Notes on DDGS and DACITIC Tuff Breccia (DTB) Effects on Pellet Production Rate and Pellet Durability

Objective and context

• Investigates how distillers dried grain with solubles (DDGS) and a dacitic tuff breccia (DTB, AZOMITE) affect pellet production rate and pellet durability in broiler diets.
• DDGS is known to reduce pellet production efficiency and pellet quality; minerals like DTB may improve pellet efficiency by scouring die holes and reducing friction.
• Primary objective: understand the relationship between a broad range of DDGS inclusions (0, 4, 8, 12, 16%) and DTB inclusion (0 or 0.25%) in terms of pellet production rate and pellet durability index (PDI).
• Context: DDGS quality varies across sources; its composition (low starch, high fat and fiber) can impede pelleting, but processing factors and mineral additives may mitigate issues.

Experimental design

• Design: 5 × 2 factorial arrangement, blocked by day, repeated on 2 days.
• Factors:
  • DDGS levels: 0, 4, 8, 12, 16% (formulated into finisher broiler diet).
  • DTB levels: 0% or 0.25% (AZOMITE Feed Grit, a hydrated sodium calcium aluminosilicate).
• Experimental units: 10 treatment combinations per day (5 DDGS levels × 2 DTB levels) × 2 days, with day as the block.
• Each batch per day: 363 kg, representing the experimental unit; when 0.25% DTB was added, it replaced 0.25% of ground corn.
• Diets were created by blending two basal diets containing 0% DDGS and 16% DDGS to achieve equidistant DDGS levels across the five target levels (0, 4, 8, 12, 16%).
• Total diet quantity per treatment: 726 kg per day (two batches of 363 kg each).
• Pelleting setup: 4.0 × 35 mm (L/D ≈ 9) pelleting die (Model 1112-4, California Pellet Mill Co.).
• Warm-up: A diet with 8% DDGS used at the beginning of each day to warm up the pellet mill.
• Conditioning: steam conditioned at 82.2°C for 45 s of retention time.
• Pellet mill operation: motor load fixed at 40% to standardize throughput across treatments.
• Replacement rule: when DTB was included (0.25%), it replaced 0.25% of ground corn in the blend.

Diets and formulations

• Basal diet formulation: corn–soybean meal-based with either 0% or 16% DDGS (Table 1 in the source).
• Ingredient/proximate composition (selected highlights):
  • DDGS: moisture ~12.23%, crude protein ~27.63%, crude fat ~5.20%, crude fiber ~7.93%.
  • AMEn (apparent metabolizable energy, nitrogen-corrected): $AMEn \approx 3{,}185 \, kcal/kg$ for both 0% and 16% DDGS bases.
  • Nutritional comparisons: increasing DDGS typically lowers starch and increases fiber/lipid; can influence pelleting behavior due to matrix effects.
• Table 1 (basal diet formulations) shows the two DDGS levels (0% and 16%) with corresponding proportions of Corn, Soybean meal, DDGS, Soybean oil, minerals, vitamins, amino acids, and phytase to meet finisher diet requirements.
• Calculated analysis (per kg of diet):
  • Crude protein: CP \approx 16.83\% \text{(0% DDGS)} \rightarrow 17.48\% \text{(16% DDGS)}
  • Digestible lysine: ${\text{lys}} \approx 0.90\%$; Digestible methionine: ${\text{Met}} \approx 0.45\%$; Digestible TSAA: ${\text{TSAA}} \approx 0.68\%$
  • Calcium: ${\text{Ca}} \approx 0.76\%$; Available phosphorus: ${\text{Available P}} \approx 0.36\%$
• When DTB is included, 0.25% DTB replaces 0.25% of the corn in the diet (i.e., the DTB is substituted for corn).

Pelleting process and physical measurements

• Pelleting conditions and measurements:
  • Die: 4.0 × 35 mm (L/D ≈ 9).
  • Conditioning and moisture: steam conditioning at 82.2°C for 45 seconds retention.
  • Pellet production rate (throughput): measured as metric tons per hour (MT/h).
  • PDI (pellet durability index): measured by two methods:
  • Holmen NHP100 (Holmen PDI).
  • Tumbler method (Tumbler PDI).
  • PDI calculation: $PDI = \left(\frac{\text{weight after tumbling}}{\text{weight before tumbling}}\right) \times 100$
• Sampling and replication:
  • Sampling window: complete capture over a 60 s window, recorded every 150 s with 90 s between collections.
  • A total of 6 samples were collected every 3 minutes from each treatment during each manufacturing day.
  • Each whole collection sample served as a replicate for pellet production rate and durability measurements.
• Pre-experiment preparation:
  • Before test diets, an 8% DDGS diet was produced to warm up the mill.
  • The particle size of ground ingredients (for geometric mean diameter calculations) was measured by Ro-Tap sieve analysis (ASABE S319.4).
  • Particle sizes reported (by mass): ground corn ≈ 769 μm, soybean meal ≈ 1155 μm, DDGS ≈ 409 μm.
  • Geometric mean diameter by mass, D_{gw}, calculated from sieve fractions using the ASABE S319.4 method.

Particle size analysis and quality metrics

• Ro-Tap sieve analysis used 13 sieves (US standard numbers: 6, 8, 12, 16, 20, 30, 40, 50, 70, 100, 140, 200, 270 and pan).
• D_{gw} (geometric mean diameter by mass) calculated from retained fractions on sieves.
• PDI measured with Holmen NHP100 and with the tumbler method as described.

Statistical analysis

• Model: linear mixed model (SAS v9.4; Proc GLIMMIX) with fixed effects DTB, DDGS, and repeated measures nested within a treatment run within a production day.
• Blocking: day (2 days).
• Post hoc: Tukey multiple comparisons.
• Significance: P < 0.05; trends considered if 0.05 ≤ P < 0.10.

Results (Day 1 vs Day 2)

• Day 1 results:
  • Production rate showed a significant interaction between DDGS level and DTB (P = 0.010).
  • Diets containing 12% DDGS with 0.25% DTB had higher production rate than 0% and 4% DDGS with DTB, and higher than any 0% DTB diets across DDGS levels except 16% DDGS (which also yielded high production rate).
  • There was a linear increase in production rate with increasing DDGS level (P = 0.001).
  • Pellet durability index showed DTB had a positive main effect on PDI on day 1 (Holmen and tumbler methods showed improvements with DTB; exact values from the table indicate Holmen PDI improved and tumbler PDI improved modestly).
  • Increasing DDGS level positively influenced pellet quality, with Holmen PDI and tumbler PDI significantly higher as DDGS increased (P < 0.001 for both methods).
  • Summary observation: higher DDGS improved PDI on day 1, while DTB showed some positive effects on PDI, but effects varied by method.
• Day 2 results:
  • Interaction between DDGS and DTB for production rate was also significant (P < 0.001).
  • Diets with 4% and 8% DDGS plus 0.25% DTB exhibited higher production rates than their non-DTB counterparts and than 16% DDGS diets (with or without DTB).
  • DDGS had a quadratic effect on production rate (P = 0.001) with the highest production rate observed at 4% DDGS.
  • PDI results on day 2 showed DDGS had a strong influence on pellet durability: Holmen PDI was highest with 16% DDGS, and tumbler PDI was highest with 12% and 16% DDGS (P < 0.001 for DDGS effects).
  • Linear effects of DDGS on PDI were observed (Holmen and tumbler, P = 0.001).
  • Overall interpretation: the interaction between DDGS and DTB influenced production rate variably across days; DTB tended to improve production rate for some DDGS levels (notably 4–12%), while DDGS generally improved PDI in day 2 as well as day 1, with a stronger DDGS effect on quality than DTB in some cases.

Key observations and interpretation

• The pelleting system shows a complex, multifactorial response where DDGS characteristics (starch content, lipid level, fiber) and mineral abrasion from DTB can influence die surface interactions and pellet formation.
• The DTB effect is hypothesized to act by scouring the pellet mill die holes, reducing friction and enabling higher production rates, particularly when DDGS levels range from 4% to 12%.
• Day-to-day variability suggests processing order, batch size, environmental conditions, ingredient variability, and potential inventory differences (source batch/lot of DDGS) can influence outcomes.
• Previous literature shows mixed results for DDGS effects on pellet quality and production rate; this study confirms potential for DTB to mitigate DDGS-associated losses in production rate at specific DDGS levels (4–12%), but effects are not completely consistent across days.
• The sequence of diet manufacturing (ascending on day 1, then mixed ascending for no-DTB and descending for DTB on day 2) was purposeful to gauge DTB mitigation effects following DDGS exposure, though it introduces potential run-order biases.
• Implications for practice:
  • DTB may be a useful addition to pelleting formulations when DDGS inclusion is moderate (4–12%), potentially increasing production rate.
  • DDGS inclusion generally improved pellet durability index across days, albeit with some day-to-day variability.
  • Processing order, batch size, and diet sequencing should be considered in commercial pelleting when DDGS and DTB are used together.

Formulas and equations

• Pellet durability index (PDI) calculation (example):
  $PDI = \left(\frac{W<em>{after\ tumbling}}{W</em>{before\ tumbling}}\right) \times 100$
• Particle size metric:
  • Geometric mean diameter by mass: $D_{gw} = f(\text{particle size distribution by mass})$
  • The calculation follows ASABE S319.4 procedures (size distribution by mass across sieve stack).
• Energy and nutrient benchmarks (examples):
  • Apparent metabolizable energy (AMEn): $AMEn \approx 3{,}185\ \text{kcal/kg}$ (diet basis)
  • Digestible lysine, methionine, TSAA, calcium, and available phosphorus are given in the diet formulation table; values vary slightly with DDGS level.

Conclusions and practical takeaways

• Conclusions:
  1) Pellet quality was influenced by DTB and DDGS independently. DTB improved PDI on day 1 (Holmen ≈ 2.5% increase; tumbler ≈ 0.9% increase), but this effect did not consistently persist on day 2.
  2) Increasing DDGS levels linearly improved pellet durability index across the study, which contradicts some expectations from prior work (DDGS often reduces pellet quality). The positive DDGS effect on PDI was observed on both Holmen and tumbler measures.
  3) DTB shows potential to improve pellet production rate when DDGS inclusion is in the 4–12% range, though day-to-day results varied and not all outcomes were consistent across days/order of treatments.
  4) Sequencing and processing order, as well as batch size, appear to modulate DTB’s mitigating effect; future studies should explore serial-day designs with reduced treatment complexity to isolate run-order effects.
• Applications:
  • Pelleting operations could consider DTB inclusion to offset DDGS-induced production-rate declines for 4–12% DDGS in finisher diets.
  • DDGS can be used to improve pellet durability, but operators should monitor batch-to-batch variability and adjust conditioning temperature and die parameters accordingly.
• Limitations and future work:
  • The study observed day-to-day variability; results may depend on DDGS source variability, batch differences, and processing conditions.
  • Future research should examine sequencing effects with fewer treatments or in a fully randomized design, include different DTB dosages (e.g., 0.25%, 0.50%), and explore interactions with other processing variables (conditioning temperature, moisture, and particle size).

Ethics, disclosures, and references

• Disclosures: The authors declare no conflicts of interest.
• References (selected):
  • Behnke, K. (1981, 2007) on pellet mill performance and DDGS considerations.
  • Loar et al. (2010) on DDGS effects on pellet quality and production rate in broilers.
  • Tillman et al. (2020) on DTB mitigating effects with 8% DDGS.
  • Shim et al. (2011); Kim et al. (2018) on DDGS in broiler diets and pellet quality.
  • Wamsley et al. (2012, 2013) on inorganic phosphate and DDGS utilization in pelleting.
  • Spiehs et al. (2002) on DDGS composition variability.
  • Pedersen et al. (2014); Liu (2008); Kerr et al. (2013) on DDGS composition and particle size variability.

Note on terminology

• DDGS: Distillers dried grain with solubles.
• DTB: Dacitic tuff breccia (AZOMITE nutritional supplement for pelleting).
• PDI: Pellet durability index, measured by Holmen NHP100 and tumbler methods.
• D_{gw}: Geometric mean diameter by mass, derived from sieve analysis.
• AMEn: Apparent metabolizable energy, nitrogen-corrected.