Pub Date : 2025-09-17DOI: 10.1016/j.cpb.2025.100547
Samia Mokh , Tania Portoles , Jordi Gamir
Plants use volatile organic compounds (VOCs) as one of several signaling mechanisms to interact with each other and their environment. These chemical messages play a vital role in plant survival, influencing stress responses, defense mechanisms, and interactions with other organisms. However, the precise chemical composition and functional diversity of these volatile blends remain largely unknown. Metabolomic profiling through advanced analytical techniques based on chromatography hyphened to mass spectrometry has become a powerful approach for deciphering this complex chemical dialogue. Choosing the correct methodology is critical for conducting a successful analysis and this review aims to bridge the gap in our understanding by critically analyzing the main factors influencing VOCs analysis. Additionally, we will explore the strengths and limitations of different sampling methodologies, focusing on their effectiveness in profiling complex VOCs mixtures. By optimizing VOCs analytical methodologies, we can improve our understanding of plant-plant communication and stress responses, which may contribute to insights into ecosystems functioning and potential resilience under environmental change.
{"title":"Analytical approaches for volatile organic compounds to understand plant communication","authors":"Samia Mokh , Tania Portoles , Jordi Gamir","doi":"10.1016/j.cpb.2025.100547","DOIUrl":"10.1016/j.cpb.2025.100547","url":null,"abstract":"<div><div>Plants use volatile organic compounds (VOCs) as one of several signaling mechanisms to interact with each other and their environment. These chemical messages play a vital role in plant survival, influencing stress responses, defense mechanisms, and interactions with other organisms. However, the precise chemical composition and functional diversity of these volatile blends remain largely unknown. Metabolomic profiling through advanced analytical techniques based on chromatography hyphened to mass spectrometry has become a powerful approach for deciphering this complex chemical dialogue. Choosing the correct methodology is critical for conducting a successful analysis and this review aims to bridge the gap in our understanding by critically analyzing the main factors influencing VOCs analysis. Additionally, we will explore the strengths and limitations of different sampling methodologies, focusing on their effectiveness in profiling complex VOCs mixtures. By optimizing VOCs analytical methodologies, we can improve our understanding of plant-plant communication and stress responses, which may contribute to insights into ecosystems functioning and potential resilience under environmental change.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100547"},"PeriodicalIF":4.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The quality of horticultural crops is significantly crucial for agricultural yield because of market demand, quality, and the priority of consumers. Macronutrients like nitrogen (N) and potassium (K) are crucial for the normal growth and development of crops. Thus, detecting nutritional deficiency in eggplant is very important for ensuring optimal growth and yield. The traditional approaches are time-consuming and require expert knowledge. The previously reported research in eggplant with a deep learning (DL) approach targeted disease detection and classification work. No work has been reported on eggplant nutritional deficiency detection using the genetic algorithm (GA) based tuning approach with data augmentation. This paper presents a YOLOv9 deep-learning model, optimized with a GA to find the best hyperparameters and data augmentation techniques to increase its robustness. The study used the OLID I dataset to detect nutritional deficiencies in eggplant leaves. The experimental results show that our approach achieved an accuracy of 94.52 %, mAP50 of 94.55 %, mAP50–95 of 93.23 %, Precision of 95.9 %, Recall of 92.8 %, and F1 Score of 94.32 %. These results suggest that the proposed approach is a significant step towards developing a practical application to support farmers in detecting nutrition deficiencies in the eggplant crop.
{"title":"Genetic algorithm enhanced deep learning with data augmentation for nitrogen and potassium deficiency detection in eggplant","authors":"Kamaldeep Joshi , Sahil Hooda , Yashasvi Yadav , Gurdiyal Singh , Ashima Nehra , Narendra Tuteja , Ritu Gill , Sarvajeet Singh Gill","doi":"10.1016/j.cpb.2025.100546","DOIUrl":"10.1016/j.cpb.2025.100546","url":null,"abstract":"<div><div>The quality of horticultural crops is significantly crucial for agricultural yield because of market demand, quality, and the priority of consumers. Macronutrients like nitrogen (N) and potassium (K) are crucial for the normal growth and development of crops. Thus, detecting nutritional deficiency in eggplant is very important for ensuring optimal growth and yield. The traditional approaches are time-consuming and require expert knowledge. The previously reported research in eggplant with a deep learning (DL) approach targeted disease detection and classification work. No work has been reported on eggplant nutritional deficiency detection using the genetic algorithm (GA) based tuning approach with data augmentation. This paper presents a YOLOv9 deep-learning model, optimized with a GA to find the best hyperparameters and data augmentation techniques to increase its robustness. The study used the OLID I dataset to detect nutritional deficiencies in eggplant leaves. The experimental results show that our approach achieved an accuracy of 94.52 %, mAP50 of 94.55 %, mAP50–95 of 93.23 %, Precision of 95.9 %, Recall of 92.8 %, and F1 Score of 94.32 %. These results suggest that the proposed approach is a significant step towards developing a practical application to support farmers in detecting nutrition deficiencies in the eggplant crop.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100546"},"PeriodicalIF":4.5,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-06DOI: 10.1016/j.cpb.2025.100533
Fuyad Hasan Bhoyan , Md Humaion Kabir Mehedi , Meharun Ohona , Sharmin Rashid , M.F. Mridha
Medicinal plants are important because of their diverse benefits. However, the accurate identification of these plants poses a significant challenge to the healthcare, agriculture, and pharmaceutical industries. Visual similarities between species and environmental variations complicate this process. Although traditional deep learning (DL) and machine learning (ML) approaches have demonstrated promising results in classifying medicinal plants, the question remains as to whether a model can perform more effectively and multidimensionally, incorporating features such as a plain and real image background and lightweight design. This study introduced a dual-attention convolutional neural network based on the DenseNet121 model named ”DenseDANet,”. The dual attention mechanisms enhance classification accuracy and effectiveness. The model employs Local Interpretable Model-Agnostic Explanations (LIME) to improve transparency, thereby enabling reliable and explainable identification of medicinal plants. Furthermore, this model outperformed transformer-based models, including Swin-T, MaxVit-T, FastVit-MA36, Vit-B16, and deep learning convolutional neural networks (CNNs), such as VGG19, ResNet50, ConvNextV2-T, and DenseNet161. DenseDANet was trained and evaluated on two public datasets: DS1 (Bangladeshi Medicinal Plant Dataset) and DS2 (BDMediLeaves), collectively comprising original 7029 images from 20 classes. A 70:20:10 split was used for training, validation, and testing, respectively, achieving the highest test accuracy of 99.50%. The proposed model offers a lightweight, interpretable, and efficient method for identifying medicinal plants. It significantly benefits traditional medicine, pharmaceutical research, and biodiversity conservation through its accurate specifications, making it ideal for real-time applications and reducing computational costs.
{"title":"An efficient dual-attention guided deep learning model with interpretability for identifying medicinal plants","authors":"Fuyad Hasan Bhoyan , Md Humaion Kabir Mehedi , Meharun Ohona , Sharmin Rashid , M.F. Mridha","doi":"10.1016/j.cpb.2025.100533","DOIUrl":"10.1016/j.cpb.2025.100533","url":null,"abstract":"<div><div>Medicinal plants are important because of their diverse benefits. However, the accurate identification of these plants poses a significant challenge to the healthcare, agriculture, and pharmaceutical industries. Visual similarities between species and environmental variations complicate this process. Although traditional deep learning (DL) and machine learning (ML) approaches have demonstrated promising results in classifying medicinal plants, the question remains as to whether a model can perform more effectively and multidimensionally, incorporating features such as a plain and real image background and lightweight design. This study introduced a dual-attention convolutional neural network based on the DenseNet121 model named ”DenseDANet,”. The dual attention mechanisms enhance classification accuracy and effectiveness. The model employs Local Interpretable Model-Agnostic Explanations (LIME) to improve transparency, thereby enabling reliable and explainable identification of medicinal plants. Furthermore, this model outperformed transformer-based models, including Swin-T, MaxVit-T, FastVit-MA36, Vit-B16, and deep learning convolutional neural networks (CNNs), such as VGG19, ResNet50, ConvNextV2-T, and DenseNet161. DenseDANet was trained and evaluated on two public datasets: DS1 (Bangladeshi Medicinal Plant Dataset) and DS2 (BDMediLeaves), collectively comprising original 7029 images from 20 classes. A 70:20:10 split was used for training, validation, and testing, respectively, achieving the highest test accuracy of 99.50%. The proposed model offers a lightweight, interpretable, and efficient method for identifying medicinal plants. It significantly benefits traditional medicine, pharmaceutical research, and biodiversity conservation through its accurate specifications, making it ideal for real-time applications and reducing computational costs.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100533"},"PeriodicalIF":4.5,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The combined activity of plant growth promoting rhizobacteria (PGPR) and nanomaterials offers a ray of hope in the pursuit of sustainable production of crops, beyond the capacity of either of the two used alone. Plant stress resistance, effective nutrient use and reduction in the rate of environmental degradation are promoted by the all-inclusive use of both techniques together. In this review, we provide a comprehensive overview of the role played by nanoparticles in promoting the development of crops. It is well known that PGPRs function to promote biological nitrogen fixation and hormone production in plants. On the other hand, nanoparticles promote the slow release of nutrients and the balancing of plant hormones. However, when combined, their individual functions can create a compounded effect; nanoparticles symbiotically associated with PGPR creates a nutrient-rich environment for them to proliferate in the rhizosphere leading to increased production of key plant metabolites, while PGPR, in return, improves the bioavailability of nutrients being warehoused by the nanoparticles, thus maximizing nutrient assimilation by plants. This review infuses a novel perspective on the molecular and eco-friendly basis for this symbiosis. Existing studies have demonstrated significant improvement in plant biomass, physiological, biochemical and molecular parameters because of the co-application of PGPR and nanoparticles. The challenges and regulatory considerations associated with the use of nanomaterials, current safety assessments, and public perception are major constraints hampering its development. The current work further reinforces the need for continued research into the application of nanobiofertilizers, gaining knowledge of their lasting consequences on ecosystem sustainability, with the hope of optimizing their benefits while ensuring effective and safe integration into farming practices.
{"title":"Synergy for plant health - plant growth-promoting rhizobacteria and nanomaterials","authors":"Okainemen Godfrey Oribhabor , Damian C. Onwudiwe , Muthukrishnan Sathiyabama , Olubukola Oluranti Babalola","doi":"10.1016/j.cpb.2025.100545","DOIUrl":"10.1016/j.cpb.2025.100545","url":null,"abstract":"<div><div>The combined activity of plant growth promoting rhizobacteria (PGPR) and nanomaterials offers a ray of hope in the pursuit of sustainable production of crops, beyond the capacity of either of the two used alone. Plant stress resistance, effective nutrient use and reduction in the rate of environmental degradation are promoted by the all-inclusive use of both techniques together. In this review, we provide a comprehensive overview of the role played by nanoparticles in promoting the development of crops. It is well known that PGPRs function to promote biological nitrogen fixation and hormone production in plants. On the other hand, nanoparticles promote the slow release of nutrients and the balancing of plant hormones. However, when combined, their individual functions can create a compounded effect; nanoparticles symbiotically associated with PGPR creates a nutrient-rich environment for them to proliferate in the rhizosphere leading to increased production of key plant metabolites, while PGPR, in return, improves the bioavailability of nutrients being warehoused by the nanoparticles, thus maximizing nutrient assimilation by plants. This review infuses a novel perspective on the molecular and eco-friendly basis for this symbiosis. Existing studies have demonstrated significant improvement in plant biomass, physiological, biochemical and molecular parameters because of the co-application of PGPR and nanoparticles. The challenges and regulatory considerations associated with the use of nanomaterials, current safety assessments, and public perception are major constraints hampering its development. The current work further reinforces the need for continued research into the application of nanobiofertilizers, gaining knowledge of their lasting consequences on ecosystem sustainability, with the hope of optimizing their benefits while ensuring effective and safe integration into farming practices.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100545"},"PeriodicalIF":4.5,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-05DOI: 10.1016/j.cpb.2025.100544
Xiumei Luo , Ying Wang , Jiasui Zhan , Maozhi Ren
Interstellar migration offers great potential for expanding human habitable space. As a powerful entropy-reducing system, plants convert simple, disordered chemical elements into complex, ordered organic macromolecules. They are expected to grow successfully on some planets and meet the essential nutritional and medical requirements for future interstellar migration. Taking Mars as a model planet, we analyze the basic physical, chemical and biological laws of plant growth on the terrestrial planet and propose terrestrial planetary plants (TPPs) for future terrestrial planetary agriculture (TPA). Biotechnological improvement of 25 TPPs candidates screened from 450,000 plants would reduce the dependence of interstellar migrants on farmland, poultry, livestock and hospitals, thus achieving self-sufficiency in food and medicine on Mars and other terrestrial planets. The TPPs are expected to break the 10 % rule in traditional food chains and provide new insights into enhancing agricultural production and food security on the earth.
{"title":"Terrestrial planetary plants: Essential preparations for interstellar migration","authors":"Xiumei Luo , Ying Wang , Jiasui Zhan , Maozhi Ren","doi":"10.1016/j.cpb.2025.100544","DOIUrl":"10.1016/j.cpb.2025.100544","url":null,"abstract":"<div><div>Interstellar migration offers great potential for expanding human habitable space. As a powerful entropy-reducing system, plants convert simple, disordered chemical elements into complex, ordered organic macromolecules. They are expected to grow successfully on some planets and meet the essential nutritional and medical requirements for future interstellar migration. Taking Mars as a model planet, we analyze the basic physical, chemical and biological laws of plant growth on the terrestrial planet and propose terrestrial planetary plants (TPPs) for future terrestrial planetary agriculture (TPA). Biotechnological improvement of 25 TPPs candidates screened from 450,000 plants would reduce the dependence of interstellar migrants on farmland, poultry, livestock and hospitals, thus achieving self-sufficiency in food and medicine on Mars and other terrestrial planets. The TPPs are expected to break the 10 % rule in traditional food chains and provide new insights into enhancing agricultural production and food security on the earth.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100544"},"PeriodicalIF":4.5,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145004486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-05DOI: 10.1016/j.cpb.2025.100543
Arnold Rácz, Zoltán Katona, Éva Hideg
Exposing a single leaf of tobacco plants to ultraviolet (UV) radiation, we detected eustress-like pigment and antioxidant responses not only in the directly treated leaf itself but also in the leaf above it (the systemic leaf), which was not directly exposed to UV radiation. To the best of our knowledge, this study is the first to investigate the systemic UV responses in plants. The experiments used low-dose, supplemental UV irradiation indoors (two hours daily, for two days), which had no significant effect on photosynthesis in the directly exposed leaves but influenced their antioxidant status. Systemic leaves showed increased H2O2 levels, indicating the involvement of reactive oxygen species in the underlying complex signalling cascade. Metabolic changes in systemic leaves are driven by increased carbon dioxide assimilation, supported by more open stomata. Compared with the leaves of untreated plants of the same age, systemic leaves exhibited higher adaxial flavonoid levels and more efficient H2O2 housekeeping (higher peroxidase and catalase activities and lower superoxide dismutase activities). The role of H2O2 in the systemic UV effect was supported by another experiment, showing that direct H2O2 treatment increased the H2O2 levels in a systemic manner in the leaves above the treated ones. Notably, unlike its direct effects, the systemic effects of UV radiation did not enhance hydroxyl radical scavenging activity, indicating the unique nature of direct UV-driven responses. The possibility presented here to induce eustress-like antioxidant responses in distal leaves without direct UV exposure could be relevant to indoor plant growth systems as a potential biofortification tool.
{"title":"Systemic antioxidant effects of low-dose ultraviolet treatment on tobacco leaves are mediated by hydrogen peroxide","authors":"Arnold Rácz, Zoltán Katona, Éva Hideg","doi":"10.1016/j.cpb.2025.100543","DOIUrl":"10.1016/j.cpb.2025.100543","url":null,"abstract":"<div><div>Exposing a single leaf of tobacco plants to ultraviolet (UV) radiation, we detected eustress-like pigment and antioxidant responses not only in the directly treated leaf itself but also in the leaf above it (the systemic leaf), which was not directly exposed to UV radiation. To the best of our knowledge, this study is the first to investigate the systemic UV responses in plants. The experiments used low-dose, supplemental UV irradiation indoors (two hours daily, for two days), which had no significant effect on photosynthesis in the directly exposed leaves but influenced their antioxidant status. Systemic leaves showed increased H<sub>2</sub>O<sub>2</sub> levels, indicating the involvement of reactive oxygen species in the underlying complex signalling cascade. Metabolic changes in systemic leaves are driven by increased carbon dioxide assimilation, supported by more open stomata. Compared with the leaves of untreated plants of the same age, systemic leaves exhibited higher adaxial flavonoid levels and more efficient H<sub>2</sub>O<sub>2</sub> housekeeping (higher peroxidase and catalase activities and lower superoxide dismutase activities). The role of H<sub>2</sub>O<sub>2</sub> in the systemic UV effect was supported by another experiment, showing that direct H<sub>2</sub>O<sub>2</sub> treatment increased the H<sub>2</sub>O<sub>2</sub> levels in a systemic manner in the leaves above the treated ones. Notably, unlike its direct effects, the systemic effects of UV radiation did not enhance hydroxyl radical scavenging activity, indicating the unique nature of direct UV-driven responses. The possibility presented here to induce eustress-like antioxidant responses in distal leaves without direct UV exposure could be relevant to indoor plant growth systems as a potential biofortification tool.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100543"},"PeriodicalIF":4.5,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-02DOI: 10.1016/j.cpb.2025.100539
Odongkara Peter, Sang-Mo Kang, Muhammad Imran, Kil-Ung Kim, In-Jung Lee
Despite its toxicity, glufosinate ammonium (G-A) remains a popular herbicide. While microbial and plant-based detoxification have advanced, gaps still exist. This study aims to unravel strains with diverse metabolic and biochemical capabilities for G-A degradation. Herein, rhizospheric isolates from non-G-A contaminated sites were assayed for detoxification and plant growth promotion (PGP) using gradient concentration (0.0, 1.0, 1.5, 2.0, and 2.5 mM) over 84-hours. In between, PGP traits, including production of indole acetic acid (IAA), exopolysaccharides (EPS), siderophores, and phosphate solubilization and – secretion of sugars and amino acids were assayed. Six G-A tolerant isolates were identified through 16S rDNA analysis. Inoculation of soybean with cultures (1.4 × 10⁻⁴ CFU/mL, OD₆₀₀ nm) and 2.5 mM G-A treatment (1.0 mL/plant) increased germination (90 %), lengths of radicle (6.6 cm), mesocotyl (4.5 cm), and total fresh weight (1.83 mg) compared to controls (100 %, 7.12 cm, 5.1 cm, and 1.90 mg, respectively), and enhanced catalase, superoxide dismutase and glutathione antioxidants activities by 82, 78, and 60 percent respectively. Soil drench and foliar treatment of isolates and G-A in pot trials showed differential resistance, enhanced biomass, and increased chlorophyll concentration. Phylogenetic analysis revealed significant sequence similarities; OC-1042 to Stenotrophomonas sp. (97.5 %), OC-1054 to Klebsiella penumoniae (99 %), RB-1011, GH-1050, OC-1040 by 100, 99.9, and 99.8 percent respectively to Serratia marcescens, and UF-1050 to Pseudomonas nitroreducens (99.9 %). In conclusion, the diversity of G-A tolerant isolates facilitates detoxification, colonization, plant growth, and resilience. This variation contributes to their adaptability and roles, highlighting a path toward sustainable weed management.
{"title":"Functional profiling of novel glufosinate ammonium-tolerant, and secondary metabolite-secreting plant growth-promoting rhizobacteria","authors":"Odongkara Peter, Sang-Mo Kang, Muhammad Imran, Kil-Ung Kim, In-Jung Lee","doi":"10.1016/j.cpb.2025.100539","DOIUrl":"10.1016/j.cpb.2025.100539","url":null,"abstract":"<div><div>Despite its toxicity, glufosinate ammonium (G-A) remains a popular herbicide. While microbial and plant-based detoxification have advanced, gaps still exist. This study aims to unravel strains with diverse metabolic and biochemical capabilities for G-A degradation. Herein, rhizospheric isolates from non-G-A contaminated sites were assayed for detoxification and plant growth promotion (PGP) using gradient concentration (0.0, 1.0, 1.5, 2.0, and 2.5 mM) over 84-hours. In between, PGP traits, including production of indole acetic acid (IAA), exopolysaccharides (EPS), siderophores, and phosphate solubilization and – secretion of sugars and amino acids were assayed. Six G-A tolerant isolates were identified through 16S rDNA analysis. Inoculation of soybean with cultures (1.4 × 10⁻⁴ CFU/mL, OD₆₀₀ nm) and 2.5 mM G-A treatment (1.0 mL/plant) increased germination (90 %), lengths of radicle (6.6 cm), mesocotyl (4.5 cm), and total fresh weight (1.83 mg) compared to controls (100 %, 7.12 cm, 5.1 cm, and 1.90 mg, respectively), and enhanced catalase, superoxide dismutase and glutathione antioxidants activities by 82, 78, and 60 percent respectively. Soil drench and foliar treatment of isolates and G-A in pot trials showed differential resistance, enhanced biomass, and increased chlorophyll concentration. Phylogenetic analysis revealed significant sequence similarities; OC-1042 to <em>Stenotrophomonas sp.</em> (97.5 %), OC-1054 to <em>Klebsiella penumoniae</em> (99 %), RB-1011, GH-1050, OC-1040 by 100, 99.9, and 99.8 percent respectively to <em>Serratia marcescens</em>, and UF-1050 to <em>Pseudomonas nitroreducens</em> (99.9 %). In conclusion, the diversity of G-A tolerant isolates facilitates detoxification, colonization, plant growth, and resilience. This variation contributes to their adaptability and roles, highlighting a path toward sustainable weed management.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100539"},"PeriodicalIF":4.5,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-30DOI: 10.1016/j.cpb.2025.100542
Marko Bajus , Zuzana Vivodová , Michaela Bačovčinová , Eva Labancová , Danica Kučerová , Ágnes Horváthová , Kristína Holeková , Diana Hačkuličová , Renáta Vadkertiová , Karin Kollárová
Drought stress can significantly affect maize growth; hence, new substances with a potential to alleviate drought-induced damage in plants are being investigated. Here, we studied the biostimulant potential and mechanisms of the yeast Papiliotrema laurentii CCY 17–3–24. The maize grains were treated with P. laurentii suspensions of different yeast concentrations (106, 107, 108, and 109 cells ml−1) during the imbibition and germination. The yeast did not have plant-growth promoting effects in well-watered plants; however, it stimulated the growth of the drought-stressed maize in the concentration 10⁷ cells ml−1 (e.g., shoot dry weight by 21.6 %). Furthermore, the relative water content and oxidative stress were improved in plants treated with the yeast compared to drought-stressed plants (e.g., decreased H2O2 concentration by 46.1 % in roots). The expression of LEA genes, which can be triggered by hormones, was significantly downregulated in yeast-treated plants compared to untreated plants. Although the yeast-treated plants showed slightly improved hormone concentrations (IAA, ABA) in drought compared to untreated plants (IAA concentration increased approximately by 19 %), the action of P. laurentii was not likely connected to its ability to produce hormones, neither its ability to change the accumulation of proline. However, based on the oleaginous nature of P. laurentii, its positive influence on plants suffering from drought can be possibly explained by the production of fatty acids and their uptake by plants. This was supported by the increased concentration of fatty acids, especially in the roots of the yeast-treated plants (by 205.3 %).
{"title":"The yeast Papiliotrema laurentii alleviates drought-induced stress in maize and affects oxidative status, LEA genes, hormone concentrations, and fatty acid allocation","authors":"Marko Bajus , Zuzana Vivodová , Michaela Bačovčinová , Eva Labancová , Danica Kučerová , Ágnes Horváthová , Kristína Holeková , Diana Hačkuličová , Renáta Vadkertiová , Karin Kollárová","doi":"10.1016/j.cpb.2025.100542","DOIUrl":"10.1016/j.cpb.2025.100542","url":null,"abstract":"<div><div>Drought stress can significantly affect maize growth; hence, new substances with a potential to alleviate drought-induced damage in plants are being investigated. Here, we studied the biostimulant potential and mechanisms of the yeast <em>Papiliotrema laurentii</em> CCY 17–3–24. The maize grains were treated with <em>P. laurentii</em> suspensions of different yeast concentrations (10<sup>6</sup>, 10<sup>7</sup>, 10<sup>8</sup>, and 10<sup>9</sup> cells ml<sup>−1</sup>) during the imbibition and germination. The yeast did not have plant-growth promoting effects in well-watered plants; however, it stimulated the growth of the drought-stressed maize in the concentration 10⁷ cells ml<sup>−1</sup> (e.g., shoot dry weight by 21.6 %). Furthermore, the relative water content and oxidative stress were improved in plants treated with the yeast compared to drought-stressed plants (e.g., decreased H<sub>2</sub>O<sub>2</sub> concentration by 46.1 % in roots). The expression of <em>LEA</em> genes, which can be triggered by hormones, was significantly downregulated in yeast-treated plants compared to untreated plants. Although the yeast-treated plants showed slightly improved hormone concentrations (IAA, ABA) in drought compared to untreated plants (IAA concentration increased approximately by 19 %), the action of <em>P. laurentii</em> was not likely connected to its ability to produce hormones, neither its ability to change the accumulation of proline. However, based on the oleaginous nature of <em>P. laurentii</em>, its positive influence on plants suffering from drought can be possibly explained by the production of fatty acids and their uptake by plants. This was supported by the increased concentration of fatty acids, especially in the roots of the yeast-treated plants (by 205.3 %).</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100542"},"PeriodicalIF":4.5,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-30DOI: 10.1016/j.cpb.2025.100540
Peng Xu , Chenxin Zhao , Shuxuan Li , Shuoxuan Li , Aifang Li , Jie Zhao , Aoqi Ma , Qianqian Wang , Dandan Guo , Jin Zhou , Shuying Feng
Plant genetic engineering serves as a crucial technology in enhancing crop quality, promoting pharmaceutical product biosynthesis, and changing agricultural practices. While conventional nuclear transgenic systems demonstrate generally stable and efficient transgene expression profiles, infrequent but persistent technical challenges-including gene silencing as well as low or unstable expression-continue to hinder precise genetic manipulation of nuclear genomes. Since the characteristics of maternal inheritance of plastid genome, chloroplast transformation circumvents this limitation and the risk of transgenic ecological pollution is greatly reduced. Although chloroplast gene engineering (CGE) has some unique advantages, it also has its own disadvantages, including low-efficiency transformation, a limited ability to target organelles, and a low number of species that can transform chloroplast genomes. Over the past few years, the establishment of several novel gene editing technologies has offered beneficial tools to solve these issues. This review explores advanced CGE tools (transcription activator-like effector nucleases, clustered regularly interspaced short palindromic repeats/CRISPR-associated systems, base editors, and prime editors) for sustainable agriculture, focusing on crop yield improvement, accelerated breeding of resistant varieties, enhanced stress tolerance, and optimized growth traits. Additionally, we thoroughly discuss the current challenges in CGE as well as its potential and future development. Moreover, new technologies and tools, such as nanotechnology, designer pentatricopeptide repeat proteins, and aptamers, are also considered with the aim of improving gene targeting and expression levels in CGE, which could potentially promote advances in CGE and extend its utility for different applications. Challenges in implementation and regulatory considerations are also discussed.
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