Feasibility of detecting aflatoxin B1 on inoculated maize kernels surface using Vis/NIR hyperspectral imaging.

The feasibility of using a visible/near-infrared hyperspectral imaging system with a wavelength range between 400 and 1000 nm to detect and differentiate different levels of aflatoxin B1 (AFB1 ) artificially titrated on maize kernel surface was examined. To reduce the color effects of maize kernels, image analysis was limited to a subset of original spectra (600 to 1000 nm). Residual staining from the AFB1 on the kernels surface was selected as regions of interest for analysis. Principal components analysis (PCA) was applied to reduce the dimensionality of hyperspectral image data, and then a stepwise factorial discriminant analysis (FDA) was performed on latent PCA variables. The results indicated that discriminant factors F2 can be used to separate control samples from all of the other groups of kernels with AFB1 inoculated, whereas the discriminant factors F1 can be used to identify maize kernels with levels of AFB1 as low as 10 ppb. An overall classification accuracy of 98% was achieved. Finally, the peaks of ß coefficients of the discrimination factors F1 and F2 were analyzed and several key wavelengths identified for differentiating maize kernels with and without AFB1 , as well as those with differing levels of AFB1 inoculation. Results indicated that Vis/NIR hyperspectral imaging technology combined with the PCA-FDA was a practical method to detect and differentiate different levels of AFB1 artificially inoculated on the maize kernels surface. However, indicated the potential to detect and differentiate naturally occurring toxins in maize kernel.

Detection by hyperspectral imaging of shiga toxin-producing Escherichia coli serogroups O26, O45, O103, O111, O121, and O145 on rainbow agar.

The U.S. Department of Agriculture, Food Safety Inspection Service has determined that six non-O157 Shiga toxin-producing Escherichia coli (STEC) serogroups (O26, O45, O103, O111, O121, and O145) are adulterants in raw beef. Isolate and phenotypic discrimination of non-O157 STEC is problematic due to the lack of suitable agar media. The lack of distinct phenotypic color variation among non-O157serogroups cultured on chromogenic agar poses a challenge in selecting colonies for confirmation. In this study, visible and near-infrared hyperspectral imaging and chemometrics were used to detect and classify non-O157 STEC serogroups grown on Rainbow agar O157. The method was first developed by building spectral libraries for each serogroup obtained from ground-truth regions of interest representing the true identity of each pixel and thus each pure culture colony in the hyperspectral agar-plate image. The spectral library for the pure-culture non-O157 STEC consisted of 2,171 colonies, with spectra derived from 124,347 of pixels. The classification models for each serogroup were developed with a k nearest-neighbor classifier. The overall classification training accuracy at the colony level was 99%. The classifier was validated with ground beef enrichments artificially inoculated with 10, 50, and 100 CFU/ml STEC. The validation ground-truth regions of interest of the STEC target colonies consisted of 606 colonies, with 3,030 pixels of spectra. The overall classification accuracy was 98%. The average specificity of the method was 98% due to the low false-positive rate of 1.2%. The sensitivity ranged from 78 to 100% due to the false-negative rates of 22, 7, and 8% for O145, O45, and O26, respectively. This study showed the potential of visible and near-infrared hyperspectral imaging for detecting and classifying colonies of the six non-O157 STEC serogroups. The technique needs to be validated with bacterial cultures directly extracted from meat products and positive identification of colonies by using confirmatory tests such as latex agglutination tests or PCR.

Classification and structural analysis of live and dead Salmonella cells using Fourier transform infrared spectroscopy and principal component analysis.

Fourier transform infrared spectroscopy (FT-IR) was used to detect Salmonella Typhimurium and Salmonella Enteritidis food-borne bacteria and to distinguish between live and dead cells of both serotypes. Bacteria cells were prepared in 10(8) cfu/mL concentration, and 1 mL of each bacterium was loaded individually on the ZnSe attenuated total reflection (ATR) crystal surface (45° ZnSe, 10 bounces, and 48 mm × 5 mm effective area of analysis on the crystal) and scanned for spectral data collection from 4000 to 650 cm(-1) wavenumber. Analysis of spectral signatures of Salmonella isolates was conducted using principal component analysis (PCA). Spectral data were divided into three regions such as 900-1300, 1300-1800, and 3000-2200 cm(-1) based on their spectral signatures. PCA models were developed to differentiate the serotypes and live and dead cells of each serotype. Maximum classification accuracy of 100% was obtained for serotype differentiation as well as for live and dead cells differentiation. Soft independent modeling of class analogy (SIMCA) analysis was carried out on the PCA model and applied to validation sample sets. It gave a predicted classification accuracy of 100% for both the serotypes and its live and dead cells differentiation. The Mahalanobis distance calculated in three different spectral regions showed maximum distance for the 1800-1300 cm(-1) region, followed by the 3000-2200 cm(-1) region, and then by the 1300-900 cm(-1) region. It showed that both of the serotypes have maximum differences in their nucleic acids, DNA/RNA backbone structures, protein, and amide I and amide II bands.

Evaluation of activation of G proteins in response to thyroid stimulating hormone in thyroid gland cells from euthyroid and hyperthyroid cats.

OBJECTIVE: To evaluate alterations in ligand-stimulated activity of G proteins in thyroid gland cells of hyperthyroid cats. SAMPLE POPULATION: Membranes of thyroid gland cells isolated from 5 hyperthyroid cats and 3 age-matched euthyroid (control) cats immediately after the cats were euthanatized. PROCEDURES: Isolated thyroid cell membranes were treated with thyroid-stimulating hormone (TSH), and activation of G protein was quantified by measurement of the binding of guanosine triphosphate gamma labeled with sulfur 35 (GTPgamma(35)S). The separate effects of G-protein inhibitory (G(i)) and G-protein stimulatory (G(s)) proteins were determined by the use of pertussis toxin and cholera toxin, respectively. RESULTS: Thyroid cell membranes from hyperthyroid cats had higher basal GTPgamma(35)S binding than did thyroid cell membranes from euthyroid cats. Thyroid cell membranes from hyperthyroid and euthyroid cats had a concentration-dependent increase in TSH-stimulated GTPgamma(35)S binding over the TSH range of 0 to 100 mU/mL, with maximal activity at 1 to 100 mU/mL for both. The percentage increase in GTPgamma(35)S binding stimulated by TSH was similar in magnitude between the membranes from hyperthyroid and euthyroid cats. The TSH-stimulated activation of G(s) and G(i) was not different between euthyroid and hyperthyroid cats. CONCLUSIONS AND CLINICAL RELEVANCE: Ligand-stimulated activation of G proteins was the same in thyroid cell membranes obtained from hyperthyroid and euthyroid cats. Therefore, alterations in inherent G(s) or G(i) activities did not appear to be part of the pathogenesis of hyperthyroidism in cats.

Comparison of FTIR spectra between Huanglongbing (citrus greening) and other citrus maladies.

Fourier transform infrared (FTIR) spectroscopy has the ability to quickly identify the presence of specific carbohydrates in plant materials. The presence of the disease huanglongbing (HLB) in the leaves of infected citrus plants has a distinctive spectrum that can be used to distinguish an infected plant from a healthy plant. However, many citrus diseases display similar visible symptoms and are of concern to citrus growers. In this study several citrus diseases (citrus leaf rugose virus, citrus tristeza virus, citrus psorosis virus, and Xanthomonas axonopodis ) and nutrient deficiencies (iron, copper, zinc, manganese, and magnesium) were compared with HLB using FTIR spectroscopy to determine if the spectra alone can be used to identify plants that are infected with HLB instead of another disease. The results indicate that the spectra of some diseases and deficiencies more closely resemble those of apparently healthy plants and some share the carbohydrate transformation that has been seen in the spectra of HLB-infected plants.

Detection of citrus Huanglongbing by Fourier transform infrared-attenuated total reflection spectroscopy.

Citrus Huanglongbing (HLB, also known as citrus greening disease) was discovered in Florida in 2005 and is spreading rapidly amongst the citrus growing regions of the state. Detection via visual symptoms of the disease is not a long-term viable option. New techniques are being developed to test for the disease in its earlier presymptomatic stages. Fourier transform infrared-attenuated total reflection (FT-IR-ATR) spectroscopy is a candidate for rapid, inexpensive, early detection of the disease. The mid-infrared region of the spectrum reveals dramatic changes that take place in the infected leaves when compared to healthy non-infected leaves. The carbohydrates that give rise to peaks in the 900-1180 cm(-1) range are reliable in distinguishing leaves from infected plants versus non-infected plants. A model based on chemometrics was developed using the spectra from 179 plants of known disease status. This model then correctly predicted the status of >95% of the plants tested.

Two-dimensional correlation analysis of visible/near-infrared spectral intensity variations of chicken breasts with various chilled and frozen storages.

Generalized two-dimensional (2D) correlation analysis of visible/near-infrared (NIR) spectra was performed to characterize the spectral intensity variations of chicken muscles induced by either storage time/temperature regime or shear force values. The results showed that intensities of two visible bands at 445 and 560 nm increase with the storage temperature under identical treatment, possibly indicating a color change due to frozen storage. The 2D NIR correlation spectra indicated that all NIR bands reduce their spectral intensities, probably due to the water loss and compositional alterations during the freeze-thaw process as well as the tenderization development in muscle storage. The heterospectra correlating the spectral bands in both visible and NIR regions exhibited a strong correlation and suggested the sequential change between color and other developments in muscles. In addition, shear value-induced NIR spectral intensity variations detected significant differences in spectral features between tender and tough muscles.

Prediction of color, texture, and sensory characteristics of beef steaks by visible and near infrared reflectance spectroscopy. A feasibility study.

Color, instrumental texture, and sensory attributes of steaks from 24 beef carcasses at 2, 4, 8, 14, and 21 days post mortem were predicted by visible/near infrared (visible/NIR) reflectance spectroscopy in 400-1080 nm region. Predicting the Hunter a, b, and E* yielded the coefficient of determination (R(2)) in calibration to be 0.78-0.90, and R(2) was between 0.49 and 0.55 for tenderness, Hunter L, sensory chewiness and juiciness. The prediction R(2) for tenderness was in the range of 0.22-0.72 when the samples were segregated according to the aging days. Based on partial least square (PLS) model predicted tenderness, beef samples were classified into tender and tough classes with a correct classification of 83%. Soft independent modeling of class analogy of principal component analysis (SIMCA/PCA) model of measured tenderness showed great promise in the classification of tender and tough meats with over 96% success.