Comprehensive Measurement and Evaluation of Modern Paddy Cultivation with A Hydroganics System Under Different Nutrient Regimes Using WSN and Ground-Based Remote Sensing
Several studies have corroborated the potential applications of advanced technologies such as wireless sensor networks (WSNs) and remote sensing to cultivation, especially in open fields. However, there are limited studies related to plant properties and yield monitoring, as well as to comprehensive...
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| Main Authors: | , , , , , , |
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| Format: | Academic Paper |
| Published: |
ELSEVIER, Measurement,
2021-08-23T04:24:50Z.
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| Online Access: | Get Fulltext |
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| Summary: | Several studies have corroborated the potential applications of advanced technologies such as wireless sensor networks (WSNs) and remote sensing to cultivation, especially in open fields. However, there are limited studies related to plant properties and yield monitoring, as well as to comprehensive measurements attainment when using a modern cultivation method, such as hydroganics. The hydroganics method utilizes a combination of hydroponic and organic matter as a planting medium for paddies. In this study, we evaluated the use of hydroganics on paddies by applying a smart farming system incorporated with advanced technologies that include WSN and ground-based remote sensing. These technologies were developed for comprehensive measurements, such as environmental conditions, plant allometry monitoring, and grain yield under different nutritional treatments and water needs. The imaging and water applications were controlled by the host analysis system on the basis of sensor data. For validation, the plant nitrogen status was analyzed using chemical analysis (the Kjeldahl method) and was compared using a spectrometer and an imaging system. The results showed that data obtained from the imaging system were highly correlated with the allometric parameters, such as plant height, leaf length, width of the leaf, plant canopy, total leaves, and panicles, with R2 values of 0.95, 0.92, 0.93, 0.87, 0.80, and 0.67, respectively. Additionally, water demands, nutrient applications, and plant roots were highly correlated with grain yields with R2 values of 0.89, 0.83, and 0.89, respectively. The present study shows that the application of WSN can be used to estimate plant allometry, water requirements, and environmental information that supports decision making in determining nutrient applications and water needs through an automated system. |
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| Item Description: | http://repository.unej.ac.id/handle/123456789/105078 KODEPRODI1710201#TeknikPertanian NIDN0008108402 NIDN0001017022 NIDN0005047804 |