Frontiers in Plant Science最新文献

{"title":"Induced biochemical variations in maize parental lines affect the life table and age-specific reproductive potential of <i>Spodoptera frugiperda</i> (J.E. Smith).","authors":"K S Ishwarya Lakshmi, Mukesh K Dhillon, Ganapati Mukri, K R Mahendra, K V Gowtham, Aditya K Tanwar","doi":"10.3389/fpls.2024.1517848","DOIUrl":"https://doi.org/10.3389/fpls.2024.1517848","url":null,"abstract":"<p><p>In recent years, the fall armyworm, <i>Spodoptera frugiperda</i> has rapidly emerged as a global invasive pest, challenging the maize production and leading to considerable economic losses. Developing resistant hybrids is essential for sustainable maize cultivation, which requires a comprehensive understanding of resistance traits and the underlying mechanisms in parental lines. To address this need, the present study aimed to identify the sources of resistance, age and stage-specific effects and role of phytochemicals in plant defense against <i>S. frugiperda</i> in thirty diverse maize parental lines [17 female (A) and 13 male (R) lines]. The study revealed that the larvae fed on maize A-lines CML 565, AI 501, AI 544 and PDIM 639, and R-lines AI 125, AI 542, AI 155, AI 1100 and PML 105 exhibited a reduced intrinsic (r) and finite rate of increase (λ), and net (R₀) and gross reproduction rates (GRR); while, increased mean generation time (T) and doubling time (DT). Among these, A-lines CML 565, PDIM 639 and AI 544, and R-lines AI 125, AI 155 and AI 1100 showed higher detrimental effect on reproductive value of <i>S. frugiperda</i>. Aforesaid A- and R-lines were also found with greater increase in insect-induced test phytochemicals compared to other lines, accounting for 25.0 to 72.8% variation in the life table parameters, indicating antibiosis effect on <i>S. frugiperda</i>. Among the test phytochemicals, tannins, CAT, PAL, TAL and APX inflicted greater effect, indicating their role in induced-biochemical defense against <i>S. frugiperda.</i></p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1517848"},"PeriodicalIF":4.1,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11663683/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular basis of resistance to leaf spot disease in oil palm.","authors":"Cahyo S Wibowo, Ricki Susilo, Reza Ernawan, Ardha Apriyanto, Mohammed O Alshaharni, Graham R Smith, Angharad M R Gatehouse, Martin G Edwards","doi":"10.3389/fpls.2024.1458346","DOIUrl":"https://doi.org/10.3389/fpls.2024.1458346","url":null,"abstract":"<p><strong>Introduction: </strong>Leaf spot disease caused by the fungal pathogen <i>Curvularia oryzae</i> is one of the most common diseases found in oil palm (<i>Elaeis guineensis</i>) nurseries in South East Asia, and is most prevalent at the seedling stage. Severe infections result in localized necrotic regions of leaves that rapidly spread within nurseries leading to poor quality seedlings and high economic losses.</p><p><strong>Methods: </strong>To understand the molecular mechanisms of this plant-pathogen interaction, RNA-Seq was used to elucidate the transcriptomes of three oil palm genotypes with contrasting pathogen responses (G10 and G12, resistant and G14, susceptible) following infection with <i>C. oryzae</i> spores. Transcriptomes were obtained from Illumina NovaSeq 6000 sequencing of mRNA at four different time points (day 0, before treatment; day 1, 7, and 21 post treatment).</p><p><strong>Results and discussion: </strong>Analysis of differentially expressed gene (DEG) profiles in these three genotypes provided an overview of the genes involved in the plant defence. Genes involved in disease resistance, phytohormone biosynthesis, gene regulation (transcription factors), and those encoding proteins associated with cell wall hardening were identified and likely contribute to the resistance of oil palm to <i>C. oryzae</i>. Such genes represent good candidates for targets to enhance oil palm productivity and resilience through molecular breeding approaches.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1458346"},"PeriodicalIF":4.1,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11663676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of stripe rust resistance and analysis of resistance genes in wheat genotypes from Pakistan and Southwest China.","authors":"Sakina Abbas, Yunfang Li, Jing Lu, Jianming Hu, Xinnuo Zhang, Xue Lv, Armghan Shahzad, Donghui Ao, Maryam Abbas, Yu Wu, Lei Zhang, Muhammad Fayyaz","doi":"10.3389/fpls.2024.1494566","DOIUrl":"https://doi.org/10.3389/fpls.2024.1494566","url":null,"abstract":"<p><strong>Introduction: </strong>Stripe rust, caused by <i>Puccinia striiformis</i> f. sp. <i>tritici</i>, poses a significant threat to wheat quality and production worldwide. The rapid evolution of <i>Pst</i> races caused several resistance genes to be ineffective.</p><p><strong>Methods: </strong>This study evaluated stripe rust resistance genes in 349 Pakistan and Southwest China genotypes. We utilized previously published functional and linked molecular markers to detect 13 major stripe rust resistance genes: <i>Yr5, Yr9, Yr10, Yr15, Yr17, Yr18, Yr26, Yr29, Yr30, Yr36, Yr48, Yr65</i>, and <i>YrSp</i>. Field evaluations assessed IT and resistance levels, while the impact of gene combinations on resistance was also analyzed.</p><p><strong>Results: </strong>Field evaluations showed that over 60% of Chuanyu wheat, 50% of recent Pakistani cultivars, and 20% of historic Pakistani lines were resistant to current stripe rust races. In Chuanyu wheat, the dominant genes were <i>Yr17, YrSp</i>, and <i>Yr48</i>; however, <i>Yr17, Yr26</i>, and <i>YrSp</i> were overused, while <i>Yr36</i> was absent, and <i>Yr18</i> was rare. In historic lines, <i>Yr5, Yr17, Yr18</i>, and <i>Yr26</i> were prevalent, with <i>Yr15, Yr26</i>, and <i>YrSp</i> demonstrating effective resistance against current stripe rust races. Furthermore, the study identified specific combinations of <i>Yr</i> genes (<i>Yr26+Yr48, Yr29+Yr5, Yr26+Yr30</i>, and <i>Yr30+Yr17</i>) that enhanced resistance to <i>Pst</i>.</p><p><strong>Discussion: </strong>This research highlights effective resistance genes and gene combinations for stripe rust in wheat and emphasizes the deployment of durable resistance. The findings guide the strategic use of these genes in breeding programs aimed at developing durable resistance in wheat genotypes in Pakistan and Southwest China.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1494566"},"PeriodicalIF":4.1,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11663667/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A lightweight MHDI-DETR model for detecting grape leaf diseases.","authors":"Zilong Fu, Lifeng Yin, Can Cui, Yi Wang","doi":"10.3389/fpls.2024.1499911","DOIUrl":"https://doi.org/10.3389/fpls.2024.1499911","url":null,"abstract":"<p><p>Accurate diagnosis of grape leaf diseases is critical in agricultural production, yet existing detection techniques face challenges in achieving model lightweighting while ensuring high accuracy. In this study, a real-time, end-to-end, lightweight grape leaf disease detection model, MHDI-DETR, based on an improved RT-DETR architecture, is presented to address these challenges. The original residual backbone network was improved using the MobileNetv4 network, significantly reducing the model's computational requirements and complexity. Additionally, a lightSFPN feature fusion structure is presented, combining the Hierarchical Scale Feature Pyramid Network with the Dilated Reparam Block structure design from the UniRepLKNet network. This structure is designed to overcome the challenges of capturing complex high-level and subtle low-level features, and it uses Efficient Local Attention to focus more efficiently on regions of interest, thereby enhancing the model's ability to detect complex targets while improving accuracy and inference speed. Finally, the integration of GIou and Focaler-IoU into Focaler-GIoU enhances detection accuracy and convergence speed for small targets by focusing more effectively on both simple and difficult samples. The findings from the experiments suggest that The MHDI-DETR model results in a 56% decrease in parameters and a 49% reduction in floating-point operations, respectively, compared with the RT-DETR model, in terms of accuracy, the model achieved precision rates of 96.9%, 92.6%, and 72.5% for accuracy, mAP50, and mAP50:95, respectively. Compared with the RT-DETR model, these represent improvements of 1.9%, 1.2%, and 1.2%. Overall, the MHDI-DETR model surpasses the RT-DETR and other mainstream detection models in both detection accuracy and degree of lightness, achieving dual optimization in efficiency and accuracy, and providing an efficient technical solution for automated agricultural disease management.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1499911"},"PeriodicalIF":4.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11659005/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping rapeseed (<i>Brassica napus L.</i>) aboveground biomass in different periods using optical and phenotypic metrics derived from UAV hyperspectral and RGB imagery.","authors":"Chuanliang Sun, Weixin Zhang, Genping Zhao, Qian Wu, Wanjie Liang, Ni Ren, Hongxin Cao, Lidong Zou","doi":"10.3389/fpls.2024.1504119","DOIUrl":"https://doi.org/10.3389/fpls.2024.1504119","url":null,"abstract":"<p><p>Aboveground biomass (AGB) is a key indicator of crop nutrition and growth status. Accurately and timely obtaining biomass information is essential for crop yield prediction in precision management systems. Remote sensing methods play a key role in monitoring crop biomass. However, the saturation effect makes it challenging for spectral indices to accurately reflect crop changes at higher biomass levels. It is well established that rapeseed biomass during different growth stages is closely related to phenotypic traits. This study aims to explore the potential of using optical and phenotypic metrics to estimate rapeseed AGB. Vegetation indices (VI), texture features (TF), and structural features (SF) were extracted from UAV hyperspectral and ultra-high-resolution RGB images to assess their correlation with rapeseed biomass at different growth stages. Deep neural network (DNN), random forest (RF), and support vector regression (SVR) were employed to estimate rapeseed AGB. We compared the accuracy of various feature combinations and evaluated model performance at different growth stages. The results indicated strong correlations between rapeseed AGB at the three growth stages and the corresponding indices. The estimation model incorporating VI, TF, and SF showed higher accuracy in estimating rapeseed AGB compared to models using individual feature sets. Furthermore, the DNN model (R² = 0.878, RMSE = 447.02 kg/ha) with the combined features outperformed both the RF (R² = 0.812, RMSE = 530.15 kg/ha) and SVR (R² = 0.781, RMSE = 563.24 kg/ha) models. Among the growth stages, the bolting stage yielded slightly higher estimation accuracy than the seedling and early blossoming stages. The optimal model combined DNN with VI, TF, and SF features. These findings demonstrate that integrating hyperspectral and RGB data with advanced artificial intelligence models, particularly DNN, provides an effective approach for estimating rapeseed AGB.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1504119"},"PeriodicalIF":4.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11659009/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research progress and prospect of key technologies of fruit target recognition for robotic fruit picking.","authors":"Shaohua Liu, Jinlin Xue, Tianyu Zhang, Pengfei Lv, Huanhuan Qin, Tianxing Zhao","doi":"10.3389/fpls.2024.1423338","DOIUrl":"https://doi.org/10.3389/fpls.2024.1423338","url":null,"abstract":"<p><p>It is crucial for robotic picking fruit to recognize fruit accurately in orchards, this paper reviews the applications and research results of target recognition in orchard fruit picking by using machine vision and emphasizes two methods of fruit recognition: the traditional digital image processing method and the target recognition method based on deep learning. Here, we outline the research achievements and progress of traditional digital image processing methods by the researchers aiming at different disturbance factors in orchards and summarize the shortcomings of traditional digital image processing methods. Then, we focus on the relevant contents of fruit target recognition methods based on deep learning, including the target recognition process, the preparation and classification of the dataset, and the research results of target recognition algorithms in classification, detection, segmentation, and compression acceleration of target recognition network models. Additionally, we summarize the shortcomings of current orchard fruit target recognition tasks from the perspectives of datasets, model applicability, universality of application scenarios, difficulty of recognition tasks, and stability of various algorithms, and look forward to the future development of orchard fruit target recognition.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1423338"},"PeriodicalIF":4.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11659763/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agronomic biofortification of genetically biofortified wheat genotypes with zinc, selenium, iodine, and iron under field conditions.","authors":"Hari Ram, Asif Naeem, Abdul Rashid, Charanjeet Kaur, Muhammad Y Ashraf, Sudeep Singh Malik, Muhammad Aslam, Gurvinder S Mavi, Yusuf Tutus, Mustafa A Yazici, Velu Govindan, Ismail Cakmak","doi":"10.3389/fpls.2024.1455901","DOIUrl":"https://doi.org/10.3389/fpls.2024.1455901","url":null,"abstract":"<p><p>Inherently low concentrations of zinc (Zn), iron (Fe), iodine (I), and selenium (Se) in wheat (<i>Triticum aestivum</i> L.) grains represent a major cause of micronutrient malnutrition (hidden hunger) in human populations. Genetic biofortification represents a highly useful solution to this problem. However, genetic biofortification alone may not achieve desirable concentrations of micronutrients for human nutrition due to several soil- and plant-related factors. This study investigated the response of genetically biofortified high-Zn wheat genotypes to soil-applied Zn and foliarly applied Zn, I, and Se in India and Pakistan. The effect of soil-applied Zn (at the rate of 50 kg ha^-1 as ZnSO₄·7H₂O) and foliar-applied Zn (0.5% ZnSO₄·7H₂O), I (0.04% KIO₃), Se (0.001% Na₂SeO₄), and a foliar cocktail (F-CT: combination of the above foliar solutions) on the grain concentrations of Zn, I, Se, and Fe of high-Zn wheat genotypes was investigated in field experiments over 2 years. The predominantly grown local wheat cultivars in both countries were also included as check cultivars. Wheat grain yield was not influenced by the micronutrient treatments at all field locations, except one location in Pakistan where F-CT resulted in increased grain yield. Foliar-applied Zn, I, and Se each significantly enhanced the grain concentration of the respective micronutrients. Combined application of these micronutrients was almost equally effective in enhancing grain Zn, I, and Se, but with a slight reduction in grain yield. Foliar-applied Zn, Zn+I, and F-CT also enhanced grain Fe. In India, high-Zn genotypes exhibited a minor grain yield penalty as compared with the local cultivar, whereas in Pakistan, high-Zn wheat genotypes could not produce grain yield higher than the local cultivar. The study demonstrates that there is a synergism between genetic and agronomic biofortification in enrichment of grains with micronutrients. Foliar Zn spray to Zn-biofortified genotypes provided additional increments in grain Zn of more than 15 mg kg^-1. Thus, combining agronomic and genetic strategies will raise grain Zn over 50 mg kg^-1. A combination of fertilization practice with plant breeding is strongly recommended to maximize accumulation of micronutrients in food crops and to make significant progress toward resolving the hidden hunger problem in human populations.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1455901"},"PeriodicalIF":4.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11662280/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative analysis of stomatal pore instance segmentation: Mask R-CNN vs. YOLOv8 on Phenomics Stomatal dataset.","authors":"Thanh Tuan Thai, Ki-Bon Ku, Anh Tuan Le, San Su Min Oh, Ngo Hoang Phan, In-Jung Kim, Yong Suk Chung","doi":"10.3389/fpls.2024.1414849","DOIUrl":"https://doi.org/10.3389/fpls.2024.1414849","url":null,"abstract":"<p><p>This study conducts a rigorous comparative analysis between two cutting-edge instance segmentation methods, Mask R-CNN and YOLOv8, focusing on stomata pore analysis. A novel dataset specifically tailored for stomata pore instance segmentation, named PhenomicsStomata, was introduced. This dataset posed challenges such as low resolution and image imperfections, prompting the application of advanced preprocessing techniques, including image enhancement using the Lucy-Richardson Algorithm. The models underwent comprehensive evaluation, considering accuracy, precision, and recall as key parameters. Notably, YOLOv8 demonstrated superior performance over Mask R-CNN, particularly in accurately calculating stomata pore dimensions. Beyond this comparative study, the implications of our findings extend across diverse biological research, providing a robust foundation for advancing our understanding of plant physiology. Furthermore, the preprocessing enhancements offer valuable insights for refining image analysis techniques, showcasing the potential for broader applications in scientific domains. This research marks a significant stride in unraveling the complexities of plant structures, offering both theoretical insights and practical applications in scientific research.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1414849"},"PeriodicalIF":4.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11659011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive mapping of molecular cytogenetic markers in pitaya (<i>Hylocereus undatus</i>) and related species.","authors":"Arrashid Harun, Shipeng Song, Xixi You, Hui Liu, Xiaopeng Wen, Zhongming Fang, Zhihao Cheng, Chunli Chen","doi":"10.3389/fpls.2024.1493776","DOIUrl":"https://doi.org/10.3389/fpls.2024.1493776","url":null,"abstract":"<p><p>Pitaya (<i>Hylocereus undatus</i>; 2n=22) is an important fruit crop from the <i>Cactaceae</i> family, originally domesticated in Mexico and the USA, and is now widely cultivated for its nutritional benefits. It is characterized by its distinctive triangular-shaped stems and large, showy flowers, thriving in arid and semi-arid environments, particularly in hot, dry climates. However, systematic chromosomal studies, including chromosomal mapping of cytogenetic markers in pitaya, are limited, presenting challenges for its cytogenetic improvement. To address this issue, we designed oligo-barcodes specific to thirty-three chromosome regions based on the pitaya reference genome and applied them to both pitaya and cactus (<i>Selenicerus grandifloras</i>; 2n=22) for oligo-barcodes mapping, karyotyping, and chromosome identification. We utilized FISH technology, employing oligo, rDNA, and tandem repeat probes for chromosomal mapping, identification, and karyotyping of pitaya and related species. We successfully localized oligo-barcodes on eleven pairs of chromosomes in both pitaya and cactus, demonstrating the effectiveness of the synthesized oligo-barcodes. We used two ribosomal DNA (rDNA) probes (45S and 5S) and two tandem repeat probes (GTR11 and STR3) in pitaya (both diploid and tetraploid) and two other <i>Cactaceae</i> species (<i>S. grandifloras</i> and <i>Opuntia humifusa</i>; 2n=40) for chromosomal mapping. The analysis of rDNA distribution and CMA (Chromomycin A3) banding across different chromosomes in pitaya and cacti highlights the concept of conserved rDNA. This study provides fundamental insights into cytogenetic markers and their localization across different chromosomes in pitaya and other <i>Cactaceae</i> species.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1493776"},"PeriodicalIF":4.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11662977/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential physiological tolerance mechanisms in faba bean to <i>Orobanche</i> spp. parasitism.","authors":"Siwar Thebti, Amal Bouallegue, Touhami Rzigui, Youness En-Nahli, Faouzi Horchani, Taoufik Hosni, Mohamed Kharrat, Moez Amri, Zouhaier Abbes","doi":"10.3389/fpls.2024.1497303","DOIUrl":"https://doi.org/10.3389/fpls.2024.1497303","url":null,"abstract":"<p><p><i>Orobanche</i> spp. are root parasitic plants that cause severe yield losses in faba bean (<i>Vicia faba</i> L.). The use of tolerant varieties remains a pivotal component of a successful integrated control strategy. In this study, we investigated the potential physiological mechanisms associated with tolerance to <i>O. crenata</i> and <i>O. foetida</i> in faba bean. The results showed that <i>Orobanche</i> parasitism significantly affected faba bean plants' growth and seed production, especially in the sensitive Bachaar variety (up to 61.77% and 83.53% in shoot dry weight, up to 79.59% in pod number and no pod development when infected with <i>O. foetida</i> and <i>O. crenata</i>, respectively). This reduction was correlated with photosynthetic capacity (A_max) decreases in response to both <i>O. foetida</i> and <i>O. crenata</i> parasitism. This decrease was highly pronounced in the sensitive Bachaar variety with 24.57% and 63.43% decreases, respectively. Significant decreases were also observed in the sensitive Bachaar cultivar for the photochemical efficiency of PSII (F_v/F_m) (1.1% and 4.78%), the maximum transpiration (E_max) (11.8% and 39.13%), and the maximum water use efficiency (WUE_max) (24.97% and 41.77%) in response to <i>O. foetida</i> and <i>O. crenata</i> parasitism, respectively, compared to non-significant differences for the tolerant Chams, Chourouk, and Zaher varieties. The tolerant faba bean varieties were able to maintain a normal function of their photosynthesis capacity (A_n) and conserve their growth and seed production level as a result of an acclimation to parasitic attack (Maintaining WUE_max). Our results suggest that yield components such as shoot dry weight, pod and leaf numbers, and photosynthetic parameters, notably the transpiration rate, can serve as suitable traits for assessing tolerance to <i>Orobanche</i> parasitism in faba bean plants.</p>","PeriodicalId":12632,"journal":{"name":"Frontiers in Plant Science","volume":"15 ","pages":"1497303"},"PeriodicalIF":4.1,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11658979/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}