Row spacing and planting density effects on the growth and yield of sugarcane. 3. Responses with different cultivars.

The promotion of controlled traffic (matching wheel and row spacing) in the Australian sugar industry is necessitating a widening of row spacing beyond the standard 1.5 m. As all cultivars grown in the Australian industry have been selected under the standard row spacing there are concerns that at least some cultivars may not be suitable for wider rows. To address this issue, experiments were established in northern and southern Queensland in which cultivars, with different growth characteristics, recommended for each region, were grown under a range of different row configurations. In the northern Queensland experiment at Gordonvale, cultivars Q187((sic)), Q200((sic)), Q201((sic)), and Q218((sic)) were grown in 1.5-m single rows, 1.8-m single rows, 1.8-m dual rows (50 cm between duals), and 2.3-m dual rows (80 cm between duals). In the southern Queensland experiment at Farnsfield, cvv. Q138, Q205((sic)), Q222((sic)) and Q188((sic)) were also grown in 1.5-m single rows, 1.8-m single rows, 1.8-m dual rows (50 cm between duals), while 1.8-m-wide throat planted single row and 2.0-m dual row (80 cm between duals) configurations were also included. There was no difference in yield between the different row configurations at Farnsfield but there was a significant row configuration x cultivar interaction at Gordonvale due to good yields in 1.8-m single and dual rows with Q201((sic)) and poor yields with Q200((sic)) at the same row spacings. There was no significant difference between the two cultivars in 1.5-m single and 2.3-m dual rows. The experiments once again demonstrated the compensatory capacity that exists in sugarcane to manipulate stalk number and individual stalk weight as a means of producing similar yields across a range of row configurations and planting densities. There was evidence of different growth patterns between cultivars in response to different row configurations (viz. propensity to tiller, susceptibility to lodging, ability to compensate between stalk number and stalk weight), suggesting that there may be genetic differences in response to row configuration. It is argued that there is a need to evaluate potential cultivars under a wider range of row configurations than the standard 1.5-m single rows. Cultivars that perform well in row configurations ranging from 1.8 to 2.0 m are essential if the adverse effects of soil compaction are to be managed through the adoption of controlled traffic.

The effect of foliar sprays of the synthetic auxin 3-5-6 TPA, on fruit drop, fruit size and seed development in three lychee (Litchi chinensis) cultivars: Tai So, Fay Zee Sui and Kwai Mai Pink.

Fruit drop in lychee can cause major yield losses in Australia, the severity varying with cultivar and season. Research in China, South Africa and Israel has demonstrated the potential for synthetic auxins used as foliar sprays to reduce fruit drop in lychee. Trials were initiated in Australia to test the efficacy of the synthetic auxin, 3-5-6 Trichloro-2-phridyl-oxyacetic acid (3-5-6 TPA) at 50 ppm on the cultivars Tai So, Fay Zee Sui and Kwai Mai Pink. Results indicate that in most cases the TPA reduced natural fruit drop however the size of the fruit at the time of application affects the response and the ideal application time varies with cultivar; approximately 13 mm fruit length in 'Kwai Mai Pink', 20 mm in 'Fay Zee Sui' and 27 mm in 'Tai So'. If applied too early in 'Tai So', it caused an increase in fruit drop. The TPA was most effective when natural fruit drop was high, reducing fruit drop from 74.7 to 34.9% in 'Kwai Mai Pink' and least effective when natural fruit drop was low. An increase in the percentage of fruit with poorly developed (chicken tongue) seed and slightly larger fruit size was also observed in treated trees.

Objective `Safe' Grazing Capacities for South-West Queensland Australia: Development of a Model for Individual Properties

Few tools are available to assist graziers, land administrators and financiers in making objective grazing capacity decisions on Australian rangelands, despite existing knowledge regarding stocking rate theory and the impact of stocking rates on land condition. To address this issue a model for objectively estimating 'safe' grazing capacities on individual grazing properties in south-west Queensland was developed. The method is based on 'safe' levels of utilisation (15%-20%) by domestic livestock of average annual forage grown for each land system on a property. Average annual forage grown (kglha) was calculated as the product of the rainfall use efficiency (kglhdmm) and average annual rainfall (mm) for a land system. This estimate included the impact of tree and shrub cover on forage production. The 'safe' levels of forage utilisation for south- west Queensland pastures were derived from the combined experience of (1) re-analysis of the results of grazing trials, (2) reaching a consensus on local knowledge and (3) examination of existing grazing practice on 'benchmark' grazing properties. We recognise the problems in defining, determining and using grazing capacity values, but consider that the model offers decision makers a tool that can be used to assess the grazing capacity of individual properties.

Individual-based modelling of the efficacy of fumigation tactics to control lesser grain borer (Rhyzopertha dominica) in stored grain

Increasing resistance to phosphine (PH 3) in insect pests, including lesser grain borer (Rhyzopertha dominica) has become a critical issue, and development of effective and sustainable strategies to manage resistance is crucial. In practice, the same grain store may be fumigated multiple times, but usually for the same exposure period and concentration. Simulating a single fumigation allows us to look more closely at the effects of this standard treatment.We used an individual-based, two-locus model to investigate three key questions about the use of phosphine fumigant in relation to the development of PH 3 resistance. First, which is more effective for insect control; long exposure time with a low concentration or short exposure period with a high concentration? Our results showed that extending exposure duration is a much more efficient control tactic than increasing the phosphine concentration. Second, how long should the fumigation period be extended to deal with higher frequencies of resistant insects in the grain? Our results indicated that if the original frequency of resistant insects is increased n times, then the fumigation needs to be extended, at most, n days to achieve the same level of insect control. The third question is how does the presence of varying numbers of insects inside grain storages impact the effectiveness of phosphine fumigation? We found that, for a given fumigation, as the initial population number was increased, the final survival of resistant insects increased proportionally. To control initial populations of insects that were n times larger, it was necessary to increase the fumigation time by about n days. Our results indicate that, in a 2-gene mediated resistance where dilution of resistance gene frequencies through immigration of susceptibles has greater effect, extending fumigation times to reduce survival of homozygous resistant insects will have a significant impact on delaying the development of resistance. © 2012 Elsevier Ltd.

Constructing a new individual-based model of phosphine resistance in lesser grain borer (Rhyzopertha dominica): do we need to include two loci rather than one?

In this article, we describe and compare two individual-based models constructed to investigate how genetic factors influence the development of phosphine resistance in lesser grain borer (R. dominica). One model is based on the simplifying assumption that resistance is conferred by alleles at a single locus, while the other is based on the more realistic assumption that resistance is conferred by alleles at two separate loci. We simulated the population dynamic of R. dominica in the absence of phosphine fumigation, and under high and low dose phosphine treatments, and found important differences between the predictions of the two models in all three cases. In the absence of fumigation, starting from the same initial frequencies of genotypes, the two models tended to different stable frequencies, although both reached Hardy-Weinberg equilibrium. The one-locus model exaggerated the equilibrium proportion of strongly resistant beetles by 3.6 times, compared to the aggregated predictions of the two-locus model. Under a low dose treatment the one-locus model overestimated the proportion of strongly resistant individuals within the population and underestimated the total population numbers compared to the two-locus model. These results show the importance of basing resistance evolution models on realistic genetics and that using oversimplified one-locus models to develop pest control strategies runs the risk of not correctly identifying tactics to minimise the incidence of pest infestation.

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.