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Record W2104920699 · doi:10.1093/jxb/erv123

C<sub>4</sub>bioenergy crops for cool climates, with special emphasis on perennial C<sub>4</sub>grasses

2015· review· en· W2104920699 on OpenAlexaff
Rowan F. Sage, Murilo de Melo Peixoto, Patrick Friesen, Bill Deen

Bibliographic record

VenueJournal of Experimental Botany · 2015
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsUniversity of GuelphUniversity of Toronto
Fundersnot available
KeywordsMiscanthusPerennial plantPanicum virgatumAgronomyBioenergyBiologyOverwinteringRhizomeEnvironmental scienceBiofuelEcology

Abstract

fetched live from OpenAlex

There is much interest in cultivating C4 perennial plants in northern climates where there is an abundance of land and a potential large market for biofuels. C4 feedstocks can exhibit superior yields to C3 alternatives during the long warm days of summer at high latitude, but their summer success depends on an ability to tolerate deep winter cold, spring frosts, and early growth-season chill. Here, we review cold tolerance limits in C4 perennial grasses. Dozens of C4 species are known from high latitudes to 63 °N and elevations up to 5200 m, demonstrating that C4 plants can adapt to cold climates. Of the three leading C4 grasses being considered for bioenergy production in cold climates--Miscanthus spp., switchgrass (Panicum virgatum), and prairie cordgrass (Spartina pectinata)--all are tolerant of cool temperatures (10-15 °C), but only cordgrass tolerates hard spring frosts. All three species overwinter as dormant rhizomes. In the productive Miscanthus×giganteus hybrids, exposure to temperatures below -3 °C to -7 °C will kill overwintering rhizomes, while for upland switchgrass and cordgrass, rhizomes survive exposure to temperatures above -20 °C to -24 °C. Cordgrass emerges earlier than switchgrass and M. giganteus genotypes, but lacks the Miscanthus growth potential once warmer days of late spring arrive. To enable C4-based bioenergy production in colder climates, breeding priorities should emphasize improved cold tolerance of M.×giganteus, and enhanced productivity of switchgrass and cordgrass. This should be feasible in the near future, because wild populations of each species exhibit a diverse range of cold tolerance and growth capabilities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
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)0.0000.000

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 head0.048
GPT teacher head0.295
Teacher spread0.247 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations56
Published2015
Admission routes1
Has abstractyes

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