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Titlebook: Nutraceuticals Production from Plant Cell Factory; Tarun Belwal,Milen I. Georgiev,Jameel M Al-Khayri Book 2022 The Editor(s) (if applicabl

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發(fā)表于 2025-3-21 18:53:56 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Nutraceuticals Production from Plant Cell Factory
編輯Tarun Belwal,Milen I. Georgiev,Jameel M Al-Khayri
視頻videohttp://file.papertrans.cn/670/669503/669503.mp4
概述Provides contemporary understanding of the techniques of in vitro production of nutraceutical compounds.Comprehensively discusses nutraceutical production using in vitro cell culture techniques and it
圖書(shū)封面Titlebook: Nutraceuticals Production from Plant Cell Factory;  Tarun Belwal,Milen I. Georgiev,Jameel M Al-Khayri Book 2022 The Editor(s) (if applicabl
描述This book focuses on?in vitro techniques and challenges of producing nutraceutical compounds? from plant cells. In addition, it provides an overview of different biosynthesis pathways and their modulation through cell culture techniques for the production of nutraceutical compounds in high quantity and quality. It also includes the assessment of the factors influencing production and advances in cell culture techniques, including the scale-up approach using bioreactors. Lastly it?provides valuable suggestion for future research..
出版日期Book 2022
關(guān)鍵詞Nutraceuticals production; In vitro plant cell culture; Biosynthesis pathways; Scale-up bioreactors; Nut
版次1
doihttps://doi.org/10.1007/978-981-16-8858-4
isbn_softcover978-981-16-8860-7
isbn_ebook978-981-16-8858-4
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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” to human computer interfaces. An EEG-enabled music therapy site was proposed and implemented. The music played to the patients helps them deal with problems such as pain and depression. An EEG-based web-enable music player which can display the music according to the user’s current emotion states was designed and implemented.
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Sandeep Ramchandra Paiidirectional Encoder Representations from Transformers (BERT) that outperforms its state-of-the-art unsupervised counterparts achieving an average of 77.84% Sparsman’s correlation on standard Semantic Textual Similarity (STS) tasks.
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