Development of a mobile computing framework to aid decision-making on organic fertilizer management using a crop model

Authors: HYUN, S - Seoul National University; YANG, S - Seoul National University; JUNHWAN, K - National Institute Of Crop Science - Korea; KIM, K - Seoul National University; SHIN, J - Rural Development Administration - Korea; LEE, S - National Institute Of Crop Science - Korea; LEE, B - Seoul National University; BERESFORD, R - New Zealand Institute For Crop & Food Research; Fleisher, David

Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/1/2020
Publication Date: 1/7/2021
Citation: Hyun, S., Yang, S.M., Junhwan, K., Kim, K.S., Shin, J.H., Lee, S.M., Lee, B.W., Beresford, R.M., Fleisher, D.H. 2021. Development of a mobile computing framework to aid decision-making on organic fertilizer management using a crop model. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2020.105936.
DOI: https://doi.org/10.1016/j.compag.2020.105936

Interpretive Summary: Crop production in many countries is consider intensive in terms of the amount of chemical fertilizers being used. These fertilizers have large economic and environmental costs associated with them, so growers are increasingly looking at less expensive and more environmentally friendly 'organic' fertilizers. These growers need accurate, portable, easy to use decision support tools that can identify how much of these organic fertilizers to use, and when to apply them, so as to optimize crop yield and resource use. A software program called the Organic-fertilizer Application Support Information System (OASIS) was developed as a smart phone application. This tool links an existing mathematical rice model with techniques to obtain field weather data behind an easy to use graphical interface. Research showed that OASIS was able to accurately predict rice yield and flowering dates across many growing areas in South Korea. Because OASIS can be easily modified to simulate other crops, such as corn and potato, this new tool can help other growers increase their use of organic fertilizers. The study benefits crop consultants, agricultural extension agents, and crop modelers interested in helping farmers grow their crops more sustainably.

Technical Abstract: Interest in organic farming has increased in large part due to environmental issues associated with intensive crop production systems. However, decision support for on-farm organic fertilizer management has been limited, which may be barrier for wide adoption of organic farming. A software development framework focused on a mobile computing platform, the Organic-fertilizer Application Support Information System (OASIS), was developed to address this problem. OASIS was designed to be compatible with the Android operating system. It was integrated with the ORYZA crop model and an improved soil nitrogen decomposition module to perform hindcast simulations of crop growth under organic management practices in different rice growing areas in South Korea. The performance of OASIS was tested using 16 different smartphones. It was found that on average, OASIS took less than five seconds to simulate crop growth even when installed on an outdated smartphone. However, downloading weather data associated with a given farm took an average 55 seconds before simulations could be executed. Observations from rice field experiments were used to evaluate OASIS predictions for rice growth under different organic fertilizer applications. Simulated hindcasts had relatively small differences as compared with observed values for heading date (one day or less) and yield (less than 10 percent error). These results suggest that OASIS would address general decision-making needs for rice farmers interested in adopting organic fertilizer management practices. Our framework can be modified for other crops and thus can serve as a template for the implementation of mobile applications to support decision-making on specific crop management practices.