Sweetpotato consumer research: insights to increasing consumption

This report provides an evaluation of the behaviours and purchasing drivers of key sweetpotato consumers defined by Nielsen consumer research as Established Couples (two or more adults with no children 17 and under, and head of house 35-59), Senior Couples (two or more adults with no children 17 or under, and head of house 60 or over), and Independent Singles (one person household 35 or over, no children 17 or under). Research was qualitative in nature. Methods used included focus groups, depth interviews and shop-a-longs. The report found that preferences for sweetpotato amongst these groups were varied. In general a smaller torpedo shaped vegetable was valued for ease of preparation and the convenience of being of sufficient size for a meal for two. Satisfaction with sweetpotato was high with negative comments on quality exceedingly rare within discussions. However, shop-a-longs revealed that some quality issues were apparent at retail such as withered product, pitting and occasionally damage. A display with stock resting in any amount of water was a barrier to purchase for consumers and this was apparent on two out 15 occasions. A high quality sweetpotato was of a deep orange/red colour, had a smooth skin and was extremely dense and hard. An inferior sweetpotato was wrinkly, spongy, pitted and damaged. Awareness of sweetpotato was a relatively recent phenomenon amongst the respondents of this study with most recalling eating the vegetable in the last five to 10 years. Life-time eating patterns emerged as a consequence of childhood food experiences such as growing up with a ‘meat and three’ veg philosophy and traditional Australian meals. However, this was dependent on cultural background and those with ties to diverse cultures were more likely to have always known of the vegetable. Sweetpotato trial and consumption coincided with a breaking away from these traditional patterns, or was integrated into conventional meals such as a baked vegetable to accompany roasts. Increased health consciousness also led to awareness of the vegetable. A primary catalyst for consumption within the Established and Senior Couples groups was the health benefits associated with sweetpotato. Consumers had very little knowledge of the specific health properties of the vegetable and were surprised at the number of benefits consumption provided. Sweetpotato was important for diabetics for its low Glycemic Index status. Top-of-the-mind awareness of the vegetable resulted from the onset of the disease. Increasing fibre was a key motive for this demographic and this provided a significant link between consumption and preventing bowel cancer. For those on a weight loss regime, sweetpotato was perceived as a tasty, satisfying food that was low in carbohydrates. Swapping behaviours where white potato was replaced by sweetpotato was often a response to these health concerns. Other health properties mentioned by participants through the course of the research included the precursor β-carotene and Vitamins A & C. The sweetpotato was appreciated for its hedonic and timesaving qualities. For consumers with a high involvement in food, the vegetable was valued for its versatility in meals. These consumers took pride in cooking and the flavour and texture of sweetpotato lent itself to a variety of meals such as soups, salads, roasts, curries, tagines and so on. Participants who had little time or desire to prepare and cook meals valued sweetpotato because it was an easy way to add colour and variety to the plate and because including an orange vegetable to meals is a shortcut to ensuring vitamin intake. Several recommendations are made to the sweetpotato industry. • Vigorously promote the distinct nutritional and health properties of sweetpotatoes, particularly if they can be favourably compared to other vegetables or foods • Promote the salient properties to specific targets such as diabetics, those that are at risk to bowel cancer, and those embarking on a weight-loss regime. Utilise specialist channels of communication such as diabetic magazines and websites • Promote styles of cooking of sweetpotato that would appeal to traditionalists such as roasts and BBQs • Promote the vegetable as a low maintenance vegetable, easy to store, easy to cook and particularly focusing on it as a simple way to boost the appearance and nutritional value of meals. • Promote the vegetable to high food involvement consumers through exotic recipes and linking it to feelings of accomplishment with cooking • Promote the versatility of the vegetable • Devise promotions that link images and tone of communications with enjoying life to the fullest, having time to enjoy family and grandchildren, and of partaking in social activities • Educate retailers on consumer perceptions of quality and ensuring moisture and mould is not present at displays Qualitative information while providing a wealth of detail cannot be extrapolated to the overall target population and this may be considered a limitation to the research. However, within research theory, effective quantitative design is believed to stem from the insights developed from qualitative studies. • Develop and implement a quantitative study on sweetpotato attitudes and behaviours based on the results of this study.

Pleopod Cuticular Morphology as an Index of Moult Stage in the Ornate Rock Lobster, Panulirus ornatus (Fabricius 1789)

Seven discrete stages and substages of moulting in the ornate rock lobster, Panulirus ornatus, have been distinguished by microscopic examination of the cuticle and setae of the pleopods . The diagnostic features and the duration of each of the stages are described. Freezing did not visually alter the tissue features used to identify each moult stage. Pleopod morphology can reliably indicate whether a lobster has moulted within the previous 24 h or is within 72 h of the next ecdysis.

Development of a stable isotope index to assess decadal-scale vegetation change and application to woodlands of the Burdekin catchment, Australia

Forty-four study sites were established in remnant woodland in the Burdekin River catchment in tropical north-east Queensland, Australia, to assess recent (decadal) vegetation change. The aim of this study was further to evaluate whether wide-scale vegetation 'thickening' (proliferation of woody plants in formerly more open woodlands) had occurred during the last century, coinciding with significant changes in land management. Soil samples from several depth intervals were size separated into different soil organic carbon (SOC) fractions, which differed from one another by chemical composition and turnover times. Tropical (C4) grasses dominate in the Burdekin catchment, and thus δ13C analyses of SOC fractions with different turnover times can be used to assess whether the relative proportion of trees (C3) and grasses (C4) had changed over time. However, a method was required to permit standardized assessment of the δ13C data for the individual sites within the 13 Mha catchment, which varied in soil and vegetation characteristics. Thus, an index was developed using data from three detailed study sites and global literature to standardize individual isotopic data from different soil depths and SOC fractions to reflect only the changed proportion of trees (C3) to grasses (C3) over decadal timescales. When applied to the 44 individual sites distributed throughout the Burdekin catchment, 64% of the sites were shown to have experienced decadal vegetation thickening, while 29% had remained stable and the remaining 7% had thinned. Thus, the development of this index enabled regional scale assessment and comparison of decadal vegetation patterns without having to rely on prior knowledge of vegetation changes or aerial photography.

Spatial model of site index based on Y-ray spectrometry and a digital elevation model for two Pinus species in Tuan Toolara State Forest, Queensland, Australia

Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI).

Varying the spatial distribution of applied nitrogen (N) fertilizer to match demand in crops has been shown to increase profits in Australia. Better matching the timing of N inputs to plant requirements has been shown to improve nitrogen use efficiency and crop yields and could reduce nitrous oxide emissions from broad acre grains. Farmers in the wheat production area of south eastern Australia are increasingly splitting N application with the second timing applied at stem elongation (Zadoks 30). Spectral indices have shown the ability to detect crop canopy N status but a robust method using a consistent calibration that functions across seasons has been lacking. One spectral index, the canopy chlorophyll content index (CCCI) designed to detect canopy N using three wavebands along the "red edge" of the spectrum was combined with the canopy nitrogen index (CNI), which was developed to normalize for crop biomass and correct for the N dilution effect of crop canopies. The CCCI-CNI index approach was applied to a 3-year study to develop a single calibration derived from a wheat crop sown in research plots near Horsham, Victoria, Australia. The index was able to predict canopy N (g m-2) from Zadoks 14-37 with an r2 of 0.97 and RMSE of 0.65 g N m-2 when dry weight biomass by area was also considered. We suggest that measures of N estimated from remote methods use N per unit area as the metric and that reference directly to canopy %N is not an appropriate method for estimating plant concentration without first accounting for the N dilution effect. This approach provides a link to crop development rather than creating a purely numerical relationship. The sole biophysical input, biomass, is challenging to quantify robustly via spectral methods. Combining remote sensing with crop modelling could provide a robust method for estimating biomass and therefore a method to estimate canopy N remotely. Future research will explore this and the use of active and passive sensor technologies for use in precision farming for targeted N management.

Evaluating and validating abundance monitoring methods in the absence of populations of known size: review and application to a passive tracking index

Rarely is it possible to obtain absolute numbers in free-ranging populations and although various direct and indirect methods are used to estimate abundance, few are validated against populations of known size. In this paper, we apply grounding, calibration and verification methods, used to validate mathematical models, to methods of estimating relative abundance. To illustrate how this might be done, we consider and evaluate the widely applied passive tracking index (PTI) methodology. Using published data, we examine the rationality of PTI methodology, how conceptually animal activity and abundance are related and how alternative methods are subject to similar biases or produce similar abundance estimates and trends. We then attune the method against populations representing a range of densities likely to be encountered in the field. Finally, we compare PTI trends against a prediction that adjacent populations of the same species will have similar abundance values and trends in activity. We show that while PTI abundance estimates are subject to environmental and behavioural stochasticity peculiar to each species, the PTI method and associated variance estimate showed high probability of detection, high precision of abundance values and, generally, low variability between surveys, and suggest that the PTI method applied using this procedure and for these species provides a sensitive and credible index of abundance. This same or similar validation approach can and should be applied to alternative relative abundance methods in order to demonstrate their credibility and justify their use.