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Record W2792677724 · doi:10.2136/sssaj2017.08.0284

Modeling Barley Yield in a Dark Brown Chernozem after Discontinuation of Long‐term Manure Application

2018· article· en· W2792677724 on OpenAlexafffundabout
Ikechukwu Agomoh, Francis Zvomuya, Xiying Hao, Mônica B. Benke

Bibliographic record

VenueSoil Science Society of America Journal · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsUniversity of ManitobaLethbridge CollegeAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsChernozemManureHordeum vulgareAgronomySoil waterEnvironmental scienceYield (engineering)FertilizerCrop yieldMathematicsSoil sciencePoaceaeBiology

Abstract

fetched live from OpenAlex

Core Ideas Soil properties at the discontinuation of manuring adequately explained subsequent grain yield. Soil TOC, TP, TN, and NO 3 –N were most influential and consistent in explaining yield variability. No evidence of convergence in grain yield among the discontinued manure treatments after 7 yr. Fertilizer application on soils that have received long‐term manure application is often not necessary and typically not advised for environmental reasons. Soil properties at the discontinuation of manure application may assist in modeling crop yield trends on such soils in subsequent years. The data used in this study were from a long‐term field experiment initiated in 1973 at the Agriculture and Agri‐Food Canada Research and Development Centre in Lethbridge, Alberta. Soil and plant samples were collected annually from 1973 through 2010 from irrigated plots that were cropped to barley ( Hordeum vulgare L.) every year. Soil properties measured at the start of the experiment in 1973 were used to model yield in the control plots while soil properties measured at the end of annual manure applications in 2003 were used as predictors in partial least squares (PLS) regressions to model barley yield in subsequent years in plots in which manure application was discontinued. Soil total N, organic carbon, P, and NO 3 –N concentrations were the most important soil properties for modeling annual barley grain yield in manured soils using PLS regression. Our results indicate that initial measured soil properties can be a useful tool in modeling yearly crop yield. During the 7 yr following discontinuation of manure application, there was no evidence of convergence in grain yield among amendment treatments, reflecting that the soil nutrient levels were above agronomic thresholds for optimum yields. Long‐term monitoring of yield will assist in the development of models for predicting when nutrient application will become necessary.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.562

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.239
Teacher spread0.225 · 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 designSimulation or modeling
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

Citations1
Published2018
Admission routes3
Has abstractyes

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