PREDICTION OF LEAF-STEM RATIO IN GRASSES USING NEAR-INFRARED REFLECTANCE SPECTROSCOPY

Leaf:stem ratio of grass stands is an important factor affecting diet selection, quality, and forage intake. Estimates of leaf:stem ratios c ommonly are based on a labor intensive process of hand separating leaf and stem fractions. Near infrared reflectance spectroscopy (NIRS) has been used successfully to predict forage quality and botanical compos ition of vegetation samples. The objective of this study was to evalua te the use of NIBS to predict leaf:stem ratios in big bluestem (Androp ogon gerardii Vitman), switchgrass (Panicum virgatum L.), and smooth b romegrass (Bromus inermis Leyss.). A total of 72 hand-clipped samples of each species was taken from seeded monocultures in eastern Nebraska throughout the 1992, 1993, and 1994 growing seasons. Leaf:stem ratio was determined first.for each Sample and then the entire sample was gr ound. Samples were scanned by a Perstorp model 6500 near infrared scan ning monochromator. Three calibration equations were developed based o n using 18, 36, and 54 (1/4, 1/2, and 3/4 of total samples, respective ly) samples. These 3 calibration equations were used to determine the number of samples necessary to achieve an r(2) of 0.70 or higher for e ach data set. Big bluestem and switchgrass had coefficients of determi nation (r(2)) of less than or equal to 0.69 for all calibration equati ons except for the equation using only 18 samples of big bluestem r(2) = 0.60). Smooth bromegrass had a r(2) ranging from only 0.06 to 0.14 for the calibration equations regardless of the number of samples used . Near infrared reflectance spectroscopy was a rapid means of estimati ng leaf:stem ratios in monocultures of big bluestem and switchgrass bu t it was not suitable for smooth bromegrass.