Prediction of leaf:stem ratio in grasses using near infrared reflectance spectroscopy

Abstract

Leaf:stem ratio of grass stands is an important factor affecting diet selection, quality, and forage intake. Estimates of leaf:stem ratios commonly 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 composition of vegetation samples. The objective of this study was to evaluate the use of NIRS to predict leaf:stem ratios in big bluestem (Andropogon gerardii Vitman), switchgrass (Panicum virgatum L.), and smooth bromegrass (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 ground. Samples were scanned by a Perstorp model 6500 near infrared scanning monochromator. Three calibration equations were developed based on using 18, 36, and 54 (1/4, 1/2, and 3/4 of total samples, respectively) samples. These 3 calibration equations were used to determine the number of samples necessary to achieve an r2 of 0.70 or higher for each data set. Big bluestem and switchgrass had coefficients of determination (r2) of less than or greater than 0.69 for all calibration equations except for the equation using only 18 samples of big bluestem r2 = 0.60). Smooth bromegrass had a r2 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 estimating leaf:stem ratios in monocultures of big bluestem and switchgrass but it was not suitable for smooth bromegrass.