54 research outputs found
Wheat hardness by near infrared (NIR) spectroscopy: New insights
The determination of wheat hardness by the evaluation of whole wheat grain would be of
considerable value to the UK Milling Industry. Until now, accurate whole wheat grain
hardness predictions by NIR spectroscopy have only been reported for North American
wheats. By the evaluation of selected samples of UK and North American wheats this
study showed that the prediction of whole wheat grain hardness by NTR spectroscopy
depends only on the scattering properties of the sample and that there is no direct
relationship with chemical composition. The scattering effect, in case of whole wheat grain
reflectance and transmittance spectra, was found not to be multiplicative as in the case of
ground wheat grain spectra.
Empirical NIR spectroscopy calibrations are often performed without knowing what is
measured or understanding the basis of the measurement. In other words the NIR
spectrophotometer is often used as a "black box". Empirical calibrations were performed
using three different software packages i.e. lnfrasoft International (ISI) Software,
NIRSystems Spectral Analysis Software (NSAS) and UNSCRAMBLER. Successful NIR
spectroscopy hardness measurements on ground wheat are based on light scattering.
Separating the scattering effect from whole wheat grain spectra mathematically allowed
predictions not significantly different to empirical calibrations, with the benefit of a
theoretical explanation and fewer terms used.
Although hardness predictions for whole wheat grain were not as accurate as in the case
of ground wheat grain, it did prove to predict hardness with an acceptable accuracy with
practical use as screening methods for grain trading.
This study did not completely solve the problem of predicting whole wheat grain hardness
by NIR spectroscopy, but new insights were provided which would hopefully encourage
further work in this area and lead to a more complete fundamental understanding of the
properties of whole wheat grain hardness using NIR spectroscopy
Hierarchical classification pathway for white maize, defect and foreign material classification using spectral imaging
This study aimed to present the South African maize industry with an accurate and affordable automated analytical technique for white maize grading using near infrared (NIR) spectral imaging. The 17 categories and sub-categories stipulated in South African maize grading legislation were simultaneously classified (1044 samples; 60 kernels of each class) using 25 partial least squares discriminant analysis (PLS-DA) models. The models were assembled in a hierarchical decision pathway that progressed from the most easily classified classes to the most difficult. The full NIR spectrum (288 wavebands) model performed with an overall accuracy of 93.3% for the main categories. Three waveband selection techniques were employed, namely waveband windows (48 wavebands), variable importance in projection (VIP) (21 wavebands) and covariance selection (CovSel) (13 wavebands). Overall, the VIP set based on only 7.3% of the original spectral variables was recommended as the best trade-off between performance and expected cost of a reduced waveband system. © 2020 Elsevier B.V
Discriminating muscle type of selected game species using near infrared (NIR) spectroscopy
CITATION: Dumalisile, P. et al. 2020. Discriminating muscle type of selected game species using near infrared (NIR) spectroscopy. Food Control, 110. doi:10.1016/j.foodcont.2019.106981.The original publication is available at http://www.journals.elsevier.com/food-control/In this study near infrared (NIR) spectroscopy was used to discriminate between different muscle types within each species of selected game animals, and to classify species regardless of the muscle. Muscle steaks from longissimus thoracis et lumborum (LTL) located at the 6th rib of the carcasses, infraspinatus (IS) and supraspinatus (SS) located on the forequarter, and biceps femoris (BF), semitendinosus (ST) and semimembranosus (SM) located on the hindquarter of impala and eland species; and samples from fan fillet (FF), big drum (BD), triangle steak (TS), moon steak (MS) and rump steak (RS) of ostrich species were scanned with a handheld NIR spectrophotometer in the spectral range of 908–1700 nm. Spectra were pre-treated with different pre-processing methods and classification models were developed using partial least squares discriminant analysis (PLS-DA). Classification accuracies were higher when the muscles were grouped according to their anatomical location in the carcass, than attempting to classify them separately. Classification accuracies ranging from 85.0 to 100% were achieved throughout, with forequarter muscles yielding the highest classification accuracy rate for both impala and eland species. Furthermore, when the species were discriminated regardless of muscles, PLS-DA models pre-treated with SNV-Detrend and Savitzky-Golay 1st derivative yielded accuracies of 97, 81 and 92% for eland, impala and ostrich, respectively. These results indicate that NIR spectroscopy can be used for the authentication of game meat, specifically impala, eland and ostrich. Furthermore, it was easier to discriminate species regardless of the muscle used than different muscles within each species.https://www.sciencedirect.com/science/article/pii/S0956713519305705Publishers versio
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Effects of storage conditions and duration on physicochemical and microbial quality of the flour of two cassava cultivars (TME 419 and UMUCASS 36)
This study investigated the effects of storage conditions: cool (15 ± 1°C, 90% relative humidity (RH)), ambient (23 ± 2°C, 60% RH) and higher (38 ± 2°C, 60% RH) on changes in physicochemical quality attributes of two cassava flour cultivars (TME 419 and UMUCASS 36) packaged in paper bags and stored for 12 weeks. Physicochemical and microbial qualities were studied at weeks 0, 4, 8 and 12. Moisture content decreased from 12.0% to 7.1% and 9.8% to 6.8% in cultivars ‘TME 419’ and ‘UMUCASS 36’, respectively. Carotenoid content was higher in cultivar (cv.) ‘UMUCASS 36’ (2.5 ± 0.10 mg/g) compare to cv. ‘TME 419’ (1.8 ± 0.11 mg/g). Colour indices of the cassava flour were significantly influenced by storage duration. A slight decrease in microbial load from 5.4 to 4.8 log CFU/g was observed, with increase in temperature from 15°C to 38°C at the end of storage. The ambient storage condition best maintained nutritional and physicochemical quality.Este estudio investigó los efectos de las condiciones de almacenamiento: frÃo (15 ± 1°C, 90% humedad relativa (RH); ambiente (23 ± 2°C, 60% RH); y alta (38 ± 2°C, 60% RH) en los cambios en los atributos cualitativos fisicoquÃmicos de dos cultivares de harina de mandioca (TME 419 y UMUCASS 36) empaquetados en bolsas de papel y almacenados durante 12 semanas. Se estudió la calidad fisicoquÃmica y microbiana en las semanas 0, 4, 8 y 12. El contenido de humedad disminuyó de 12,0 a 7,1% y de 9,8 a 6,8% en los cultivares ‘TME 419’ y ‘UMUCASS 36’, respectivamente. El contenido en carotenoides fue mayor en el cv. ‘UMUCASS 36’ (2,5 ± 0,10 mg/g) en comparación con el cv. ‘TME 419’ (1,8 ± 0,11 mg/g). Los Ãndices de color de la harina de mandioca estuvieron influenciados significativamente por la duración del periodo de almacenamiento. Se observó un ligero descenso en la carga microbiana de 5,4 a 4,8 log CFU/g, con un aumento en la temperatura de 15°C a 38°C al final del periodo de almacenamiento. El almacenamiento a temperatura ambiente fue el que mantuvo una mejor calidad nutricional y fisicoquÃmic
Wheat starch structure–function relationship in breadmaking: A review
Bread dough and bread are dispersed systems consisting of starch polymers that interact with other flour components and added ingredients during processing. In addition to gluten proteins, starch impacts the quality characteristics of the final baked product. Wheat starch consists of amylose and amylopectin organized into alternating semicrystalline and amorphous layers in granules that vary in size and are embedded in the endosperm protein matrix. Investigation of the molecular movement of protons in the dough system provides a comprehensive insight into granular swelling and amylose leaching. Starch interacts with water, proteins, amylase, lipids, yeast, and salt during various stages of breadmaking. As a result, the starch polymers within the produced crumb and crust, together with the rate of retrogradation and staling due to structural reorganization, moisture migration, storage temperature, and relative humidity determines the final product's textural perception. This review aims to provide insight into wheat starch composition and functionality and critically review recently published research results with reference to starch structure–function relationship and factors affecting it during dough formation, fermentation, baking, cooling, and storage of bread
Effect of colony age on near infrared hyperspectral images of foodborne bacteria
Near infrared hyperspectral imaging (NIR-HSI) and multivariate image analysis were used to distinguish between foodborne pathogenic bacteria, Bacillus cereus, Escherichia coli, Salmonella Enteritidis, Staphylococcus aureus and a non-pathogenic bacterium, Staphylococcus epidermidis. Hyperspectral images of bacteria, streaked out on Luria–Bertani agar, were acquired after 20 h, 40 h and 60 h growth at 37 °C using a SisuCHEMA hyperspectral pushbroom imaging system with a spectral range of 920–2514 nm. Three different pre-processing methods: standard normal variate (SNV), Savitzky–Golay (1st derivative, 2nd order polynomial, 15-point smoothing) and Savitzky–Golay (2nd derivative, 3rd order polynomial, 15-point smoothing) were evaluated. SNV provided the most distinct clustering in the principal component score plots and was thus used as the sole pre-processing method. Partial least squares discriminant analysis (PLS-DA) models were developed for each growth period and was tested on a second set of plates, to determine the effect the age of the colony has on classification accuracies. The highest overall prediction accuracies where test plates required the least amount of growth time, was found with models built after 60 h growth and tested on plates after 20 h growth. Predictions for bacteria differentiation within these models ranged from 83.1 % to 98.8 % correctly predicted pixels
X-ray computed tomography
X-ray computed tomography (CT) can reveal the internal details of objects in three dimensions non-destructively. In this Primer, we outline the basic principles of CT and describe the ways in which a CT scan can be acquired using X-ray tubes and synchrotron sources, including the different possible contrast modes that can be exploited. We explain the process of computationally reconstructing three-dimensional (3D) images from 2D radiographs and how to segment the 3D images for subsequent visualization and quantification. Whereas CT is widely used in medical and heavy industrial contexts at relatively low resolutions, here we focus on the application of higher resolution X-ray CT across science and engineering. We consider the application of X-ray CT to study subjects across the materials, metrology and manufacturing, engineering, food, biological, geological and palaeontological sciences. We examine how CT can be used to follow the structural evolution of materials in three dimensions in real time or in a time-lapse manner, for example to follow materials manufacturing or the in-service behaviour and degradation of manufactured components. Finally, we consider the potential for radiation damage and common sources of imaging artefacts, discuss reproducibility issues and consider future advances and opportunities
Chemical, antioxidant and sensory properties of pasta from fractionated whole wheat and Bambara groundnut flour
Pasta from whole-grain wheat is highly nutritious but has poor sensory properties. Hence, this study prepared pasta from fractionated whole-grain wheat flour enriched with 20% Bambara groundnut. The chemical, antioxidant and sensory properties of the pasta were assessed using standard methods. The fat, protein, ash contents, lightness and antioxidant properties value of the flour and pasta increased, while carbohydrate and fibre contents decreased with a reduction in particle size from 500 μm to 112 μm. Potassium (246.50–249.00 mg/kg), calcium (223.50–254.00 mg/kg) and magnesium (184.50–192.00 mg/kg) were the major mineral element in the pasta samples, while zinc (1.00–2.00 mg/kg) and iron (3.50–13.00 mg/kg) are present in small quantities. The optimum cooking time of pasta (average 6.55 min) from the fractionated flours was shorter compared to the control pasta (pasta made from unfractionated wheat flour), but the cooking loss was not significantly affected. Pasta from flour with particle sizes of 300 and 112 μm were very similar in their sensory attributes and showed the highest ratings in overall acceptability. Fractionation of whole-grain wheat flour seems very promising in producing pasta with fairly good antioxidant potentials and high level of protein and fibre to improve the health of pasta-loving individuals.The Faculty of Science-University Research Committee Fellowship of the University of Johannesburg, South Africa.http://www.elsevier.com/locate/lwthj2022Consumer ScienceFood Scienc
Hardness methods for testing maize kernels
Maize is a highly important crop to many countries around the world, through the sale of the maize crop to domestic processors and subsequent production of maize products and also provides a staple food to subsistance farms in undeveloped countries. In many countries, there have been long-term research efforts to develop a suitable hardness method that could assist the maize industry in improving efficiency in processing as well as possibly providing a quality specification for maize growers, which could attract a premium. This paper focuses specifically on hardness and reviews a number of methodologies as well as important biochemical aspects of maize that contribute to maize hardness used internationally. Numerous foods are produced from maize, and hardness has been described as having an impact on food quality. However, the basis of hardness and measurement of hardness are very general and would apply to any use of maize from any country. From the published literature, it would appear that one of the simpler methods used to measure hardness is a grinding step followed by a sieving step, using multiple sieve sizes. This would allow the range in hardness within a sample as well as average particle size and/or coarse/fine ratio to be calculated. Any of these parameters could easily be used as reference values for the development of near-infrared (NIR) spectroscopy calibrations. The development of precise NIR calibrations will provide an excellent tool for breeders, handlers, and processors to deliver specific cultivars in the case of growers and bulk loads in the case of handlers, thereby ensuring the most efficient use of maize by domestic and international processors. This paper also considers previous research describing the biochemical aspects of maize that have been related to maize hardness. Both starch and protein affect hardness, with most research focusing on the storage proteins (zeins). Both the content and composition of the zein fractions affect hardness. Genotypes and growing environment influence the final protein and starch content and, to a lesser extent, composition. However, hardness is a highly heritable trait and, hence, when a desirable level of hardness is finally agreed upon, the breeders will quickly be able to produce material with the hardness levels required by the industry
Zein characterisation of South African maize hybrids and their respective parental lines using MALDI-TOF MS
Zeins are important storage proteins and play a role in grain texture and impact on processing. Having a technique to accurately quantify the individual zeins and the size of these proteins would allow for more precise understanding of the impact these individual protein have on grain texture and/or processing. Matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS) was used to characterise zein protein profiles of five South African maize hybrids, grown at three locations, and their respective parental lines. A new, simplified and shortened zein extraction method was used to characterise the zein profiles and to determine any possible relationship between the hybrids and their parents. A matrix solution comprising two matrices, α-cyano-4-hydroxy-cinammic acid (CHCA) and 2-(4-hydroxyphenylazo) benzoic acid (HABA), was required to detect all major zein (α, β, γ and δ) classes. Within the set of hybrids and parents, additional peaks with molecular weights not previously reported were observed. These were identified as belonging to the δ-zein, β-zein and γ-zein. Relationships between the hybrids and their respective parental lines were observed indicating genetic variation for these zein classes exists. The MALDI-TOF MS method identified differences in individual zein proteins and these differences were observed between hybrids. The method shows a potential for accurately quantifying the presence and molecular size of zein proteins which may be important in milling and food processing. Storage proteins play an important role not only in grain composition but also in some processes such as milling, and variation in these individual proteins may impact on efficiency of processing
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