MétaCan
Menu
Back to cohort
Record W2940421828 · doi:10.5539/jas.v11n5p259

Zinc Diffusion and Availability Affected by Different Sources in Soils of Contrasting Textures

2019· article· en· W2940421828 on OpenAlexvenueno aff
Wedisson Oliveira Santos, Priscila de Souza Aquino, Rafael Lucas Coca Cuesta, Isabela Maísa Honorato Saldanha, Edson Márcio Mattiello, Leonardus Vergütz

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsPetri dishFertilizerZincSoil waterDiffusionLimeFilter paperFactorial experimentChemistryNutrientLoamIncubationMathematicsMaterials scienceEnvironmental scienceSoil scienceMetallurgyPhysicsChromatographyBiology

Abstract

fetched live from OpenAlex

Trends in new fertilizer technologies should balance the nutrient release rate from fertilizers with plant demands over time, while developing suitable physical characteristics of the fertilizer’s particles. The objective of this study was to evaluate the performance of three zinc fertilizers [ZnO, ZnSO4, and a commercial co-granulated ZnO+S0 fertilizer (ES_Zn)] on Zn diffusion in soil and their agronomic performances. A Petri dish trial was carried out in order to evaluate the diffusion of Zn in the soil. The experiment was designed as a factorial scheme (3 + 1) × 2 × 3, with three Zn sources, one control treatment (without Zn application), two soils of contrasting textures (sandy and clay), and three incubation times (1, 30 and 60 d). The experiment was carried out under a completely randomized design with four replications. Zinc diffusion was assessed according to the method proposed by Degryse et al. (2015) along of incubation times. For that, a ZnSO4 solution or ZnO suspension was applied by pipetting 15 μL of solution or suspension into a small hole (~0.5-cm deep) in the center of the Petri dish. A single pastille of ES_Zn fertilizer (30±0.5 mg) was placed in the center of the Petri dish, at the same depth. Soil was watered to 80% of field capacity. Filter papers (Whatman) were impregnated with CaCO3 and placed on the soil surface. After 2 h of reaction, the CaCO3-impregnated filter papers were collected, and the precipitated Zn in the papers was colored with dithizone, giving a pink color. The performance of Zn sources was evaluated in a greenhouse through a successive maize-soybean-millet crop. The trial was designed as a 2 × (3 × 3 +1) factorial scheme, being two soils (sandy and clay), three Zn sources (ZnSO4, ZnO, and ES_Zn), three Zn doses (1.5, 3.0, and 6.0 mg dm-3 Zn), and a control treatment. The experiment was a randomized block design with four replications, being the experimental unit composed of a pot with 4 dm3 of soil. Pastille ES_Zn, ZnO (as suspension), and ZnSO4 (as solution) were applied at five equidistant points, at 5 cm below the soil surface. After 30, 60 and 60 days of planting, shoot of maize soybean and millet were harvest, oven-dried at 70 °C for 72 h (until constant weight), weighed and milled for chemical analysis. ES_Zn fertilizer promoted a delay Zn release in the soil, being effective as a fertilizer only in the last crop (millet), as well as ZnO. Zinc oxide and ZnSO4 had similar performances for increasing Zn availability in the inner soil portion, but its diffusion in soil was superior when the source was sulfate. The highly soluble ZnSO4 was more effective than ZnO-based fertilizers in terms of plant nutrition, especially for the two first crops. Our results also suggest that ZnO is solubilized in soil at high pH (6.6), its dispersion in soil being a key factor for the dissolution rate.

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 score0.805
Threshold uncertainty score0.123

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)0.0000.000

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 head0.005
GPT teacher head0.196
Teacher spread0.191 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicPlant Micronutrient Interactions and EffectsFrench-language works237,207