Steam stripping of aroma from roast and ground coffee: A - - PowerPoint PPT Presentation

Steam stripping of aroma from roast and ground coffee: A mathematical modelling approach

David Beverly Peter Fryer, Serafim Bakalis, Estefania Lopez-Quiroga, Robert Farr and John Melrose

Monday 10th September 2018

Why investigate aroma in instant coffee?

Why investigate aroma extraction?

Making coffee ‘more aromatic’ or giving ‘new & improved flavour’ requires process modification Aroma is complex…

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Thiols Diketones Furanones Guaiacols Pyrazines

The instant coffee process and aroma extraction

The instant coffee process

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Roasting Grinding Evaporatio n Spray drying Freeze drying Extraction

AROMA

The aroma extraction process – steam stripping

6 Steam

’00s kg coffee < 1.8 mm grind size 4-70% w/w added water Aromatized condensate 1.1-2.0 barg inlet 2-40 mins steaming Plant scale

• A

previous Government funded collaboration (Innovate UK) with University of Birmingham was project RICE (Reduced Energy Instant Coffee)

• Project aim was to reduce energy and water use

in the freeze drying process by 25% by increasing the solids content of the feed to the freeze-dryer

• Using more concentrated aromas is one way to

achieve this concentration increase

• Process

aims are to maximise yield and concentration

• f

aroma whilst tailoring the sensory profile

The nature of roasted coffee

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Mesopores (~40 μm) Soluble material & aroma starts here Cell wall (~10 μm) Nanoporous

10 20 30 40 50 60 70 80 90 100 Cumulative distribution Q3 / % 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 Density distribution q3* 1 5 10 50 100 500 1000 particle size / µm

Bimodal size distribution of coarse particles (see SEM) and fragments of cell wall (fines) 8 cm

Coffee modelling in literature

1) Caffeine extraction characterized by effective diffusion coefficient 2) Extraction from solid phase to intra- and inter- granular pores using mass transfer coefficients 3) Measurements of aroma extraction fitted with apparent diffusion coefficient and/or Weibull distribution

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1) Spiro, M. and Chong, Y.Y. (1997). The Kinetics and Mechanism of Caffeine Infusion from Coffee: the Temperature Variation of the Hindrance Factor. Journal of the Science of Food and Agriculture, 74, 416-420 2) Moroney,K.M., Lee,W.T., O’Brien,S.B.G., Suijver,F. and Marra,J. (2015). Modelling of coffee extraction during brewing using multiscale methods: An experimentally validated model. Chemical Engineering Science, 137, 216-234 3) Mateus, M.L., Lindinger, C., Gumy, J.C. and Liardon, R. (2007). Release Kinetics of Volatile Organic Compounds from Roasted and Ground Coffee: Online Measurements by PTR-MS and Mathematical Modelling. Journal of Agricultural and Food Chemistry, 55(25), 10117-10128

Model Description

The modelling strategy

10 Oil film dpore δ Mesopore O~(μm) Water-filled mesopore Z dcol Pout Pin Column O~(m) dpart Water film Coarse particle Fine particle Column section O~(cm) Nanoporous cell wall Particle section O~(mm)

Particle scale extraction – the mesopore – aroma’s release from the oil

A spherical oil shell with aroma concentration 𝑑𝑒𝑝 coats the mesopores Partition into water described by octanol-water coefficient 𝐿 Τ

𝑝 𝑥

Transfer coefficient is free diffusion over the pore radius

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𝒅𝒆𝒑 𝒅𝒒 𝒅𝒆𝒑 𝑳 Τ

𝒑 𝒙

𝑠

𝑞𝑝𝑠

Particle scale extraction – intraparticle diffusion

Released aroma undergoes hindered diffusion to the particle surface Diffusivity calculated by Maxwell homogenization of free and hindered diffusion

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Oil-water partitioning and diffusion Hindered diffusion Mesopore Nanoporous coffee cell wall

Particle-water-steam transfer

Water is considered a stagnant film Henry’s law volatility constant determines partition from water to air

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𝐷𝑥 𝐼 𝑆𝑈 𝐷𝑥 𝐷𝑞,𝑆 𝐷𝑕 𝑙𝑥 𝑙𝑕 particle water water-steam boundary layer steam

(1)

1) Carberry, J. (1960). A Boundary-Layer Model of Fluid-Particle Mass Transfer in Fixed Beds. American Institute of Chemical Engineers Journal, 6 (3), 460-462

Column scale advection

Fresh steam enters the column base Open boundary at the column top Everything that exits the column is condensed

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Advection Source: Water-gas mass transfer

𝑑𝑕 𝑨 = 0, ∀𝑢 = 0 Steam

Pressur e and temper ature gradient

Model results Comparisons with data from Mateus et al. (2007)

Mateus, M.L., Lindinger, C., Gumy, J.C. and Liardon, R. (2007c). Release Kinetics of Volatile Organic Compounds from Roasted and Ground Coffee: Online Measurements by PTR-MS and Mathematical Modelling. Journal of Agricultural and Food Chemistry, 55(25), 10117-10128

Published vs Model data – acetaldehyde – the ‘simple’ aroma

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Single coarse particle Coarse + fine particle Optimized cell wall porosity (%) 3.3 2.8 Root mean square error (%) 6.8 5.6

Published vs Model data – acetic acid

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Average Optimized ∆𝐼 𝑆 [𝐿−1] 6400 9408 Root mean square error (%) 67 17

log 𝐼 𝑈𝑐 𝐼298 = − ∆𝐼 𝑆 1 𝑈𝑐 − 1 298

Determines Henry’s constant relation with temperature

Published vs Model data – reactive aroma - Pyridine

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Optimized 𝑙𝑝𝑜 8.1x10-4 Root mean square error (%) 5.2 Assuming a 1:1 ratio or reactants and a reaction rate first order in both reactants leads to a good approximation Aroma-matrix interactions are widely discussed in literature1-3

1.Guichard, E. (2015) Interaction of aroma compounds with food matrices in Parker, J.K., Elmore, S., Methven, L. and José, M. (eds.) Flavour Development, Analysis and Perception in Food and Beverages. Cambridge: Woodhead Publishing, pp. 273-295 2.Hofmann, T., Czerny, Calligaris, S. and Schieberle, P. (2001) Model Studies on the Influence of Coffee Melanoidins on Flavor Volatiles of Coffee Beverages. Journal of Agricultural and Food Chemistry, 49, pp. 2382-2386 3.Charles-Bernard, M., Kraehenbuehl, Rytz, A. and Roberts, D.D. (2005) Interactions between Volatile and Nonvolatile Coffee Components. 1. Screening of Nonvolatile Components. Journal of Agricultural and Food Chemistry., 53 (11), pp. 4417-25

Model results Predictions of plant scale steam stripping

Extraction is determined by polarity and partitioning behaviour

Furaneol concentration in the steam throughout the column with time

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The effect of steaming time

Very polar compounds (e.g. furaneol) increase in concentration with time Other compounds are diluted, with reactive compounds diluting most and apolar compounds diluting the least

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Optimizing extraction

Grind size and steaming time are significant variables but they affect aromas differently Coarse grinds and long times favour polar compounds Finer grinds and short times favour guaiacols

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Summary and next steps

Summary

• Aroma steam stripping can be modelled by oil release, diffusion,

Henry’s law partition and advection

• Three categories of aroma can be identified by physical-chemical

properties

• Process variables (time and grind size) can be optimized for particular

compounds and aromatic notes Next Steps

• Extraction from partially wet coffee + wetting kinetics
• Experimental data at lab and pilot plant scale
• Identifying reactive compounds

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Acknowledgement and thanks

Thank you

Any questions?