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.

Mango fruit peel and flesh extracts affect adipogenesis in 3T3-L1 cells

Obesity is associated with many chronic disease states, such as diabetes mellitus, coronary disease and certain cancers, including those of the breast and colon. There is a growing body of evidence that links phytochemicals with the inhibition of adipogenesis and protection against obesity. Mangoes (Mangifera indica L.) are tropical fruits that are rich in a diverse array of bioactive phytochemicals. In this study, methanol extracts of peel and flesh from three archetypal mango cultivars; Irwin, Nam Doc Mai and Kensington Pride, were assessed for their effects on a 3T3-L1 pre-adipocyte cell line model of adipogenesis. High content imaging was used to assess: lipid droplets per cell, lipid droplet area per cell, lipid droplet integrated intensity, nuclei count and nuclear area per cell. Mango flesh extracts from the three cultivars did not inhibit adipogenesis; peel extracts from both Irwin and Nam Doc Mai, however, did so with the Nam Doc Mai extract most potent at inhibiting adipogenesis. Peel extract from Kensington Pride promoted adipogenesis. The inhibition of adipogenesis by Irwin (100 mu g mL(-1)) and Nam Doc Mai peel extracts (50 and 100 mu g mL(-1)) was associated with an increase in the average nuclear area per cell; similar effects were seen with resveratrol, suggesting that these extracts may act through pathways similar to resveratrol. These results suggest that differences in the phytochemical composition between mango cultivars may influence their effectiveness in inhibiting adipogenesis, and points to mango fruit peel as a potential source of nutraceuticals.

Polyphenolic contents and the effects of methanol extracts from mango varieties on breast cancer cells

Bioactivities of peel and flesh extracts of 3 genetically diverse mango (Mangifera indica L.) varieties were studied. Nam Doc Mai peel extracts, containing the largest amounts of polyphenols, were associated with an effect on MCF-7 viable cell numbers with an IC50 (dose required for 50% inhibition of cell viability) of 56 μg/mL and significantly (p<0.01) induced cell death in MDA-MB-231 cells, compared with other varieties. Hydrophilic fractions of Nam Doc Mai peel extracts had the highest bioactivity values against both MCF-7 and MDA-MB-231 cells. Soluble polyphenols were present in the largest amounts in most hydrophilic fractions. The Nam Doc Mai mango variety contains high levels of fruit peel bioactivity, which appears to be related to the nature of the polyphenol composition.