Smartphone application development for rice field management through aerial imagery and normalised difference vegetation index (NDVI) analysis

Nor Athirah Roslin, . and Nik Norasma Che’Ya, . and Rhushalshafira Rosle, . and Mohd Razi Ismail, . Smartphone application development for rice field management through aerial imagery and normalised difference vegetation index (NDVI) analysis. pp. 809-836. ISSN 2231-8526

In the current practices farmers typically rely on the traditional method paper-based for farming data records which leads to human error. However the paper-based system can be improved by the mobile app technology to ease the farmers acquiring farm data as all of the farm information will be stored in digital form. This study aimed to develop a smartphone agricultural management app known as Padi2U and implement User Acceptance Test (UAT) for end-users. Padi2U was developed using Master App Builder software and integration with the multispectral imagery. Padi2U provides recommendations based on the Department of Agricultures (DOA) such as rice check pest and disease control and weed management. Through the Padi2U farmers can access the field data to understand the crop health status online using the Normalised Difference Vegetation Index (NDVI) map derived from the multispectral images. The NDVI is correlated to the Soil Plant Analysis Development (SPAD) value corresponding to R 0.4012. UAT results showed a 100 percent satisfaction score with suggestions were given to enhance the Padi2U performance. It shows that Padi2U can be improved to help farmers in the field monitoring virtually by integrating multispectral imagery and information from the field.

Full text available from: Official URL: http://www.pertanika.upm.edu.my/resources/files/Pe...

Abstract

In the current practices farmers typically rely on the traditional method paper-based for farming data records which leads to human error. However the paper-based system can be improved by the mobile app technology to ease the farmers acquiring farm data as all of the farm information will be stored in digital form. This study aimed to develop a smartphone agricultural management app known as Padi2U and implement User Acceptance Test (UAT) for end-users. Padi2U was developed using Master App Builder software and integration with the multispectral imagery. Padi2U provides recommendations based on the Department of Agricultures (DOA) such as rice check pest and disease control and weed management. Through the Padi2U farmers can access the field data to understand the crop health status online using the Normalised Difference Vegetation Index (NDVI) map derived from the multispectral images. The NDVI is correlated to the Soil Plant Analysis Development (SPAD) value corresponding to R 0.4012. UAT results showed a 100 percent satisfaction score with suggestions were given to enhance the Padi2U performance. It shows that Padi2U can be improved to help farmers in the field monitoring virtually by integrating multispectral imagery and information from the field.

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Item Type:	Article
AGROVOC Term:	Rice fields
AGROVOC Term:	Multispectral imagery
AGROVOC Term:	Agricultural machinery (industry)
AGROVOC Term:	Crop monitoring
AGROVOC Term:	Crop management
AGROVOC Term:	Data acquisition
AGROVOC Term:	Data collection
AGROVOC Term:	Data analysis
AGROVOC Term:	Statistical analysis
AGROVOC Term:	Image processing
Depositing User:	Mr. AFANDI ABDUL MALEK
Last Modified:	24 Apr 2025 00:55
URI:	http://webagris.upm.edu.my/id/eprint/9788

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