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Record W2963103012

Maize inbreds for multiple resistance breeding against major foliar, ear and stalk rot diseases.

2019· article· en· W2963103012 on OpenAlexaffabout
K.K. Jindal, Xiaoyang Zhu, T. Woldemariam, Albert Tenuta, M. K. Jindal, N. Javed, Fouad Daayf, L. M. Reid

Bibliographic record

VenueMaydica · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsUniversity of ManitobaMinistry of Agriculture, Food and Rural AffairsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsEyespotBiologyRust (programming language)SmutAgronomyResistance (ecology)Leaf spotCropBlightHorticultureBotany
DOInot available

Abstract

fetched live from OpenAlex

Resistance breeding is considered the most effective and eco-friendly method to manage most of the crop diseases, but it can be challenging to find sources of resistance in maize for short growing season regions. In this study, 218 maize inbreds were evaluated in order to select those, which possess resistance to one or more of the following diseases:  Northern Corn Leaf Blight (NCLB), common rust, eyespot, grey leaf spot (GLS), goss’s bacterial wilt and leaf blight (goss’s wilt), Gibberella (fusarium) ear and stalk rot, and common smut. Significant variation in disease resistance was detected in the inbreds evaluated. Twenty-six inbreds, most of them of Canadian origin, were found to possess excellent resistance to multiple diseases. Three inbreds (CO428, CO470 and CO471) exhibited resistance to five foliar diseases (NCLB, common rust, eyespot, GLS, and goss’s wilt), while another seven inbreds had a resistant reaction to four diseases (CO452, CO466 and CO468 to common rust, eyespot, GLS and goss’s wilt; C0473 to NCLB, common rust, GLS and goss’s wilt; CO464 to NCLB, eyespot, GLS, and goss’s wilt, and PHZ51 to eyespot, ERSC, common smut, and goss’s wilt). Five of these inbreds also had intermediate resistance against stalk and ear rot. Forty-five inbreds were found to have resistance against two to three diseases. Inbreds CO457, CO458, CO459 and CO460 released as highly resistance to common rust were also found to have good resistance against eyespot, and GLS or goss’s wilt. CO450 released for eyespot resistance had good resistance against common rust and GLS, and moderate resistance against goss’s wilt. Three inbreds CO387, CO441, and CO449 were found to have resistance for gibberellic ear rot both by silk and kernel inoculation methods and common smut. Most of these inbreds found resistant in this study were from the Stiff Stalk (BSSS), Lancaster and Iodent maize heterotic groups. Many of the resistant inbreds identified in this study are excellent sources of resistance to leaf, ear and stalk rot diseases, and could be utilized in maize breeding programs for developing new hybrids with multiple disease resistance.

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 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 score0.198
Threshold uncertainty score0.212

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 head0.010
GPT teacher head0.193
Teacher spread0.183 · 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 teacher head, 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".

Quick stats

Citations11
Published2019
Admission routes2
Has abstractyes

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