Online monitoring of mashing. infrared spectroscopy

Transcription

1 Online monitoring of mashing processes using the Specshell SIBA infrared spectroscopy Andreas Kunov-Kruse a) ; August Bekkers b) ; Jens Piltoft a) ; Christian Nybo a) ; Jan-Maarten Geertman b) ; Erik Hoffmann-Petersen a) a) b)

2 Outline 1. Technology behind ATR-FTIR spectroscopic SIBA analyzer 2. In-line Results from trial at HEINEKEN Pilot brewery in Zoeterwoude 3. Optimization perspectives from inline monitoring

3 Specshell Spinout from Technical University of Denmark (DTU) 2014 Located in Valby near Copenhagen Employing scientific staff of 7 Close academic connections to DTU Co-financed by innovation fund Markedsmodningsfonden

4 Background for developing the technology Challenging to adapt fast to (seasonal) changes in raw materials, e.g. gelatinization temperature, enzyme content etc. A non-optimal mashing procedure(e.g. yield and poor fermentability) is usually discovered too late Optimal temperature profile? Balancing optimal conditions for: Efficient starch gelatinization α- and β-amylase stability Local or remote monitoring of mashing process No state-of-the-art methods currently available for industrial online realtime monitoring of mashing processes

5 Specshell Inline Brew Analyzer (SIBA) Self draining ATR-MIR spectroscopic unit Robust Industrial pump for continuous sampling Control room Big Data server Remote monitoring CIP ready DN15 tubings Real time output: Total carbohydrate, Degree of polymerization Carbohydrate profiling Fermentability Starch Hydrolysis Products Powerful integrated processing units Data collection: s Rapid analysis < 3 s Integrated SIBA Chemometric Carbohydrate Software

6 ATR-IR spectroscopic control of mashing With in situ spectroscopy, special software and a specially build setup it is possible to monitor the mashing in real time Glycoside bonds, anomeric rearrangements, etc. introduces new features in IR spectra Carbohydrate composition can be elucidated from an IR spectra Glycosidic antisymmetric C-O-C stretching 1155 cm -1 Glucoside bonds/acetal groups

7 NIR vs. MIR spectroscopy NIR and MIR are two very (e.g. typical in-line probes) different techniques! (e.g. SIBA analyzer) (overtones) Easy to implement Limited information (fundamental vibrations) Often challenging to implement Very detailed information

8 Continuous and realtime ATR-IR sampling concept Slurry in Slurry flow Diamond Ultra-low sample penetration (<1µm): no interference from slurry particles No sample filtration needed Corrosion and temperature resistance Sanitary design New spectra can be obtained several times per minute. *Attenuated Total Reflectance

9 Important scales in the mashing process Malted barley 1 mm β-amylases α-amylases + H 2 O Heat α-amylases Limit dextrinases β-amylases raw starch granule gelatinized starch granule α-amylases Microscopy photos: Guelph Ceral Lab ( 9

10 Can ATR-FTIR see everything? Evanescent wave 1 µm IR beam in IR beam to detector 10

11 Data processing scheme Raw spectra Results: Rapid software analysis Rapid drift correction and multivariate methods applied Current version: Total carbohydrate, Polymerization, Carbohydrate profiling Beta version: Fermentable carbohydrates Maltodextrin

12 Applies a combination of powerful multivariate methods Relative degree of polymerization Glucose fraction Specshell software Maltose fraction Lower attenuation limit Relative degree of polymerization RDP = n glycosidebond /n glucose units

13 Orthogonal calibration methods Present use of H 1 -C 13 HSQC-NMR, offers detailed insight in structure (e.g. clear discrimination between α(1-6) and α(1-4) glycoside bonds) UV-VIS to determine exact degree of polymerization in calibration standards(cu ,2 -Biquinolinat method)

14 Testing of SIBA analyzer in HEINEKEN pilot facilities in line monitoring of all-malt pilsner mashing using the SIBA analyzer 25 hl pilot mash tun used In duplicate mashing to investigate reproducibility of the SIBA Analyzer

15 Set up of pilot brew trials Around 10 sample aliquot was extracted from each of the two duplicate mashing procedures Sugar profiles were determined in HEINEKEN labs using Ultra Performance Liquid Chromatography (UPLC) The same aliquots was analyzed by ( off-line ) MIR spectroscopy at Specshell's laboratories in Copenhagen The UPLC and MIR results were perfectly consistent

16 Main results (in-line) Perfect reproducibility Majority dissolved carbohydrates are already produced during mashing-in Rough carbohydrate profile determined Average degree of polymerization of (dissolved) carbohydrates drops rapidly during mashing and approaches value of 2

17 Perspectives of real-time mash monitoring Until now, limited data obtainable from mashing process SIBA analyzer provides continuous Carbohydrate profiling during wort production (mashing) SIBA provides tools for process and raw material optimization

18 From static to dynamic analysis Offline analysis only supplies static snapshot information Time resolved analysis: not just more data Time-derived properties can be determined: Not just position, but also speed and acceleration [C] Mashing-in T 1 T 2 d[c] dt d[c] dt Sample aliquots analyzed offline d[c] dt d[c] dt T 3 Mashing d[c] dt x50 time

19 Using time resolved output in process optimization Possible to determine when growth stagnates: Growth increased when entering temperature ramp i.e. possibly smaller starch granules gelatinizes at higher temperature suggestion from 1st derivative : Duration of T2 step could be shortened E.g. all starch possible gelatinized at T2 [C] Mashing-in T 1 T 2 d[c] dt T 3 Mashing Growth stagnates (i.e. First derivative rapidly approaches zero) Growth increases (i.e. positive second derivative) x50 time

20 Using time resolved output in process optimization Possible to determine when growth stagnates: Growth increased when entering temperature ramp i.e. possibly smaller starch granules gelatinizes at higher temperature suggestion from 1st derivative : Duration of T2 step could be shortened E.g. all starch possible gelatinized at T2 [C] Mashing-in T 1 T 2 d[c] dt T 3 Mashing x50 time

21 Using time resolved output in process optimization Possible to determine when growth stagnates: Growth increased when entering temperature ramp i.e. possibly smaller starch granules gelatinizes at higher temperature suggestion from 1st derivative : Duration of T2 step could be shortened E.g. all starch possible gelatinized at T2 d[carbohydrate] dt [C] is just one of serveral time-resolved outputs! T 2 Mashing-in T 1 d[c] dt Time shorted What could be optimized from:? d maltodextrin dt Time saved T 3 T 3 x50 time

22 Conclusions SIBA mid infrared analyzer able to do real-time inline analysis of mashing process Enables brewer to respond immediately to seasonal changes in raw materials, new recipes etc. by optimizing time/temperature Possibilities for detailed process and raw material optimization using 1st order derivatives

23 Thank you for your attention!