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Record W2591012596 · doi:10.2135/cropsci2016.08.0698

Biomass Yield of Switchgrass Cultivars under High‐ versus Low‐Input Conditions

2017· article· en· W2591012596 on OpenAlexfundno aff
Michael D. Casler, Sergio Rubiano Sosa, L. Richard Hoffman, Hilary Mayton, Calvin L. Ernst, Paul R. Adler, Arvid R. Boe, Stacy A. Bonos

Bibliographic record

VenueCrop Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsnot available
FundersNational Institute of Food and AgricultureMinistry of Agriculture - SaskatchewanU.S. Department of Agriculture
KeywordsPanicum virgatumCultivarAgronomyBiomass (ecology)BiologyCellulosic ethanolHardiness (plants)Energy cropBioenergyCompetition (biology)SaccharumFertilizerCropEnvironmental scienceBiofuelBiotechnologyEcologyCellulose

Abstract

fetched live from OpenAlex

Switchgrass ( Panicum virgatum L.) is undergoing development as a biomass crop to support conversion of cellulosic biomass to energy. To avoid the competition of biomass with food or feed crops, most commercialization proposals suggest that switchgrass should be grown exclusively on marginal lands that are not fit for food or feed production. The objective of this study was to investigate the potential for cultivar × environment interactions that would affect the methods and approaches for breeding and evaluating switchgrass cultivars, including both upland and lowland types, for high‐input versus low‐input types of environments. Biomass yield was measured on 14 cultivars that were present in 28 replicated field experiments representing seven regions, ranging from 75 to 100° W and spanning USDA Hardiness Zones 4 through 7. Region was the most important environmental factor interacting with cultivars, supporting the idea that the north‐central and northeastern United States should have independent switchgrass breeding programs. Cultivars interacted with soil phosphorus concentration in New Jersey and with depth of the A and B horizons in New York and showed mild interactions with rate of nitrogen fertilizer at several locations. Cultivar rank correlation coefficients between the two rates of nitrogen fertilization (100 vs. 0 kg N ha −1 ) ranged from 0.23 to 0.88, suggesting a possible benefit to breeding and selection without applied nitrogen fertilizer.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.638
Threshold uncertainty score0.963

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 studies0.0010.001
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 head0.049
GPT teacher head0.282
Teacher spread0.233 · 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 designBench or experimental
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

Citations38
Published2017
Admission routes1
Has abstractyes

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