of the tree. A pattern can be obtained that is more accurate than what can be seen with the naked eye, and this is something that is conceivable.

Country : Sri Lanka

1 W.V.M.G. Perera2 P.G.N.T. Vimalasooriya3 P.M.U.N. Purandara4 Uthpala Samarakoon5 Pasangi Rathnayake

  1. Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  2. Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  3. Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  4. Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  5. Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka

IRJIET, Volume 7, Issue 5, May 2023 pp. 202-208

doi.org/10.47001/IRJIET/2023.705024

References

  1. “(PDF) Android Based Mobile Application for Rice Crop Management.” https://www.researchgate.net/publication/358579699_Android_Based_Mobile_Application_for_Rice_Crop_Management (accessed Mar. 18, 2023).
  2. F. S. Saquee, S. Diakite, N. J. Kavhiza, E. Pakina, and M. Zargar, “The Efficacy of Micronutrient Fertilizers on the Yield Formulation and Quality of Wheat Grains,” Agron. 2023, Vol. 13, Page 566, vol. 13, no. 2, p. 566, Feb. 2023, doi: 10.3390/AGRONOMY13020566.
  3. C. J. D.Dewbre et al., The future of food and agriculture: trends and challenges, vol. 4, no. 4. 2014.
  4. E. W. Chu and J. R. Karr, “Environmental Impact: Concept, Consequences, Measurement,” Ref. Modul. Life Sci., 2017, doi: 10.1016/B978-0-12-809633-8.02380-3.
  5. G. Vinci, R. Ruggieri, M. Ruggeri, and S. A. Prencipe, “Rice Production Chain: Environmental and Social Impact Assessment—A Review,” Agric., vol. 13, no. 2, p. 340, Feb. 2023, doi: 10.3390/AGRICULTURE13020340/S1.
  6. P. Chivenge, S. Sharma, M. A. Bunquin, and J. Hellin, “Improving Nitrogen Use Efficiency—A Key for Sustainable Rice Production Systems,” Front. Sustain. Food Syst., vol. 5, p. 400, Nov. 2021, doi: 10.3389/FSUFS.2021.737412/BIBTEX.
  7. J. Liu and X. Wang, “Plant diseases and pests detection based on deep learning: a review,” Plant Methods, vol. 17, no. 1, pp. 1–18, Dec. 2021, doi: 10.1186/S13007-021-00722-9/TABLES/4.
  8. A.Hollaus, C. Schunko, R. Weisshaidinger, P. Bala, and C. R. Vogl, “Indigenous farmers’ perceptions of problems in the rice field agroecosystems in the upper Baram, Malaysia,” J. Ethnobiol. Ethnomed., vol. 18, no. 1, pp. 1–25, Dec. 2022, doi: 10.1186/S13002-022-00511-1/FIGURES/7.
  9. T. Tsuboi, “Rice Diseases & Insects,” Jica, 2012.
  10. “(PDF) Android Based Mobile Application for Rice Crop Management.” https://www.researchgate.net/publication/358579699_Android_Based_Mobile_Application_for_Rice_Crop_Management (accessed Mar. 18, 2023).
  11. N. Cha-un et al., “SMART GHG Mobile Application: A New Agricultural App for Tracking GHG Emissions and Low-Carbon Rice Production in Thailand’s Local Communities,” 78, 2022, doi: 10.3390/iocag2022-12259.
  12. Q. YUE et al., “Rotation with green manure increased rice yield and soil carbon in paddies from Yangtze River valley, China,” Pedosphere, Nov. 2022, doi: 10.1016/J.PEDSPH.2022.11.009.
  13. Y. Zhang, G. Liu, Y. Cheng, J. Xu, C. Wang, and J. Yang, “The effects of dry cultivation on grain-filling and chalky grains of upland rice and paddy rice,” Food Energy Secur., vol. 9, no. 2, May 2020, doi: 10.1002/FES3.198.
  14. “Field Abandonment Problem in Rice Paddy Fields | Request PDF.” https://www.researchgate.net/publication/366880332_Field_Abandonment_Problem_in_Rice_Paddy_Fields (accessed Mar. 18, 2023).
  15. N. Athirah Roslin, N. Norasma Che, R. Rosle, and M. Razi Ismail, “SCIENCE & TECHNOLOGY Smartphone Application Development for Rice Field Management Through Aerial Imagery and Normalised Difference Vegetation Index (NDVI) Analysis,” Pertanika J. Sci. Technol, vol. 29, no. 2, pp. 809–836, 2021, doi: 10.47836/pjst.29.2.07.
  16. “ICAR-NRRI developed Mobile app ‘riceXpert’ – National Rice Research Institute.” https://icar-nrri.in/icar-nrri-developed-mobile-app-ricexpert/ (accessed Mar. 18, 2023).
  17. Z. Matos, D. Sugot, M. Aljas, J. Baguio, C. Abapo, and M. V. Mangao, “E-FARMING: A GUIDE FOR SUSTAINABLE ORGANIC RICE CULTIVATION MOBILE APPLICATION.” Sci. Asia Rev., vol. 2, Oct. 2019, Accessed: Mar. 18, 2023. [Online]. Available: https://zchrd.herdin.ph/index.php/herdin-home?view=research&cid=75228.