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Simple Summary: Mitigating methane emissions from ruminants requires strategies that are sustainable and acceptable to both consumers and producers. Direct-fed microbials could meet these requirements. Forty Holstein-Friesian cows were randomly allocated one of two treatments, a control or control plus a direct-fed microbial (MYLO®—a mixture of Lactobacillus species; Terragen Biotech Pty Ltd., Coolum Beach, Queensland, Australia). Adding the direct-fed microbial had no significant effect on feed intake, milk yield, feed conversion efficiency, or methane parameters. While these results are contrary to our expectations, all were numerically in a favorable direction. Given there are reports that diet and dose rate may impact the size of any effect, we recommend a dose–response study be undertaken using a basal diet that is commonly used in pasture-based dairy systems. Using direct-fed microbials to mitigate enteric methane emissions could be sustainable and acceptable to both consumers and producers. Forty lactating, multiparous, Holstein-Friesian cows were randomly allocated one of two treatments: (1) a base of ad libitum vetch (Vicia sativa) hay and 7.0 kg DM/d of a grain mix, or (2) the basal diet plus 10 mL of MYLO® (Terragen Biotech Pty Ltd., Coolum Beach, Queensland, Australia) delivering 4.17 × 108 cfu of Lactobacillus per mL. Neither feed intake (25.4 kg/d vs. 24.8 kg/d) nor milk yield (29.9 vs. 30.3 kg/d) were affected by treatment. Feed conversion efficiency was not affected by treatment when expressed on an energy-corrected milk basis (1.15 vs. 1.18 kg/kg DMI). Neither methane yield (31.6 vs. 31.1 g/kg DMI) nor methane intensity (27.1 vs. 25.2 g/kg energy corrected milk) were affected by treatments. While these results are contrary to our expectations and not significant, all were numerically in a favorable direction. Given there are reports that diet and dose rate may impact the size of any effect, we recommend a dose–response study be undertaken using a basal diet that is commonly used in pasture-based dairy systems. [ABSTRACT FROM AUTHOR]

Attract and kill (A&K) is an effective control technique for Carpophilus spp. attacking stone fruit but high cost has limited its adoption by growers. Field experiments during two successive growing seasons evaluated the potential to reduce the spatial density of A&K traps from three traps per ha (3 A&K) to two traps per ha (2 A&K), against medium to low beetle populations. Fruit damage in 2 A&K and 3 A&K treated blocks was significantly lower than in pesticide-treated control blocks. However there were no significant differences in blocks treated with either 2 A&K or 3 A&K traps in either season. The results suggest that the number of traps per ha can be reduced without reducing the efficacy of the A&K treatment where Carpophilus population levels are medium to low. [ABSTRACT FROM AUTHOR]

Field longevity of synthetic lures for Carpophilus spp. (Coleoptera: Nitidulidae) was evaluated by trapping studies in Australia, accompanied by chemical analyses. Carpophilus spp. are serious pests of ripening fruits, and an attract-and-kill method has been developed for their control. Traps are baited with one of two types of lure: synthetic pheromone (in rubber septa) and a host-related synthetic co-attractant (as an aqueous solution). No information was available on the longevity of either lure type. The objective of the study was to understand changes in attractiveness of the pheromone septa and co-attractant over time under field conditions. Pheromone septa were still attractive after 28 days in the field, but activity declined over time. Relative to fresh septa, catches in traps baited only with the pheromone declined to 75, 53, 32, 21, and 16% for 3-, 7-, 14-, 21-, and 28-day-old septa, respectively. Chemical emissions from aged septa showed a very similar decrease with time. Trap catches when both pheromone and co-attractant were present were far higher, and the decrease as the pheromone aged was less rapid (catches were 87, 73, 55, 44, and 36% of the original level for 3-, 7-, 14-, 21-, and 28-day-old septa, respectively). Apparently the presence of co-attractant could partially compensate for the deterioration of pheromone septa. The chemical changes of the co-attractant decreased more rapidly than the pheromone. In a laboratory study, two minor components (acetaldehyde and ethyl acetate) were essentially gone after 1 day, while the major component (ethanol) and the other three minor components (2-methyl-1-propanol, 3-methyl-1-butanol, and 2-methyl-1-butanol) were detectable for up to 4–8 days. Co-attractant evaporation was somewhat slower under field conditions. Trap catches for co-attractant of various ages and pheromones decreased three-fold as co-attractant age increased from 0 to 14 days. Implications with respect to beetle control are discussed. [ABSTRACT FROM AUTHOR]

• Accurate seasonal predictions of ryegrass cultivar DM yields using LMMs. • Base AR 37 and Bealy NEA2 were the best performing cultivars based on annual ranking. • Seasonal variability was found to be larger than genotypic variability. • An antedependence of order 3 was the best residual covariance structure for harvests. With over 60 commercial perennial ryegrass cultivars available on the market in Australia, selecting cultivars with high dry matter (DM) yield and economic profitability requires accurate estimates of their DM yield across target environments. This study, using data from multi-environment multi-harvest (MEMH) trials conducted in south-eastern Australia, derived accurate seasonal predictions of DM yield of these cultivars using linear mixed models (LMM). Base AR37 and Bealy NEA2 were found to be the best performing cultivars in most of the seasons in the target south-eastern Australian environments. Seasonal variability was found to be larger than genotypic variability as usually is the case in multi-environment trials. We have provided details of the LMM methodology used, along with ASReml-R code, to enable others to apply it in similar studies with appropriate changes as required for dataset used. The statistical theory underlying this methodology has also been briefly described in an Appendix for interested readers. [ABSTRACT FROM AUTHOR]