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Analysis of Chlorophyll and Carotenoids Content in Brassica Chinensis Plants Using IoT-Based Sprinkle Irrigation
 
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1
Civil Engineering, Universitas Islam Malang, Jalan Mayjen Haryono No.193, Dinoyo, Kec. Lowokwaru, Kota Malang, Jawa Timur 65144, Indonesia
 
2
Electrical Engineering, Universitas Negeri Malang, Jalan. Semarang 5 Malang, Malang, Indonesia
 
3
Agriculture Technology, Universitas Islam Malang, Jalan Mayjen Haryono No.193, Dinoyo, Kec. Lowokwaru, Kota Malang, Jawa Timur 65144, Indonesia
 
4
Electrical Engineering, Universitas Islam Malang, Jalan Mayjen Haryono No.193, Dinoyo, Kec. Lowokwaru, Kota Malang, Jawa Timur 65144, Indonesia
 
 
Corresponding author
Eko Noerhayati   

Civil Engineering, Universitas Islam Malang, Jalan Mayjen Haryono No.193, Dinoyo, Kec. Lowokwaru, Kota Malang, Jawa Timur 65144, Indonesia
 
 
J. Ecol. Eng. 2022; 23(9):25-33
 
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ABSTRACT
The agricultural sector is currently witnessing the use of Internet of Things (IoT) to drive significant innovations across key interests, particularly irrigation. A sprinkler designed with an Arduino controller was developed in this study. The device is among the fastest growing agricultural irrigation systems. The plant studied is Brassica Chinensis, because this vegetable is one of the most commonly consumed vegetables by Indonesian people. However, emphasis is also placed on plant quality as an important consideration, not only on the device’s operational performance. The purpose of this research was to compare the plant quality, including the dissolved solids, chlorophyll, carotenoid, and vitamin C using manual and Arduino-based sprinkler. As consequence, three treatment methods were employed, termed: the use of manual sprinkle, e.g. P0, and Arduino-based IoT sprinkler, described as P1 and P2. Under these conditions, the chlorophyll quality was comparable to the results obtained using the manual application. P1 is a situation where the sprinkler is manually set by the farmer via the app. Meanwhile, P2 uses a sprinkler which is automatically regulated by the system. Under these conditions, the chlorophyll quality generated with the IoT sprinkler was comparable to the results obtained using the manual application.
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