Development of environmental control method base on plant shoot tip model
| Project/Area Number |
14560208
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
農業機械学
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| Research Institution | Ibaraki University |
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Principal Investigator |
SHIMIZU Hiroshi Ibaraki Univ., the College of Agriculture, Associate Professor, 農学部, 助教授 (50206207)
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| Project Period (FY) |
2002 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥2,700,000 (Direct Cost: ¥2,700,000)
Fiscal Year 2004: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2003: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2002: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Keywords | shoot-tip temperature / model / neural network / environmental control / pot plant |
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| Research Abstract |
Understanding and controlling the rate of plant development is required to manage production of ornamental crops to meet predetermined market finish dates. Many studies have found that apical meristem temperature, or shoot-tip temperature, is the primary factor that controls the rate of plant development. Plant shoot-tip temperature is often warmer or cooler than air temperature. For example, shoot-tip temperature of Catharanthus roseus L.(vinca) grown at 15℃ was equal to the dry-bulb greenhouse air temperature for only a brief period during the morning and late afternoon, and was almost always 4 to 6℃ lower when grown at a 35℃ air temperature. Although shoot-tip temperature is seldom equal to air temperature, greenhouse climate control systems generally target air temperature, not plant temperature. Controlling greenhouse environments based on shoot-tip temperature would improve the accuracy and management of scheduling production of ornamental crops. A model which predicts a plant sh
… More
oot-tip temperature with sufficient accuracy from the environmental conditions as drybulb temperature, wetbulb temperature, shortwave radiation, longwave radiation and air velocity was constructed base on the energy balance concept. The additional experiment must be conducted to obtain a specie-dependent parameter"cuticle resistance"since the constructed model contains it. Then, to avoid this inconvenient, a neural network model that requires only a data set of input and output was created. In case an energy balance model, it is clear that the model predicts the shoot-tip temperature accurately, however, there is a week point that this type of model requires specie-dependent parameter. On the other hand, it is clarified that the neural network model can be applicable because its inputs consist of four environmental factors that are easily and/or commonly measured in commercial greenhouses, and may thus be a useful tool for evaluating the environmental factors that affect plant shoot-tip temperature under greenhouse conditions. Less
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Report
(4 results)
Research Products
(2 results)
