Spoilage pattern of five species of Australian prawns: Deterioration is influenced by environment of capture and mode of storage

Five species of commercial prawns Penaeus plebejus, P. merguiensis, P. semisulcatus/P. esculentus and M. bennettae, were obtained from South-East and North Queensland, chilled soon after capture and then stored either whole or deheaded on ice and ice slurry, until spoilage. Total bacterial counts, total volatile nitrogen, K-values and total demerit scores were assessed at regular intervals. Their shelf lives ranged from 10-17 days on ice and >20 days on ice slurry. Initial bacterial flora on prawns from shallower waters (4-15m) were dominated by Gram-positives and had lag periods around 7 days, whereas prawns from deeper waters (100m) were dominant in Pseudomonas spp. with no lag periods in bacterial growth. The dominant spoiler in ice was mainly Pseudomonas fragi whereas the main spoiler in ice slurry was Shewanella putrefaciens. Bacterial interactions seem to play a major role in the patterns of spoilage in relation to capture environment and pattern of storage

Robustness of NIR calibrations for assessing fruit quality

Predictive models based on near infra-red spectroscopy for the assessment of fruit internal quality attributes must exhibit a degree of robustness across the parameters of variety, district and time to be of practical use in fruit grading. At the time this thesis was initiated, while there were a number of published reports on the development of near infra-red based calibration models for the assessment of internal quality attributes of intact fruit, there were no reports of the reliability ("robustness") of such models across time, cultivars or growing regions. As existing published reports varied in instrumentation employed, a re-analysis of existing data was not possible. An instrument platform, based on partial transmittance optics, a halogen light source and (Zeiss MMS 1) detector operating in the short wavelength near infra-red region was developed for use in the assessment of intact fruit. This platform was used to assess populations of macadamia kernels, melons and mandarin fruit for total soluble solids, dry matter and oil concentration. Calibration procedures were optimised and robustness assessed across growing areas, time of harvest, season and variety. In general, global modified partial least squares regression (MPLS) calibration models based on derivatised absorbance data were better than either multiple linear regression or `local' MPLS models in the prediction of independent validation populations . Robustness was most affected by growing season, relative to the growing district or variety . Various calibration updating procedures were evaluated in terms of calibration robustness. Random selection of samples from the validation population for addition to the calibration population was equivalent to or better than other methods of sample addition (methods based on the Mahalanobis distance of samples from either the centroid of the population or neighbourhood samples). In these exercises the global Mahalanobis distance (GH) was calculated using the scores and loadings from the calibration population on the independent validation population. In practice, it is recommended that model predictive performance be monitored in terms of predicted sample GH, with model updating using as few as 10 samples from the new population undertaken when the average GH value exceeds 1 .0 .

Inferential, non-parametric statistics to assess quality of probabilistic forecast systems

Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

Effect of s-methylmethionine sulphonium chloride on oesophagogastric ulcers in pigs

Objective: To assess the value of s-methylmethionine sulphonium chloride (SMMSC) (200 mg/kg) on nutritional performance of pigs and as prevention or therapy for oesophagogastric ulcers. Design: Sixty pigs from a high health status herd with continuing oesophagogastric ulcer problems were endoscopically assessed for the presence or absence of oesophagogastric ulcers. Forty-eight pigs were then selected and allocated according to an initial oesophagogastric epithelial (ulcer score) classification to replicated treatment groups in a 2 × 2 factorial design. Weight gain and feed intake were measured over 49 d, after which pigs were killed and stomachs were collected, re-examined and scored for oesophagogastric ulceration. Results: There was no difference over the 49 d in weight gain, feed intake and backfat in pigs with and without SMMSC supplementation between pigs with or without fully developed oesophagogastric ulcers at the start of the study. In pigs with an initially low ulcer score, feeding SMMSC did not prevent further oesophagogastric ulcer development. No significant effect of SMMSC was apparent when final mean oesophagogastric ulcer scores were compared in pigs with existing high ulcer score. However, further analysis of the changes in individual pig oesophagogastric ulcer scores during the experiment showed that the observed reductions in scores of the high ulcer group was significantly different from all other groups. Conclusion: This study has indicated that supplementation of pig diets with SMMSC cannot be justified unless the slight ulcer score improvement observed could be translated to some commercial production advantage such as a reduction in pig mortalities due to oesophagogastric ulcers. This study has further confirmed the benefit of endoscopy as a tool to enable objective assessment of oesophageal gastric health.

Genetic Impacts of the Hull on Barley Grain Quality

Barley hull plays an important role in malt and feed quality and processing. In this study we measured the variation in hull con-tent along with other grain quality traits namely, kernel discolouration and degree of pre-harvest sprouting, in a single map-ping population. There were significant (p < 0.05) genetic as well as environment effects. In addition, heritability was calculated for hull content to be 29% and 47% for two years’ data. From the analysis, major QTL markers were identified in con-trolling the expression of hull content on chromosomes 2 (2H), and 6 (6H) with significant (P < 0.05) LOD scores of 5.4 and 3.46 respectively. Minor QTLs were identified on 1 (7H), 4 (4H), 5 (1H) and 7 (5H). The region at marker Bmac310 on 4(4H) could be associated with dormancy gene SD4. A number of the QTLs also coincided with regions for either kernel discolouration or preharvest sprouting resistance (dormancy). The results indicate that variation exists for hull content, which is influenced by both growing environment as well as genetically, although the genetic variance explained less than half of the total variance. Further, hull content also impacts on other grain quality attributes including dormancy, sprouting resistance and kernel appearance.

Measurement of genetic and environmental variation in barley (Hordeum vulgare) grain hardness

In this study, we assessed a broad range of barley breeding lines and commercial varieties by three hardness methods (two particle size methods and one crush resistance method (SKCS—Single-Kernel Characterization System), grown at multiple sites to see if there was variation in barley hardness and if that variation was genetic or environmentally controlled. We also developed near-infrared reflectance (NIR) calibrations for these three hardness methods to ascertain if NIR technology was suitable for rapid screening of breeding lines or specific populations. In addition, we used this data to identify genetic regions that may be associated with hardness. There were significant (p<0.05) genetic effects for the three hardness methods. There were also environmental effects, possibly linked to the effect of protein on hardness, i.e. increasing protein resulted in harder grain. Heritability values were calculated at >85% for all methods. The NIR calibrations, with R2 values of >90%, had Standard Error of Prediction values of 0.90, 72 and 4.0, respectively, for the three hardness methods. These equations were used to predict hardness values of a mapping population which resulted in genetic markers being identified on all chromosomes but chromosomes 2H, 3H, 5H, 6H and 7H had markers with significant LOD scores. The two regions on 5H were on the distal end of both the long and short arms. The region that showed significant LOD score was on the long arm. However, the region on the short arm associated with the hardness (hordoindoline) genes did not have significant LOD scores. The results indicate that barley hardness is influenced by both genotype and environment and that the trait is heritable, which would allow breeders to develop very hard or soft varieties if required. In addition, NIR was shown to be a reliable tool for screening for hardness. While the data set used in this study has a relatively low variation in hardness, the tools developed could be applied to breeding populations that have large variation in barley grain hardness.

From inferential statistics to climate knowledge

Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population samples, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.

Nutritional management for reproductive efficiency

Nutrition influences reproductive efficiency and the survival of lambs and weaners but the costs of supplementary feeding or maintaining low stocking rates are not justified by the resulting income from higher lamb weaning rates and reduced weaner mortality. The current practice of segmenting the ewe flock using ultrasound scanning to determine the number of foetuses still results in groups of ewes with a wide range of condition scores and with widely differing nutritional requirements. This report describes an approach to precision management of pregnant ewes and weaners that is based on the e-sheep platform of technologies and uses computer-directed drafting for nutritional management of individual animals and walk-through weighing to monitor changing nutritional status. It is estimated that the cost of feeding a thousand-ewe flock can be reduced from $14,000 for feeding all animals to $3300 for targeted feeding of 25% of ewes requiring additional nutrition and 20% of weaners at risk of dying. The cost of the targeted feeding strategy is more than justified by the value of additional 12-month-old animals, which is $9000. The e-sheep precision nutrition system is not attractive to industry at this stage because of the cost of the e-sheep infrastructure, the perceived complexity of the technology and the requirement for further research, but it is expected to be a commercial option within three years.

Evaluation of the most effective measures of infectivity of a precocious line of Eimeria acervulina in poultry

Coccidiosis is an economically important parasitic disease of chickens that, in Australia, is caused by seven species of the genus Eimeria.1 The disease has traditionally been controlled by prophylactic drugs, but vaccination with attenuated lines of the parasites2–4 is rapidly gaining acceptance world wide. Live Eimeria vaccines are produced in batches which are not frozen and have a limited shelf life. The per cent infectivity of vaccine seed stocks and the vaccines produced from them must therefore be accurately monitored using standardised dose dependant assays to ensure that shelf life, quality control and vaccine release specifications are met. Infectivity for the chicken host cannot readily be determined by microscopic observation of oocysts or sporocyst hatching.5 Dose dependent parameters such as body weight gain, feed conversion ratio, visual lesion scores, mortality, oocysts production, clinical symptoms and microscopic lesion counts could be used as measures of infectivity.6–11 These parameters show significant dose dependant effects with field strains, but lines of vaccine parasites that have been selected for precocious development with associated reduced virulence and reproductive capability may not have the same effect.3,4 The aim of this trial was to determine which parameters provide the most effective measures of infective dose in birds inoculated with a precocious vaccine strain.