The influences of progenitor filtering, domestication selection and the boundaries of nature on the domestication of grain crops
Bibliographic record
Abstract
Abstract Domestication generally involves two sequential processes: initial identification of wild species with desirable characteristics (‘progenitor filtering’) and subsequent artificial and natural selection that, respectively, improve features preferred by humans and adapt species to cultivation/captivity (‘domestication selection’). Consequently, domesticated species can differ from wild species and may share characteristics owing to convergent evolution (‘domestication syndrome’). Baring evolutionary constraints, domestication selection may generate extreme phenotypes that transcend the ‘boundaries of nature’ evident for wild species. Despite evidence of domestication syndromes in some clades, broader contributions of progenitor filtering and domestication selection to characteristics of contemporary domesticated species have received limited attention. Using comparative analysis of 49 grain‐crop and 87 wild annual plant species from 15 families, we (1) addressed whether plants of crop and wild species differ for mean seed number, per‐seed mass and total seed‐mass investment; (2) assessed contributions of (a) progenitor filtering and (b) domestication selection to these differences; (3) evaluated whether crop characteristics exceed the boundaries of nature and (4) assessed whether seed‐production characteristics of grain crops constitute components of a generic domestication syndrome. On average, grain‐crop plants produce heavier seeds and greater total seed mass than wild species, but seed number per plant does not differ. Comparison of wild species between genera with or without crop species found no evidence of progenitor filtering. In contrast, crop species differed from congeneric wild species for the mass traits, but not for seed number. Greater seed investment by crops is consistent with artificial selection for enhanced seed yield (mass per harvested area), whereas heavier individual seeds suggest selection for improved nutritional quality and (or) adaptation to cultivation environments. Seed number–size characteristics of grain‐crop species lie within the bivariate variation among wild species and so do not exceed the boundaries of nature. Seed number and size varied similarly between species types and generally aligned with seed‐investment isoclines, suggesting an upper investment limit. Despite greater average investment in seed production and individual seeds by grain‐crop species, seed‐production characteristics did not vary less among crop species than among wild species, which is inconsistent with a common domestication syndrome. A free Plain Language Summary can be found within the Supporting Information of this article.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".