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Journal of Physics: Conference Series
PAPER • OPEN ACCESS
Thai Hom Mali rice purity test by using digital image analysis
To cite this article: T Kleawphaipan et al 2019 J. Phys.: Conf. Ser. 1380 012076
View the article online for updates and enhancements.
This content was downloaded from IP address 46.4.80.155 on 10/02/2021 at 01:23
Siam Physics Congress 2019 (SPC2019): Physics beyond disruption society IOP Publishing
Journal of Physics: Conference Series 1380 (2019) 012076 doi:10.1088/1742-6596/1380/1/012076
Thai Hom Mali rice purity test by using digital
image analysis
T Kleawphaipan1 , S Somprasong1 , T Srahongthong2 and B
Pattanasiri2,∗
1
Kasetsart University Laboratory School Kamphaeng Saen Campus Center for Educational
Research and Development, Nakhon Pathom 73140, Thailand
2
Department of Physics, Faculty of Liberal Arts and Science, Kasetsart University
Kamphaeng Saen Campus, Nakhon Pathom 73140, Thailand
E-mail: faasbrp@ku.ac.th
Abstract. The mixing of non-aromatic rice is one of the major problems that impact directly
to Thai Hom Mali Rice export markets. Thus, to preserve the Thai Hom Mali Rice quality and
reputation of exporting, the National Bureau of Agricultural Commodity and Food Standards
(ACFS) establishes a manual of Thai Hom Mali Rice standards, where the rice grain must have
at least 92% of Thai Hom Mali. Nowadays, the DNA-based method has been proved to be a
robust and accurate tool for testing rice purity. However, this adulterants detection technique
is expensive and unfit for a small scale of commercial. In this work, we applied image analysis
by using the computer together with a flatbed scanner to characterize the rice grain and classify
different rice varieties. We found that some rice grain morphological features, such as chaff-
tip width, right concave depth, chaff-tip angle, and interior angle, are possible to be used for
distinguishing between Khao Dawk Mali 105, Chainat 1, Pathum Thani 1, and RD 23.
1. Introduction
Thai Hom Mali Rice, Khao Dawk Mali 105 and RD 15, are one of the most famous rice. They
are popular among the consumers due to their remarkable texture and scent. However, both
species are photoperiod-sensitive rice causing low productivity and cannot meet the world’s
consumption [1, 2]. There is thus an adulterating of similar physical appearance rice, such as
Suphan Buri 1 and Pathum Thani 1, causing a decrease in rice quality and a complaint from
the consumer. Because of that, the Ministry of Commerce proclaimed a regulation of the Thai
Hom Mali rice standard to preserve the quality and reputation of Thai rice exporting [2].
There are several methods to classified species of rice by investigated their chemicals and
physicals properties [3]. The most accurate and acceptable tool is an analysis of rice heredity
[4]. However, it requires a substantial amount of cost which is not suitable for small retailers.
Nowadays, physical analysis by using image processing becomes more popular. Image-based
approaches have been applying to many fields, such as medical and agriculture [5, 6]. To
investigate and classify an adulteration of Thai Hom Mali Rice with other varieties, we analyzed
several morphological features of both Thai Hom Mali Rice and non-aromatic rice that similar
in appearance, including Khao Dawk Mali 105, Chainat 1, Pathum Thani 1, and RD 23. In this
work, we used a flatbed scanner together with an acrylic template to obtain rice images. The
morphological features of rice grain are characterized by using image analysis in MATLAB.
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution
of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Published under licence by IOP Publishing Ltd 1
Siam Physics Congress 2019 (SPC2019): Physics beyond disruption society IOP Publishing
Journal of Physics: Conference Series 1380 (2019) 012076 doi:10.1088/1742-6596/1380/1/012076
2. Material and methods
In this work, five varieties of rice seeds, Khao Dawk Mali 105 (KDML105), Chainat 1 (CHN1),
Pathum Thani 1 (PTT1), and RD 23 (RD23), were used as shown in table 1. All samples were
grown and harvested in Thailand. KDML105 and CHN1 samples were acquired from Nakhon
Ratchasima Rice Seed Center, while PTT1 and RD23 were acquired from Suphan Buri Rice
Research Institute and Pathum Thani Rice Research Center, respectively.
Table 1. Types of rice and their typical image.
Rice variety Growing season (in 2018) Seed Grain
KDML105 Wet
CHN1 Wet
PTT1 Wet
RD23 Dry
Before image acquisition, imperfect grains, such as broken grains and grain with molds or
fungi, must be removed. Flatbed scanner (Epson Perfection V800 Photo) was used with a 20.5
cm x 18 cm acrylic template with 17 x 27 laser-drilled holes. This technique facilitates the
separation of touching grains and provides 459 grains per scan. The image was acquired in film
positive mode at the resolution of 3200 dpi. Image segmentation and analysis were performed
with MATLAB R2017a.
Figure 1. Grain morphological traits.
2
Siam Physics Congress 2019 (SPC2019): Physics beyond disruption society IOP Publishing
Journal of Physics: Conference Series 1380 (2019) 012076 doi:10.1088/1742-6596/1380/1/012076
Figure 2. Boxplot of morphological traits: (a) area per box, (b) radius ratio, (c) L1 , (d) L2 ,
(e) LA, (f) RA, (g) seed width, (h) seed height, (i) glumes angle (θ1 ), (j) chaff-tip angle (θ2 ), (k)
Kd Ku , (l) Ld Lu , (m) chaff-tip width (KL), (n) dK, (o) dL, and (p) interior angle φ, of Chainat
1 (CHN1), Khao Dawk Mali 105 (KDML105), Pathum Thani 1 (PTT1), and RD 23 (RD23).
3
Siam Physics Congress 2019 (SPC2019): Physics beyond disruption society IOP Publishing
Journal of Physics: Conference Series 1380 (2019) 012076 doi:10.1088/1742-6596/1380/1/012076
To describe grain shape, several morphological traits, such as grain area, box area, area per
box, perimeter, diameter, radius ratio, seed height, and seed width were observed (see figure 1).
The grain area and box area are defined as the total number of pixels of grain and the total
number of pixels in the rectangle that fit the grain, respectively. The area per box is the ratio
of grain area to box area. The diameter is defined as the diameter of a circle that has the same
area of the grain. The radius ratio is the ratio between perimeter to diameter. Seed height
is defined as the longest line connecting the awn and pedicel points, while seed width is the
longest line that perpendicular to the seed height. Interior angle, concave depth, and key lines
that defined by seed contour are also observed. When the pedicel is at the top, the left area
(LA) and right area (RA) are defined as the left-hand side area and right-hand side area of the
seed, respectively. CD is defined as the length at that perpendicular to the seed height at its
center. KL is a chaff-tip width. L1 and L2 are defined as the length that perpendicular to the
seed height at the 1/6 and 5/6 of seed height, respectively. Consequently, L1A and L2A are the
areas of seed above and below L1 and L2, respectively. See [7, 8] for more details about the rice
grain morphological features.
3. Results and discussion
Figure 2 shows the boxplots of (a) area per box, (b) radius ratio, (c) L1 , (d) L2 , (e) LA, (f) RA,
(g) seed width, (h) seed height, (i) glumes angle (θ1 ), (j) chaff-tip angle (θ2 ), (k) Kd Ku , (l) Ld Lu ,
(m) chaff-tip width (KL), (n) the left concave depth (dK), (o) the right concave depth (dL), and
(p) interior angle (φ). The results show that, among these quantities, there is a possibility that
KL can be used for sorting KDML105 out from CNT1, while dL can be used to differentiate
KDML105 from CNT1 and RD23. In addition, θ2 and φ can be used to distinguish between
PTT1 and RD23.
4. Conclusion
In this work, we applied image analysis by using a computer together with a flatbed scanner
to characterize the rice grains. Several morphological traits have been considered to distinguish
between the Thai Hom Mali Rice seed and ordinary, non-aromatic rice (Chainat 1, Pathum
Thani 1, and RD 23). We found a possibility that some of those traits, such as rice grain chaff-
tip width, right concave depth, chaff-tip angle, and interior angle, can be used to distinguish
them. These illustrate the applicability of image processing to purify the test of rice that quite
similar in appearance.
Acknowledgments
The authors thank Dr.Apichart Vanavichit and Dr.Siriphat Ruengphayak for fruitful discussions.
T Kleawphaipan was sponsored by Science Classrooms in University-Affiliated School Project
at Kasetsart University Kamphaeng Saen Campus. Rice seed samples were provided by Suphan
Buri Rice Research Institute, Pathum Thani Rice Research Center, and Nakhon Ratchasima
Rice Seed Center. Part of the work was performed at Rice Science Center (RSC) & Rice Gene
Discovery Unit (RGDU), Kasetsart University Kamphaeng Saen Campus.
References
[1] Prathepha P 2009 Weed Biol. Manag. 9 1–9
[2] Rerkasem B 2017 ASR: CMU J. Soc. Sci. Humanit. 4 1–26
[3] Suwannaporn P, Pitiphunpong S and Champangern S 2007 Starch-Stärke 59 171–7
[4] Wei J, Xie W, Li R, Wang S, Qu H, Ma R, Zhou X and Jia Z 2019 Heredity 28 1–4
[5] Liming X and Yanchao Z 2010 Comput. Electron. Agr. 71S S32–9
[6] Robertson S, Azizpour H, Smith K and Hartman J 2018 Transl. Res. 194 19–35
[7] Kuo T Y, Chung C L, Chen S Y, Lin H A and Kuo Y F 2016 Comput. Electron. Agr. 127 716–25
[8] Huang K Y and Chien M C 2017 Sensors 17 809
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