Online Analytics for Shrimp Farm Management to Control Water Quality Parameters and Growth Performance

Siriwan Kajornkasirat, Jareeporn Ruangsri, Charuwan Sumat and Pete Intaramontri
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Siriwan Kajornkasirat: Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Surat Thani 84000, Thailand
Jareeporn Ruangsri: Department of Fishery and Coastal Resources, Faculty of Innovative Agriculture and Fishery, Prince of Songkla University, Surat Thani Campus, Surat Thani 84000, Thailand
Charuwan Sumat: Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Surat Thani 84000, Thailand
Pete Intaramontri: Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus, Surat Thani 84000, Thailand

Sustainability, 2021, vol. 13, issue 11, 1-11

Abstract: An online analytic service system was designed as a web and a mobile application for shrimp farmers and shrimp farm managers to manage the growth performance of shrimp. The MySQL database management system was used to manage the shrimp data. The Apache Web Server was used for contacting the shrimp database, and the web content displays were implemented with PHP script, JavaScript, and HTML5. Additionally, the program was linked with Google Charts to display data in various graphs, such as bar graphs and scatter diagrams, and Google Maps API was used to display water quality factors that are related to shrimp growth as spatial data. To test the system, field survey data from a shrimp farm in southern Thailand were used. Growth performance of shrimp and water quality data were collected from 13 earthen ponds in southern peninsular Thailand, located in the Surat Thani, Krabi, Phuket, and Satun provinces. The results show that the system allowed administrators to manage shrimp and farm data from the field sites. Both mobile and web applications were accessed by the users to manage the water quality factors and shrimp data. The system also provided the data analysis tool required to select a parameter from a list box and shows the association between water quality factors and shrimp data with a scatter diagram. Furthermore, the system generated a report of shrimp growth for the different farms with a line graph overlay on Google Maps™ in the data entry suite via mobile application. Online analytics for the growth performance of shrimp as provided by this system could be useful as decision support tools for effective shrimp farming.

Keywords: shrimp; water quality; web application; mobile application; google map (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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