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Chung-Liang Chang and Ming-Fong Sie

A multistaged fuzzy logic control method was used in the development of a bionic botanical growth control system. The growth mode combined fuzzy logic inference with expert knowledge to regulate the growth rate of plants. First, environment factors such as the light, temperature, and water required for plants in different stages of growth were analyzed. Fuzzy logic was then used to establish membership functions, an inference engine, and rule table. An expert database related to plant growth was combined with the fuzzy logic controller to formulate a plant growth control system. Sunflowers were used as a simulated model and the results correspond to the information provided by experts. The proposed model was used to control the growth rate of plants based on data provided in the expert database. The proposed method and results of this study are applicable in the management and control of environments for the growth of crops.

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William B. Miller and Madeline W. Olberg

delivered in 120-mL drench volume (which is a typical volume used for substrate drenches in floriculture for crops growing in 15-cm pots). For daffodil, unlike most other floriculture crops, growth control is needed more in the post-greenhouse retail and

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Ming Li and Wei-tang Song

Prod. Sci. 7 4 851 855 Van Henten, E.J. 1994 Validation of a dynamic lettuce growth model for greenhouse climate control Agr. Syst. 45 1 851 855 Van Henten, E.J. Bontsema, J. 1995 Non-destructive crop measurements by image processing for crop growth

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Koichi Nomura, Eriko Wada, Masahiko Saito, Hiromi Yamasaki, Daisuke Yasutake, Tadashige Iwao, Ikunao Tada, Tomihiro Yamazaki, and Masaharu Kitano

. Veg. Sci. 27 427 435 https://doi.org/10.1111/jvs.12350 Van Henten, E.J. Bontsema, J. 1995 Non-destructive crop measurements by image processing for crop growth control J. Agr. Eng. Res. https://doi.org/10.1006/jaer.1995.1036 Weiss