Outline General concepts Instruments Applications reflectance, - PowerPoint PPT Presentation

Outline  General concepts  Instruments  Applications  reflectance, absorption, fluorescence  Non-conventional instruments for absorption spectroscopy  Spectroscopy by mobile devices  Raman spectroscopy  The kitchen of the future 1

2 the Swiss-knife of XXI century Smartphone:

3 Smartphone – Startrek tricorder

China and mobile phones http://www.chinadaily.com.cn/china/2013 -01/25/content_16172589.htm

5 Trends

 Scenarios for smartphone-based sensors  Passive: info retrieval only  Plug-in sensors  Embedded spectroscopy 6

Passive: info retrieval only Smartphone camera used to read QR or bar-code  QR/bar-code pic sent through internet to a data warehouse where  the info is stored Info retrieval using internet connection  This approach implies that the info requested by the consumer has  been acquired and is available 7

Embedded spectroscopy  White LED = source  Camera = spectrometer  3 channels only: RGB  Added chemometric functionalities for a better exploitation of spectroscopic info 0.014 OPTIMO Samsung 0.012 0.01 Normalized Units 0.008 0.006 0.004 0.002 0 400 450 500 550 600 650 700 750 Wavelength ( nm ) + clip-on coupling and diffractive optics 8

Embedded spectroscopy outside source 9 Smith et alii, PLOS ONE, vol. 6, 2011, e17150

Embedded spectroscopy Shazam for materials........ & food Advanced prototype - 3D printed http://store.publiclab.org/products/smartphone-spectrometer 10

Embedded spectroscopy by means of a special cover https://fringoe.com/

Lab in a phone http://innovate.ee.ucla.edu/welcome.html http://www.iplaustralia.com/

https://phonebloks.com/plan/ - http://www.dscout.com

Smartphone sensors  External unit with sensors  Plug-in through socket  Blue-tooth connection for stand-alone units http://www.mydario.com/#Device J. Li et alii, IEEE Sensors Conf. 2012 http://www.sensorcon.com/sensordrone/

Mobile spectroscopy + cloud computing 15

TellSpec http://www.tellspec.com 16

SCiO http://www.consumerphysics.com 17

SCiO http://www.consumerphysics.com 18

SCiO http://www.consumerphysics.com 19

Outline  General concepts  Instruments  Applications  reflectance, absorption, fluorescence  Non-conventional instruments for absorption spectroscopy  Spectroscopy by mobile devices  Raman spectroscopy  The kitchen of the future 20

………… Steps towards multicomponent analysis Spectroscopy  Chemometrics  Classification maps  Library of ref. spectra / analytical data  Model for prediction of quality indicators  Validation  R 2

Raman spectroscopy • Most of the scattered light has the same frequency/energy as that of the incident light (scattering Rayleigh) • A slight fraction of the incident light donates or receives energy to contribute to a change in the vibrational and rotational state of molecules. • The change in the photon energy as a result of inelastic scattering of light with anti-Stokes Stokes molecules is the “Raman shift” I Raman   Raman shift (cm -1 ) 22

Raman @785nm VS @1064nm 8000 M1 7000 M2 M3 6000 Power ( counts / s ) M4 5000 M5 M7 @ 785nm 4000 PL 3000 M6 M8 2000 1000 0 0 500 1000 1500 2000 2500 3000 Raman Shift ( cm -1 ) 1000 Maple Syrup Honey Lizzano Honey Mielizia 800 Crystal Honey Power ( counts / s ) @ 1064nm 600 400 200 0 500 1000 1500 2000 2500 3000 Raman Shift ( cm -1 ) 23

Raman – food fingerprints salmon olive oil different brands powder milk whole and skim R.M. El-Abassy et alii, JAOCS , vol. 86, 2009, pp. 507-511 C.M. McGoverin et alii, Anal. Chim. Acta , vol. 673, 2010, pp. 26-32 fresh herbs N.K. Afseth et alii, Anal. Chim. Acta , vol. 572, 2006, pp. 85-92 B. Schrader, J. Mol. Str. , vol. 480-481, 1999, pp. 21-32 24

25 Raman spectroscopy @ 1064 nm

Raman spectroscopy @ 1064 nm Laser power: 400 mW Detector cooling: - 55°C RamSpec-1064nm-HR BaySpec Inc., San Josè CA www.bayspec.com www.bayspec.com www.rigakuraman.com www.wysri.com www.metrohm.com

Raman spectroscopy for honey applications: the collection of honeys from Calabria  Distinguishing the botanic origin  Predictive models for sugar profile  Potassium as important nutraceutic indicator

Raman spectra 0.12 Citrus Chestnut 0.1 Acacia Normalized Units 0.08 0.06 0.04 0.02 0 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 Wavenumber ( cm -1 )

0.12 Citrus Chestnut 0.1 Acacia Normalized Units 0.08 0.06 0.04 0.02 0 Raman band Main Secondary 800 1000 1200 1400 1600 Wavenumber ( cm -1 ) (cm ‐ 1 ) contribution contribution 707 Fructose Concentration = 20% w/w 0.16 821 Fructose Sucrose Fructose 0.14 867 Fructose Glucose Glucose Maltose Output ( conts / ms ) 0.12 917 Glucose Maltose 1060 ‐ 1080 Fructose Glucose 0.1 1127 Glucose Maltose 0.08 1267 Fructose Glucose 0.06 1372 Glucose Maltose 0.04 1460 Fructose Glucose 0.02 800 1000 1200 1400 1600 Wavenumber ( cm -1 )

Distinguishing the botanic origin 0.12 Citrus PCA + LDA + KNN Chestnut 0.1 Acacia Normalized Units 0.08 0.06 1.5 0.04 h31 1 0.02 tc h28 h32 0.5 h21 h26 h23 0 800 1000 1200 1400 1600 0 Wavenumber ( cm -1 ) h27 DF 2 -0.5 h30 h14 ta -1 h19 -1.5 Citrus -2 Chestnut Acacia h25 -2.5 -2 -1 0 1 2 DF 1

Sugar profile 60 450 50 Sugar content ( mg / g ) Sugar content ( mg / g ) 400 40 350 30 20 300 10 250 0 glucose fructose DS-Maltose DS-TIKN Total TS

R 2 = 1 Results of PLS predictive models for sugars & potassium R 2 (cal) R 2 (val) Analyte RMSEC RMSECV Glucose 7,3 0,96 11 0,92 Monosaccharides (mg/g) Fructose 5,5 0,89 7,6 0,82 SUGARS Maltose 3,5 0,83 5,3 0,66 Disaccharides Trehalose+Isomaltose 2,3 0,91 3,6 0,83 (mg/g) +Kojibiose+Nigerose Trisaccharides Erlose+Isomaltotriose 2,6 0,89 3,9 0,80 (mg/g) +Panose POTASSIUM (  g/g) 0,3 0,97 0,5 0,94 A.G. Mignani et alii , IEEE-JLT, 2016

Raman fingerprints of blueberry juices Brix and Carbohydrates Parameter and Carbohydrates BRIX model results degrees RMSEC 0,80 g/hg 0,97% RMSCV 0,97 g/hg 1,1% R 2 (cal) 0,887 0,9 R 2 (val) 0,840 0,88

Mycotoxins in wheat flour DON – Raman spectra and predictive model Cross ‐ validation Parameter Calibration 4 levels of contamination: (LOO) 1) < 20 ppb RMSE (ppb) 313 357 2) 100 ‐ 500 ppb R squared 0,72 0,65 3) 500 ‐ 1000 ppb 4) > 1000 ppb 34

Mycotoxins in wheat flour DON – Raman spectra and predictive model 0.5 DON < 400  g/Kg DON < 500 DON > 400  g/Kg DON >= 500 0.4 Normalized Units 0.3 0.2 0.1 0 500 1000 1500 2000 KNN decision border ( K = 3 ) Wavenumber ( cm -1 ) 0.4 DON < 400  g/Kg DON < 400  g/Kg DON < 500 ppb DON < 500 DON < 500 ppb DON < 500 90 DON > 400  g/Kg DON > 400  g/Kg DON >= 500 ppb DON >= 500 DON >= 500 ppb DON >= 500 90 89 90 14 0.2 90 90 91 14 14 89 91 90 0.2 89 91 91 91 90 86 90 33 33 14 90 33 33 33 20 91 90 91 90 90 33 20 91 33 90 33 29 91 89 29 91 21 86 30 20 21 29 21 89 30 30 21 14 91 29 30 90 30 89 28 33 33 33 33 29 28 14 30 90 33 33 91 90 21 30 28 33 0 28 14 91 20 30 33 28 98 21 20 0 21 91 91 89 89 20 91 29 21 29 21 28 PC 3 86 21 21 29 29 30 29 30 98 20 29 89 21 20 14 86 PC 2 28 98 28 29 21 30 30 86 86 29 28 29 86 21 30 98 20 98 20 21 30 28 86 98 21 30 28 20 30 89 29 14 86 98 29 28 28 20 98 98 89 20 98 20 14 28 28 98 98 -0.2 98 14 98 -0.2 98 28 14 86 89 98 89 89 14 86 86 20 86 86 14 20 86 89 -0.4 86 14 0.2 1 0 89 0.5 -0.2 14 0 -0.6 -0.4 -0.5 -1 -0.5 0 0.5 1 1.5 PC 2 PC 1 35 PC 1

Outline  General concepts  Instruments  Applications  reflectance, absorption, fluorescence  Non-conventional instruments for absorption spectroscopy  Spectroscopy by mobile devices  Raman spectroscopy  The kitchen of the future 36

Home farming http://www.nextnature.net/2009/10/food- design-in-the-21th-century/

https://www.alamy.com/indoor-soil-free-gardens-with-herb-plants-and-vegetables-producing-food-on- display-at-the-consumer-electronics-show-ces-in-las-vegas-nv-usa-image221407345.html Home farming @ CES 2019

Digital gastronomy http://www.nextnature.net/2010/05/nano- product-the-food-printer/ http://www.nextnature.net/2010/01/digital- gastronomy/

https://www.naturalmachines.com/foodini/ Digital gastronomy

https://nimasensor.com/ http://situscale.com/ Curiosity and gadgets

The Internet of Things - IoT 42

The kitchen of the future http://www.digitaltrends.com/home/heck-internet-things-dont-yet/

The fridge of the future – a family hub http://koreabizwire.com/from-ai-to-iot-home-appliances-get-tech-treatment/99404 44

The fridge of the future – a community hub https://pulsenews.co.kr/view.php?year= 2017&no= 565012 45