The effect of foliar sprays of the synthetic auxin 3-5-6 TPA, on fruit drop, fruit size and seed development in three lychee (Litchi chinensis) cultivars: Tai So, Fay Zee Sui and Kwai Mai Pink.

Fruit drop in lychee can cause major yield losses in Australia, the severity varying with cultivar and season. Research in China, South Africa and Israel has demonstrated the potential for synthetic auxins used as foliar sprays to reduce fruit drop in lychee. Trials were initiated in Australia to test the efficacy of the synthetic auxin, 3-5-6 Trichloro-2-phridyl-oxyacetic acid (3-5-6 TPA) at 50 ppm on the cultivars Tai So, Fay Zee Sui and Kwai Mai Pink. Results indicate that in most cases the TPA reduced natural fruit drop however the size of the fruit at the time of application affects the response and the ideal application time varies with cultivar; approximately 13 mm fruit length in 'Kwai Mai Pink', 20 mm in 'Fay Zee Sui' and 27 mm in 'Tai So'. If applied too early in 'Tai So', it caused an increase in fruit drop. The TPA was most effective when natural fruit drop was high, reducing fruit drop from 74.7 to 34.9% in 'Kwai Mai Pink' and least effective when natural fruit drop was low. An increase in the percentage of fruit with poorly developed (chicken tongue) seed and slightly larger fruit size was also observed in treated trees.

Remote sensing to implement an effective pest management strategy for canegrubs

Develop a remote-sensing system that can identify canegrub infestations and provide early- warning to growers via the internet.

Processing Tomato Production in the Burdekin: Opportunities and Risks for Growers

The research undertaken here was in response to a decision by a major food producer in about 2009 to consider establishing processing tomato production in northern Australia. This was in response to a lack of water availability in the Goulburn Valley region following the extensive drought that continued until 2011. The high price of water and the uncertainty that went with it was important in making the decision to look at sites within Queensland. This presented an opportunity to develop a tomato production model for the varieties used in the processing industry and to use this as a case study along with rice and cotton production. Following some unsuccessful early trials and difficulties associated with the Global Financial Crisis, large scale studies by the food producer were abandoned. This report uses the data that was collected prior to this decision and contrasts the use of crop modelling with simpler climatic analyses that can be undertaken to investigate the impact of climate change on production systems. Crop modelling can make a significant contribution to our understanding of the impacts of climate variability and climate change because it harnesses the detailed understanding of physiology of the crop in a way that statistical or other analytical approaches cannot do. There is a high overhead, but given that trials are being conducted for a wide range of crops for a variety of purposes, breeding, fertiliser trials etc., it would appear to be profitable to link researchers with modelling expertise with those undertaking field trials. There are few more cost-effective approaches than modelling that can provide a pathway to understanding future climates and their impact on food production.

A highly effective and selective male lure for Bactrocera jarvisi (Tryon) (Diptera: Tephritidae)

Bactrocera jarvisi (Tryon) is a moderate pest fruit fly particularly in northern Australia where mango is its main commercial host. It was largely considered non-responsive to the known male lures. However, male B. jarvisi are attracted to the flowers of Bulbophyllum baileyi, Passiflora ligularis, Passiflora maliformis and Semecarpus australiensis and this paper describes an attempt to determine the attractive compounds in the latter two species through chemical analysis. At about the same time, zingerone was identified as a fruit fly attractant in the flowers of Bulbophyllum patens in Malaysia, and this led the author to speculate that it could be attracting B. jarvisi to the flowers of B. baileyi. Two long-term traps, each with lures containing 2 g of liquefied zingerone and 1 mL maldison EC were established at Speewah, west of Cairns, in November 2001 and retained until April 2007. Over five complete years, 68 897 flies were captured, of which 99.6% were male B. jarvisi. Annual peaks in activity occurred between mid-January and early February, when they averaged 1428.5 +/- 695.6 (mean +/- standard error) male B. jarvisi/trap/week. Very few B. jarvisi were caught between June and September. Among 12 other species of Bactrocera and Dacus attracted to zingerone were the previously non-lure responsive Bactrocera aglaiae, a new species Bactrocera speewahensis, and the rarely trapped Dacus secamoneae. Four separate trials were conducted over 8- to 19-week periods to compare the numbers and species of Bactrocera and Dacus caught by zingerone, raspberry ketone/cue-lure or methyl eugenol-baited traps. Overall, 27 different species of Bactrocera and Dacus were recorded. The zingerone-baited traps caught 97.799.3% male B. jarvisi and no methyl eugenol responsive flies. Significantly more Bactrocera neohumeralis or Bactrocera tryoni were attracted to raspberry ketone/cue-lure than to zingerone (P < 0.001). Zingerone and structurally related compounds should be tested more widely throughout the region.

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.