A.T. Abebe, J. Near Infrared Spectrosc. 14, 67–70 (2006)
67
Short communication
Total sugar and maturity evaluation of intact
watermelon using near infrared spectroscopy
Ashenafi Tessema Abebe
OMI Weighing Machine Inc., Higashi-yagura, 3-11-70, Kusatsu, Shiga, Japan. E-mail: [email protected]
In this study, a near infrared spectroscopy (700–1100 nm) measurement technique was used to evaluate the internal quality of
watermelons non-destructively. A spectrometer and near infrared ray emitting diode were designed and developed to evaluate the
internal quality parameters such as total sugar content and maturity of intact watermelons. A relationship was found between
the maturity of intact watermelon and the diffuse transmittance spectra. The total sugar content was calculated from the second
derivative spectral values at four selected wavelengths. The verification correlation coefficient and standard error of prediction
values were 0.81 and 0.42 Brix% respectively.
Keywords: NIRRED, diffuse transmittance, maturity, total sugar
Introduction
destructive methods, such as extracting juice and chemical
analysis of total sugar content.
The internal qualities of agricultural products include
moisture, starch, protein and fat content, and their maturity.
The problem of watermelon maturity gained the attention of researchers as a direct result of difficulties growers
and distributors face to solve the same problem based on
external features such as colour, texture and conformity.
The near infrared (NIR) diffuse transmittance method is
becoming a promising tool for measuring internal quality
of agricultural products such as watermelon. Non-destructive methods of evaluation have been used to determine
papaya maturity,1 dry matter in onion,2 soluble solid content of intact cantaloupe,3 sugar content of intact peaches,4
acidity, soluble solids and firmness of Jonagold apples,5
optical methods for quality evaluation of fruits6 and nondestructive prediction of internal quality of heat-treated
“Irwin” mango by near infrared spectroscopy.7 Other near
infrared spectroscopic studies report versatile intact fruit
spectroscopy,8 optical properties of selected fruits vs maturity,9 design of a high-speed, fibre-optic blueberry sorter10
and internal quality assessment of kiwifruit.11 Watermelons,
compared to other fruit products, are larger in size and their
internal quality, such as maturity and total sugar content,
is commonly determined based on their external appearance including colour, texture and conformity and by using
Objective
The objective of this research was to examine the potential of the NIR diffuse transmittance method to estimate the
total sugar and maturity parameters of intact watermelons.
Materials and methods
Samples
Watermelons harvested from the Nagano, Akita and
Nigata areas of Japan, specified in Table 1, were used for this
particular study. Large numbers of samples were used at site
to investigate the internal quality parameters of watermelon.
Table 1. Watermelon sample specifications (n = 390).
Watermelon
Max.
Min.
Mean
Weight (kg)
15
3.5
7
Rind size (mm)
15
9.5
10
© NIR Publications 2006, ISSN 0967-0335
68
Total Sugar and Maturity Evaluation of Intact Watermelon
Instrumentaion
Table 2. Spectrometer (Zeiss MCS-NIR) diode array specifications.
In order to acquire the diffuse transmittance spectra for
internal quality measurement, high-energy incident light is
required. A high-energy monochromatic light source, such as
halogen, was found inconvenient as it emits intense heat that
affects measurement accuracy. In this study, a pre-fabricated
array of NIR ray-emitting diodes (NIRRED) capable of emitting near infrared rays with a wavelength of 700–1100 nm
was developed and used as a source of incident light.
Spectral acqusition
A watermelon sample was positioned in contact with the
receptor urethane embedded fibre-optic and radiation from the
near infrared emitting diodes, as shown in Figure 1. Radiation
leaving the sample was scanned using a computer-controlled
spectrometer from 700–1100 nm at 0.8 nm increments thus
generating 512 data points per spectrum (Table 2). The standard spectrum was taken from a 15 cm (W × H × B) cubical
Teflon block. The ratio of the watermelon spectral data to the
standard produced a relative diffuse transmittance spectrum
(T) for watermelon, which was converted to an optical density
log (1/T) and the 2nd derivative was computed.
Chemical analysis
Watermelons were cut into approximately two haves and
the edible portion was removed and juice samples were
made with a juicer. The standard total sugar (Brix%) data
was measured from the juice using a refractometer (Atago
PR-101 model, Tokyo, Japan).
Dark box
Pixel size
25 × 2500 µm2
Maximum clock rate
2 MHz
Diode array size
512 pixels
Spectral distance
0.8 nm
Temperature drift
0.005 nm °C–1
NIR imaging
Watermelon samples were sectioned along the equator and
the seeds and flesh colour were visually inspected. The juice off
the edible portion of the upper half of the sample was used for
the measurement of total sugar (Brix). Samples with light pink
tissue, white seeds and sugar content less than 10% Brix were
identified as immature and samples with light red tissue, black
seeds and sugar content greater than Brix 10% were identified as matured. The lower half of the sample was used for the
NIR diffuse transmission test. The sample was positioned on a
NIRRED light tray (100 × 100 mm) where the rind surface faced
the lighting device and the edible surface faced the NIR camera
(CCD type with spectral range 400–1000 nm and 768 × 498
pixel array) in a dark box. Figures 2, 3 and 4 are examples of
watermelon tissue images taken using the NIR camera.
Data analysis
A step-forward linear regression analysis program was
developed and used in the computation of correlation values
of the 2nd derivative diffuse transmittance spectra of intact
watermelon with the standard Brix values as
SS = kx(λ) + C0
Watermelon
where,
SS = standard total sugar; Brix(%)
Diffuse
Transmittance
Optical
NIRRED
Fibre
Spectrometer
PC
No seed image
Urethane
Foam
Figure 1. NIR ray emitting diode (NIRRED; with inner
diameter = 50 mm and outer diameter = 110 mm) diffused transmittance system for watermelon internal quality measurement (optical
fibre sensing diameter 600 µm).
Figure 2. Example of image of distribution and intensity of NIRdiffuse transmittance of immature watermelon tissue.
A.T. Abebe, J. Near Infrared Spectrosc. 14, 67–70 (2006)
69
Brix(%) = α1x(λ1) + α2x(λ2) + α3x(λ3) + α4x(λ4) + C0
where,
α1, α2, α3, α4 = regression coefficients of selected wavelengths
λ1, λ2, λ3, λ4 = selected wavelengths
C0 = constant
Seed
Results and discussion
Total sugar evaluation
Results of the investigation of the relationship between
spectral and chemical data of watermelons from three major
production regions of Japan showed that NIRRED system
based NIR spectroscopy gave good results in determining
the total sugar content, as shown in Table 3 and Figure 5.
Figure 3. Example of image of distribution and intensity of NIRdiffuse transmittance of matured watermelon tissue.
Images and spectra of watermelon
The images in Figures 2, 3 and 4 clearly show the difference in diffuse transmittance distribution for different
maturity levels of watermelon samples. It was observed that
immature watermelon transmitted less NIR light compared
to mature watermelon and over mature watermelon. The
transmitted light intensity around seeds for mature watermelons was greater than other parts of the tissue section.
x(λ) = d2 log(1/Tλ)
C0 = constant
K = regression coefficient
The wavelengths with higher correlations were selected
and the calibration coefficients were computed using multiple linear regression (MLR) analysis as shown in Table 3.
14.0
Predicted NIR (%)
13.0
Seed
12.0
11.0
n=
10.0
9.0
8.0
8.0
9.0
10.0
11.0
12.0
13.0
14.0
Measured SS(Brix%)
Figure 4. Example of image of distribution and intensity of NIRdiffuse transmittance of over matured watermelon tissue.
Figure 5. Measured and predicted total sugar content of watermelon.
Table 3. Statistical analysis for determining sugar content of watermelon.
Selected wavelngth
λ1
λ2
λ3
λ4
SEC
Brix%
SEP
Brix%
r2
Bias
Brix%
n
770
830
865
887
0.52
0.42
0.81
0.28
192
70
Total Sugar and Maturity Evaluation of Intact Watermelon
2.0
matured
immature
tissue seemed to have a light pink colour and the colour of
the seeds was white, while matured watermelon tissue had
a light red colour and the seed colour was black. Immature
watermelon transmitted less light as compared to matured
watermelon and over matured watermelon.
3. An exponential relationship was found between watermelon total sugar and optical density measurements of intact
watermelon. The relationship showed that watermelon absorbance in the NIR region is a good indicator for the prediction
of its maturity.
overmatured
log(1/T)
1.5
1.0
0.5
0.0
700
725
750
775
800
825
850
875
900
925
950
Wavelength (nm)
Figure 6. Optical density curve of mature (12% Brix), immature
(9.6% Brix) and over mature (13% Brix) watermelon.
Figure 6 shows the optical density spectrum of immature,
mature and over mature watermelon. The major difference
in the absorption between mature and immature samples was
observed in the wavelength range of 850–900 nm. This suggests the mean of the optical density spectrum in this range
can be used to investigate watermelon maturity and total
sugar content relationships. The total sugar and mean optical
density at the peak wavelength range of 700–1110 nm gave a
relationship expressed as:
SS = 16.527e–0.4243A,
R2 = 0.76
where,
SS = total sugar content,
A = absorption at mean diffuse transmittance
Conclusion
The above results indicate that:
1. internal quality evaluation of constituents such as total
sugar of intact watermelons can be achieved using the
NIRRED diffuse transmittance spectral analysis
2. the test for watermelons with known date of flowering
indicated that the edible portion of immature watermelon
References
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G.S. Birth, G.G. Dull, J.B. Magee, H.T. Chan and C.G.
Cavaletto, J. Am. Soc. Hort. Sci. 109, 62 (1984).
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Food Soc. Sci. 54, 393 (1989).
4. S. Kawano and S.H. Watanabe, J. Japan. Soc. Hort. Sci.
61(2), 445 (1992).
5. J. Lammertyn, B. Nicolai, K. Ooms, V. De. Smedt and J.
De Baerdemaeker, Trans. ASAE 41(4), 1089 (1998).
6. W I. Budiastra, unpublished PhD dissertation, Kyoto
University, Kyoto, Japan (1998).
7. R. Hasbullah, T. Tanabe, M. Tanaka and T. Tanabe, J.
SASJ. 33(3), 155 (2002).
8. T.A. Ashenafi and T. Suzuki, Proceedings of Japanese
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9. D.R. Bittner and K.H. Norris, Trans. ASAE 11(4), 534
(1968).
10. W.F. McClure, R.P. Rohrbach, L.J. Kushman and W.E.
Bullinger, Trans. ASAE 18(3), 487 (1975).
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Received: 5 April 2005
Revised: 4 November 2005
Accepted: 5 December 2005
Web Publication: 4 April 2006
G.D. Batten, J. Near Infrared Spectrosc. 14, vii–viii (2006)
vii
Book review
Spectrochemical analysis using infrared
multichannel detectors
Graeme D Batten
Seas Spec Pty Ltd, PO Box 487, Woolgoolga, NSW 2456, Australia. E-mail: [email protected]
Spectrochemical analysis using infrared multichannel detectors, Edited by Rohit Bhargava and Ira W. Levin. Blackwell
Publishing Ltd, published November 2005, 328 pp in hardback, ISBN: I 405125047 Price: £110.00, Available on-line from
www.blackwellpublishing.com
This smartly presented volume contains 13 chapters
written by a total of 35 authors—26 based in the USA and
nine in four other countries. It is a timely summary of the
developments in, and current status of, infrared analyses
and provides basic theory and many practical examples of
the value and potential of multi-channel detectors. This
text achieves its aim of capturing the advances made
in imaging, which began over 50 years ago, when a
spectrometer was interfaced with a microscope, attracted
more interest in the 1970s and advanced rapidly along
with improved instruments and computer power over the
last ten years.
The strengths of this publication lie in the clear
descriptions of theory and basic concepts, the breadth of
subjects included and the clear comparisons, aided by black
and white illustrations and many full colour images.
Chapter 1 is an overview of available Fourier transform
and mid-infrared (MIR) instruments, the salient features
of interferometers for data acquisition, evolution of
microspectrometry and multi-channel detectors and data
analysis techniques.
Chapter 2 discusses the advantages of near infrared and
MIR with interesting reports from the 1922 to 1945 era,
which many of us have overlooked. There are some useful
notes on available hardware, detectors and data processing.
Chapter 3 gives an excellent introduction to synchrotron
radiation as the source. The first hand experience of the
authors is evident in their discussion on edge sharpness in
regular and biological samples.
Chapter 4 is an excellent review of data pre-processing
and processing options for hyperspectral images and the
examples given are practical and easy to follow. This topic
is further discussed with reference to real time analysis in
Chapters 7 and 10.
Chapters 5–13 contain further basic information plus a
wealth of experience with examples of practical applications
of spectral imaging. In several examples, the authors mention
the value of non-contact analysis of samples of variable
shape and heterogeneous composition at competitive prices
in real times.
The text contains illustration and additional references to
an extensive range of products including catalysts, polymers,
industrial wastes, foods (including wheat, raw and processed
meats and fruits), animal feeds (mixtures; soils v grasslands),
contamination of foods by pathogens and insects, metal
surfaces, fabrics, petroleum products, gemstones, biological
samples, pharmaceuticals, monitoring patterns from aerosol
sprays, movement of water, distribution of food flavourings,
histology of bone, skin and cartilage and improved detection
of cancerous cells.
While the potential of spectral imaging is reported
in a positive manner, the authors are careful to mention
the limitations imposed by computer power and time per
analysis relative to practical needs and mention alternative
techniques where a comparison is appropriate.
The volume has minimal typographical errors. As in many
publications where different regions of the electromagnetic
spectrum are discussed, it is difficult to standardise on
terminology, such as wavelengths or wavenumber, but this
is a minor criticism. A list of abbreviations and how to
convert between units would be helpful to less experienced
readers.
© NIR Publications 2006, ISSN 0967-0335
viii
The images in this text do more than boost its visual
impact; they clearly demonstrate the potential, and in some
cases, the pitfalls, of the technique for assessing chemical
abundance, statistical analyses of component distribution
and morphological analysis of discrete particles; these being
valuable for inter and intra-sample comparisons.
Book Review
This neatly presented volume would make a valuable
addition to the library of any spectroscopist. It is an essential
primary source of information for students, researchers,
process control managers and quality assurance technicians
and contains references to more detailed information.