Raw Beef Patty Analysis Using Near-Infrared Hyperspectral Imaging: Identification of Four Patty Categories.

South African legislation regulates the classification/labelling and compositional specifications of raw beef patties, to combat processed meat fraud and to protect the consumer. A near-infrared hyperspectral imaging (NIR-HSI) system was investigated as an alternative authentication technique to the current destructive, time-consuming, labour-intensive and expensive methods. Eight hundred beef patties (ca. 100 g) were made and analysed to assess the potential of NIR-HSI to distinguish between the four patty categories (200 patties per category): premium 'ground patty'; regular 'burger patty'; 'value-burger/patty' and the 'econo-burger'/'budget'. Hyperspectral images were acquired with a HySpex SWIR-384 (short-wave infrared) imaging system using the Breeze® acquisition software, in the wavelength range of 952-2517 nm, after which the data was analysed using image analysis, multivariate techniques and machine learning algorithms. It was possible to distinguish between the four patty categories with accuracies ≥97%, indicating that NIR-HSI offers an accurate and reliable solution for the rapid identification and authentication of processed beef patties. Furthermore, this study has the potential of providing an alternative to the current authentication methods, thus contributing to the authenticity and fair-trade of processed meat products locally and internationally.

Differentiation of South African Game Meat Using Near-Infrared (NIR) Spectroscopy and Hierarchical Modelling.

Near-infrared (NIR) spectroscopy, combined with multivariate data analysis techniques, was used to rapidly differentiate between South African game species, irrespective of the treatment (fresh or previously frozen) or the muscle type. These individual classes (fresh; previously frozen; muscle type) were also determined per species, using hierarchical modelling. Spectra were collected with a portable handheld spectrophotometer in the 908-1676-nm range. With partial least squares discriminant analysis models, we could differentiate between the species with accuracies ranging from 89.8%-93.2%. It was also possible to distinguish between fresh and previously frozen meat (90%-100% accuracy). In addition, it was possible to distinguish between ostrich muscles (100%), as well as the forequarters and hindquarters of the zebra (90.3%) and springbok (97.9%) muscles. The results confirm NIR spectroscopy's potential as a rapid and non-destructive method for species identification, fresh and previously frozen meat differentiation, and muscle type determination.

Pharmacokinetic and Pharmacodynamic Analyses To Determine the Optimal Fixed Dosing Regimen of Iclaprim for Treatment of Patients with Serious Infections Caused by Gram-Positive Pathogens.

Iclaprim is a bacterial dihydrofolate reductase inhibitor that is currently being evaluated in two phase 3 trials for the treatment of patients with acute bacterial skin and skin structure infections (ABSSSI). Prior animal infection model studies suggest that the pharmacokinetic/pharmacodynamic (PK/PD) drivers for efficacy are area under the concentration-time curve from 0 to 24 h at steady state (AUC0-24ss), AUC/MIC, and time above the MIC during the dosing interval (T > MIC), while QTc prolongation was associated with the maximal concentration at steady state (Cmaxss) in a thorough QTc phase 1 study. Using PK data collected from 470 patients from the previously conducted phase 3 complicated skin and skin structure infection (cSSSI) trials, population PK modeling and Monte Carlo simulation (MCS) were used to identify a fixed iclaprim dosage regimen for the ongoing phase 3 ABSSSI studies that maximizes AUC0-24ss, AUC/MIC, and T > MIC while minimizing the probability of a Cmaxss of ≥800 ng/ml relative to the values for the previously employed cSSSI regimen of 0.8 mg/kg of body weight infused intravenously over 0.5 h every 12 h. The MCS analyses indicated that administration of 80 mg as a 2-h infusion every 12 h provides 28%, 28%, and 32% increases in AUC0-24ss, AUC/MIC, and T > MIC, respectively, compared to values for the 0.8-mg/kg cSSSI regimen, while decreasing the probability of a Cmaxss of ≥800 ng/ml, by 9%. Based on PK/PD analyses, 80 mg iclaprim administered over 2 h every 12 h was selected as the dosing scheme for subsequent phase 3 clinical trials.

Near infrared hyperspectral imaging in quality and safety evaluation of cereals.

The requirements of cereal research, as well as grading and evaluation of food products, have encouraged the development of nondestructive, rapid, and accurate analytical techniques to evaluate grain quality and safety. NIR hyperspectral imaging integrates spectroscopy and imaging techniques in one analytical system, allowing direct identification of chemical components and their distribution within the sample. It is a promising technique that may be implemented on-line, enabling the cereal industry to move away from subjective, manual classification and measuring methods. NIR hyperspectral imaging has gained popularity for rapidly acquiring information to enable the quantification, identification or differentiation of a variety of cereal properties. The technique can potentially replace multiple conventional chemical, microbial or physical tests with a single, automated image acquisition. Individual kernels can be analyzed nondestructively, enabling one to follow changes in the same kernel over time (e.g. fungal development). Although NIR hyperspectral imaging has not been extensively implemented in industry, it shows great potential for the development of an evaluation system to assess cereal grains, especially regarding variety discrimination and grading/classification properties. This review outlines the theory and principles of NIR hyperspectral imaging, and focuses specifically on its application in cereal science research and industry.

Differentiation of foodborne bacteria using NIR hyperspectral imaging and multivariate data analysis.

The potential for near-infrared (NIR) hyperspectral imaging and multivariate data analysis to be used as a rapid non-destructive tool for detection and differentiation of bacteria was investigated. NIR hyperspectral images were collected of Bacillus cereus, Escherichia coli, Salmonella enteritidis, Staphylococcus aureus and Staphylococcus epidermidis grown on agar for 20 h at 37 °C. Principal component analysis (PCA) was applied to mean-centred data. Standard normal variate (SNV) correction and the Savitzky-Golay technique was applied (2nd derivative, 3rd-order polynomial; 25 point smoothing) to wavelengths in the range of 1103 to 2471 nm. Chemical differences between colonies which appeared similar in colour on growth media (B. cereus, E. coli and S. enteritidis.) were evident in the PCA score plots. It was possible to distinguish B. cereus from E. coli and S. enteritidis along PC1 (59 % sum of squares (SS)) and between E. coli and S. enteritidis in the direction of PC2 (6.85 % SS). S. epidermidis was separated from B. cereus and S. aureus along PC1 (37.5 % SS) and was attributed to variation in amino acid and carbohydrate content. Two clusters were evident in the PC1 vs. PC2 PCA score plot for the images of S. aureus and S. epidermidis, thus permitting distinction between species. Differentiation between genera (similarly coloured on growth media), Gram-positive and Gram-negative bacteria and pathogenic and non-pathogenic species was possible using NIR hyperspectral imaging. Partial least squares discriminant analysis (PLS-DA) models were used to confirm the PCA data. The best predictions were made for B. cereus and Staphylococcus species, where results ranged from 82.0 to 99.96 % correctly predicted pixels.

Exploring the potential of hyperspectral imaging for microbial assessment of meat: A review.

Food safety is always of paramount importance globally due to the devasting social and economic effects of foodborne disease outbreaks. There is a high consumption rate of meat worldwide, making it an essential protein source in the human diet, hence its microbial safety is of great importance. The food industry stakeholders are always in search of methods that ensure safe food whilst maintaining food quality and excellent sensory attributes. Currently, there are several methods used in microbial food analysis, however, these methods are often time-consuming and do not allow real-time analysis. Considering the recent technological breakthroughs in artificial intelligence and machine learning, it raises the question of whether these advancements could be leveraged within the meat industry to improve turnaround time for microbial assessments. Hyperspectral imaging (HSI) is a highly prospective technology worth exploring for microbial analysis. The rapid, non-destructive method has the potential to be integrated into food production systems and allows foodborne pathogen detection in food samples, thus saving time. Although there has been a substantial increase in research on the utilisation of HSI in food applications over the past years, its use in the microbial assessment of meat is not yet optimal. This review aims to provide a basic understanding of the visible-near infrared HSI system, recent applications in the microbial assessment of meat products, challenges, and possible future applications.

Differentiation of Listeria monocytogenes serotypes using near infrared hyperspectral imaging.

Among the severe foodborne illnesses, listeriosis resulting from the pathogen Listeria monocytogenes exhibits one of the highest fatality rates. This study investigated the application of near infrared hyperspectral imaging (NIR-HSI) for the classification of three L. monocytogenes serotypes namely serotype 4b, 1/2a and 1/2c. The bacteria were cultured on Brain Heart Infusion agar, and NIR hyperspectral images were captured in the spectral range 900-2500 nm. Different pre-processing methods were applied to the raw spectra and principal component analysis was used for data exploration. Classification was achieved with partial least squares discriminant analysis (PLS-DA). The PLS-DA results revealed classification accuracies exceeding 80 % for all the bacterial serotypes for both training and test set data. Based on validation data, sensitivity values for L. monocytogenes serotype 4b, 1/2a and 1/2c were 0.69, 0.80 and 0.98, respectively when using full wavelength data. The reduced wavelength model had sensitivity values of 0.65, 0.85 and 0.98 for serotype 4b, 1/2a and 1/2c, respectively. The most relevant bands for serotype discrimination were identified to be around 1490 nm and 1580-1690 nm based on both principal component loadings and variable importance in projection scores. The outcomes of this study demonstrate the feasibility of utilizing NIR-HSI for detecting and classifying L. monocytogenes serotypes on growth media.

DHA is a more potent inhibitor of breast cancer metastasis to bone and related osteolysis than EPA.

Breast cancer patients often develop bone metastasis evidenced by osteolytic lesions, leading to severe pain and bone fracture. Attenuation of breast cancer metastasis to bone and associated osteolysis by fish oil, rich in EPA and DHA, has been demonstrated previously. However, it was not known whether EPA and DHA differentially or similarly affect breast cancer bone metastasis and associated osteolysis. In vitro culture of parental and luciferase gene encoded MDA-MB-231 human breast cancer cell lines treated with EPA and DHA revealed that DHA inhibits proliferation and invasion of breast cancer cells more potently than EPA. Intra-cardiac injection of parental and luciferase gene encoded MDA-MB-231 cells to athymic NCr nu/nu mice demonstrated that DHA-treated mice had significantly less breast cancer cell burden in bone, and also significantly less osteolytic lesions than EPA-treated mice. In vivo cell migration assay as measured by luciferase intensity revealed that DHA attenuated cell migration specifically to the bone. Moreover, the DHA-treated group showed reduced levels of CD44 and TRAP positive area in bone compared to EPA-treated group. Breast cancer cell burden and osteolytic lesions were also examined in intra-tibially breast cancer cell injected mice and found less breast cancer cell growth and associated osteolysis in DHA-treated mice as compared to EPA-treated mice. Finally, doxorubicin-resistant MCF-7 (MCF-7dox) human breast cancer cell line was used to examine if DHA can improve sensitization of MCF-7dox cells to doxorubicin. DHA improved the inhibitory effect of doxorubicin on proliferation and invasion of MCF-7dox cells. Interestingly, drug resistance gene P-gp was also down-regulated in DHA plus doxorubicin-treated cells. In conclusion, DHA attenuates breast cancer bone metastasis and associated osteolysis more potently than EPA, possibly by inhibiting migration of breast cancer cell to the bone as well as by inhibiting osteoclastic bone resorption.

Near-infrared (NIR) hyperspectral imaging and multivariate image analysis to study growth characteristics and differences between species and strains of members of the genus Fusarium.

Near-infrared (NIR) hyperspectral imaging was used to study three strains of each of three Fusarium spp. (Fusarium subglutinans, Fusarium proliferatum and Fusarium verticillioides) inoculated on potato dextrose agar in Petri dishes after either 72 or 96 h of incubation. Multivariate image analysis was used for cleaning the images and for making principal component analysis (PCA) score plots and score images and local partial least squares discriminant analysis (PLS-DA) models. The score images, including all strains, showed how different the strains were from each other. Using classification gradients, it was possible to show the change in mycelium growth over time. Loading line plots for principal component (PC) 1 and PC2 explained variation between the different Fusarium spp. as scattering and chemical differences (protein production), respectively. PLS-DA prediction results (including only the most important strain of each species) showed that it was possible to discriminate between species with F. verticillioides the least correctly predicted (between 16 and 47 % pixels correctly predicted). For F. subglutinans, 78-100 % pixels were correctly predicted depending on the training and test sets used. Similarly, the percentage correctly predicted values of F. proliferatum were 60-80 %. Visualisation of the mycelium radial growth in the PCA score images was made possible due to the use of NIR hyperspectral imaging. This is not possible with bulk spectroscopy in the visible or NIR regions.

Growth characteristics of three Fusarium species evaluated by near-infrared hyperspectral imaging and multivariate image analysis.

Colony growth of three Fusarium spp. on potato dextrose agar was followed by collecting near-infrared (NIR) hyperspectral images of the colonies at regular intervals after inoculation up to 55 h. After principal component analysis (PCA), two clusters were apparent in the score plot along principal component 1. Using the brushing technique, these clusters were divided into four groups of pixels with similar score values. These could be visualised as growth zones within the colonies in the corresponding score image. Three spectral bands, i.e. 1,166, 1,380 and 1,918 nm, were prominent in the multiplicative scatter corrected and Savitzky-Golay second derivative spectra. These indicated chemical changes, associated with carbohydrates (1,166 and 1,380 nm) and protein (1,918 nm), that occurred as the mycelium grew and matured. The protein band was more prominent in the mature fungal material while the carbohydrate band was less pronounced. The younger material and the agar were characterised by the carbohydrate spectral band. Integrating whole mycelium colonies as the sum of pixels over time made it possible to construct curves that resembled growth curves; this included the lag phase, active growth phase, deceleration phase and phase of constant growth. Growth profiles constructed from individual growth zones indicated more detailed growth characteristics. The use of NIR hyperspectral imaging and multivariate image analysis (MIA) allowed one to visualise radial growth rings in the PCA score images. This would not have been possible with bulk spectroscopy. Interpreting spectral data enabled better understanding of microbial growth characteristics on agar medium. NIR hyperspectral imaging combined with MIA is a powerful tool for the evaluation of growth characteristics of fungi.

The Imperative to Reimagine Assisted Living.

Assisted living (AL) has existed in the United States for decades, evolving in response to older adults' need for supportive care and distaste for nursing homes and older models of congregate care. AL is state-regulated, provides at least 2 meals a day, around-the-clock supervision, and help with personal care, but is not licensed as a nursing home. The key constructs of AL as originally conceived were to provide person-centered care and promote quality of life through supportive and responsive services to meet scheduled and unscheduled needs for assistance, an operating philosophy emphasizing resident choice, and a residential environment with homelike features. As AL has expanded to constitute half of all long-term care beds, the increasing involvement of the real estate, hospitality, and health care sectors has raised concerns about the variability of AL, the quality of AL, and standards for AL. Although the intent to promote person-centered care and quality of life has remained, those key constructs have become mired under tensions related to models of AL, regulation, financing, resident acuity, and the workforce. These tensions have resulted in a model of care that is not as intended, and which must be reimagined if it is to be an affordable care option truly providing quality, person-centered care in a suitable environment. Toward that end, 25 stakeholders representing diverse perspectives conferred during 2 half-day retreats to identify the key tensions in AL and discuss potential solutions. This article presents the background regarding those tensions, as well as potential solutions that have been borne out, paving the path to a better future of assisted living.

t10c12-CLA maintains higher bone mineral density during aging by modulating osteoclastogenesis and bone marrow adiposity.

Conjugated linoleic acid (CLA) has been shown to positively influence calcium and bone metabolism. Earlier, we showed that CLA (equal mixture of c9t11-CLA and t10c12-CLA) could protect age-associated bone loss by modulating inflammatory markers and osteoclastogenesis. Since, c9t11-CLA and t10c12-CLA isomers differentially regulate functional parameters and gene expression in different cell types, we examined the efficacy of individual CLA isomers against age-associated bone loss using 12 months old C57BL/6 female mice fed for 6 months with 10% corn oil (CO), 9.5% CO + 0.5% c9t11-CLA, 9.5% CO + 0.5% t10c12-CLA or 9.5% CO + 0.25% c9t11-CLA + 0.25% t10c12-CLA. Mice fed a t10c12-CLA diet maintained a significantly higher bone mineral density (BMD) in femoral, tibial and lumbar regions than those fed CO and c9t11-CLA diets as measured by dual-energy-X-ray absorptiometry (DXA). The increased BMD was accompanied by a decreased production of osteoclastogenic factors, that is, RANKL, TRAP5b, TNF-alpha and IL-6 in serum. Moreover, a significant reduction of high fat diet-induced bone marrow adiposity was observed in t10c12-CLA fed mice as compared to that of CO and c9t11-CLA fed mice, as measured by Oil-Red-O staining of bone marrow sections. In addition, a significant reduction of osteoclast differentiation and bone resorbing pit formation was observed in t10c12-CLA treated RAW 264.7 cell culture stimulated with RANKL as compared to that of c9t11-CLA and linoleic acid treated cultures. In conclusion, these findings suggest that t10c12-CLA is the most potent CLA isomer and it exerts its anti-osteoporotic effect by modulating osteoclastogenesis and bone marrow adiposity.

Fish oil decreases inflammation and reduces cardiac remodeling in rosiglitazone treated aging mice.

Clinical studies suggest that rosiglitazone (RSG) treatment may increase the incidence of heart failure in diabetic patients. In this study, we examined whether a high corn oil diet with RSG treatment in insulin resistant aging mice exerted metabolic and pro-inflammatory effects that stimulate cardiac dysfunction. We also evaluated whether fish oil attenuated these effects. Female C57BL/6J mice (13 months old) were divided into 5 groups: (1) lean control (LC), (2) corn oil, (3) fish oil, (4) corn oil+RSG and (5) fish oil+RSG. Mice fed a corn oil enriched diet and RSG developed hypertrophy of the left ventricle (LV) and decreased fractional shortening, despite a significant increase in total body lean mass. In contrast, LV hypertrophy was prevented in RSG treated mice fed a fish oil enriched diet. Importantly, hyperglycemia was controlled in both RSG groups. Further, fish oil+RSG decreased LV expression of atrial and brain natriuretic peptides, fibronectin and the pro-inflammatory cytokines interleukin-6 and tumor necrosis factor-α, concomitant with increased interleukin-10 and adiponectin levels compared to the corn oil+RSG group. Fish oil+RSG treatment suppressed inflammation, increased serum adiponectin, and improved fractional shortening, attenuating the cardiac remodeling seen in the corn oil+RSG diet fed C57BL/6J insulin resistant aging mice. Our results suggest that RSG treatment has context-dependent effects on cardiac remodeling and serves a negative cardiac role when given with a corn oil enriched diet.

Fish oil concentrate delays sensitivity to thermal nociception in mice.

Fish oil has been used to alleviate pain associated with inflammatory conditions such as rheumatoid arthritis. The anti-inflammatory property of fish oil is attributed to the n-3 fatty acids docosahexaenoic acid and eicosapentaenoic acid. Contrarily, vegetable oils such as safflower oil are rich in n-6 fatty acids which are considered to be mediators of inflammation. This study investigates the effect of n-3 and n-6 fatty acids rich oils as dietary supplements on the thermally induced pain sensitivity in healthy mice. C57Bl/6J mice were fed diet containing regular fish oil, concentrated fish oil formulation (CFO) and safflower oil (SO) for 6 months. Pain sensitivity was measured by Plantar test and was correlated to the expression of acid sensing ion channels (ASICs), transient receptor potential vanilloid 1 (TRPV1) and c-fos in dorsal root ganglion cells. Significant delay in sensitivity to thermal nociception was observed in mice fed CFO compared to mice fed SO (p<0.05). A significant diminution in expression of ion channels such as ASIC1a (64%), ASIC13 (37%) and TRPV1 (56%) coupled with reduced expression of c-fos, a marker of neuronal activation, was observed in the dorsal root ganglion cells of mice fed CFO compared to that fed SO. In conclusion, we describe here the potential of fish oil supplement in reducing sensitivity to thermal nociception in normal mice.

Non-Destructive Spectroscopic and Imaging Techniques for the Detection of Processed Meat Fraud.

In recent years, meat authenticity awareness has increased and, in the fight to combat meat fraud, various analytical methods have been proposed and subsequently evaluated. Although these methods have shown the potential to detect low levels of adulteration with high reliability, they are destructive, time-consuming, labour-intensive, and expensive. Therefore, rendering them inappropriate for rapid analysis and early detection, particularly under the fast-paced production and processing environment of the meat industry. However, modern analytical methods could improve this process as the food industry moves towards methods that are non-destructive, non-invasive, simple, and on-line. This review investigates the feasibility of different non-destructive techniques used for processed meat authentication which could provide the meat industry with reliable and accurate real-time monitoring, in the near future.

Application of ANOVA-simultaneous component analysis to quantify and characterise effects of age, temperature, syrup adulteration and irradiation on near-infrared (NIR) spectral data of honey.

NIR spectroscopy combined with chemometric analysis has proven to be a rapid and cost-effective screening tool for the detection of syrup-adulterated honey. Processing and storage conditions which alter the chemical and physical state of honey may affect the spectra. The effects of age, storage temperature, syrup adulteration (10 and 20% w/w) and irradiation treatment on the NIR spectra of honey were investigated as a function of time with ANOVA-simultaneous component analysis (ASCA), an experimental design-focused exploratory data analysis method. The factors 'time', 'temperature' and 'adulteration' were found to have significant effects (p < 0.05), but no significant effect was observed for irradiation treatment. A significant interaction effect was found between factors 'time' and 'adulteration', with the greatest disparity between authentic and adulterated class signals found immediately after adulteration and decreasing within three months thereafter.

In silico prediction of drug permeability across buccal mucosa.

PURPOSE: To develop and validate a computational model capable of predicting buccal permeability based on various structural and physicochemical descriptors. METHODS: Apparent permeability coefficients (K(p)) of 15 different drugs across porcine buccal mucosa were determined. Multiple linear regression (MLR) and maximum likelihood estimations (MLE) were used to develop the model based on a training set of 15 drugs with permeability as the response variable and the various descriptors as the predictor variables. The final model was validated with an external data set consisting of permeability values obtained from the literature. RESULTS: Drug permeabilities ranged from 30 x 10(-6) (nimesulide) to 3.3 x 10(-9) cm/s (furosemide). Regression analysis showed that 95% of the variability in permeability data can be explained by a model that includes molecular volume, distribution coefficient at pH 6.8, number of hydrogen bond donors, and number of rotatable bonds. Smaller molecular size, high lipophilicity, lower hydrogen bond capability and greater flexibility were important for permeability. The buccal model was found to have a good predictive capability. CONCLUSION: A simple model was developed and validated for predicting the buccal drug permeability. This model will be useful in assessing the feasibility of drugs for transbuccal delivery.

Detection of myeloma in skeleton of mice by whole-body optical fluorescence imaging.

Development of new therapies for myeloma has been hindered by the lack of suitable preclinical animal models of the disease in which widespread tumor foci in the skeleton can be detected reliably. Traditional means of detecting skeletal tumor infiltration such as histopathology are cumbersome and labor-intensive and do not allow temporal monitoring of tumor progression or regression in response to therapy. To resolve this problem, we modified the Radl 5TGM1 model of myeloma bone disease such that fluorescent myeloma tumors can be optically imaged in situ. Here, we show that murine myeloma 5TGM1 tumor cells, engineered to express enhanced green fluorescent protein (eGFP; 5TGM1-eGFP cells), can be imaged in a temporal fashion using a fluorescence illuminator and a charge-coupled device camera in skeletons of live C57BL/KaLwRij mice. High-resolution, whole-body images of tumor-bearing mice revealed that myeloma cells homed almost exclusively to the skeleton, with multiple focal tumor foci in the axial skeleton, consistent with myeloma tumor distribution in humans. Finally, the tested antitumor treatment effect of Velcade (bortezomib), a proteasome inhibitor used clinically in myeloma, was readily detected by GFP imaging, suggesting the power of the technique in combination with the Radl 5TGM1-eGFP model for rapid preclinical assessment and sensitive monitoring of novel and potential therapeutics. Whole-body GFP imaging is practical, convenient, inexpensive, and rapid, and these advantages should enable a high throughput when evaluating in vivo efficacy of new potential antimyeloma therapeutics and assessing response to treatment.

Classification of white maize defects with multispectral imaging.

Multispectral imaging with object-wise multivariate image analysis was evaluated for its potential to grade whole white maize kernels. The types of defective materials regarded in grading legislation were divided into 13 classes, and were imaged with a multispectral imaging instrument spanning the UV, visible and NIR regions (19 wavelengths ranging from 375 to 970nm). Object-wise partial least squares discriminant analysis (PLS-DA) models were developed and validated with an independent data set. Results demonstrated good performance in distinguishing between sound maize and undesirable materials, with cross-validated coefficients of determination (Q2) and classification accuracies ranging from 0.35 to 0.99 and 83 to 100%, respectively. Wavelengths related to absorbance of green, yellow and orange colour indicated the presence of lycopene and anthocyanin (505, 525, 570 and 590 nm). NIR wavelengths 890, 940 nm (associated with fat) and 970 nm (associated with water) were generally identified as important features throughout the study.

Non-destructive techniques for the detection of fungal infection in cereal grains.

Infection of cereal grains by fungi is a serious problem worldwide. Depending on the environmental conditions, cereal grains may be colonised by different species of fungi. These fungi cause reduction in yield, quality and nutritional value of the grain; and of major concern is their production of mycotoxins which are harmful to both humans and animals. Early detection of fungal contamination is an essential control measure for ensuring storage longevity and food safety. Conventional methods for detection of fungal infection, such as culture and colony techniques or immunological methods are either slow, labour intensive or difficult to automate. In recent years, there has been an increasing need to develop simple, rapid, non-destructive methods for early detection of fungal infection and mycotoxins contamination in cereal grains. Methods such as near infrared (NIR) spectroscopy, NIR hyperspectral imaging, and electronic nose were evaluated for these purposes. This paper reviews the different non-destructive techniques that have been considered thus far for detection of fungal infection and mycotoxins in cereal grains, including their principles, application and limitations.