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Record W2998258329 · doi:10.15414/afz.2019.22.03.84-89

Identification and relative abundance of native arbuscular mycorrhizal fungi associated with oil-seed crops and maize (Zea mays L.) in derived savannah of Nigeria

2019· article· en· W2998258329 on OpenAlexaboutno aff
Nurudeen Olatunbosun Adeyemi

Bibliographic record

VenueActa fytotechnica et zootechnica/Acta fytotechnica et zootechnica · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsZea maysAgronomyArbuscular mycorrhizal fungiBiologyPoaceaeIdentification (biology)BotanyHorticultureInoculation

Abstract

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Article Details: Received: 2019-07-22 | Accepted: 2019-10-10 | Available online: 2019-09-30 https://doi.org/10.15414/afz.2019.22.03.84-89 A field survey was conducted to assess root colonization, spore densities and relative abundance of native arbuscular mycorrhizal fungi (AMF) based on morphological aspects. Roots and rhizosphere soil samples were collected from established fields of selected oil seed crops [soybean (Glycine max L.), sesame (Sesamum indicum) and sunflower (Helianthus annuus)] and maize (Zea mays L.) grown in derived savannah agro-ecology of Southwest Nigeria. The mean percentage of AMF colonization across all crops was 60.8%, ranging from 34% to 87.5%, with highest root colonization observed in soybean. The spore densities retrieved from the different rhizospheres were relatively high, varying from 124 to 298 spores per 50 g dry soil, with highest spore densities observed in maize rhizosphere soils. The spore densities in the soil significantly correlated (r = 0.52, and P <0.05) with the root colonization. A total of 4 morphologically classifiable genera (Glomus, Gigaspora, Acaulospora, and Scutellospora) of AMF within the phylum Glomeromycota were detected. The dominant genus was Glomus in all the crops with highest relative abundance of 60.9%, followed by Acaulospora (21.3%) and Scutellospora (12.8%), with lowest relative abundance of AM spores observed for Gigaspora (5%). This study could contribute significantly to a better understanding of AMF community structure in derived savannah agro-ecology of Nigeria. Keywords: Arbuscular mycorrhizal fungi, community structure, oil-seed crops, root colonization, spore density References AZCÓN-AGUILAR, C. and BAREA, J.M. (1997) Arbuscular mycorrhizas and biological control of soil-borne plant pathogens – an overview of the mechanisms involved. In Mycorrhiza, vol. 6, pp. 457–464. BIERMANN, B. and LINDERMAN, R.G. (1983) Use of vesicular-arbuscular mycorrhizal roots, intraradical vesicles and extraradical vesicles as inoculum. In New Phytolologist, vol. 95, pp. 97–105. BODDINGTON, C.L., and DODD, J.C. (2000) The effect of agricultural practices on the development of indigenous arbuscular mycorrhizal fungi. I. Field studies in an Indonesian ultisol. In Plant Soil, vol. 218, pp. 137–144. BRUNDRETT, M.C. (2002) Coevolution of roots and mycorrhizas of land plants. In New Phytologist, vol. 154, pp. 275–304. DAVISON, J. et al. (2015) Global assessment of arbuscular mycorrhizal fungus diversity reveals very low endemism. In Science, vol. 349, pp. 970- 973. DOUDS, D.D. Jr, 2005. On-farm production and utilization of arbuscular mycorrhizal fungus inoculum. In Canadian Journal of Plant Science, vol. 85, pp. 15–21. EVELIN, H., KAPOOR, R. and GIRI, B. (2009) Arbuscular mycorrhizal fungi in alleviation of salt stress: a review. In Annals of Botany, vol. 104, pp.1263–1280. GIOVANNETTI, M. and MOSSE, B. (1980) An evaluation of techniques for measuring vesicular arbuscular mycorrhizal infection in roots. In New Phytologist, vol. 84, pp. 489–500. HAZARD, C. et al. (2013) The role of local environment and geographical distance in determining community composition of arbuscular mycorrhizal fungi at the landscape scale. In The ISME Journal, vol. 7, pp. 498–508. LEKBERG, Y. et al. (2007) Role of niche restrictions and dispersal in the composition of arbuscular mycorrhizal fungal communities. In Journal of Ecology, vol. 95, pp. 95–105. LIN, X. et al. (2012) Long-term balanced fertilization decreases arbuscular mycorrhizal fungal diversity in an arable soil in north China revealed by 454 pyrosequencing. In Environmental Science & Technology, vol. 46, pp. 5764–5771. OEHL, F. et al. (2003) Impact of land use intensity on the species diversity of arbuscular mycorrhizal fungi in agroecosystems of Central Europe. In Applied Environmental Microbiology, vol. 69, pp. 2816–2824. OEHL, F. et al. (2009) Distinct sporulation dynamics of arbuscular mycorrhizal fungal communities from different agroecosystems in longterm microcosms. In Agric Ecosyst Environ., vol. 134, pp. 257–268. OEHL, F. et al. (2010) Soil type and land use intensity determine the composition of arbuscular mycorrhizal fungal communities. In Soil Biology and Biochemistry, vol. 42, pp. 724–738. OHSOWSKI, B.M. et al. (2014) Where the wild things are: looking for uncultured Glomeromycota. In New Phytologist, no. 204, pp. 171–179. PEYRET-GUZZON, M. et al. (2016) Arbuscular mycorrhizal fungal communities and Rhizophagus irregularis populations shift in response to short term ploughing and fertilisation in a buffer strip. In Mycorrhiza, vol. 26, pp. 33–46. PHILLIPS, J.M. and HAYMAN, D.S. (1970) Improved procedures for clearing roots and staining parasitic and VA mycorrhizal fungi for rapid assessment of infection. In Trans Br Mycol Soc., vol. 55, no.158–161. PIVATO, B. et al. (2007) Medicago species affect the community composition of arbuscular myccorhizal fungi associated with roots. In New Phytologist, no. 176, pp. 197–210. RILLIG, M. C. (2004) Arbuscular mycorrhizae, glomalin, and soil aggregation. In Canadian Journal of Soil Science, vol. 84, pp. 355–363. RILLIG, M.C. and Mummey, D.L. (2006) Mycorrhizas and soil structure. In New Phytologist, no.171, pp. 41–53 SCHENCK, N.C. and PEREZ, Y. (eds.) (1990) Manual for identification of VA mycorrhizal fungi. Gainesville: INVAM, University of Florida. 241 p. SCHEUBLIN, T.R. et al.( 2004) Nonlegumes, legumes, and root nodules harbor different arbuscular mycorrhizal fungal communities. In Applied Environmental Microbiology, vol. 70, pp. 6240–6246. SCHÜΒLER, A, SCHWARZOTT, D. and WALKER, C. (2001) A new fungal phylum, the Glomeromycota: phylogeny and evolution. In Mycology Research, vol. 105, pp. 1413–1421. SMITH, S.E., and READ, D.J. (2008) Mycorrhizal symbiosis. 3rd ed. New York: Academic Press. 787 p. VERBRUGGEN, E., and TOBY KIERS, E. (2010) Evolutionary ecology of mycorrhizal functional diversity in agricultural systems. In Evolutionary Appl., no. 3, pp. 547–560. YAMATO, M., IKEDA, S., and IWASE, K. (2009) Community of arbuscular mycorrhizal fungi in drought-resistant plants, Moringa spp., in semiarid regions in Madagascar and Uganda. In Mycoscience., vol. 50, pp. 100–105.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.216
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations12
Published2019
Admission routes1
Has abstractyes

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