Fungal infection and mycotoxin contamination in agricultural products are a serious food safety issue. The detection of fungal infection and mycotoxin contamination in food products should be in a rapid way. A Near-infrared (NIR) hyperspectral imaging system was used to detect fungal infection in 2013 crop year canola, wheat, and barley at different periods after inoculation and different concentration levels of ochratoxin A in wheat and barley. Artificially fungal infected (Fungi: Aspergillus glaucus, Penicillium spp.) kernels of canola, wheat and barley, were subjected to single kernel imaging after 2, 4, 6, 8, and 10 weeks post inoculation in the NIR region from 1000 to 1600 nm at 61 evenly distributed wavelengths at 10 nm intervals. The acquired image data were in the three-dimensional hypercube forms, and these were transformed into two-dimensional data. The two-dimensional data were subjected to principal component analysis to identify significant wavelengths based on the highest principal component factor loadings. Wavelengths 1100, 1130, 1250, and 1300 nm were identified as significant for detection of fungal infection in canola kernels, wavelengths 1280, 1300, and 1350 nm were identified as significant for detection of fungal infection in wheat kernels, and wavelengths 1260, 1310, and 1360 nm were identified as significant for detection of fungal infection in barley kernels. The linear, quadratic and Mahalanobis statistical discriminant classifiers differentiated healthy canola kernels with > 95% and fungal infected canola kernels with > 90% classification accuracy. All the three classifiers discriminated healthy wheat and barley kernels with > 90% and fungal infected wheat and barley kernels with > 80% classification accuracy. The wavelengths 1300, 1350, and 1480 nm were identified as significant for detection of ochratoxin A contaminated wheat kernels, and wavelengths 1310, 1360, 1480 nm were identified as significant for detection of ochratoxin A contaminated barley kernels. All the three statistical classifiers differentiated healthy wheat and barley kernels and ochratoxin A contaminated wheat and barley kernels with a classification accuracy of 100%. The classifiers were able to discriminate between different durations of fungal infections in canola, wheat, and barley kernels with classification accuracy of more than 80% at initial periods (2 weeks) of fungal infection and 100% at the later periods of fungal infection. Different concentration levels of ochratoxin A contamination in wheat and barley kernels were discriminated with a classification accuracy of > 98% at ochratoxin A concentration level of ≤ 72 ppb in wheat kernels and ≤ 140 ppb in barley kernels and with 100% classification accuracy at higher concentration levels. / May 2016

The selection of a representative sample is a delicate problem when drug seizures comprised of large number of units arrive at the Swedish National Forensic Centre (NFC). If deviating objects in the selected sample size are found, additional analyzes are required to investigate how representative the results are for the entire population. This generates further pressure on operational analysis flow. With the goal to provide a tool which forensic scientists at NFC can base their assessment of the representative nature of the selected sampling of large drug seizures on, this project investigated the possibilities of evaluating the level of homogeneity in drug seizures using near-infrared (NIR) hyperspectral imaging along with principal component analysis (PCA). A total of 27 sample groups (homogeneous, heterogeneous and seized sample groups) were analyzed and different predictive models were developed. The models were either based on quantifying the variation in NIR spectra or in PCA scores plots. It was shown that in the spectral range of 1300-2000 nm, using a pre-processing combination of area normalization, quadratic (second polynomial) detrending and mean centering, promising predictive abilities of the models in their evaluation of the level of homogeneity in drug seizures were achieved. A model where the approximated signal-dependent variation was related to the quotient of significant and noise explained variance given by PCA indicated most promising predictive abilities when quantifying the variation in NIR spectra. Similarly, a model where a rectangular area, defined by the maximum distances along PC1 and PC2, was related to the cumulative explained variance of the two PCs showed most promising predictive abilities when quantifying the variation in PCA scores plots. Different zones for which within sample groups are expected to appear based upon their degree of homogeneity could be established for both models. The two models differed in sensitivity. However, more comprehensive studies are required to evaluate the models applicability from an operational point-of-view.

Thesis (MSc Food Sc)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: Hectolitre mass (HLM) measurements allow rapid and accurate determination of grain density. HLM devices from different countries (Australia, Canada, France, Germany, South Africa, the United Kingdom and the United States of America [USA]) have been investigated for their effect on the HLM measurements of oats. In addition, the potential of near infrared (NIR) hyperspectral imaging has been evaluated to distinguish between oat samples with different HLM values. Comparing HLM measurements obtained from the respective devices, the USA and the South African devices resulted in significantly (P<0.05) lower HLM values compared to the other devices where as the German device resulted in higher values (P<0.05) than the other devices. HLM values from all the devices were highly correlated with intra-class correlation (ICC) consistency values of at least 0.90. These high correlations would allow direct replacement of the South African device with any of the other devices. The equipment selected as replacement should ideally be calibrated according to the ISO 7971-3 standard (i.e. the device currently used in Germany). HLM values significantly (P<0.05) increased when oat samples were rubbed before measurements were made, indicating the importance of continuation of this sample preparation step. The investigation on the effect of the operator on HLM determinations showed that the unskilled operator measured HLM values significantly different to those obtained by the skilled operator. This emphasises the importance of training in spite of HLM measurements being a simple procedure. A poor correlation (r = 0.18) was found between protein content and HLM values of oat samples. Moisture content significantly affected the HLM values of oats and results clearly showed a decrease in HLM values with increasing moisture content. Scanning electron microscope (SEM) micrographs revealed that the starch granules became swollen and that they increased in size with an increase in moisture content, resulting in a decrease in HLM. NIR hyperspectral imaging offers the testing of individual grains non-destructively. This is often required by plant breeders because they subsequently need to plant selected grains. NIR offers this option to plant breeders. NIR hyperspectral imaging, which combines NIR spectroscopy with digital imaging, was used to distinguish between six oat samples with varying HLM values. NIR spectroscopic differences were observed between the images of the two samples with the highest and lowest HLM values (60.2 and 49.35 kg.hL-1). Less distinct differences were observed in the NIR hyperspectral images of two samples differing by less than 2.0 kg.hL-1. Although mixed oat samples were used, these preliminary results established the possible use of NIR hyperspectral imaging in evaluating oat samples from breeding trials. The use of this technique could also be extended to evaluation of other quality characteristics of oats. / AFRIKAANSE OPSOMMING: Hektolitermassa- (HLM-)metings maak snelle en akkurate bepaling van korreldigtheid moontlik. HLM-toestelle van verskillende lande (Australië, Kanada, Frankryk, Duitsland, Suid-Afrika, die Verenigde Koninkryk en die Verenigde State van Amerika) is ondersoek vir hulle uitwerking op die HLM-metings van hawer. Daarby is die potensiaal van nabyinfrarooi- (NIR-)hiperspektrale beelding geëvalueer om tussen hawermonsters met verskillende HLM-waardes te onderskei. Tydens vergelyking van HLM-metings verkry van die onderskeie toestelle, het die Amerikaanse en die Suid-Afrikaanse toestelle beduidend (P<0.05) laer HLM-waardes opgelewer in vergelyking met die ander toestelle terwyl die Duitse toestel hoër waardes (P<0.05) as die ander toestelle getoon het. Daar was hoë korrelasies tussen die HLM waardes verkry van die apparate met intraklaskorrelasie (IKK) konsekwentheidwaardes van ten minste 0.90. Hierdie hoë korrelasies sou direkte vervanging van die Suid-Afrikaanse toestel met enige van die ander toestelle moontlik maak. Die toerusting gekies as vervanging sou ideaal gesproke in ooreenstemming met die ISO 7971-3 standaard gekalibreer kon word (bv. die toestel wat tans in Duitsland gebruik word). HLM-waardes het beduidend (P<0.05) verhoog toe hawermonsters gevryf is voor metings gemaak is, wat dui op die belang van verlengde gebruik van hierdie stap tydens die voorbereiding van monsters. Die ondersoek na die uitwerking van die operateur op HLM-bepalings het getoon dat die onervare operateur HLM-waardes beduidend verskillend gemeet het teenoor dié verkry deur die ervare operateur. Dit beklemtoon die belang van opleiding ten spyte daarvan dat HLM-metings ’n eenvoudige prosedure is. ’n Swak korrelasie (r = 0.18) is aangetref tussen proteïeninhoud en HLM-waardes van hawermonsters. Voginhoud het die HLM-waardes van hawer beduidend beïnvloed en resultate het duidelik ’n styging in HLM-waardes met verhoging van die voginhoud getoon. Aftaselektronmikroskoop- (AEM-)mikrobeelde het aangedui dat die styselgranules swel en in grootte toeneem met verhoging van die voginhoud, wat aanleiding gee tot ’n verlaging in HLM. NIR-hiperspektrale beelding maak die toets van individuele korrels op niedestruktiewe wyse moontlik. Dit word dikwels deur plantkwekers vereis aangesien hulle na toetsing uitgesoekte korrels moet plant. Nabyinfrarooi bied hierdie opsie aan plantkwekers. NIR-hiperspektrale beelding, wat NIRspektroskopie met digitale beelding kombineer, is gebruik om te onderskei tussen ses hawermonsters met wisselende HLM-waardes. NIR-spektroskopiese verskille tussen die beelde van die twee monsters met die hoogste en laagste HLM-waardes (60.2 en 49.35 kg.hL-1) is waargeneem. Minder duidelike verskille is in die NIR-hiperspektrale beelde van twee monsters wat met minder as 2.0 kg.hL-1 verskil het, waargeneem. Alhoewel gemengde hawermonsters gebruik is, het hierdie voorlopige resultate die moontlike gebruik van NIR-hiperspektrale beelding by die evaluering van hawermonsters van kweekproewe vasgestel. Die gebruik van hierdie tegniek sou ook uitgebrei kon word tot die evaluering van ander kwaliteitseienskappe van hawer.