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Smart Horticulture, Plant Secondary Compounds and Their Applications

This special issue belongs to the section “Postharvest Biology, Quality, Safety, and Technology“.

Special Issue Information

Dear Colleagues,

COVID-19, warfare, and the deficiency of human resources for agriculture around the world present the challenge of applying smart sensing techniques, deep-learning approaches, and robotic applications for solving these problems. The applied sciences in agriculture have significantly expanded the development of smart technologies for horticulture, supporting the problem-solving time for controlling, monitoring, and rapidly detecting pathogens during plant growth. The application of smart technologies has also increased the high-value compounds, especially in the quantity of secondary compounds in plants, which is also necessary to support the development. These goals are linked to resource-efficient uses via sensors, deep machine learning, smart system applications for horticulture, plant secondary compounds, and their applications to open the proper opportunities for smart horticulture. We would like to receive manuscripts that are relevant to smart farming techniques, plant secondary compounds, and their applications. Moreover, studies that focus on the various protected pathogens in the horticulture sector using smart technologies are welcomed.

Dr. Jin Hee Lim
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Horticulturae is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • deep machine learning
  • digital breeding
  • plant secondary compounds
  • quick-detecting pathogens in plant
  • sensors
  • smart horticulture
  • smart model for plant breeding

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Horticulturae - ISSN 2311-7524