New sweetpotato cultivars to meet market needs

The Australian Sweetpotato Growers Association partnered researchers from Agri-Science Queensland (with co-funding from Horticulture Australia Limited) to identify new, high performing sweetpotato cultivars with diverse colours and tastes. The project evaluated a mix of purple, red, orange and white skin and flesh, tailored for Australian growers and consumers. Australia's sweetpotato market currently relies on one gold cultivar for 90% of national production. Major retailers were requesting a reliable supply of quality sweetpotatoes in emerging categories such as red or white skin or purple flesh. To identify suitable cultivars, over 40 new sweetpotato cultivars were virus tested, and extensively evaluated in multiple experiments in Queensland and northern New South Wales. Larger-scale plantings by growers, using standard agronomy, provided additional performance feedback under commercial conditions. In partnership with growers and wholesalers, cultivars were evaluated in field and laboratory for desired characteristics such as shape, size range, skin and flesh colour, estimates of productivity and suitability for commercial production, cooking characteristics and taste. New high performing gold cultivars had better soil insect and nematode tolerance than the current cultivars. The new colours offered diverse health-related opportunities for consumers, more anthocyanins in purple-fleshed cultivars; higher beta carotene content in new gold fleshed cultivars; and potentially lower GI in white-fleshed cultivars. To enhance adoption, the industry/research partnership will tailor agronomic guidelines to maximise on-farm performance and identify niche marketing pathways for each of the cultivars. Increased consumption of this versatile vegetable will drive sweetpotato industry development and expansion into the future.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).