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 .

The use of heat-sums to predict harvest dates following potassium chlorate (KClO3) application in longan.

The ability to initiate and manipulate flowering with KClO3 allows flowering of longan, to be triggered outside of the normal flowering season (July-September) in Australia. Fruit maturity following normal flowering will occur approximately six-eight months (180-220 days) from flowering, depending on variety. Out of season flowering will result in differing times to maturity due to different temperature regimes during the maturity period. Knowing how long fruit will take to mature from different KClO3 application dates is potentially a valuable tool for growers to use as it would allow them to time their applications with market opportunities, e.g. Chinese New Year, periods of low volumes or periods of high prices. A simple heat-sum calculation was shown to reliably quantify fruit maturity periods, 2902 and 3432 growing degree days for Kohala and Biew Kiew respectively. Growers can use heat-sum as a predictive tool to allow for efficient planning of harvesting, packaging and freight requirements.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

Activating Mango Fruit Defence to Anthracnose Disease

The fungus causing anthracnose disease in mango, Colletotrichum gloeosporioides, (C g.), infects immature fruit early in the season, then enters a long latent phase. After harvest, when fruit start to ripen, the latency breaks and the fungus ramifies through the peel and pulp tissues causing black disease lesions. The breaking of pathogen latency in ripening mango fruit has been correlated with decreasing concentrations of the endogenous antifungal resorcinol compounds (Droby et al., 1986). The level of these antifungal resorcinols vary among mango cultivars (Droby et a1 , 1986). Controlling diseases by managing natural resistance of fruit to fungal attack could minimize the use of pesticides, which have become of major public concern on health and environmental grounds. The plant resistance activator benzo(l,2,3)thiadiazole-7-carbothioic acid S-methyl ester (trade name Bion®) has been widely reported as an effective inducer of systemic resistance. For example, Bion® was reported to induce pathogenesis-related proteins (PR proteins) and stimulate plant defence in peas (Dann and Deverall, 2000) and roses (Suo and Leung, 2001). However, until now, there is no information about the role of Bion® in activation of mango (cv. Kensington Pride) fruit resistance to anthracnose disease. The aim of this research is to determine the effect of resistance activators on defence responses of mango fruit to anthracnose disease.

Effects of Nutrition and Time of Weaning on Dry Season Liveweight Loss of Breeder Cows

In the seasonally dry tropics of northern Australia, breeder cows may lose up to 30% liveweight during the dry season when pasture is of low nutritive value. This is a major cause of low reproductive rates and high mortality. Weaning early in the dry season is effective to reduce this liveweight loss of the breeder (Holroyd et al. 1988). An experiment examined the dry season liveweight loss of breeders for a range of weaning times and levels of nutrition. From April to October through the dry season, 209 Bos indicus x Shorthorn cross cows 4-6 years of age grazed speargrass pastures in north Queensland. The cows had been joined with bulls from late January until April. Twenty-nine breeders had not suckled a calf during the previous wet season (DRY cows). In addition 180 cows lactating in April were weaned in late April, mid July or early September. The cows were allocated by stratified randomisation based on lactational status, stage of pregnancy and body condition to 15 x 40 ha paddocks. Five paddocks with low fertility soils provided LOW nutrition, while 10 paddocks with medium fertility soils and no supplementation or with supplementation provided MEDIUM and HIGH nutrition, respectively. The supplement consisted of molasses containing 14% urea offered ad libitum. Liveweight was measured at intervals and conceptus-free liveweight (CF-LW) calculated. Data were analyses by AOV within groups of paddocks. Animal production for a consuming world : proceedings of 9th Congress of the Asian-Australasian Association of Animal Production Societies [AAAP] and 23rd Biennial Conference of the Australian Society of Animal Production [ASAP] and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, [DRF]. 2-7 July 2000, Sydney, Australia.

Influence of nitrogen based supplements on live weight, fertility and mortality of heifers grazing dry season native pasture

Supplements containing urea or biuret were fed in the dry season to yearling and two year old pregnant heifers grazing native spear grass pastures in north Queensland. Liveweight change and survival during the dry season and fertility in the following year were measured. In the first experiment during a relatively favourable dry season, supplementation significantly (P<0.01) reduced liveweight loss in yearling heifers (5 vs. 32 kg). In the following year during a drought, supplement significantly (P<.01) reduced liveweight loss in yearling heifers (32 vs. 41 kg) and significantly (P <0.01) reduced mortalities (23.5% vs. 5.2%) in pregnant and lactating heifers. The supplement had no significant effect on subsequent fertility in either experiment. 14th Biennial Conference.

Management of white grubs (Coleoptera: Scarabaeidae) on groundnut in southern India

The chemical control of groundnut white grubs, Holotrichia serrata F. and H. reynaudi Blanchard (Coleoptera: Scarabaeidae), was studied in south--central India. Microplot trials demonstrated that chlorpyrifos and imidacloprid seed--dressings were effective against H. serrata at rates as low as 0.6 and 3.5 g a.i. kg-1, respectively, while microplot and on--farm trials showed that 1.2 and 3.5 g a.i. kg-1of chlorpyrifos and imidacloprid, respectively, were required for H. reynaudi. Chlorpyrifos residue analyses indicated that at 20 days after sowing (d.a.s.) rates up to 5.0 g a.i. kg-1 produced residues in soil and groundnut seedlings markedly below the relevant MRL, and no detectable residues at harvest under the southern Indian rainy--season environment. A farmer survey found that in Andhra Pradesh (AP), insecticides (chlorpyrifos and phorate) were applied for white grub control in 37.5% of farms sampled, while no insecticides were applied for this purpose in Karnataka and Tamil Nadu. The white grub density on farms in AP where insecticide had been applied averaged 0.07 larvae m-2, compared to 1.04 larvae m-2 in the remaining AP farms. In AP, Karnataka and Tamil Nadu, 70%, 42% and 39% of currently untreated groundnut fields, respectively, exceed the provisional economic threshold. A survey in the Anantapur district of AP found that farmer’s target and achieved rates for seed treatment averaged 0.44 and 0.52 g a.i. kg-1, both below optimal rates determined in microplot experiments. These data provide the foundation for an effective and sustainable program of management for groundnut white grubs in south--central India by providing key efficacy data and baseline data on farmer insecticide- use patterns.

Mango anthracnose disease: Present status and future research priorities

Occurrence and Importance: Anthracnose is presently recognized as the most important field and post-harvest disease of mango worldwide (Ploetz and Prakasli, 1997). It is the major disease limiting fruit production in all countries where mangoes are grown, especially where high humidity prevails during the cropping season. The post-harvest phase is the most damaging and economically significant phase of the disease worldwide. It directly affects the marketable fruit rendering it worthless. This phase is directly linked to the field phase where initial infection usually starts on young twigs and leaves and spreads to the flowers, causing blossom blight and destroying the inflorescences and even preventing fruit set.

Long-term impacts of harvest residue management on nutrition, growth and productivity of an exotic pine plantation of sub-tropical Australia

Residue retention is an important issue in evaluating the sustainability of production forestry. However, its long-term impacts have not been studied extensively, especially in sub-tropical environments. This study investigated the long-term impact of harvest residue retention on tree nutrition, growth and productivity of a F1 hybrid (Pinus elliottii var. elliottii × Pinus caribaea var. hondurensis) exotic pine plantation in sub-tropical Australia, under three harvest residue management regimes: (1) residue removal, RR0; (2) single residue retention, RR1; and (3) double residue retention, RR2. The experiment, established in 1996, is a randomised complete block design with 4 replicates. Tree growth measurements in this study were carried out at ages 2, 4, 6, 8 and 10 years, while foliar nutrient analyses were carried out at ages 2, 4, 6 and 10 years. Litter production and litter nitrogen (N) and phosphorus (P) measurements were carried out quarterly over a 15-month period between ages 9 and 10 years. Results showed that total tree growth was still greater in residue-retained treatments compared to the RR0 treatment. However, mean annual increments of diameter at breast height (MAID) and basal area (MAIB) declined significantly after age 4 years to about 68-78% at age 10 years. Declining foliar N and P concentrations accounted for 62% (p < 0.05) of the variation of growth rates after age 4 years, and foliar N and P concentrations were either marginal or below critical concentrations. In addition, litter production, and litter N and P contents were not significantly different among the treatments. This study suggests that the impact of residue retention on tree nutrition and growth rates might be limited over a longer period, and that the integration of alternative forest management practices is necessary to sustain the benefits of harvest residues until the end of the rotation.

Modelling climatic risks of aflatoxin contamination in maize

Aflatoxins are highly carcinogenic mycotoxins produced by two fungi, Aspergillus flavus and A. parasiticus, under specific moisture and temperature conditions before harvest and/or during storage of a wide range of crops including maize. Modelling of interactions between host plant and environment during the season can enable quantification of preharvest aflatoxin risk and its potential management. A model was developed to quantify climatic risks of aflatoxin contamination in maize using principles previously used for peanuts. The model outputs an aflatoxin risk index in response to seasonal temperature and soil moisture during the maize grain filling period using the APSIM's maize module. The model performed well in simulating climatic risk of aflatoxin contamination in maize as indicated by a significant R2 (P ≤ 0.01) between aflatoxin risk index and the measured aflatoxin B1 in crop samples, which was 0.69 for a range of rainfed Australian locations and 0.62 when irrigated locations were also included in the analysis. The model was further applied to determine probabilities of exceeding a given aflatoxin risk in four non-irrigated maize growing locations of Queensland using 106 years of historical climatic data. Locations with both dry and hot climates had a much higher probability of higher aflatoxin risk compared with locations having either dry or hot conditions alone. Scenario analysis suggested that under non-irrigated conditions the risk of aflatoxin contamination could be minimised by adjusting sowing time or selecting an appropriate hybrid to better match the grain filling period to coincide with lower temperature and water stress conditions.

Impacts of feeding system and season on milk composition and Cheddar cheese yield in a subtropical environment

Milk obtained from cows on 2 subtropical dairy feeding systems were compared for their suitability for Cheddar cheese manufacture. Cheeses were made in a small-scale cheesemaking plant capable of making 2 blocks ( about 2 kg each) of Cheddar cheese concurrently. Its repeatability was tested over 10 separate cheesemaking days with no significant differences being found between the 2 vats in cheesemaking parameters or cheese characteristics. In the feeding trial, 16 pairs of Holstein - Friesian cows were used in 2 feeding systems (M1, rain-grown tropical grass pastures and oats; and M5, a feedlot, based on maize/barley silage and lucerne hay) over 2 seasons ( spring and autumn corresponding to early and late lactation, respectively). Total dry matter, crude protein (kg/cow. day) and metabolisable energy (MJ/cow.day) intakes were 17, 2.7, and 187 for M1 and 24, 4, 260 for M5, respectively. M5 cows produced higher milk yields and milk with higher protein and casein levels than the M1 cows, but the total solids and fat levels were similar (P > 0.05) for both M1 and M5 cows. The yield and yield efficiency of cheese produced from the 2 feeding systems were also not significantly different. The results suggest that intensive tropical pasture systems can produce milk suitable for Cheddar cheese manufacture when cows are supplemented with a high energy concentrate. Season and stage of lactation had a much greater effect than feeding system on milk and cheesemaking characteristics with autumn ( late lactation) milk having higher protein and fat contents and producing higher cheese yields.

Odour emissions from anaerobic piggery ponds. 1. Results of a three season, 14-month survey

Odour emission rates were measured for seven different anaerobic ponds treating piggery wastes at six to nine discrete locations across the surface of each pond on each sampling occasion over a 14-month period. Emission rate values varied between ponds, between seasons for the same pond and even for the same pond on different days of a sampling week. Average seasonal emission rates ranged from 7.9 to 46.5 OU/m2 s, while average emission rates ranged from 16.0 to 29.0 OU/m2 s. Factors potentially responsible for the variability in emission rates were investigated, including air and pond liquor temperatures, time of day of sample collection, season and the impact of a prolonged drought.

Value-adding Australian sardines: Factors affecting rates of deterioration in sardine (Sardinops sagax) quality during post-harvest handling

Deficiencies in sardine post-harvest handling methods were seen as major impediments to development of a value-adding sector supplying Australian bait and human consumption markets. Factors affecting sardine deterioration rates in the immediate post-harvest period were investigated and recommendations made for alternative handling procedures to optimise sardine quality. Net to factory sampling showed that post-mortem autolysis was probably caused by digestive enzyme activity contributing to the observed temporal increase in sardine Quality Index. Belly burst was not an issue. Sardine quality could be maintained by reducing tank loading, and rapid temperature reduction using dedicated, on-board value-adding tanks. Fish should be iced between the jetty and the processing factory, and transport bins chilled using an efficient cooling medium such as flow ice.

Probabilistic forecasts of the onset of the north Australian wet season

The amount and timing of early wet-season rainfall are important for the management of many agricultural industries in north Australia. With this in mind, a wet-season onset date is defined based on the accumulation of rainfall to a predefined threshold, starting from 1 September, for each square of a 1° gridded analysis of daily rainfall across the region. Consistent with earlier studies, the interannual variability of the onset dates is shown to be well related to the immediately preceding July-August Southern Oscillation index (SOI). Based on this relationship, a forecast method using logistic regression is developed to predict the probability that onset will occur later than the climatological mean date. This method is expanded to also predict the probabilities that onset will be later than any of a range of threshold dates around the climatological mean. When assessed using cross-validated hindcasts, the skill of the predictions exceeds that of climatological forecasts in the majority of locations in north Australia, especially in the Top End region, Cape York, and central Queensland. At times of strong anomalies in the July-August SOI, the forecasts are reliably emphatic. Furthermore, predictions using tropical Pacific sea surface temperatures (SSTs) as the predictor are also tested. While short-lead (July-August predictor) forecasts are more skillful using the SOI, long-lead (May-June predictor) forecasts are more skillful using Pacific SSTs, indicative of the longer-term memory present in the ocean.