Rapid assessment of protein structural changes from frost damage: A proof-of-concept study using Pittosporum spinescens (Apiales)

Frost damage remains an important driver of floral ecological dynamics in certain areas of the Australian landscape. However, the responses of native Australian species to frost damage remain largely understudied. Here, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, conducted on intact leaves, was used to monitor changes in the protein secondary structures of Pittosporum spinescens upon exposure to below-zero temperatures. The dominant secondary structures present in fresh leaves were the inter-molecular aggregates (40%), α-helices (20%), β-sheets (15%) and random coil structures (14%). During simulated severe frost (−18 °C), a reduction in α-helices and increase in the amount of inter-molecular structures were observed, followed by transmutation of the latter into anti-parallel β-sheets or another form of inter-molecular structures. After 6 h, the dominant protein secondary structures were anti-parallel β-sheets and inter-molecular aggregates (ca. 64% and 17%, respectively), with only small amounts of α-helices (4%), β-sheets (9%) and random coil structures (5%) present. Overall, this indicates a reduction in the organisation level of protein secondary structures, resulting in a probable loss of function and considerable damage to the functional activity of any proteins in the leaves. The technique of ATR-FTIR spectroscopy should be considered by future researchers interested in investigating responses to frost damage in other species, particularly at an ecological level. Portable FTIR instrumentation would greatly expand the potential range of applications

Near-infrared spectroscopy (NIRS) for taxonomic entomology: A brief review

For over two decades, near-infrared spectroscopy (NIRS) has been applied to a wide spectrum of problems in the field of insect taxonomy. It provides a rapid, non-destructive and relatively cheap method of metabolomic profiling, which can often be used to discriminate closely related species in the same genus. Furthermore, very little training or entomological knowledge is required to operate the instrument. However, a taxonomist is still required to ensure accurate identification of samples used for NIRS model creation and validation. To date, most research has focused on species of economic or epidemiological importance, such as mosquitoes, flies or stored product pests. However, an increasing number of studies are applying NIRS for entomological research with a purely “academic” purpose. As research continues in this field, NIRS has the potential to become more widely accepted in entomology, allowing for the rapid metabolomic profiling of thousands of species. © 2020 Blackwell Verlag Gmb

Quantification and distribution of a Tetragonula carbonaria swarm (Hymenoptera: Apidae)

Manual mark-by-mark image analysis was used to quantify the number of individuals present in a Tetragonula carbonaria swarm. A total of 7328 bees were identified in the swarm. The distribution of individuals within the swarm followed a Gaussian distribution, with the distances to the nearest neighbour strongly positively skewed. The clustering of bees in the centre of the swarm is likely a mechanism for reducing predation risk. In the case of male mating swarms, large aggregations may increase the mating success of the species. © 2020 Korean Society of Applied Entomolog

An overview of near-infrared spectroscopy (NIRS) for the detection of insect pests in stored grains

Applications of near-infrared spectroscopy for measuring various aspects of grain quality have expanded rapidly in recent years. One application that could be of particular use to growers and industry is the detection of insect pests across a range of stored grains. This prospect was first reported over 20 years ago, but the accuracy of this technique does not currently meet FDA standards for the quantification of insect fragments in bulk wheat and flour samples. When considering bulk samples, near-infrared spectroscopy may be suitable for identifying the presence of infestation in samples, followed by flotation testing to provide an accurate quantitative value. Much higher accuracy has been found for the detection of pest species at the single-kernel level. With faster spectrophotometers and kernel sorting systems, single-kernel analysis is likely to be utilised more in the future and could even render bulk analysis of samples redundant. This technology could allow for the detection and identification of pest species in every single kernel of a representative grain sample. The development and application of more sensitive spectrophotometers, such as FT-NIR (Fourier transform near infrared) and more powerful chemometric data analysis techniques are also likely to provide significant improvements, through allowing the minute chemical differences present in bulk infested grains to be accurately detected and quantified

Discrimination of centre composition in panned chocolate goods using nearinfrared spectroscopy

Non-destructively identifying the centre composition of panned chocolate goods may be useful in quality assurance settings. However, no studies to date have investigated this topic. In this study, nearinfrared spectra (1000–2500 nm) were collected from chocolate-coated peanuts and chocolate-coated sultanas (n = 170 of each) in order to investigate the prospect of non-invasively detecting the composition of the centre. Principal component analysis confirmed that the spectra of these samples were distinct from one another. The partial least squares discriminant analysis (PLS-DA) model showed a high level of separation between chocolate-coated peanuts and sultanas in the training set (R2 = 0.95; RPD = 4.4). Discrimination between peanut and sultana samples from an independent test set was also possible, although with slightly less distinct separation between the sample types. A soft independent modelling by class analogy model was also able to differentiate between the two sample types, albeit with higher levels of misclassification compared to PLS-DA. Incorporating samples from different manufacturers may be useful for improving the broader applicability of the model

Observations on the common brown butterfly (Heteronympha merope) in the early 1900s in Australia using digitized specimens

The Common Brown butterfly, Heteronympha merope (Fabricius 1775), is a ubiquitous species from the family Nymphalidae, distributed across south-eastern Australia. Using online photographs of 33 digitized museum specimens provided by the Atlas of Living Australia, forewing length was found to be highly correlated with the total wing surface area (r = 0.962), indicating that this metric can be used as an accurate estimate of body size. No significant relationship was found between body size and environmental temperatures, latitude, or the year of collection (1902–1948). The size of females was higher between October and December compared to the rest of the year, while the size of males did not change. Collection of contemporary data on the body size of H. merope would allow the assessment of whether the body size of this species has changed over the past 70 years

Investigation of the phenolic and antioxidant content in Australian grains using traditional and non-invasive analytical techniques

Recent years have seen the emergence of the concept of “functional foods”– where the value of food products is based on their health-benefiting properties in addition to their basic nutritional value. Globally, the functional food market is worth US $170 billion and is projected to grow at 7.5% p.a. over the next 10 years. In order to capitalise on this lucrative emerging market, producers and wholesalers need to demonstrate that their products contain high levels of these desirable compounds. This is typically assessed through time-consuming, expensive analytical techniques such as high-performance liquid chromatography (HPLC) or liquid chromatography-mass spectrometry (LC-MS). While these methods provide a high level of specificity and sensitivity, more rapid analytical techniques may be better suited to the routine, near-real-time analysis of large numbers of samples. Furthermore, there is currently a lack of basic context data on the typical levels of bioactive compounds that are found in many crops grown under Australian conditions, particularly for grain crops. This lack of context data makes it challenging to know whether a particular product would be considered high or low quality from a functional food perspective. Consequently, the first major aim of this project was to profile the typical levels of bioactive compounds present in economically significant grain crops grown in Australia – specifically faba bean, wheat, mungbean and chickpea. The major focus was on phenolic compounds, as these possess high levels of antioxidant activity and are found in relatively high levels in grain crops. Furthermore, this class of compounds is associated with a wide range of health benefits, particularly for the prevention of cardiovascular disease. Using spectrophotometric methods and HPLC analysis, moderate differences were found in the phenolic contents and antioxidant capacity of different varieties from each crop. This was particularly noted for the ten varieties of faba bean analysed, where there was a 121% difference in total phenolic content (TPC) between the varieties with the lowest and highest contents. This pulse also contained the highest total phenolic contents (258-571 mg GAE/100 g) and ferric reducing antioxidant potential (237-531 mg TE/100 g) of all crops investigated. The five mungbean varieties showed lower levels and more minor differences in phenolic content (79-105 mg GAE/100 g; 32% variation between varieties) and cupric reducing antioxidant capacity (498-584 mg TE/100 g; 17% variation), while the while the ferric reducing antioxidant potential did not differ significantly between varieties (14-20 mg TE/100 g). However, the content of numerous phenolic compounds (p-hydroxybenzoic acid, vanillic acid, caffeic acid, sinapic acid, trans-ferulic acid, cinnamic acid and vitexin) were significantly different between the mungbean varieties investigated. Similar observations were made for the chickpea samples, where there were moderate differences in total phenolic content (73-94 mg GAE/100 g; 29% variation) and ferric reducing antioxidant potential (25-40 mg TE/100 g; 62% variation) between varieties. Again, the content of most phenolic acids analysed by HPLC were significantly different between varieties. Although varietal differences were not examined for wheat, the TPC of the 65 samples was higher than mungbean and chickpea (130-180 mg GAE/100 g), while the ferric reducing antioxidant potential ranged from 14-64 mg TE/100 g. In addition to the varietal differences, the impact of growing location and season on phenolic content and antioxidant capacity were investigated in faba bean. Although these variables had no effect on the total phenolic content, the growing location did alter the levels of several individual phenolic compounds (protocatechuic, vanillic and chlorogenic acids, as well as the flavonoids vitexin and rutin). The second major aim of this project was to investigate the prospect of infrared spectroscopy as a rapid technique for the prediction of phenolic content and antioxidant capacity in Australian grain crops. Promising results were found for the estimation of total phenolic content and antioxidant capacity in faba bean and wheat flour, particularly using near-infrared spectroscopy. The NIR model for TPC showed an R2test of 0.66 and RMSEP of 76 mg GAE/100 g when applied to faba bean, and an R2test of 0.86 and RMSEP of 4 mg GAE/100 g in wheat. However, infrared spectroscopy was unable to predict the concentrations of these analytes in mungbean or chickpea flour. This may be due to additional matrix constituents obscuring the analyte signals in the infrared region, or a consequence of the lower phenolic/antioxidant contents in these crops. Nevertheless, the overall results suggest that infrared spectroscopy could be used for the estimation of total phenolic content or antioxidant capacity (i.e., prediction of high or low contents) in certain grain crops. This technique could potentially be applied for the routine screening of bioactive constituents, helping Australian producers to capitalise on the growing domestic and international functional food markets. Monitoring bioactive compound levels in Australian grain – either through traditional or non-invasive analytical techniques – could provide an additional level of quality assurance for producers of functional food crops and help maintain Australia’s global recognition as a producer of high-quality food

An Introduction to Atmospheric Pollutant Dispersion Modelling

Modelling the dispersion of atmospheric pollutants plays an important role in regulatory and epidemiological settings. Although the majority of modelling concepts were developed in the 1980s, a significant amount of optimisation and refinement of dispersion models has occurred since this time. In addition, some completely novel models such as computational fluid dynamics have emerged. Furthermore, next generation models are continually improving the accuracies of the results obtained. This review provides a non-technical outline of the mechanisms of atmospheric pollutant dispersion modelling and discusses common model types and their applications

Rapid Prediction of Leaf Water Content in Eucalypt Leaves Using a Handheld NIRS Instrument

Leaf water content (LWC) is a crucial physiological parameter that plays a limiting role in the efficiency of photosynthesis and biomass production in many plants. This study investigated the use of diffuse reflectance near-infrared spectroscopy (NIRS) for the rapid prediction of the gravimetric LWC in eucalypt leaves from Eucalyptus and Corymbia genera. The best-performing model for LWC gave a R2pred of 0.85 and RMSEP of 2.32% for an independent test set, indicating that the handheld NIR instrument could predict the LWC with a high level of accuracy. The use of support vector regression gave slightly more accurate results compared with partial least squares regression. Prediction models were also developed for leaf thickness, although these were somewhat less accurate (R2pred of 0.58; RMSEP of 2.7 µm). Nevertheless, the results suggest that handheld NIR instruments may be useful for in-field screening of LWC and leaf thickness in Australian eucalypt species. As an example of its use, the NIR method was applied for rapid analysis of the LWC and leaf thickness of every leaf found on an E. populnea sapling

Seeing red: A review of the use of near-infrared spectroscopy (NIRS) in entomology

Near-infrared spectroscopy (NIRS) is a rapid, noninvasive and cheap method of profiling the chemical composition of a broad range of sample types. Over the past two decades, it has been used in numerous entomological applications, ranging from taxonomy and metabolomic profiling to the prediction of insect age and sex. This review provides a perspective on the historical and contemporary applications of NIRS for entomology. Two areas that show particular promise are the detection and identification of insects infesting stored food products, and the rapid, low-cost and non-lethal profiling of cuticular hydrocarbons of individual insects