Metabolizable energy value of porcine meat and bone meal for broiler chickens

OA Bolarinwa, OA Olukosi, O Adeola

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

308 broiler chickens at 14 d post-hatch were used in a 7-d experiment to determine the metabolizable energy (ME) value of two meat and bone meal (MBM) samples. Three hundred and thirty-six broiler chickens were grouped by weight into eight blocks of seven cages with six birds per cage. The seven diets consisted of a corn-soybean meal reference diet formulated to meet the NRC (1994) requirement, and six test diets. The reference diet contained four energy sources namely corn, soybean meal, corn starch and soy oil. In the test diets, each of the two MBM samples were added to the reference diet at 30, 60 or 90 g kg 1 diet to partly replace the energy sources such that the ratio of the energy sources to one another was kept constant in all the diets. The ME and nitrogen-corrected ME (MEn) of the MBM samples were determined by the regression method in which the MBM contribution to ME, and MEn of the diets, in kilocalories, were regressed against the amount of MBM intake in grams. Gross energy of MBM1 and MBM2 were 4247 and 4697 kcal kg 1 DM, respectively. The crude protein, ash, and crude fat contents for MBM1 or MBM2 were 567 or 594, 264 or 211, and 106 or 116 g kg 1 DM. Addition of MBM linearly decreased (PB0.05) ileal nitrogen digestibility, total tract utilization of DM, energy and nitrogen as well as ME and MEn of the diets. In conclusion, the respective ME and MEn values were 2512 and 2345 kcal kg 1 DM for MBM1, and 2711 and 2127 kcal kg 1 DM for MBM2; thus MBM can be included in the diets of broiler chickens at less than 10% to provide energy.
Original languageEnglish
Pages (from-to)73 - 78
Number of pages6
JournalCanadian Journal of Animal Science
Volume91
Publication statusFirst published - 2012

Bibliographical note

2063344

Keywords

  • Broiler chickens
  • Meat and bone meal
  • Metabolizable energy
  • Regression method

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