|Cosgrove, G - NCSU|
|Mueller, J - NORTH CAROLINA STATE UNIV|
|Pond, K - NORTH CAROLINA STATE UNIV|
Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 4, 1993
Publication Date: N/A
Interpretive Summary: This information is useful for scientists working with the diet for grazing animals. It shows that the technology provided by near infrared reflective spectrocopy (NIRS) can be used to predict the nutritive value of the animal's diet after samples were freeze-dried and ground. The use of NIRS removes the analytical aspect of the research from being the limiting factor because the general equation from all forage species was acceptable. This means that only about 100 samples need to be analyzed to predict a large number. The limitation to such research resides with the collection aspect vs. analytical analyses.
Technical Abstract: Masticated forage provides information relation to the quality and fractionation characteristics of a ruminant's diet. This study reports the use of near infrared reflectance spectroscopy (NIRS) to predict the in vitro dry matter disappearance (IVDMD), in vitro organic matter disappearance (IVOMD) and cell-wall concentrations of particle size fractions and the whole masticate of temperate forages. Esophageal extrusa samples, with saliva retained, were obtained from fistulated steers intermittently grazing tall fescue (Festuca arundinacea Schreb.), orchardgrass (Dactylis glomerata L.) and ryegrass (Lolium perenne L.). Grazing was initiated at canopy heights of 100, 200 and 300 mm during spring and fall of two consecutive years. Samples were collected at the start of grazing at each canopy height (T1) and after defoliation to a 50-mm residue (T2). Masticates, quick-frozen in liquid N2, were subsequently lyophilized and dry-sieved into seven particle size fractions and, along with a whole-masticate subsample, were scanned for NIRS analyses. A single broad-based calibration encompassing all experimental factors predicted quality constituents within acceptable limits of precision for this methodology. Standard errors of cross-validation (SECV) were 6 g/kg for organic matter.