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.

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.

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.

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.

Assessing similarity analysis of chromatographic fingerprints of Cyclopia subternata extracts as potential screening tool for in vitro glucose utilisation.

Similarity analysis of the phenolic fingerprints of a large number of aqueous extracts of Cyclopia subternata, obtained by high-performance liquid chromatography (HPLC), was evaluated as a potential tool to screen extracts for relative bioactivity. The assessment was based on the (dis)similarity of their fingerprints to that of a reference active extract of C. subternata, proven to enhance glucose uptake in vitro and in vivo. In vitro testing of extracts, selected as being most similar (n = 5; r ≥ 0.962) and most dissimilar (n = 5; r ≤ 0.688) to the reference active extract, showed that no clear pattern in terms of relative glucose uptake efficacy in C2C12 myocytes emerged, irrespective of the dose. Some of the most dissimilar extracts had higher glucose-lowering activity than the reference active extract. Principal component analysis revealed the major compounds responsible for the most variation within the chromatographic fingerprints, as mangiferin, isomangiferin, iriflophenone-3-C-ß-D-glucoside-4-O-ß-D-glucoside, iriflophenone-3-C-ß-D-glucoside, scolymoside, and phloretin-3',5'-di-C-ß-D-glucoside. Quantitative analysis of the selected extracts showed that the most dissimilar extracts contained the highest mangiferin and isomangiferin levels, whilst the most similar extracts had the highest scolymoside content. These compounds demonstrated similar glucose uptake efficacy in C2C12 myocytes. It can be concluded that (dis)similarity of chromatographic fingerprints of extracts of unknown activity to that of a proven bioactive extract does not necessarily translate to lower or higher bioactivity.

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.

Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials.

Near-infrared (NIR) spectroscopy has come of age and is now prominent among major analytical technologies after the NIR region was discovered in 1800, revived and developed in the early 1950s and put into practice in the 1970s. Since its first use in the cereal industry, it has become the quality control method of choice for many more applications due to the advancement in instrumentation, computing power and multivariate data analysis. NIR spectroscopy is also increasingly used during basic research performed to better understand complex biological systems, e.g. by means of studying characteristic water absorption bands. The shorter NIR wavelengths (800-2500 nm), compared to those in the mid-infrared (MIR) range (2500-15 000 nm) enable increased penetration depth and subsequent non-destructive, non-invasive, chemical-free, rapid analysis possibilities for a wide range of biological materials. A disadvantage of NIR spectroscopy is its reliance on reference methods and model development using chemometrics. NIR measurements and predictions are, however, considered more reproducible than the usually more accurate and precise reference methods. The advantages of NIR spectroscopy contribute to it now often being favoured over other spectroscopic (colourimetry and MIR) and analytical methods, using chemicals and producing chemical waste, such as gas chromatography (GC) and high performance liquid chromatography (HPLC). This tutorial review intends to provide a brief overview of the basic theoretical principles and most investigated applications of NIR spectroscopy. In addition, it considers the recent development, principles and applications of NIR hyperspectral imaging. NIR hyperspectral imaging provides NIR spectral data as a set of images, each representing a narrow wavelength range or spectral band. The advantage compared to NIR spectroscopy is that, due to the additional spatial dimension provided by this technology, the images can be analysed and visualised as chemical images providing identification as well as localisation of chemical compounds in non-homogenous samples.

Applications of single kernel conventional and hyperspectral imaging near infrared spectroscopy in cereals.

Single kernel (SK) near infrared (NIR) reflectance and transmittance technologies have been developed during the last two decades for a range of cereal grain physical quality and chemical traits as well as detecting and predicting levels of toxins produced by fungi. Challenges during the development of single kernel near infrared (SK-NIR) spectroscopy applications are modifications of existing NIR technology to present single kernels for scanning as well as modifying reference methods for the trait of interest. Numerous applications have been developed, and cover almost all cereals although most have been for key traits including moisture, protein, starch and oil in the globally important food grains, i.e. maize, wheat, rice and barley. An additional benefit in developing SK-NIR applications has been to demonstrate the value in sorting grain infected with a fungus or mycotoxins such as deoxynivalenol, fumonisins and aflatoxins. However, there is still a need to develop cost-effective technologies for high-speed sorting which can be used for small grain samples such as those from breeding programmes or commercial sorting; capable of sorting tonnes per hour. Development of SK-NIR technologies also includes standardisation of SK reference methods to analyse single kernels. For protein content, the use of the Dumas method would require minimal standardisation; for starch or oil content, considerable development would be required. SK-NIR, including the use of hyperspectral imaging, will improve our understanding of grain quality and the inherent variation in the range of a trait. In the area of food safety, this technology will benefit farmers, industry and consumers if it enables contaminated grain to be removed from the human food chain.

Novel, non-destructive cereal quality analysis: potential for triticale.

Near infrared (NIR) spectroscopy, NIR hyperspectral imaging and X-ray computed technology (XCT) can each in its own way contribute to the effective analysis of whole grain triticale. With NIR spectroscopy only giving an average result, NIR hyperspectral imaging gives spatial as well as spectral information of a sample. Chemical information as well as the localisation of the chemical compounds is thus obtained. XCT advanced on these two techniques in that it allows three dimensional (3D) visualisation of the internal structure of a sample. The availability of X-ray microcomputed tomography (microCT) instruments and now also nanoCT instruments allow high resolution images of the microstructure of samples to be obtained. These techniques, reviewed in this paper, can be used in association, each with their own advantages and disadvantages, to most effectively analyse whole grain triticale.

Non-invasive exploration of malting barley (Hordeum vulgare) in vitro germination and varietal effects using short wave infrared spectral imaging and ANOVA simultaneous component analysis.

ANOVA-simultaneous component analysis (ASCA) was applied to short-wave infrared spectral fingerprints of 5 malting barley varieties collected using a hyperspectral imaging system to determine the effect of germination, the influence of time and the influence of barley by means of a full factorial experimental design. ASCA indicated that there was a significant (p < 0.0001) effect of the germination status, the germination time and interaction on the spectral data for all varieties. The biochemical and physiological modification of the samples were characterised by visualisation of the longitudinal scores obtained from simultaneous component analysis for the germination time factor. This resulted in the visualisation and explanation of biochemical change over the course of barley germination as a factor of time. The relevant loadings indicated a significant change to the proteome, lipid and starch structure as driven by the uptake of water over time. The ASCA model were extrapolated to include the effect of barley variety to the already mentioned germination status and germination time factors, resulting once again in all the effects being significant (p < 0.0001). Here it was shown that all the barley varieties are significantly different from one another pre- and post-modification, based on the molecular vibrations observed in the short wave-infrared (SWIR) spectra, suggesting that the detection of biotic stress factors, such as pre-harvest germination, also differ for each variety, by indicating that the germination profile of each barley variety varies as a function of germination time. Thus, also the malting performance, germinative energy and chemical profile of each barley variety tested will vary before, during and after imbibition and germination - indicating the importance of malting commercial barley malt true to variety. These results indicate that (SWIR) spectral imaging instrumentation can possibly be used to monitor controlled germination of barley grain. Due to the shown ability of SWIR spectral imaging to detect small biochemical changes over time of barley grain during germination.

Classification and quantification of sucrose from sugar beet and sugarcane using optical spectroscopy and chemometrics.

Sucrose, obtained from either sugar beet or sugarcane, is one of the main ingredients used in the food industry. Due to the same molecular structure, chemical methods cannot distinguish sucrose from both sources. More practical and affordable methods would be valuable. Sucrose samples (cane and beet) were collected from nine countries, 25% (w/w) aqueous solutions were prepared and their absorbances recorded from 200 to 1380 nm. Spectral differences were observable in the ultraviolet-visible (UV-Vis) region from 200 to 600 nm due to impurities in sugar. Linear discriminant analysis (LDA), classification and regression trees, and soft independent modeling of class analogy were tested for the UV-Vis region. All methods showed high performance accuracies. LDA, after selection of five wavelengths, gave 100% correct classification with a simple interpretation. In addition, binary mixtures of the sugar samples were prepared for quantitative analysis by means of partial least squares regression and multiple linear regression (MLR). MLR with first derivative Savitzky-Golay were most acceptable with root mean square error of cross-validation, prediction, and the ratio of (standard error of) prediction to (standard) deviation values of 3.92%, 3.28%, and 9.46, respectively. Using UV-Vis spectra and chemometrics, the results show promise to distinguish between the two different sources of sucrose. An affordable and quick analysis method to differentiate between sugars, produced from either sugar beet or sugarcane, is suggested. This method does not involve complex chemical analysis or high-level experts and can be used in research or by industry to detect the source of the sugar which is important for some countries' agricultural policies.

Effect of wheat roasting conditions and wheat type on short-wave infrared (SWIR) spectral data of whole and milled wheat by ANOVA-simultaneous component analysis.

ANOVA-simultaneous component analysis (ASCA) was used to investigate the effect of roasting and wheat type on shortwave-infrared (SWIR) spectra of whole wheat and flour through assessment of statistical significance and characterisation of the contributing spectral features. The full factorial experimental design included two wheat types, three roasting temperatures and three roasting frequencies. SWIR spectral images were collected from the two roasted wheat types and their two milled samples. Three ASCA models, one for each wheat conformation (kernel, whole wheat flour, white flour) were investigated. It was evidenced that all factors and interaction in the whole wheat flour model had a significant (p ≤ 0.05) effect on spectral data. Only the factor roasting frequency was not significant in white flour model and only the interaction between roasting frequency and wheat type was not significant for the kernel model. The main variations in the loading line plots were identified and characterised by chemical structural differences that occur within the sample. The effect of roasting frequency had a more adverse effect on protein stability, moisture evaporation, water soluble carbohydrates and aromatic amino acids, compared to roasting temperature. A Rapid Visco-Analyser (RVA) was used to further investigate difference in wheat type as almost all spectral data sets differed significantly. The most prominent difference between the two wheat types was observed as differences in amylase activity and presence of lipids. ASCA applied to SWIR whole wheat and flour spectral data effectively characterised the significant effect of roasting on wheat starch and protein structures.

Application of segmented analysis via multivariate curve resolution with alternating least squares to 1H-nuclear magnetic resonance spectroscopy to identify different sugar sources.

The different types of sugar employed in the food industry exhibit chemical similarity and are mostly dominated by sucrose. Owing to the sugar origin of and differences in production, the presence of certain minor organic compounds differs. To differentiate between sugars based on their botanical source, geographical origin, or storage conditions, commercial brown sugars and sugar beet extracts were analyzed by 1H NMR spectroscopy applying a segmented analysis by means of multivariate curve resolution-alternating least squares (MCR-ALS). Principal component analysis and partial least squares-discriminant analysis yielded excellent differentiation between sugars from different sources after the application of this preprocessing strategy; without loss of chemical information and with direct interpretation of the results. By applying a segmented analysis via MCR-ALS to 1H NMR sugar data, similar spectroscopic profiles could be differentiated. This improved the selectivity of 1H NMR spectroscopy for sugar source differentiation which can be useful for industrial sugar authentication purposes.

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.

Enhancing aspalathin stability in rooibos (Aspalathus linearis) ready-to-drink iced teas during storage: the role of nano-emulsification and beverage ingredients, citric and ascorbic acids.

BACKGROUND: The effects of citric and ascorbic acids on the stability of aspalathin in rooibos (Aspalathus linearis) ready-to-drink (RTD) formulations containing fermented rooibos extract (FR), aspalathin-enriched green rooibos extract (GR) and aspalathin-enriched green rooibos extract ascorbic acid solubilisate (GR-solubilisate) were investigated during storage (12 weeks at 25 °C). RESULTS: Storage of iced tea formulations containing FR and GR extracts reduced their flavonoid content. The aspalathin content of FR iced tea without citric or ascorbic acid was reduced to undetectable levels by week 8 of storage. Addition of citric acid resulted in improved stability of aspalathin, but ascorbic acid did not impart additional stability. Iso-orientin and orientin were less affected than aspalathin, presumably owing to partial conversion of aspalathin to these flavones. Similar results were obtained for GR iced tea formulations. Improved stability of aspalathin was noted in iced tea containing GR-solubilisate with or without citric acid. Lower pH was shown to favour stability, especially for fermented rooibos iced teas. CONCLUSION: Citric and ascorbic acids contribute to the stability of rooibos flavonoids during storage. Differences in stability between formulations are not due to pH differences but may be related to the matrix.

Phenolic profiling and antioxidant evaluation of extracts from Southern African indigenous fruits byproducts.

The call to build climate-resilient food systems in Africa has revived interest in indigenous fruits, which, however, remain under-researched. In this study, the phenolic content and antioxidant profiles of seed and pulp of ethanolic extracts from eight Southern African indigenous fruits were evaluated using UPLC-ESI-Q-TOF/MS and four antioxidant assays. Total phenols and hydroxycinnamic acids were highest in Dovyalis caffra (Kei apple) seed (5084.5 and 3403.83 mg/kg). Flavonoids were most abundant in Colpoon compressum (Colpoon) seed (1127.23 mg/kg), while hydrolysable tannins were highest in Syzygium guineense (Water pear) seed (666.13 mg/kg). Proanthocyanidins were abundant in Harpephyllum caffrum (Wild plum) pulp while anthocyanins were highest in Olea africana (Wild olive) pulp. Hierarchical clustering heatmap analysis showed similar concentration and diversity in the composition of reported compounds. Syzygium guineense seed had the lowest DPPH values. ORAC values were highest in O. africana pulp while H. caffrum pulp had the highest FRAP values and lipoxygenase inhibition capacity. In conclusion, the study revealed a diverse profile of phenolics in indigenous fruits extracts, to which their bioactivity is attributed. Specifically, H. caffrum pulp and S. guineense seed have potential as natural sources of phenolic antioxidants for food application.

Holistic View of Starch Chemistry, Structure and Functionality in Dry Heat-Treated Whole Wheat Kernels and Flour.

Heat treatment is used as a pre-processing step to beneficially change the starch properties of wheat flour to enhance its utilisation in the food industry. Heat-treated wheat flour may provide improved eating qualities in final wheat-based products since flour properties predominantly determine the texture and mouthfeel. Dry heat treatment of wheat kernels or milled wheat products involves heat transfer through means of air, a fluidising medium, or radiation-often resulting in moisture loss. Heat treatment leads to changes in the chemical, structural and functional properties of starch in wheat flour by inducing starch damage, altering its molecular order (which influences its crystallinity), pasting properties as well as its retrogradation and staling behaviour. Heat treatment also induces changes in gluten proteins, which may alter the rheological properties of wheat flour. Understanding the relationship between heat transfer, the thermal properties of wheat and the functionality of the resultant flour is of critical importance to obtain the desired extent of alteration of wheat starch properties and enhanced utilisation of the flour. This review paper introduces dry heat treatment methods followed by a critical review of the latest published research on heat-induced changes observed in wheat flour starch chemistry, structure and functionality.

Characterisation of non-viable whole barley, wheat and sorghum grains using near-infrared hyperspectral data and chemometrics.

Undesired germination of cereal grains diminishes process utility and economic return. Pre-germination, the term used to describe untimely germination, leads to reduced viability of a grain sample. Accurate and rapid identification of non-viable grain is necessary to reduce losses associated with pre-germination. Viability of barley, wheat and sorghum grains was investigated with near-infrared hyperspectral imaging. Principal component analyses applied to cleaned hyperspectral images were able to differentiate between viable and non-viable classes in principal component (PC) five for barley and sorghum and in PC6 for wheat. An OH stretching and deformation combination mode (1,920-1,940 nm) featured in the loading line plots of these PCs; this water-based vibrational mode was a major contributor to the viable/non-viable differentiation. Viable and non-viable classes for partial least squares-discriminant analysis (PLS-DA) were assigned from PC scores that correlated with incubation time. The PLS-DA predictions of the viable proportion correlated well with the viable proportion observed using the tetrazolium test. Partial least squares regression analysis could not be used as a source of contrast in the hyperspectral images due to sampling issues.

A review of triticale uses and the effect of growth environment on grain quality.

Triticale (× Triticosecale sp. Wittmack ex A. Camus 1927) is an anthropogenic cereal designed to incorporate the functionality and high yield of wheat (Triticum spp. Linnaeus 1753) and durability of rye (Secale cereale Linnaeus 1753). The potential of triticale has remained largely unrealised, and in the 135 years since A. Stephen Wilson first crossed wheat and rye, triticale has mostly been used as animal feed. Growing demand for food resources has led to an increased interest in triticale development. Efforts to breed cultivars appropriate for baking have met with difficulty, although relatively new approaches to triticale end-use propose greater applicability for human consumption. Further, environmental awareness has generated interest in the use of triticale within biofuel production. We review environmental and genetic effects on triticale yield with a view towards increased demand on a hardy and useful cereal crop. We find triticale could satisfy many of the hopes originally placed upon it, and may be useful in foodstuffs and fuel, but only when growth environment is carefully considered.