Development of an Application for Rice Cultivation:  Weather Forecasting System and Crop Variety Selection

Attapol Kunlerd; Boonlueo  Nabumroong; Kraisak  Jantarakomet; Ruttanachira  Ruttanaprasert; Kunlachat  Burana

doi:10.69650/ahstr.2025.3364

Authors

Attapol Kunlerd Department of Computer Technology, Faculty of Agriculture and Technology, Rajamangala University of Technology Isan Surin Campus 32000, Thailand https://orcid.org/0009-0007-2406-7030
Boonlueo Nabumroong Department of Computer Technology, Faculty of Agriculture and Technology, Rajamangala University of Technology Isan Surin Campus 32000, Thailand
Kraisak Jantarakomet Demonstration School of Khon Kaen University 40002, Thailand
Ruttanachira Ruttanaprasert Department of Plant Science Textile and Design, Faculty of Agriculture and Technology, Rajamangala University of Technology Isan Surin Campus 32000, Thailand
Kunlachat Burana Department of Agricultural Extension, Surin 32000, Thailand

DOI:

https://doi.org/10.69650/ahstr.2025.3364

Keywords:

Agricultural Mobile Application, Weather Forecasting, Crop Variety Selection, Farm Management Technology, Decision Support System

Abstract

The primary objective of this research was to develop a mobile application aimed at supporting rice production planning, specifically in the areas of weather forecasting and selecting suitable rice varieties for cultivation. Additionally, the study assessed technology acceptance using the Technology Acceptance Model (TAM), which is a key framework for evaluating consumers' attitudes towards new technologies. The research employed the Extreme Programming (XP) approach in software development to connect data through an Application Programming Interface (API), allowing for the collection of weather forecasts and agricultural information from government organizations. The sample group comprises 50 rice farmers from Mueang District, Surin Province, in the Lower Northeastern Region of Thailand, selected using a purposive sampling technique. Participants were required to have a basic understanding of technology and the ability to access information online. The research team systematically gathered data using questionnaires to explore and process descriptive statistics. The findings indicated that the developed application successfully provided relevant information for rice cultivation decision-making, including weather forecasts, expected rainfall, appropriate rice varieties for the production area, agricultural market information, and contact information of agricultural agencies. The evaluation of technology acceptance among the sample group showed high levels of satisfaction regarding usability, with a mean score of 4.07 (S.D. = 0.80), and perceived usefulness, with a mean score of 4.16 (S.D. = 0.63). The result indicated that the farmers’ technology acceptance was at a high level, which reflected the essential beginning of adaptation to a new form of data-driven agriculture for decision-making.

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