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Record W2159953687 · doi:10.23986/afsci.5682

Yield trends of temperate cereals in high latitude countries from 1940 to 1998

2001· article· en· W2159953687 on OpenAlexaboutno aff
Gustavo A. Slafer, Pirjo Peltonen‐Sainio

Bibliographic record

VenueAgricultural and Food Science · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetics and Plant Breeding
Canadian institutionsnot available
FundersHelsingin Yliopisto
KeywordsYield (engineering)Temperate climateAgronomyAgricultureMathematicsLatitudeAnimal scienceGeographyBiologyBotanyEcology

Abstract

fetched live from OpenAlex

Wheat is the only temperate cereal for which yield trends have been exhaustively analysed on both global and national bases. This paper aims (i) to compare global yield trends of wheat, barley, oat and rye for the last five decades, (ii) to analyse their yield trends in Canada, Denmark, Norway, Sweden and Finland, the northernmost limits for extensive agriculture, and (iii) using case studies, to assess the relative contribution to yield gains made by cereal breeding. Average global yield data from FAO were regressed against years using linear or bilinear regressions. Yield gains in absolute and relative terms were calculated for comparison among countries and cereals. Data from the literature were used to assess the estimated contributions made by breeding to yield gains. Global yield trends were not standard throughout the 1950-1998 period: rye exhibited a constant yield gain (c. 28 kg ha-1 y-1), while barley and oat showed marked increases until around 1970 (c. 38 and 32 kg ha-1 y-1, respectively) but quite modest increases (c.19 and 5 kg ha-1 y-1, respectively) over the last 30 years. Wheat also showed a bilinear trend with only limited yield gains until the 1960s, followed by a more than 3-fold increase in rate of yield gain from then on (16 and 40 kg ha-1 y-1, respectively). However, during the 1990s wheat yield gains have been less than previously. Hence, global yields of barley, oat and wheat have increased very slowly lately. Trends for each combination of cereals and countries indicated consistently higher yields during the 1990s than at mid-century. In general, wheat yield tended to increase at a faster rate than yield of the other cereals. There was a trend in the last decade of low rates of yield increase compared with those of previous decades. This was clear for oat and barley, and a similar trend is emerging for wheat. This suggests that genetic and/or management improvements have had less effect in recent times. Furthermore, we found preliminary evidence to suggest that with the exception of wheat in Canada, genetic contributions in northern areas were smaller than those reported for wheat and barley at lower latitudes. Therefore, alternative approaches must be sought for future breeding work under these high latitude conditions. ;

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)0.001
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.205
Teacher spread0.177 · 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".

Quick stats

Citations45
Published2001
Admission routes1
Has abstractyes

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