NEAR-INFRARED REFLECTANCE ANALYSIS WITH SINGLE-PRODUCT AND MULTIPRODUCT CALIBRATIONS

Single-product calibrations for near infrared (NIR) spectrophotometers are normally developed for each type of material to achieve a high le vel of prediction accuracy. Developing multiproduct calibrations with thousands of samples was not practical with personal computers until r ecently. Advancements in software now make it possible to include thou sands of samples into multiproduct calibrations. This study was conduc ted to evaluate the accuracy of a multiproduct calibration consisting of forage samples. Large single-product files of hay and fresh forage, haylage, and small grain silage spectra were available for this study . Every sixth sample from each file was reserved to test calibration a ccuracy. Single-product calibrations were developed for each product a nd a multiproduct calibration was developed for all four products. The re was very little difference between the accuracy of the multiproduct calibration containing all samples and the single-product calibration s. In a second study, a multiproduct calibration developed from 756 ha ylage and small grain silage samples was used to predict the quality o f 100 hay samples. The prediction error was found to be unsatisfactory , so 50, 100, 166, and 500 hay samples were added to the multiproduct calibration file to see if the hay prediction errors could be improved . The expanded multiproduct calibration was more accurate than a custo m single-product hay calibration when < 150 hay samples were available to develop a custom calibration or expand the multiproduct calibratio n. This suggests that if only a few samples are available, it may be m ore cost-effective to expand a similar product library and recalibrate than to gather a large number of samples for a new calibration.