Getting value out of your sensory testing - the difference from control test

Non-parametric difference tests such as triangle and duo-trio tests traditionally are used to establish differences or similarities between products. However they only supply the researcher with partial answers and often further testing is required to establish the nature, size and direction of differences. This paper looks at the advantages of the difference from control (DFC) test (also known as degree of difference test) and discusses appropriate applications of the test. The scope and principle of the test, panel composition and analysis of results are presented with the aid of suitable examples. Two of the major uses of the DFC test are in quality control and shelf-life testing. The role DFC takes in these areas and the use of other tests to complement the testing is discussed. Controls or standards are important in both these areas and the use of standard products, mental and written standards and blind controls are highlighted. The DFC test has applications in products where the duo-trio and triangle tests cannot be used because of the normal heterogeneity of the product. While the DFC test is a simple difference test it can be structured to give the researcher more valuable data and scope to make informed decisions about their product.

Oesophagogastric ulceration in pigs: A visual morphological scoring guide

Objective: To provide a visual guide for oesophagogastric ulcer scoring and recognition of different morphological changes in the pars oesophagea. Design: Pig stomachs were collected at slaughter and visually evaluated and scored for parakeratosis, erosion and ulceration in the pars oesophagea. Results: A visual and descriptive guide is presented that will aid in the objective assessment and scoring of oesophagogastric ulceration in pigs within the pig health monitoring system (PHMS), namely to the four categories of 0 = normal stomach, 1 = parakeratosis and thickened epithelium, 2 = erosions and 3 = developed ulcers with and without stenosis. Conclusion: A visual guide has been developed that illustrates the full range of morphological changes that can occur in the pars oesophagea of the stomach within the few currently recognised stages of the disease.

An evaluation of genetic analyses, skull morphology and visual appearance for assessing dingo purity: implications for dingo conservation

The introgression of domestic dog genes into dingo populations threatens the genetic integrity of 'pure' dingoes. However, dingo conservation efforts are hampered by difficulties in distinguishing between dingoes and hybrids in the field. This study evaluates consistency in the status of hybridisation (i.e. dingo, hybrid or dog) assigned by genetic analyses, skull morphology and visual assessments. Of the 56 south-east Queensland animals sampled, 39 (69.6%) were assigned the same status by all three methods, 10 (17.9%) by genetic and skull methods, four (7.1%) by genetic and visual methods; and two (3.6%) by skull and visual methods. Pair-wise comparisons identified a significant relationship between genetic and skull methods, but not between either of these and visual methods. Results from surveying 13 experienced wild dog managers showed that hybrids were more easily identified by visual characters than were dingoes. A more reliable visual assessment can be developed through determining the relationship between (1) genetics and phenotype by sampling wild dog populations and (2) the expression of visual characteristics from different proportions and breeds of domestic dog genes by breeding trials. Culling obvious hybrids based on visual characteristics, such as sable and patchy coat colours, should slow the process of hybridisation.

Sexing Sirenians: Validation of Visual and Molecular Sex Determination in Both Wild Dugongs (Dugong dugon) and Florida Manatees (Trichechus manatus latirostris)

Sexing wild marine mammals that show little to no sexual dimorphism is challenging. For sirenians that are difficult to catch or approach closely, molecular sexing from tissue biopsies offers an alternative method to visual discrimination. This paper reports the results of a field study to validate the use of two sexing methods: (1) visual discrimination of sex vs (2) molecular sexing based on a multiplex PCR assay which amplifies the male-specific SRY gene and differentiates ZFX and ZFY gametologues. Skin samples from 628 dugongs (Dugong dugon) and 100 Florida manatees (Trichechus manatus latirostris) were analysed and assigned as male or female based on molecular sex. These individuals were also assigned a sex based on either direct observation of the genitalia and/or the association of the individual with a calf. Individuals of both species showed 93 to 96% congruence between visual and molecular sexing. For the remaining 4 to 7%, the discrepancies could be explained by human error. To mitigate this error rate, we recommend using both of these robust techniques, with routine inclusion of sex primers into microsatellite panels employed for identity, along with trained field observers and stringent sample handling.

Improved hatchery and grow-out technology for marine finfish

To enhance the sustainability of marine finfish aquaculture in the Asia-Pacific (AP) region by improving hatchery production technology and facilitating the uptake of compounded feeds for grow-out.

Fisheries Queensland Long Term Monitoring Program Underwater Visual Census of twenty-four reefs on the Great Barrier Reef between 1999 and 2004.

In 1999, the Department of Employment, Economic Development and Innovation (DEEDI), Fisheries Queensland undertook a new initiative to collect long term monitoring data of various important stocks including reef fish. This data and monitoring manual for the reef fish component of that program which was based on Underwater Visual Census methodology of 24 reefs on the Great Barrier Reef between 1999 and 2004. Data was collected using six 50m x 5m transects at 4 sites on 24 reefs. Benthic cover type was also recorded for 10m of each transect. The attached Access Database contains 5 tables being: SITE DETAILS TABLE Survey year Data entry complete REF survey site ID Site # (1-4) Location (reef name) Site Date (date surveyed) Observer 1 (3 initials to identify who estimated fish lengths and recorded benthic cover) TRANSECT DETAILS Survey ID Transect Number (1-6) Time (the transect was surveyed) Visibility (in metres) Minimum Depth surveyed (m) Maximum Depth surveyed (m) Percent of survey completed (%) Comments SUBSTRATE Survey ID Transect Number (1-6) then % cover of each of eth following categories of benthic cover types Dead Coral Live Coral Soft Coral Rubble Sand Sponge Algae Sea Grass Other COORDINATES (over survey sites) from -14 38.792 to -19 44.233 and from 145 21.507 to 149 55.515 SIGHTINGS ID Survey ID Transect Number (1-6) CAAB Code Scientific Name Reef Fish Length (estimated Fork Length of fish; -1 = unknown or not recorded) Outside Transect (if a fish was observed outside a transect -1 was recorded) Morph Code (F = footballer morph for Plectropomus laevis, S = Spawning colour morph displayed)

Stock assessment of the Queensland east coast common coral trout (Plectropomus leopardus) fishery

Common coral trout Plectropomus leopardus is an iconic fish of the Great Barrier Reef (GBR) and is the most important fish for the commercial fishery there. Most of the catch is exported live to Asia. This stock assessment was undertaken in response to falls in catch sizes and catch rates in recent years, in order to gauge the status of the stock. It is the first stock assessment ever conducted of coral trout on the GBR, and brings together a multitude of different data sources for the first time. The GBR is very large and was divided into a regional structure based on the Bioregions defined by expert committees appointed by the Great Barrier Reef Marine Park Authority (GBRMPA) as part of the 2004 rezoning of the GBR. The regional structure consists of six Regions, from the Far Northern Region in the north to the Swains and Capricorn–Bunker Regions in the south. Regions also closely follow the boundaries between Bioregions. Two of the northern Regions are split into Subregions on the basis of potential changes in fishing intensity between the Subregions; there are nine Subregions altogether, which include four Regions that are not split. Bioregions are split into Subbioregions along the Subregion boundaries. Finally, each Subbioregion is split into a “blue” population which is open to fishing and a “green” population which is closed to fishing. The fishery is unusual in that catch rates as an indicator of abundance of coral trout are heavily influenced by tropical cyclones. After a major cyclone, catch rates fall for two to three years, and rebound after that. This effect is well correlated with the times of occurrence of cyclones, and usually occurs in the same month that the cyclone strikes. However, statistical analyses correlating catch rates with cyclone wind energy did not provide significantly different catch rate trends. Alternative indicators of cyclone strength may explain more of the catch rate decline, and future work should investigate this. Another feature of catch rates is the phenomenon of social learning in coral trout populations, whereby when a population of coral trout is fished, individuals quickly learn not to take bait. Then the catch rate falls sharply even when the population size is still high. The social learning may take place by fish directly observing their fellows being hooked, or perhaps heeding a chemo-sensory cue emitted by fish that are hooked. As part of the assessment, analysis of data from replenishment closures of Boult Reef in the Capricorn–Bunker Region (closed 1983–86) and Bramble Reef in the Townsville Subregion (closed 1992–95) estimated a strong social learning effect. A major data source for the stock assessment was the large collection of underwater visual survey (UVS) data collected by divers who counted the coral trout that they sighted. This allowed estimation of the density of coral trout in the different Bioregions (expressed as a number of fish per hectare). Combined with mapping data of all the 3000 or so reefs making up the GBR, the UVS results provided direct estimates of the population size in each Subbioregion. A regional population dynamic model was developed to account for the intricacies of coral trout population dynamics and catch rates. Because the statistical analysis of catch rates did not attribute much of the decline to tropical cyclones, (and thereby implied “real” declines in biomass), and because in contrast the UVS data indicate relatively stable population sizes, model outputs were unduly influenced by the unlikely hypothesis that falling catch rates are real. The alternative hypothesis that UVS data are closer to the mark and declining catch rates are an artefact of spurious (e.g., cyclone impact) effects is much more probable. Judging by the population size estimates provided by the UVS data, there is no biological problem with the status of coral trout stocks. The estimate of the total number of Plectropomus leopardus on blue zones on the GBR in the mid-1980s (the time of the major UVS series) was 5.34 million legal-sized fish, or about 8400 t exploitable biomass, with an 2 additional 3350 t in green zones (using the current zoning which was introduced on 1 July 2004). For the offshore regions favoured by commercial fishers, the figure was about 4.90 million legal-sized fish in blue zones, or about 7700 t exploitable biomass. There is, however, an economic problem, as indicated by relatively low catch rates and anecdotal information provided by commercial fishers. The costs of fishing the GBR by hook and line (the only method compatible with the GBR’s high conservation status) are high, and commercial fishers are unable to operate profitably when catch rates are depressed (e.g., from a tropical cyclone). The economic problem is compounded by the effect of social learning in coral trout, whereby catch rates fall rapidly if fishers keep returning to the same fishing locations. In response, commercial fishers tend to spread out over the GBR, including the Far Northern and Swains Regions which are far from port and incur higher travel costs. The economic problem provides some logic to a reduction in the TACC. Such a reduction during good times, such as when the fishery is rebounding after a major tropical cyclone, could provide a net benefit to the fishery, as it would provide a margin of stock safety and make the fishery more economically robust by providing higher catch rates during subsequent periods of depressed catches. During hard times when catch rates are low (e.g., shortly after a major tropical cyclone), a change to the TACC would have little effect as even a reduced TACC would not come close to being filled. Quota adjustments based on catch rates should take account of long-term trends in order to mitigate variability and cyclone effects in data.

Water activity of poultry litter: Relationship to moisture content during a grow-out

Poultry grown on litter floors are in contact with their own waste products. The waste material needs to be carefully managed to reduce food safety risks and to provide conditions that are comfortable and safe for the birds. Water activity (Aw) is an important thermodynamic property that has been shown to be more closely related to microbial, chemical and physical properties of natural products than moisture content. In poultry litter, Aw is relevant for understanding microbial activity; litter handling and rheological properties; and relationships between in-shed relative humidity and litter moisture content. We measured the Aw of poultry litter collected throughout a meat chicken grow-out (from fresh pine shavings bedding material to day 52) and over a range of litter moisture content (10–60%). The Aw increased non-linearly from 0.71 to 1.0, and reached a value of 0.95 when litter moisture content was only 22–33%. Accumulation of manure during the grow-out reduced Aw for the same moisture content. These results are relevant for making decisions regarding litter re-use in multiple grow-outs as well as setting targets for litter moisture content to minimise odour, microbial risks and to ensure necessary litter physical conditions are maintained during a grow-out. Methods to predict Aw in poultry litter from moisture content are proposed.