农学最新文献

{"title":"Plant graph-based pangenomics: techniques, applications, and challenges.","authors":"Ze-Zhen Du, Jia-Bao He, Wen-Biao Jiao","doi":"10.1007/s42994-025-00206-7","DOIUrl":"10.1007/s42994-025-00206-7","url":null,"abstract":"<p><p>Innovations in DNA sequencing technologies have greatly boosted population-level genomic studies in plants, facilitating the identification of key genetic variations for investigating population diversity and accelerating the molecular breeding of crops. Conventional methods for genomic analysis typically rely on small variants, such as SNPs and indels, and use single linear reference genomes, which introduces biases and reduces performance in highly divergent genomic regions. By integrating the population level of sequences, pangenomes, particularly graph pangenomes, offer a promising solution to these challenges. To date, numerous algorithms have been developed for constructing pangenome graphs, aligning reads to these graphs, and performing variant genotyping based on these graphs. As demonstrated in various plant pangenomic studies, these advancements allow for the detection of previously hidden variants, especially structural variants, thereby enhancing applications such as genetic mapping of agronomically important genes. However, noteworthy challenges remain to be overcome in applying pangenome graph approaches to plants. Addressing these issues will require the development of more sophisticated algorithms tailored specifically to plants. Such improvements will contribute to the scalability of this approach, facilitating the production of super-pangenomes, in which hundreds or even thousands of de novo-assembled genomes from one species or genus can be integrated. This, in turn, will promote broader pan-omic studies, further advancing our understanding of genetic diversity and driving innovations in crop breeding.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"6 2","pages":"361-376"},"PeriodicalIF":4.6,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12237840/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient data filtering with multiple group conditions: a command tool for bioinformatics data analysis.","authors":"Wenpeng Deng, Jianye Chang, Alun Li, He Xie, Jue Ruan","doi":"10.1007/s42994-025-00207-6","DOIUrl":"https://doi.org/10.1007/s42994-025-00207-6","url":null,"abstract":"<p><p>Bioinformatics analysis often requires the filtering of multi-datasets, based on frequency or frequency of occurrence, for decisions on retention or deletion. Existing tools for this purpose often present a challenge with complex installation, which necessitate custom coding, thereby impeding efficient data processing activities. To address this issue, Filterx, a user-friendly command line tool that written in C language, was developed that supports multi-condition filtering, based on frequency or occurrence. This tool enables users to complete the data processing tasks through a simple command line, greatly reducing both workload and data processing time. In addition, future development of this tool could facilitate its integration into various bioinformatics data analysis pipelines.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"6 2","pages":"274-277"},"PeriodicalIF":4.6,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12237833/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of cultivating biotech maize GG2 and glyphosate treatment on the rhizospheric microbial community structure.","authors":"Yinxiao Wang, Yihe Hao, Shengyan Li, Ning Wen, Mingyuan Yin, Zhihong Lang","doi":"10.1007/s42994-025-00205-8","DOIUrl":"10.1007/s42994-025-00205-8","url":null,"abstract":"<p><p>In environmental biosafety assessments of glyphosate-tolerant crops, it is essential to evaluate the effects of cultivating these crops and applying glyphosate on the microbial community in the rhizosphere soil, which play a critical role in maintaining soil health, plant growth, and crop productivity. Maize (<i>Zea mays</i>) line GG2 was previously generated by transforming wild-type maize with the <i>gat</i> and <i>gr79-epsps</i> genes, endowing GG2 with both active and passive resistance to glyphosate. However, the ecological risk of introducing these two new glyphosate-tolerance genes into maize, as well as glyphosate treatment, to rhizosphere microorganisms remain unclear. In this study, we used high-throughput sequencing to analyze the diversity and composition of the bacterial and fungal communities in the rhizosphere soil around biotech maize GG2, with (GG2-H) and without glyphosate treatment (GG2-N), compared with the near-isogenic, non-biotech maize line ZD958 at seven stages of growth. The structure and diversity of the bacterial and fungal communities of GG2-H were similar to those of ZD958, whereas glyphosate treatment had temporary effects on bacterial and fungal diversity and richness. The differences in the bacterial and fungal communities were associated with changes in soil properties such as pH, available phosphorus and organic matter, and seasonal changes. These factors, rather than maize lines, made the greatest contributions to the shifts in bacterial and fungal community structure. This study provides a comprehensive analysis of the effects of biotech crop cultivation, glyphosate treatment, soil physicochemical properties of soil, and maize growth stages on soil microbial communities, offering valuable insights for the large-scale adoption of biotech crops in China.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s42994-025-00205-8.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"6 2","pages":"174-188"},"PeriodicalIF":4.6,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12237839/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interactive effect of potassium and zinc application on oil yield of sunflower","authors":"Farid Hellal,&nbsp;Doaa Abou Basha,&nbsp;Saied El Sayed,&nbsp;Hanan Abdelkader","doi":"10.1016/j.ocsci.2025.03.001","DOIUrl":"10.1016/j.ocsci.2025.03.001","url":null,"abstract":"<div><div>Several initiatives have been made in Egypt to increase the overall production of oil crops, especially sunflower and to close the gap between edible oil production and demand. Field experiments were conducted during the main seasons of 2022 and 2023 ​at the agricultural research station of National Research Centre, Nubaria, Egypt to investigate the effects of potassium nitrate (0, 20, 40, 60 ​kg K₂O fed⁻¹) (fed ​= ​feddan ​= ​2.4 ​ha) and zinc sulfate (0, 25, 50, 75 ​ppm Zn) on growth, oil yield, nutrients components and chemical composition of sunflower. Results indicated that application of potassium nitrate has a promoted effect on chlorophyll content, growth parameters (Head weight, head diameter and 100 seed weight), protein content, oil yield as well as nutrient content under all applied levels. The data also showed that the highest significant increase occurred with the soil application of 40 ​kg fed⁻¹ potassium nitrate combined with 75 ​ppm Zn foliar spray. Meanwhile, the lowest values were obtained at the control treatment. Therefore, the current study detected that potassium soil addition at 40 ​kg K₂O fed⁻¹, besides foliar application with 75 ​ppm Zn are important to improve the growth, macro-micronutrient, seeds and oil productivity of sunflower crops. Oil yield and nutrient content exhibit a strong positive correlation, with a correlation coefficient of 0.903 for N, 0.94 for P, 0.962 for K and 0.966 for Zn. This indicates that a higher nutrient percentage is associated with higher oil content of sunflower. Study underscores the importance of comprehending the interplay between potassium and zinc treatments in sunflower plants to enhance growth, yield, and oil production effectively. Understanding these relationships can lead to optimized cultivation practices and improved outcomes in sunflower farming.</div></div>","PeriodicalId":34095,"journal":{"name":"Oil Crop Science","volume":"10 2","pages":"Pages 79-86"},"PeriodicalIF":0.0,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907930","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}

{"title":"Correction to: Local and systemic transcriptome and spliceome reprogramming induced by the root-knot nematode <i>Meloidogyne incognita</i> in tomato.","authors":"","doi":"10.1093/hr/uhaf056","DOIUrl":"https://doi.org/10.1093/hr/uhaf056","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1093/hr/uhae206.].</p>","PeriodicalId":57479,"journal":{"name":"园艺研究(英文)","volume":"12 3","pages":"uhaf056"},"PeriodicalIF":7.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11890024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An accelerated transgene-free genome editing system using microparticle bombardment of sorghum immature embryos.","authors":"Yan Zhang, Ming Cheng, Karen Massel, Ian D Godwin, Guoquan Liu","doi":"10.1007/s42994-025-00204-9","DOIUrl":"10.1007/s42994-025-00204-9","url":null,"abstract":"<p><p>The key factors for genome-editing in plants using CRISPR/Cas9, such as the Cas9 nuclease and guide RNA (gRNA) are typically expressed from a construct that is integrated into the plant genome. However, the presence of foreign DNA in the host genome causes genetic and regulatory concerns, particularly for commercialization. To address this issue, we developed an accelerated pipeline for generating transgene-free genome-edited sorghum (<i>Sorghum bicolor</i>) in the T₀ generation. For proof-of-concept, we selected the <i>Phytoene desaturase</i> (<i>PDS</i>) gene as the target due to its visible phenotype (albinism) upon mutation. Following microprojectile-mediated co-transformation with a maize (<i>Zea mays</i>)-optimized Cas9 vector and a guide RNA (gRNA) cassette with a geneticin (G418) resistance gene, we divided tissue derived from immature embryos into two groups (with and without antibiotic selection) and cultured them separately as parallel experiments. In regenerated plants cultured on medium containing MS basal nutrition (to allow albino plants to survive), we detected higher rates of albinism in the non-selection group, achieving editing rates of 11.1-14.3% compared with 4.2-8.3% in the antibiotic selection group. In the T₀ generation, 22.2-38.1% of albino plants from the non-selection group were identified as transgene-free, whereas only 0-5.9% from the selection group were transgene-free. Therefore, our strategy efficiently produced transgene-free genome-edited plants without the need for self-crossing or outcrossing, demonstrating the feasibility of achieving transgene-free genome-edited sorghum plants within a single generation. These findings pave the way for commercializing transgene-free genome-edited lines, particularly for vegetatively propagated crops like pineapple, sugarcane, and banana.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s42994-025-00204-9.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"6 2","pages":"202-214"},"PeriodicalIF":4.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12238444/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: Potassium stimulates fruit sugar accumulation by increasing carbon flow in <i>Citrus sinensis</i>.","authors":"","doi":"10.1093/hr/uhaf057","DOIUrl":"10.1093/hr/uhaf057","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1093/hr/uhae240.].</p>","PeriodicalId":57479,"journal":{"name":"园艺研究(英文)","volume":"12 3","pages":"uhaf057"},"PeriodicalIF":7.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11890026/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"OsbHLH062 regulates iron homeostasis by inhibiting iron deficiency responses in rice.","authors":"Wujian Wang, Fengyu He, Hui Zhang, Yue Yang, Xiaojuan Wang, Yue Fu, Huixia Shou, Luqing Zheng","doi":"10.1007/s42994-025-00203-w","DOIUrl":"10.1007/s42994-025-00203-w","url":null,"abstract":"<p><p>Iron (Fe) homeostasis in plant cells is crucial for crop productivity and quality. An intricate transcriptional network involving numerous basic Helix-Loop-Helix (bHLH) transcription factors has been proposed to control Fe homeostasis. In the present study, we characterized rice (<i>Oryza sativa</i>) OsbHLH062, a member of the IVb subgroup of the bHLH family, demonstrating that it negatively regulates Fe-deficiency responses. OsbHLH062 represses transcription by recruiting TOPLESS/TOPLESS-RELATED co-repressors (TPL/TPRs) through its ethylene-responsive element binding factor-associated amphiphilic repression (EAR) motif. Under Fe deficiency, the expression of <i>OsbHLH062</i> is upregulated in roots and downregulated in shoots. Overexpression of <i>OsbHLH062</i> leads to decreased Fe accumulation in the shoot. Furthermore, OsbHLH062 interacts with POSITIVE REGULATOR OF IRON HOMEOSTASIS 1 (OsPRI1) and inhibits its transactivation activity, thereby negatively regulating the expression of many Fe homeostasis-related genes. These results indicate an important role for OsbHLH062 in regulating Fe homeostasis by negatively regulating Fe deficiency responses in rice. This knowledge will aid in the design of Fe-biofortified rice plants that can help to address the global issue of Fe deficiency.</p>","PeriodicalId":53135,"journal":{"name":"aBIOTECH","volume":"6 2","pages":"215-231"},"PeriodicalIF":4.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12238704/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An automatic method for estimating insect defoliation with visual highlights of consumed leaf tissue regions","authors":"Gabriel S. Vieira ,&nbsp;Afonso U. Fonseca ,&nbsp;Naiane Maria de Sousa ,&nbsp;Julio C. Ferreira ,&nbsp;Juliana Paula Felix ,&nbsp;Christian Dias Cabacinha ,&nbsp;Fabrizzio Soares","doi":"10.1016/j.inpa.2024.03.001","DOIUrl":"10.1016/j.inpa.2024.03.001","url":null,"abstract":"<div><div>As an essential component of the architecture of a plant, leaves are crucial to sustaining decision-making in cultivars and effectively support agricultural processes. When the leaf area is constantly monitored, a plant’s health and productive capacity can be assessed to foment proactive and reactive strategies. Because of that, one of the most critical tasks in agricultural processes is estimating foliar damage. In this sense, we present an automatic method to estimate leaf stress caused by insect herbivory, including damage in border regions. As a novelty, we present a method with well-defined processing steps suitable for numerical analysis and visual inspection of defoliation severity. We describe the proposed method and evaluate its performance concerning 12 different plant species. Experimental results show high assertiveness in estimating leaf area loss with a concordance correlation coefficient of 0.98 for grape, soybean, potato, and strawberry leaves. A classic pattern recognition approach, named template matching, is at the core of the method whose performance is compared to cutting-edge techniques. Results demonstrated that the method achieves foliar damage quantification with precision comparable to deep learning models. The code prepared by the authors is publicly available.</div></div>","PeriodicalId":53443,"journal":{"name":"Information Processing in Agriculture","volume":"12 1","pages":"Pages 40-53"},"PeriodicalIF":7.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140084130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deep learning framework for prediction of crop yield in Australia under the impact of climate change","authors":"Haydar Demirhan","doi":"10.1016/j.inpa.2024.04.004","DOIUrl":"10.1016/j.inpa.2024.04.004","url":null,"abstract":"<div><div>Accurate prediction of crop yields is essential to ensure food security. In this study, a new deep neural networks framework is developed to predict crop yields in Australia, considering the impact of climate change, fertilizer use, and crop area. It is implemented for oats, corn, rice, and wheat crops, and its forecasting performance is benchmarked against five statistical and machine learning methods. All the software codes for the implementation of the proposed framework are freely available. The proposed framework shows the highest forecasting performance for all the considered crop types. It provides 23%, 38%, 39%, and 40% lower average mean absolute error than the benchmark methods for oat, corn, rice, and wheat crops, respectively. The reductions in average root mean squared error are 19%, 25%, 37%, and 29% over the benchmark methods. Then, it is used to predict yields of the considered crops in Australia towards 2025 under six different climate change scenarios. It is observed that although climate change has some boosting impact on crop yield, it is not sustainable to meet the demand. However, it is possible to keep crop yields rising while mitigating climate change.</div></div>","PeriodicalId":53443,"journal":{"name":"Information Processing in Agriculture","volume":"12 1","pages":"Pages 125-138"},"PeriodicalIF":7.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140761172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}