Near infrared reflectance (NIR) spectroscopy is a rapid and cost-effective method for the measurement of organic constituents of agricultural products. NIR is widely used to measure feed quality around the world and is gaining acceptance in Australia. This study describes the development of an NIR calibration to measure crude protein (CP), predicted in vivo dry matter digestibility (IVDMD) and neutral detergent fibre (NDF) in temperate pasture species grown in south-western Victoria. A subset of 116 samples was selected on the basis of spectral characteristics from 461 pasture samples grown in 1987-89. Several grass and legume species were present in the population. Stepwise multiple linear regression analysis was used on the 116 samples to develop calibration equations with standard errors of 0.8,2.3 and 2.2% for CP, NDF and IVDMD, respectively. When these equations were tested on 2 independent pasture populations, a significant bias existed between NIR and reference values for 2 constituents in each population, indicating that the calibration samples did not adequately represent the new populations for these constituents. The results also showed that the H statistic alone was inadequate as an indicator of equation performance. It was confirmed that it was possible to develop a broad-based calibration to measure accurately the nutritive value of closed populations of temperate pasture species. For the resulting equations to be used for analysis of other populations, however, they must be monitored by comparing reference and NIR analyses on a small number of samples to check for the presence of bias or a significant increase in unexplained error.

Near infrared reflectance spectroscopy (NIR) was used to develop calibration equations to measure the magnesium concentration in perennial ryegrass herbage (Lolium perenne). A subset of 72 samples was selected on the basis of spectral variation from 400 samples grown in 1988-1989. Three alternative equations were chosen using stepwise multiple linear regression, with standard errors ranging from 0.4 to 0.3 g/kg DM with corresponding squared multiple correlation coefficients ( R2) of 0.68 to 0.82. The equations had 2, 4 and 4 wavelength terms respectively. When these equations were tested on an independent population of perennial ryegrass samples, a significant bias existed when using the 4 term equations but there was no bias when the 2 term equation was used. We conclude that NIR can be used to screen large numbers of perennial ryegrass plants for magnesium concentration. However, for the calibration equations to be used for the analysis of other populations equation performance must be monitored by comparing reference and NIR analyses on a small number of samples.

Summary. The suitability of near infrared reflectance (NIR) spectroscopy for predicting the concentration of several quality traits in samples of annual ryegrass (Lolium rigidum Gaud.) herbage was assessed in 2 separate experiments. In the first experiment, NIR calibration equations were developed for 6 traits (water-soluble carbohydrates, dry matter digestibility, neutral detergent solubles, neutral detergent solubles digestibility, neutral detergent fibre digestibility and nitrogen) using 4 calibration methods. No significant differences were found in the accuracy of NIR equations developed using either stepwise multiple linear regression (SMLR) or partial least squares regression (PLS) techniques when the equations were used to predict the concentration of constituents in those samples not used during the calibration process. The process of removing samples identified by the computer as spectral outliers was found to improve those statistics that related NIR data to the reference data of the samples used during calibration development (i.e. improved the goodness of fit of the regressions). However, when the resulting equations were used on all of the samples there was no improvement in the accuracy of the prediction of composition, and the estimates were less accurate for 2 of the equations. In the second experiment, plant part-specific equations (leaf blade, stem and leaf sheath) were developed. The specific equations were found to be no more accurate than those developed using a subset of all samples when used to analyse samples of the same plant part. However, using equations developed on either stem or leaf sheath samples to predict the composition of leaf blade samples led to inaccurate estimates of composition, illustrating the potential for error when NIR calibration equations are used on dissimilar samples. The similarity of the NIR estimates of decline in nutritive value and those obtained using reference analyses was illustrated by plotting the actual and predicted decline in nutritive value. The results of the experiments in this paper illustrate the need to monitor the accuracy of any NIR prediction of nutritive value. Striving for very low standard errors of calibration either by eliminating outliers or by limiting the plant tissues used during calibration did not lead to more accurate predictions of the composition of samples other than those used during the calibration process.

The phenotypic variation of 10 important botanical traits and 2 traits related to herbage quality was measured in tall wheatgrass (Thinopyrum elongatum) cv. Tyrrell. Five certified lines of Tyrrell were compared among themselves and with cvv. Largo and San Jose. Significant differences, both between cultivars and within lines of Tyrrell, were observed for several traits. The phenotypic variability measured confirms that Tyrrell is distinct from its progenitor, Largo, and has sufficient variability to make it suitable for use in a selection program. In a second experiment, from November 1990 to February 1993, the yield and nutritive value of Tyrrell, Largo, and San Jose were compared with perennial ryegrass (Lolium perenne) cv. Ellett and tall fescue (Festuca arundinacea) cv. Demeter. There were no differences (P>0.05) between cultivars for either total dry matter yield or total yield of digestible dry matter. Seasonal differences in growth and nutritive value were observed. Ellett showed superior growth in winter and early spring, while tall wheatgrass and Demeter were more summer-active. In 6 of the 11 harvests measured for nutritive value, there were no differences (P>0.05) between treatments for yield of digestible dry matter; for 2 of the remaining 5 harvests, Tyrrell yielded more digestible dry matter than Ellett. Dry matter digestibility of tall wheatgrass did not fall below 60%. The results suggest that with appropriate management, tall wheatgrass can produce nutritious forage in quantities sufficient for animal production systems, particularly as a special purpose summer pasture.

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