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Agronomy
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Multiomics and Biotechnological Approaches for Increasing the Abiotic Stress Resistance...
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Multiomics and Biotechnological Approaches for Increasing the Abiotic Stress Resistance of Plants

A special issue of Agronomy (ISSN 2073-4395).

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4534

Special Issue Editors

Prof. Dr. Yuelin Zhu

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Guest Editor
Key Laboratory of Biology and Germplasm Enhancement of Horticultural Crop (East China), Ministry of Agriculture and Rural Affairs, College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China
Interests: the multidisciplinary studies of multi-omics, biotechnology, and physiology of vegetable plants for increasing their productivity under abiotic and biotic stresses
Prof. Dr. Huatao Chen

E-Mail Website
Guest Editor
Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
Interests: the intensive integration of multi-omics, biotechnology, and breeding of agronomically-important plants for improving their yields and quality under abiotic and biotic stresses

Special Issue Information

Dear Colleagues,

Due to the climate change, plant abiotic stresses are major causes for the reduction of yield and quality of agricultural crops. With the rapid progress in technologies of plant multiomics and biotechnology, the resultant data have brought new challenges and opportunities in plant and agricultural sciences. Such significant advancements have helped to strengthen the profound understanding of molecular insights into the plant tolerance to abiotic stresses. There are urgent needs to understand the crucial integrative multiomics and biotechnological techniques to provide approaches for increasing plant tolerance to abiotic stresses. This Special Issue covers not only the roles of the integration of multiomics and biotechnology in the elucidation of mechanisms underlying the enhancement of plant tolerance to abiotic stresses, but also the novel insights that could substantialy contribute to develop new approaches for agriculture to overcome yield and quality losses caused by abiotic stresses, which sheds light on the understanding of the sustainable agricultural production to feed the growing world population.

In this Special Issue, we aim to renew knowledge on any aspect involved in plant multiomics and biotechnology for facilitating their applications and improving plant tolerance to abiotic stresses to achieve sustainable plant production in the harsh environments.

Prof. Dr. Yuelin Zhu
Prof. Dr. Huatao Chen
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

  • biotechnology
  • cold
  • drought
  • heat
  • multiomics
  • plant production
  • quality
  • salinity
  • stress tolerance
  • yield

Published Papers (2 papers)

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Research

13 pages, 3843 KiB  
Article
Genome-Wide Identification and Analysis of the MAPK and MAPKK Gene Families in Potato (Solanum tuberosum L.)
by Yutong Shang, Xiaobo Luo, Heng Zhang, Mingjun Chen, Wang Yin, Zhenju Cao, Renju Deng, Yan Li and Fei Li
Agronomy 2023, 13(1), 93; https://doi.org/10.3390/agronomy13010093 - 28 Dec 2022
Cited by 1 | Viewed by 1959
Abstract
Mitogen-activated protein kinase (MAPK) is an important component of the signal transduction pathway, which plays important roles in regulating plant growth and development, and abiotic stress. Potato (Solanum tuberosum L.) is one of the most popular tuber crops in the world. Genome-wide [...] Read more.
Mitogen-activated protein kinase (MAPK) is an important component of the signal transduction pathway, which plays important roles in regulating plant growth and development, and abiotic stress. Potato (Solanum tuberosum L.) is one of the most popular tuber crops in the world. Genome-wide identification and analysis of the MAPK and MAPKK gene family in potato is not clear. A total of 20 MAPK genes and 8 MAPKK genes were identified in the potato genome. A conservative motif analysis showed that the MAPK protein contained a typical TxY phosphorylation site, and the MAPKK protein contained a conservative characteristic motif S/T-x5-S/T. Phylogenetic analysis showed that potato MAPK (mitogen-activated protein kinase) and MAPKK (mitogen-activated protein kinase kinase) were similar to Arabidopsis, including four groups of members A, B, C and D. Gene structure and promoter sequence analysis showed that all 28 gene family members of potato Solanum tuberosum MAPK (StMAPK) and StMAPKK have coding regions (CDS), and family members in the same group have similar intron and exon compositions, and that most cis-acting elements upstream of gene promoters elements have related to stress response. Chromosome location analysis found that MAPKs were unevenly distributed on 11 chromosomes, while MAPKKs were only distributed on chromosomes Chr. 03 and Chr. 12. Collinearity analysis showed that StMAPKK3 and StMAPKK6 have the same common ancestors among potato, pepper, and tomato. qRT-PCR results showed that the relative expressions of StMAPK14 and StMAPKK2 were significantly upregulated under low-temperature stress. These results could provide new insights into the characteristics and evolution of the StMAPK and StMAPKK gene family and facilitate further exploration of the molecular mechanism responsible for potato abiotic stress responses. Full article
(This article belongs to the Special Issue Multiomics and Biotechnological Approaches for Increasing the Abiotic Stress Resistance of Plants)
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15 pages, 5094 KiB  
Article
Rapid Nondestructive Detection of Chlorophyll Content in Muskmelon Leaves under Different Light Quality Treatments
by Ling Ma, Yao Zhang, Yiyang Zhang, Jing Wang, Jianshe Li, Yanming Gao, Xiaomin Wang and Longguo Wu
Agronomy 2022, 12(12), 3223; https://doi.org/10.3390/agronomy12123223 - 19 Dec 2022
Cited by 3 | Viewed by 1633
Abstract
In order to select the light quality suitable for plant growth, a quantitative detection model of chlorophyll content in muskmelon leaves was established to monitor plant growth quickly and accurately. In the paper, muskmelon “Boyang 91” was used as the experimental material, and [...] Read more.
In order to select the light quality suitable for plant growth, a quantitative detection model of chlorophyll content in muskmelon leaves was established to monitor plant growth quickly and accurately. In the paper, muskmelon “Boyang 91” was used as the experimental material, and six different light proportion treatments were set up. Through measuring plant height, stem diameter, number of leaves, nodes, and other growth indicators, in addition to leaf chlorophyll content, the response difference of muskmelon to different light qualities was explored in a plant factory. The hyperspectral imaging technology was used to establish the prediction model for the chlorophyll content of muskmelon. The original spectrum was preprocessed and optimized by five pretreatments, and then the characteristic wavelengths were extracted by six methods. Partial least squares regression (PLSR), least squares support vector machine (LSSVM), and convolutional neural network (CNN) were established for optimal feature wavelength. The results showed that the plant height and stem diameter of the T3 treatment were higher than those of other treatments, and their values were 14.48 (cm) and 5.02 (mm), respectively. The chlorophyll content of the T3 treatment was the highest, and its value was 40.16 (mg/g), which was higher than that of other treatments. Through comprehensive analysis, the T3 treatment (light ratio: 6R/1B/2W, light quantum flux: 360 μmol/(m2·s), photoperiod: 12 h) was optimal. Meanwhile, the average spectral reflectance data of 216 leaf samples were extracted, and the S-G preprocessing method was selected to preprocess the original spectral data (Rc = 0.860, RMSEC = 1.806; Rcv = 0.790, RMSECV = 2.161). By comparing and analyzing the correlation coefficients and root mean square errors of six feature wavelength extraction methods, it was concluded that the variable combination population analysis (VCPA) method had the best model effect for feature wavelength extraction (RP = 0.824, RMSEP = 1.973). Ten characteristic wavelengths ( 396, 409, 457, 518, 532, 565, 687, 691, 701, and 705 nm) extracted by the VCPA method were used to establish the chlorophyll content prediction model, and the chlorophyll content prediction model of S-G-VCPA-CNN had the best performance (Rc = 0.9151, RMSEC = 1.445; Rp = 0.811, RMSEP = 2.055). The results of this study provide data support and a theoretical basis for screening the light ratio of other crops, and also present technical support for online monitoring of crop growth in plant factories. Full article
(This article belongs to the Special Issue Multiomics and Biotechnological Approaches for Increasing the Abiotic Stress Resistance of Plants)
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