Search

Autumn grazing management aims to accumulate herbage for defoliation prior to a decrease in growth rates for the extension of the grazing season. The current study investigated the impact of building different target herbage masses (THMs) in autumn and imposing one of three different defoliation dates (DDs) between mid-October and late November on light transmitted to the base of the sward, free leaf lamina (FLL), leaf stage and internode elongation. Four THMs (low, medium, high and very high) and three DDs (DD1—15 October, DD2—7 November and DD3—21 November) were assigned to a 4 × 3 split plot design over two years. Light transmitted to the base of the sward was greatest in the low THM and decreased in all other THMs. Internode elongation increased in tillers in the medium to the very high THMs. Defoliation of the medium, high and, in particular, the very high THMs earlier in autumn reduced the effect of decreased light transmission on internode elongation. This study highlights that, as light transmitted to the base of the sward decreases, internode elongation increases, and this could negatively impact sward structure. [ABSTRACT FROM AUTHOR]

This study focuses on calibrating and validating models for hyperspectral canopy reflectance data that are useful to predict the nutritive value of ryegrass-white clover mixed herbage available to the grazing cow. Hyperspectral measurements and herbage cuts were collected from 286 sampling plots from a dairy farm from July 2017 to May 2018. Hyperspectral data were pre-treated by applying a Savitzky-Golay filter followed by a Gap-segment derivative algorithm. Herbage samples were analyzed for determination of herbage nutritive value traits, digestible organic matter in dry matter (DOMD), metabolizable energy (ME), crude protein (CP), neutral detergent fiber (NDF) and acid detergent fiber (ADF). Partial least squares regression was performed to calibrate the spectra against the five nutritive value traits. Results indicate that accuracy was moderately high for the CP model (R2 = 0.78) and moderate for the DOMD, ME, NDF and ADF models (0.54 < R2 < 0.67). The possibility of being able to use proximal sensing for the estimation of herbage nutritive value in the field could potentially contribute to more efficient grazing management with potential economic benefits for the farm business. [ABSTRACT FROM AUTHOR]