High-throughput screening for aroma production in food fermentations.

A microtiter plate (MTP) method was developed to screen 1064 unique microorganisms-substrate fermentations for production of 68 target aroma compounds. Based on the number of hits identified by GC-MS, 50 fermentations were repeated at 50-mL scale in flasks. Comparison of GC-MS data showed that scaling up from MTP to flask did not generally result in large differences between the volatile profiles, even with a wide variety of substrates (juice, food slurry and food side-streams) and microorganisms (yeast, bacteria and fungi) used. From the screening results, Lactobacillus plantarum fermentation of chilli pepper was further studied as a high amount of phenols, especially guaiacol and 4-ethylphenol, was produced after fermentation. From HPLC-MS and sensory analysis, capsaicin was shown to be a probable precursor for these phenols and a potential mechanism was proposed. The protocol described herein to screen aroma compounds from fermentation of agri-food products and side streams can support development of clean label flavourful food ingredients.

Flavor-protein interactions for four plant proteins with ketones and esters.

The interaction between flavors and proteins results in a reduced headspace concentration of the flavor, affecting flavor perception. We analyzed the retention of a series of esters and ketones with different chain lengths (C4, C6, C8, and C10) by protein isolates of yellow pea, soy, fava bean, and chickpea, with whey as a reference. An increase in protein concentration led to a decrease in flavor compound in the headspace as measured with atmospheric pressure chemical ionization time-of-flight mass spectroscopy (APCI-TOF-MS). Flavor retention was described with a flavor-partitioning model. It was found that flavor retention could be well predicted with the octanol-water partitioning coefficient and by fitting the hydrophobic interaction parameter. Hydrophobic interactions were highest for chickpea, followed by pea, fava bean, whey, and soy. However, the obtained predictive model was less appropriate for methyl decanoate, possibly due to its solubility. The obtained models and fitted parameters are relevant when designing flavored products with high protein concentrations.

Non-linear rheology reveals the importance of elasticity in meat and meat analogues.

The interest in plant-based meat analogues as an alternative to meat is currently growing. Rheological benchmarking is used to reveal how closely meat analogues resemble the original meat products. Texture maps and dissipation colour schemes were used to reveal similarities in and differences between rheological responses of meat and meat analogues (especially chicken analogues). Under heating, meat analogues differ in terms of their lower elasticity compared with heated meat. The changes caused by heating meat and meat analogues were different as well. Heating of meat resulted in a tougher and more elastic material, while heating has a minor effect on meat analogues. Future developments should therefore focus on routes to create more elasticity and possibly allow heating effects on texture to mimic meat characteristics even better.

Dynamic flavor release from chewing gum: Mechanisms of release.

Dynamic flavor release curves from chewing gum were measured using an Artificial Mouth coupled to the AFFIRM®. A flavor distribution model for chewing gum is proposed, where flavor is present as droplets in both the hydrophilic (water-soluble) and the hydrophobic (water insoluble) parts of the chewing gum and as molecularly dissolved in the hydrophobic part of the gum. During mastication, the flavor droplets in the water-soluble phase are released and responsible for an initial burst release. The flavor droplets captured in the gum-base are pushed towards the interface by mastication and are responsible for the subsequent release. The flavor molecules dissolved in the gum-base, released by diffusion, are only responsible for the release at very long time scales. It was found that the oil-water partition constant is an important parameter to explain the flavor release, where hydrophobic components show slower and longer release, while more hydrophilic components show more burst release.

A predictive model for flavor partitioning and protein-flavor interactions in fat-free dairy protein solutions.

Flavor perception is directly related to the concentration of aroma compounds in the headspace above a food matrix before and during consumption. With the knowledge of flavor partition coefficients, the distribution of aroma compounds within the food matrix and towards the headspace can be calculated. In this study static headspace measurements and modelling are combined to predict flavor partitioning of a wide range of flavor compounds above fat-free dairy protein mixture solutions. AFFIRM® (based on Atmospheric Pressure Chemical Ionization-Mass Spectrometry) was used to measure the static headspace concentrations of 9 flavor compounds (3 esters, 3 aldehydes and 3 alcohols) above protein solutions with different concentrations and ratios of sodium caseinate and whey protein isolate. Proteins had a small pushing out effect, leading to increased release of hydrophilic flavor compounds. This effect was negligible for more hydrophobic compounds, where clear retention was observed. An increased total protein concentration and higher whey to casein ratio increased the retention for all flavor compounds. Within the same chemical class, the retention increased with chain length. The experimental data was interpreted with a model describing flavor partitioning in protein solutions (Harrison & Hills, 1997), thereby enabling to extract protein-flavor binding constants. A clear power law was found between the protein-flavor binding constant and log P (octanol-water partition coefficient). Assuming solely non-specific hydrophobic interactions gave satisfying partitioning predictions for the esters and alcohols. For aldehydes specific chemical interactions with proteins turned out to be significant. This rendered a binding constant for whey protein that is 5 times higher than for caseinate in case of esters and alcohols, and 3 times higher in case of aldehydes. The model can accurately predict equilibrium flavor partitioning in dairy protein mixtures with only the knowledge of the octanol-water partition coefficients of the flavor compounds, and the composition of the protein mixture.

Novel Methodology for Measuring Temperature-Dependent Henry's Constants of Flavor Molecules.

A new methodology is presented to measure water-air partition coefficients (Henry's constants) of volatiles, using APCI-MS. Significant advantages over other Henry's constant determination methods include the short measurement and sample preparation time and the possibility for simultaneous measurement of multiple volatiles. The methodology is validated by obtaining good agreement with reliable literature values for a series of 2-ketones. The methodology is further explored for eight key volatiles typically found in citrus fruits, including the temperature dependence of the Henry's constant. Using these data can improve estimates of flavor losses during processing and volatile release during consumption.