Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis.

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images. PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.

Novel vaccine acceptance in emerging infectious diseases: a case study of Hendra virus vaccine uptake in Australia

Background: The development of a horse vaccine against Hendra virus has been hailed as a good example of a One Health approach to the control of human disease. Although there is little doubt that this is true, it is clear from the underwhelming uptake of the vaccine by horse owners to date (approximately 10%) that realisation of a One Health approach requires more than just a scientific solution. As emerging infectious diseases may often be linked to the development and implementation of novel vaccines this presentation will discuss factors influencing their uptake; using Hendra virus in Australia as a case study. Methods: This presentation will draw on data collected from the Horse owners and Hendra virus: A Longitudinal cohort study To Evaluate Risk (HHALTER) study. The HHALTER study is a mixed methods research study comprising a two-year survey-based longitudinal cohort study and qualitative interview study with horse owners in Australia. The HHALTER study has investigated and tracked changes in a broad range of issues around early uptake of vaccination, horse owner uptake of other recommended disease risk mitigation strategies, and attitudes to government policy and disease response. Interviews provide further insights into attitudes towards risk and decision-making in relation to vaccine uptake. A combination of quantitative and qualitative data analysis will be reported. Results: Data collected from more than 1100 horse owners shortly after vaccine introduction indicated that vaccine uptake and intention to vaccinate was associated with a number of risk perception factors and financial cost factors. In addition, concerns about side effects and veterinarians refusing to treat unvaccinated horses were linked to uptake. Across the study period vaccine uptake in the study cohort increased to more than 50%, however, concerns around side effects, equine performance and breeding impacts, delays to full vaccine approvals, and attempts to mandate vaccination by horse associations and event organisers have all impacted acceptance. Conclusion: Despite being provided with a safe and effective vaccine for Hendra virus that can protect horses and break the transmission cycle of the virus to humans, Australian horse owners have been reluctant to commit to it. General issues pertinent to novel vaccines, combined with challenges in the implementation of the vaccine have led to issues of mistrust and misconception with some horse owners. Moreover, factors such as cost, booster dose schedules, complexities around perceived risk, and ulterior motives attributed to veterinarians have only served to polarise attitudes to vaccine acceptance.

Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.