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Plants
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Responses of Crops to Abiotic Stress—2nd Edition
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Responses of Crops to Abiotic Stress—2nd Edition

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Response to Abiotic Stress and Climate Change".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 1764

Special Issue Editors

Dr. Georgios Koubouris

E-Mail Website
Guest Editor
Hellenic Agricultural Organization ELGO-DIMITRA, Olive Cultivation Lab, Institute of Olive Tree, Subtropical Crops and Viticulture, 73134 Chania, Greece
Interests: climate change; agricultural sustainability; circular economy; soil, water and biodiversity conservation; remote sensing; plant breeding; ecosystem services; olive growing
Special Issues, Collections and Topics in MDPI journals
Dr. Giora Ben-Ari

E-Mail Website
Guest Editor
Volcani Center, Institute of Plant Sciences, ARO, Rishon LeZion 7528809, Israel
Interests: olive pollination; biochemical and anatomical characterization of the olive abscission zone in fruits and leaves; olive breeding program; the effects of climate change on olive productivity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The agricultural industry is currently undergoing a marked transformation to address economic and climatic challenges. Global climate change has been identified as a major threat to the survival of natural ecosystems. It involves a series of dynamic alterations in environmental conditions that affect both abiotic and biotic components of the world. These changes, induced by heat waves, varying rainfall intensity and increasing CO2 concentration and temperature, can lead to a rise in new pests, weeds and pathogens, thus affecting plant physiology. Abiotic stresses cause interrelated changes in morphological, physiological, biochemical and molecular properties that adversely affect plant growth and productivity, ultimately leading to a reduced yield. Additionally, it has been proven that the sexual reproductive phase in plants is vulnerable to the negative effects of abiotic stress.

The aim of this Special Issue is to compile the latest research advances on the effects of climate change on crop yield and quality. We welcome original research papers, perspectives, opinions, reviews, modeling approaches and methods that explore how to adapt agriculture to current and future environmental challenges.

Dr. Georgios Koubouris
Dr. Giora Ben-Ari
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

  • climate change
  • stress
  • plant physiology
  • resilience
  • plant phenotyping
  • drought
  • water
  • soil
  • biodiversity
  • ecosystem
  • ecology

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Related Special Issue

Published Papers (4 papers)

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Research

26 pages, 11026 KiB  
Article
Machine Learning-Driven Identification of Key Environmental Factors Influencing Fiber Yield and Quality Traits in Upland Cotton
by Mohamadou Souaibou, Haoliang Yan, Panhong Dai, Jingtao Pan, Yang Li, Yuzhen Shi, Wankui Gong, Haihong Shang, Juwu Gong and Youlu Yuan
Plants 2025, 14(13), 2053; https://doi.org/10.3390/plants14132053 - 4 Jul 2025
Viewed by 324
Abstract
Understanding the influence of environmental factors on cotton performance is crucial for enhancing yield and fiber quality in the context of climate change. This study investigates genotype-by-environment (G×E) interactions in cotton, using data from 250 recombinant inbred lines (CCRI70 RILs) cultivated across 14 [...] Read more.
Understanding the influence of environmental factors on cotton performance is crucial for enhancing yield and fiber quality in the context of climate change. This study investigates genotype-by-environment (G×E) interactions in cotton, using data from 250 recombinant inbred lines (CCRI70 RILs) cultivated across 14 diverse environments in China’s major cotton cultivation areas. Our findings reveal that environmental effects predominantly influenced yield-related traits (boll weight, lint percentage, and the seed index), contributing to 34.7% to 55.7% of their variance. In contrast fiber quality traits showed lower environmental sensitivity (12.3–27.0%), with notable phenotypic plasticity observed in the boll weight, lint percentage, and fiber micronaire. Employing six machine learning models, Random Forest demonstrated superior predictive ability (R2 = 0.40–0.72; predictive Pearson correlation = 0.63–0.86). Through SHAP-based interpretation and sliding-window regression, we identified key environmental drivers primarily active during mid-to-late growth stages. This approach effectively reduced the number of influential input variables to just 0.1–2.4% of the original dataset, spanning 2–9 critical time windows per trait. Incorporating these identified drivers significantly improved cross-environment predictions, enhancing Random Forest accuracy by 0.02–0.15. These results underscore the strong potential of machine learning to uncover critical temporal environmental factors underlying G×E interactions and to substantially improve predictive modeling in cotton breeding programs, ultimately contributing to more resilient and productive cotton cultivation. Full article
(This article belongs to the Special Issue Responses of Crops to Abiotic Stress—2nd Edition)
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24 pages, 4564 KiB  
Article
Variation of Seed Yield and Nutritional Quality Traits of Lentil (Lens culinaris Medikus) Under Heat and Combined Heat and Drought Stresses
by Hasnae Choukri, Khawla Aloui, Noureddine El Haddad, Kamal Hejjaoui, Abdelaziz Smouni and Shiv Kumar
Plants 2025, 14(13), 2019; https://doi.org/10.3390/plants14132019 - 1 Jul 2025
Viewed by 320
Abstract
Lentil (Lens culinaris Medikus) is a critical food crop offering high protein and essential micronutrients. However, its productivity and nutritional quality are increasingly threatened by climate change. In this study, 36 lentil genotypes were evaluated across two Moroccan locations under normal, heat [...] Read more.
Lentil (Lens culinaris Medikus) is a critical food crop offering high protein and essential micronutrients. However, its productivity and nutritional quality are increasingly threatened by climate change. In this study, 36 lentil genotypes were evaluated across two Moroccan locations under normal, heat stress, and combined heat and drought stresses. Significant effects of genotype, environment, and their interactions were observed on seed yield, seed size, cooking time, and nutritional quality. Heat and drought stresses caused substantial reductions in seed yield (up to 40% under combined stress), protein content, iron, and zinc concentration, and increased phytic acid levels, which negatively impacted iron and zinc bioavailability. Cooking time significantly decreased under stress conditions, with up to 54% reduction under combined heat and drought stresses at Annoceur research station. Correlation analysis revealed complex trade-offs among yield, nutritional quality, and cooking traits under stress conditions. Principal component analysis and GGE biplot analyses identified genotypes with superior yield, micronutrient concentration, and cooking time stability across environments. Genotypes such as G32, G3, and G36 combined high iron and zinc levels; G13 and G30 showed low phytic acid, while G 15 exhibited the shortest cooking time. These genotypes also demonstrated adaptability across the tested environment. This study highlights the potential of selecting climate-resilient, nutrient-dense lentil genotypes to support breeding efforts aimed at improving food security in the face of global climate variability. These genotypes can be suggested as elite climate-resilient parental lines to support breeders in enhancing lentil yield, nutritional quality, and stability under multiple stress conditions. Full article
(This article belongs to the Special Issue Responses of Crops to Abiotic Stress—2nd Edition)
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15 pages, 6310 KiB  
Article
Transcriptome and Metabolome Reveal Ferulic Acid as a Critical Phenylpropanoid for Drought Resistance in Dendrobium sinense
by Huiyan You, Ao Yi, Qiongjian Ou, Jia Wang and Jun Niu
Plants 2025, 14(12), 1841; https://doi.org/10.3390/plants14121841 - 15 Jun 2025
Viewed by 441
Abstract
As an endemic epiphytic orchid of Hainan Island, Dendrobium sinense exhibits remarkable ecological and economic value, serving important ornamental and medicinal purposes. The combination of its epiphytic growth habit and the distinct dry season in Hainan (November–May) under the subtropical monsoon climate makes [...] Read more.
As an endemic epiphytic orchid of Hainan Island, Dendrobium sinense exhibits remarkable ecological and economic value, serving important ornamental and medicinal purposes. The combination of its epiphytic growth habit and the distinct dry season in Hainan (November–May) under the subtropical monsoon climate makes D. sinense particularly vulnerable to recurrent drought stress. Therefore, elucidating its drought tolerance mechanisms offers critical insights for both conservation strategies and stress resistance studies in D. sinense. Using polyethylene glycol (PEG)-induced drought stress, chlorophyll content decreased significantly with increasing PEG concentration, while MDA and proline content, SOD, POD CAT, and APX activity showed a significant increase. The analysis of physiological indicators indicated that plants have been subjected to drought stress. We then conducted the joint analysis of the metabolomics and transcriptomics data. Cluster analysis of differentially expressed genes and metabolites showed that drought stress markedly upregulates phenylpropanoid biosynthesis, with ferulic acid (FA) identified as a pivotal metabolite. Exogenous FA application alleviated drought-induced chlorophyll degradation in D. sinense seedlings. Heterologous expression of DsCOMT (a key FA biosynthetic gene) in Arabidopsis thaliana significantly enhanced drought survival. These results demonstrate the crucial role of FA in drought resistance and provide key insights into drought-related metabolic mechanisms. Full article
(This article belongs to the Special Issue Responses of Crops to Abiotic Stress—2nd Edition)
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31 pages, 7842 KiB  
Article
Genome-Wide Characterization and Functional Analysis of CsDOF Transcription Factors in Camellia sinensis cv. Tieguanyin Under Combined Heat–Drought Stress
by Yingxin Wen, Cunyi Tan, Yujie Zhang, Hua Wu, Dian Chen, Heng Yue, Zekai Ding, Shijiang Cao and Kehui Zheng
Plants 2025, 14(12), 1829; https://doi.org/10.3390/plants14121829 - 14 Jun 2025
Viewed by 507
Abstract
Tieguanyin tea, celebrated as one of China’s top ten famous teas, is highly regarded for its unique flavor and taste. However, recent intensification of global warming has escalated the occurrence of abiotic stresses, posing significant threats to the growth, development, yield, and quality [...] Read more.
Tieguanyin tea, celebrated as one of China’s top ten famous teas, is highly regarded for its unique flavor and taste. However, recent intensification of global warming has escalated the occurrence of abiotic stresses, posing significant threats to the growth, development, yield, and quality of Tieguanyin tea plants. DOF (DNA-binding one zinc finger protein), a plant-specific transcription factor, plays a critical role in plant development and stress response. In this study, we identified and analyzed 58 CsDOF genes across the whole genome, which were found to be randomly and unevenly distributed across 15 chromosomes. A phylogenetic tree was constructed using DOF genes from Arabidopsis thaliana and Tieguanyin, categorizing these genes into 10 subgroups. Collinearity analysis revealed homologous gene pairs between CsDOF and OsDOF(19 pairs), StDOF (101 pairs), and ZmDOF (24 pairs). Cis-acting element analysis indicated that CsDOF genes contain elements related to both stress and hormone responses. Heat map analysis demonstrated that subfamily C2 predominantly regulates the growth and development of roots, stems, and leaves in Tieguanyin. Tertiary structure analysis of CsDOF proteins revealed diverse structures, underscoring the functional variability within the CsDOF gene family. Furthermore, qRT-PCR analysis was employed to assess the expression profiles of 13 CsDOF genes under high-temperature and drought conditions. Notably, CsDOF51 and CsDOF12 exhibited significant expression changes under drought and high-temperature stress, respectively, while CsDOF44 showed significant changes under both conditions. This study provides foundational knowledge of the CsDOF gene family and offers novel insights for enhancing the drought and heat tolerance of Tieguanyin tea. Full article
(This article belongs to the Special Issue Responses of Crops to Abiotic Stress—2nd Edition)
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