Quality Prediction of Small Grain Forages by Near Infrared Reflectance Spectroscopy1

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Abstract
A paucity of information exists concerning the utility of near infrared reflectance spectroscopy (NIRS) for prediction of forage quality of annual forage crops and concerning the influence of environmental and plant factors on NIRS prediction equation development and use. Our objective was to ascertain whether NIRS can be relied upon to predict the quality of small grain crop forages at diverse maturation stages. We assayed five forage quality traits in a total of 700 forages comprised of up to four field replicates of two cultivars each of oats (Arena sativa L.), barley (Hordeum vulgate L.), spring wheat (Triticum aestivum L.), and triticale (Triticum durum Desf. ✕ Secale cereale L.) each harvested at six growth stages in two locations in years. Empirical quality prediction equations were obtained by multiple linear regression of known quality values on NIR values from 48 samples obtained from one replicate from one location in 1 year. A scanning monochromator NIR spectro‐computer system was used to develop the prediction equations and to validate them via tests of their applicability to the remaining 652 samples that were grown in other replicates or in other environments. From two to six wavelengths were needed to develop the best prediction equations for crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL) or in vitro digestible dry matter (IVDDM). The squared coefficients of multiple determination (R2) of the prediction equations ranged from 0.92 for IVDDM to 0.99 for CP. These calibration equations predicted the quality values for samples from other replicates, locations, and years within standard errors of ± 0.7 to 1.1% for CP, ± 1.8 to 2.3% for NDF, ± 1.0 to 1.6% for ADF, ± 0.3 to 0.4% for ADL, and ± 3.1 to 4.1% for IVDDM. We concluded that NIRS can evaluate forage quality of small grain crops to a degree of accuracy equivalent to or greater than that reported for perennial forage species, and that relative forage quality of small grain crops was adequately determined for several growth environments when prediction equations were developed from forages grown in a single environment.