Abstract
Pasture nutritive value is economically important in south-eastern Australian dairy production systems, yet measurement of nutritive characteristics in pasture cultivar evaluation trials is not routinely undertaken, primarily due to cost. An approach aiming to reduce the total laboratory analysis costs in multi-harvest field trials by testing some entries as composite samples is provided. A field trial evaluating 31 trial entries sown in 4 replicates was used. On nine harvest occasions, samples were collected from each plot, dried, ground and analysed using near infrared spectroscopy for key nutritive characteristics (metabolisable energy (ME), crude protein (CP) and neutral detergent fibre (NDF)). Additionally, composite samples of 17 of the 31 entries from each harvest were created by combining sub-samples of material from each of four replicate plots into a single sample that was also analysed. A linear mixed model (LMM) analysis accounting for spatial and temporal variation as well as spatial and temporal correlations was conducted, comparing the full data model where all plots at all harvests were tested individually to a data model where some entries were evaluated as individual plots and others as composites. The precision and accuracy of the estimates for the two models were similar and best linear unbiased prediction (BLUP) means of the composite sampling strategy model were comparable to the full data model. It was concluded that if composite sampling is used in conjunction with testing samples from individual plots on a selection of cultivars, statistically valid inferences are possible and the total cost of determining the nutritive characteristics of perennial ryegrass cultivars in field trials can be reduced.
Highlights
Perennial ryegrass (Lolium perenne L.) underpins the “home grown” forage supply on dairy farms in south-eastern Australia, with farmers able to choose from more than 60 commercially available cultivars [1]
Average estimated Metabolisable energy (ME) in the full data model was 0.18 and 0.08 MJ ME/kg DM higher than the composite data model (CDM) and single data model (SDM), respectively
Trial entry variance was smaller in the SDM and CDM compared to the full data model (FDM) for each nutritive characteristic (Table 2)
Summary
Perennial ryegrass (Lolium perenne L.) underpins the “home grown” forage supply on dairy farms in south-eastern Australia, with farmers able to choose from more than 60 commercially available cultivars [1]. The relative merit of these cultivars is routinely assessed in small plot trials managed by pasture seed companies and industry groups These trials measure forage mass (kg DM/ha) at a sequence of harvests throughout the year; they do not routinely measure the nutritive characteristics of the cultivars, despite them being economically important in pasture-based dairy production systems. Analysis of nutritive characteristics can be laborious and costly when there are many samples to test over multiple harvests/grazings and years, such as the case in perennial ryegrass cultivar evaluation trials These trials commonly test around 30 cultivars of perennial ryegrass in a replicated (row-column) design, with current industry protocols specifying the use of four replicates for the determination of forage mass [3].
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