Pub Date : 2025-11-14DOI: 10.1016/j.cpb.2025.100565
Javier Villacreses , Carolina Sanchez-Doñas , Victor Polanco , Nathan R. Johnson , Vinicius Maracaja-Coutinho , Alberto J.M. Martin
Endogenous pararetroviruses (EPRVs), integrated viral elements from the Caulimoviridae family, are increasingly recognized as dynamic regulators of plant development. This study investigates the activity and functional impact of EPRVs on the ripening process of Solanum lycopersicum (tomato). Using genomic and transcriptomic datasets, we identified 16,012 EPRV sequences in the tomato genome via Hidden Markov Models, with 134 sequences showing differential expression during ripening stages. Co-expression analysis revealed 28 EPRVs that are linked with 259 tomato genes, highlighting their possible regulatory roles. These tomato genes participate in pathways associated with ethylene signaling, pigment biosynthesis, and stress responses. The role of EPRV-derived small RNAs (sRNAs) was also explored, identifying these sRNAs as potential mediators of ripening-related gene expression. These findings reveal the regulatory significance of EPRVs in tomato ripening and establish a foundation for leveraging these elements in crop improvement strategies.
{"title":"Activity of novel endogenous pararetroviruses and their associations with S. lycopersicum ripening","authors":"Javier Villacreses , Carolina Sanchez-Doñas , Victor Polanco , Nathan R. Johnson , Vinicius Maracaja-Coutinho , Alberto J.M. Martin","doi":"10.1016/j.cpb.2025.100565","DOIUrl":"10.1016/j.cpb.2025.100565","url":null,"abstract":"<div><div>Endogenous pararetroviruses (EPRVs), integrated viral elements from the Caulimoviridae family, are increasingly recognized as dynamic regulators of plant development. This study investigates the activity and functional impact of EPRVs on the ripening process of <em>Solanum lycopersicum</em> (tomato). Using genomic and transcriptomic datasets, we identified 16,012 EPRV sequences in the tomato genome via Hidden Markov Models, with 134 sequences showing differential expression during ripening stages. Co-expression analysis revealed 28 EPRVs that are linked with 259 tomato genes, highlighting their possible regulatory roles. These tomato genes participate in pathways associated with ethylene signaling, pigment biosynthesis, and stress responses. The role of EPRV-derived small RNAs (sRNAs) was also explored, identifying these sRNAs as potential mediators of ripening-related gene expression. These findings reveal the regulatory significance of EPRVs in tomato ripening and establish a foundation for leveraging these elements in crop improvement strategies.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100565"},"PeriodicalIF":4.5,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145578840","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 : 2025-11-09DOI: 10.1016/j.cpb.2025.100563
Irish Lorraine B. Pabuayon , Jessica Joy B. Bicaldo , Zelalem A. Alemar , Isaiah Catalino M. Pabuayon , Glen L. Ritchie
In semi-arid environments, crop production is heavily impacted by drought, salinity, and low nutrient availability. These marginal environmental conditions disrupt photosynthetic efficiency, translocation, and assimilate partitioning, all of which lead to yield reductions. As a result, maximizing crop productivity under marginal environments requires plants to effectively balance assimilate production (source strength) with use or storage (sink strength). Understanding the relative trade-offs between resources devoted to plant sources and sinks is critical to the development of resilient, productive crops. This review synthesizes research identifying physiological, morphological, and developmental traits that improve source and sink strength under stress conditions in semi-arid regions. Key source-related traits include intrinsic water-use efficiency, sustained photosynthetic capacity under stress, the stay-green phenotype, and favorable leaf area and canopy architecture. Sink traits such as stable reproductive organ development, phenotypic plasticity, root-shoot balance, and optimized phenological timing are highlighted as critical to maintaining sink strength under limiting conditions. We also assess the potential of advanced genetic, biotechnological, and "omics" approaches to develop climate-resilient crops, while addressing inherent trade-offs. Finally, we discuss emerging tools and conceptual frameworks that hold promise for improving selection and management of source–sink traits in climate-resilient cropping systems. This review provides a framework for integrating physiological, morphological, and developmental traits into breeding programs aimed at improving source-sink dynamics and advancing sustainable crop production in semi-arid and other marginal environments.
{"title":"Dynamics of source-sink relationships in crops under marginal environments","authors":"Irish Lorraine B. Pabuayon , Jessica Joy B. Bicaldo , Zelalem A. Alemar , Isaiah Catalino M. Pabuayon , Glen L. Ritchie","doi":"10.1016/j.cpb.2025.100563","DOIUrl":"10.1016/j.cpb.2025.100563","url":null,"abstract":"<div><div>In semi-arid environments, crop production is heavily impacted by drought, salinity, and low nutrient availability. These marginal environmental conditions disrupt photosynthetic efficiency, translocation, and assimilate partitioning, all of which lead to yield reductions. As a result, maximizing crop productivity under marginal environments requires plants to effectively balance assimilate production (source strength) with use or storage (sink strength). Understanding the relative trade-offs between resources devoted to plant sources and sinks is critical to the development of resilient, productive crops. This review synthesizes research identifying physiological, morphological, and developmental traits that improve source and sink strength under stress conditions in semi-arid regions. Key source-related traits include intrinsic water-use efficiency, sustained photosynthetic capacity under stress, the stay-green phenotype, and favorable leaf area and canopy architecture. Sink traits such as stable reproductive organ development, phenotypic plasticity, root-shoot balance, and optimized phenological timing are highlighted as critical to maintaining sink strength under limiting conditions. We also assess the potential of advanced genetic, biotechnological, and \"omics\" approaches to develop climate-resilient crops, while addressing inherent trade-offs. Finally, we discuss emerging tools and conceptual frameworks that hold promise for improving selection and management of source–sink traits in climate-resilient cropping systems. This review provides a framework for integrating physiological, morphological, and developmental traits into breeding programs aimed at improving source-sink dynamics and advancing sustainable crop production in semi-arid and other marginal environments.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100563"},"PeriodicalIF":4.5,"publicationDate":"2025-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525672","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 : 2025-11-02DOI: 10.1016/j.cpb.2025.100562
Raghvendra Kumar , Chandrakanta Mahanty , Bhawani Sankar Panigrahi , S. Gopal Krishna Patro , Tran Manh Tuan , Le Hoang Son
Various viral illnesses impact plant development, causing farmers to lose a lot of revenue. Early diagnosis and prediction of these viral infections can help farmers take preventive measures and mitigate the impacts on crop productivity and quality. As a result, there is a need to develop automated tools for identifying viral infections in crops that analyze symptoms at various parts of the plant. The prediction of Vigna mungo millet disease is critical for food security and agricultural sustainability. In this article, a practical and reproducible pipeline is proposed for the automatic detection of leaf diseases in Vigna mungo, which combines ImageNet-pretrained CNN backbones (GoogleNet, MobileNetV2, Xception) with a lightweight recurrent classifier. Our original contribution is to treat convolutional feature maps as ordered spatial sequences and to use a single-layer LSTM to model spatial dependencies across the leaf surface. This design more effectively captures the diffuse and irregular lesion patterns characteristic of viral infections. To address the modest dataset size (660 images, with 220 images per class), we freeze the backbones, apply augmentation on the fly, and utilize dropout, gradient clipping, and early stopping. The models were evaluated with stratified 5-fold cross-validation and statistical tests. It has been revealed that the Xception with LSTM attained the best mean performance (98.34 % ± 0.34 % across folds; peak 98.48 % on the test split). Vigna mungo/ Black gram plant leaf diseases can significantly reduce crop yields, leading to lower food production and higher food prices. By detecting and identifying these diseases early on, farmers can take appropriate measures to control the spread of the disease and prevent crop losses.
{"title":"A new method for prediction of Vigna mungo millet disease based on deep learning","authors":"Raghvendra Kumar , Chandrakanta Mahanty , Bhawani Sankar Panigrahi , S. Gopal Krishna Patro , Tran Manh Tuan , Le Hoang Son","doi":"10.1016/j.cpb.2025.100562","DOIUrl":"10.1016/j.cpb.2025.100562","url":null,"abstract":"<div><div>Various viral illnesses impact plant development, causing farmers to lose a lot of revenue. Early diagnosis and prediction of these viral infections can help farmers take preventive measures and mitigate the impacts on crop productivity and quality. As a result, there is a need to develop automated tools for identifying viral infections in crops that analyze symptoms at various parts of the plant. The prediction of Vigna mungo millet disease is critical for food security and agricultural sustainability. In this article, a practical and reproducible pipeline is proposed for the automatic detection of leaf diseases in Vigna mungo, which combines ImageNet-pretrained CNN backbones (GoogleNet, MobileNetV2, Xception) with a lightweight recurrent classifier. Our original contribution is to treat convolutional feature maps as ordered spatial sequences and to use a single-layer LSTM to model spatial dependencies across the leaf surface. This design more effectively captures the diffuse and irregular lesion patterns characteristic of viral infections. To address the modest dataset size (660 images, with 220 images per class), we freeze the backbones, apply augmentation on the fly, and utilize dropout, gradient clipping, and early stopping. The models were evaluated with stratified 5-fold cross-validation and statistical tests. It has been revealed that the Xception with LSTM attained the best mean performance (98.34 % ± 0.34 % across folds; peak 98.48 % on the test split). Vigna mungo/ Black gram plant leaf diseases can significantly reduce crop yields, leading to lower food production and higher food prices. By detecting and identifying these diseases early on, farmers can take appropriate measures to control the spread of the disease and prevent crop losses.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100562"},"PeriodicalIF":4.5,"publicationDate":"2025-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525671","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}
Rising global temperature makes sustainable agricultural production increasingly challenging. This is particularly worrying for staple crops like wheat, mainly in regions like the Mediterranean basin where high temperature extremes and heat waves frequently occur. A strategic commodity there at risk is durum wheat (DW), for which development of heat-tolerant varieties represents a key adaptive strategy with potential short-term effects. In contrast with mostly sensitive cultivars, wild relatives are endowed with numerous stress-adaptive and exploitable traits to reinforce the crop resilience. In this frame, three DW-Thinopyrum ponticum near-isogenic recombinant lines (NIRLs+), containing small alien segments on their 7AL arm, were previously subjected to transient heat stress (HS) at anthesis and their physiological and yield-related response compared to that of DW-only sib (NIRLs−) and non-sib control lines. HS at anthesis is known to greatly impair morphology and function of reproductive structures, yet limited knowledge is available on HS-triggered molecular/metabolic mechanisms in wheat floral organs, particularly the female one (pistil), directly involved in seed development and grain yield. Here, untargeted metabolomics was applied to identify pathways/metabolites in pistils sampled from heat-stressed and control plants of the above materials. Differential metabolic avenues were found to be undertaken by NIRLs+ vs. control lines under HS, including tricarboxylic acid cycle, pentose phosphate pathway, purine and pyrimidine, ascorbate and glutathione metabolisms, and specific metabolites (e.g. allantoin) produced, usable as selection biomarkers. The novel insights not only help explain the genotypes’ differential yield formation and stability but are also instrumental to breeding programs in which various effective metabolic strategies could be profitably combined.
{"title":"Metabolomic profiling provides novel insights into pistil adaptation to heat stress at anthesis in durum wheat lines carrying segmental introgressions from the wild grass Thinopyrum ponticum","authors":"Ljiljana Kuzmanović , Giuseppina Fanelli , Gloria Giovenali , Sara Rinalducci , Carla Ceoloni","doi":"10.1016/j.cpb.2025.100561","DOIUrl":"10.1016/j.cpb.2025.100561","url":null,"abstract":"<div><div>Rising global temperature makes sustainable agricultural production increasingly challenging. This is particularly worrying for staple crops like wheat, mainly in regions like the Mediterranean basin where high temperature extremes and heat waves frequently occur. A strategic commodity there at risk is durum wheat (DW), for which development of heat-tolerant varieties represents a key adaptive strategy with potential short-term effects. In contrast with mostly sensitive cultivars, wild relatives are endowed with numerous stress-adaptive and exploitable traits to reinforce the crop resilience. In this frame, three DW-<em>Thinopyrum ponticum</em> near-isogenic recombinant lines (NIRLs+), containing small alien segments on their 7AL arm, were previously subjected to transient heat stress (HS) at anthesis and their physiological and yield-related response compared to that of DW-only sib (NIRLs−) and non-sib control lines. HS at anthesis is known to greatly impair morphology and function of reproductive structures, yet limited knowledge is available on HS-triggered molecular/metabolic mechanisms in wheat floral organs, particularly the female one (pistil), directly involved in seed development and grain yield. Here, untargeted metabolomics was applied to identify pathways/metabolites in pistils sampled from heat-stressed and control plants of the above materials. Differential metabolic avenues were found to be undertaken by NIRLs+ vs. control lines under HS, including tricarboxylic acid cycle, pentose phosphate pathway, purine and pyrimidine, ascorbate and glutathione metabolisms, and specific metabolites (e.g. allantoin) produced, usable as selection biomarkers. The novel insights not only help explain the genotypes’ differential yield formation and stability but are also instrumental to breeding programs in which various effective metabolic strategies could be profitably combined.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100561"},"PeriodicalIF":4.5,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465694","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 : 2025-10-27DOI: 10.1016/j.cpb.2025.100560
Xiaoqian Chen , Guanmin Huang , Xiaofen Ge , Anran Song , Guangjie Qiu , Yue Zhao , Xinyu Guo , Wanneng Yang
Improving light-use efficiency (LUE) is essential for boosting crop productivity, particularly in controlled-environment agriculture. Despite recent advances, most studies still rely on destructive measurements or one-dimensional data, which limits insight into the structural–physiological coordination underlying LUE. We established a multimodal phenotyping platform to dissect the phenotypic regulatory network of LUE in lettuce (Lactuca sativa L.). Integrating hyperspectral imaging with multiview three-dimensional (3D) reconstruction, we developed a noninvasive, high-throughput system that simultaneously estimates 3D plant architecture, photosynthetic physiology—net photosynthetic rate (A) and relative chlorophyll content (SPAD)—and aboveground biomass (AGB) across 35 cultivars. A modeling pipeline combining StandardScaler (SS) normalization, genetic algorithm (GA) feature selection, and artificial neural networks (ANN) achieved robust prediction of A (R²=0.72), SPAD (R²=0.87), and AGB (R²=0.85). Spectral contribution analysis revealed distinct sensitivities: SPAD across 400–700 nm, A near 430 and 680 nm, and AGB across 500–580 nm. The 426–430 nm blue band emerged as a key region: high-efficiency cultivars showed distinctive reflectance (42.93–59.03 %), consistent with superior photosynthetic performance. Structurally, high-efficiency types exhibited “large-and-loose” canopies, with greater plant height (+64.37 %), projected area (+59.42 %), and convex-hull volume (+166.3 %), alongside reduced compactness (−23.48 %). Network analysis indicated progressively tighter coupling between spectral and structural traits from low- to high-efficiency groups, consistent with adaptive coordination for light capture and use. These results identify actionable phenotypic markers for selecting high-LUE cultivars and provide a transferable platform for phenomics-driven breeding and management in controlled-environment crops.
{"title":"Multimodal phenotyping reveals structural–physiological coordination mechanisms underlying light-use efficiency in lettuce","authors":"Xiaoqian Chen , Guanmin Huang , Xiaofen Ge , Anran Song , Guangjie Qiu , Yue Zhao , Xinyu Guo , Wanneng Yang","doi":"10.1016/j.cpb.2025.100560","DOIUrl":"10.1016/j.cpb.2025.100560","url":null,"abstract":"<div><div>Improving light-use efficiency (LUE) is essential for boosting crop productivity, particularly in controlled-environment agriculture. Despite recent advances, most studies still rely on destructive measurements or one-dimensional data, which limits insight into the structural–physiological coordination underlying LUE. We established a multimodal phenotyping platform to dissect the phenotypic regulatory network of LUE in lettuce (<em>Lactuca sativa</em> L.). Integrating hyperspectral imaging with multiview three-dimensional (3D) reconstruction, we developed a noninvasive, high-throughput system that simultaneously estimates 3D plant architecture, photosynthetic physiology—net photosynthetic rate (A) and relative chlorophyll content (SPAD)—and aboveground biomass (AGB) across 35 cultivars. A modeling pipeline combining StandardScaler (SS) normalization, genetic algorithm (GA) feature selection, and artificial neural networks (ANN) achieved robust prediction of A (R²=0.72), SPAD (R²=0.87), and AGB (R²=0.85). Spectral contribution analysis revealed distinct sensitivities: SPAD across 400–700 nm, A near 430 and 680 nm, and AGB across 500–580 nm. The 426–430 nm blue band emerged as a key region: high-efficiency cultivars showed distinctive reflectance (42.93–59.03 %), consistent with superior photosynthetic performance. Structurally, high-efficiency types exhibited “large-and-loose” canopies, with greater plant height (+64.37 %), projected area (+59.42 %), and convex-hull volume (+166.3 %), alongside reduced compactness (−23.48 %). Network analysis indicated progressively tighter coupling between spectral and structural traits from low- to high-efficiency groups, consistent with adaptive coordination for light capture and use. These results identify actionable phenotypic markers for selecting high-LUE cultivars and provide a transferable platform for phenomics-driven breeding and management in controlled-environment crops.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100560"},"PeriodicalIF":4.5,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416360","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 : 2025-10-27DOI: 10.1016/j.cpb.2025.100559
Bing Han , Zichao Zhu , Xiaoding Ma , Ying Xiong , Di Cui , Chutao Wang , Li Chen , Xianyong Li , Longzhi Han
Grain shattering is one of the critical traits in rice, influencing harvesting methods and yield. Seeds from varieties that shatter easily often begin to drop before reaching full maturity. Varieties with difficult-to-thresh or non-threshing characteristics are susceptible to having their branches broken and mixed with straw during mechanical harvesting, leading to relatively severe losses. Therefore, developing rice varieties with a moderate degree of shattering, suitable for production applications, is the primary focus in rice breeding. In this study, the F2:3 generation population from a cross between the easy-shattering weedy rice variety "H21" and the non-shattering japonica rice variety "Longdao 18" was utilized to investigate shattering resistance through phenotypic identification, Bulk Segregant Analysis (BSA), gene editing, and cytological detection. Gene Os01g0935000, a ZOS1–23 - C2H2 zinc finger protein involved in the regulation of shattering, was preliminarily localized and named OsZIPH1. Mutant phenotype identification showed that the shattering rate of the mutant is 41.98 %, while that of the wild type is 84.33 %, the decrease is 50.2 % compared to the wild type H21. Cytological analysis revealed that mutant spikelets had incomplete abscission layer structures between the lemma and rachis branches, whereas wild-type plants exhibited clearly defined abscission layer structures. The expression level of this gene in the wild type is 2.63 times that in the knockout mutant. Haplotype analysis has revealed that this gene comprises five haplotypes. HAP5 is unique to Oryza rufipogon, while HAP1 is found in nearly all japonica rice varieties. HAP2 is predominantly present in 70 % of indica weedy rice, and HAP3 is primarily associated with 59.37 % of indica improved rice. HAP4 is found in SH and BHA weedy rice, indicating that the shattering gene Os01g0935000 plays a significant role in the domestication process of rice. These findings enhance our understanding of the biological mechanisms underlying rice shattering and are crucial for developing rice varieties with desirable shattering characteristics.
{"title":"Identification of gene OsZIPH1 related to rice shattering using Bulk Segregant Analysis","authors":"Bing Han , Zichao Zhu , Xiaoding Ma , Ying Xiong , Di Cui , Chutao Wang , Li Chen , Xianyong Li , Longzhi Han","doi":"10.1016/j.cpb.2025.100559","DOIUrl":"10.1016/j.cpb.2025.100559","url":null,"abstract":"<div><div>Grain shattering is one of the critical traits in rice, influencing harvesting methods and yield. Seeds from varieties that shatter easily often begin to drop before reaching full maturity. Varieties with difficult-to-thresh or non-threshing characteristics are susceptible to having their branches broken and mixed with straw during mechanical harvesting, leading to relatively severe losses. Therefore, developing rice varieties with a moderate degree of shattering, suitable for production applications, is the primary focus in rice breeding. In this study, the F<sub>2:3</sub> generation population from a cross between the easy-shattering weedy rice variety \"H21\" and the non-shattering japonica rice variety \"Longdao 18\" was utilized to investigate shattering resistance through phenotypic identification, Bulk Segregant Analysis (BSA), gene editing, and cytological detection. Gene <em>Os01g0935000,</em> a ZOS1–23 - C2H2 zinc finger protein involved in the regulation of shattering, was preliminarily localized and named <em>OsZIPH1</em>. Mutant phenotype identification showed that the shattering rate of the mutant is 41.98 %, while that of the wild type is 84.33 %, the decrease is 50.2 % compared to the wild type H21. Cytological analysis revealed that mutant spikelets had incomplete abscission layer structures between the lemma and rachis branches, whereas wild-type plants exhibited clearly defined abscission layer structures. The expression level of this gene in the wild type is 2.63 times that in the knockout mutant. Haplotype analysis has revealed that this gene comprises five haplotypes. HAP5 is unique to <em>Oryza ruf</em>ipogon, while HAP1 is found in nearly all <em>japoni</em>ca rice varieties. HAP2 is predominantly present in 70 % of indica weedy rice, and HAP3 is primarily associated with 59.37 % of indica improved rice. HAP4 is found in SH and BHA weedy rice, indicating that the shattering gene <em>Os01g</em>0935000 plays a significant role in the domestication process of rice. These findings enhance our understanding of the biological mechanisms underlying rice shattering and are crucial for developing rice varieties with desirable shattering characteristics.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100559"},"PeriodicalIF":4.5,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465693","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 : 2025-10-24DOI: 10.1016/j.cpb.2025.100558
Zena J. Rawandoozi , Tessa Hochhaus , Maad Y. Rawandoozi , Patricia E. Klein , David H. Byrne , Oscar Riera-Lizarazu
Roses (Rosa spp.) are globally valued for the ornamental, medicinal, culinary, and cosmetic applications of the flowers and hips. Rose hips hold significant economic value; however, the genetic basis of the rose hip set remains unexplored. This research sought to identify quantitative trait loci (QTLs) related to hip set and characterize hip set alleles using two multi-parental diploid rose populations evaluated over multiple years. Pedigree-based quantitative trait locus (QTL) mapping for rose hips has identified a significant QTL on linkage group (LG) 3, spanning from 23.0 to 34.0 Mbp on the Rosa chinensis genome. This QTL was consistently detected in both populations and various environments, accounting for 18–56 % of phenotypic variation. Additional QTLs with minor effects were detected across all linkage groups except for LG4. Single nucleotide polymorphism (SNP) haplotypes linked to higher or lower hip production were identified, with ‘Old Blush’ and the pollen parent of J14–3 (Texas A&M breeding line) being the sources of Q- and q-alleles, respectively. These findings contribute to a deeper understanding of genetic regulation in rose hip set. Additional research is needed to validate these findings. This study lays a foundation for developing tools to enhance rose hip production. It also has broader implications for other Rosaceae crops like blackberries, raspberries, and strawberries, where high fruit set is vital for yield. Validating these markers could improve breeding efficiency across important crops.
{"title":"Determining the genetic basis of hip set in diploid roses","authors":"Zena J. Rawandoozi , Tessa Hochhaus , Maad Y. Rawandoozi , Patricia E. Klein , David H. Byrne , Oscar Riera-Lizarazu","doi":"10.1016/j.cpb.2025.100558","DOIUrl":"10.1016/j.cpb.2025.100558","url":null,"abstract":"<div><div>Roses (<em>Rosa</em> spp.) are globally valued for the ornamental, medicinal, culinary, and cosmetic applications of the flowers and hips. Rose hips hold significant economic value; however, the genetic basis of the rose hip set remains unexplored. This research sought to identify quantitative trait loci (QTLs) related to hip set and characterize hip set alleles using two multi-parental diploid rose populations evaluated over multiple years. Pedigree-based quantitative trait locus (QTL) mapping for rose hips has identified a significant QTL on linkage group (LG) 3, spanning from 23.0 to 34.0 Mbp on the <em>Rosa chinensis</em> genome. This QTL was consistently detected in both populations and various environments, accounting for 18–56 % of phenotypic variation. Additional QTLs with minor effects were detected across all linkage groups except for LG4. Single nucleotide polymorphism (SNP) haplotypes linked to higher or lower hip production were identified, with ‘Old Blush’ and the pollen parent of J14–3 (Texas A&M breeding line) being the sources of <em>Q</em>- and <em>q</em>-alleles, respectively. These findings contribute to a deeper understanding of genetic regulation in rose hip set. Additional research is needed to validate these findings. This study lays a foundation for developing tools to enhance rose hip production. It also has broader implications for other Rosaceae crops like blackberries, raspberries, and strawberries, where high fruit set is vital for yield. Validating these markers could improve breeding efficiency across important crops.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100558"},"PeriodicalIF":4.5,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416359","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 : 2025-10-10DOI: 10.1016/j.cpb.2025.100557
Adriano Griffo , Francesca Usai , Stefanie Sehmisch , Frédéric Laager , Andreas Börner , Lorenzo Pasotti , Anca Macovei
The integration of artificial intelligence (AI) in agriculture has revolutionized traditional farming practices, addressing challenges in food security, sustainability, and climate change. In seed science, AI-driven models enhance seed quality assessment, moving beyond conventional time-consuming and invasive methods. This study presents a pipeline that combines deep learning and machine learning approaches to predict legume seed germination potential using heterogeneous features, including color, physical traits, and chemiluminescence data (ultra-weak photon emission and delayed luminescence). A dataset of 1038 seed samples from five legume species was analyzed, aiming at finding the most informative features to discriminate germination potential, and evaluating whether classification performance could reach promising levels. Results demonstrated that machine learning models trained using color and physical features outperform those relying only on chemiluminescence data. Notably, the best-performing model leveraged gradient boosting techniques and reached about 80 % prediction accuracy. Our findings underscore the importance of multimodal approaches in seed quality assessment, highlighting the role of AI in advancing non-invasive agricultural diagnostics. This research contributes to precision agriculture by providing a promising AI-powered framework for seed quality evaluation, based on selected features, which could potentially support enhanced crop yield and sustainability.
{"title":"Application of machine learning models for non-invasive seed quality detection","authors":"Adriano Griffo , Francesca Usai , Stefanie Sehmisch , Frédéric Laager , Andreas Börner , Lorenzo Pasotti , Anca Macovei","doi":"10.1016/j.cpb.2025.100557","DOIUrl":"10.1016/j.cpb.2025.100557","url":null,"abstract":"<div><div>The integration of artificial intelligence (AI) in agriculture has revolutionized traditional farming practices, addressing challenges in food security, sustainability, and climate change. In seed science, AI-driven models enhance seed quality assessment, moving beyond conventional time-consuming and invasive methods. This study presents a pipeline that combines deep learning and machine learning approaches to predict legume seed germination potential using heterogeneous features, including color, physical traits, and chemiluminescence data (ultra-weak photon emission and delayed luminescence). A dataset of 1038 seed samples from five legume species was analyzed, aiming at finding the most informative features to discriminate germination potential, and evaluating whether classification performance could reach promising levels. Results demonstrated that machine learning models trained using color and physical features outperform those relying only on chemiluminescence data. Notably, the best-performing model leveraged gradient boosting techniques and reached about 80 % prediction accuracy. Our findings underscore the importance of multimodal approaches in seed quality assessment, highlighting the role of AI in advancing non-invasive agricultural diagnostics. This research contributes to precision agriculture by providing a promising AI-powered framework for seed quality evaluation, based on selected features, which could potentially support enhanced crop yield and sustainability.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100557"},"PeriodicalIF":4.5,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324763","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 : 2025-10-09DOI: 10.1016/j.cpb.2025.100553
Pasquale Luca Curci , Jia Min Lee , Qiao Wen Tan , Marek Mutwil , Aurelio Ciancio , Isabella Pentimone , Mariella M. Finetti-Sialer
It is currently poorly understood how endophyte colonization and nematode parasitism affect host plants. To address this, we explored the transcriptional responses of sweet pepper (Capsicum annuum L. cv “Crusco di Senise”) roots colonized by the endophyte and nematophagous fungus Pochonia chlamydosporia (Pc), either alone or in combination with the root-knot nematode Meloidogyne incognita (RKN). Biometric data from Pc-inoculation revealed significant growth enhancements, including increased leaf number, chlorophyll content, height, and biomass. Transcriptomic analyses highlighted most pronounced gene expression changes at 14 days after inoculation (dai), with activation of plant defense and suppression of energy metabolism processes, indicating a trade-off between growth and defense. Functional over-representation analyses showed that Pc alone suppressed ethylene signaling, hydrolases, proteases, and terpenoid biosynthesis, the latter being induced instead under RKN parasitism. The combined Pc+RKN treatment showed activation of phenylpropanoid biosynthesis, secondary metabolism, fungal response, and broad defense mechanisms. Despite Pc influence, gene expression patterns in the Pc+RKN treatment largely reflected RKN-induced responses, suggesting that nematode-induced stress dominates the transcriptional landscape. Nevertheless, Pc modulated specific secondary metabolism pathways and activated key transcription factors which persisted when the nematode was present, involved in keeping defense and growth responses under combined stress. These findings highlight Pc dual role in promoting growth and enhancing resilience against RKN, supporting and integrating its potential as a biocontrol agent. The study also identifies candidate genes that could aid pepper breeding programs aimed at improving resistance to biotic stress, providing deeper insight into the molecular dynamics between beneficial fungi and parasitic nematodes in crop systems.
目前，人们对内生菌定植和线虫寄生如何影响寄主植物知之甚少。为了解决这个问题，我们研究了内生和噬线虫真菌衣孢Pochonia chlamydosporia （Pc）定殖的甜椒（Capsicum annuum L. cv " Crusco di Senise "）根系的转录反应，无论是单独定殖还是与根结线虫Meloidogyne incognita （RKN）联合定殖。接种pc后的生物特征数据显示了显著的生长增强，包括叶片数量、叶绿素含量、高度和生物量的增加。转录组学分析显示，在接种后14天，基因表达发生了最显著的变化，同时激活了植物防御和抑制了能量代谢过程，表明了生长和防御之间的权衡。功能过代表性分析表明，Pc单独抑制乙烯信号、水解酶、蛋白酶和萜类生物合成，后者在RKN寄生下被诱导。Pc+RKN联合处理显示出苯丙类生物合成激活、次生代谢、真菌反应和广泛的防御机制。尽管有Pc的影响，但Pc+RKN处理中的基因表达模式在很大程度上反映了RKN诱导的应答，这表明线虫诱导的应激在转录格局中占主导地位。然而，Pc调节了特定的次级代谢途径，激活了线虫存在时持续存在的关键转录因子，参与了在联合胁迫下保持防御和生长反应。这些发现强调了Pc在促进生长和增强抗RKN能力方面的双重作用，支持并整合了其作为生物防治剂的潜力。该研究还确定了候选基因，这些基因可以帮助辣椒育种计划提高对生物胁迫的抵抗力，为作物系统中有益真菌和寄生线虫之间的分子动力学提供更深入的了解。
{"title":"Transcriptional re-programming of defense responses in Capsicum annuum roots induced by the interaction of the endophyte fungus Pochonia chlamydosporia and the plant-parasitic nematode Meloidogyne incognita","authors":"Pasquale Luca Curci , Jia Min Lee , Qiao Wen Tan , Marek Mutwil , Aurelio Ciancio , Isabella Pentimone , Mariella M. Finetti-Sialer","doi":"10.1016/j.cpb.2025.100553","DOIUrl":"10.1016/j.cpb.2025.100553","url":null,"abstract":"<div><div>It is currently poorly understood how endophyte colonization and nematode parasitism affect host plants. To address this, we explored the transcriptional responses of sweet pepper (<em>Capsicum annuum</em> L. cv “Crusco di Senise”) roots colonized by the endophyte and nematophagous fungus <em>Pochonia chlamydosporia</em> (Pc), either alone or in combination with the root-knot nematode <em>Meloidogyne incognita</em> (RKN). Biometric data from Pc-inoculation revealed significant growth enhancements, including increased leaf number, chlorophyll content, height, and biomass. Transcriptomic analyses highlighted most pronounced gene expression changes at 14 days after inoculation (dai), with activation of plant defense and suppression of energy metabolism processes, indicating a trade-off between growth and defense. Functional over-representation analyses showed that Pc alone suppressed ethylene signaling, hydrolases, proteases, and terpenoid biosynthesis, the latter being induced instead under RKN parasitism. The combined Pc+RKN treatment showed activation of phenylpropanoid biosynthesis, secondary metabolism, fungal response, and broad defense mechanisms. Despite Pc influence, gene expression patterns in the Pc+RKN treatment largely reflected RKN-induced responses, suggesting that nematode-induced stress dominates the transcriptional landscape. Nevertheless, Pc modulated specific secondary metabolism pathways and activated key transcription factors which persisted when the nematode was present, involved in keeping defense and growth responses under combined stress. These findings highlight Pc dual role in promoting growth and enhancing resilience against RKN, supporting and integrating its potential as a biocontrol agent. The study also identifies candidate genes that could aid pepper breeding programs aimed at improving resistance to biotic stress, providing deeper insight into the molecular dynamics between beneficial fungi and parasitic nematodes in crop systems.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100553"},"PeriodicalIF":4.5,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324762","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 : 2025-10-08DOI: 10.1016/j.cpb.2025.100555
Ayyagari Ramlal , Pang Wei Quan , Ambika Rajendran , Sreeramanan Subramaniam
Fragaria, commonly known as the strawberry, is one of the most economically important genera of fruit plants. Strawberries have a wide range of health-promoting and nutritious ingredients. They can be found all over the world and appeal to people due to both their flavor and appearance. Strawberries are propagated either by runners or by in vitro methods. Meristems, callus or shoot cultures of strawberries are used for in vitro propagation to increase the production- and cost- efficiency. The interaction of various physical, chemical and biological factors has been shown to have a profound effect on micropropagation. Light is one of the important physical variables that influences the growth and development of plants, especially in plant tissue culture, such as light-emitting diodes (LEDs). LED technology has proven to be advantageous for plant production in greenhouses for various purposes, including the induction of photomorphogenic responses of plants grown in vitro. Chemical and biological parameters such as media composition, growth regulators and choice of explants are also critical factors for micropropagation. This review summarizes the effects of biophysical-chemical factors on in vitro propagation as well as the production of haploids and doubled haploids (DHs). The review will also discuss the challenges associated with developing a standardized protocol for mass propagation and the production of haploids and DHs in strawberries, which will eventually help in breeding and crop improvement programs.
{"title":"Impact of biophysicochemical factors on micropropagation, haploidy and doubled haploidy in strawberry (Fragaria sp.): A critical revisit","authors":"Ayyagari Ramlal , Pang Wei Quan , Ambika Rajendran , Sreeramanan Subramaniam","doi":"10.1016/j.cpb.2025.100555","DOIUrl":"10.1016/j.cpb.2025.100555","url":null,"abstract":"<div><div><em>Fragaria</em>, commonly known as the strawberry, is one of the most economically important genera of fruit plants. Strawberries have a wide range of health-promoting and nutritious ingredients. They can be found all over the world and appeal to people due to both their flavor and appearance. Strawberries are propagated either by runners or by <em>in vitro</em> methods. Meristems, callus or shoot cultures of strawberries are used for <em>in vitro</em> propagation to increase the production- and cost- efficiency. The interaction of various physical, chemical and biological factors has been shown to have a profound effect on micropropagation. Light is one of the important physical variables that influences the growth and development of plants, especially in plant tissue culture, such as light-emitting diodes (LEDs). LED technology has proven to be advantageous for plant production in greenhouses for various purposes, including the induction of photomorphogenic responses of plants grown <em>in vitro</em>. Chemical and biological parameters such as media composition, growth regulators and choice of explants are also critical factors for micropropagation. This review summarizes the effects of biophysical-chemical factors on <em>in vitro</em> propagation as well as the production of haploids and doubled haploids (DHs). The review will also discuss the challenges associated with developing a standardized protocol for mass propagation and the production of haploids and DHs in strawberries, which will eventually help in breeding and crop improvement programs.</div></div>","PeriodicalId":38090,"journal":{"name":"Current Plant Biology","volume":"44 ","pages":"Article 100555"},"PeriodicalIF":4.5,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145362637","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}
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