1. Non-destructive Measurement of Color, Firmness and Lycopene Content of Tomato using Visible and NIR Spectroscopy
Limei Chen
Vijaya Raghavan, Ph.D
Denis Charlebois, Ph.D
Marie Thérèse Charles, Ph.D
Clément Vigneault, Ph.D
50th Annual Conference/Conférence Annuelle
13-16 July/juillet, 2008
Lonsdale Quay Hotel, 123 Carrie Cates Court
North Vancouver, British Columbia, Canada

2. Outline Introduction Objective Materials and methods Results
Conclusions

3. Tomato 2006 world production: 125 Tg*
Low in fat, calories and cholesterol-free; rich in vitamins A and C, lycopene, and β-carotene
Skin color and firmness - two important quality attributes for consumers**
References: *FAOSTAT online, faostat.fao.org/default.aspx
**Tijskens and Evelo, Postharvest Biology and Technology, 4, 85–89

4. Health benefits of lycopene
A carotenoid imparting red color to fruits
Potent antioxidant: neutralize free radicals, protect body cells against oxidative damage
Possible preventive effect against several types of cancer (e.g. liver cancer, lung cancer and prostate cancer)
there is currently no recommended daily amount of lycopene intake.
the suggested daily intake of lycopene was 5-10 mg.
Cooking and processing tomatoes stimulates and concentrates their lycopene content, making tomato pastes and sauces a rich source. Lycopene is fat-soluble, therefore, its absorption can be enhanced by adding a little fat to meals – such as olive oil -when cooking with tomato products.
References: Clinton, Nutrition Reviews, 56, 35–51
Rao and Agarwal, Journal of the American College of Nutrition, 19,

5. Introduction of vis/NIR spectroscopy
Vis/NIR spectroscopy - a spectroscopic method utilising the visible and near infrared region of the electromagnetic spectrum (from about 380 to 2500 nm)
(Photo:

6. Principle of spectroscopy
NIR spectroscopy
Large number of overtones and combination bands results in broad, poorly defined peaks
Higher signal-to-noise ratio compared to mid-IR spectroscopy

7. NIR application in food analysis
Good results for predicting SSC and dry matter
Grading line with NIR sensors are available from many companies (e.g. Aweta, Greefa, Mitsui-kinzoku)
Papers about fresh tomato analysis

8. Objective Problem Objective
Current methods to measure the lycopene content are laborious, destructive and organic solvents needed
Different instruments are employed for evaluation of tomato quality
Objective
Study the feasibility to evaluate the quality of tomatoes with non-destructive method based upon vis/NIR spectroscopy
Establish calibration models to predict color, firmness and lycopene content, simultaneously

9. Materials and methods 90 tomatoes Stored under 16ºC, 90-93% RH
Spectra and quality parameters of 6 tomatoes measured at 1, 5, 8, 12 and 16 days of ripening (DOR)
Cultivars
2 (cv. DRK 453 & cv. Trust )
Measuring times 5
(breaker, turning, pink, light-red, red)
Tomatoes in each combination of cultivar and DOR 3
Collection times
3 (2 for calibration, 1 for validation)
Total No. of tomatoes
= 2*5*3*3 = 90

10. Approach for building a spectroscopic method
Collecting spectral data (x-variables)
Determining quality parameters
(y-variables) by reference methods
Developing the calibration model
Y = f (x)
Validating the model

11. Spectra acquisition
Spectrometer (FieldSpec® Pro FSP P) coupled with a reflectance contact probe
6 (1 and 5 DOR) or 4 (8, 12 and 16 DOR) equidistant positions around the equator
Reflectance spectra nm

12. Color and firmness measurement
Firmness measured by a universal testing machine, expressed as peak force (N)
Based on CIELAB system, color value L*, a*, b* measured by Minolta Chromameter

13. CIE L* a* b* TCI = 2000a*/(L*(a*2+b*2)1/2)*
a*/b* ratio is a better index than a* in distinguishing varieties**
(Photo:
References: *Gómez et al., J. Sci. Food Agric, 81, 1101–1105
**Richardson and Hobson, J. Sci. Food Agric, 40, 245–252

14. Lycopene content measurement
Homogenized and filtered to tomato juice extract
According to the reduced volumes of organic solvents method of Fish et al (2002), lycopene content determined by a spectrophotometer
Lycopene (mg/kg) = (A503 * 31.2) / (quantity of tissue used (g))
References: Fish et al., Journal of Food Composition and Analysis, 15,

15. Absorbance spectra
1930 nm
1450 nm
560 nm
1200 nm
675 nm
980 nm

16. Change of quality attributes

17. Multivariate calibration
Software package - “The Unscrambler v9.7”
Partial least squares (PLS) regression method was chosen due to the collinearity of x-variables
Full cross-validation used to determine the optimal PC number
Good PLS model: low RMSEC, RMSECV or RMSEP, high R2, SDR (SD/RMSEP)>3

18. Wavelength range selection
For a*/b* nm

19. Wavelength range selection
For TCI nm

20. Wavelength range selection
For firmness nm

21. Wavelength range selection
For lycopene content nm

22. Model results

23. Model results
TCI
R2= RMSECV=2.02
SDR=8.84

24. Model results

25. Model results

26. External validation
Parameters
Wavelength range (nm)
Preprocessing method
No. of PCs
RMSEP R2
SDR
Color a*/b*
S.Golay 1st derivative 2
0.06
0.99
10.49
TCI - 3
1.52
11.74
Firmness 4
1.44
0.97
6.12
Lycopene 8
2.15
0.96
5.18
The result of firmness was superior to that reported by Shao et al. (2007) (r = 0.82, RMSEP=15.80)
The result of lycopene was better than that reported by Baranska et al. (2006) using NIR (R2=0.85 and SECV=91.19)

27. Correlation of quality attributes

28. PLS2 model results 450-1100 nm 6 Color a*/b* 0.05 0.99 10.57 0.06 8.89
Wavelength
No. of
PCs
Parameters
Calibration
Cross-validation
External validation
RMSEC R2
RMSECV
SDR
RMSEP nm 6
Color a*/b*
0.05
0.99
10.57
0.06
8.89
TCI
2.25
0.98
2.49
7.17
1.75
11.65
Firmness
1.85
0.93
2.24
0.90
3.10
1.44
0.97
4.83
Lycopene
2.75
3.17
0.91
3.35
3.03
0.92
3.51

29. Conclusions
It is feasible to build a fast and non-destructive measurement of color, firmness and lycopene content of tomato fruits based on vis/NIR spectroscopy.
Calibration models with excellent performance were established to predict color value a*/b* ratio, tomato color index, firmness and lycopene content of tomato fruits.

30. Thank you