@conference {41853,
	title = {Digestion kinetics of New Zealand native flax},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {65},
	year = {2005},
	month = {Jan},
	pages = {367-371},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	address = {Christchurch},
	abstract = {This experiment compares the nutritive value of New Zealand native flax, Phormium tenax, by-products i.e. leaves (L), butts (B), thrash-stripped fibre (F) and green matter (G), with white clover (WC) via digestion kinetics derived from in vitro and in sacco incubations. The WC had a high nutritive quality (11.1 MJME/kg DM, CP 28\% DM), G a moderate (10.1 MJME/kg DM, CP 9\% DM), and L, B, F were of very low nutritive quality (< 8 MJME/kg DM, CP < 6 \% DM). After 24 hours, 96, 76, 47, 47, and 30 \% of the DM was degraded for WC, G, L, B and F, respectively (P < 0.001). The degradation rates (\%/h) of digestible DM were faster (P < 0.001) for WC (13) and G (11) than B (3.8), L (4.6) and F (2.7). Flax by-products had a net loss of ammonia after 2 (B), 4 (F and L) and 8 hours (G). The proportion of DM converted to VFA by 8 hours was 21 \%, and 14 \% for WC and G respectively, but only 9-10 \% for the other flax by-products (P < 0.001). The feeding model BestFeed{\texttrademark} predicted that G could grow a 500 kg bull at 0.8 kg/day and had potential as a supplement for pasture-fed animals.
KEYWORDS: flax; Phormium tenax; in sacco; in vitro; digestion kinetics; nutritive value; forage ration, BestFeed. },
	issn = {1176-5283},
	author = {Litherland AJ and Layton DL and Burke JL and Corson DC and Peters JS}
}
@conference {41051,
	title = {The determination of sulphur in wool using near infrared reflectance spectrometry},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {58},
	year = {1998},
	month = {Jan},
	pages = {281-283},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	abstract = {A method and calibration for estimating sulphur (S) concentration in wool using near infrared reflectance spectrometry (NIRS) is described. The NIRS measurements were calibrated against wet chemistry determinations of wool S (R{\texttwosuperior} = 0.81, relative standard error {\textpm} 3.7\%, n=339). The first derivative spectra with 14 partial least squares terms gave the lowest cross-validation error for the calibration using an independent set of wool samples (R{\texttwosuperior} = 0.78, cross-validation error {\textpm} 0.11, n=66, mean 2.88 g S/100g wool). The correlation spectrum gave a series of approximately equally weighted peaks from about 1300 - 2400 nm, corresponding to -NH stretching and bending modes (protein). The -SH absorption between 1736 and 1746 nm could also be identified. Although scouring differences contributed to marked spectral differences in the visible region (yellowness was related to the first 3 principal component scores) these did not affect the overall S calibration. Uses for the calibration include wool S as an indicator of lifetime wool production, changes in wool composition in response to supplemented cysteine or energy intake, and the relationship between wool S and wool characteristics. },
	issn = {1176-5283},
	author = {Corson DC and Martin W and Lee J}
}
@conference {40977,
	title = {Sampling strategy for estimating dairy-pasture quality},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {58},
	year = {1998},
	month = {Jan},
	pages = {25-28},
	publisher = {New Zealand Society of Animal Production},
	organization = {New Zealand Society of Animal Production},
	abstract = {Rapid determination of pasture quality using near infrared reflectance spectroscopy (NIRS) makes it feasible for farmers to
incorporate forage composition in feed budgeting and feed supplementation decisions for grazing animals.  In grazed pastures,
heterogeneity in the distribution of the mass and quality, necessitates a sampling strategy to accurately predict the diet. A single paddock
was systematically sampled by selecting 60 sites according to a pre-determined grid. At 12 of these sites, 4 separate but adjacent samples
of 150 x 150 mm were taken from within a 300 x 300 mm quadrat. To characterise vertical heterogeneity, the herbage at each of the
60 sites was cut sequentially into 4 equal strata, the depth of each being one-quarter of the canopy surface height at that site. These
samples were used to derive a statistically-based 3-dimensional characterisation of variability of herbage mass and of several
parameters of herbage quality determined using NIRS. This description was used to calculate the number of samples necessary to
estimate parameters to arbitary, pre-determined levels of accuracy of {\textpm} 50 kg DM/ha for herbage mass in each stratum, {\textpm} 50 g/kg protein
(PROT), acid detergent and neutral detergent fibre (ADF; NDF), {\textpm} 20 g/kg for soluble carbohydrate (CARB), {\textpm} 25 g/kg for in-vitro
dry matter digestibility (DIG) and {\textpm} 0.5 MJ/kg for metabolizable energy (ME). A minimum of six samples bulked together is necessary
to estimate PROT, CARB, NDF and ADF to the specified level of accuracy, and this number was similar for each stratum. Twelve
samples are required to estimate ME and DIG for each of the 3 upper strata, but in the lowest stratum with greater variability, 48 and
19 samples would be required for ME and DIG, respectively, to reach the same accuracy. A sampling strategy should take the suggested
number of samples by systematically covering the paddock area. Uncertainty in the depth of sampling because of the necessity to sample
before grazing has little effect on the number of samples required or on the accuracy of estimates, providing the lowest stratum is not
penetrated during either sampling or grazing.},
	issn = {1176-5283},
	author = {Cosgrove GP and Betteridge K and Thomas VJ and Corson DC}
}
