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All Journal Jurnal Keteknikan Pertanian
H. Suhardiyanto
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Agriculture, Biological Sciences & Forestry

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A Model of Vegetative Stage of Baby Cucumber Using Artificial Neural Network Tamrin .; K. B. Seminar; H. Suhardiyanto; S. Hardjoamidjojo
Jurnal Keteknikan Pertanian Vol. 19 No. 1 (2005): Buletin Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.019.1.%p

Abstract

A model of how plant reacts to their micro climate is of great importance to control the physical micro climate around the plant and to other major input problems (such as rutinition intake). Artificial Neural Network (ANN) can be utilized to model a plant reaction to their microclimate in a more objective facshion by applying the ANN to measured data, and not from a pre-assumed model structure. This paper discusses a model of the plant response (the ratio of canopy area-stem diameter of baby cucumber) and the loss of nutrition solution as output and nutrition solution intake and microclimate (temperature, humidity, and irradiation) as input by using artificial neural network of dynamic response.
Optimization of Vegetative Stage of Baby Cucumber (Cucumis sativus L. Var. Marta) using the Genetic Algorithm Tamrin .; K. B. Seminar; H. Suhardiyanto; S. Hardjoamidjojo
Jurnal Keteknikan Pertanian Vol. 19 No. 3 (2005): Buletin Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.019.3.%p

Abstract

An  optimization was conducted to a growth model for baby cucumber (Cucumis sativus L. Var. Marta). The model gives information of nutrient intake and micro climate conditions (temperature, humidity, and irrediation) to get response of the plant (ratio of canopy area and stem diameter) and the loss of nutrient solution. The model ws then coupled with genetic algoritm in order to get optimum result efficiently. Two fitness functions were used in the application og genetic algoritm. The result showed that the first fitness function could be used to optimize the plant response (ratio of canopy area and stem diameter) and the loss of nutrient solution efficiently as indicated by the maximum fitness value (Pc = 0.6 and Pm = 0.01).
Co-Authors K. B. Seminar S. Hardjoamidjojo Tamrin .