PREDICTION OF THE IN-VITRO GAS-PRODUCTION DYNAMICS OF KIKUYU GRASS BYNEAR-INFRARED REFLECTANCE SPECTROSCOPY USING SPECTRALLY-STRUCTURED SAMPLE-POPULATIONS

A study was carried out to test: (1) if the prediction of in vitro gas production of kikuyu grass (Pennisetum clandestinum) samples by near- infrared reflectance spectroscopy (NIRS) could be improved by the use of a spectrally-structured sample population; and (2) if the parameter s from exponential models used to describe the kinetics of gas product ion could be calibrated by NIRS. Forty-one kikuyu grass samples (calib ration set) were chosen out of a total of 288 on the basis of their sp ectral characteristics as representative samples of the whole sample p opulation. Measurements of cumulative in vitro gas production were rec orded at 3, 6, 12, 24, 48, 72 and 96 h. Spectra were transformed with 1st, 2nd or 3rd derivative mathematical treatments. NIRS calibration e quations were derived for in vitro gas production, with or without sca tter correction for particle size using modified partial least squares . The equations were validated using a set of 48 samples previously ch osen at random from the total sample population (validation set). Sati sfactory calibrations and cross-validations were obtained for all the static measurements of gas production (R-2 = 0.77-0.86 (S.E. 0.48-2.06 ) and 0.74-0.82 (S.E. 0.50-2.18), for the gas volumes from 3 to 96 h, respectively), and the use of a spectrally-structure population improv ed the calibration and cross-validation statistics of the MRS equation s. However, when three exponential models were fitted to the gas produ ction data. only the asymptote values could be satisfactorily calibrat ed or cross-validated. When the NIRS equations were used in the valida tion set, the static gas volumes were predicted with R-2 values betwee n 0.60 and 0.71 (S.E. 0.65 to 3.83, for the gas volumes from 3 to 96 h ). These results were less accurate than within the calibration set, b ut they were still better than when the parameters from the exponentia l models were fitted. The results suggested that the calibration of st atic gas volumes is a more promising alternative than to fit specific parameters of kinetic fermentation models by NIRS. (C) 1997 Elsevier S cience B.V.