Spiroacetal biosynthesis in insects from diptera to hymenoptera: The Giant Ichneumon wasp Megarhyssa nortoni nortoni Cresson

The volatile components of the mandibular gland secretion generated by the Giant Ichneumon parasitoid wasp Megarhyssa nortoni nortoni Cresson are mainly spiroacetals and methyl ketones, and all have an odd number of carbon atoms. A biosynthetic scheme rationalizing the formation of these diverse components is presented. This scheme is based on the results of incorporation studies using 2H-labeled precursors and [18O]dioxygen. The key steps are postulated to be decarboxylation of β-ketoacid equivalents, β-oxidation (chain shortening), and monooxygenase-mediated hydroxylation leading to a putative ketodiol that cyclizes to spiroacetals. The generality of the role of monooxygenases in spiroacetal formation in insects is considered, and overall, a cohesive, internally consistent theory of spiroacetal generation by insects is presented, against which future hypotheses will have to be compared.

Detecting the attributes of a wheat crop using digital imagery acquired from a low-altitude platform

A low-altitude platform utilising a 1.8-m diameter tethered helium balloon was used to position a multispectral sensor, consisting of two digital cameras, above a fertiliser trial plot where wheat (Triticum spp.) was being grown. Located in Cecil Plains, Queensland, Australia, the plot was a long-term fertiliser trial being conducted by a fertiliser company to monitor the response of crops to various levels of nutrition. The different levels of nutrition were achieved by varying nitrogen application rates between 0 and 120 units of N at 40 unit increments. Each plot had received the same application rate for 10 years. Colour and near-infrared images were acquired that captured the whole 2 ha plot. These images were examined and relationships sought between the captured digital information and the crop parameters imaged at anthesis and the at-harvest quality and quantity parameters. The statistical analysis techniques used were correlation analysis, discriminant analysis and partial least squares regression. A high correlation was found between the image and yield (R2 = 0.91) and a moderate correlation between the image and grain protein content (R2 = 0.66). The utility of the system could be extended by choosing a more mobile platform. This would increase the potential for the system to be used to diagnose the causes of the variability and allow remediation, and/or to segregate the crop at harvest to meet certain quality parameters.