Pub Date : 2025-01-30DOI: 10.1016/j.agrcom.2025.100071
Changxuan Xia , Shanshan Yin , Jian Zhang , Huitong Teng , Ying Li , Aijun Mao , Changlong Wen
Improving antioxidant activity to preserve nutritional quality and enhance environmental resilience is a primary goal in vegetable breeding. Cucumber is known to have relatively low antioxidant activity among commonly consumed vegetables, yet the specific genetic factors underlying this trait remain largely unexplored. In this study, a significantly divergence in the antioxidant activity of cucumber inbred lines was revealed by Ferric Ion Reducing Antioxidant Power (FRAP) assay. A gene responsible for this divergence, designated as Cvergence 1 (CAD1), was map-based cloned through Bulked Segregant Analysis (BSA) sequencing and molecular marker-assisted selection from a F2 population. Subsequently, gene editing and overexpression analysis demonstrated that CAD1 is essential for antioxidant activity. Furthermore, qRT-PCR and phylogenetic tree analysis showed that CAD1 encodes a fruit-specific expressed MYB transcription factor. Comprehensive untargeted metabolomics analysis and Electrophoretic Mobility Shift Assay (EMSA) revealed that CAD1 transcriptionally activates genes involved in flavonoid synthesis, thereby promoting flavonoid production and boosting the antioxidant activity of cucumber. Finally, cold treatment showed that CAD1 improves cold storage resilience, which is directly activated by CsCBF2. In summary, this study provides valuable insights and data for breeding cucumbers with enhanced antioxidant activity.
{"title":"CAD1 enhances antioxidant activity to facilitate cold storage by regulating flavonoid synthesis in cucumber","authors":"Changxuan Xia , Shanshan Yin , Jian Zhang , Huitong Teng , Ying Li , Aijun Mao , Changlong Wen","doi":"10.1016/j.agrcom.2025.100071","DOIUrl":"10.1016/j.agrcom.2025.100071","url":null,"abstract":"<div><div>Improving antioxidant activity to preserve nutritional quality and enhance environmental resilience is a primary goal in vegetable breeding. Cucumber is known to have relatively low antioxidant activity among commonly consumed vegetables, yet the specific genetic factors underlying this trait remain largely unexplored. In this study, a significantly divergence in the antioxidant activity of cucumber inbred lines was revealed by Ferric Ion Reducing Antioxidant Power (FRAP) assay. A gene responsible for this divergence, designated as <em><u>C</u></em><em>vergence <u>1</u></em> (<em>CAD1</em>), was map-based cloned through Bulked Segregant Analysis (BSA) sequencing and molecular marker-assisted selection from a F<sub>2</sub> population. Subsequently, gene editing and overexpression analysis demonstrated that <em>CAD1</em> is essential for antioxidant activity. Furthermore, qRT-PCR and phylogenetic tree analysis showed that <em>CAD1</em> encodes a fruit-specific expressed MYB transcription factor. Comprehensive untargeted metabolomics analysis and Electrophoretic Mobility Shift Assay <strong>(</strong>EMSA) revealed that <em>CAD1</em> transcriptionally activates genes involved in flavonoid synthesis<em>,</em> thereby promoting flavonoid production and boosting the antioxidant activity of cucumber. Finally, cold treatment showed that <em>CAD1</em> improves cold storage resilience, which is directly activated by <em>CsCBF2</em>. In summary, this study provides valuable insights and data for breeding cucumbers with enhanced antioxidant activity.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"3 1","pages":"Article 100071"},"PeriodicalIF":0.0,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479430","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}
Pub Date : 2024-12-01DOI: 10.1016/j.agrcom.2024.100065
Hairong Gao , Shaokai Wang , Dandan Shen , Wenshuang Li , Yan Zhang , Jingyi Deng , Jiapeng Jiao , Pinge Huang , Qianli Ma , Yuan Huang , Fangting Yuan , Xin Wang , Junhong Zhang , Wenyue Liao , Mengjie Li , Yan Yan , Qiang Li , Yunjiang Cheng
Protected cultivation enables the production of vegetables and fruits throughout the year without compromising of farming field for grain production. However, it is generally associated with high resource consumption, including building materials, consumables, and energy, raising severe concerns about its future sustainability, especially the intensity of its carbon emissions, which is less well-understood. This study focused on the carbon emissions of two typical protected cultivation constructions for tomato cultivation in China, using life cycle assessment (LCA). Tomato production generated 354.4 and 173.1 kg CO2-eq/ton carbon emissions in a typical solar greenhouse in northern China and a typical naturally ventilated polyhouse in southern China, which represented 41.9% and 21.7% reduction, respectively, compared to field production in the same area. Further analysis of protected cultivation inputs revealed that agricultural consumables are the main contributors to carbon emissions. Among them, fertilizers were the dominant contributor to carbon emissions, accounting for 73.0% and 67.5% of the total carbon emissions for solar greenhouses and polyhouses, respectively. Based on this finding, a sensitivity analysis revealed the potential of two advanced fertilizer management practices to reduce carbon emissions. Drip irrigation and slow-release fertilizers in protected cultivation can reduce carbon emissions by 16.5–17.7% and 12.9–13.8%, respectively, compared to traditional chemical fertilizers. In addition, the analysis of environmental effects suggested that protected tomato production can significantly reduce environmental impact. Overall, this research highlighted that protected cultivation can substantially mitigate carbon emissions, demonstrating its high efficiency toward low-carbon agriculture.
{"title":"Protected cultivation can mitigate carbon emissions for tomato production","authors":"Hairong Gao , Shaokai Wang , Dandan Shen , Wenshuang Li , Yan Zhang , Jingyi Deng , Jiapeng Jiao , Pinge Huang , Qianli Ma , Yuan Huang , Fangting Yuan , Xin Wang , Junhong Zhang , Wenyue Liao , Mengjie Li , Yan Yan , Qiang Li , Yunjiang Cheng","doi":"10.1016/j.agrcom.2024.100065","DOIUrl":"10.1016/j.agrcom.2024.100065","url":null,"abstract":"<div><div>Protected cultivation enables the production of vegetables and fruits throughout the year without compromising of farming field for grain production. However, it is generally associated with high resource consumption, including building materials, consumables, and energy, raising severe concerns about its future sustainability, especially the intensity of its carbon emissions, which is less well-understood. This study focused on the carbon emissions of two typical protected cultivation constructions for tomato cultivation in China, using life cycle assessment (LCA). Tomato production generated 354.4 and 173.1 kg CO<sub>2</sub>-eq/ton carbon emissions in a typical solar greenhouse in northern China and a typical naturally ventilated polyhouse in southern China, which represented 41.9% and 21.7% reduction, respectively, compared to field production in the same area. Further analysis of protected cultivation inputs revealed that agricultural consumables are the main contributors to carbon emissions. Among them, fertilizers were the dominant contributor to carbon emissions, accounting for 73.0% and 67.5% of the total carbon emissions for solar greenhouses and polyhouses, respectively. Based on this finding, a sensitivity analysis revealed the potential of two advanced fertilizer management practices to reduce carbon emissions. Drip irrigation and slow-release fertilizers in protected cultivation can reduce carbon emissions by 16.5–17.7% and 12.9–13.8%, respectively, compared to traditional chemical fertilizers. In addition, the analysis of environmental effects suggested that protected tomato production can significantly reduce environmental impact. Overall, this research highlighted that protected cultivation can substantially mitigate carbon emissions, demonstrating its high efficiency toward low-carbon agriculture.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 4","pages":"Article 100065"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143163104","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}
Pub Date : 2024-12-01DOI: 10.1016/j.agrcom.2024.100060
Jibo Yue , Ting Li , Haikuan Feng , Yuanyuan Fu , Yang Liu , Jia Tian , Hao Yang , Guijun Yang
Accurate information on the soil moisture content in croplands is essential for monitoring crop growth conditions. This study aimed to enhance soil moisture monitoring by employing laboratory-based soil spectral measurements and radiative transfer models. This study comprised three main components: (1) Utilizing laboratory-measured soil spectra to investigate the influence of soil moisture content on soil spectral properties (n = 178), and describing the impact of canopy coverage on the mixed spectra of wheat and soil in croplands using a radiative transfer model (RTM) (n = 144, 180); (2) employing a deep learning model trained on extensive simulated datasets to estimate soil moisture beneath the canopy from wheat‒soil mixed spectra (n = 200); and (3) comparing the performance of deep learning model with statistical regression techniques based on soil moisture spectral index (SI) for estimating wheat fractional vegetation cover (FVC) and relative soil moisture content (RMC) under medium to low canopy coverage. The conclusions of this study were as follows: (1) Compared with the conventional statistical regression approaches, the deep learning model exhibited superior accuracy in estimating RMC across all levels of normalized difference vegetation index (NDVI). (2) By combining laboratory soil spectral measurements with an RTM, a pretrained dataset can be created. When combined with transfer learning techniques (FVC: R2 = 0.782, RMSE = 0.107, and RMC: R2 = 0.825, RMSE = 0.130), this approach enhanced the accuracy of estimating wheat FVC and RMC. Future research should expand experiments to include additional regions and crop types to verify the accuracy and generalizability of this method for estimating FVC and RMC under various remote sensing conditions.
{"title":"Enhancing field soil moisture content monitoring using laboratory-based soil spectral measurements and radiative transfer models","authors":"Jibo Yue , Ting Li , Haikuan Feng , Yuanyuan Fu , Yang Liu , Jia Tian , Hao Yang , Guijun Yang","doi":"10.1016/j.agrcom.2024.100060","DOIUrl":"10.1016/j.agrcom.2024.100060","url":null,"abstract":"<div><div>Accurate information on the soil moisture content in croplands is essential for monitoring crop growth conditions. This study aimed to enhance soil moisture monitoring by employing laboratory-based soil spectral measurements and radiative transfer models. This study comprised three main components: (1) Utilizing laboratory-measured soil spectra to investigate the influence of soil moisture content on soil spectral properties (n = 178), and describing the impact of canopy coverage on the mixed spectra of wheat and soil in croplands using a radiative transfer model (RTM) (n = 144, 180); (2) employing a deep learning model trained on extensive simulated datasets to estimate soil moisture beneath the canopy from wheat‒soil mixed spectra (n = 200); and (3) comparing the performance of deep learning model with statistical regression techniques based on soil moisture spectral index (SI) for estimating wheat fractional vegetation cover (FVC) and relative soil moisture content (RMC) under medium to low canopy coverage. The conclusions of this study were as follows: (1) Compared with the conventional statistical regression approaches, the deep learning model exhibited superior accuracy in estimating RMC across all levels of normalized difference vegetation index (NDVI). (2) By combining laboratory soil spectral measurements with an RTM, a pretrained dataset can be created. When combined with transfer learning techniques (FVC: <em>R</em><sup>2</sup> = 0.782, RMSE = 0.107, and RMC: <em>R</em><sup>2</sup> = 0.825, RMSE = 0.130), this approach enhanced the accuracy of estimating wheat FVC and RMC. Future research should expand experiments to include additional regions and crop types to verify the accuracy and generalizability of this method for estimating FVC and RMC under various remote sensing conditions.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 4","pages":"Article 100060"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162569","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}
Pub Date : 2024-12-01DOI: 10.1016/j.agrcom.2024.100063
Wen Ren , Zi Shi , Yongxin Zhao , Qian Zhang , Miaoyi Zhou , Chen Cheng , Mengyuan Liu , Bingbing Zhao , Yuhui Guo , Hewei Du , Xiaozeng Yang , Ya Liu
Drought, one of the most devastating abiotic stresses to affect agricultural production worldwide, causes significant crop yield loss. In China, the yield and value of maize, a drought-sensitive staple crop, is significantly affected by drought conditions. Jing24 (J24), an elite, robust, and drought-resistant maize inbred line, yet the underlying genetic basis for this resistance remains imperfectly understood. We characterized the overall performance of three maize varieties (J24, B73, and X178) under moderate and severe drought conditions at seedling and flowering stages. RNA-Seq analysis revealed more genes to respond to drought treatment in J24 than in either B73 or X178, with some drought-responsive genes were common to each line in leaf and root tissues. Gene ontology analysis of common differentially expressed genes in J24 and X178 showed that membrane and transporter-related genes were significantly enriched in roots, whereas genes associated with photosynthesis and membrane were most-enriched in leaves. The expression of ZmMAPKKK21 was significantly up-regulated in the root of J24 in the moderate drought treatment, the transgenic Arabidopsis plants overexpressing ZmMAPKKK21 we obtained exhibited a substantial reduction in ABA sensitivity and an increase in drought tolerance. In contrast, maize plants in which ZmMAPKKK21 was knocked out were more sensitive to water deficiency, and have a smaller root system and a lower survival rate after rewatering than wild type plants. These results suggest that ZmMAPKKK21 is a positive regulator for drought response in J24, which provides insights into the molecular mechanism underlying the strong drought resistance of J24.
{"title":"Transcriptional analysis of maize elite inbred line Jing24 and the function of ZmMAPKKK21 in the response to drought stress","authors":"Wen Ren , Zi Shi , Yongxin Zhao , Qian Zhang , Miaoyi Zhou , Chen Cheng , Mengyuan Liu , Bingbing Zhao , Yuhui Guo , Hewei Du , Xiaozeng Yang , Ya Liu","doi":"10.1016/j.agrcom.2024.100063","DOIUrl":"10.1016/j.agrcom.2024.100063","url":null,"abstract":"<div><div>Drought, one of the most devastating abiotic stresses to affect agricultural production worldwide, causes significant crop yield loss. In China, the yield and value of maize, a drought-sensitive staple crop, is significantly affected by drought conditions. Jing24 (J24), an elite, robust, and drought-resistant maize inbred line, yet the underlying genetic basis for this resistance remains imperfectly understood. We characterized the overall performance of three maize varieties (J24, B73, and X178) under moderate and severe drought conditions at seedling and flowering stages. RNA-Seq analysis revealed more genes to respond to drought treatment in J24 than in either B73 or X178, with some drought-responsive genes were common to each line in leaf and root tissues. Gene ontology analysis of common differentially expressed genes in J24 and X178 showed that membrane and transporter-related genes were significantly enriched in roots, whereas genes associated with photosynthesis and membrane were most-enriched in leaves. The expression of <em>ZmMAPKKK21</em> was significantly up-regulated in the root of J24 in the moderate drought treatment, the transgenic <em>Arabidopsis</em> plants overexpressing ZmMAPKKK21 we obtained exhibited a substantial reduction in ABA sensitivity and an increase in drought tolerance. In contrast, maize plants in which ZmMAPKKK21 was knocked out were more sensitive to water deficiency, and have a smaller root system and a lower survival rate after rewatering than wild type plants. These results suggest that ZmMAPKKK21 is a positive regulator for drought response in J24, which provides insights into the molecular mechanism underlying the strong drought resistance of J24.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 4","pages":"Article 100063"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162571","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}
Pub Date : 2024-12-01DOI: 10.1016/j.agrcom.2024.100061
Maolin Liu , Yushu Li , Haixia Chen , Chunjie He , Lei Sun , Xiuhai Zhang , Zongda Xu , Hua Liu
Opisthopappus taihangensis (Anthemideae, Asteraceae), which is rich in bioactive components, produces flowers and leaves with robust fragrances. In this study, we conducted comprehensive metabolomic and transcriptomic analyses to identify changes in terpenoid metabolites and associated gene expression across various O. taihangensis tissues (leaves, buds, and inflorescences at the exposure, initial-bloom, and full-bloom stages). We identified 1370 metabolites using headspace solid-phase micro-extraction/gas chromatography-mass spectrometry (HS-SPME/GC–MS), 308 of which were terpenoid metabolites. The expression of terpenoid synthesis-related genes was relatively consistent with the synthesis of terpenoid metabolites at each examined developmental stage. An analysis of gene networks governing terpenoid synthesis revealed that MCT genes (OtMCT1, OtMCT2, and OtMCT3), TPS genes (OtTPS5, OtTPS9, and OtTPS10), and OtISPS1 may be crucial for synthesizing specific metabolites in different tissues. Additionally, the essential oil extracted from leaves by water distillation showed that thujone and camphor were the predominant components. The considerable antioxidant activity of the leaf essential oil was comparable to that of vitamin C (16 μg/mL). Notably, its antimicrobial effects against Staphylococcus aureus and Escherichia coli growth were greater than those of ampicillin and vancomycin at the same concentrations. Scanning electron microscopy images indicated that the leaf essential oil significantly disrupted bacterial cell structures. This study thoroughly analyzed the network of genes regulating terpenoid metabolites in different O. taihangensis tissues, and elucidated the antioxidant and antibacterial potential of the leaf essential oil, thus providing valuable insights for breeding, molecular characterization, and the potential application of O. taihangensis in developing useful essential oil-based natural products.
{"title":"Integrated omics profiles for exploring the potential mechanism underlying aroma formation in the terpenoid-rich aromatic plant Opisthopappus taihangensis and the bioactivity of its leaf essential oil","authors":"Maolin Liu , Yushu Li , Haixia Chen , Chunjie He , Lei Sun , Xiuhai Zhang , Zongda Xu , Hua Liu","doi":"10.1016/j.agrcom.2024.100061","DOIUrl":"10.1016/j.agrcom.2024.100061","url":null,"abstract":"<div><div><em>Opisthopappus taihangensis</em> (Anthemideae, Asteraceae), which is rich in bioactive components, produces flowers and leaves with robust fragrances. In this study, we conducted comprehensive metabolomic and transcriptomic analyses to identify changes in terpenoid metabolites and associated gene expression across various <em>O. taihangensis</em> tissues (leaves, buds, and inflorescences at the exposure, initial-bloom, and full-bloom stages). We identified 1370 metabolites using headspace solid-phase micro-extraction/gas chromatography-mass spectrometry (HS-SPME/GC–MS), 308 of which were terpenoid metabolites. The expression of terpenoid synthesis-related genes was relatively consistent with the synthesis of terpenoid metabolites at each examined developmental stage. An analysis of gene networks governing terpenoid synthesis revealed that <em>MCT</em> genes (<em>OtMCT1</em>, <em>OtMCT2</em>, and <em>OtMCT3</em>), <em>TPS</em> genes (<em>OtTPS5</em>, <em>OtTPS9</em>, and <em>OtTPS10</em>), and <em>OtISPS1</em> may be crucial for synthesizing specific metabolites in different tissues. Additionally, the essential oil extracted from leaves by water distillation showed that thujone and camphor were the predominant components. The considerable antioxidant activity of the leaf essential oil was comparable to that of vitamin C (16 μg/mL). Notably, its antimicrobial effects against <em>Staphylococcus aureus</em> and <em>Escherichia coli</em> growth were greater than those of ampicillin and vancomycin at the same concentrations. Scanning electron microscopy images indicated that the leaf essential oil significantly disrupted bacterial cell structures. This study thoroughly analyzed the network of genes regulating terpenoid metabolites in different <em>O. taihangensis</em> tissues, and elucidated the antioxidant and antibacterial potential of the leaf essential oil, thus providing valuable insights for breeding, molecular characterization, and the potential application of <em>O. taihangensis</em> in developing useful essential oil-based natural products.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 4","pages":"Article 100061"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143163102","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}
Pub Date : 2024-12-01DOI: 10.1016/j.agrcom.2024.100064
Zan Li , Xiaokai Bao , Xiumei Liu , Yongjie Wang , Xueyu Zhu , Yuwei Zhang , Zhenwei Wang , Sergei Maslennikov , Michael Whiteside , Weijun Wang , Xiaohui Xu , Bin Li , Qihao Luo , Yan Li , Shuhai Wang , Bin Hu , Jianmin Yang
Sepia esculenta is an economically important cephalopod species contributing to aquaculture in China. Global climate changes have increased fluctuations in the ocean salinity level, which is a major problem for S. esculenta populations because extreme changes in salinity may be fatal to marine life. In this study, S. esculenta larvae were subjected to high salinity stress to investigate their stress resistance mechanisms. High-throughput transcriptome sequencing technology was used to detect transcript-level changes in samples. A total of 1126 significant differentially expressed genes were identified. The results of functional enrichment analyses showed that high salinity activated apoptosis and several innate immunity-related pathways in S. esculenta larvae. On the basis of a protein–protein interaction network analysis, PARP1, PIK3CB and FLNA were identified as hub genes involved in larval resistance to high salinity. Quantitative real-time PCR technology was used to analyze gene expression and verify the accuracy of the transcriptome sequencing results. The process of apoptosis can restrict high salinity-induced tissue damage, while the activation of an inflammatory response can maintain cellular homeostasis. Therefore, we speculate that high salinity induces innate immunity and apoptosis in S. esculenta larvae and modulates growth and development. These findings also suggest that aquaculture losses due to increased seawater salinity must be prevented in artificial aquaculture systems.
{"title":"Transcriptome analysis provides preliminary insights into the response of Sepia esculenta to high salinity stress","authors":"Zan Li , Xiaokai Bao , Xiumei Liu , Yongjie Wang , Xueyu Zhu , Yuwei Zhang , Zhenwei Wang , Sergei Maslennikov , Michael Whiteside , Weijun Wang , Xiaohui Xu , Bin Li , Qihao Luo , Yan Li , Shuhai Wang , Bin Hu , Jianmin Yang","doi":"10.1016/j.agrcom.2024.100064","DOIUrl":"10.1016/j.agrcom.2024.100064","url":null,"abstract":"<div><div><em>Sepia esculenta</em> is an economically important cephalopod species contributing to aquaculture in China. Global climate changes have increased fluctuations in the ocean salinity level, which is a major problem for <em>S. esculenta</em> populations because extreme changes in salinity may be fatal to marine life. In this study, <em>S. esculenta</em> larvae were subjected to high salinity stress to investigate their stress resistance mechanisms. High-throughput transcriptome sequencing technology was used to detect transcript-level changes in samples. A total of 1126 significant differentially expressed genes were identified. The results of functional enrichment analyses showed that high salinity activated apoptosis and several innate immunity-related pathways in <em>S. esculenta</em> larvae. On the basis of a protein–protein interaction network analysis, PARP1, PIK3CB and FLNA were identified as hub genes involved in larval resistance to high salinity. Quantitative real-time PCR technology was used to analyze gene expression and verify the accuracy of the transcriptome sequencing results. The process of apoptosis can restrict high salinity-induced tissue damage, while the activation of an inflammatory response can maintain cellular homeostasis. Therefore, we speculate that high salinity induces innate immunity and apoptosis in <em>S. esculenta</em> larvae and modulates growth and development. These findings also suggest that aquaculture losses due to increased seawater salinity must be prevented in artificial aquaculture systems.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 4","pages":"Article 100064"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143163103","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}
Pub Date : 2024-12-01DOI: 10.1016/j.agrcom.2024.100066
Camilla Beate Hill , Tefera Tolera Angessa , Sharon Westcott , Lee-Anne McFawn , Hamid Shirdelmoghanloo , Yong Han , Chengdao Li
Against the backdrop of a warming climate, heat stress has become one of the most limiting factors to crop productivity and food security worldwide. The flowering stage is susceptible to high temperatures in cereal crops, leading to severe grain yield losses by decreasing fertility and seed-setting rate. Our objective was to (1) assess a global panel of 572 barley varieties with contrasting genetic backgrounds for various agronomic traits related to spikelet fertility and grain quality, (2) identify barley germplasm with superior spikelet fertility and seed set under extreme heat conditions, and (3) understand the relationship between spikelet fertility and grain quality traits under heat stress at flowering time. Delayed sowing in target field environments as well as combined birdcage and heat chamber experiments were conducted in Western Australia for two consecutive years. Twenty-one agronomic traits, including spikelet fertility, grain plumpness, thousand-kernel weight, and screenings, were assessed when heat stress occurred during the crucial flowering period. Our study showed that varieties that flowered during heat stress periods recorded an average of 5–20 % lower spikelet fertility than those flowered outside the stress windows. Varieties with high or reduced spikelet fertility under heat stress were identified in the barley panel and showed significant differences of more than 80 % in Australian varieties. Based on decreased spikelet fertility, several research lines, but only a few cultivars, maintain spikelet fertility after heat stress compared to control conditions, providing evidence of adaptation to high temperatures in some genotypes. Our study shows that spikelet fertility at high temperatures is a valuable screening tool for heat tolerance during the reproductive phase. Information on heat-tolerant and susceptible varieties can improve the spikelet fertility of the next generation of barley cultivars and enhance adaptation to a changing climate.
{"title":"Evaluation of the impact of heat stress at flowering on spikelet fertility and grain quality in barley","authors":"Camilla Beate Hill , Tefera Tolera Angessa , Sharon Westcott , Lee-Anne McFawn , Hamid Shirdelmoghanloo , Yong Han , Chengdao Li","doi":"10.1016/j.agrcom.2024.100066","DOIUrl":"10.1016/j.agrcom.2024.100066","url":null,"abstract":"<div><div>Against the backdrop of a warming climate, heat stress has become one of the most limiting factors to crop productivity and food security worldwide. The flowering stage is susceptible to high temperatures in cereal crops, leading to severe grain yield losses by decreasing fertility and seed-setting rate. Our objective was to (1) assess a global panel of 572 barley varieties with contrasting genetic backgrounds for various agronomic traits related to spikelet fertility and grain quality, (2) identify barley germplasm with superior spikelet fertility and seed set under extreme heat conditions, and (3) understand the relationship between spikelet fertility and grain quality traits under heat stress at flowering time. Delayed sowing in target field environments as well as combined birdcage and heat chamber experiments were conducted in Western Australia for two consecutive years. Twenty-one agronomic traits, including spikelet fertility, grain plumpness, thousand-kernel weight, and screenings, were assessed when heat stress occurred during the crucial flowering period. Our study showed that varieties that flowered during heat stress periods recorded an average of 5–20 % lower spikelet fertility than those flowered outside the stress windows. Varieties with high or reduced spikelet fertility under heat stress were identified in the barley panel and showed significant differences of more than 80 % in Australian varieties. Based on decreased spikelet fertility, several research lines, but only a few cultivars, maintain spikelet fertility after heat stress compared to control conditions, providing evidence of adaptation to high temperatures in some genotypes. Our study shows that spikelet fertility at high temperatures is a valuable screening tool for heat tolerance during the reproductive phase. Information on heat-tolerant and susceptible varieties can improve the spikelet fertility of the next generation of barley cultivars and enhance adaptation to a changing climate.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 4","pages":"Article 100066"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143162570","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}
Pub Date : 2024-12-01DOI: 10.1016/j.agrcom.2024.100062
Qifeng Li , Zhenyuan Zhuo , Ronghua Gao , Rong Wang , Na Zhang , Yan Shi , Tonghui Wu , Weihong Ma
Given that the pig behavior reflects their health status, continuous and precise monitoring of behavior is important for effective health management and welfare protection. To mitigate potential tracking failures during analysis of video footage, we introduced a novel multi-target pig tracking method that consisted of detection and tracking components. The detection model was enhanced with an efficient attention mechanism and a Cross Stage Partial Darknet backbone network, which significantly improved detection accuracy. The tracking component used the Bytetrack algorithm to accurately track the movement trajectories of individual pigs. Together, these components were combined into the Dual-YOLOX-Tiny-ByteTrack (DYTB) model, which demonstrated superior performance in automatic monitoring of pig behaviors compared to previously published approaches. We established multi-object pig tracking datasets with 180,321 images to evaluate this method. The DYTB method achieved a pig detection accuracy of 98.3% and tracking accuracies of 95.3% and 97.1%. Compared to the YOLOX-Tiny-ByteTrack base model, DYTB showed a 3.4% improvement in multiple object tracking accuracy, making it a robust method for non-contact, intelligent monitoring of pig health and contributing to advances in precision livestock farming.
{"title":"A pig behavior-tracking method based on a multi-channel high-efficiency attention mechanism","authors":"Qifeng Li , Zhenyuan Zhuo , Ronghua Gao , Rong Wang , Na Zhang , Yan Shi , Tonghui Wu , Weihong Ma","doi":"10.1016/j.agrcom.2024.100062","DOIUrl":"10.1016/j.agrcom.2024.100062","url":null,"abstract":"<div><div>Given that the pig behavior reflects their health status, continuous and precise monitoring of behavior is important for effective health management and welfare protection. To mitigate potential tracking failures during analysis of video footage, we introduced a novel multi-target pig tracking method that consisted of detection and tracking components. The detection model was enhanced with an efficient attention mechanism and a Cross Stage Partial Darknet backbone network, which significantly improved detection accuracy. The tracking component used the Bytetrack algorithm to accurately track the movement trajectories of individual pigs. Together, these components were combined into the Dual-YOLOX-Tiny-ByteTrack (DYTB) model, which demonstrated superior performance in automatic monitoring of pig behaviors compared to previously published approaches. We established multi-object pig tracking datasets with 180,321 images to evaluate this method. The DYTB method achieved a pig detection accuracy of 98.3% and tracking accuracies of 95.3% and 97.1%. Compared to the YOLOX-Tiny-ByteTrack base model, DYTB showed a 3.4% improvement in multiple object tracking accuracy, making it a robust method for non-contact, intelligent monitoring of pig health and contributing to advances in precision livestock farming.</div></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 4","pages":"Article 100062"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143163101","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}
Pub Date : 2024-09-01DOI: 10.1016/j.agrcom.2024.100055
Fenghua Yu , Juchi Bai , Jianyu Fang , Sien Guo , Shengfan Zhu , Tongyu Xu
The PROSPECT model, widely employed for leaf radiation transfer analysis, relies heavily on input biochemical parameters to calculate spectral reflectance. This dependence often results in similar simulated spectra for different parameter combinations, which complicates the inversion of leaf chlorophyll content (Cab). To address this ill-posed problem, we enhanced the model's application by integrating a support vector machine (SVM)-based parameter combination discriminator with the Look-Up Table (LUT) constructed from the PROSPECT model. We marked samples in the LUT to reflect their closeness to measured parameters, facilitating the identification of reasonable versus unreasonable parameter combinations. The discriminator could effectively discriminate between reasonable and unreasonable parameter combinations, achieving accuracies of 0.894 and 0.888 in the training and test sets, respectively. The discriminator was then employed to refine the LUT, and an improved third-generation non-dominated ranking genetic algorithm (NSGA-III) was used to optimize the extreme learning machine. The inversion of rice Cab using the refined LUT and the NSGA-III demonstrated substantial improvements. The LUT was significantly improved after integration with the discriminator, yielding R2 and RMSE of 0.665 and 7.220 μg cm−2, respectively. The NSGA-III inversion, which utilized the “constraint method” with discriminator results as optimization objectives, achieved the best inversion accuracy, with R2 and RMSE values of 0.809 and 4.788, respectively. This study demonstrates that the effective use of a parameter discriminator can significantly enhance the accuracy of Cab inversion based on the PROSPECT model, offering a substantial advancement in addressing its inherent ill-posed challenges.
{"title":"Integration of a parameter combination discriminator improves the accuracy of chlorophyll inversion from spectral imaging of rice","authors":"Fenghua Yu , Juchi Bai , Jianyu Fang , Sien Guo , Shengfan Zhu , Tongyu Xu","doi":"10.1016/j.agrcom.2024.100055","DOIUrl":"10.1016/j.agrcom.2024.100055","url":null,"abstract":"<div><p>The PROSPECT model, widely employed for leaf radiation transfer analysis, relies heavily on input biochemical parameters to calculate spectral reflectance. This dependence often results in similar simulated spectra for different parameter combinations, which complicates the inversion of leaf chlorophyll content (Cab). To address this ill-posed problem, we enhanced the model's application by integrating a support vector machine (SVM)-based parameter combination discriminator with the Look-Up Table (LUT) constructed from the PROSPECT model. We marked samples in the LUT to reflect their closeness to measured parameters, facilitating the identification of reasonable versus unreasonable parameter combinations. The discriminator could effectively discriminate between reasonable and unreasonable parameter combinations, achieving accuracies of 0.894 and 0.888 in the training and test sets, respectively. The discriminator was then employed to refine the LUT, and an improved third-generation non-dominated ranking genetic algorithm (NSGA-III) was used to optimize the extreme learning machine. The inversion of rice Cab using the refined LUT and the NSGA-III demonstrated substantial improvements. The LUT was significantly improved after integration with the discriminator, yielding R<sup>2</sup> and RMSE of 0.665 and 7.220 μg cm<sup>−2</sup>, respectively. The NSGA-III inversion, which utilized the “constraint method” with discriminator results as optimization objectives, achieved the best inversion accuracy, with R<sup>2</sup> and RMSE values of 0.809 and 4.788, respectively. This study demonstrates that the effective use of a parameter discriminator can significantly enhance the accuracy of Cab inversion based on the PROSPECT model, offering a substantial advancement in addressing its inherent ill-posed challenges.</p></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 3","pages":"Article 100055"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949798124000310/pdfft?md5=0e6d0bea9575791d3d27b69824f5f3e0&pid=1-s2.0-S2949798124000310-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142157827","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}
Pub Date : 2024-09-01DOI: 10.1016/j.agrcom.2024.100054
Meng She , Dengyu Zheng , Shipeng Zhang , Zhao Ke , Zhongyi Wu , Huawen Zou , Zhongbao Zhang
Abiotic stresses, such as drought and salt, are major factors affecting plant growth, development, and productivity. The GRAS gene family is a class of transcriptional regulators in plants that influence plant responses to various biotic and abiotic stresses. In this study, we cloned the maize (Zea mays L.) GRAS gene ZmGRAS72 and preliminarily analyzed its biological function. ZmGRAS72 was highly expressed in maize stems and young leaves, and was induced by abiotic stress and phytohormone treatments. Transient expression assays of maize protoplasts showed that ZmGRAS72 was localized to the nucleus. Heterologous expression of ZmGRAS72 in A. thaliana significantly improved plant tolerance to drought and salt stresses, increased chlorophyll content, decreased malondialdehyde content, and enhanced peroxidase activity. In addition, heterologous expression of ZmGRAS72 in A. thaliana upregulated or downregulated the expression levels of abscisic acid biosynthesis genes (NCED3), signaling genes (ABI1, ABI2, ABI4, and ABI5), and stress-related genes (RD22, RD29A, and KIN1) under abiotic stress. These results indicate that ZmGRAS72 may be responsive to abiotic stress, which forms a basis for further research on the mechanisms underlying the action of ZmGRAS72 in maize.
{"title":"Functional analysis of maize GRAS transcription factor gene ZmGRAS72 in response to drought and salt stresses","authors":"Meng She , Dengyu Zheng , Shipeng Zhang , Zhao Ke , Zhongyi Wu , Huawen Zou , Zhongbao Zhang","doi":"10.1016/j.agrcom.2024.100054","DOIUrl":"10.1016/j.agrcom.2024.100054","url":null,"abstract":"<div><p>Abiotic stresses, such as drought and salt, are major factors affecting plant growth, development, and productivity. The GRAS gene family is a class of transcriptional regulators in plants that influence plant responses to various biotic and abiotic stresses. In this study, we cloned the maize (<em>Zea mays</em> L.) GRAS gene <em>ZmGRAS72</em> and preliminarily analyzed its biological function. <em>ZmGRAS72</em> was highly expressed in maize stems and young leaves, and was induced by abiotic stress and phytohormone treatments. Transient expression assays of maize protoplasts showed that ZmGRAS72 was localized to the nucleus. Heterologous expression of <em>ZmGRAS72</em> in <em>A. thaliana</em> significantly improved plant tolerance to drought and salt stresses, increased chlorophyll content, decreased malondialdehyde content, and enhanced peroxidase activity. In addition, heterologous expression of <em>ZmGRAS72</em> in <em>A. thaliana</em> upregulated or downregulated the expression levels of abscisic acid biosynthesis genes (<em>NCED3</em>), signaling genes (<em>ABI1</em>, <em>ABI2</em>, <em>ABI4</em>, and <em>ABI5</em>), and stress-related genes (<em>RD22</em>, <em>RD29A</em>, and <em>KIN1</em>) under abiotic stress. These results indicate that <em>ZmGRAS72</em> may be responsive to abiotic stress, which forms a basis for further research on the mechanisms underlying the action of <em>ZmGRAS72</em> in maize.</p></div>","PeriodicalId":100065,"journal":{"name":"Agriculture Communications","volume":"2 3","pages":"Article 100054"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949798124000309/pdfft?md5=82c7b11e7a4f49e60ab268a1b9aca4a8&pid=1-s2.0-S2949798124000309-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142136903","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号