An evaluation of genetic analyses, skull morphology and visual appearance for assessing dingo purity: implications for dingo conservation

The introgression of domestic dog genes into dingo populations threatens the genetic integrity of 'pure' dingoes. However, dingo conservation efforts are hampered by difficulties in distinguishing between dingoes and hybrids in the field. This study evaluates consistency in the status of hybridisation (i.e. dingo, hybrid or dog) assigned by genetic analyses, skull morphology and visual assessments. Of the 56 south-east Queensland animals sampled, 39 (69.6%) were assigned the same status by all three methods, 10 (17.9%) by genetic and skull methods, four (7.1%) by genetic and visual methods; and two (3.6%) by skull and visual methods. Pair-wise comparisons identified a significant relationship between genetic and skull methods, but not between either of these and visual methods. Results from surveying 13 experienced wild dog managers showed that hybrids were more easily identified by visual characters than were dingoes. A more reliable visual assessment can be developed through determining the relationship between (1) genetics and phenotype by sampling wild dog populations and (2) the expression of visual characteristics from different proportions and breeds of domestic dog genes by breeding trials. Culling obvious hybrids based on visual characteristics, such as sable and patchy coat colours, should slow the process of hybridisation.

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.

Development of commercial application of an avocado fruit robustness test

Fruit quality is one of the major factors limiting growth in avocado retail sales. Avocado growers are often unaware of their end-use fruit quality since quality problems only manifest upon fruit ripening and growers receive limited feedback from the supply chain. If growers were aware of their expected fruit quality they would be equipped to make better marketing decisions and if necessary to take remedial actions to improve their fruit quality. Avotest is being developed as a quick and easy method of determining expected end-use fruit quality before the start of the commercial fruit harvest. The test aims at distinguishing between blocks with robust fruit and those with less robust fruit. The test could also be used to predict the resulting fruit quality after the implementation of new farming practices.

Sequence variation in the putative effector gene SIX8 facilitates molecular differentiation of Fusarium oxysporum f. sp. cubense

Fusarium oxysporum f. sp. cubense (Foc), causal agent of fusarium wilt of banana, is among the most destructive pathogens of banana and plantain. The development of a molecular diagnostic capable of reliably distinguishing between the various races of the pathogen is of key importance to disease management. However, attempts to distinguish isolates using the standard molecular loci typically used for fungal phylogenetics have been complicated by a poor correlation between phylogeny and pathogenicity. Among the available alternative loci are several putative effector genes, known as SIX genes, which have been successfully used to differentiate the three races of F. oxysporum f. sp. lycopersici. In this study, an international collection of Foc isolates was screened for the presence of the putative effector SIX8. Using a PCR and sequencing approach, variation in Foc-SIX8 was identified which allowed race 4 to be differentiated from race 1 and 2 isolates, and tropical and subtropical race 4 isolates to be distinguished from one another.