Dynamic Optimization of Solution Nutrient Concentration to Promote the Initial Growth of Tomato Plants in Hydroponics

Yumeina, Diyah; Morimoto, Takeshi

doi:10.2525/ecb.52.87

Cited by 3 publications

(2 citation statements)

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“…In previous studies, the examination of dynamic plant growth control using root zone environmental factors in hydroponic cultivation was limited to nutrient solution concentration [16]. Meanwhile, optimal temperature control of the root zone environment, which is one of the essential determining factors in hydroponic cultivation, had not been thoroughly investigated [18].…”

Section: Discussionmentioning

confidence: 99%

“…By constructing a dynamic model of the process, the optimal control strategy of RZT in hydroponic systems can be determined. In recent years, various studies on eco-physiological modeling and environmental control technology for plant production systems in protected cultivation have been intensively conducted [8,9,11,13,14,16,17]. In our previous study, we examined and identified the response of the leaf water content of plants as affected by changes in the RZT within a short period of time [18]; however, the dynamic response of plant growth as affected by change in the RZT has not been identified.…”

Section: Introductionmentioning

confidence: 99%

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Modeling the Dynamic Response of Plant Growth to Root Zone Temperature in Hydroponic Chili Pepper Plant Using Neural Networks

2020

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One of the essential factors in the root zone environment that affects plant growth is temperature. Determining the optimal root zone temperature condition in a hydroponic system during cultivation could lead to an improvement in plant growth. An optimal control strategy can be determined by identifying the eco-physiological process using a dynamic model. However, it is difficult to develop a dynamic model of the responses of plant growth to root zone temperature because the eco-physiological processes of plants are quite complicated. We propose an intelligent approach that can deal with this complex system. Non-linear autoregressive with exogenous input (NARX) neural networks were used to develop a dynamic model of the responses of plant growth to root zone temperature. The responses of chili pepper plant growth as affected by root zone temperature were measured during 60 days of cultivation inside a growth chamber using a non-destructive and continuous system based on a load cell. Five datasets of dynamic responses of plant growth were obtained for system identification. The results suggest that the application of a neural network is useful for modeling the dynamic response of plant growth to root zone temperature in hydroponic cultivation, with promising performance.

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Section: Discussionmentioning

confidence: 99%