A precision apparatus, with solid phase micro-extraction monitoring capability, for incorporation studies of gaseous precursors into insect-derived metabolites

An apparatus is described that facilitates the determination of incorporation levels of isotope labelled, gaseous precursors into volatile insect-derived metabolites. Atmospheres of varying gas compositions can be generated by evacuation of a working chamber followed by admission of the required levels of component gases, using a precision, digitised pressure read-out system. Insects such as fruit-flies are located initially in a small introduction chamber, from which migration can occur downwards into the working chamber. The level of incorporation of labelled precursors is continuously assayed by the Solid Phase Micro Extraction (SPME) technique and GC-MS analyses. Experiments with both Bactrocera species (fruit-flies) and a parasitoid wasp, Megarhyssa nortoni nortoni (Cresson) and oxygen-18 labelled dioxygen illustrate the utility of this system. The isotope effects of oxygen-18 on the carbon-13 NMR spectra of 1,7- dioxaspiro[5,5]undecane are also described.

A comparison of the excretion rate of endogenous purine derivatives in the urine of Bos indicus and Bos taurus steers

Estimates of microbial crude protein (MCP) production by ruminants, using a method based on the excretion of purine derivatives in urine, require an estimate of the excretion of endogenous purine derivatives (PD) by the animal. Current methods allocate a single value to all cattle. An experiment was carried out to compare the endogenous PD excretion in Bos taurus and high-content B. indicus (hereafter, B. indicus) cattle. Five Holstein–Friesian (B. taurus) and 5 Brahman (> 75% B. indicus) steers (mean liveweight 326 ± 3.0 kg) were used in a fasting study. Steers were fed a low-quality buffel grass (Cenchrus ciliaris; 59.4 g crude protein/kg dry matter) hay at estimated maintenance requirements for 19 days, after which hay intake was incrementally reduced for 2 days and the steers were fasted for 7 days. The excretion of PD in urine was measured daily for the last 6 days of the fasting period and the mean represented the daily endogenous PD excretion. Excretion of endogenous PD in the urine of B. indicus steers was less than half that of the B. taurus steers (190 µmol/kg W0.75.day v. 414 µmol/kg W0.75.day; combined s.e. 37.2 µmol/kg W0.75.day; P < 0.001). It was concluded that the use of a single value for endogenous PD excretion is inappropriate for use in MCP estimations and that subspecies-specific values would improve precision.

Frequency and precision of aerial surveys for kangaroo management

The appropriate frequency and precision for surveys of wildlife populations represent a trade-off between survey cost and the risk of making suboptimal management decisions because of poor survey data. The commercial harvest of kangaroos is primarily regulated through annual quotas set as proportions of absolute estimates of population size. Stochastic models were used to explore the effects of varying precision, survey frequency and harvest rate on the risk of quasiextinction for an arid-zone and a more mesic-zone kangaroo population. Quasiextinction probability increases in a sigmoidal fashion as survey frequency is reduced. The risk is greater in more arid regions and is highly sensitive to harvest rate. An appropriate management regime involves regular surveys in the major harvest areas where harvest rate can be set close to the maximum sustained yield. Outside these areas, survey frequency can be reduced in relatively mesic areas and reduced in arid regions when combined with lowered harvest rates. Relative to other factors, quasiextinction risk is only affected by survey precision (standard error/mean × 100) when it is >50%, partly reflecting the safety of the strategy of harvesting a proportion of a population estimate.

Wood properties and knot occlusion of plantation grown Eucalyptus dunnii and Corymbia citriodora subsp. variegata in a pruning and thinning experiment.

A 2 × 2 factorial combination of thinned or unthinned, and pruned or unpruned 11-year-old Eucalyptus dunnii (DWG) and 12-year-old Corymbia citriodora subsp. variegata (CCV) was destructively sampled to provide 60 trees in total per species. Two 1.4 m long billets were cut from each tree and were rotary veneered in a spindleless lathe down to a 45 mm diameter core to expose knots which were classified as either alive, partially occluded or fully occluded. Non-destructive evaluation of a wider range of thinning treatments available in these trials was undertaken with Pilodyn and Fakopp tools. Disc samples were also taken for basic density and modulus of elasticity. Differences between treatments for all wood property assessments were generally small and not significantly different.Thinning and pruning had little effect on the stem diameter growth required to achieve occlusion, therefore occlusion would be more rapid after thinning due to more rapid stem diameter growth. The difference between the treatments of greatest management interest, thinned and pruned (T&P) and unthinned and unpruned (UT&UP) were small. The production of higher value clear wood produced after all knots had occluded, measured as the average stem diameter growth over occlusion of the three outermost knots, was approximately 2 centimetres diameter. Two of the treatments can be ruled out as viable management alternatives: (i) the effect of thinning without pruning (T&UP) is clear, leading to a large inner core of stem wood containing knots (large knotty core diameter) and (ii) pruning without thinning (UT&P) results in a small knotty core diameter, however the tree and therefore log diameters are also small.

The performance of broilers offered sorghum - compared to wheat-based diets: a large sacle experiment.

Sufficient evidence tended to indicate that at least four factors can negatively influence broiler performance when offered sorghum-based diets; in particular energy utilisation of sorghum in young birds. It was proposed that mainly CT would further influence sorghum grain AME values when consumed by young chicks (0-7 and 7-14 d old). Overall, birds consuming sorghum-based diets during the starter phase (0-21 d), did not match the performance of birds offered wheat-based diets. The use of phytase enzymes in sorghum-based diets tended to improve bird performance. However, reducing the obtained AME of sorghum grains by -0.8 MJ during the 0-21 d period appears to be a practical solution.

Remote Sensing - based precision agriculture tool for the sugar industry

The project will produce practical and relevant benchmarks, protocols and recommendations for the adoption of remote sensing technologies for improved in season management and therefore production within the Australian sugar cane industry.

Optimising crop and economic performance of precision overhead irrigation

This project aims to develop integrated irrigation and nutrition management strategies under limited water for irrigators currently investing in overhead irrigation systems (CPLM) to minimize the learning lag in their use and optimize crop and economic performance.

Precision Agriculture and Remote Sensing Technologies in Central Queensland agricultural production systems

Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.

Economic evaluation of precision controlled traffic farming in the Australian sugar industry: a case study of an early adopter

Controlled traffic has been identified as the most practical method of reducing compaction-related soil structural degradation in the Australian sugarcane industry. GPS auto-steer systems are required to maximize this potential. Unfortunately there is a perception that little economic gain will result from investing in this technology. Regardless, a number of growers have made the investment and are reaping substantial economic and lifestyle rewards. In this paper we assess the cost effectiveness of installing GPS guidance and using it to implement Precision Controlled Traffic Farming (PCTF) based on the experience of an early adopter. The Farm Economic Analysis Tool (FEAT) model was used with data provided by the grower to demonstrate the benefits of implementing PCTF. The results clearly show that a farming system based on PCTF and the minimum tillage improved farm gross margin by 11.8% and reduced fuel usage by 58%, compared to producers' traditional practice. PCTF and minimum tillage provide sugar producers with a tool to manage the price cost squeeze at a time of low sugar prices. These data provide producers with the evidence that investment in PCTF is economically prudent.

Scaling results up from a plot and paddock scale to a property - a case study from a long-term grazing experiment in northern Australia

Grazing experiments are usually used to quantify and demonstrate the biophysical impact of grazing strategies, with the Wambiana grazing experiment being one of the longest running such experiments in northern Australia. Previous economic analyses of this experiment suggest that there is a major advantage in stocking at a fixed, moderate stocking rate or in using decision rules allowing flexible stocking to match available feed supply. The present study developed and applied a modelling procedure to use data collected at the small plot, land type and paddock scales at the experimental site to simulate the property-level implications of a range of stocking rates for a breeding-finishing cattle enterprise. The greatest economic performance was achieved at a moderate stocking rate of 10.5 adult equivalents 100 ha(-1). For the same stocking rate over time, the fixed stocking strategy gave a greater economic performance than strategies that involved moderate changes to stocking rates each year in response to feed supply. Model outcomes were consistent with previous economic analyses using experimental data. Further modelling of the experimental data is warranted and similar analyses could be applied to other major grazing experiments to allow the scaling of results to greater scales.

Understanding the barriers to the implementation of precision agriculture in the central region

There is an increasing requirement for more astute land resource management through efficiencies in agricultural inputs in a sugar cane production system. A precision agriculture (PA) approach can provide a pathway for a sustainable sugarcane production system. One of the impediments to the adoption of PA practices is access to paddock-scale mapping layers displaying variability in soil properties, crop growth and surface drainage. Variable rate application (VRA) of nutrients is an important component of PA. However, agronomic expertise within PA systems has fallen well behind significant advances in PA technologies. Generally, advisers in the sugar industry have a poor comprehension of the complex interaction of variables that contribute to within-paddock variations in crop growth. This is regarded as a significant impediment to the progression of PA in sugarcane and is one of the reasons for the poor adoption of VRA of nutrients in a PA approach to improved sugar cane production. This project therefore has established a number of key objectives which will contribute to the adoption of PA and the staged progression of VRA supported by relevant and practical agronomic expertise. These objectives include provision of base soils attribute mapping that can be determined using Veris 3100 Electrical Conductivity (EC) and digital elevation datasets using GPS mapping technology for a large sector of the central cane growing region using analysis of archived satellite imagery to determine the location and stability of yield patterns over time and in varying seasonal conditions on selected project study sites. They also include the stablishment of experiments to determine appropriate VRA nitrogen rates on various soil types subjected to extended anaerobic conditions, and the establishment of trials to determine nitrogen rates applicable to a declining yield potential associated with the aging of ratoons in the crop cycle. Preliminary analysis of archived yield estimation data indicates that yield patterns remain relatively stable overtime. Results also indicate the where there is considerable variability in EC values there is also significant variation in yield.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.