Innovative ingredients and emerging technologies for controlling ice recrystallisation, texture and structure stability in frozen dairy desserts: a review

Over the past decade, ice cream manufacturers have developed a strong understanding of the functionality of key ingredients and processing, developing effective explanations for the link between structure forming agents, stability mechanisms and perceived quality. Increasing demand for products perceived as healthier / more natural with minimal processing has identified a number of new tools to improve quality and storage stability of frozen dairy desserts. Ingredients such as dietary fibre, polysaccharides, prebiotics, alternate sweeteners, fat sources rich in unsaturated fatty acids and ice structuring proteins have been successfully applied as cryoprotective, texturizing and structuring agents. Emerging minimal processing technologies including hydrostatic pressure processing, ultrasonic or high pressure assisted freezing, low temperature extrusion and enzymatically induced biopolymers crosslinking have been evaluated for their ability to improve colloidal stability, texture and sensory quality. It is therefore timely for a comprehensive review

Soybean (Glycine max) oil bodies and their associated phytochemicals

Abstract:  Soybean oil bodies were isolated from 3 cultivars (Ustie, K98, and Elena) and the occurrence of 2 classes of phytochemicals (tocopherol isoforms and isoflavones) and strength of their association with isolated oil bodies was evaluated. Tocopherol is shown to be closely associated with soybean oil bodies; δ-tocopherol demonstrated a significantly greater association with oil bodies over other tocopherol isoforms. Isoflavones do not show a significant physical association with oil bodies, although there is some indication of a passive association of the more hydrophobic aglycones during oil body isolation. Practical Application:  Oil bodies are small droplets of oil that are stored as energy reserves in the seeds of oil seeds, and have the potential to be used as future food ingredients. If oil body suspensions are commercialized on a large scale, knowledge of the association of phytochemicals with oil bodies will be valuable in deciding species of preference and predicting shelf life and nutritional value

Impact of nitrogen flushing and oil choice on the progression of lipid oxidation in unwashed fried sliced potato crisps

Unwashed, sliced, batch-fried potato crisps have a unique texture and are growing in popularity in the UK/EU premium snack food market. In this study, the storage stability of unwashed sliced (high surface starch) potatoes (crisps) fried in regular sunflower oil (SO) or in high oleic sunflower oil (HOSO) was compared over accelerated shelf life testing (45 °C, 6 weeks); with and without nitrogen gas flushing. Primary oxidation products (lipid hydroperoxides) were measured with a ferrous oxidation-xylenol orange (FOX) assay and volatile secondary oxidation products (hexanal) were quantified by using solid phase micro-extraction gas chromatography mass spectrometry (HS-SPME-GC/MS). Results revealed that crisps fried in SO were the least stable. Flushing the stored crisps with nitrogen gas proved to be effective in slowing down the oxidation rate after frying with sunflower oil, significantly stabilizing the crisps. However, crisps fried in HOSO were the most stable, with the lowest rate of development of oxidation markers, and this has previously not been shown for crisps with a high free starch content

Application of calibrations to hyperspectral images of food grains: example for wheat falling number

The presence of a few kernels with sprouting problems in a batch of wheat can result in enzymatic activity sufficient to compromise flour functionality and bread quality. This is commonly assessed using the Hagberg Falling Number (HFN) method, which is a batch analysis. Hyperspectral imaging (HSI) can provide analysis at the single grain level with potential for improved performance. The present paper deals with the development and application of calibrations obtained using an HSI system working in the near infrared (NIR) region (~900–2500 nm) and reference measurements of HFN. A partial least squares regression calibration has been built using 425 wheat samples with a HFN range of 62–318 s, including field and laboratory pre-germinated samples placed under wet conditions. Two different approaches were tested to apply calibrations: i) application of the calibration to each pixel, followed by calculation of the average of the resulting values for each object (kernel); ii) calculation of the average spectrum for each object, followed by application of the calibration to the mean spectrum. The calibration performance achieved for HFN (R2 = 0.6; RMSEC ~ 50 s; RMSEP ~ 63 s) compares favourably with other studies using NIR spectroscopy. Linear spectral pre-treatments lead to similar results when applying the two methods, while non-linear treatments such as standard normal variant showed obvious differences between these approaches. A classification model based on linear discriminant analysis (LDA) was also applied to segregate wheat kernels into low (250 s) HFN groups. LDA correctly classified 86.4% of the samples, with a classification accuracy of 97.9% when using HFN threshold of 150 s. These results are promising in terms of wheat quality assessment using a rapid and non-destructive technique which is able to analyse wheat properties on a single-kernel basis, and to classify samples as acceptable or unacceptable for flour production

Atmospheric pressure chemical ionisation mass spectrometry analysis linked with chemometrics for food classification – a case study: geographical provenance and cultivar classification of monovarietal clarified apple juices

In the present work, we have evaluated for first time the feasibility of APCI-MS volatile compound fingerprinting in conjunction with chemometrics (PLS-DA) as a new strategy for rapid and non-destructive food classification. For this purpose 202 clarified monovarietal juices extracted from apples differing in their botanical and geographical origin were used for evaluation of the performance of APCI-MS as a classification tool. For an independent test set PLS-DA analyses of pre-treated spectral data gave 100% and 94.2% correct classification rate for the classification by cultivar and geographical origin, respectively. Moreover, PLS-DA analysis of APCI-MS in conjunction with GC-MS data revealed that masses within the spectral ACPI-MS data set were related with parent ions or fragments of alkyesters, carbonyl compounds (hexanal, trans-2-hexenal) and alcohols (1-hexanol, 1-butanol, cis-3-hexenol) and had significant discriminating power both in terms of cultivar and geographical origin

Microencapsulation of Lactobacillus acidophilus NCIMB 701748 in matrices containing soluble fibre by spray drying: technological characterization, storage stability and survival after in vitro digestion

We evaluated sodium alginate, chitosan and hydroxypropyl methylcellulose (HPMC) as co-encapsulants for spray dried Lactobacillus acidophilus NCIMB 701748 by assessing their impact on cell viability and physicochemical properties of the dried powders, viability over 35 days of storage at 25 °C and survival after simulated digestion. Fibres were added to a control carrier medium containing whey protein concentrate, d-glucose and maltodextrin. Sodium alginate and HPMC did not affect cell viability but chitosan reduced viable counts in spray dried powders, as compared to the control. Although chitosan caused large losses of viability during spray-drying, these losses were counteracted by the excellent storage stability compared to control, sodium alginate and HPMC, and the overall effect became positive after the 35-day storage. Chitosan also improved survival rates in simulated GI conditions, however no single fibre could improve L. acidophilus NCIMB 701748 viability in all steps from production through storage and digestion

Development and validation of an APCI-MS / GC-MS approach for the classification and prediction of cheddar cheese maturity

Headspace techniques have been extensively employed in food analysis to measure volatile compounds, which play a central role in the perceived quality of food. In this study atmospheric pressure chemical ionisation-mass spectrometry (APCI-MS), coupled with GC-MS (gas chromatography–mass spectrometry), was used to investigate the complex mix of volatile compounds present in Cheddar cheese of different maturity, processing and recipes to enable characterization of the cheeses based on their ripening stages. Partial Least Square-Linear Discriminant Analysis (PLS-DA) provided a 70% success rate in correct prediction of the age of the cheeses based on their key headspace volatile profiles. In addition to predicting maturity, the analytical results coupled with chemometrics offered a rapid and detailed profiling of the volatile component of Cheddar cheeses, which could offer a new tool for quality assessment and accelerate product development timelines

Hyperspectral imaging for non-destructive prediction of fermentation index, polyphenol content and antioxidant activity in single cocoa beans

The aim of the current work was to use hyperspectral imaging (HSI) in the spectral range 1000-2500 nm to quantitatively predict fermentation index (FI), total polyphenols (TP) and antioxidant activity (AA) of individual dry fermented cocoa beans scanned on a single seed basis. Seventeen cocoa bean batches were obtained and 10 cocoa beans were used from each batch. PLS regression models were built on 170 samples. The developed HSI predictive models were able to quantify three quality-related parameters with sufficient performance for screening purposes, with external validation R2 of 0.50 (RMSEP=0.27, RPD=1.40), 0.70 (RMSEP=34.1 mg ferulic acid g-1, RPD=1.77) and 0.74 (60.0 mmol Trolog kg-1, RPD=1.91) for FI, TP and AA, respectively. The calibrations were subsequently applied at a single bean and pixel level, so that the distribution was visualised within and between single seeds. HSI is thus suggested as a promising approach to estimate cocoa bean composition rapidly and non-destructively, thus offering a valid tool for food inspection and quality control

Non-destructive characterisation of mesenchymal stem cell differentiation using LC-MS-based metabolite footprinting

Bone regeneration is a complex biological process where major cellular changes take place to support the osteogenic differentiation of mesenchymal bone progenitors. To characterise these biological changes and better understand the pathways regulating the formation of mature bone cells, the metabolic profile of mesenchymal stem cell (MSC) differentiation in vitro has been assessed non-invasively during osteogenic (OS) treatment using a footprinting technique. Liquid chromatography (LC)-mass spectrometry (MS)-based metabolite profiling of the culture medium was carried out in parallel to mineral deposition and alkaline phosphatase activity which are two hallmarks of osteogenesis in vitro. Metabolic profiles of spent culture media with a combination of univariate and multivariate analyses investigated concentration changes of extracellular metabolites and nutrients linked to the presence of MSCs in culture media. This non-invasive LC-MS-based analytical approach revealed significant metabolic changes between the media from control and OS-treated cells showing distinct effects of MSC differentiation on the environmental footprint of the cells in different conditions (control vs. OS treatment). A subset of compounds was directly linked to the osteogenic time-course of differentiation, and represent interesting metabolite candidates as non-invasive biomarkers for characterising the differentiation of MSCs in a culture medium

Enhancing Robusta coffee aroma by modifying flavour precursors in the green coffee bean

© 2018 Elsevier Ltd This study attempted to improve Robusta sensory properties by modifying the beans chemical composition. Building on our previous work, which modified bean pH through acid pre-treatment, a model system was developed where, sugar solutions (glucose, fructose, sucrose) were used to pre-treat Robusta coffee beans with the aim to modify the concentration/availability/location of these aroma precursors. Beans were then dried to equal water activity, subjected to equal roast intensity and ground to comparable particle size distributions. The treatment significantly impacted aroma generation during roasting leading to an altered level of pyrazines, furans, ketones, organic acid and heterocyclic nitrogen-containing compounds (p < 0.05). The optimum treatment was 15 g/100 g fructose. 80% treated Robusta could be blended with Arabica in coffee brew without significant aroma differences being perceived when compared to 100% Arabica brew. Furthermore the aroma of the fructose treated Robusta was more stable than Arabica over six weeks accelerated shelflife storage