999 resultados para Quality quiz


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The utility of near infrared spectroscopy as a non-invasive technique for the assessment of internal eating quality parameters of mandarin fruit (Citrus reticulata cv. Imperial) was assessed. The calibration procedure for the attributes of TSS (total soluble solids) and DM (dry matter) was optimised with respect to a reference sampling technique, scan averaging, spectral window, data pre-treatment (in terms of derivative treatment and scatter correction routine) and regression procedure. The recommended procedure involved sampling of an equatorial position on the fruit with 1 scan per spectrum, and modified partial least squares model development on a 720–950-nm window, pre-treated as first derivative absorbance data (gap size of 4 data points) with standard normal variance and detrend scatter correction. Calibration model performance for the attributes of TSS and DM content was encouraging (typical Rc2 of >0.75 and 0.90, respectively; typical root mean squared standard error of calibration of <0.4 and 0.6%, respectively), whereas that for juiciness and total acidity was unacceptable. The robustness of the TSS and DM calibrations across new populations of fruit is documented in a companion study.

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The robustness of multivariate calibration models, based on near infrared spectroscopy, for the assessment of total soluble solids (TSS) and dry matter (DM) of intact mandarin fruit (Citrus reticulata cv. Imperial) was assessed. TSS calibration model performance was validated in terms of prediction of populations of fruit not in the original population (different harvest days from a single tree, different harvest localities, different harvest seasons). Of these, calibration performance was most affected by validation across seasons (signal to noise statistic on root mean squared error of prediction of 3.8, compared with 20 and 13 for locality and harvest day, respectively). Procedures for sample selection from the validation population for addition to the calibration population (‘model updating’) were considered for both TSS and DM models. Random selection from the validation group worked as well as more sophisticated selection procedures, with approximately 20 samples required. Models that were developed using samples at a range of temperatures were robust in validation for TSS and DM.

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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 .

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Considerable export opportunities exist in countries such as Japan, Canada, and Europe (Germany) for peeled rockmelon frozen in quarters or as diced product. Processing of these products is limited because the cost of hand labour for peeling is prohibitive. Consequently, development of mechnanical peeling equipment is essential for Australian industry to compete. In this project, appropriate machinery for the production of a high quality product is being developed, and basic studies in food technology, marketing, and production are being carried out. There are no Australian publications on rockmelon freezing, although fresh fruit quality of various cultivars has been investigated (Mutton, 1978). Very little overseas information on freezing rockmelons has been published (del Rio and Miller, 1979 and Martinez-Javega et al., 1975). In this project, the freezing quality of new rockmnelon and honeydew melon cultivars was evaluated.

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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.

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The focus of this article is on the cost-effectiveness of mitigation strategies to reduce pollution loads and improve water quality in South-East Queensland. Scenarios were developed about the types of catchment interventions that could be considered, and the resulting changes in water quality indicators that may result. Once these catchment scenarios were modelled, the range of expected outcomes was assessed and the costs of mitigation interventions were estimated. Strategies considered include point and non-point source interventions. Predicted reductions in pollution levels were calculated for each action based on the expected population growth. The cost of the interventions included the full investment and annual running costs as well as planned public investment by the state agencies. Cost-effectiveness of strategies is likely to vary according to whether suspended sediments, nitrogen or phosphorus loads are being targeted.

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The intent of this study was to design, document and implement a Quality Management System (QMS) into a laboratory that incorporated both research and development (R&D) and routine analytical activities. In addition, it was necessary for the QMS to be easily and efficiently maintained to: (a) provide documented evidence that would validate the system's compliance with a certifiable standard, (b) fit the purpose of the laboratory, (c) accommodate prevailing government policies and standards, and (d) promote positive outcomes for the laboratory through documentation and verification of the procedures and methodologies implemented. Initially, a matrix was developed that documented the standards' requirements and the necessary steps to be made to meet those requirements. The matrix provided a check mechanism on the progression of the system's development. In addition, it was later utilised in the Quality Manual as a reference tool for the location of full procedures documented elsewhere in the system. The necessary documentation to build and monitor the system consisted of a series of manuals along with forms that provided auditable evidence of the workings of the QMS. Quality Management (QM), in one form or another, has been in existence since the early 1900's. However, the question still remains: is it a good thing or just a bugbear? Many of the older style systems failed because they were designed by non-users, fiercely regulatory, restrictive and generally deemed to be an imposition. It is now considered important to foster a sense of ownership of the system by the people who use the system. The system's design must be tailored to best fit the purpose of the operations of the facility if maximum benefits to the organisation are to be gained.

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Runoff and sediment loss from forest roads were monitored for a two-year period in a Pinus plantation in southeast Queensland. Two classes of road were investigated: a gravelled road, which is used as a primary daily haulage route for the logging area, and an ungravelled road, which provides the main access route for individual logging compartments and is intensively used as a haulage route only during the harvest of these areas (approximately every 30 years). Both roads were subjected to routine traffic loads and maintenance during the study. Surface runoff in response to natural rainfall was measured and samples taken for the determination of sediment and nutrient (total nitrogen, total phosphorus, dissolved organic carbon and total iron) loads from each road. Results revealed that the mean runoff coefficient (runoff depth/rainfall depth) was consistently higher from the gravelled road plot with 0.57, as compared to the ungravelled road with 0.38. Total sediment loss over the two-year period was greatest from the gravelled road plot at 5.7 t km−1 compared to the ungravelled road plot with 3.9 t km−1. Suspended solids contributed 86% of the total sediment loss from the gravelled road, and 72% from the ungravelled road over the two years. Nitrogen loads from the two roads were both relatively constant throughout the study, and averaged 5.2 and 2.9 kg km−1 from the gravelled and ungravelled road, respectively. Mean annual phosphorus loads were 0.6 kg km−1 from the gravelled road and 0.2 kg km−1 from the ungravelled road. Organic carbon and total iron loads increased in the second year of the study, which was a much wetter year, and are thought to reflect the breakdown of organic matter in roadside drains and increased sediment generation, respectively. When road and drain maintenance (grading) was performed runoff and sediment loss were increased from both road types. Additionally, the breakdown of the gravel road base due to high traffic intensity during wet conditions resulted in the formation of deep (10 cm) ruts which increased erosion. The Water Erosion Prediction Project (WEPP):Road model was used to compare predicted to observed runoff and sediment loss from the two road classes investigated. For individual rainfall events, WEPP:Road predicted output showed strong agreement with observed values of runoff and sediment loss. WEPP:Road predictions for annual sediment loss from the entire forestry road network in the study area also showed reasonable agreement with the extrapolated observed values.

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Grain samples from a combined intermediate and advanced stage barley breeding trial series, grown at two sites in two consecutive years were assessed for detailed grain quality and ruminant feed quality. The results indicated that there were significant genetic and environmental effects for “feed” traits as measured using grain hardness, acid detergent fibre (ADF), starch and in-sacco dry matter digestibility (ISDMD) assays. In addition, there was strong genotypic discrimination for the regressed feed performance traits, namely Net Energy (NE) and Average Daily Gain (ADG). There was considerable variation in genetic correlations for all traits based on variance from the cultivars used, sites or laboratory processing effects. There was a high level of heritability ranging from 89% to 88% for retention, 60% to 80% for protein and 56% to 68% for ADF. However, there were only low to moderate levels of heritability for the feed traits, with starch 30–39%, ISDMD 55–63%, ADF 56–68%, particle size 47–73%, 31–48% NE and ADG 44–51%. These results suggest that there were real differences in the feed performance of barleys and that selection for cattle feed quality is potentially a viable option for breeding programs.

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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.

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Barley (Hordeum vulgare) genotypes were sequenced for polymorphism in the hardness genes, these being the three hordoindoline (hin a, hin b1 and hin b2) genes. The variation in haplotype was determined by sequencing for single nucleotide polymorphisms (SNPs). Polymorphism between each gene was then compared to grain hardness (three methods), malt quality characteristics (hot water extract and friability) and cattle feed quality. Two haplotypes were found in a set of forty barley genotypes. For hin a, two alleles were present, namely hin a1 and hin a2. However, there was no specific hin a allele that was associated with grain hardness, malt and feed quality. Barley has two hin b genes, namely hin b1 and hin b2, and the genotypes tested here had one of two alleles for each gene. However, there were no obvious effects on hardness or quality from either of these hin b alleles. Unlike wheat, where a clear relationship has been demonstrated between a number of SNPs in the wheat hardness genes and quality (soft or hard wheat), there was no such relationship for barley. Despite the wide range in hardness, malt and feed quality, there were only two haplotypes for each of the hin a, hin b1 and hin b2 genes and there was no clear relationship between grain hardness, malt or feed quality. The genotypes used in this study demonstrated that there was a low level of polymorphism in hardness genes in current commercial varieties as well as breeding lines and these polymorphisms had no impact on quality.

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This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

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Leaf carbon (C) content, leaf nitrogen (N) content, and C:N ratio are especially useful for understanding plant-herbivore interactions and may be important in developing control methods for the invasive riparian plant Arundo donax L. We measured C content, N content, C:N ratio, and chlorophyll index (SPAD 502 reading) for 768 leaves from A. donax collected over a five year period at several locations in California, Nevada, and Texas. Leaf N was more variable than leaf C, and thus we developed a linear regression equation for estimating A. donax leaf N from the leaf chlorophyll index (SPAD reading). When applied to two independent data sets, the equation (leaf N content % = -0.63 + 0.08 x SPAD) produced realistic estimates that matched seasonal and spatial trends reported from a natural A. donax population. Used in conjunction with the handheld SPAD 502 meter, the equation provides a rapid, non-destructive method for estimating A. donax leaf quality.

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Three drafts of Bos indicus cross steers (initially 178-216 kg) grazed Leucaena-grass pasture [Leucaena leucocephala subspecies glabrata cv. Cunningham with green panic (Panicum maximum cv. trichoglume)] from late winter through to autumn during three consecutive years in the Burnett region of south-east Queensland. Measured daily weight gain (DWGActual) of the steers was generally 0.7-1.1 kg/day during the summer months. Estimated intakes of metabolisable energy and dry matter (DM) were calculated from feeding standards as the intakes required by the steers to grow at the DWGActual. Diet attributes were predicted from near infrared reflectance spectroscopy spectra of faeces (F.NIRS) using established calibration equations appropriate for northern Australian forages. Inclusion of some additional reference samples from cattle consuming Leucaena diets into F.NIRS calibrations based on grass and herbaceous legume-grass pastures improved prediction of the proportion of Leucaena in the diet. Mahalanobis distance values supported the hypothesis that the F.NIRS predictions of diet crude protein concentration and DM digestibility (DMD) were acceptable. F.NIRS indicated that the percentage of Leucaena in the diet varied widely (10-99%). Diet crude protein concentration and DMD were usually high, averaging 12.4 and 62%, respectively, and were related asymptotically to the percentage of Leucaena in the diet (R2 = 0.48 and 0.33, respectively). F.NIRS calibrations for DWG were not satisfactory to predict this variable from an individual faecal sample since the s.e. of prediction were 0.33-0.40 kg/day. Cumulative steer liveweight (LW) predicted from F.NIRS DWG calibrations, which had been previously developed with tropical grass and grass-herbaceous legume pastures, greatly overestimated the measured steer LW; therefore, these calibrations were not useful. Cumulative steer LW predicted from a modified F.NIRS DWG calibration, which included data from the present study, was strongly correlated (R2 = 0.95) with steer LW but overestimated LW by 19-31 kg after 8 months. Additional reference data are needed to develop robust F.NIRS calibrations to encompass the diversity of Leucaena pastures of northern Australia. In conclusion, the experiment demonstrated that F.NIRS could improve understanding of diet quality and nutrient intake of cattle grazing Leucaena-grass pasture, and the relationships between nutrient supply and cattle growth.

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As is the case globally, Australian schools that serve high-poverty communities most often employ the least experienced, least prepared teachers. Beginning with a discussion of poverty in Australia this chapter draws on 6 years of learnings from Australia's National Exceptional Teachers for Disadvantaged Schools (NETDS) program to examine how social justice can be taught within a mainstream Initial Teacher Education program in an increasingly neoliberal climate where teacher education curriculum around social justice struggles to find a place within the current discourses of quality teaching and its preoccupations with standards, accountability, and high-stakes testing.