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Plants
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Next-Generation Crop Plant Breeding Approaches for Resilient Agriculture
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Next-Generation Crop Plant Breeding Approaches for Resilient Agriculture

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Genetics, Genomics and Biotechnology".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 6363

Special Issue Editors

Prof. Dr. Gianni Barcaccia

E-Mail Website1 Website2
Guest Editor
Laboratory of Genomics for Breeding, Department of Agronomy, Food, Natural resources, Animals and Environment—DAFNAE, University of Padova, Campus of Agripolis—Legnaro, 35020 Padova, Italy
Interests: plant genetics; plant reproductive systems and population genetics; genomics applied to plant breeding
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Paolo Sambo

E-Mail Website
Guest Editor
Laboratory of Horticulture, Department of Agronomy, Food, Natural resources, Animals and Environment—DAFNAE, University of Padova, Campus of Agripolis—Legnaro, 35020 Padova, Italy
Interests: horticulture; plant nutrition; sustainable plant growing systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Agriculture is called not only to produce food and raw materials in a sustainable way, but also to contribute to environmental quality traits and to the mitigation of climate change risks worldwide. The unprecedented economic and social crisis due to the global coronavirus pandemic and the current Russian–Ukrainian conflict will likely mean a turning point to deal with the overall resilience of agriculture systems and sustainability of food supplies. Both integrated and multifunctional solutions should be developed at different scales for the molecular selection and prediction of resilient traits in the main crop plants. In particular, at crop level we need to exploit next-generation genotyping and phenotyping technologies and platforms to predict and select resistance to plant pathogens and tolerance to environmental stresses, and to develop new cultivated varieties based on genotypes that ensure greater unit yields (i.e., the “more with less” principle) and better quality characteristics for economically important plant species, according to the “do no significant harm” principle. We are confident that the application of genomics combined with phenomics is the answer, as it can provide a key contribution for the development of new plant genotypes and molecular assays for the main crop species to implement and predict the agronomic added value of plant varieties expressing resilient traits and phenotypes. Gathering relevant information as to how and why given genotypes/phenotypes can be amenable to particular environmental conditions and suitable for specific cultivation systems is the main goal of our Special Issue. Overall, this activity is carried out within the Agritech National Research Center, which received funding from the European Union’s Next-Generation EU instrument. In particular, it is related to Spoke 4, dealing with multifunctional and resilient agriculture and forestry systems for the mitigation of climate change risks.

Prof. Dr. Gianni Barcaccia
Prof. Dr. Paolo Sambo
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. 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

  • crop plants
  • genomics
  • phenomics
  • plant genotyping
  • plant phenotyping
  • plant breeding
  • crop varieties

Published Papers (3 papers)

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Research

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23 pages, 4547 KiB  
Article
Pipeline to Design Inbred Lines and F1 Hybrids of Leaf Chicory (Radicchio) Using Male Sterility and Genotyping-by-Sequencing
by Francesco Scariolo, Fabio Palumbo, Silvia Farinati and Gianni Barcaccia
Plants 2023, 12(6), 1242; https://doi.org/10.3390/plants12061242 - 09 Mar 2023
Cited by 2 | Viewed by 1959
Abstract
Chicory, a horticultural crop cultivated worldwide, presents many botanical varieties and local biotypes. Among these, cultivars of the Italian radicchio group of the pure species Cichorium intybus L. and its interspecific hybrids with Cichorium endivia L.—as the “Red of Chioggia” biotype—includes several phenotypes. [...] Read more.
Chicory, a horticultural crop cultivated worldwide, presents many botanical varieties and local biotypes. Among these, cultivars of the Italian radicchio group of the pure species Cichorium intybus L. and its interspecific hybrids with Cichorium endivia L.—as the “Red of Chioggia” biotype—includes several phenotypes. This study uses a pipeline to address the marker-assisted breeding of F1 hybrids: it presents the genotyping-by-sequencing results of four elite inbred lines using a RADseq approach and an original molecular assay based on CAPS markers for screening mutants with nuclear male sterility in the radicchio of Chioggia. A total of 2953 SNP-carrying RADtags were identified and used to compute the actual estimates of homozygosity and overall genetic similarity and uniformity of the populations, as well as to determine their genetic distinctiveness and differentiation. Molecular data were further used to investigate the genomic distribution of the RADtags among the two Cichorium species, allowing their mapping in 1131 and 1071 coding sequences in chicory and endive, respectively. Paralleling this, an assay to screen the genotype at the male sterility locus Cims-1 was developed to discriminate wild-type and mutant alleles of the causative gene myb80-like. Moreover, a RADtag mapped close to this genomic region proved the potential application of this method for future marker-assisted selection tools. Finally, after combining the genotype information of the core collection, the best 10 individuals from each inbred line were selected to compute the observed genetic similarity as a measure of uniformity as well as the expected homozygosity and heterozygosity estimates scorable by the putative progenies derived from selfing (pollen parent) and full-sibling (seed parent) or pair-wise crossing (F1 hybrids). This predictive approach was conducted as a pilot study to understand the potential application of RADseq in the fine tuning of molecular marker-assisted breeding strategies aimed at the development of inbred lines and F1 hybrids in leaf chicory. Full article
(This article belongs to the Special Issue Next-Generation Crop Plant Breeding Approaches for Resilient Agriculture)
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14 pages, 3403 KiB  
Article
Brown Seaweed Extract (BSE) Application Influences Auxin- and ABA-Related Gene Expression, Root Development, and Sugar Yield in Beta vulgaris L.
by Giovanni Bertoldo, Claudia Chiodi, Maria Cristina Della Lucia, Matteo Borella, Samathmika Ravi, Andrea Baglieri, Piergiorgio Lucenti, Bhargava Krishna Ganasula, Chandana Mulagala, Andrea Squartini, Giuseppe Concheri, Francesco Magro, Giovanni Campagna, Piergiorgio Stevanato and Serenella Nardi
Plants 2023, 12(4), 843; https://doi.org/10.3390/plants12040843 - 13 Feb 2023
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Abstract
The molecular and phenotypic effects of a brown seaweed extract (BSE) were assessed in sugar beet (Beta vulgaris L.). Transcript levels of BSE-treated and untreated plants were studied by RNA-seq and validated by quantitative real-time PCR analysis (RT-qPCR). Root morphology, sugar yield, [...] Read more.
The molecular and phenotypic effects of a brown seaweed extract (BSE) were assessed in sugar beet (Beta vulgaris L.). Transcript levels of BSE-treated and untreated plants were studied by RNA-seq and validated by quantitative real-time PCR analysis (RT-qPCR). Root morphology, sugar yield, and processing quality traits were also analyzed to better elucidate the treatment effects. RNA-seq revealed 1019 differentially expressed genes (DEGs) between the BSE-treated and untreated plants. An adjusted p-value < 0.1 and an absolute value of log2 (fold change) greater than one was used as criteria to select the DEGs. Gene ontology (GO) identified hormone pathways as an enriched biological process. Six DEGs involved in auxin and ABA pathways were validated using RT-qPCR. The phenotypic characterization indicated that BSE treatment led to a significant increase (p < 0.05) in total root length and the length of fine roots of plants grown under hydroponics conditions. The sugar yield of plants grown under field conditions was higher (p < 0.05) in the treated field plots compared with the control treatment, without impacting the processing quality. Our study unveiled the relevant effects of BSE application in regulating auxin- and ABA-related gene expression and critical traits related to sugar beet development and yield. Full article
(This article belongs to the Special Issue Next-Generation Crop Plant Breeding Approaches for Resilient Agriculture)
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Review

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35 pages, 4586 KiB  
Review
Plant Physiological Analysis to Overcome Limitations to Plant Phenotyping
by Matthew Haworth, Giovanni Marino, Giulia Atzori, Andre Fabbri, Andre Daccache, Dilek Killi, Andrea Carli, Vincenzo Montesano, Adriano Conte, Raffaella Balestrini and Mauro Centritto
Plants 2023, 12(23), 4015; https://doi.org/10.3390/plants12234015 - 29 Nov 2023
Viewed by 1854
Abstract
Plant physiological status is the interaction between the plant genome and the prevailing growth conditions. Accurate characterization of plant physiology is, therefore, fundamental to effective plant phenotyping studies; particularly those focused on identifying traits associated with improved yield, lower input requirements, and climate [...] Read more.
Plant physiological status is the interaction between the plant genome and the prevailing growth conditions. Accurate characterization of plant physiology is, therefore, fundamental to effective plant phenotyping studies; particularly those focused on identifying traits associated with improved yield, lower input requirements, and climate resilience. Here, we outline the approaches used to assess plant physiology and how these techniques of direct empirical observations of processes such as photosynthetic CO2 assimilation, stomatal conductance, photosystem II electron transport, or the effectiveness of protective energy dissipation mechanisms are unsuited to high-throughput phenotyping applications. Novel optical sensors, remote/proximal sensing (multi- and hyperspectral reflectance, infrared thermography, sun-induced fluorescence), LiDAR, and automated analyses of below-ground development offer the possibility to infer plant physiological status and growth. However, there are limitations to such ‘indirect’ approaches to gauging plant physiology. These methodologies that are appropriate for the rapid high temporal screening of a number of crop varieties over a wide spatial scale do still require ‘calibration’ or ‘validation’ with direct empirical measurement of plant physiological status. The use of deep-learning and artificial intelligence approaches may enable the effective synthesis of large multivariate datasets to more accurately quantify physiological characters rapidly in high numbers of replicate plants. Advances in automated data collection and subsequent data processing represent an opportunity for plant phenotyping efforts to fully integrate fundamental physiological data into vital efforts to ensure food and agro-economic sustainability. Full article
(This article belongs to the Special Issue Next-Generation Crop Plant Breeding Approaches for Resilient Agriculture)
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