Journal Detail

Research Article

ArticleID :JTPA/2025/11/01/01

Insights on the Mesembryanthemum forsskalii phenotype and study of the effects of several exogenous plant growth regulators via plant tissue culture

Issue No. 01 (Jan-Mar)

Authors: Sumayah I. Alsanie

Background: Samh (Mesembryanthemum forsskalii, M. cryptanthum) belongs to Aizoaceae family and is found in northern Saudi Arabia, primarily in desert or dry shrubland habitats. M. forsskalii is characterized by several nutritional and medicinal benefits. This study aimed to explore the phenotypic features of M. forsskalii and investigate the impact of exogenous plant growth regulators (PGRs) on this species using tissue culture techniques. Different auxin (naphthalene acetic acid (NAA), 2,4-dichlorophenoxyacetic acid (2,4-D) and indole butyric acid (IBA) in addition cytokinin (benzyl amino purine (BA), and kinetin (Ki) treatments were used.

Results: The phenotypic features of M. forsskalii included being decumbent to erect, with many terete succulent branches covered by epidermal bladder cells. Plant size determines its branching type, phyllotaxis, and inflorescence. Large plants have trichotomous branching; the two lower nodes have opposite decussate leaves; and compound dichasia. The flowers are pedicellate, perigynous, and have single, tricorporate pollen grains. Additionally, M. forsskalii has taproots, which differs from what was reported for M. forsskalii in previous studies in that it has fibrous roots. A 98% response rate was seen when the receptacle was used as an initiated explant. Adding BA to the MS medium also showed a significant increase in the size of the shoot system area and the number of roots. as well as the combined Ki + 2,4-D treatment had a significant effect on the callus volume. The callus color ranged from yellowish green to brown, and compact and rooty calli (callus cells differentiated into root hairs) were observed.

Conclusions: This study investigated the phenotypic features of M. forsskalii (samh), and its micropropagation that had not been previously reported in the literature. Its branching type, phyllotaxis, and inflorescence were described. The flowers are pedicellate, and the pollen grains are single, tricorporate, and oblate. M. forsskalii has taproots, which differs from what was reported for M. cryptanthum (M. forsskalii) in previous studies in that it has fibrous roots. Therefore, the difference in the type of root may be an indication that the variety found in the Al-Jouf area is different than the previous varieties. This study was the first to examine the impact of exogenous PGR on M. forsskalii under tissue culture conditions. Based on the results of this study, the use of 2 mg/ml BA for M. forsskalii micropropagation

How To Cite this Article

© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http//creativecommons.org//licensses/by-nc-nd/40/. 

Research Article

ArticleID :JTPA/2025/11/01/02

Expression divergence of BAG gene family in maize under heat stress

Issue No. 01 (Jan-Mar)

Authors: Babar Farid, Muhammad Abu Bakar Saddique, Muhammad Hammad Nadeem Tahir, Rao Muhammad Ikram, Zulfiqar Ali and Waseem Akbar

Heat stress poses a significant challenge for maize production, especially during the spring when high temperatures disrupt cellular processes, impeding plant growth and development. The B-cell lymphoma-2 (Bcl 2) associated athanogene (BAG) gene family is known to be relatively conserved across various species. It plays a crucial role as molecular chaperone cofactors that are responsible for programmed cell death and tumorigenesis. Once the plant is under heat stress, the BAG genes act as co-chaperones and modulate the molecular functions of HSP70/HSC70 saving the plant from the damage of high temperature stress. The study was planned to identify and characterize the BAG genes for heat stress responsiveness in maize. Twenty-one (21) BAG genes were identified in the latest maize genome. The evolutionary relationship of Zea mays BAGs (ZmBAGs) with Arabidopsis thaliana, Solanum lycopersicum, Theobroma cacao, Sorghum bicolor, Ananas comosus, Physcomitrium patens, Oryza sativa and Populus trichocarpa were represented by the phylogenetic analysis. Differential expressions of BAG gene family in leaf, endosperm, anther, silk, seed and developing embryo depict their contribution to the growth and development. The in-silico gene expression analysis indicated ZmBAG-8 (Zm00001eb170080), and ZmBAG-11 (Zm00001eb237960) showed higher expression under abiotic stresses (cold, heat and salinity). The RT-qPCR further confirmed the expression of ZmBAG-8 and ZmBAG-11 in plant leaf tissue across the contrasting inbred lines and their F1 hybrid (DR-139, UML-1 and DR-139 × UML-1) when exposed to heat stress. Furthermore, the protein-protein interaction networks of ZmBAG-8 and ZmBAG-11 further elucidated their role in stress tolerance related pathways. This research offers a roadmap to plan functional research and utilize ZmBAG genes to enhance heat tolerance in grasses.

How To Cite this Article

© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Research Article

ArticleID :JTPA/2025/11/01/03

Differential biochemical responses of seven Indian wheat genotypes to temperature stress

Issue No. 01 (Jan-Mar)

Authors: Satbhai Ravindra, Bharad Swati and Moharil Mangesh

Background: Changes in the temperature induction response are potential tools for the empirical assessment of plant cell tolerance. This technique is used to identify thermotolerant lines in field crops. In the present investiga tion, ten-day-old seedlings of six wheat genotypes released by Dr. PDKV, Akola, Maharashtra, India were exposed to gradual increases in high temperature and duration (control 25 °C to 30 °C for 1 h, 34 °C for 1 h, 38 °C for 2 h and 42 °C for 3 h) to investigate their effects on some physiological and biochemical parameters to provide basic information for improving heat-tolerant cultivars.

Results: Proline levels increased with increasing temperature up to 34 °C for 1 h but then decreased at higher temperatures (depending on genotype). Notably, proline levels decreased at 38 °C for 2 h in PDKV-Washim, AKAW 3722, and PDKV Sardar and at 42 °C for 3 h in all the genotypes. The relative leaf water content (RLWC) and chlo rophyll ’b’ content significantly decreased with increasing temperature. Hydrogen peroxide (H₂O₂) levels increased with temperature. The enzyme activities of superoxide dismutase (SOD), ascorbate peroxidase (APX), and peroxidase also increased with temperature. However, these parameters, along with other biochemical indicators, generally decreased at 42 °C for 3 h.

Conclusion: This study revealed positive relationships between increasing temperatures. Hydrogen peroxide levels and the activities of SOD, APX, and peroxidase enzymes across all the genotypes. The AKAW-4627 genotype pre sented better maintenance of physiological and biochemical parameters and lower H₂O₂ levels, indicating greater heat tolerance. Compared with PDKV-Washim and AKAW-3722, which are more susceptible to high temperatures, the WSM-109–04, AKAW-4627 and PDKV Sardar genotypes presented better adaptability to heat stress. These findings suggest that selecting wheat genotypes with higher proline accumulation and better maintenance of physiological and biochemical parameters under heat stress, such as AKAW-4627, can help in the development of heat-tolerant wheat cultivars.

How To Cite this Article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creativecommons.org/licen ses/by-nc-nd/4.0/

Research Article

ArticleID :JTPA/2025/11/01/04

The StbHLH47 transcription factor negatively regulates drought tolerance in potato (Solanum tuberosum L.)

Issue No. 01 (Jan-Mar)

Authors: Peijie Wang, Xiaojuan Wu, Nan Li, Hushuai Nie, Yu Ma, Juan Wu, Zhicheng Zhang and Yanhong Ma

Results: In this study, the StbHLH47 gene, which is highly expressed in potato leaves, was cloned and isolated. Subcellular localization assays revealed that the gene StbHLH47 performs transcriptional functions in the nucleus, as evidenced by increased malondialdehyde (MDA) content and relative conductivity under drought stress. These findings indicate that overexpressing plants are more sensitive to drought stress. Differential gene expression analysis of wild type plants (WT) and plants overexpressing StbHLH47 (OE-StbHLH47) under drought stress revealed that the significantly differentially expressed genes were enriched in metabolic pathways, biosynthesis of various plant secondary metabolites, biosynthesis of metabolites, plant hormone signal transduction, mitogen-activated protein kinase (MAPK) signaling pathway-plant, phenylpropanoid biosynthesis, and plant‒pathogen interactions. Among these pathways, the phenylalanine and abscisic acid (ABA) signal transduction pathways were enriched in a greater number of differentially expressed genes, and the expression trends of these differentially expressed genes (DEGs) were significantly different between WT and OE-StbHLH47. Therefore, it is speculated that StbHLH47 may regulate drought resistance mainly through these two pathways. Additionally, RT‒qPCR was used for fluorescence quantification of the expression of StNCED1 and StERD11, which are known for their drought resistance, and the results revealed that the expression levels were much lower in OE-StbHLH47 than in WT plants. 

Conclusion: RNA-seq, RT‒qPCR, and physiological index analyses under drought conditions revealed that overexpression of the StbHLH47 gene increased the sensitivity of potato plants to drought stress, indicating that StbHLH47 negatively regulates drought tolerance in potato plants. In summary, our results indicate that StbHLH47 is a negative regulator of drought tolerance and provide a theoretical basis for further studies on the molecular mechanism involved.

How To Cite this Article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Research Article

ArticleID :JTPA/2025/11/01/05

Assembly and analysis of the first complete mitochondrial genome sequencing of main Tea-oil Camellia cultivars Camellia drupifera (Theaceae): revealed a multi-branch mitochondrial conformation for Camellia

Issue No. 01 (Jan-Mar)

Authors: Heng Liang, Huasha Qi, Jiali Chen, Yidan Wang, Moyang Liu, Xiuxiu Sun, et.al.,

Background: Tea-oil Camellia within the genus Camellia is renowned for its premium Camellia oil, often described as “Oriental olive oil”. So far, only one partial mitochondrial genomes of Tea-oil Camellia have been published (no main Tea-oil Camellia cultivars), and comparative mitochondrial genomic studies of Camellia remain limited.

Results: In this study, we first reconstructed the entire mitochondrial genome of C. drupifera to gain insights into its genetic structure and evolutionary history. Through our analysis, we observed a characteristic multi-branched configuration in the mitochondrial genomes of C. drupifera. A thorough examination of the protein-coding regions (PCGs) across Camellia species identified gene losses that occurred during their evolution. Notably, repeat sequences showed a weak correlation between the abundance of simple sequence repeats (SSRs) and genome size of Camellia. Additionally, despite of the considerable variations in the sizes of Camellia mitochondrial genomes, there was little diversity in GC content and gene composition. The phylogenetic tree derived from mitochondrial data was inconsistent with that generated from chloroplast data.

Conclusions: In conclusion, our study provides valuable insights into the molecular characteristics and evolutionary mechanisms of multi-branch mitochondrial structures in Camellia. The high-resolution mitogenome of C. drupifera enhances our understanding of multi-branch mitogenomes and lays a solid groundwork for future advancements in genomic improvement and germplasm innovation within Tea-oil Camellia.

How To Cite this Article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

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ArticleID :JTPA/2025/11/02/01

Citrus phloem specific transcriptional profiling through the development of a citrus tristeza virus expressed translating ribosome affinity purification system

Issue No. 02 (Apr-June)

Authors: James N. Culver, Meinhart Vallar, Erik Burchard, Sophie Kamens, Sebastien Lair, et.al.,

Background: The analysis of translationally active mRNAs, or translatome, is a useful approach for monitoring cellular and plant physiological responses. One such method is the translating ribosome affinity purification (TRAP) system, which utilizes tagged ribosomal proteins to isolate ribosome-associated transcripts. This approach enables spatial and temporal gene expression analysis by driving the expression of tagged ribosomal proteins with tissue- or development-specific promoters. In plants, TRAP has enhanced our understanding of physiological responses to various biotic and abiotic factors. However, its utility is hampered by the necessity to generate transgenic plants expressing the tagged ribosomal protein, making this approach particularly challenging in perennial crops such as citrus. 

Results: This study involved the construction of a citrus tristeza virus (CTV) vector to express an immuno-tagged ribosome protein (CTV-hfRPL18). CTV, limited to the phloem, has been used for expressing marker and therapeutic sequences, making it suitable for analyzing citrus vascular tissue responses, including those related to huanglongbing disease. CTV-hfRPL18 successfully expressed a clementine-derived hfRPL18 peptide, and polysome purifications demonstrated enrichment for the hfRPL18 peptide. Subsequent translatome isolations from infected Nicotiana benthamiana and Citrus macrophylla showed enrichment for phloem-associated genes.

Conclusion: The CTV-hfRPL18 vector offers a transgene-free and rapid system for TRAP expression and translatome analysis of phloem tissues within citrus.

How To Cite this Article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Research Article

ArticleID :JTPA/2025/11/02/02

Lightweight highland barley detection based on improved YOLOv5

Issue No. 02 (Apr-June)

Authors: Minghui Cai, Hui Deng, Jianwei Cai, Weipeng Guo, Zhipeng Hu, Dongzheng Yu and Houxi Zhang

Accurate and efficient assessment of highland barley (Hordeum vulgare L.) density is crucial for optimizing cultivation and management practices. However, challenges such as overlapping spikes in unmanned aerial vehicle (UAV) images and the computational requirements for high-resolution image analysis hinder real-time detection capabilities. To address these issues, this study proposes an improved lightweight YOLOv5 model for highland barley spike detection. We chose depthwise separable convolution (DSConv) and ghost convolution (GhostConv) for the backbone and neck networks, respectively, to reduce the parameter and computational complexity. In addition, the integration of convolutional block attention module (CBAM) enhances the model’s ability to focus on target object in complex backgrounds. The results show that the improved YOLOv5 model has a significant improvement in detection performance. Precision and recall increased by 3.1% to 92.2% and 86.2%, respectively, with an F1 score of 0.892. The AP0.5 reaches 92.7% and 93.5% for highland barley in the growth and maturation stages, respectively, and the overall mAP0.5 improved to 93.1%. Compared to the baseline YOLOv5n model, the number of parameters and floating-point operations (FLOPs) were reduced by 70.6% and 75.6%, respectively, enabling lightweight deployment without compromising accuracy. In addition,the proposed model outperformed mainstream object detection algorithms such as Faster R-CNN, Mask R-CNN, RetinaNet, YOLOv7, and YOLOv8, in terms of detection accuracy and computational efficiency. Although this study also suffers from limitations such as insufficient generalization under varying lighting conditions and reliance on rectangular annotations, it provides valuable support and reference for the development of real-time highland barley spike detection systems, which can help to improve agricultural management.

How To Cite this Article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creativecommons.org/licenses/by-nc-nd/4.0/.

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ArticleID :JTPA/2025/11/02/03

Efficient mutagenesis and genotyping of maize inbreds using biolistics, multiplex CRISPR/Cas9 editing, and Indel-Selective PCR

Issue No. 02 (Apr-June)

Authors: Maruti Nandan Rai, Brian Rhodes, Stephen Jinga, Praveena Kanchupati, Edward Ross, Shawn R. Carlson and Stephen P. Moose

CRISPR/Cas9 based genome editing has advanced our understanding of a myriad of important biological phenomena. Important challenges to multiplex genome editing in maize include assembly of large complex DNA constructs, few genotypes with efficient transformation systems, and costly/labor-intensive genotyping methods. Here we present an approach for multiplex CRISPR/Cas9 genome editing system that delivers a single compact DNA construct via biolistics to Type I embryogenic calli, followed by a novel efficient genotyping assay to identify desirable editing outcomes. We first demonstrate the creation of heritable mutations at multiple target sites within the same gene. Next, we successfully created individual and stacked mutations for multiple members of a gene family. Genome sequencing found off-target mutations are rare. Multiplex genome editing was achieved for both the highly transformable inbred line H99 and Illinois Low Protein1 (ILP1), a genotype where transformation has not previously been reported. In addition to screening transformation events for deletion alleles by PCR, we also designed PCR assays that selectively amplify deletion or insertion of a single nucleotide, the most common outcome from DNA repair of CRISPR/Cas9 breaks by non-homologous end-joining. The Indel-Selective PCR (IS PCR) method enabled rapid tracking of multiple edited alleles in progeny populations. The ‘end to end’ pipeline presented here for multiplexed CRISPR/Cas9 mutagenesis can be applied to accelerate maize functional genomics in a broader diversity of genetic backgrounds.

How To Cite this Article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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ArticleID :JTPA/2025/11/02/04

A rapid and efficient in vivo inoculation method for introducing tree stem canker pathogens onto leaves: suitable for large-scale assessment of resistance in poplar breeding progeny

Issue No. 02 (Apr-June)

Authors: Zheng Li, Bingyu Zhang, Yuchen Fu, Yutian Suo, Yinan Zhang, Jinxia Feng, Long Pan, Wanna Shen, Huixiang Liu, Xiaohua Su and Jiaping Zhao

Background: Hybrid breeding, a direct and efficient strategy for disease control and management in tree species, is currently limited by the selection method of resist clones: the “in vitro stem segment inoculation method”. This method, constrained by the availability of inoculating materials, cannot rapidly, efficiently, and cost-effectively screen the resistance of all hybrid clones. To overcome these limitations, we introduce a novel pathogen inoculation method for the resistance assessment of hybrid clones in the poplar-Valsa sordida pathosystem. This method involves inoculating the stem canker pathogen on the host leaf, a unique and promising approach we have successfully validated. 

Results: Results showed that stem canker pathogen V. sordida induced the extended necrotic lesion and even induced the formation of pycnidium structure and conidia on the leaf surface 5 days after mycelium inoculation; (1) the upper 5–7thleaves exhibited higher resistance than the middle 18–20th leaves; (2) the shading conditions induced more severe symptoms on the leaves than lighting conditions; (3) the poplar leaves were more susceptible to the juvenile mycelium inoculums (4-day-cultured) than the old ones (7-day-cultured). Our results demonstrate the robustness ofthe “in vivo leaf inoculation method” in revealing the resistance differentiation in poplar hybrid clones. According to the leaf necrotic area disease index, we divided these poplar clones into seven different resist ance groups. The resistance assessed by leaf assessment was validated in 15 selected poplar clones using the “in vitro stem segment inoculation method”. Results showed that the effectiveness of these two methods was consist ent. Moreover, results also revealed the pathogenicity diversity of the pathogen population of tree species using leaf the inoculation method. 

Conclusions: Compared to the conventional “in vitro stem segment inoculation method”, the leaf method has the advantages of abundant inoculation materials, easy operation, rapid disease onset, and almost no adverse effect on the host. It is particularly suitable for the resistance screening of all progeny and the early (seedling)

How To Cite this Article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creativecommons.org/licenses/by-nc-nd/4.0/.

Research Article

ArticleID :JTPA/2025/11/02/05

GrainNet: efficient detection and counting of wheat grains based on an improved YOLOv7 modeling

Issue No. 02 (Apr-June)

Authors: Xin Wang, Changchun Li, Chenyi Zhao, Yinghua Jiao, Hengmao Xiang, Xifang Wu and Huabin Chai

Background: Seed testing plays a crucial role in improving crop yields.In actual seed testing processes, factors such as grain sticking and complex imaging environments can significantly affect the accuracy of wheat grain counting, directly impacting the effectiveness of seed testing. However, most existing methods primarily focus on simple counting tasks and lack general applicability.

Results: To enable fast and accurate counting of wheat grains under severe adhesion and complex scenarios, this study collected images of wheat grains from different varieties, backgrounds, densities, imaging heights, adhesion levels, and other natural conditions using various imaging devices and constructed a comprehensive wheat grain dataset through data enhancement techniques. We propose a wheat grain detection and counting model called GrainNet, which significantly improves the counting performance and detection speed across diverse conditions and adhesion levels by incorporating lightweight and efficient feature fusion modules. Specifically, the model incorporates an Efficient Multi-scale Attention (EMA) mechanism, effectively mitigating the interference of background noise on detection results. Additionally, the ASF-Gather and Distribute (ASF-GD) module optimizes the feature extraction component of the original YOLOv7 network, improving the model’s robustness and accuracy in complex scenarios. Ablation experiments validate the effectiveness of the proposed methods.Compared with classic models such as Faster R-CNN, YOLOv5, YOLOv7, and YOLOv8, the GrainNet model achieves better detection performance and computational efficiency in various scenarios and adhesion levels. The mean Average Precision reached 93.15%, the F1 score was 0.946, and the detection speed was 29.10 frames per second (FPS). A comparative analysis with manual counting results revealed that the GrainNet model achieved the highest coefficient of determination and Mean Absolute Error values for wheat grain counting tasks, which were 0.93 and 5.97, respectively, with a counting accuracy of 94.47%.

Conclusions: Overall, the GrainNet model presented in this study enables accurate and rapid recognition and quantification of wheat grains, which can provide a reference for effective seed examination of wheat grains in real scenarios. Related content can be accessed through the following link: https://gitub.com/1371530728/grainnet.git

How To Cite this Article

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Others

ArticleID :JTPA/2025/11/03/01

Optical coherence tomography for early detection of crop infection

Issue No. 03 (July-Sept)

Authors: Ghada Salem Sasi, Stephen J. Matcher and Adrien Alexis Paul Chauvet

Background: Fungal diseases are among the most significant threats to global crop production, often leading to sub stantial yield losses. Early detection of crop infection by fungus is the very first step to deploying a timely and effec tive treatment. Early and reliable detection is thus key to improving yields, sustainability, and achieving food security. Conventional diagnostic methods are however often destructive, slow, or requiring visible symptoms which appear late in the infection process. To overcome these challenges, we propose using optical coherence tomography (OCT) as an innovative imaging tool to provide cross-sectional and three-dimensional images of the plant internal micro structure non-invasively, in vivo, and in real-time. 

Results: We demonstrate the use of low-cost OCT to monitoring wheat (cultivar AxC 169) when infected by Septoria tritici. We show that OCT analysis can effectively detect signs of infection before any external symptoms appear. Although OCT cannot directly visualize fungal hyphae, OCT reveals apparent morphological changes of the mesophyll where the fungal filaments are expected to develop. This study thus focuses on monitoring and correlating changes within the mesophyll structural organisation with the state of infection. It results in distinct statistical difference between intact and infected wheat plants two days only after infection. We then demonstrate the use of machine learning (ML) for high throughput segmentation of OCT scans, providing a foundation for future auto mated fungus-detection analysis. 

Conclusions: This work highlights the potential of OCT, combined with ML tools, to enable rapid, non-invasive, and early diagnosis of crop fungal infections, opening new avenues for precision agriculture and sustainable disease management.

How To Cite this Article

Sasi, G.S., Matcher, S.J. & Chauvet, A.A.P. Optical coherence tomography for early detection of crop infection. Plant Methods 21, 92 (2025). https://doi.org/10.1186/s13007-025-01411-7

Research Article

ArticleID :JTPA/2025/11/03/02

Attomolar electrochemical direct and sandwich immunoassays for the ultrasensitive detection of tomato brown rugose fruit virus

Issue No. 03 (July-Sept)

Authors: Negin Rezaei, Ahmad Moshaii, Mohammad Reza Safarnejad, Reza H. Sajedi, Mahsa Rahmanipour and Masoud Shams-Bakhsh

Tomato brown rugose fruit virus (TBRFV; Tobamovirus fructirugosum) is a highly virulent tobamovirus that has emerged as a major global threat to tomato and pepper crops over the past decade. Early and ultra-sensitive detection of TBRFV is critical for effective disease management and the mitigation of agricultural losses. In this study, a highly sensitive electrochemical immunosensor was developed based on both direct and sandwich immunoassays for the detection of TBRFV. The assay employs TBRFV-CP-IgG and TBRFV-CP-IgGHRP antibodies, with the latter conjugated to horseradish peroxidase (HRP). The immunoassays were assembled on a nanoporous gold electrode, providing an enhanced electroactive surface for efficient antigen capture and signal amplification. Electrochemical characterization confirmed the successful immobilization of TBRFV-CP-IgG, its specific interaction with the recombinant coat protein of TBRFV (rp-CP-TBRFV), the subsequent binding of TBRFV-CP-IgGHRP as the detection antibody, and the formation of the complete sandwich complex. The assays achieved linear detection ranges of 10–10⁵ fg/mL. The direct assay yielded a limit of detection (LoD) of 1.14 fg/mL (65.14 aM), while the sandwich assay, enhanced by enzymatic amplification, achieved 1.06 fg/mL (60.57 aM). The direct assay’s simplicity suits rapid diagnostics, whereas the sandwich assay’s superior sensitivity is ideal for low-concentration samples. Electrochemical characterization confirmed specific antigen capture and signal amplification. The biosensor demonstrated high specificity, distinguishing TBRFV from other viruses, and detected TBRFV in leaf and seed extracts, offering a promising platform for agricultural biosecurity.

How To Cite this Article

Rezaei, N., Moshaii, A., Safarnejad, M.R. et al. Attomolar electrochemical direct and sandwich immunoassays for the ultrasensitive detection of tomato brown rugose fruit virus. Plant Methods 21, 91 (2025). https://doi.org/10.1186/s13007-025-01407-3

Others

ArticleID :JTPA/2025/11/03/03

A new phenotyping method for root growth studies in compacted soil validated by GWAS in barley

Issue No. 03 (July-Sept)

Authors: Giorgia Carletti, Agostino Fricano, Elisabetta Mazzucotelli and Luigi Cattivelli

Background: Soil compaction is defined as the reduction of air-filled pore space affecting soil density, water conductivity and nutrient availability. These conditions negatively influence root morphology, root development and plant growth leading to yield loss. To date, the ability of roots to penetrate compacted soil has been investigated using high density agar or wax-petrolatum layers as a proxy for compaction. Nevertheless, these methods are not realistic and fail to account for the root-soil interaction that influences root growth ability.

Results: Artificially compacted soil lumps were prepared using natural field soil mixed with sand and vermiculite in a 1:1:0.2 ratio and adjusted to a final water content of 31%. A Genome Wide Association Study (GWAS) was performed to validate this new methodology, combining a panel of 139 barley cultivars with a Single Nucleotide Polymorphism (SNP) dataset of 5,317 polymorphic markers. The panel was evaluated at seedling stage for four traits: total root length, average of diameter width, seminal root number, shoot: root weight ratio and two novel Quantitative Trait Loci (QTLs) associated with total root length were identified on Chr 4 H and 5 H. Four genes (a Nitrate Transporter1 (NRT1)/Peptide Transporter (PTR) family protein 2.2, a Hedgehog-interacting-like protein, an expansin and a cyclic nucleotide-gated channel) were hypothesized as plausible candidates for further investigation, given their implication in root development. In addition, the new phenotyping method revealed an altered plagiogravitropism phenomenon in barley during root emergence in compact substrates. In uncompacted soil, only the primary root exhibits vertical gravitropic set-point angle while a variable number of embryonic seminal roots develop with a shallower growth angle. In contrast, in compacted substrate all roots developed vertically to restore the growth angle after reaching a length of 4–5 millimetres.

Conclusions: A methodology based on root-soil interaction is presented as a new method for root growth evaluation and genomic studies in seedlings growing in compacted soil.

How To Cite this Article

Carletti, G., Fricano, A., Mazzucotelli, E. et al. A new phenotyping method for root growth studies in compacted soil validated by GWAS in barley. Plant Methods 21, 93 (2025). https://doi.org/10.1186/s13007-025-01408-2

Research Article

ArticleID :JTPA/2025/11/03/04

Ionic liquid-assisted seed genomic DNA extraction for advanced sequencing applications

Issue No. 03 (July-Sept)

Authors: Shashini De Silva, Philip C. Bentz, Cecilia Cagliero, Morgan R. Gostel, Gabriel Johnson and Jared L. Anderson

Background:  Modern plant breeding strategies rely on the intensive use of advanced genomic tools to expedite the development of improved crop varieties. Genomic DNA extraction from crop seeds eliminates the need to grow plants in contrast to fresh leaf tissue; however, it can still be a bottleneck due to the presence of stored compounds and the complexity of the matrix. The interaction of environmentally benign choline-based ionic liquids (ILs) with DNA offers an innovative approach to enhance the quality of extracted DNA from seeds. While prior IL-based plant DNA extraction workflows have primarily supported polymerase chain reaction (PCR) and quantitative PCR-based applications, their suitability for high-throughput sequencing (HTS) remained largely unexplored. This study explores the efficacy of IL-assisted method for genomic DNA extraction from soybean (Glycine max) seeds, addressing the limited application of ILs in HTS.

Results: The optimized DNA extraction method, utilizing 25% (w/v) choline formate, enabled the recovery of high-purity DNA with abundant fragment sizes > 20 kb, suitable for downstream applications including PCR, whole genome amplification (WGA), simple sequence repeat (SSR) amplification, and high-throughput Illumina sequencing. The IL-method was benchmarked against a silica-binding method using cetyltrimethylammonium bromide (CTAB) and sodium dodecyl sulfate (SDS) as lysis agents using a commercial plant DNA extraction kit in terms of DNA yield, purity, abundant DNA fragment size distribution, and integrity. In addition, DNA isolated from this method demonstrated successful PCR amplification of markers from both the nuclear and plastid genomes and yielded > 99% whole genome coverage with Illumina (PE150) sequencing reads.

Conclusions: This is the first known instance of a whole genome sequence generated from DNA extracted with ILs. These findings mark a significant milestone in establishing ILs as promising alternatives to conventional methods for seed DNA extraction, with potential utility in third generation (long-read) sequencing experiments.

How To Cite this Article

De Silva, S., Bentz, P.C., Cagliero, C. et al. Ionic liquid-assisted seed genomic DNA extraction for advanced sequencing applications. Plant Methods 21, 97 (2025). https://doi.org/10.1186/s13007-025-01417-1

Research Article

ArticleID :JTPA/2025/11/03/05

YOLOV8-CMS: a high-accuracy deep learning model for automated citrus leaf disease classification and grading

Issue No. 03 (July-Sept)

Authors: Hongyan Zhu, Dani Wang, Yuzhen Wei, Pengcheng Wang and Min Su

Background: Citrus leaf diseases significantly affect production efficiency and fruit quality in the citrus industry. To effectively identify and classify citrus leaf diseases, this study proposed a classification approach leveraging deep learning techniques (YOLOV8 equipped with CSPPC, MultiDimen, SpatialConv, YOLOV8-CMS). Additionally, a segmentation method was utilized to extract leaf and lesion areas for disease severity grading based on their pixel ratio.

Results:  By collecting and preprocessing a citrus leaf image dataset, the YOLOV8-CMS model was trained for disease classification. The model integrated MultiDimen attention, SpatialConv, and the CSPPC module to enhance performance. Furthermore, a segmentation approach was applied to precisely segment both leaf and lesion areas, enabling a quantitative assessment of disease severity. To verify the effectiveness of the proposed approach, multiple YOLO based architectures, including different YOLOV8 series models, YOLOV5, and YOLOV3, were compared and analyzed. Results demonstrated that the proposed method achieved outstanding performance in citrus leaf disease classification, with an mAP50 of 98.2% in distinguishing healthy and diseased leaves and an accuracy of 97.9% in multi-class disease classification tasks.

Conclusions: The proposed YOLOV8-CMS model outperformed traditional methods in citrus leaf disease classification, while the segmentation-based approach enabled an accurate and quantitative assessment of disease severity. These findings highlighted the potential of deep learning in precision agriculture, contributing to more effective disease management in citrus production.

How To Cite this Article

Zhu, H., Wang, D., Wei, Y. et al. YOLOV8-CMS: a high-accuracy deep learning model for automated citrus leaf disease classification and grading. Plant Methods 21, 88 (2025). https://doi.org/10.1186/s13007-025-01396-3

Research Article

ArticleID :JTPA/2025/11/04/01

Truncated CMV2bN43 enhances virus-induced gene silencing in pepper by retaining systemic but not local silencing suppression

Issue No. 04 (Oct-Dec)

Authors: Yingjia Zhou, Yaqi Wang, Dunyu Huang and Feng Li

Pepper is an economically important crop. Owing to its recalcitrance to genetic transformation, virus-induced gene silencing (VIGS) is currently the major technique available for validating gene function in pepper. However, the low efficiency and difficulty of silencing genes in reproductive organs remain major challenges in pepper VIGS studies. To address these limitations, we developed an optimized VIGS system by structure-guided truncation of the Cucumber mosaic virus 2b (C2b) silencing suppressor. A silencing suppression assay revealed that the C2bN43 mutant retained systemic silencing suppression while abrogated local silencing suppression activity in systemic leaves. The engineered TRV-C2bN43 system significantly enhanced VIGS efficacy in pepper, providing a powerful tool for functional genomics studies in pepper. By leveraging transcriptomic profiles, we identified CaAN2, an anther-specific MYB transcription factor, whose suppression via TRV-C2bN43 perturbation resulted in coordinated downregulation of structural genes in anthocyanin biosynthesis pathway and abolished anthocyanin accumulation in anthers establishing its essential regulatory role in pigmentation. This study validated and provided mechanistic insight for a further optimized VIGS system in pepper.

How To Cite this Article

Zhou, Y., Wang, Y., Huang, D. et al. Truncated CMV2bN43 enhances virus-induced gene silencing in pepper by retaining systemic but not local silencing suppression. Plant Methods 21, 132 (2025). https://doi.org/10.1186/s13007-025-01446-w

Others

ArticleID :JTPA/2025/11/04/02

An optimized DNA extraction protocol for reliable PCR-based detection and characterization of grapevine flavescence dorée phytoplasma

Issue No. 04 (Oct-Dec)

Authors: Marco Carli, Athos Pedrelli, Alessandra Panattoni, Elisa Pellegrini, Cristina Nali, Lorenzo Cotrozzi and Domenico Rizzo

Background: Flavescence dorée (FD) is one of the most damaging grapevine diseases in Europe, caused by the quarantine-listed Grapevine flavescence dorée phytoplasma (FDp). Given the absence of resistant cultivars and curative treatments, effective disease control relies on early and accurate FDp detection. PCR-based diagnostics are the gold standard, but their accuracy depends on DNA extraction quality. Grapevine tissues contain PCR inhibitors like polysaccharides and polyphenols, complicating DNA isolation. While CTAB methods yield high-quality DNA, they are time-consuming, and commercial kits provide purer but often lower DNA yields at high costs. A rapid and optimized DNA extraction method for FDp detection is urgently needed.

Results: We developed the “HotShot Vitis” (HSV) method, a modified HotSHOT protocol optimized for grapevine tissues. HSV was benchmarked against the CTAB method and a commercial silica membrane kit. Although HSV showed limitations in DNA quantification due to buffer composition, it efficiently extracted DNA suitable for amplifying the grapevine trnL-F gene and detecting FDp by two qPCR assays. DNA extracted by HSV also supported molecular typing and sequencing of FDp 16 S rRNA and map genes, performing comparably to CTAB and the commercial kit. Importantly, HSV reduced the extraction time to about 30 min, significantly faster than the CTAB (2 h) and kit (40 min) methods.

Conclusions: HSV is a fast, reliable, and chemically low-risk DNA extraction method for FDp detection and characterization in grapevine. Its efficiency and simplicity make HSV ideal for large-scale diagnostics and early disease management.

How To Cite this Article

Carli, M., Pedrelli, A., Panattoni, A. et al. An optimized DNA extraction protocol for reliable PCR-based detection and characterization of grapevine flavescence dorée phytoplasma. Plant Methods 21, 131 (2025). https://doi.org/10.1186/s13007-025-01460-y

Research Article

ArticleID :JTPA/2025/11/04/03

EBS-YOLO: edge-optimized bidirectional spatial feature augmentation for in-field detection of wheat Fusarium head blight epidemics

Issue No. 04 (Oct-Dec)

Authors: Rui Mao, Hongli Yuan, Feilong Li, Ying Shi, Jia Zhou, Xuemei Hu and Xiaoping Hu

Fusarium head blight (FHB), caused by the Fusarium species complex, significantly endangers wheat yield and safety. Accurate and timely assessment of FHB epidemic level in the field is crucial for effective disease management. However, the complex environment and indistinct edges of diseased areas present substantial challenges in distinguishing between healthy and diseased ears, thereby impacting the accuracy of FHB epidemic level detection. This study proposes EBS-YOLO, a novel Edge-Optimized Bidirectional Spatial Feature Augmentation YOLO Network, specifically designed for the rapid and precise determination of FHB epidemic levels at the canopy level. The Focal-Edge Selection Module (FSM) within the backbone replaces original C2f module to enhance edge feature representation and facilitate multi-scale feature extraction. Furthermore, the Dual Spatial-Connection Feature Pyramid Network (DSCFPN), integrating Global-to-Local Spatial Aggregation (GLSA) with bidirectional pyramid interaction, balances global and local feature acquisition while optimizing the feature fusion mechanism. This design enables the model to effectively handle occlusions, scale variations, and complex environments. Experimental results demonstrate substantial improvements over eight comparative models in detecting healthy and diseased wheat ears, achieving mean Average Precision (mAP) of 86.1% and 82.9%, respectively. Notably, the model achieved a mean accuracy of 94.7% in detecting FHB epidemic levels through rigorous spatiotemporal validation using datasets collected from independent fields across different years, underscoring its robust generalization capability. Characterized by its low complexity and lightweight design, EBS-YOLO features a parameter count of 2.05 M, 7.4 GFLOPs, and a model size of 5.0 MB, making it an efficient approach for real-time FHB epidemic level detection.

How To Cite this Article

Mao, R., Yuan, H., Li, F. et al. EBS-YOLO: edge-optimized bidirectional spatial feature augmentation for in-field detection of wheat Fusarium head blight epidemics. Plant Methods 21, 133 (2025). https://doi.org/10.1186/s13007-025-01449-7

Research Article

ArticleID :JTPA/2025/11/04/04

Large-scale non-destructive crown-level assessment of Ginkgo pigments via hyperspectral and machine learning techniques

Issue No. 04 (Oct-Dec)

Authors: Xin Yang, Zihan Wei, Lehao Li, Xiaoming Yang, Jimei Han, Meiling Ming, Guibin Wang, Fuliang Cao, Kai Zhou and Fangfang Fu

The photosynthetic pigments – chlorophyll a (Chl a), chlorophyll b (Chl b), and carotenoids (Car) – in juvenile ginkgo leaves are crucial for growth monitoring as they reflect physiological status and directly influence the biosynthesis of bioactive compounds such as flavonoids and terpene lactones. Traditional pigment measurement methods (acetone/ethanol extraction, SPAD, etc.) are inadequate for large-scale dynamic monitoring and high-throughput phenotyping analysis. To address this, this study developed a non-destructive prediction model for Chl a, Chl b, and Car contents in ginkgo seedlings using hyperspectral imaging combined with machine learning algorithms, which is applicable to seedlings with different genetic backgrounds and at various color development phases. A total of 3,460 seedlings from 590 families, sourced from ancient trees across 19 provinces in China, were analyzed using hyperspectral imaging and biochemical pigment quantification. A phased optimization strategy was implemented, including preprocessing method screening, model comparison, and feature wavelength selection. Among the four tested preprocessing methods (raw reflectance, normalization, first derivative, and second derivative), normalization significantly improved model accuracy. The Adaptive Boosting (AdaBoost) algorithm outperformed partial least squares regression (PLSR) and random forest (RF), achieving coefficients of determination (R²) above 0.83 and the ratio of performance to deviation (RPD) values exceeding 2.4 across all pigments. Compared with competitive adaptive reweighted sampling (CARS), the successive projections algorithm (SPA) demonstrated more effective spectral dimensionality reduction while preserving predictive power. This framework enables efficient, accurate, and scalable pigment phenotyping in Ginkgo biloba, offering technical support for large-scale germplasm screening and precision breeding.

How To Cite this Article

Yang, X., Wei, Z., Li, L. et al. Large-scale non-destructive crown-level assessment of Ginkgo pigments via hyperspectral and machine learning techniques. Plant Methods 21, 130 (2025). https://doi.org/10.1186/s13007-025-01439-9

Others

ArticleID :JTPA/2025/11/04/05

AlloSHP: deconvoluting single homeologous polymorphism for phylogenetic analysis of allopolyploids

Issue No. 04 (Oct-Dec)

Authors: R. Sancho, P. Catalán, J. P. Vogel and B. Contreras-Moreira

Background: The genomic and evolutionary study of allopolyploid organisms involves multiple copies of homeologous chromosomes, making their assembly, annotation, and phylogenetic analysis challenging. Bioinformatics tools and protocols have been developed to study polyploid genomes, but sometimes require the assembly of their genomes, or at least the genes, limiting their use.

Results: We have developed AlloSHP, a command-line tool for detecting and extracting single homeologous polymorphisms (SHPs) from the subgenomes of allopolyploid species. This tool integrates three main algorithms, WGA, VCF2ALIGNMENT and VCF2SYNTENY, and allows the detection of SHPs for the study of diploid-polyploid complexes with available diploid progenitor genomes, without assembling and annotating the genomes of the allopolyploids under study. AlloSHP has been validated on three diploid-polyploid plant complexes, Brachypodium, Brassica, and Triticum-Aegilops, and a set of synthetic hybrid yeasts and their progenitors of the genus Saccharomyces. The results and congruent phylogenies obtained from the four datasets demonstrate the potential of AlloSHP for the evolutionary analysis of allopolyploids with a wide range of ploidy and genome sizes.

Conclusions: AlloSHP combines the strategies of simultaneous mapping against multiple reference genomes and syntenic alignment of these genomes to call SHPs, using as input data a single VCF file and the reference genomes of the known or closest extant diploid progenitor species. This novel approach provides a valuable tool for the evolutionary study of allopolyploid species, both at the interspecific and intraspecific levels, allowing the simultaneous analysis of a large number of accessions and avoiding the complex process of assembling polyploid genomes.

How To Cite this Article

Sancho, R., Catalán, P., Vogel, J.P. et al. AlloSHP: deconvoluting single homeologous polymorphism for phylogenetic analysis of allopolyploids. Plant Methods 21, 134 (2025). https://doi.org/10.1186/s13007-025-01458-6