System Identification of Linearized Rice Growth Dynamic for Precision Irrigation

Poster


Cabrera, John Audie, Radanielson, Ando Mariot and Pedrasa, Jhoanna Rhodette. 2019. "System Identification of Linearized Rice Growth Dynamic for Precision Irrigation." International Tropical Agriculture Conference 2019 (TropAg 2019). Brisbane, Australia 11 - 13 Nov 2019 Basel, Switzerland. https://doi.org/10.3390/proceedings2019036031
Paper/Presentation Title

System Identification of Linearized Rice Growth Dynamic for Precision Irrigation

Presentation TypePoster
AuthorsCabrera, John Audie (Author), Radanielson, Ando Mariot (Author) and Pedrasa, Jhoanna Rhodette (Author)
Journal or Proceedings TitleProceedings of The Third International Tropical Agriculture Conference (TROPAG 2019)
Journal Citation36 (1)
Article Number31
Number of Pages1
Year2019
Place of PublicationBasel, Switzerland
Digital Object Identifier (DOI)https://doi.org/10.3390/proceedings2019036031
Web Address (URL) of Paperhttps://www.mdpi.com/2504-3900/36/1/31
Conference/EventInternational Tropical Agriculture Conference 2019 (TropAg 2019)
Event Details
International Tropical Agriculture Conference 2019 (TropAg 2019)
Delivery
In person
Event Date
11 to end of 13 Nov 2019
Event Location
Brisbane, Australia
Abstract

Modeling crop growth dynamics has been used to predict and analyze the effects of water stress on crop yields for different irrigation managements. In particular, rice, a water intensive crop, has been extensively modeled using simulation software such as ORYZA3, Aquacrop, and WARM. Despite these established simulation models, only soil water balance models are utilized for real time irrigation control. The reasons are twofold: the complexity in incorporating non-linear and highly interactive nature of crop physiological mechanisms in a control framework; and the difficulty in estimating these physiological mechanisms compared to using soil water sensors for soil water balance models. This work developed a system identification technique that improves accuracy in irrigation timing, amount and efficiency by integrating crop growth dynamics to estimate evapotranspiration as feedback in the soil water balance model. Sample simulation runs from ORYZA3 were used to build and validate a water limited growth dynamics. A two level regression technique was used resulting in reduced expressions for leaf area index, biomass, and soil water depletion. With advancements in wireless sensor technologies, the modeling framework maximizes use of field sensor information to adequately estimate the crop state. Thus, it can be adopted in advance control techniques for irrigation.

KeywordsCrop modeling; precision irrigation; control
ANZSRC Field of Research 2020300206. Agricultural spatial analysis and modelling
300205. Agricultural production systems simulation
300207. Agricultural systems analysis and modelling
Byline AffiliationsUniversity of the Philippines
Centre for Sustainable Agricultural Systems
Institution of OriginUniversity of Southern Queensland
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