(Z)-11-Hexadecenal and (3Z,6Z,9Z)-Tricosatriene: Sex Pheromone Components of the Red Banded Mango Caterpillar Deanolis sublimbalis

The sex pheromone of the red banded mango caterpillar, Deanolis sublimbalis (Lepidoptera: Crambidae), a serious pest of the mango Mangifera indica (Anacardiaceae) in India and Southeast Asia and a recent invader into northern Australia, has been identified. Three candidate compounds were identified from pheromone gland extracts of female moths, using gas chromatography (GC), GC-electroantennographic detection and GC-mass spectrometric analyses, in conjunction with dimethyldisulfide derivatization. Field bioassays established that both (Z)-11-hexadecenal (Z11-16:Ald) and (3Z,6Z,9Z)-tricosatriene (3Z,6Z,9Z-23:Hy) were required for attraction of male D. sublimbalis moths, and 1,000 μg of a 1:1 mix of Z11-16:Ald and 3Z,6Z,9Z-23:Hy was more attractive to male moths than caged virgin females. However, the binary blend was only attractive when the isomeric purity of the monounsaturated aldehyde was >99%, suggesting that the (E)-isomer was inhibitory. Although (Z)-11-hexadecen-1-ol (Z11-16:OH) was tentatively identified in gland extracts, the addition of this compound to the binary blend did not increase the numbers of moths captured. The pheromone can now be used in integrated pest management strategies.

Fungal colonization of sago starch in Papua New Guinea

Sago starch is an important source of dietary carbohydrates in lowland Papua New Guinea. Over the past 30 years there have been sporadic reports of severe illness following consumption of sago starch. A common assumption is that fungal metabolites might be associated with the illness, leading to the need for a more thorough investigation of the mycoflora of sago starch. Sago starch was collected from areas of high sago consumption in Papua New Guinea for fungal analysis (69 samples). Storage methods and duration were recorded at the time of collection and pH on arrival at the laboratory. Yeasts were isolated from all samples except two, ranging from 1.2 × 103 to 8.3 × 107 cfu/g. Moulds were isolated from 65 of the 69 samples, ranging from 1.0 × 102 to 3.0 × 106 cfu/g. Of 44 samples tested for ergosterol content, 42 samples showed the presence of fungal biomass. Statistical analyses indicated that sago starch stored for greater than five weeks yielded significantly higher ergosterol content and higher numbers of moulds than sago stored for less than five weeks. The method of storage was also shown to influence mould numbers with storage in natural woven fibre containers returning significantly greater numbers than present in other storage methods tested. Potentially mycotoxigenic genera of moulds including Aspergillus and Penicillium were commonly isolated from sago starch, and as such storage factors that influence the growth of these and other filamentous fungi might contribute to the safety of traditional sago starch in PNG.

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.

Influence of plant traits on production costs and profitability of strawberry in southeast Queensland.

In Queensland the subtropical strawberry ( Fragaria * ananassa) breeding program aims to combine traits into novel genotypes that increase production efficiency. The contribution of individual plant traits to cost and income under subtropical Queensland conditions was investigated, with the overall goal of improving the profitability of the industry through the release of new strawberry cultivars. The study involved specifying the production and marketing system using three cultivars of strawberry that are currently widely grown annually in southeast Queensland, developing methods to assess the economic impact of changes to the system, and identifying plant traits that influence outcomes from the system. From May through September P (price; $ punnet -1), V (monthly mass; tonne of fruit on the market) and M (calendar month; i.e. May=5) were found to be related ( r2=0.92) by the function (SE) P=4.741(0.469)-0.001630(0.0005) V-0.226(0.102) M using data from 2006 to 2010 for the Brisbane central market. Both income and cost elements in the gross margin were subject to sensitivity analysis. 'Harvesting' and 'Handling/Packing' 'Groups' of 'Activities' were the major contributors to variable costs (each >20%) in the gross margin analysis. Within the 'Harvesting Group', the 'Picking Activity' contributed most (>80%) with the trait 'display of fruit' having the greatest (33%) influence on the cost of the 'Picking Activity'. Within the 'Handling/Packing Group', the 'Packing Activity' contributed 50% of costs with the traits 'fruit shape', 'fruit size variation' and 'resistance to bruising' having the greatest (12-62%) influence on the cost of the 'Packing Activity'. Non-plant items (e.g. carton purchases) made up the other 50% of the costs within the 'Handling/Packing Group'. When any of the individual traits in the 'Harvesting' and 'Handling/Packing' groups were changed by one unit (on a 1-9 scale) the gross margin changed by up to 1%. Increasing yield increased the gross margin to a maximum (15% above present) at 1320 g plant -1 (94% above present). A 10% redistribution of total yield from September to May increased the gross margin by 23%. Increasing fruit size increased gross margin: a 75% increase in fruit size (to ~30 g) produced a 22% increase in the gross margin. The modified gross margin analysis developed in this study allowed simultaneous estimation of the gross margin for the producer and gross value of the industry. These parameters sometimes move in opposite directions.