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Record W2966784123

Dependence of species composition and development of root rots pathogens of spring barley on abiotic factors in the Eastern Forest-Steppe of Ukraine

2019· article· en· W2966784123 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUkrainian Journal of Ecology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Biological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAbiotic componentAgronomyBiologyBipolarisSteppeFusariumMonocultureRoot rotBotanyEcology
DOInot available

Abstract

fetched live from OpenAlex

Root rots of spring barley have become widespread and cause a significant damage to agriculture. The poorer the culture of agriculture is, the higher are the losses from the root rots. Non-observance of crop rotation, the presence of monoculture of one or another species of cereals and poor agricultural technique lead to deterioration of the structure and depletion of the soil, create the unfavourable conditions for the development of plants, and facilitate the accumulation of pathogenic fungi in the soil and plant remains. Abiotic factors significantly affect the species composition and pathogens of the root rots, which requires the specification of these indices parameters, especially under the conditions of the Eastern Forest-Steppe of Ukraine. We have found that Helminthosporium and Fusarium root rots of spring barley are the most widespread in the zone of the Eastern Forest-Steppe of Ukraine, the pathogenic organisms of which are fungi of the genus Drechslera spp. and Fusarium spp. The development and prevalence of root rots directly depend on the weather conditions during the vegetation period of spring barley and are intensified with a considerable amount of precipitation, high air humidity (60-80%), moderate temperature (19-20° Ði), and hydrothermal coefficient of 1,2-1,4. Under the conditions of the Eastern Forest-Steppe of Ukraine these diseases are taking their dynamic courses with a significant increase in the later stages of the plant-feeder development. Keywords: Root rots of spring barley; Bipolaris sorokiniana Shoem.; Fusarium spp.; abiotic factors References: Bilyk, M. O., & Kulieshov, A. V. (2006). Praktykum z fitosanitarnoho monitorynhu i prohnozu. Kharkiv. (in Ukrainian). Boyko, A. K., & Radyina, A. A. (2004). Vliyanie temperaturyi i otnositelnoy vlajnosti vozduha na porajennost kolosa yarovogo yachmenya vozbuditelyami fuzarioza. Іntegrovaniy zahist roslin na pochatku XXI stolN–ttya. Proceed. Int Conf. Kiev: ІZR. (in Russian). Engle, J. S., Lipps, P. E., & Mills, D. (2004). Spot blotch and common root rot. Frankfort: Ohio University press.  Fernandez, M. R., Holzgang, G., & Turkington, T. K. (2009). Common root rot of barley in Saskatchewan and north-central Alberta. Canadian Journal of Plant Pathology, 31(1), 96-102. doi:10.1080/07060660909507577 Fernandez, M. R., & Conner, R. L. (2011). Root and crown rot of wheat. Prairie Soils Crops J, 4, 151-157. Kumar, J., Schafer, P., Huckelhoven, R., Langen, G., Baltruschat, H., Stein, E., Nagarajan, S., Kogel, H. K. (2002). Bipolaris sorokiniana, a cereal pathogen of global concern: cytological and molecular approaches towards better control. Mol Plant Pathol, 3, 185-195 Markov, I. L., Bashta, O. V., Hentosh, D. T., Dermenko, O. P., & Pikovskyi, M. I. (2017). Silskohospodarska fitopatolohiia. Kyiv: Interservis. (in Ukrainian). Mathre, D. E., Johnston, R. H., & Grey, W. E. (2003). Diagnosis of common root rot of wheat and barley. Plant Health Progress, 4(1). doi:10.1094/PHP-2003-0819-01-DG. Meldrum, S. I., Platz, G. J., & Ogle, H. J. (2004). Pathotypes of Cochliobolus sativus on barley in Australia. Aust Plant Pathol, 33, 109–114. Naumova, N. A. (1970). Analiz semyan na gribnuyu bakterialnuyu infektsiyu. Leningrad. (in Russian). Peresyipkin, V. F., Tyuterev, S. L., & Batalova, T. S. (1991). Bolezni zernovyih kultur pri intensivnyih tehnologiyah ih vozdelyivaniya. Moscow: Agropromizdat. (in Russian). Prodaievych, T., & Hentosh, D. T. (2015). Osoblyvosti rozvytku korenevykh hnylei yachmeniu v umovakh SFH “Tsabii L.V.” Kirovohradskoi oblasti. Dosiahnennia i perspektyvy v zakhysti roslyn vid khvorob. Materialy I Vseukrainskoi studentskoi naukovoi konferentsii (26-27 bereznia 2015 roku, m. Kyiv). Kyiv: TOV “TsP KOMPRYNT” (in Ukrainian). Stack, W. R. (1992). Bipolaris. In: Singleton, L. L., Mihail, J. D., and Rush, C. M. (eds.). Methods for Research on Soilborne Pathogenic Fungi. American Phytopathological Society, St. Paul, MN. Tinline, R. D., Diehl, J. A., & Spurr, D. T. (1994). Assessment methods for evaluating common root rot in spring wheat and infection of subterranean plant parts by the causal fungus Cochliobolus sativus. Can J Plant Pathol, 16, 207-214.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.159
Threshold uncertainty score0.124

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.028
GPT teacher head0.211
Teacher spread0.182 · 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