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[4J2-GS-5-01] Simulation of Lodging in Sake Rice: Yamada Nishiki
- Comparison with Aerial Drone Images -
Keywords:simulation, lodging, drone
Recent advancements in digital technology have made it possible to collect growth data in rice cultivation. This study examines the sake rice variety Yamada-Nishiki, which is known for its large grains and a total height of about 130 cm. Yamada-Nishiki is more difficult to cultivate than food rice due to its tendency to lodge in the wind. During the harvest season, the weight of the grain contributes to lodging, which results in decreased yield and quality.
Since field growth and lodging can only be observed once a year, a simulation model was developed to understand the lodging mechanism. The model incorporates factors like stem strength and the number of stems per plant. The simulation begins with randomized parameters, including the number of plants, total stem height, stems per plant, and stem strength. At each time interval, the interaction between neighboring rice ears and wind forces determines the state of each ear at the next interval. This set of rules models the spatial distribution and mutual interactions of rice ears throughout the field.
This framework allows for simulating the progression of lodging. The post-lodging state generated by the simulation was compared to aerial drone images of a paddy field where lodging occurred, confirming that the patterns and edge features in the affected areas matched.
Since field growth and lodging can only be observed once a year, a simulation model was developed to understand the lodging mechanism. The model incorporates factors like stem strength and the number of stems per plant. The simulation begins with randomized parameters, including the number of plants, total stem height, stems per plant, and stem strength. At each time interval, the interaction between neighboring rice ears and wind forces determines the state of each ear at the next interval. This set of rules models the spatial distribution and mutual interactions of rice ears throughout the field.
This framework allows for simulating the progression of lodging. The post-lodging state generated by the simulation was compared to aerial drone images of a paddy field where lodging occurred, confirming that the patterns and edge features in the affected areas matched.
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