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Genomic prediction of seasonal forage yield in perennial ryegrass 多年生黑麦草季节性饲料产量的基因组预测
Pub Date : 2023-09-05 DOI: 10.1002/glr2.12058
Agnieszka Konkolewska, Steffie Phang, Patrick Conaghan, D. Milbourne, Aonghus Lawlor, Stephen Byrne
Genomic selection has the potential to accelerate genetic gain in perennial ryegrass breeding, provided complex traits such as forage yield can be predicted with sufficient accuracy.In this study, we compared modelling approaches and feature selection strategies to evaluate the accuracy of genomic prediction models for seasonal forage yield production.Overall, model selection had limited impact on predictive ability when using the full data set. For a baseline genomic best linear unbiased prediction model, the highest mean predictive accuracy was obtained for spring grazing (0.78), summer grazing (0.62) and second cut silage (0.56). In terms of feature selection strategies, using uncorrelated single‐nucleotide polymorphisms (SNPs) had no impact on predictive ability, allowing for a potential decrease of the data set dimensions. With a genome‐wide association study, we found a significant SNP marker for spring grazing, located in the genic region annotated as coding for an enzyme responsible for fucosylation of xyloglucans—major components of the plant cell wall. We also presented an approach to increase interpretability of genomic prediction models with the use of Gene Ontology enrichment analysis.Approaches for feature selection will be relevant in development of low‐cost genotyping platforms in support of routine and cost‐effective implementation of genomic selection.
基因组选择有可能加速多年生黑麦草育种的遗传增益,前提是能够足够准确地预测诸如饲料产量之类的复杂性状。在本研究中,我们比较了建模方法和特征选择策略,以评估季节性饲料产量基因组预测模型的准确性。总的来说,当使用完整的数据集时,模型选择对预测能力的影响有限。对于基线基因组最佳线性无偏预测模型,春季放牧(0.78)、夏季放牧(0.62)和二次青贮(0.56)的平均预测精度最高。在特征选择策略方面,使用不相关的单核苷酸多态性(snp)对预测能力没有影响,允许数据集维度的潜在降低。通过全基因组关联研究,我们发现了一个与春季放牧相关的显著SNP标记,该标记位于基因区域,被注释为编码一种负责木葡聚糖聚焦化的酶,木葡聚糖是植物细胞壁的主要成分。我们还提出了一种利用基因本体富集分析来提高基因组预测模型的可解释性的方法。特征选择方法将与低成本基因分型平台的开发相关,以支持常规和成本有效的基因组选择实施。
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引用次数: 0
Genomic prediction of seasonal forage yield in perennial ryegrass 多年生黑麦草季节性牧草产量的基因组预测
Pub Date : 2023-09-05 DOI: 10.1002/glr2.12058
Agnieszka Konkolewska, Steffie Phang, Patrick Conaghan, Dan Milbourne, Aonghus Lawlor, Stephen Byrne

Background

Genomic selection has the potential to accelerate genetic gain in perennial ryegrass breeding, provided complex traits such as forage yield can be predicted with sufficient accuracy.

Methods

In this study, we compared modelling approaches and feature selection strategies to evaluate the accuracy of genomic prediction models for seasonal forage yield production.

Results

Overall, model selection had limited impact on predictive ability when using the full data set. For a baseline genomic best linear unbiased prediction model, the highest mean predictive accuracy was obtained for spring grazing (0.78), summer grazing (0.62) and second cut silage (0.56). In terms of feature selection strategies, using uncorrelated single-nucleotide polymorphisms (SNPs) had no impact on predictive ability, allowing for a potential decrease of the data set dimensions. With a genome-wide association study, we found a significant SNP marker for spring grazing, located in the genic region annotated as coding for an enzyme responsible for fucosylation of xyloglucans—major components of the plant cell wall. We also presented an approach to increase interpretability of genomic prediction models with the use of Gene Ontology enrichment analysis.

Conclusions

Approaches for feature selection will be relevant in development of low-cost genotyping platforms in support of routine and cost-effective implementation of genomic selection.

背景基因组选择在多年生黑麦草育种中具有加速遗传增益的潜力,前提是能够足够准确地预测牧草产量等复杂性状。方法在本研究中,我们比较了建模方法和特征选择策略,以评估季节性牧草产量生产的基因组预测模型的准确性。结果总体而言,当使用完整的数据集时,模型选择对预测能力的影响有限。对于基线基因组最佳线性无偏预测模型,春季放牧(0.78)、夏季放牧(0.62)和二切青贮饲料(0.56)的平均预测准确率最高。在特征选择策略方面,使用不相关单核苷酸多态性(SNPs)对预测能力没有影响,允许数据集维度的潜在降低。通过一项全基因组关联研究,我们发现了一个重要的春季放牧SNP标记,位于基因区,被注释为编码一种负责木葡聚糖岩藻糖基化的酶,木葡聚糖是植物细胞壁的主要成分。我们还提出了一种使用基因本体论富集分析来提高基因组预测模型可解释性的方法。结论特征选择方法将与开发低成本基因分型平台相关,以支持基因组选择的常规和成本效益实施。
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引用次数: 0
Arachis species: High-quality forage crops—nutritional properties and breeding strategies to expand their utilization and feeding value 花生:优质饲料作物——营养特性和扩大其利用和饲养价值的育种策略
Pub Date : 2023-08-29 DOI: 10.1002/glr2.12059
Hui Song, Yafeng Huang, Lanlan Ding, Zhenquan Duan, Jiancheng Zhang

Plants of the genus Arachis originated from South America and are cultivated worldwide. The genus Arachis contains 83 species and nine intrageneric taxonomic sections. The cultivated peanut (Arachis hypogaea L.) belongs to the Arachis section, the forage peanut (Arachis pintoi Krapov. & W. C. Greg.) belongs to the Caulorrhizae section, and the perennial peanut (Arachis glabrata Benth.) belongs to the Rhizomatosae section. These three peanut species have been developed for use as fodder crops. This review summarizes the forage value of Arachis species. Forage and perennial peanuts can be intercropped with forage species to feed livestock. The cultivated peanut vines and peanut by-products, such as peanut skins and peanut meal, are also high-quality fodder used to feed sheep, cattle, and poultry. A major limiting factor in terms of adopting forage and perennial peanuts as forage crops is their limited resistance to frosts, resulting from their low winter hardiness. Therefore, the feeding value of cultivated peanuts is higher compared to forage and perennial peanuts. This review suggests that Arachis is a suitable forage crop, focusing on their nutritional properties and breeding to increase their performance under cultivation and feeding value.

花生属植物原产于南美洲,在世界各地都有栽培。Arachis属包括83个物种和9个属内分类区。栽培花生(Arachis hypogaea L.)属于花生科,饲料花生(Arachis pintoi Krapov.&;W.C.Greg.)属于茎科,多年生花生(Arachis glabrata Benth.)属于根管科。这三种花生已被开发用作饲料作物。本文综述了花生属植物的饲草价值。饲料和多年生花生可以与饲料物种间作来喂养牲畜。种植的花生藤和花生副产品,如花生皮和花生粉,也是用于饲养绵羊、牛和家禽的优质饲料。采用饲草和多年生花生作为饲草作物的一个主要限制因素是它们的抗寒性低,对霜冻的抵抗力有限。因此,与饲草和多年生花生相比,栽培花生的饲养价值更高。这篇综述表明,花生是一种合适的饲料作物,重点关注其营养特性和育种,以提高其在栽培和饲养条件下的性能。
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引用次数: 1
Arachis species: High‐quality forage crops—nutritional properties and breeding strategies to expand their utilization and feeding value 花生属:优质饲料作物——营养特性及育种策略以扩大其利用和饲用价值
Pub Date : 2023-08-29 DOI: 10.1002/glr2.12059
Hui Song, Yafeng Huang, Lanlan Ding, Zhenquan Duan, Jiancheng Zhang
Plants of the genus Arachis originated from South America and are cultivated worldwide. The genus Arachis contains 83 species and nine intrageneric taxonomic sections. The cultivated peanut (Arachis hypogaea L.) belongs to the Arachis section, the forage peanut (Arachis pintoi Krapov. & W. C. Greg.) belongs to the Caulorrhizae section, and the perennial peanut (Arachis glabrata Benth.) belongs to the Rhizomatosae section. These three peanut species have been developed for use as fodder crops. This review summarizes the forage value of Arachis species. Forage and perennial peanuts can be intercropped with forage species to feed livestock. The cultivated peanut vines and peanut by‐products, such as peanut skins and peanut meal, are also high‐quality fodder used to feed sheep, cattle, and poultry. A major limiting factor in terms of adopting forage and perennial peanuts as forage crops is their limited resistance to frosts, resulting from their low winter hardiness. Therefore, the feeding value of cultivated peanuts is higher compared to forage and perennial peanuts. This review suggests that Arachis is a suitable forage crop, focusing on their nutritional properties and breeding to increase their performance under cultivation and feeding value.
花生属植物原产于南美洲,在世界各地都有种植。花生属有83种和9个属内分类区。栽培花生(Arachis hypogaea L.)属于花生科,饲料花生(Arachis pintoi Krapov.)属于花生科。(& W. C. Greg.)属于根茎科,多年生花生(arachhis glabrata Benth.)属于根茎科。这三种花生已被开发用作饲料作物。本文综述了花生属植物的饲用价值。饲草和多年生花生可与饲草种间作以喂养牲畜。种植的花生藤和花生副产品,如花生皮和花生粉,也是用于喂养羊、牛和家禽的高质量饲料。采用牧草和多年生花生作为饲料作物的一个主要限制因素是它们的抗霜性有限,这是由于它们的耐寒性较低。因此,栽培花生的饲用价值高于饲草花生和多年生花生。因此,应重视花生的营养特性和育种,提高花生的栽培性能和饲用价值。
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引用次数: 1
Revitalizing the grassland on the Qinghai–Tibetan Plateau 振兴青藏高原草原
Pub Date : 2023-08-20 DOI: 10.1002/glr2.12055
Shikui Dong

Grassland is the largest ecosystem on the Qinghai–Tibetan Plateau (QTP) and provides multiple ecosystem functions and services. Understanding the endowment of the QTP grassland and how to revitalize it have profound implications for the sustainable use and efficient conservation of these unique and globally valuable ecosystems. In this paper, we highlight the importance of the QTP grassland in regional and global settings, stress the values of the QTP grassland in ecological and socioeconomic dimensions, and emphasize the actions needed to restore degraded grassland in the QTP region. The QTP is the largest single area of alpine grassland in the world and an important gene pool of alpine biological resources. The QTP grassland covers two critical ecoregions for conserving the best and most representative habitats for alpine biodiversity on the planet. The QTP grassland is also regarded as one of the best carriers and objects of socio-ecological systems in the world. To promote the resilience and sustainability of the QTP grassland through adaptation, different parties need to work together to find feasible options to resist shock, stresses, and disturbance and to maintain the fundamental functions and basic structures of the QTP grassland.

草原是青藏高原最大的生态系统,提供多种生态系统功能和服务。了解QTP草原的禀赋以及如何振兴它,对这些独特且具有全球价值的生态系统的可持续利用和有效保护具有深远意义。在本文中,我们强调了QTP草原在区域和全球环境中的重要性,强调了QTP草原在生态和社会经济方面的价值,并强调了恢复QTP地区退化草原所需的行动。QTP是世界上最大的高山草原单区,也是高山生物资源的重要基因库。QTP草原覆盖了两个关键的生态区,以保护地球上高山生物多样性的最佳和最具代表性的栖息地。QTP草原也是世界上最好的社会生态系统载体和对象之一。为了通过适应来提高QTP草原的恢复力和可持续性,需要各方共同努力,找到抵御冲击、压力和干扰的可行方案,并保持QTP草地的基本功能和基本结构。
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引用次数: 0
Revitalizing the grassland on the Qinghai–Tibetan Plateau 振兴青藏高原草原
Pub Date : 2023-08-20 DOI: 10.1002/glr2.12055
S. Dong
Grassland is the largest ecosystem on the Qinghai–Tibetan Plateau (QTP) and provides multiple ecosystem functions and services. Understanding the endowment of the QTP grassland and how to revitalize it have profound implications for the sustainable use and efficient conservation of these unique and globally valuable ecosystems. In this paper, we highlight the importance of the QTP grassland in regional and global settings, stress the values of the QTP grassland in ecological and socioeconomic dimensions, and emphasize the actions needed to restore degraded grassland in the QTP region. The QTP is the largest single area of alpine grassland in the world and an important gene pool of alpine biological resources. The QTP grassland covers two critical ecoregions for conserving the best and most representative habitats for alpine biodiversity on the planet. The QTP grassland is also regarded as one of the best carriers and objects of socio‐ecological systems in the world. To promote the resilience and sustainability of the QTP grassland through adaptation, different parties need to work together to find feasible options to resist shock, stresses, and disturbance and to maintain the fundamental functions and basic structures of the QTP grassland.
草原是青藏高原最大的生态系统,具有多种生态系统功能和服务。了解青藏高原草原的禀赋及其恢复方式,对青藏高原独特的、具有全球价值的生态系统的可持续利用和有效保护具有重要意义。本文强调了青藏高原草地在区域和全球背景下的重要性,强调了青藏高原草地在生态和社会经济维度上的价值,并强调了青藏高原退化草地恢复所需要采取的措施。青藏高原是世界上最大的高寒草地单一面积,也是重要的高寒生物资源基因库。青藏高原草原覆盖了两个重要的生态区域,以保护地球上最好和最具代表性的高山生物多样性栖息地。青藏高原草原也被认为是世界上最好的社会生态系统载体和对象之一。为了通过适应促进青藏高原草原的恢复力和可持续性,需要各方共同努力,寻找可行的方案来抵御冲击、应力和干扰,维护青藏高原草原的基本功能和基本结构。
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引用次数: 0
Grain yield stability analysis using parametric and nonparametric statistics in oat (Avena sativa L.) genotypes in Ethiopia 埃塞俄比亚燕麦(Avena sativa L.)基因型的参数和非参数统计分析
Pub Date : 2023-08-07 DOI: 10.1002/glr2.12056
Gezahagn Kebede, Walelign Worku, Habte Jifar, Fekede Feyissa
The performance of oat genotypes differs across environments due to variations in biotic and abiotic factors. Thus, evaluation of oat genotypes across diverse environments is very important to identify superior and stable genotypes for yield improvement.The study aimed to assess the interaction (genotype‐by‐environment interaction; GEI) effect and determine the stability of grain yield in oat (Avena sativa L.) genotypes in Ethiopia using parametric and nonparametric stability statistics. Twenty‐four oat genotypes were evaluated in nine environments using a randomized complete block design replicated three times.The pooled analysis of the variance of grain yield showed significant variations among genotypes, environments, and their interaction effects. Significant GEI revealed the rank order change of genotypes across environments. The environment main effect captured 44.62% of the total grain yield variance, while genotype and GEI effects explained 28.84% and 26.54% of the total grain yield variance, respectively. The grain yield stability was assessed based on 12 parametric and two nonparametric stability statistics. The results indicated that genotypes with superior grain yield‐ showed stable performance on the basis of the stability parameters of the genotypic superiority index (Pi), the Perkins and Jinks adjusted linear regression coefficient (Bi), and the yield stability index (YSI), indicating that selection using these stability parameters would be efficient for grain yield enhancement in oat genotypes. Spearman's rank correlation coefficients also showed that the stability parameters of Pi, Bi, and YSI had a significant positive association with grain yield. However, grain yield had an inverse correlation with the stability parameters of standard deviation, deviation from regression , the Hernandez desirability index (Dji), Wricke ecovalence (Wi), the Shukla stability variance (σi2), the AMMI stability value (ASV), and environmental variance , indicating that oat genotype selection using these stability parameters would not be efficient for yield enhancement because these stability parameters favor low‐yielding genotypes more, compared to high‐yielding ones.Therefore, G5, G8, G11, G12, G14, G16, G17, G19, and G22 genotypes were adaptable in all nine environments based on stability parameters of Pi, Bi, and YSI, and selection of these superior genotypes would improve grain yield in oat genotypes. However, the validity of this result should be confirmed by repeating the experiment in the same environments over two or more years.
背景由于生物和非生物因素的差异,不同环境下燕麦基因型的表现不同。因此,在不同环境中评估燕麦基因型对于确定优越和稳定的基因型以提高产量非常重要。方法本研究旨在评估埃塞俄比亚燕麦(Avena sativa L.)基因型之间的相互作用(基因型与环境的相互作用;GEI)效应,并使用参数和非参数稳定性统计来确定燕麦基因型的粮食产量稳定性。采用重复三次的随机完全区组设计,在九个环境中评估了24种燕麦基因型。结果粮食产量方差的集合分析显示,不同基因型、不同环境及其交互作用之间存在显著差异。显著的GEI揭示了基因型在不同环境中的等级顺序变化。环境主效应占总产量方差的44.62%,基因型效应和GEI效应分别占总产量变异的28.84%和26.54%。基于12个参数和两个非参数稳定性统计对粮食产量稳定性进行了评估。结果表明,基于基因型优势指数(Pi)、Perkins和Jinks调整线性回归系数(Bi)和产量稳定性指数(YSI)的稳定性参数,具有优异粮食产量的基因型表现稳定,表明使用这些稳定性参数的选择对于燕麦基因型的谷物产量提高是有效的。Spearman秩相关系数还表明,Pi、Bi和YSI的稳定性参数与粮食产量呈正相关。然而,粮食产量与稳定性参数标准差、回归偏差、Hernandez合意指数(Dji)、Wricke生态价(Wi)、Shukla稳定性方差(σi2)、AMMI稳定性值(ASV)和环境方差呈负相关,这表明使用这些稳定性参数的燕麦基因型选择对于提高产量是无效的,因为与高产基因型相比,这些稳定性参数更倾向于高产基因型。结论基于Pi、Bi和YSI的稳定性参数,G5、G8、G11、G12、G14、G16、G17、G19和G22基因型在所有9种环境中都具有适应性,选择这些优良基因型将提高燕麦基因型的产量。然而,这个结果的有效性应该通过在相同的环境中重复实验两年或更长时间来确认。
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引用次数: 2
Grain yield stability analysis using parametric and nonparametric statistics in oat (Avena sativa L.) genotypes in Ethiopia 埃塞俄比亚燕麦(Avena sativa L.)基因型籽粒产量稳定性的参数和非参数统计分析
Pub Date : 2023-08-07 DOI: 10.1002/glr2.12056
Gezahagn Kebede, W. Worku, Habte Jifar, Fekede Feyissa
The performance of oat genotypes differs across environments due to variations in biotic and abiotic factors. Thus, evaluation of oat genotypes across diverse environments is very important to identify superior and stable genotypes for yield improvement.The study aimed to assess the interaction (genotype‐by‐environment interaction; GEI) effect and determine the stability of grain yield in oat (Avena sativa L.) genotypes in Ethiopia using parametric and nonparametric stability statistics. Twenty‐four oat genotypes were evaluated in nine environments using a randomized complete block design replicated three times.The pooled analysis of the variance of grain yield showed significant variations among genotypes, environments, and their interaction effects. Significant GEI revealed the rank order change of genotypes across environments. The environment main effect captured 44.62% of the total grain yield variance, while genotype and GEI effects explained 28.84% and 26.54% of the total grain yield variance, respectively. The grain yield stability was assessed based on 12 parametric and two nonparametric stability statistics. The results indicated that genotypes with superior grain yield‐ showed stable performance on the basis of the stability parameters of the genotypic superiority index (Pi), the Perkins and Jinks adjusted linear regression coefficient (Bi), and the yield stability index (YSI), indicating that selection using these stability parameters would be efficient for grain yield enhancement in oat genotypes. Spearman's rank correlation coefficients also showed that the stability parameters of Pi, Bi, and YSI had a significant positive association with grain yield. However, grain yield had an inverse correlation with the stability parameters of standard deviation, deviation from regression , the Hernandez desirability index (Dji), Wricke ecovalence (Wi), the Shukla stability variance (σi2), the AMMI stability value (ASV), and environmental variance , indicating that oat genotype selection using these stability parameters would not be efficient for yield enhancement because these stability parameters favor low‐yielding genotypes more, compared to high‐yielding ones.Therefore, G5, G8, G11, G12, G14, G16, G17, G19, and G22 genotypes were adaptable in all nine environments based on stability parameters of Pi, Bi, and YSI, and selection of these superior genotypes would improve grain yield in oat genotypes. However, the validity of this result should be confirmed by repeating the experiment in the same environments over two or more years.
由于生物和非生物因素的变化,不同环境下燕麦基因型的表现不同。因此,对不同环境下的燕麦基因型进行评价,对于确定优良的、稳定的基因型以提高产量具有重要意义。该研究旨在评估相互作用(基因型-环境相互作用;利用参数稳定性统计和非参数稳定性统计分析GEI对埃塞俄比亚燕麦(Avena sativa L.)籽粒产量稳定性的影响。采用随机完全区组设计,在9种环境中评估24种燕麦基因型,重复3次。对籽粒产量方差进行汇总分析,发现基因型、环境及其互作效应之间存在显著差异。显著的GEI揭示了基因型在不同环境下的等级变化。环境主效应解释了粮食产量总方差的44.62%,基因型和GEI效应分别解释了粮食产量总方差的28.84%和26.54%。利用12个参数稳定性统计量和2个非参数稳定性统计量对粮食产量稳定性进行了评价。结果表明,基于基因型优势指数(Pi)、Perkins和Jinks校正线性回归系数(Bi)和产量稳定指数(YSI)的稳定性参数,籽粒产量优越的基因型表现稳定,表明利用这些稳定性参数进行选择是提高籽粒产量的有效途径。Spearman等级相关系数也表明,稳定参数Pi、Bi和YSI与粮食产量呈显著正相关。籽粒产量与稳定性参数标准差、回归偏差、Hernandez可取性指数(Dji)、Wricke生态价(Wi)、Shukla稳定性方差(σi2)、AMMI稳定性值(ASV)和环境方差呈负相关,表明利用这些稳定性参数进行燕麦基因型选择并不有效,因为这些稳定性参数更倾向于低产量基因型。与高产的相比。因此,基于Pi、Bi和YSI的稳定性参数,G5、G8、G11、G12、G14、G16、G17、G19和G22基因型在所有9种环境下都具有适应性,选择这些优势基因型可以提高燕麦的产量。然而,这一结果的有效性应该通过在相同的环境中重复实验两年或更长时间来证实。
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引用次数: 2
Selection of rhizobial strains differing in their nodulation kinetics under low temperature in four temperate legume species 四种温带豆科植物低温结瘤动力学差异根瘤菌的筛选
Pub Date : 2023-07-25 DOI: 10.1002/glr2.12054
Emmanuelle D’Amours, A. Bertrand, J. Cloutier, François-P. Chalifour, A. Claessens, S. Rocher, M. Bipfubusa, Chantal Giroux, C. J. Beauchamp
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引用次数: 0
Selection of rhizobial strains differing in their nodulation kinetics under low temperature in four temperate legume species 四种温带豆科植物低温结瘤动力学不同菌株的选育
Pub Date : 2023-07-25 DOI: 10.1002/glr2.12054
Emmanuelle D'Amours, Annick Bertrand, Jean Cloutier, François-Philippe Chalifour, Annie Claessens, Solen Rocher, Marie Bipfubusa, Chantal Giroux, Chantal J. Beauchamp

Background

Winter climate change including frequent freeze-thaw episodes and shallow snow cover will have major impacts on the spring regrowth of perennial crops. Non-bloating perennial forage legume species including sainfoin, birdsfoot trefoil, red clover, and alsike clover have been bred for their adaptation to harsh winter conditions. In parallel, the selection of cold-tolerant rhizobial strains could allow earlier symbiotic nitrogen (N) fixation to hasten spring regrowth of legumes.

Methods

To identify strains forming nodules rapidly and showing high N-fixing potential, 60 rhizobial strains in association with four temperate legume species were evaluated over 11 weeks under spring soil temperatures for kinetics of nodule formation, nitrogenase activity, and host yield.

Results

Strains differed in their capacity to form efficient nodules on legume hosts over time. Strains showing higher nitrogenase activity were arctic strain N10 with sainfoin and strain L2 with birdsfoot trefoil. For clovers, nitrogenase activity was similar for control and inoculated plants, likely due to formation of effective nodules in controls by endophyte rhizobia present in seeds.

Conclusions

Selection based on nodulation kinetics at low temperature, nitrogenase activity, and yield was effective to identify performant rhizobial strains for legume crops. The use of cold-tolerant strains could help mitigate winter climatic changes.

背景冬季气候变化,包括频繁的冻融和浅雪覆盖,将对多年生作物的春季再生产生重大影响。为了适应恶劣的冬季条件,人们培育了不膨胀的多年生饲料豆类物种,包括海燕草、鸟足三叶草、红三叶草和类似苜蓿的植物。同时,选择耐寒的根瘤菌菌株可以使共生的氮(N)更早地固定,以加速豆类的春季再生。方法为了快速鉴定形成根瘤并显示出高固氮潜力的菌株,在春季土壤温度下,对60株根瘤菌与4种温带豆科植物的根瘤形成动力学、固氮酶活性和寄主产量进行了为期11周的评估。结果随着时间的推移,菌株在豆类寄主上形成有效根瘤的能力不同。表现出较高固氮酶活性的菌株是含有海燕蛋白的北极菌株N10和含有鸟足三叶草的菌株L2。对于丁香,对照和接种植物的固氮酶活性相似,这可能是由于种子中存在的内生根瘤菌在对照中形成了有效的根瘤。结论基于低温结瘤动力学、固氮酶活性和产量的筛选是鉴定豆科作物高效根瘤菌的有效方法。耐寒菌株的使用有助于缓解冬季气候变化。
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Grassland Research
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