47 Feeding Pigs with Low Crude Protein Diets: Impact of Pig Manure Nitrogen Content on Biogas Production and Digestate Quality
Bibliographic record
Abstract
Abstract Lowering dietary crude protein levels is a nutritional strategy recognized to both decrease the use of high-impact feed ingredients and reduce nitrogen (N) excretion. Improved pig manure management practices can further mitigate the environmental impacts associated with pig production towards net-zero emissions. Anaerobic digestion (AD) is a promising technology for transforming pig manure into energy as biogas and into bio-based fertilizers (i.e., digestate from AD). However, little is known about the effects of pig manure N content on AD. Thus, this study aimed to evaluate the impact of pig manure N content on biogas production and digestate quality through the AD of manure from pigs fed low crude protein diets. Three pig manure N concentrations were tested: T1 = 5873, T2 = 5421, and T3 = 5149 total Kjeldahl nitrogen (TKN, mg/L). Throughout 5 sequential fed-batch cycles (25 ± 4 days/cycle), biogas production and its composition (CH4, CO2, and H2S) were measured, while raw manure and weekly digestate samples were analyzed for total solids (TS, %), volatile solids (VS, %), pH, chemical oxygen demand (COD, mg/L), TKN, and ammoniacal nitrogen (NH3-N, mg/L). In a temperature-controlled room (20 ± 1ºC), 6 digesters (3 treatments x 2 replicates) were operated as single-stage reactors to digest pig slurry (mixture of urine and feces, TS: 5.6%) inoculated with a liquid inoculum (TS: 2.3%) to improve manure-microbe interactions. Data were analyzed by ANOVA using PROC MIXED with repeated measures and comparison of means through the Tukey test (SAS software). In addition, both correlation and regression analyses were performed with R to evaluate the relationship among variables. Decreasing pig manure N content showed a tendency to reduce biogas (-20% in T3 vs T1; P = 0.0782) and methane (-22% in T3 vs T1; P = 0.0576) production per cycle, as shown in Table 1. Regarding biogas composition, CH4/biogas and CH4/CO2 decreased with N content (-3 and -4% in T3 vs T1; P ≤ 0.0082). There were strong positive correlations between the N content of pig manure and the amount of NH3-N (linear: r = 0.94, R2 = 0.88) and TKN (linear: r = 0.90, R2 = 0.81) present in the digestate at the end of each cycle. These results suggest that a reduction in pig manure N content reduces biogas production and its quality (ratio of CH4 to CO2). This latter variable is important for biogas efficiency; thus, reducing crude protein in pig diets may impair the production of biogas in AD. However, a decreased N content may cause less emissions into the environment, but when using the digestate as fertilizer, it may not entirely fulfill the N requirements of fast-growing crops for a given application rate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".