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The Effect of MSW Compost on Metal Uptake and Yield Of Wheat, Barley and Canola in Less Productive Farming Soils of Alberta

2000· article· en· W2320622398 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCompost Science & Utilization · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsAgriculture Food and Rural Development
Fundersnot available
KeywordsCompostCanolaHordeum vulgareBrassicaAgronomyBiosolidsPhosphorusRandomized block designNutrientChemistryCropAmendmentAnimal scienceEnvironmental sciencePoaceaeBiologyEnvironmental engineering

Abstract

fetched live from OpenAlex

Experiments were started in May 1998 at two sites to measure various crop responses to a mixed municipal solid waste-biosolids cocompost (named Nutri Plus) and examine the fate of certain metals associated with Nutri Plus compost. There were six treatments: Check, 50, 100, and 200 T compost/ha, NPKS (75 kg nitrogen (N) /ha, 20 kg phosphorus (P)/ha, 45 kg potassium (K) and 18 kg sulphur (S)/ha), PK (20 kg P, 45 kg K/ha), and three crops: canola (Brassica rapa cv. ‘Hysyn 110’), wheat (Triticum aestivum L. cv. ‘Roblin’) and barley (Hordeum vulgare L. cv. ‘Lacombe’). Each treatment was replicated four times and was in a complete randomized block design. In the compost treatments, 20 kg P and 45 kg K were applied due to low concentration of these two nutrients in the compost. Soil and plant samples were analyzed for nutrient content such as N, P and K. In addition, plant samples and soil samples after the compost application were also analyzed for elemental content of As, B, Cr, Co, Cu, Zn Se, Mo, Cd, Hg and Pb. The research results show that the compost slightly increased heavy metal concentrations in the soil but did not cause any phytoxicity to crops. Yield from 100 and 200 T/ha application was higher with the compost than with NPKS treatment. However, the yield of the 50 T/ha application was similar to that of NPKS treatment. Comparing the two sites, the compost apparently was more beneficial at Site 1 than at Site 2 in the year of application. This is likely due to the lower indigenous soil fertility and poor soil physical properties at Site 1. The N content in cereal grains was similar among the compost treatments but lower than the Check and NPKS treatments due to the diluting effect of higher yield. The oil content in canola seed was similar among all treatments. The results suggest that Nutri Plus compost applications generated positive yield responses in all three crops. Crop yield increased as the application rate increased. Heavy metal loading was not an immediate problem with the compost application, although it will limit total compost application over time to the same soil

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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 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 score0.271
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.257
Teacher spread0.238 · 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