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      Application of Adaptive Neuro-Fuzzy Inference System-Non-dominated Sorting Genetic Algorithm-II (ANFIS-NSGAII) for Modeling and Optimizing Somatic Embryogenesis of Chrysanthemum

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          Abstract

          A hybrid artificial intelligence model and optimization algorithm could be a powerful approach for modeling and optimizing plant tissue culture procedures. The aim of this study was introducing an Adaptive Neuro-Fuzzy Inference System- Non-dominated Sorting Genetic Algorithm-II (ANFIS-NSGAII) as a powerful computational methodology for somatic embryogenesis of chrysanthemum, as a case study. ANFIS was used for modeling three outputs including callogenesis frequency (CF), embryogenesis frequency (EF), and the number of somatic embryo (NSE) based on different variables including 2,4-dichlorophenoxyacetic acid (2,4-D), 6-benzylaminopurine (BAP), sucrose, glucose, fructose, and light quality. Subsequently, models were linked to NSGAII for optimizing the process, and the importance of each input was evaluated by sensitivity analysis. Results showed that all of the R 2 of training and testing sets were over 92%, indicating the efficiency and accuracy of ANFIS on the modeling of the embryogenesis. Also, according to ANFIS-NSGAII, optimal EF (99.1%), and NSE (13.1) can be obtained from a medium containing 1.53 mg/L 2,4-D, 1.67 mg/L BAP, 13.74 g/L sucrose, 57.20 g/L glucose, and 0.39 g/L fructose under red light. The results of the sensitivity analysis showed that embryogenesis was more sensitive to 2,4-D, and less sensitive to fructose. Generally, the hybrid ANFIS-NSGAII can be recognized as a powerful computational tool for modeling and optimizing in plant tissue culture.

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          Most cited references61

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          Plant Productivity in Response to LED Lighting

          Light-emitting diodes (LEDs) have tremendous potential as supplemental or sole-source lighting systems for crop production both on and off earth. Their small size, durability, long operating lifetime, wavelength specificity, relatively cool emitting surfaces, and linear photon output with electrical input current make these solid-state light sources ideal for use in plant lighting designs. Because the output waveband of LEDs (single color, nonphosphor-coated) is much narrower than that of traditional sources of electric lighting used for plant growth, one challenge in designing an optimum plant lighting system is to determine wavelengths essential for specific crops. Work at NASA's Kennedy Space Center has focused on the proportion of blue light required for normal plant growth as well as the optimum wavelength of red and the red/far-red ratio. The addition of green wavelengths for improved plant growth as well as for visual monitoring of plant status has been addressed. Like with other light sources, spectral quality of LEDs can have dramatic effects on crop anatomy and morphology as well as nutrient uptake and pathogen development. Work at Purdue University has focused on geometry of light delivery to improve energy use efficiency of a crop lighting system. Additionally, foliar intumescence developing in the absence of ultraviolet light or other less understood stimuli could become a serious limitation for some crops lighted solely by narrow-band LEDs. Ways to prevent this condition are being investigated. Potential LED benefits to the controlled environment agriculture industry are numerous and more work needs to be done to position horticulture at the forefront of this promising technology.
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            Cytokinin regulation of auxin synthesis in Arabidopsis involves a homeostatic feedback loop regulated via auxin and cytokinin signal transduction.

            Together, auxin and cytokinin regulate many of the processes that are critical to plant growth, development, and environmental responsiveness. We have previously shown that exogenous auxin regulates cytokinin biosynthesis in Arabidopsis thaliana. In this work, we show that, conversely, the application or induced ectopic biosynthesis of cytokinin leads to a rapid increase in auxin biosynthesis in young, developing root and shoot tissues. We also show that reducing endogenous cytokinin levels, either through the induction of CYTOKININ OXIDASE expression or the mutation of one or more of the cytokinin biosynthetic ISOPENTENYLTRANSFERASE genes leads to a reduction in auxin biosynthesis. Cytokinin modifies the abundance of transcripts for several putative auxin biosynthetic genes, suggesting a direct induction of auxin biosynthesis by cytokinin. Our data indicate that cytokinin is essential, not only to maintain basal levels of auxin biosynthesis in developing root and shoot tissues but also for the dynamic regulation of auxin biosynthesis in response to changing developmental or environmental conditions. In combination with our previous work, the data suggest that a homeostatic feedback regulatory loop involving both auxin and cytokinin signaling acts to maintain appropriate auxin and cytokinin concentrations in developing root and shoot tissues.
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              Molecular regulation of plant somatic embryogenesis

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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                05 July 2019
                2019
                : 10
                : 869
                Affiliations
                [1] 1Department of Horticultural Science, Faculty of Agriculture, University of Tehran , Karaj, Iran
                [2] 2Department of Plant Biotechnology, Faculty of Science and Biotechnology, Shahid Beheshti University , Tehran, Iran
                [3] 3Department of Plant Agriculture, University of Guelph , Guelph, ON, Canada
                Author notes

                Edited by: Juan Caballero, Universidad Autónoma de Querétaro, Mexico

                Reviewed by: Guilherme De Alencar Barreto, Universidade Federal do Ceará, Brazil; Yuriy L. Orlov, Russian Academy of Sciences, Russia

                *Correspondence: Roohangiz Naderi rnaderi@ 123456ut.ac.ir

                This article was submitted to Bioinformatics and Computational Biology, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2019.00869
                6624437
                31333705
                63ac75df-6195-4a11-9b03-9e5238a334b8
                Copyright © 2019 Hesami, Naderi, Tohidfar and Yoosefzadeh-Najafabadi.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 20 February 2019
                : 18 June 2019
                Page count
                Figures: 6, Tables: 4, Equations: 10, References: 67, Pages: 12, Words: 8965
                Categories
                Plant Science
                Methods

                Plant science & Botany
                artificial intelligence,chrysanthemum,carbohydrate,embryogenesis,in vitro culture,light quality,optimization algorithm,plant growth regulator

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