Predicting the digestible energy of corn determined with growing swine from nutrient composition and cross-species measurements

B. Smith, A. Hassen, M. Hinds, D. Rice, D. Jones, T. Sauber, C. Iiams, D. Sevenich, R. Allen, F. Owens, J. McNaughton, C. Parsons

Research output: Contribution to journalArticlepeer-review


The DE values of corn grain for pigs will differ among corn sources. More accurate prediction of DE may improve diet formulation and reduce diet cost. Corn grain sources (n = 83) were assayed with growing swine (20 kg) in DE experiments with total collection of feces, with 3-wk-old broiler chick in nitrogen-corrected apparent ME (AMEN) trials and with cecectomized adult roosters in nitrogen-corrected true ME (TMEN) studies. Additional AMEN data for the corn grain source set was generated based on an existing near-infrared transmittance prediction model (nearinfrared transmittance-predicted AMEN [NIT-AMEN]). Corn source nutrient composition was determined by wet chemistry methods. These data were then used to 1) test the accuracy of predicting swine DE of individual corn sources based on available literature equations and nutrient composition and 2) develop models for predicting DE of sources from nutrient composition and the cross-species information gathered above (AMEN, NIT-AMEN, and TMEN). The overall measured DE, AMEN, NIT-AMEN, and TMEN values were 4,105 ± 11, 4,006 ± 10, 4,004 ± 10, and 4,086 ± 12 kcal/kg DM, respectively. Prediction models were developed using 80% of the corn grain sources; the remaining 20% was reserved for validation of the developed prediction equation. Literature equations based on nutrient composition proved imprecise for predicting corn DE; the root mean square error of prediction ranged from 105 to 331 kcal/kg, an equivalent of 2.6 to 8.8% error. Yet among the corn composition traits, 4-variable models developed in the current study provided adequate prediction of DE (model R2 ranging from 0.76 to 0.79 and root mean square error [RMSE] of 50 kcal/kg). When prediction equations were tested using the validation set, these models had a 1 to 1.2% error of prediction. Simple linear equations from AMEN, NIT-AMEN, or TMEN provided an accurate prediction of DE for individual sources (R2 ranged from 0.65 to 0.73 and RMSE ranged from 50 to 61 kcal/kg). Percentage error of prediction based on the validation data set was greater (1.4%) for the TMEN model than for the NIT-AMEN or AMEN models (1 and 1.2%, respectively), indicating that swine DE values could be accurately predicted by using AMEN or NIT-AMEN. In conclusion, regression equations developed from broiler measurements or from analyzed nutrient composition proved adequate to reliably predict the DE of commercially available corn hybrids for growing pigs.

Original languageEnglish (US)
Pages (from-to)1025-1038
Number of pages14
JournalJournal of animal science
Issue number3
StatePublished - Mar 31 2015


  • Broilers
  • Corn grain
  • Digestible energy
  • Pigs
  • Prediction modeling
  • Roosters

ASJC Scopus subject areas

  • Food Science
  • Animal Science and Zoology
  • Genetics


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