Near-infrared spectroscopy on chopper to measure maize forage quality parameters online

Improving maize (Zea mays L.) forage yield and quality is a major goal for corn breeders in northern Europe. The objective of this research was to measure maize forage dry matter (DM) content and quality parameters with near-infrared spectroscopy (NIRS) directly on a harvesting machine. Coupling NIRS with harvesting eliminates time-consuming sample preparation and laboratory-based analyses. Calibrations were developed with 281 samples from the 1998-1999 growing seasons using a diode array spectrometer mounted on a forage chopper. Standard errors of cross-validation (SECVs) were 11.8 g kg(-1) for DM, 23.6 g kg(-1) for starch, 19.2 g kg(-1) for in vitro digestibility, and 13.8 g kg(-1) for soluble sugars. An independent validation study with 159 samples from the 2000 harvest resulted in standard errors of prediction (SEP) of 12.5 g kg(-1) for DM, 22.1 g kg(-1) for starch, 19.8 g kg(-1) for in vitro digestibility, and 16.7 g kg(-1) for soluble sugars. The results indicate that NIRS on chopper (NOC) can determine DM accurately, rank hybrids for starch plus sugars, and group for in vitro digestibility. Dry matter NIRS determinations were more precise than the reference method, enabling improved selection for forage yield, the key factor in product development. Instrument standardization could be achieved through spectral matching and including spectra from different instruments into the calibration database. Approximately 10 000 and 16 000 plots were analyzed by the fully automated NOC system during 2000 and 2001. The dramatic increase in the number of plots analyzed expedites development of new maize forage products.