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Record W7014763521

Productivity and environmental sustainability of grasslands receiving liquid hog manure

2007· dissertation· en· W7014763521 on OpenAlexfundno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2007
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
FundersBeef Cattle Research CouncilDairy Farmers of Canada
KeywordsForageManureNutrientHayFodderBiomass (ecology)Productivity
DOInot available

Abstract

fetched live from OpenAlex

A two-year (2004 to 2005) experiment was conducted to detemine tlie effect of liquid pratensis) and quackgrass (,4gropyron repens), its effect on forage yield and quality, as well as pasture and animal performance.Environmental sustainability in tenns of nutrient removal and enteric methane (CHq) emissions were also examined.Forage production data was collected from replicated grass hayfields and pastures receiving no liquid hog manure or liquid hog manure as a single application (Full) of 155 kg har of available nitrogen G.Ð in the spring or as a split application (split) of 74kg ha-rof available N in both the spring and the autumn.Multiple 0.25m2 quadrats of standing forage were clipped in hayfields immediately prior to haying to determine DM yield and forage nutrient composition' Quadrat samples were collected in pastures every 2g days to determine DM yield, and hand-plucked forage samples were collected to determine nutrient composition of forage consumed by cattle.As well, pasture productivity, animal production, and enteric CH¿ emissions data were collected.Enteric CH¿ emissiolls were quantified using the sulphur hexafluoride (SFe) tracer gas technique.Animal weight, blood samples and 24-h CHa expiration were measured once in each of thr ee 2g-day periods' Nutrient balance of hayf,relds and pastures was determined by comparing nutrient removal in the form of animal gain or baled hay to nutrients applied in the form of liquid hog manure.Hog manure application on hayfields increased forage yield and nutrient profiles relative to hayfields receiving no fertility.Average standing forage biomass generated in control, SplitandFullhayfieldswere 3.7,g.gandg.4+0.31rha-r,respectivery(p:0.000r).Mean lll standing forage cP was lowest in unmanured standing forage (7.1 + 0.24 yo cp, P:0'0004), while Split and Full hayf,relds had CP concentrations of 9.4 arñ 10.5 yo, in-Spli'lh¿yfi€1ds-(6rc W P:0'0545) than in control or Full hayfields (57.1 and 5s.g %)due to its advanced state of maturity at cutting' Gross energy was highest in manured hayfields (i g.3, l g.6 and I g.5 + 0.06 kJ g-l DM, in control, Sprit and Fuil hayf,rerds, respectively, p:0.0443).Application of hog manure increased nutrient profile of pasture forages relative to those receiving no fertility' Mean forage CP was more than doubled with manure application (P:0'0492).Steers gtazingunmanured pastures had lower serup urea N (2.56 t 0.61 mmol L-l, P:0.0225) values compared to steers grazingmanured pastures (Split :6.06, Full:6'09 mmol L-r¡.Animal DMI and enteric CHa emissions (% GEI) were unaltered by the changes in forage quality as a result of manure application.The addition of hog manure increased pasture carrying capacity over the grazingseason by more than three- fold compared to unmanured pastures, which averaged l0l grazingdays ha-r yr-r.Animal productivity increased from 104 kg gain ha-l for unfenilized to 325 and 344 kg gain ha-l for Split and Full pasture treatments, respectively (p=0.0019).Nitrogen and phosphorus (P) removal efficiencies based on nutrients applied were up to 7-and 4-fold greater in the hayed system compared to the pastoral system, in which only 4.7 % of applied N and 6.r % of the applied p were recovered.The low nutrient utilization effltciencies in each system indicate a need to monitor the rate or frequency of liquid hog manure application to reduce nutrient build-up in the grassland system.IV ACKNOWI,EDGEMENTS I thank Dr. I(im Ominski for hel encouragement and guidance thr.oughout my e-prograffipnd{orpn¡vi with researchers and industry members excited about "my" resealch project.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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 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

Citations1
Published2007
Admission routes1
Has abstractno

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