γ-Irradiation effects on appearance and aroma of 'Kensington Pride' mango fruit

γ-Irradiation doses of 0.5 (target) and 1.0 (high) kGy were applied as insect disinfestation treatments to 'Kensington Pride' mango fruit. The effects of these treatments on fruit physicochemical properties and aroma volatile production were investigated and compared to non-irradiated controls. There were no significant effects of the irradiation treatments on flesh total soluble solids content. However, the loss of green skin colour usually associated with fruit ripening was inhibited by irradiation at both 0.5 and 1.0 kGy by approximately 32 and 52%, respectively, relative to non-irradiated fruit. Fruit exposed to 0.5 and 1.0 kGy exhibited a 58 and 80% reduction in emission of a-terpinolene volatiles, respectively. Thus, γ-irradiation at 0.5 and 1.0 kGy can have an adverse effect on 'Kensington Pride' mango fruit aroma volatile production and skin colouration.

Effect of nitrogen on the skin colour and other quality attributes of ripe ‘Kensington Pride’ mango (Mangifera indica L.) fruit

Near-ripe ‘Kensington Pride’ mango (Mangifera indica L.) fruit with green skin colour generally return lower wholesale and retail prices. Pre-harvest management, especially nitrogen (N) nutrition, appears to be a major causal factor. To obtain an understanding of the extent of the problem in the Burdekin district (dry tropics; the major production area in Australia), green mature ‘Kensington Pride’ mango fruit were harvested from ten orchards and ripened at 20 ± 0.5 O C. Of these orchards, 70% produced fruit with more than 25% of the skin surface area green when ripe. The following year, the effect of N application on skin colour and other quality attributes was investigated on three orchards, one with a high green (HG) skin problem and two with a low green (LG) skin problem. N was applied at pre-flowering and at panicle emergence at the rate of 0,75,150,300 g per tree (soil applied) or 50 g per tree as foliar N for the HG orchard, and 0,150,300,450 g per tree (soil applied) or 50 g per tree (foliar) for the LG orchards. In all orchards the proportion of green colour on the ripe fruit was significantly (P<0.05) higher with soil applications of 150 g N or more per tree. Foliar sprays resulted in a higher proportion of green colour than the highest soil treatment in the HG orchard, but not in the LG orchards. Anthracnose disease severity was significantly (P<0.05) higher with 300 g of N per tree or foliar treatment in the HG orchard, compared with no additional N. Thus, N can reduce mango fruit quality by increasing green colour and anthracnose disease in ripe fruit.

Reducing Browning of Fresh-cut ‘Maha’ Carambola with Chemical Additives and Low-oxygen Atmospheres

The greatest attraction to using carambola (Averrhoa carambola L.) in the fresh-cut market is the star shape that the fruit presents after a transverse cut. Carambola is well-suited for minimal processing, but cut surface browning is a main cause of deterioration. This problem is exacerbated as a result of mechanical injuries occurring during processing and is mainly induced by the leakage of phenolic compounds from the vacuole and subsequent oxidation by polyphenol oxidase (PPO) (Augustin et al., 1985). The use of browning inhibitors in processed fruits is restricted to compounds that are non-toxic, ‘wholesome’, and that do not adversely affect taste and flavour (Gil et al., 1998). In the past, browning was mainly controlled by the action of sulphites, but the use of this compound has declined due to allergic reactions in asthmatics (Weller et al., 1995). The shelf life of fresh-cut products may be extended by a combination of oxygen exclusion and the use of enzymatic browning inhibitors. The objectives of this work were to determine the effects of: (1) post-cutting chemical treatments of ascorbic, citric, oxalic acids, and EDTA-Ca; (2) atmospheric modification; and (3) combinations of the above, on the shelf life of carambola slices based on appearance, colour and polyphenol oxidase activity

Modelling Leaf Production and Crop Development in Maize (Zea mays L.) After Tassel Initiation Under Diverse Conditions of Temperature and Photoperiod

Prediction of the initiation, appearance and emergence of leaves is critically important to the success of simulation models of crop canopy development and some aspects of crop ontogeny. Data on leaf number and crop ontogeny were collected on five cultivars of maize differing widely in maturity and genetic background grown under natural and extended photoperiods, and planted on seven sowing dates from October 1993 to March 1994 at Gatton, South-east Queensland. The same temperature coefficients were established for crop ontogeny before silking, and the rates of leaf initiation, leaf tip appearance and full leaf expansion, the base, optimum and maximum temperatures for each being 8, 34 and 40 degrees C. After silking, the base temperature for ontogeny was 0 degrees C, but the optimum and maximum temperatures remained unchanged. The rates of leaf initiation, appearance of leaf tips and full leaf expansion varied in a relatively narrow range across sowing times and photoperiod treatments, with average values of 0.040 leaves (degrees Cd)-1, 0.021 leaves (degrees Cd)-1, and 0.019 leaves (degrees Cd)-1, respectively. The relationships developed in this study provided satisfactory predictions of leaf number and crop ontogeny (tassel initiation to silking, emergence to silking and silking to physiological maturity) when assessed using independent data from Gatton (South eastern Queensland), Katherine and Douglas Daly (Northern Territory), Walkamin (North Queensland) and Kununurra (Western Australia).

Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: An integrated modelling approach in maize.

Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

Climatic-requirements models of cat's claw creeper Macfadyena unguis-cati (Bignoniaceae) to prioritise areas for exploration and release of biological control agents

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.

Between-tree variation in fruit quality and fruit mineral concentrations of Hass avocados

Inconsistent internal fruit quality in Hass avocados affects consumer confidence. To determine the influence of individual trees on fruit quality, Hass avocado fruit were harvested from adjacent trees of similar external appearance in 3 commercial orchards in 1998 and 1 orchard in 1999. The trees in each orchard were grown with similar commercial practices and in similar soil types. Within each location, there were significant (P<0.05) differences in the mean ripe fruit quality between trees with respect to fruit body rot severity (mainly anthracnose) with and without cold storage, internal disorders severity due to diffuse discolouration and vascular browning (after cold storage), days to ripen, percentage dry matter, and the percentage of the skin area with purple-black colour when ripe. These effects were also noted in the same orchard in 1999. There were significant (P<0.05) differences in fruit flesh calcium, magnesium, potassium, boron and zinc concentrations between trees. Significant (P<0.05) correlations were observed between average fruit mineral concentrations in each tree (particularly calcium, magnesium and potassium) and body rot severity, percentage dry matter and fruit mass. There was little conclusive evidence that characteristics such as the growth of the non-suberised roots or the degree of scion under- or overgrowth was involved in these tree effects; however, differences between trees with respect to other rootstock characteristics may be involved. The inconsistency of the correlations across sites and years suggested that other factors apart from tree influences could also affect the relationship between fruit minerals and fruit quality.

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.

The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials

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.

Models for the field-based toxicity of copper and zinc salts to wheat in 11 Australian soils and comparison to laboratory-based models

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.

Modelling environmental effects on phenology and canopy development of diverse sorghum genotypes

The ability to predict phenology and canopy development is critical in crop models used for simulating likely consequences of alternative crop management and cultivar choice strategies. Here we quantify and contrast the temperature and photoperiod responses for phenology and canopy development of a diverse range of elite Indian and Australian sorghum genotypes (hybrid and landrace). Detailed field experiments were undertaken in Australia and India using a range of genotypes, sowing dates, and photoperiod extension treatments. Measurements of timing of developmental stages and leaf appearance were taken. The generality of photo-thermal approaches to modelling phenological and canopy development was tested. Environmental and genotypic effects on rate of progression from emergence to floral initiation (E-FI) were explained well using a multiplicative model, which combined the intrinsic development rate (Ropt), with responses to temperature and photoperiod. Differences in Ropt and extent of the photoperiod response explained most genotypic effects. Average leaf initiation rate (LIR), leaf appearance rate and duration of the phase from anthesis to physiological maturity differed among genotypes. The association of total leaf number (TLN) with photoperiod found for all genotypes could not be fully explained by effects on development and LIRs. While a putative effect of photoperiod on LIR would explain the observations, other possible confounding factors, such as air-soil temperature differential and the nature of model structure were considered and discussed. This study found a generally robust predictive capacity of photo-thermal development models across diverse ranges of both genotypes and environments. Hence, they remain the most appropriate models for simulation analysis of genotype-by-management scenarios in environments varying broadly in temperature and photoperiod.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

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%.

The sensitivity of updated NIR PLS models for fruit sorting to initial parameter settings

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.

Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme.

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.