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Record W4205603904 · doi:10.3390/agronomy12020243

Long-Term Effects of Animal Manures on Nutrient Recovery and Soil Quality in Acid Typic Hapludalf under No-Till Conditions

2022· article· en· W4205603904 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.

Bibliographic record

VenueAgronomy · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Management and Crop Yield
Canadian institutionsUniversité Laval
FundersFundação de Amparo à Pesquisa do Estado do Rio Grande do SulConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsAgronomyManureEnvironmental scienceFertilizerAgroecosystemSoil qualityNutrientSoil organic matterSoil carbonCover cropOxisolSoil waterBiologyAgricultureSoil scienceEcology

Abstract

fetched live from OpenAlex

No-till farming and manure application are means of storing carbon in soil and increasing soil quality. However, the organic fertilization of no-till soils may sustain subtropical agroecosystems for only a limited period until the soil quality declines. The C, N, P, and other nutrient cycles are perturbed due to the nutrient imbalance in manures and their application on the soil surface, which poses a risk for nutrient dispersion into the environment. Long-term N-based manure application also impacts the apparent nutrient recovery (ANR) by crops and, hence, the crop quality. Our objective was to monitor changes in soil quality and to measure nutrient recovery from N-based organic fertilization in a Brazilian agroecosystem. A long-term experiment was established in May 2004 on Typic Hapludalf soil in Southern Brazil. The experiment comprised two periods: 2004–2009 and 2009–2020. The treatments were unfertilized (control), pig slurry, pig deep litter (swine manure and rice husk), cattle slurry, and mineral fertilizer (urea, triple superphosphate, and K chloride). Grain and cover crops were grown. The maize grain yield and oat biomass were used as indicators of productivity. The application of cattle slurry, pig deep litter, and pig slurry increased the grain production by 20% on average compared to mineral fertilization. Organic manuring increased the soil pH by up to one unit, while urea acidified the soil. The highest crop yields were obtained with pig deep litter, which increased the levels of P, K, Ca, Mg, and C in the soil test. Pig deep litter showed the highest N-ANR for the aboveground part of the plants. The ANRs for P, K, Ca, and Mg were also highest when pig slurry had been applied. The ANR values for the micronutrients varied widely among the organic sources but indicated large marginal offtake gains compared to mineral fertilization. The N-based fertilization with animal manures increased the rate of nutrient uptake by plants but led to an accumulation of nutrients in the soil, threatening the sustainability of the system. Manure applications must be monitored regularly to avoid the accumulation of nutrients that could impair the soil quality and become an environmental problem in the future.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.573

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.017
GPT teacher head0.240
Teacher spread0.222 · 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