Comparison of the indirect haemagglutination and gel diffusion test for serotyping Haemophilus parasuis

The aim of this study was to compare the use of indirect haemagglutination (IHA) and gel diffusion (GD) tests for serotyping Haemophilus parasuis by the Kielstein-Rapp-Gabrielson scheme. All 15 serovar reference strains, 72 Australian field isolates, nine Chinese field isolates, and seven isolates from seven experimentally infected pigs were evaluated with both tests. With the IHA test, 14 of the 15 reference strains were correctly serotyped – with serovar 10 failing to give a titre with serovar 10 antiserum. In the GD test, 13 reference strains were correctly serotyped – with antigen from serovars 7 and 8 failing to react with any antiserum. The IHA methodology serotyped a total of 45 of 81 field isolates while the GD methodology serotyped a total of 48 isolates. For 29 isolates, the GD and IHA methods gave discordant results. It was concluded that the IHA is a good additional test for the serotyping of H. parasuis by the KRG scheme if the GD methodology fails to provide a result or shows unusual cross-reactions.

A digital imaging technique to quantify the incidence of internal browning in potato (Solanum tuberosum) tubers

Internal browning disorders, including brown fleck (BF), in potato (Solanum tuberosum) tubers greatly reduce tuber quality, but the causes are not well understood. This is due, in part, to the highly variable data provided by visual value-based rating systems. A digital imaging technique was developed to quantify accurately the incidence of internal browning in potato tubers. Images of tuber sections were scanned using a flatbed scanner and digitally enhanced to highlight tuber BF lesions, and the area of affected tissue calculated using pixel quantification software. Digital imaging allowed for the determination of previously unused indices of the incidence and severity of internal browning in potato tubers. Statistical analysis of the comparison between digitally derived and visual-rating BF data from a glasshouse experiment showed that digital data greatly improved the delineation of treatment effects. The F-test probability was further improved through square root or logarithmic data transformations of the digital data, but not of the visual-rating data. Data from a field experiment showed that the area of tuber affected by BF and the number of small BF lesions increased with time and with increase in tuber size. The results from this study indicate that digital imaging of internal browning disorders of potato tubers holds much promise in determining their causes that heretofore have proved elusive.

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.

Multispectral imaging and genomic mapping

Identifying QTLs linked to malting and protein levels in barley using multispectral image data.