Synonyms: Agropyron androssovii Agrotrigia androssovii XAgrotrigia androsovii
Broader Terms: Agrotrigia  |
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 1. Trace metals accumulation in the eco-system water - soil - vegetation (Agropyron cristatum) - common voles (Microtus arvalis) - parasites (Hymenolepis diminuta) in Radnevo region, Bulgaria.
Rabadjieva D, Tepavitcharova S, Kovacheva A, Gergulova R, Ilieva R, Vladov I, Nanev V, Gabrashanska M, Karavoltsos S Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS), 2021 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
2. Identification, molecular and biological characterization of two novel secovirids in wild grass species in Belgium.
Maclot FJ, Debue V, Blouin AG, Fontdevila Pareta N, Tamisier L, Filloux D, Massart S Virus research, 2021 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
3. [Effects of Vegetation Restoration on the Structure and Function of the Rhizosphere Soil Bacterial Community of Solanum rostratum].
Zhang RH, Song Z, Fu WD, Yun LL, Gao JH, Wang R, Wang ZH, Zhang GL Huan jing ke xue= Huanjing kexue, 2021 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
4. Increasing rates of long-term nitrogen deposition consistently increased litter decomposition in a semi-arid grassland.
Hou SL, Hättenschwiler S, Yang JJ, Sistla S, Wei HW, Zhang ZW, Hu YY, Wang RZ, Cui SY, Lü XT, Han XG The New phytologist New Phytol Increasing rates of long-term nitrogen deposition consistently increased litter decomposition in a semi-arid grassland. 296-307 10.1111/nph.16854 The continuing nitrogen (N) deposition observed worldwide alters ecosystem nutrient cycling and ecosystem functioning. Litter decomposition is a key process contributing to these changes, but the numerous mechanisms for altered decomposition remain poorly identified. We assessed these different mechanisms with a decomposition experiment using litter from four abundant species (Achnatherum sibiricum, Agropyron cristatum, Leymus chinensis and Stipa grandis) and litter mixtures representing treatment-specific community composition in a semi-arid grassland under long-term simulation of six different rates of N deposition. Decomposition increased consistently with increasing rates of N addition in all litter types. Higher soil manganese (Mn) availability, which apparently was a consequence of N addition-induced lower soil pH, was the most important factor for faster decomposition. Soil C : N ratios were lower with N addition that subsequently led to markedly higher bacterial to fungal ratios, which also stimulated litter decomposition. Several factors contributed jointly to higher rates of litter decomposition in response to N deposition. Shifts in plant species composition and litter quality played a minor role compared to N-driven reductions in soil pH and C : N, which increased soil Mn availability and altered microbial community structure. The soil-driven effect on decomposition reported here may have long-lasting impacts on nutrient cycling, soil organic matter dynamics and ecosystem functioning. © 2020 The Authors New Phytologist © 2020 New Phytologist Trust. Hou Shuang-Li SL Erguna Forest-Steppe Ecotone Research Station, CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. Hättenschwiler Stephan S 0000-0001-8148-960X CEFE, CNRS, EPHE, IRD, Univ. Montpellier, Univ. Paul-Valery Montpellier 3, Montpellier 5, 34293, France. Yang Jun-Jie JJ State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China. Sistla Seeta S 0000-0002-6345-462X Natural Resources Management & Environmental Sciences, California Polytechnic State University, San Luis Obispo, CA, 93407, USA. Wei Hai-Wei HW Erguna Forest-Steppe Ecotone Research Station, CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. Zhang Zhi-Wei ZW Erguna Forest-Steppe Ecotone Research Station, CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. Hu Yan-Yu YY Erguna Forest-Steppe Ecotone Research Station, CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. Wang Ru-Zhen RZ 0000-0001-8654-6677 Erguna Forest-Steppe Ecotone Research Station, CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. Cui Shu-Yan SY Erguna Forest-Steppe Ecotone Research Station, CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. College of Life Science, Shenyang Normal University, Shenyang, 110034, China. Lü Xiao-Tao XT 0000-0001-5571-1895 Erguna Forest-Steppe Ecotone Research Station, CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. Han Xing-Guo XG 0000-0002-1836-975X Erguna Forest-Steppe Ecotone Research Station, CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China. eng Journal Article Research Support, Non-U.S. Gov't 2020 09 09 England New Phytol 9882884 0028-646X IM community level litter quality manganese nitrogen addition soil C : N soil microbial community structure soil pH 2020 05 25 2020 07 24 2020 8 8 6 0 2020 8 8 6 0 2020 8 8 6 0 ppublish 32762047 10.1111/nph.16854 References, 2021 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
5. Unitary and binary remediations by plant and microorganism on refining oil-contaminated soil.
Fei JJ, Wan YY, He XY, Zhang ZH, Ying YX Environmental science and pollution research international, 2020 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
6. Advancing crested wheatgrass [Agropyron cristatum (L.) Gaertn.] breeding through genotyping-by-sequencing and genomic selection.
Baral K, Coulman B, Biligetu B, Fu YB PloS one, 2020 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
7. [Composition and spatial distribution of main species in grassland community of Baiyinhua mining area, China].
Chun F, Bao G, Zhang WQ, Sai X Ying yong sheng tai xue bao = The journal of applied ecology, 2020 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
8. Differential stoichiometric homeostasis and growth in two native and two invasive C3 grasses.
Harvey JT, Leffler AJ Oecologia, 2020 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
9. Development of Specific Thinopyrum Cytogenetic Markers for Wheat-Wheatgrass Hybrids Using Sequencing and qPCR Data.
Nikitina E, Kuznetsova V, Kroupin P, Karlov GI, Divashuk MG International journal of molecular sciences, 2020 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
10. Dominance and G×E interaction effects improve genomic prediction and genetic gain in intermediate wheatgrass (Thinopyrum intermedium).
Bajgain P, Zhang X, Anderson JA The plant genome Plant Genome Dominance and G×E interaction effects improve genomic prediction and genetic gain in intermediate wheatgrass (Thinopyrum intermedium). e20012 10.1002/tpg2.20012 Genomic selection (GS) based recurrent selection methods were developed to accelerate the domestication of intermediate wheatgrass [IWG, Thinopyrum intermedium (Host) Barkworth & D.R. Dewey]. A subset of the breeding population phenotyped at multiple environments is used to train GS models and then predict trait values of the breeding population. In this study, we implemented several GS models that investigated the use of additive and dominance effects and G×E interaction effects to understand how they affected trait predictions in intermediate wheatgrass. We evaluated 451 genotypes from the University of Minnesota IWG breeding program for nine agronomic and domestication traits at two Minnesota locations during 2017-2018. Genet-mean based heritabilities for these traits ranged from 0.34 to 0.77. Using four-fold cross validation, we observed the highest predictive abilities (correlation of 0.67) in models that considered G×E effects. When G×E effects were fitted in GS models, trait predictions improved by 18%, 15%, 20%, and 23% for yield, spike weight, spike length, and free threshing, respectively. Genomic selection models with dominance effects showed only modest increases of up to 3% and were trait-dependent. Cross-environment predictions were better for high heritability traits such as spike length, shatter resistance, free threshing, grain weight, and seed length than traits with low heritability and large environmental variance such as spike weight, grain yield, and seed width. Our results confirm that GS can accelerate IWG domestication by increasing genetic gain per breeding cycle and assist in selection of genotypes with promise of better performance in diverse environments. © 2020 The Authors. The Plant Genome published by Wiley Periodicals, Inc. on behalf of Crop Science Society of America. Bajgain Prabin P 0000-0002-3093-5582 Department of Agronomy & Plant Genetics, University of Minnesota, St. Paul, MN, USA. Zhang Xiaofei X 0000-0003-4516-9179 The Alliance of Bioversity International and International Center for Tropical Agriculture, Cali, Colombia. Anderson James A JA 0000-0003-4655-6517 Department of Agronomy & Plant Genetics, University of Minnesota, St. Paul, MN, USA. eng Journal Article Research Support, Non-U.S. Gov't 2020 03 19 United States Plant Genome 101273919 1940-3372 IM Agropyron genetics Genome, Plant Genomics Plant Breeding Poaceae genetics 2019 12 09 2020 01 30 2020 10 5 8 45 2020 10 6 6 0 2020 10 10 6 0 ppublish 33016625 10.1002/tpg2.20012 REFERENCES, 2020 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=0
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