Plant Ecophysiology and Phenomics for Next Smart Agriculture

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Agricultural Biosystem and Biological Engineering".

Deadline for manuscript submissions: closed (25 November 2022) | Viewed by 5313

Special Issue Editors


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Guest Editor
Faculty of Agriculture, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka City, Fukuoka 819-0395, Japan
Interests: smart farming; plant phenotyping; IoT; image analysis; use of affordable devices

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Guest Editor
Faculty of Agriculture, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka City, Fukuoka 819-0395, Japan
Interests: photosynthetic model; growth model; environmental control; high-tech greenhouse

E-Mail Website
Guest Editor
Faculty of Agriculture, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka City, Fukuoka 819-0395, Japan
Interests: environmental control; genotype; plant growth and development; quality; yield

E-Mail Website
Guest Editor
Faculty of Agriculture and Marine Science, Kochi University, 200 Monobe-Otsu, Nankoku, Kochi 783-8502, Japan
Interests: modeling of plant physioecological processes; environmental control; Internet of plants

Special Issue Information

Dear Colleagues,

Agriculture is strongly influenced by climate, weather, soil properties, cultivar, and so on. Currently, Information and Communication Technologies (ICT), including the Internet of Things (IoT) and Artificial Intelligence (AI), have been utilized well to advance farming skills and techniques. These technologies have also contributed to our grasp of plants’ growth properties.

This Special Issue focuses on the “Plant ecophysiology and phenomics for next smart agriculture”. The following topics are invited:

(1) Sending technologies for field environmental information;

(2) Modeling and analysis for plant and environment system;

(3) Plant phenotyping;

(4) Plant growth and development under controlled environment;

(5) Estimation of yield and production efficiency;

(6) Precision, smart, and digital agriculture.

Dr. Takashi Okayasu
Dr. Daisuke Yasutake
Dr. Yukio Ozaki
Dr. Masaharu Kitano
Guest Editors

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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Agronomy 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 2600 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

  • Sensing on-field environmental and plant information
  • Modeling and analysis for plant and environment system
  • Plant phenotyping
  • Yield and quality estimation
  • Precision, smart, and digital agriculture

Published Papers (1 paper)

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Research

14 pages, 2938 KiB  
Article
Effects of CO2 Enrichment on Yield, Photosynthetic Rate, Translocation and Distribution of Photoassimilates in Strawberry ‘Sagahonoka’
by Ai Tagawa, Megumi Ehara, Yuusuke Ito, Takuya Araki, Yukio Ozaki and Yoshihiro Shishido
Agronomy 2022, 12(2), 473; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020473 - 14 Feb 2022
Cited by 12 | Viewed by 4661
Abstract
The method of automatically controlling the CO2 concentration in a greenhouse depending on ventilation was examined in order to efficiently improve the productivity of strawberries under the weather conditions in the northern part of Kyushu in Japan. The effects of CO2 [...] Read more.
The method of automatically controlling the CO2 concentration in a greenhouse depending on ventilation was examined in order to efficiently improve the productivity of strawberries under the weather conditions in the northern part of Kyushu in Japan. The effects of CO2 enrichment on the yields, fruit Brix, and economic value of the strawberry ‘Sagahonoka’ were investigated. In addition, in order to clarify the physiological response of ‘Sagahonoka’ to the CO2 concentration, the photosynthetic rate, translocation, and photoassimilate distribution rate were measured. It was found that maintaining the CO2 concentrations above 800 μmol mol−1 and 400 μmol mol−1 during no ventilation and ventilation, respectively, resulted in 25% increases in marketable fruit yields and a 0.2–1.2% higher fruit Brix compared to control, which was kept in 400 μmol mol−1 CO2 or above all day regardless of ventilation. Additionally, the economic value of ‘Sagahonoka’ was increased. The photosynthetic rate of ‘Sagahonoka’ increased linearly up to 800 μmol mol−1 CO2, and high CO2 concentrations affected the distribution for the primary fruit, the most significant sink. It was clarified that CO2 enrichment at 800 μmol mol−1 for ‘Sagahonoka’ was effective in increasing the photosynthetic rate and distribution of photoassimilates to fruits, and the yields of strawberries could be increased efficiently by automatically controlling the CO2 concentration depending on ventilation in a southern region of Japan. Full article
(This article belongs to the Special Issue Plant Ecophysiology and Phenomics for Next Smart Agriculture)
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