43 Approaches for improving nitrogen utilization efficiency and environmental sustainability of pork production systems
Bibliographic record
Abstract
Abstract Nitrogen (N) is an essential element for life, but due to its inefficient utilization, N waste and emissions generated have exceeded the planetary boundaries and ability of the Earth to effectively overcome these environmentally detrimental effects. Global food animal production contributes 29 to 34% of total global N emissions, with pork supply chains contributing about 16% of these emissions. Life cycle N use efficiency (NUE) of U.S. pork production is only about 56%, which is similar to broiler (55%) and egg (50%) production, but greater than beef (10%) and milk (31%) production. However, only about 10 to 44% of dietary N is converted into edible pork products. While genetic improvement has increased NUE associated with improved lean growth rate, improvement in litter size has led to an increased proportion of low-birth-weight pigs that have reduced NUE. Although metabolic modifiers including porcine somatotropin, ractopamine, and immunocastration improve NUE, they are not feasible or acceptable to consumers in many countries. Separate sex feeding and reducing market weight can also improve NUE. Ultimately feeding program design and implementation have the greatest potential to improve NUE because feed is associated with 70% of N emissions in pork production systems. Multi-objective feed formulation using Life Cycle Assessment environmental impact data of feed ingredients, precision feed formulation and feeding practices to overcome variability in digestible nutrient content of feed ingredients and nutritional requirements of pigs fed in groups, feed processing to enhance energy and nutrient digestibility, and minimizing feed wastage offer the greatest opportunity to improve NUE and environmental sustainability. There are substantial differences in greenhouse gas emissions and embedded water and land use associated with growing-finishing feeding programs depending on the dietary proportions of corn, soybean meal, distillers dried grains with solubles (DDGS), and crystalline amino acids among U.S. geographic regions. Furthermore, addition of thermally processed supermarket food waste to corn-soybean meal (CSBM) diets can significantly reduce environmental impacts and diet cost without compromising growth performance and carcass composition compared with current commercial feeding programs. Although growing-finishing feeding programs using CSBM diets with minimal crystalline amino acids result in greater N intake, N retained, and urinary N excretion compared with feeding low protein, crystalline amino acid supplemented (LP) diets, and diets containing 30% DDGS, growth performance and carcass composition are optimized and impacts on climate change, marine and freshwater eutrophication, and fossil resource are reduced by feeding CSBM diets compared with feeding LP or DDGS diets. Sourcing and using feed ingredients with reduced environmental impact metrics along with precision diet formulation and feeding practices to ensure “getting the right amount of energy and nutrients in the right feed fed to the right pigs at the right time” can improve NUE and environmental sustainability of pork production systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".