28 resultados para Panel VAR models
em eResearch Archive - Queensland Department of Agriculture
Resumo:
'Kensington' mango slices were frozen with sucrose syrup, with dry sucrose and without sugar addition, using blast freezing at -30°C, and still air freezing at -18°C. According to taste panel assessment, slices frozen in syrup were best. A syrup strength of 200 g/L was sufficient to produce a high quality product. the blast-frozen slices had a higher texture score than the still air-frozen slices.
Resumo:
Climate matching software (CLIMEX) was used to prioritise areas to explore for biological control agents in the native range of cat's claw creeper Macfadyena unguis-cati (Bignoniaceae), and to prioritise areas to release the agents in the introduced ranges of the plant. The native distribution of cat's claw creeper was used to predict the potential range of climatically suitable habitats for cat's claw creeper in its introduced ranges. A Composite Match Index (CMI) of cat's claw creeper was determined with the 'Match Climates' function in order to match the ranges in Australia and South Africa where the plant is introduced with its native range in South and Central America. This information was used to determine which areas might yield climatically-adapted agents. Locations in northern Argentina had CMI values which best matched sites with cat's claw creeper infestations in Australia and South Africa. None of the sites from where three currently prioritised biological control agents for cat's claw creeper were collected had CMI values higher than 0.8. The analysis showed that central and eastern Argentina, south Brazil, Uruguay and parts of Bolivia and Paraguay should be prioritised for exploration for new biological control agents for cat's claw creeper to be used in Australia and South Africa.
Resumo:
Urana is a hardseeded, moderately early flowering F-5-derived crossbred subterranean clover of var. subterraneum [( Katz. et Morley) Zohary and Heller] developed by the collaborating organisations of the National Annual Pasture Legume Improvement Program. It has been selected for release as a new cultivar on the basis of its high winter and spring herbage production and overall field performance relative to other subterranean clovers of similar maturity. Urana is recommended for sowing in Western Australia, New South Wales, Victoria, South Australia and Queensland. It is best suited to well-drained, moderately acidic soils in areas with a growing season of 5 - 7 months, which extends into mid-October. Urana is suited to phase farming and crop rotations. It has been granted Plant Breeders Rights in Australia.
Resumo:
Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.
Resumo:
Laboratory-based relationships that model the phytotoxicity of metals using soil properties have been developed. This paper presents the first field-based phytotoxicity relationships. Wheat(Triticum aestivum L) was grown at 11 Australian field sites at which soil was spiked with copper (Cu) and zinc (Zn) salts. Toxicity was measured as inhibition of plant growth at 8 weeks and grain yield at harvest. The added Cu and Zn EC10 values for both endpoints ranged from approximately 3 to 4760 mg/kg. There were no relationships between field-based 8-week biomass and grain yield toxicity values for either metal. Cu toxicity was best modelled using pH and organic carbon content while Zn toxicity was best modelled using pH and the cation exchange capacity. The best relationships estimated toxicity within a factor of two of measured values. Laboratory-based phytotoxicity relationships could not accurately predict field-based phytotoxicity responses.
Resumo:
To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.
Resumo:
Partial least squares regression models on NIR spectra are often optimised (for wavelength range, mathematical pretreatment and outlier elimination) in terms of calibration terms of validation performance with reference to totally independent populations.
Resumo:
Table beet production in the Lockyer Valley of south-eastern Queensland is known to be adversely affected by soilborne root disease from infection by Pythium spp. However, little is known regarding the species or genotypes that are the causal agents of both pre- and post-emergence damping off. Based on RFLP analysis with HhaI, HinfI and MboI of the PCR amplified ITS region DNA from soil and diseased plant samples, the majority of 130 Pythium isolates could be grouped into three genotypes, designated LVP A, LVP B and LVP C. These groups comprised 43, 41 and 7% of all isolates, respectively. Deoxyribonucleic acid sequence analysis of the ITS region indicated that LVP A was a strain of Pythium aphanidermatum, with greater than 99% similarity to the corresponding P. aphanidermatum sequences from the publicly accessible databases. The DNA sequences from LVP B and LVP C were most closely related to P. ultimum and P. dissotocum, respectively. Lower frequencies of other distinct isolates with unique RFLP patterns were also obtained with high levels of similarity (>97%) to P. heterothallicum, P. periplocum and genotypes of P. ultimum other than LVP B. Inoculation trials of 1- and 4-week-old beet seedlings indicated that compared with isolates of the LVP B genotype, a higher frequency of LVP A isolates caused disease. Isolates with the LVP A, LVP B and LVP C genotypes were highly sensitive to the fungicide Ridomil MZ, which suppressed radial growth on V8 agar between approximately four and thirty fold at 5 μg/mL metalaxyl and 40 μg/mL mancozeb, a concentration far lower than the recommended field application rate.
Resumo:
Coolamon is a mid-season to late-season flowering F4-derived crossbred subterranean clover of var. subterraneum, developed by the collaborating organisations of the National Annual Pasture Legume Improvement Program. It is a replacement for Junee and has been selected for release on the basis of its greater herbage production and persistence, and its resistance to both known races of clover scorch. Coolamon is recommended for sowing in Western Australia, New South Wales, Victoria, South Australia and Queensland. It is best suited to well-drained, moderately acidic soils in areas with a growing season of 6.5-8 months that extends into November. Coolamon is best suited to phase farming and permanent pasture systems. It can also be used in cropping rotations, but at least 2 years of pasture are required between crops. Coolamon has been granted Plant Breeders Rights in Australia.
Resumo:
Izmir is a hardseeded, early flowering, subterranean clover of var. subterraneum (Katz. et Morley) Zohary and Heller collected from Turkey and developed by the collaborating organisations of the National Annual Pasture Legume Improvement Program. It is a more hardseeded replacement for Nungarin and best suited to well-drained, moderately acidic soils in areas with a growing season of less than 4.5 months. Izmir seed production and regeneration densities in 3-year pasture phases were similar to Nungarin in 21 trials across southern Australia, but markedly greater in years following a crop or no seed set. Over all measurements, Izmir produced 10% more winter herbage and 7% more spring herbage than Nungarin. Its greater hardseededness and good seed production, makes it better suited to cropping rotations than Nungarin. Softening of Izmir hard seeds occurs later in the summer–autumn period than Nungarin, giving it slightly greater protection from seed losses following false breaks to the season. Izmir is recommended for sowing in Western Australia, New South Wales, Victoria, South Australia and Queensland. Izmir has been granted Plant Breeders Rights in Australia.
Resumo:
The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet market specifications. The concepts of cellular hyperplasia and hypertrophy are integral components of the Davis Growth Model. The net synthesis of total body fat (kg) is calculated from the net energy available after accounting tor energy needs for maintenance and protein synthesis. Total body fat (kg) is then partitioned into 4 fat depots (intermuscular, intramuscular, subcutaneous, and visceral). This paper reports on the parameter estimation and sensitivity analysis of the DNA (deoxyribonucleic acid) logistic growth equations and the fat deposition first-order differential equations in the Davis Growth Model using acslXtreme (Hunstville, AL, USA, Xcellon). The DNA and fat deposition parameter coefficients were found to be important determinants of model function; the DNA parameter coefficients with days on feed >100 days and the fat deposition parameter coefficients for all days on feed. The generalized NL2SOL optimization algorithm had the fastest processing time and the minimum number of objective function evaluations when estimating the 4 fat deposition parameter coefficients with 2 observed values (initial and final fat). The subcutaneous fat parameter coefficient did indicate a metabolic difference for frame sizes. The results look promising and the prototype Davis Growth Model has the potential to assist the beef industry meet market specifications.
Resumo:
Time to first root in cuttings varies under different environmental conditions and understanding these differences is critical for optimizing propagation of commercial forestry species. Temperature environment (15, 25, 30 or 35 +/- A 2A degrees C) had no effect on the cellular stages in root formation of the Slash x Caribbean Pine hybrid over 16 weeks as determined by histology. Initially callus cells formed in the cortex, then tracheids developed and formed primordia leading to external roots. However, speed of development followed a growth curve with the fastest development occurring at 25A degrees C and slowest at 15A degrees C with rooting percentages at week 12 of 80 and 0% respectively. Cutting survival was good in the three cooler temperature regimes (> 80%) but reduced to 59% at 35A degrees C. Root formation appeared to be dependant on the initiation of tracheids because all un-rooted cuttings had callus tissue but no tracheids, irrespective of temperature treatment and clone.
Resumo:
Time to first root in cuttings varies under different environmental conditions and understanding these differences is critical for optimizing propagation of commercial forestry species. Temperature environment (15, 25, 30 or 352C) had no effect on the cellular stages in root formation of the Slash * Caribbean Pine hybrid over 16 weeks as determined by histology. Initially callus cells formed in the cortex, then tracheids developed and formed primordia leading to external roots. However, speed of development followed a growth curve with the fastest development occurring at 25C and slowest at 15C with rooting percentages at week 12 of 80 and 0% respectively. Cutting survival was good in the three cooler temperature regimes (>80%) but reduced to 59% at 35C. Root formation appeared to be dependant on the initiation of tracheids because all un-rooted cuttings had callus tissue but no tracheids, irrespective of temperature treatment and clone.
Resumo:
Understanding the effects of different types and quality of data on bioclimatic modeling predictions is vital to ascertaining the value of existing models, and to improving future models. Bioclimatic models were constructed using the CLIMEX program, using different data types – seasonal dynamics, geographic (overseas) distribution, and a combination of the two – for two biological control agents for the major weed Lantana camara L. in Australia. The models for one agent, Teleonemia scrupulosa Stål (Hemiptera:Tingidae) were based on a higher quality and quantity of data than the models for the other agent, Octotoma scabripennis Guérin-Méneville (Coleoptera: Chrysomelidae). Predictions of the geographic distribution for Australia showed that T. scrupulosa models exhibited greater accuracy with a progressive improvement from seasonal dynamics data, to the model based on overseas distribution, and finally the model combining the two data types. In contrast, O. scabripennis models were of low accuracy, and showed no clear trends across the various model types. These case studies demonstrate the importance of high quality data for developing models, and of supplementing distributional data with species seasonal dynamics data wherever possible. Seasonal dynamics data allows the modeller to focus on the species response to climatic trends, while distributional data enables easier fitting of stress parameters by restricting the species envelope to the described distribution. It is apparent that CLIMEX models based on low quality seasonal dynamics data, together with a small quantity of distributional data, are of minimal value in predicting the spatial extent of species distribution.