The objectives of this study were to determine in vitro dry matter and energy utilization of hatchery waste products and to confirm whether in vivo energy digestibility of hatchery waste products could be estimated using in vitro data. Two in vitro assays were conducted for infertile eggs, unhatched eggs, culled chicks, and a mixture(20% dried infertile eggs, 20% dried unhatched eggs, and 60% dried culled chicks). In Exp.1, in vitro dry matter disappearance (IVDMD) of hatchery waste products was determined. In Exp.2, in vitro energy disappearance (IVED) was determined using undigested residues from Exp.1. The IVDMD of infertile eggs, unhatched eggs, culled chicks, and the mixture were 81.7, 88.7, 83.9, and 85.4%, respectively. The IVED of the test ingredients were 74.4, 85.1, 77.6, and 79.8%, respectively. Both IVDMD and IVED were greater in unhatched eggs compared with infertile eggs and culled chicks (p<0.05). In vivo energy digestibility was estimated well using prediction equations for hatchery waste products developed in the present study: In vivo energy digestibility(%) = 2.52 × IVDMD (%) – 133.95 with r2 = 0.70 and in vivo energy digestibility(%) = 1.63 × IVED(%) – 50.03 with r2 = 0.67. In conclusion, energy utilization of unhatched eggs was the greatest among test ingredients and energy utilization of hatchery waste products can be estimated using data from in vitro procedures.

This work was conducted to assess the use of Near-infrared reflectance spectroscopy (NIRS) as a technique to analyze nutritional constituents of Distillers dried grain with solubles (DDGS) and corn quickly and accurately, and to apply an NIRS-based indium gallium arsenide array detector, rather than a NIRS-based scanning system, to collect spectra and induce and analyze calibration equations using equipment which is better suited to field application. As a technique to induce calibration equations, Partial Least Squares (PLS) was used, and for better accuracy, various mathematical transformations were applied. A multivariate outlier detection method was applied to induce calibration equations, and, as a result, the way of structuring a calibration set significantly affected prediction accuracy. The prediction of nutritional constituents of distillers dried grains with solubles resulted in the following: moisture (R2=0.80), crude protein (R2=0.71), crude fat (R2=0.80), crude fiber (R2=0.32), and crude ash (R2=0.72). All constituents except crude fiber showed good results. The prediction of nutritional constituents of corn resulted in the following: moisture (R2=0.79), crude protein (R2=0.61), crude fat (R2=0.79), crude fiber (R2=0.63), and crude ash (R2=0.75). Therefore, all constituents except for crude fat and crude fiber were predicted for their chemical composition of DDGS and corn through Near-infrared reflectance spectroscopy.