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Advanced Technologies in High Resolution Plant Phenotyping
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Advanced Technologies in High Resolution Plant Phenotyping

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Development and Morphogenesis".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 5479

Special Issue Editor

Dr. Giacomo Mele

E-Mail Website
Guest Editor
Agrifood Imaging Lab, Institute for Agriculture and Forestry in the Mediterranean, National Research Council of Italy, Rome, Italy
Interests: agri-food Imaging; plant phenotyping; X-ray microCT; soil physics; soil hydrology

Special Issue Information

Dear Colleagues,

Plant phenotyping systems generally imply a large amount of data to be acquired, processed and managed to provide adequate information to breeders and biotechnologists in order to obtain crops suitable for facing the expected environmental and social challenges. The number of plants allowed on the automated platforms, the multiplicity of the platforms’ sensors, and the number of treatments all contribute to the number of parameters used for the phenomic characterization of the studied genotypes. In particular, the resolution in data acquisition, both spatial and temporal, plays a crucial role in the accuracy and quality of the provided traits. Non-invasive imaging techniques in three dimensions are increasingly used and are continuously developing to reach high spatial resolution of morphological traits at any plant organization level, from cells to canopy, by enhancing sensors, technologies, and acquisition configurations. This Special Issue of Plants will highlight the most recent applications of high-resolution phenotyping performed with the lab technologies of X-ray microCT (XRM), nuclear magnetic resonance imaging (MRI), and positron emission tomography (PET), which provide 3D high-resolution images of the internal structure, water content, and functional properties of the plant organs and tissues (roots, seeds, stems, etc.), thus allowing new insights into plant phenotyping based on novel traits not obtainable with the standard high-throughput phenotyping platforms.

Dr. Giacomo Mele
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 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. Plants is an international peer-reviewed open access semimonthly 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 2700 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

  • Plant morphology
  • Novel phenotypic traits
  • Noninvasive imaging
  • Seed anatomy
  • Plant tissues

Published Papers (2 papers)

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Research

14 pages, 5071 KiB  
Article
Prediction of Buckwheat Maturity in UAV-RGB Images Based on Recursive Feature Elimination Cross-Validation: A Case Study in Jinzhong, Northern China
by Jinlong Wu, Decong Zheng, Zhiming Wu, Haiyan Song and Xiaoxiang Zhang
Plants 2022, 11(23), 3257; https://doi.org/10.3390/plants11233257 - 27 Nov 2022
Cited by 5 | Viewed by 1490
Abstract
Buckwheat is an important minor grain crop with medicinal and edible functions. The accurate judgment of buckwheat maturity is beneficial to reduce harvest losses and improve yield. With the rapid development of unmanned aerial vehicle (UAV) technology, it has been widely used to [...] Read more.
Buckwheat is an important minor grain crop with medicinal and edible functions. The accurate judgment of buckwheat maturity is beneficial to reduce harvest losses and improve yield. With the rapid development of unmanned aerial vehicle (UAV) technology, it has been widely used to predict the maturity of agricultural products. This paper proposed a method using recursive feature elimination cross-validation (RFECV) combined with multiple regression models to predict the maturity of buckwheat in UAV-RGB images. The images were captured in the buckwheat experimental field of Shanxi Agricultural University in Jinzhong, Northern China, from September to October in 2021. The variety was sweet buckwheat of “Jinqiao No. 1”. In order to deeply mine the feature vectors that highly correlated with the prediction of buckwheat maturity, 22 dimensional features with 5 vegetation indexes, 9 color features, and 8 texture features of buckwheat were selected initially. The RFECV method was adopted to obtain the optimal feature vector dimensions and combinations with six regression models of decision tree regression, linear regression, random forest regression, AdaBoost regression, gradient lifting regression, and extreme random tree regression. The coefficient of determination (R2) and root mean square error (RMSE) were used to analyze the different combinations of the six regression models with different feature spaces. The experimental results show that the single vegetation index performed poorly in the prediction of buckwheat maturity; the prediction result of feature space “5” combined with the gradient lifting regression model performed the best; and the R2 and RMSE were 0.981 and 1.70 respectively. The research results can provide an important theoretical basis for the prediction of the regional maturity of crops. Full article
(This article belongs to the Special Issue Advanced Technologies in High Resolution Plant Phenotyping)
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27 pages, 5356 KiB  
Article
Plant Growth Promotion and Heat Stress Amelioration in Arabidopsis Inoculated with Paraburkholderia phytofirmans PsJN Rhizobacteria Quantified with the GrowScreen-Agar II Phenotyping Platform
by Allene Macabuhay, Borjana Arsova, Michelle Watt, Kerstin A. Nagel, Henning Lenz, Alexander Putz, Sascha Adels, Mark Müller-Linow, Jana Kelm, Alexander A. T. Johnson, Robert Walker, Gabriel Schaaf and Ute Roessner
Plants 2022, 11(21), 2927; https://doi.org/10.3390/plants11212927 - 30 Oct 2022
Cited by 6 | Viewed by 3163
Abstract
High temperatures inhibit plant growth. A proposed strategy for improving plant productivity under elevated temperatures is the use of plant growth-promoting rhizobacteria (PGPR). While the effects of PGPR on plant shoots have been extensively explored, roots—particularly their spatial and temporal dynamics—have been hard [...] Read more.
High temperatures inhibit plant growth. A proposed strategy for improving plant productivity under elevated temperatures is the use of plant growth-promoting rhizobacteria (PGPR). While the effects of PGPR on plant shoots have been extensively explored, roots—particularly their spatial and temporal dynamics—have been hard to study, due to their below-ground nature. Here, we characterized the time- and tissue-specific morphological changes in bacterized plants using a novel non-invasive high-resolution plant phenotyping and imaging platform—GrowScreen-Agar II. The platform uses custom-made agar plates, which allow air exchange to occur with the agar medium and enable the shoot to grow outside the compartment. The platform provides light protection to the roots, the exposure of it to the shoots, and the non-invasive phenotyping of both organs. Arabidopsis thaliana, co-cultivated with Paraburkholderia phytofirmans PsJN at elevated and ambient temperatures, showed increased lengths, growth rates, and numbers of roots. However, the magnitude and direction of the growth promotion varied depending on root type, timing, and temperature. The root length and distribution per depth and according to time was also influenced by bacterization and the temperature. The shoot biomass increased at the later stages under ambient temperature in the bacterized plants. The study offers insights into the timing of the tissue-specific, PsJN-induced morphological changes and should facilitate future molecular and biochemical studies on plant–microbe–environment interactions. Full article
(This article belongs to the Special Issue Advanced Technologies in High Resolution Plant Phenotyping)
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