The Effect of Silica and Manure Addition into Suppressive and Conducive Soil on the Incidence of Fusarium Wilt Disease of Banana

Fusarium wilt, caused by Fusarium oxysporum f. sp. cubense (Foc), is one of the most destructive diseases of banana. One potential method to manage fusarium wilt of banana is by manipulating the nutrient status in the soil. This study was conducted to determine the quality of Foc suppressive and conducive soil, the influence of soil application of silica and manure on the incidence of fusarium wilt of banana. Surveys were conducted in five banana plantations in three provinces in Indonesia: Lampung-Sumatra, West Java and Central Java. From the five locations, one location (Sala-man-Central Java) was heavily infected by Foc, another location (NTF Lampung-Sumatera) was slightly infected by Foc, while the rest (Sarampad-West Java, Talaga-West Java and GGP Lampung-Sumatra) were healthy banana plantations without Foc infection. Labile carbon analysis showed that the Foc suppressive soil had greater labile carbon content than conducive soil. Also, the analysis of fluorescein diacetate hydrolysis (FDA) and ?-glucosidase showed greater microbial activity in suppressive soil than the conducive soil. Observations of the incidence of necrotic rhizome of Foc susceptible 'Ambon Kuning' (AAA) banana cultivar showed that in the suppressive soil taken from Sarampad West Java, the application of silica and manure helped suppress fusarium wilt disease development. In the conducive soil taken from Salaman-Central Java, silica and manure applications were not able to suppress disease incidence. The result of this study indicated that in suppressive soil, the application of silica can increase plant resistance to Foc infection, while manure application can increase soil microbial activity, and suppress Foc development.

Does manure management affect the latent greenhouse gas emitting potential of livestock manures?

With livestock manures being increasingly sought as alternatives to costly synthetic fertilisers, it is imperative that we understand and manage their associated greenhouse gas (GHG) emissions. Here we provide the first dedicated assessment into how the GHG emitting potential of various manures responds to the different stages of the manure management continuum (e.g., from feed pen surface vs stockpiled). The research is important from the perspective of manure application to agricultural soils. Manures studied included: manure from beef feedpen surfaces and stockpiles; poultry broiler litter (8-week batch); fresh and composted egg layer litter; and fresh and composted piggery litter. Gases assessed were methane (CH4) and nitrous oxide (N2O), the two principal agricultural GHGs. We employed proven protocols to determine the manures’ ultimate CH4 producing potential. We also devised a novel incubation experiment to elucidate their N2O emitting potential; a measure for which no established methods exist. We found lower CH4 potentials in manures from later stages in their management sequence compared with earlier stages, but only by a factor of 0.65×. Moreover, for the beef manures this decrease was not significant (P < 0.05). Nitrous oxide emission potential was significantly positively (P < 0.05) correlated with C/N ratios yet showed no obvious relationship with manure management stage. Indeed, N2O emissions from the composted egg manure were considerably (13×) and significantly (P < 0.05) higher than that of the fresh egg manure. Our study demonstrates that manures from all stages of the manure management continuum potentially entail significant GHG risk when applied to arable landscapes. Efforts to harness manure resources need to account for this.

Managing cattle grazing intensity: effects on soil organic matter and soil nitrogen

Extensive cattle grazing is the dominant land use in northern Australia. It has been suggested that grazing intensity and rainfall have profound effects on the dynamics of soil nutrients in northern Australia’s semi-arid rangelands. Previous studies have found positive, neutral and negative effects of grazing pressure on soil nutrients. These inconsistencies could be due to short-term experiments that do not capture the slow dynamics of some soil nutrients and the effects of interannual variability in rainfall. In a long-term cattle grazing trial in northern Australia on Brown Sodosol–Yellow Kandosol complex, we analysed soil organic matter and mineral nitrogen in surface soils (0–10 cm depth) 11, 12 and 16 years after trial establishment on experimental plots representing moderate stocking (stocked at the long-term carrying capacity for the region) and heavy stocking (stocked at twice the long-term carrying capacity). Higher soil organic matter was found under heavy stocking, although grazing treatment had little effect on mineral and total soil nitrogen. Interannual variability had a large effect on soil mineral nitrogen, but not on soil organic matter, suggesting that soil nitrogen levels observed in this soil complex may be affected by other indirect pathways, such as climate. The effect of interannual variability in rainfall and the effects of other soil types need to be explored further.

Estimating daily methane production in individual cattle with irregular feed intake patterns from short-term methane emission measurements

Spot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a GreenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of splines on a 'per-animal per-day' basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made.

A universal equation to predict methane production of forage-fed cattle in Australia

The methods for estimating methane emissions from cattle as used in the Australian national inventory are based on older data that have now been superseded by a large amount of more recent data. Recent data suggested that the current inventory emissions estimates can be improved. To address this issue, a total of 1034 individual animal records of daily methane production (MP) was used to reassess the relationship between MP and each of dry matter intake (DMI) and gross energy intake (GEI). Data were restricted to trials conducted in the past 10 years using open-circuit respiration chambers, with cattle fed forage-based diets (forage >70%). Results from diets considered to inhibit methanogenesis were omitted from the dataset. Records were obtained from dairy cattle fed temperate forages (220 records), beef cattle fed temperate forages (680 records) and beef cattle fed tropical forages (133 records). Relationships were very similar for all three production categories and single relationships for MP on a DMI or GEI basis were proposed for national inventory purposes. These relationships were MP (g/day) = 20.7 (±0.28) × DMI (kg/day) (R2 = 0.92, P < 0.001) and MP (MJ/day) = 0.063 (±0.008) × GEI (MJ/day) (R2 = 0.93, P < 0.001). If the revised MP (g/day) approach is used to calculate Australia’s national inventory, it will reduce estimates of emissions of forage-fed cattle by 24%. Assuming a global warming potential of 25 for methane, this represents a 12.6 Mt CO2-e reduction in calculated annual emissions from Australian cattle.

Horse and Cattle Brands in Queensland

Horse and Cattle Brands in Queensland since 1872 to current year 2015