DATA - Pyrolysis-driven stabilization and micronutrient partitioning in poultry waste–derived biochars

Published: 27 January 2026| Version 1 | DOI: 10.17632/9nks6sbpd2.1
Contributors:
PEDRO GARZON CAMACHO,
,

Description

This dataset provides the complete experimental evidence supporting the article “Pyrolysis-driven stabilization and micronutrient partitioning in poultry waste–derived biochars”. It documents how increasing pyrolysis temperature regulates carbon structural transformation, mineral enrichment, and the partitioning between total and bioavailable micronutrient pools in poultry waste–derived materials. The dataset includes raw poultry waste (PW) and biochars produced by slow pyrolysis at 300 °C (BPW300) and 600 °C (BPW600). For each material, the repository contains raw and processed measurements of biochar yield, pH, electrical conductivity, moisture content, volatile matter, ash content, fixed carbon, and easily oxidizable organic carbon. Elemental composition data (C, H, N, S, and O) and derived atomic ratios (H/C, O/C, and (O+N)/C) are provided to quantify carbon condensation, aromaticity, and chemical stability. Comprehensive macro- and micronutrient datasets are included, covering total concentrations of Na, Mg, P, Ca, K, Mn, Fe, Cu, and Zn determined by acid digestion and ICP-MS. In addition, chemically extractable (DTPA-extractable) fractions of Mn, Fe, Cu, and Zn are reported as indicators of potential bioavailability. Relative bioavailable fractions (% of total) are provided to explicitly resolve pyrolysis-driven micronutrient immobilization and stabilization processes. The repository also contains the multivariate data matrix used for principal component analysis (PCA), enabling integrated assessment of physicochemical properties, carbon structural indicators, and nutrient redistribution across treatments. Summary statistics (mean ± standard deviation; n = 3) and complete R scripts used for ANOVA, post hoc testing, PCA, and figure generation are included to ensure full computational reproducibility. Overall, this dataset enables independent verification of the reported results and supports secondary analyses on biochar design, nutrient stabilization mechanisms, environmental risk mitigation, and circular management of livestock residues. It is intended for reuse in soil science, environmental chemistry, waste valorization, and climate-smart agriculture research.

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Steps to reproduce

Feedstock collection and preparation Collect fresh poultry waste from a commercial poultry production system. Oven-dry the material at 60 °C for 48 h until constant mass is achieved. Grind and sieve the dried material to obtain particles smaller than 2 cm to ensure homogeneous thermal conversion. Biochar production by slow pyrolysis Produce biochars using slow pyrolysis in a laboratory-scale electric furnace under controlled atmospheric conditions. Apply two target pyrolysis temperatures: 300 °C and 600 °C, using a constant heating rate of 3 °C min⁻¹ and a residence time of 1 h at the final temperature. Allow samples to cool naturally to room temperature, sieve to < 2 mm, and store in airtight containers. Label materials as raw poultry waste (PW), BPW300, and BPW600. Biochar yield determination Determine biochar yield (%) on a dry-mass basis by dividing the mass of biochar obtained after pyrolysis by the initial dry mass of poultry waste and multiplying by 100. Physicochemical characterization Measure pH and electrical conductivity (EC) in a 1:2.5 (w/v) biochar-to-water suspension after shaking for 1 h. Determine moisture content gravimetrically at 105 °C. Perform proximate analysis to quantify volatile matter, ash content, and fixed carbon. Quantify easily oxidizable organic carbon using the Walkley–Black method. Elemental composition and stoichiometry Determine elemental composition (C, H, N, and S) by dry combustion using an elemental analyzer. Estimate oxygen content by difference. Calculate atomic ratios (H/C, O/C, and (O+N)/C) to assess carbon condensation and chemical stability. Macro- and micronutrient analysis Digest samples using an HCl:HNO₃ solution (3:1, v/v). Quantify total concentrations of Na, Mg, P, Ca, K, Mn, Fe, Cu, and Zn by ICP-MS following standardized analytical protocols. Micronutrient bioavailability assessment Estimate potentially bioavailable Mn, Fe, Cu, and Zn using a DTPA extraction (pH 7.3). Equilibrate 3.0 g of material with 20 mL of DTPA solution, agitate at 240 rpm for 2 h at room temperature, filter, and analyze extracts by ICP-MS. Express bioavailable fractions as absolute concentrations and as percentages of total elemental pools. Statistical and multivariate analysis Perform statistical analyses using R software (version 4.5.2). Evaluate treatment effects using ANOVA followed by Tukey’s post hoc test (p < 0.05). Conduct principal component analysis (PCA) on standardized variables to integrate physicochemical properties, carbon structural indicators, and nutrient distribution patterns. Reproducibility and data reuse Use the datasets and R scripts provided in this repository to reproduce all statistical analyses, tables, and figures reported in the associated publication.

Institutions

Categories

Chemical Elements Toxicology, Soil, Circular Economy, Biological Material

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