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Acoustic Testing for Melon Fruit Ripeness Evaluation during Diff erent Stages of Ripening


Abstract and Figures

Non-destructive impulse response technique was tested on two melon varieties (‘Zard-Eyvanekey’ and ‘Sousky-Sabz’) in five different stages of ripening. Resonance frequency and sound pressure level (SPL) from the impulse response were compared with mass, elastic modulus, soluble solids contents (TSS) and sensory evaluation. Among acoustic and destructive parameters, resonance frequency is an indicator to distinguish of different maturity stage of the melon in both varieties. The sound pressure level (SPL) was not a reliable parameter to evaluate melon ripeness. It was established that the impulse response technique is useful to decide fruit maturity stage and appropriate harvest time.
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Agriculturae Conspectus Scienti cus . Vol.  () No.  (-)
Non-destructive impulse response technique was tested on two melon varieties
(‘Zard-Eyvanekey’ and ‘Sousky-Sabz’) in  ve di erent stages of ripening. Resonance
frequency and sound pressure level (SPL) from the impulse response were compared
with mass, elastic modulus, soluble solids contents (TSS) and sensory evaluation.
Among acoustic and destructive parameters, resonance frequency is an indicator
to distinguish of di erent maturity stage of the melon in both varieties.  e sound
pressure level (SPL) was not a reliable parameter to evaluate melon ripeness. It was
established that the impulse response technique is useful to decide fruit maturity
stage and appropriate harvest time.
Key words
acoustic, impulse, response, non-destructive, melon, ripeness
Acoustic Testing for Melon Fruit
Ripeness Evaluation during Di erent
Stages of Ripening
Moslem NAMJOO 1( )
1 Department of Mechanical Engineering of Biosystems, Faculty of Agricultural,
University of Jirof t, 78671-61167, Jiroft, Iran
2 Department of Mechanical Engineering, University of Jiroft, 78671-61167, Jiroft, Iran
Received: October 8, 2015 | Accepted: March 15, 2016
The authors wish to express their sincere thanks to University of Tehran for financial assis-
tance and staff members of the Faculty of Agricultural Engineering & Technology, particularly
the volunteers who participated in the sensory evaluation. They also acknowledge the Iranian
Agricultural Engineering Research Institute for providing the laboratory facilities.
Agric. conspec. sci. Vol.  () No. 
198 Farhad KHOSHNAM, Moslem NAMJOO, Hossein GOLBAKHSHI
Eating quality of melon depends mainly on harvest of mature
melons at desired stage or ripeness. Generally, optimum eating
quality requires adequate sugar and  avor development, and the
centre meat with a melting texture that progress to a crisp texture
toward the rind. Immature or underripe melons have less sugar
and  avor development, and have a  rmer texture than those
at optimum ripeness. Flavor and texture degrade dramatically
as melon progress from ripe to overripe. It is di cult to judge
ripeness by external characteristics such as size, external color,
stem condition or feel. Ripe melons should be  rm, symmetri-
cal, and fresh looking. Determining optimum melon maturity
at harvest time, however, is a critical but di cult task, even for
experienced growers.
Melons (Cucumis melo L.) are commercially important fruits,
but their ripening has been relatively poorly studied compared
to other fruits such as tomatoes, avocadoes or apples. A large
number of diverse melon cultivars are available that exhibit
variation in ripening characteristics. Early and late harvesting
varieties are known for many fruits, but in melons a selection
can also be made according to fruit color, shape or sweetness.
ere is also variation in the respiratory climacteric, which is
probably a variety-dependent characteristic of melon (Nukaya
et al., 1986; Had eld et al., 1995).
Many people have claimed that the maturity and other qual-
ities of certain fruits, such as apples, melons, and pineapples,
can be determined by listening to the sound produced by strik-
ing them. Several researchers have tried to verify such claims by
studying the acoustic responses of fruits. Hernández Gómez et
al. (2006) evaluated the capacity of acoustic signal response to
monitoring the mandarin fruit  rmness change during storage.
e results indicate that it might be possible to identify the ripe-
ness state of an individual mandarin by using the present method,
and that the nondestructive acoustic test could replace conven-
tional compression test in order to determine mandarin fruit
rmness and expected shelf- life (Gómez et al. 2006). Taniwaki
et al. (2009) investigated time-course changes in the elasticity
index (EI) and texture index (TI) of two persimmon cultivars
during the postharvest period. EI was determined using the for-
mula EI = f22 m2/3, where f2 is the second resonance frequency
of a sample, and m is the mass of the sample.  ey found that
changes in the EI of both cultivars showed quasi-exponential
decays. An improved texture measurement device was used for
measuring the TI of the cultivars.  ey determined the optimum
eating ripeness of persimmons along with the sensory test in
terms of their EI (Taniwaki et al., 2009). Zheng et al. (2014) ad-
dresses the problem of distinguishing between ripe and unripe
watermelons using mobile devices.  ey found that through an-
alyzing ripeness-related features extracted by thumping water-
melons, collecting acoustic signals by microphones on mobile
devices, this method can automatically identify the ripeness of
watermelons. Experimental results show that this method is
currently able to correctly classify ripe and unripe watermelons
with an overall accuracy exceeding 89% (Zeng et al., 2014). To
evaluate the  rmness of fruits Macrelli et al. (2013) compared
three novel sti ness indexes based on acoustic methods and in-
volving Young’s modulus and sound propagation velocity.  e
e ectiveness of the considered indexes is tested by means of an
experimental setup built with two piezoelectric transducers
contacting several samples of kiwifruits during their ripening
process.  ey found that sti ness indexes based on propagation
delays are more rapid and reliable than those based on fruit res-
onance in assessing the ripeness degree (Macrelli et al., 2013).
Hongwiangjan et al. (2015) investigated the maturity as-
sessment of pomelo using acoustic properties obtained from
an impact of fruit, optical properties of the peel and variables
related to oil glands from peel images.  ey found that the clas-
si cation model based on the nondestructive variables showed
that fruits could be separated into immature, early-mature and
late-mature groups with an accuracy of 96.7% (Hongwiangjan
et al., 2015). Mao et al. (2016) developed an acoustic device a er
investigating the in uence of hitting ball and fruit tray on spec-
trum.  ey proposed three  rmness indices to correlate with
rmness of watermelon.  ey found that signi cant correlation
was between  rmness and these indices using linear regressive
model and nonlinear model of arti cial neural network (ANN)
(Mao et al., 2016). An experimental system for nondestructive
rmness evaluation, based on the  exible piezoelectric sensors,
a microphone or and accelerometer was developed and tested
on several fruit and other products, such as: apple (Yamamoto
et al., 1980; Woensel et al., 1988; Armstrong et al., 1989; Chen et
al., 1992; Chen 1993); tomato (Duprat et al., 1997; Schotte et al.,
1999; Baltazar et al., 2008), avocado (Shmulevich et al., 2003);
muskmelon (Sugiyama, 1994); watermelon (Stone et al., 1996;
Diezma-Iglesias et al., 2004); pear (Jancsók et al., 2001; Wang et
al., 2004); peach (Goliáš et al., 2003; Gómez et al. 2005); potato
(Baritelle, 1997), and many others. Most of these researches used
an experimental system for non-destructive  rmness evaluation
based on microphone techniques, which have successfully been
used for several fruits and other products. De Belie et al. (2000)
point out the advantage of the acoustic technique that is an
overall measure and a very reproducible and sensitive method.
With the acoustic impulse response technique the resonance
frequency is obtained by performing a Fourier transformation
on the recorded sound of an intact fruit.  e sound is produced
by impacting the fruit, which then vibrates and causes pressure
waves in the air. For contact sensing typically sensors, such as
accelerometers and piezoelectric  lms are used. For non-contact
sensing a microphone or laser vibrometer is needed.  e prima-
ry objective of the present work was to develop a nondestruc-
tive method based on impulse response technology for quality
evaluation of two di erent melon varieties ‘Zard-Eyvanekey’
and ‘Sousky-Sabz’.
Materials and methods
Sampling of melon
This research was conducted on ‘Zard-Eyvanekey’ and
‘Sousky-Sabz’ varieties obtained from a plantation in Garmsar
township (35º13ʹ20˝ N, 52º20ʹ26 E).  ey were carefully picked
by hand during the summer and autumn in the early morning
from the area of Davarabad, Garmsar, Iran. Fruits were selected
according to color, size and lack of blemishes in order to obtain
homogeneous samples. Before each test series, the melons were
transferred to department laboratory at 18 to 22oC temperature
Agric. conspec. sci. Vol.  () No. 
Acoustic Testing for Melon Fruit Ripeness Evaluation during Different Stages of Ripening
and kept for 24 hours.  ey were selected at  ve di erent stages
of ripening (Table 1). All physical parameters were studied for
65 fruits from each variety. e experiments were conducted at
Biophysical and Biological laboratory of University of Tehran,
Karaj, Iran.
Determination of physical and mechanical
properties and TSS
Mass (M) of the melons was measured with a precision bal-
ance with a sensitivity of 1 g and actual volume was determined
by the water displacement technique.  e true density (ρ) is the
ratio of mass of melon to its actual volume.  ree cylindrical
cores were cut near the equator from one half of each melon,
where the  esh tends to have the largest thickness, using a cy-
lindrical borer through the  esh along the radial direction. Each
14 mm diameter cylindrical core was then cut into 14 mm long
samples.  e modulus of elasticity (E) of melon was evaluated
using 20 samples by Universal Testing Machine (Santam, SMT-
5).  e machine was equipped with a load cell of 150 N at a com-
pressive rate of 25.4 mm/min
For assessment of the total soluble solids (TSS or the ‘Brix’
refractomet ric measurement) a core (22 mm d iameter or greater)
was sampled from a randomly selected equatorial position on
the fruit, and the rind and green inedible tissue (5 mm thick-
ness) and placenta and seed were removed. All remaining edible
mesocarp tissue was juiced.
Panel selection and training
e eating experience of a piece of fruit re ects physical
characters such as texture, and chemical characters such as
sweetness, acidity, and volatiles composition. Sensory analysis
was performed for each harvest by 30-35 untrained assessors
that are familiar with the product in question.  e testers for
the sensory evaluation were graduate students of the faculty of
agricultural engineering and technology, university of Tehran,
Iran.  e esh of fruit was cut into about 2x2 cm pieces and then
samples were coded with 3-digit random numbers.
Presentation of samples was randomized among the panelists
and sessions, and they were presented one at a time under mod-
erate incandescent lighting. Assessors were instructed to clean
their palates with a sip of room temperature water and it was
a small time lag before each sample. Taste analysis acceptabil-
ity (consumer-oriented testing method) scored on a scale of 1-5
where: 1, very bad; 2, poor; 3, fair; 4, good and 5, excellent were
used to assess  ve attributes:  avor, bitterness, sourness,  rm
texture and juiciness. Finally the assessors determined the gen-
eral acceptability (GA) and later the average of it was calculated.
Experimental equipment
e laboratory recording system used to acquire the acoustic
impulse information is comprised of a melon-bed, an impactor
(pendulum), sensing device, a lap-top computer and so ware to
control the experimental setup and to analyze its results. During
the test, the fruit (melon) was placed on a so foam support in
order to create free support conditions and not to disturb the vi-
bration pattern.  e frequency of all individual fruit was meas-
ured on the three positions along the equator approximately 120º
between them.  e impact needs a su cient stroke, mass, veloc-
ity and right angle.  e combination of these causes problems to
miniaturise the little impactor.  e impactor consists of a steel
ball of diameter of 26 mm and a 256 mm long copper rod.  e
weight of the impactor was 72 g; the impact angle was of 70º.
Chen (1993) postulates as i mpact requi rements that the impact
force is high enough to excite the expected frequency range. He
also mentions that the force should be low enough not to damage
the fruit. He suggests that the mass, the initial contact velocity,
the curvature in the contact area, and the elastic modulus of the
impact material should be controlled (Chen, 1993).
e acoustic signal was sensed by a sound level meter (SLM)
type 2270 B&K that have a prepolarised free- eld 1/2” micro-
phone type 4189 B&K with  at frequency response in human
threshold of hearing range (20 to 20000 Hz) and sensitivity
50mVPa-1.  e sound level meter is a measuring instrument
Stage Operation Date Description
1 First series of test Mid-Au
ust Immature
2 Second series of test Late-Au
ust Earl
3 Third series of test Mid-Se
tember Moderatel
4 Forth series of test Late-Se
tember Ri
5 Fifth series of test Mid-October Overripe
Table 1. Date of harvesting and tests series
Figure 2. Setup of experiment for acoustic impact test
Figure 1. Wave form Di splay
Agric. conspec. sci. Vol.  () No. 
200 Farhad KHOSHNAM, Moslem NAMJOO, Hossein GOLBAKHSHI
used to measure sound pressure level. It was at a distance of 2-5
mm from the fruit surface when detecting the impulse acous-
tic response. User friendly Windows-based so ware, Cool Edit
Pro 2.0 was used for the control of the process and the regis-
ter of data, providing an easy output to be used with Microso
Excel. e so ware shows the acoustic signal ‘time versus sam-
pling rate’ for each test on the screen, and saves it in an ASCII
le (Fig.1). Cool Edit Pro 2.0 is combination of digital recording
and editing features. To start recording, we simply used /File/
New to open a new  le, then selected the sample rate, bit resolu-
tion, and number of channels (stereo or mono) that we wanted to
use, pressed OK, and clicked on the Record button in the lower
le area of the main window to begin. When we were done re-
cording, we clicked on Stop and then saved our recording. We
selected the sample rate 192000, resolution 16-bit, and channel
mono.  e Amplitude Ruler displayed the relative amplitude
of a waveform over time.  e ruler’s display format can be set
to either Samples (exact sample value of the data), a percentage
(from -100% to 100%, where 100% is 0 dB) or as a normalized
value (-1 to 1) in Waveform View. In Spectral View, the vertical
ruler is always in frequency (Hz) format.  e display format can
easily be changed, using the le and right and dragging. Fig. 2
shows setup of experiment for acoustic impact test.  e acoustic
response of each melon was measured by hitting the fruit with
an impactor and detecting the output sound by a sound level
meter.  e sound pressure level (SPL) was measured by sound
level meter. A fast Fourier transform (FFT) of the signal was
performed to determine the natural frequencies of the melons
(Fig. 3). Analysis of variance (ANOVA) was applied to the data.
Means corresponding to the di erent stages of evolution were
compared using Duncan’s multiple range tests (p 0.05).
Results and discussion
During ripening, a fruit passes through a series of changes in
color, texture and  avor indicating that compositional changes
are taking place.
Table 2 shows changes in mass (M), true density (ρ), modu-
lus of elasticity (E), total soluble solids (TSS), frequency (f) and
sound pressure level (SPL) during the ripening of melon fruits.
As it can be seen in table, melon mass, total soluble solid and
sound pressure level increased during ripening period, while
true density, modulus of elasticity and frequency decreased from
immature fruits to over ripe fruits.
e Fig. 4 shows that the mass increased progressively in
both varieties over the period of development and ripening as
expected. However, the increasing rates were di erent during
the harvesting stages in both varieties: faster rate in the initial
stages and lower in the  nal stages.  e mass of samples increased
during the growing season rapidly; the mass of ‘Zard-Eyvanekey
increased from 591.73 to 3913.15 grams (about 6.6 times) and
the mass of ‘Sousky-Sabz’ from 569.52 to 3904.56 grams (about
Figure 3. Typical acoustic signal of melon: (a) time domain, (b) frequency domain
Maturity Stage M (g) ρ (kg/m3) E (MPa) TSS (°Brix) f (Hz) SPL (dB)
First 591.8e 901.84
132.25 49.21c
Second 1490.2d 886.13
128.91 49.59c
Third 2978.8c 863.16b 0.211c
9.43c 119.14 54.19b
Fourth 3663.9b 855.45bc 0.199bc 11.07b 113.34 56.93
Fifth 3913.1
842.33c 0.149
111.33 57.74
-Sabz First 569.5e 908.11
128.91 49.66
Second 1581.5d 898.85
0.294b 6.43c 123.05 50.15
Third 3016.6c 878.34
0.226bc 9.30bc 119.14 53.23c
Fourth 3424.7b 865.41b 0.176c 10.80b 114.26 56.25b
Fifth 3904.6
860.03bc 0.154c
111.33 58.22
Means in the same column followed by different letters are significantly different according to Duncan’s test (p<0.05).
Table 2. Changes of physical and mechanical properties and acoustic parameters of melon during harvesting (average values of
65 melons from each variety)
Agric. conspec. sci. Vol.  () No. 
Acoustic Testing for Melon Fruit Ripeness Evaluation during Different Stages of Ripening
6.8 times).  e average of mass in the fourth harvest (ripened),
‘Zard-Eyvanekey’ and ‘Sousky-Sabz’ was estimated to be 3663.92
and 3424.70 grams, respectively.  e ‘Zard-Eyvanekey mass was
higher than the ‘Sousky-Sabz mass in full ripening, alt hough t he
rate of increase of the mass was higher in ‘Sousky-Sabz’ variety.
e true density of two varieties had shown a decreasing trend.
True density or ‘Zard-Eyvanekey’, was 901.84kgm–3 in  rst stage
and 842.33kgm–3 in  h stage (reduction 6.6%), whereas these
values for ‘Sousky-Sabz’ were 908.11kgm–3 and 860.03kgm–3
(reduction 5.3%).  e true density of (865.41kgm–3) was a little
higher than of ‘Zard-Eyvanekey’ (855.45kgm–3) in full ripen-
ing (Fig. 5).
The elastic modulus values decreased in both varieties
throughout ripening (Fig. 6). Its values fall from 0.466 to 0.149
MPa and from 0.417 to 0.154 in ‘Zard-Eyvanekey’ and ‘Sousky-
Sabz’, respectively. Initial elastic modulus values of ‘Zard-
Eyvanekey’ were higher than those of ‘Sousky-Sabz’.  is may
be related to di erences in physiological stage of ripeness, but
also to the higher amount of cell wa ll polysaccharides in ‘Zard-
Eyvanekey’ than in ‘Sousky-Sabz’ pulp. Both varieties have fruits
with high elastic modulus at the  rst harvest date that shows
compact and high density fruit.  e rate of elastic modulus loss
was also higher in ‘Zard-Eyvanekey’ than in ‘Sousky-Sabz’.  e
elastic modulus of ‘Zard-Eyvanekey variety (0.199 MPa) esti-
mated to be higher than in ‘Sousky-Sabz’ variety (0.176 MPa)
in full ripening.
Melons are among the fruits with the highest sugar content.
In melons, sweetness is the dominant consumer acceptance
factor, and total soluble solids (TSS), as a measure of sweetness,
is the most useful chemical measurement for assessing melon
e total soluble solids (TSS) followed upward trends through-
out ripening in both varieties as expected, though values were
higher in ‘Zard-Eyvanekey’ variety than in ‘Sousky-Sabz’ vari-
ety. TSS of ‘Zard-Eyvanekey’ variety was initially at 4.93°Brix
and reached a value of 13.03°Brix, these values were 4.83°Brix
and 12.43°Brix in ‘Sousky-Sabz’ variety (Fig. 7).
e resonance frequency values of ‘Zard-Eyvanekey’ and
‘Sousky-Sabz’ varieties decreased during whole harvesting
period from 132.25 to 111.33 Hz and from 128.91 to 111.33 Hz
respectively.  e average of resonance frequency in the fourth
harvest (ripened) for ‘Zard-Eyvanekey’ and ‘Sousky-Sabz’ was
estimated to be 113.34 and 114.26 Hz, respectively. Consequently,
the resonance frequency of ‘Zard-Eyvanekey’ variety was a little
Figure 4. Mass changes during the fruit ripening of melon
Figure 6. Modulus of elasticity changes during the fruit
ripening of melon
Figure 5. True density changes during the fruit ripening of
Figure 7. TSS changes during the fruit ripening of melon
Agric. conspec. sci. Vol.  () No. 
202 Farhad KHOSHNAM, Moslem NAMJOO, Hossein GOLBAKHSHI
lower than the resonance frequency of ‘Sousky-Sabz’ variety in
full ripening (Fig. 8).
As mentioned, the resonance frequency decreased in both
varieties during ripening. e other researchers kept samples in
cold storage (optimum temperature and relative humidity) and
found that resonance frequency decreases with fruit ripening.
e samples have been provided with the uniform shape, size
and color at the same time.  e researches were done on speci-
ed samples under controlled conditions and generalization of
the conclusions is di cult. In this work, the samples were pre-
pared at several times and had non-monotonous shape, size and
color. Furthermore, the control of many environmental and  eld
factors is di cult and even impossible.
e response to vibrations in the fruits and vegetables de-
pends on their elasticity modulus, mass and shape.  is result
means a diminution of 15.8% and 13.6% in the resonance fre-
quency values respective to their initial values.  is diminution
is most likely caused by a di erent ripening rate of each vari-
ety, since it is assumed that the resonant frequency in fruits is
changed mainly by ripeness. High frequencies were found from
unripe fruit for both variet ies. In general, it means that t he more
the fruit is ripened, the lower is its frequency. Chen (1993) found
the measured frequencies to decrease with storage time and to
be correlated with fruit  rmness and sensory measurements.
As it can be seen in Fig. 9 the sound pressure level (SPL) varied
and increased from 49.21 to 57.74 dB for ‘Zard-Eyvanekey’ vari-
ety and from 49.66 to 58.22 dB for ‘Sousky-Sabz’ variety during
ripening of fruit.  e average of sound pressure level in the fourth
harvest (ripened) for ‘Zard-Eyvanekey’ and ‘Sousky-Sabz’ was
estimated 56.93 and 56.25 dB, respectively. Consequently, the
sound pressure level of ‘Zard-Eyvanekey’ variety was a little
higher than the sound pressure level of ‘Sousky-Sabz’ variety.
e variation in the distance between sound level meter (SLM)
and melon surface a ect the sound pressure level (SPL).  is
method is not very precise because of distance change (2–5 mm)
of sound level meter from the melon surface.  erefore we found
that it is not possible to measure ripeness accurately simply by
determining the sound pressure level. Probably due to the in-
crease of the mass of both varieties during the growing season,
the sound pressure level of the process increased.
We concluded that the melon ripening is characterized by a
progressive increase in the mass and TSS and a decrease in the
resonance frequency and elastic modulus.  e higher mass and
TSS correspond to the sweeter melon and the higher resonance
frequency and elastic modulus correspond to the  rmer melon
prior harvesting.
e sensory score for both varieties increased with the degree
of ripeness to reach a maximum general acceptability at fourth
stage, and therea er decreased with further ripening. Consumers
preferred the general acceptability of melon pieces from ‘Zard-
Eyvanekey’ variety compared to ‘Sousky-Sabz’ variety (Fig. 10).
Due to the similar the taste and  rmness of melon to cu-
cumber at the  rst stage of harvesting (Mid-August, immature
melon) to cucumber, the Garmsar farmers used the melons as a
salad, and this would a ect the assessors scoring.  e assessors
scoring were high in this stage. To solve this problem, we asked
the assessors to compare the samples to ripe melon.  e melons
are not consumed at second stage of harvesting (Late-August,
early ripening) because of rapid increase in the amount of TSS
in respect to the  rst stage ( e TSS of ‘Zard-Eyvanekey’ vari-
ety were 4.93° Brix and 6.53° Brix and in ‘Sousky-Sabz’ variety,
these values were 4.83° Brix and 6.43° Brix) and water shortage.
In the  nal stage of harvesting of both varieties assessors deter-
mined that although TSS increased, the  rmness of tissue and
consequently general acceptability decreased.
One of the main objectives in scienti c research is the re-
lationship between these phenomena. Correlation analysis was
carried out to determine the strength of the relationship between
each acoustic parameter with destructively measured ripeness
indicators for both varieties (Table 3).
Figure 8. Frequency changes during the fruit ripening of
Figure 9. Sound Pressure Level (SPL) changes during the
fruit ripening of melon
Figure 10. General acceptability changes in melon
(average va lu es)
Agric. conspec. sci. Vol.  () No. 
Acoustic Testing for Melon Fruit Ripeness Evaluation during Different Stages of Ripening
A very high correlation between resonance frequency and
sound pressure level parameters and mass, total soluble solids
(TSS) were obtained for both varieties.
e correlations between mass and TSS for both varieties are
excellent, with a determination coe cient of 0.965 and 0.977 for
‘Sousky-Sabz’ and ‘Zard-Eyvanekey’, respectively, which means
that more than 96% of the variation in mass is explained by TSS.
Levels of correlation coe cient of 0.522 for ‘Zard-Eyvanekey’
variety and 0.632 for ‘Sousky-Sabz’ variety were found between
the resonance frequency and general acceptability.  e correla-
tion coe cients were low because the resonance frequency had
increase trend, while the general acceptability had increase trend
until forth stage of ripening and then decreased.
Also, the elastic modulus and resonance frequency showed
negative correlations with TSS, sound pressure level and general
acceptability parameters in bot h varieties.  e good correlation
(R2=0.865) was obtained for ‘Zard-Eyvanekey’ variety and ex-
cellent correlation (R2=0.963) for ‘Sousky-Sabz’ variety between
elastic modulus and resonance frequency.  ese ndings can be
explained by the high sensitivity of the acoustic method (reso-
nance frequency) to elastic modulus of fruit.
Also, a strong correlation between resonance frequency
and sound pressure level (R2=0.991 for ‘Zard-Eyvanekey’ and
R2=0.933 for ‘Sousky-Sabz’) was observed. Statistical analysis
of the data indicated high correlation between acoustic param-
eters and others ripeness indicators.
Our results showed that the value of resonance frequency
is a useful indicator of maturity stage, as it decreases linearly
throughout ripeness for both varieties.
e acoustic impulse response method is then an indirect
way for non-destructive sensing of the melon ripeness. On the
other hand, the data suggests that resonance frequency and elas-
tic modulus can both be used to distinguish among fruits with
diferent maturity and ripeness levels. During the all experiments
no sign of bruising was observed on the melon’s skin, con rm-
ing the nondestructiveness of this technique.
e major changes that occur during harvesting period of
both varieties are reduction in true density and elastic modulus.
e general acceptability of both melons determined by asses-
sors and correlation coe cients between them are low because
the resonance frequency had increase trend, while the general
acceptability had increase trend until forth stage of ripening
and then decreased. A very high correlations between resonance
frequency and sound pressure level parameters and mass and
total soluble solids (TSS) were obtained for both varieties. It is
not possible to measure ripeness accu rately simply by determin-
ing the sound pressure level (SPL). Experiments con rmed that
non-destructive acoustic impulse response can be successfully
used to distinguish di erent stage of ripeness.
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M 1 0.929 0.965 0.986 0.957 0.522
E 1 0.883 0.865 0.795 0.399
TSS 1 0.978 0.961 0.400
f 1 0.991 0.517
SPL 1 0.508
GA 1
M 1 0.969 0.977 0.961 0.890 0.632
E 1 0.931 0.963 0.822 0.646
TSS 1 0.979 0.963 0.642
f 1 0.933 0.675
SPL 1 0.678
GA 1
M (Mass, kg), E (Elastic Modulus, MPa), TSS (Total Soluble Solids, °Brix),
f (Resonance Frequency, Hz), SPL (Sound Pressure Level, dB) and GA
(General Acceptability, without unit)
Table 3. Absolute value of correlation coe cients between
acoustic parameters and other ripeness indicators of ‘Sousky-
Sabz’ and ‘Zard-Eyvanekey’ melons
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... Suciyati et al. (2007) meneliti spektrum bunyi dari semangka merah, pisang, dan pepaya berbasis komputer dan melaporkan penurunan frekuensi dominan seiring dengan peningkatan umur panen. Khoshnam et al. (2015) melakukan evaluasi 2 kultivar buah melon selama 5 tahap pematangan yang berbeda menggunakan impactor (pendulum) dan sound level meter dan melaporkan adanya penurunan frekuensi dan modulus elastis selama pematangan buah-buahan. ...
... Sampel buah kemudian diketuk dari jarak ± 0,5 cm dari permukaan kulit buah menggunakan alat pengetuk. Metode akuisisi data akustik pada penelitian ini merupakan trial-error dari penulis dengan mempertimbangkan penelitian sebelumnya oleh Khoshnam et al. (2015). Set-up akuisisi data sifat akustik dan diagram alir penelitian ditampilkan pada Gambar 1 dan Gambar 2. ...
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Determining the right time to harvest is very important to do for agricultural commodities. This is related to post-harvest handling and extending the shelf life of fruits. Determining the level of melon maturity is still done manually by tapping the surface of the fruit by hand, but this method is still subjective. This research aims to study the maturity level of the 'Premier' melon to determine the appropriate harvest time based on acoustic properties and its relationship to the physic-chemical properties of the melon using a self-made tapping device. Based on the results obtained, the acoustic properties parameters showed a strong enough relationship to the physico-chemical parameters of melons. Based on linear regression analysis, it can be seen that the best acoustic parameters in estimating and determining the right harvest time for melons are the dominant frequency (f), magnitude (M), and zero moment power (Mo). 'Premier' melons can be harvested when the dominant frequency (f) is ≤ 219.92 Hz with a magnitude (M) of ≤ 39.72 dB, and the zero moment power (Mo) value is ≤ 68.99 according to the actual harvest age in the field conducted by farmers at the harvest age of 64 DAP.
... e hormone ethylene in climacteric melon causes this type of melon to be harvested when the fruit is not yet ripe. However, climacteric fruit harvested early causes fruit to be underripe [33], while fruit harvested late causes fruit to be too ripe when consumed [35]. e determination of the right harvest time is needed to maintain the quality of melons. ...
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Melon breeding is directed at improving the quality of the fruit needed to meet consumers' demands. e assessment of hybrid melon candidates on important characteristics (vitamin A, vitamin C, and TSS) at ve maturity stages is needed to get hybrid melon varieties with good fruit quality and determine the right harvest time. is study aimed to evaluate the genetic parameters of vitamin A, vitamin C, and TSS contents of D-612 × PK-669 and PK-361 × PK-165 crossings at ve stages of maturity. e study used a randomized complete block design (RCBD) with eight genotypes as treatment and three replications, so there were 24 experimental units. e eight melon genotypes were G 1 = D-612 × PK-669, G 2 = PK-669 × D-612, G 3 = D-612, G 4 = PK-669, G 5 = PK-361 × PK-165, G 6 = PK-165 × PK-361, G 7 = PK-361, and G 8 = PK-165. e content of vitamin A, vitamin C, and TSS was observed at ve maturity stages, namely, at 55 DAP, 60 DAP, 65 DAP, 70 DAP, and 75 DAP. e right harvest time for the eight genotypes tested was maturity stage 4 (70 DAP) because it had the highest vitamin A, vitamin C, and TSS contents compared to other maturity stages. e inheritance of vitamin A and C content was not a ected by the maternal e ect, while TSS was in uenced by the maternal e ect. e vitamin A, vitamin C, and TSS content characteristics had higher phenotypic diversity coe cients than genetic diversity coe cients, while heritability values in the broad sense for the three melon genotypic characteristics ranged from 0.613 to 0.968. Crosses of PK-165 × PK-361 can be used to assemble hybrid melon varieties that have high vitamin A, vitamin C, and TSS contents because they have positive values for heterosis and heterobeltiosis for the three characteristics.
... Most of these acoustic techniques utilize an accelerometer, microphone, piezoelectric sensors, in testing fruits such as kiwi [10], mandarin [11], peach [12], melon [13], apple [14], and pomelo [15]. On the other hand, an acoustic tester with a mechanical plunger was found in a study to determine the ripeness of Juan canary melon [16]. ...
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Cacao pod's ideal harvesting time is when it is about to be ripe. Immature harvest would result in hard cacao beans not suitable for fermentation, while overripe cacao pods lead to fungal-infected, defective, and poor-quality yields. The demand for high-quality cacao products is expected to rise due to advancing technology in the present. Pre-harvesting needs to provide optimal identification of which amongst the pods are ripened enough and ready for the next stage of the cacao process. This paper recommends a technique to determine the ripeness of cacao. Nine hundred thirty-three cacao samples were used to collect thumping audio data at five different pod's exocarp locations. Each sound file is 1 second long, creating 4665 cacao sound file datasets at 16kHz sample rate and 16-bit audio bit depth. The process of the Mel-Frequency Cepstral Coefficient Spectogram was then applied to extract recognizable features for the training process. The deep learning method integrated was a convolutional neural network (CNN) to classify the cacao sound successfully. The experimental design model's output exhibits an accuracy of 97.50 % for the training data and 97.13 % for the validation data. While the overall accuracy mean of the classification system is 97.46 %, whether the cacao is unripe or ripe.
Codling moth (CM) (Cydia pomonella L.) is the most destructive pest for apples, causing large economic losses when not properly mitigated. Efficient detection methods can limit the spread of this pest in the apple supply chain. Nondestructive methods have several advantages over the current methods in that they can be applied to every apple (or a much larger sample) thereby reducing the possibility of missed detection. This paper examines the feasibility of acoustic impulse response methods for detecting CM larvae-infested apples. Experiments were performed on control and artificially infested apples from three different cultivars. Signals were recorded with a contact sensor, and 21 signal features were proposed and extracted to characterise relevant properties of the response. The 21 features were evaluated with 11 machine leaning algorithms to determine if the features or their subsets contained information that could reliability determine if an apple was/is infested. Classification test results using a 10-fold cross-validation indicated accuracy rates between 80% and 92% for Fuji apples, between 92% and 99% for Gala apples, and 63% and 97% for Granny Smith apples. The impulse response required between 60-80 ms for each apple (not counting setup/transition time). These results from this study suggest that active impulse response classification can potentially improve the detection of post-harvest apple CM infestation detection along the supply chain.
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This research aims to enhance the watermelon’s quality selection process, which was traditionally conducted by knocking the watermelon fruit and sort out by the sound’s character. The proposed method in this research is generating the sound spectrum through the watermelon and then analyzes the response signal’s frequency and the amplitude by Fast Fourier Transform (FFT). Then the obtained data were used to train and verify the neural network processor. The result shows that, the frequencies of 129 and 172 Hz were suit to be used in the comparison. Thirty watermelons, which were randomly selected from the orchard, were used to create a data set, and then were cut to manually check and match to the fruits’ quality. The 129 Hz frequency gave the response ranging from 13.57 and above in 3 groups of watermelons quality, including, not fully ripened, fully ripened, and close to rotten watermelons. When the 172 Hz gave the response between 11.11–12.72 in not fully ripened watermelons and those of 13.00 or more in the group of close to rotten and hollow watermelons. The response was then used as a training condition for the artificial neural network processor of the sorting machine prototype. The verification results provided a reasonable prediction of the ripeness level of watermelon and can be used as a pilot prototype to improve the efficiency of the tools to obtain a modern-watermelon quality selection tool, which could enhance the competitiveness of the local farmers on the product quality control.
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Introduction: Fruit and vegetables are an important component of the human diet and consumers usually expect such products to have premium quality. The texture is a major quality attribute that influences consumer acceptance, shelf life, resistance, and transportability. Also, the quality of fruits and vegetables can be determined by their external and internal characteristics. Recognition of agricultural product characteristics may help to design new machines, industrial processes to reduce the damages (Tavakkoli hashtjin, 2003). The first step in the codification of qualitative standards for the agricultural product is the recognition of different properties and different modifications of these products caused by various factors (Mohsenin 1986). Persimmon (Diospyros) is a member of Ebenaceae family and originated from China and Japan. D. Lotus, D.Virginiana and D.Kaki are three important persimmon cultivars in Iran. According to the FAO statistics, the Iran persimmon harvested area was about 1692 ha in 2017. In this year Iran produced about 24326 tons of persimmon (with an average yield of 14.3 ton/ha) which ranked 11th in the world. Although many researchers conducted some investigations on the mechanical properties of agricultural products, but studies on persimmon mechanical properties have been very limited. Hezbavi et al. (2008) studied the physical and mechanical responses of Japanese cultivar of persimmon (D.Kaki) and reported that there was a significant difference in all mechanical properties between soft and stiff persimmon, except fruit deformation. Altuntas et al (2013) determined the physical, mechanical and chemical properties of medlar during physiological maturity and ripening period. The physical properties such as geometric mean diameter, sphericity, bulk and true densities, porosity, projected area and color characteristics were measured during physiological maturity and ripening period of medlar. Mechanical properties such as rupture force, deformation and rupture energy and chemical properties (total soluble solid content, titratable acidity and pH) of medlar fruit were determined. The results of Altuntas et al. (2010) have shown that the correlation coefficients between the physical parameters of persimmon fruits were significant. The coefficient of static friction was greater on plywood as compared to the chipboard and galvanized metal surfaces. They reported that the required force for punching persimmons along the Y-axis was higher than along the X-axis. Review of literature showed that the effect of harvesting time, cultivar and loading speed of D.Kaki and D.virginiana persimmon cultivars on some mechanical properties and coefficient of restitution of persimmon have not been studied. Therefore, in this research, some mechanical properties of two persimmon cultivars (D.Kaki and D.virginiana) at three harvests time (immature, semi-mature and mature) and coefficient of restitution were studied. Material and methods: In this study, some tests were conducted to determine these mechanical properties of two persimmon varieties D. Virginiana and D. Kaki at the three harvest times with three different loading speeds of 50, 100 and 200 mm/min using fruit texture analyzer and to obtain resilience coefficient used an invented device equipped with sonic sensor, so that it can be used as a criteria for bruising damage. The persimmon fruits (D.Kaki and D.virginiana) at three harvest times were provided from gardens of East Azarbaijan province. Then, the samples were transferred to the biophysical and mechanical lab of university of Tabriz. The moisture content of fruits was determined by the standard method (ASAE 1998). The acoustic test was used to determine the resilience coefficient that is a criterion for determining persimmon bruising damage. For this purpose, persimmons were dropped from three heights 10, 20 and 30 cm on the plate equipped with an acoustic sensor located underneath that plate. The amplitude-time curve was obtained using Praat software for each drop test. According to this curve, rebound time (the time required for the first and second peaks of curve) was determined. Results and discussion: According to the results, the main effects of variety, harvesting time and speed of loading and also interaction of variety*harvesting time were significant at the probability level of 1% and the other interactions were not significant. It means, in general, as expected, the mean values of puncture force for the two varieties, at three harvesting times and in three different loading speeds, had a significant effect at the probability level of 1%. The reason for the significance of interaction of variety*harvesting time is the behavior of puncture force at different times of harvesting persimmons. The results showed that the required mean value of puncture force in D. Virginiana variety was greater than D. Kaki variety and the average force required to punch the persimmon fruit, with Magness Taylor probe for the first harvesting time (immature stage) is nearly doubled compared with the third harvesting (mature stage). It shows that if persimmon has been marketed in the immature stage or in semi-mature stage, mechanical damage can be decreased to one-half value. By increasing the loading speed, the average force required to punch the persimmon increased. The average energy required to punch of persimmon fruit, using Magness Taylor probe for the first harvesting time (immature stage) is nearly doubled in comparison with the second harvesting time (semi-mature stage) and nearly tripled in comparison with the third harvesting time (mature stage). By increasing the loading speeds, the average energy required to punch the persimmon fruit increased and also the same results were obtained for three harvesting stages. It can be concluded that, for example, during sorting operation, whatever Persimmon move at a slower speed, minimum energy can cause mechanical damage. When the product getting ripe the mean value of puncture energy decreased and by increasing loading speeds the mean value of puncture force increased. The difference between mean values of resilience coefficients of fruits released from different heights at the three different harvest times for both two varieties was significant at the probability level of 1%.
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یکی از روش‌های غیرمخرب تعیین کیفیت بافت و سفتی میوه‌هایی مانند سیب، گلابی، هلو و محصولات جالیزی مانند هندوانه، خربزه و طالبی، استفاده از روش تحلیل پاسخ صوتی می‌باشد. در این پژوهش به منظور بررسی کیفیت غیرمخرب میوه سیب بر اساس سفتی، دستگاهی قابل حمل طراحی و ساخته شد که دارای یک آونگ برای اعمال ضربه قابل کنترل با رایانه به نمونه مورد آزمون می باشد. در هنگام وارد کردن ضربه دو حسگر صوتی و ارتعاشی همزمان سیگنال های ضربه را دریافت نموده و پس از انتقال به رایانه، با تبدیل فوریه سریع، بسامد غالب آنها بدست می آید. شاخص سفتی محصول از بسامد غالب و وزن میوه محاسبه می شود. بسامدهای غالب و شاخص‌های سفتی بدست آمده از این دستگاه برای میوه سیب با سفتی پانچ و ضریب کشسانی بدست آمده با روش مخرب به ترتیب بیش از %92 و %93 همبستگی داشته و در سطح یک درصد معنی‌دار می‌باشد. نتایج پژوهش نشان میدهد که سیگنال‌های ارتعاشی برای تخمین ضریب کشسانی (دقت بیش از %96) و سیگنال‌های صوتی برای تخمین سفتی بافت (دقت بیش از %95) نتایج بهتری حاصل می کنند.
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This paper presents a statistical method for the calibration of an acoustic technique for the real-time evaluation of fruit firmness. The technique uses an experimental setup based on two standard piezoelectric transducers and exploits two novel stiffness indexes developed in the first part of this paper. Extensive experimental measurements show good correlation (r = 0.930, R2 = 0.865) between the proposed non-destructive test and the traditional destructive Magness-Taylor test. An evaluation of the statistical significance (t-test) of the obtained regression model parameters has been performed and validates the method. The presented sorting analysis complements the physical detection techniques presented in the first part of the paper, allowing to classify individual kiwifruits with high accuracy and high prediction rate (∼90%). The technology is suitable for industrial real-time and in-line applications aiming to improve warehouse stock management and market stock uniformity.
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This work addresses the problem of distinguishing between ripe and unripe watermelons using mobile devices. Through analysing ripeness-related features extracted by thumping watermelons, collecting acoustic signals by microphones on mobile devices, our method can automatically identify the ripeness of watermelons. This is possible in real time, making use of machine learning techniques to provide good accuracy. We firstly collect a training dataset comprising acoustic signals generated by thumping both ripe and unripe watermelons. Audio signal analysis on this helps identify features related to watermelon ripeness. These features are then used to construct a classification model for future signals. Based on this, we developed a crowdsourcing application for Android which allows users to identify watermelon ripeness in real time while submitting their results to us allowing continuous improvement of the classification model. Experimental results show that our method is currently able to correctly classify ripe and unripe watermelons with an overall accuracy exceeding 89 %.
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An investigation was carried out to establish the basic relationship between mechanical resonance, firmness, chemical composition and ethylene production during the maturity time and the ripening time of peach fruit. The stiffness factor calculated by a non-destructive frequency response technique was compared with biological properties obtained by measurement of chemical composition, firmness and ethylene production in the internal atmosphere of tested fruit. The correlation between the biological multifunction and the mechanical resonance frequency of peach fruit can be expressed by an exponential relationship. Multifactorial index seems to describe the rupture point that for peach fruit coincides with the beginning of climacteric developmental stage, detected by ethylene production.
Sound pitch levels of fourteen apples were evaluated by human auditory sensing and compared with instrumental measurements of acoustic response of the fruits. Results indicated that the sound pitch level had a direct correlation with the first and the second resonant frequencies of the fruit. A linear model based on amplitudes of the power spectrum at selected frequencies could determine the sound levels of the fruit with a coefficient of multiple determination (R 2) of 0.96. The acoustic impulse generating method, test location on the fruit, and fruit holding method did not affect the resonant frequencies of the fruit, but affected the amplitudes of vibrations at the second and higher resonant frequencies.
Abstract Firmness can be used to indicate ripeness of many agro-products, usually determined by acoustic impulse method nondestructively. An acoustic device was developed after investigating the influence of hitting ball and fruit tray on spectrum. Three firmness indices such as f2m, MI1 (index of the first order moment) and MI2 (index of the second order moment) were proposed to correlate with firmness of watermelon. Significant correlation was found out between firmness and these indices using linear regressive model and nonlinear model of artificial neutral network (ANN). It was concluded the linear model was more suitable than nonlinear model using ANN because of little difference of correlation coefficients. Although more computations needed, index MI1 was considered more precisely to use as firmness indices than f2m in the case of splitting peaks with almost the same amplitude around the first resonant frequency.
A portable system using acoustic impulse impedance techniques was developed to nondestructively determine watermelon maturity. The system was used in the field to measure the maturity of three watermelon varieties 'Allsweet', 'Sangria' and 'King of Hearts'. Frequency domain parameters from the impulse response were compared with sugar content, flesh color, Effe-gi firmness and mass for individual melons. The effect of testing the melons in their natural growing position and resting on a hard base was determined. The system was also examined as a method to detect hollow heart in watermelons. Correlations between acoustic and destructive maturity parameters indicated relationships were too weak to be of value for maturity sorting. Relationships between acoustic parameters and level of hollow heart were weak for 'King of Hearts' but much stronger for the 'Black Diamond' cultivar.
A method to evaluate the ripeness of musk melons using nondestructive acoustic impulses is described. The relationship between transmission velocity and firmness of the fruit has been established. The transmission velocity of; edible musk melons ranged from 37 to 50 m/s.
Apple modulus of elasticity was readily predicted (r2 > 0.76) from acoustic resonant frequency vibrations caused by an impulse striking the apple. Magness-Taylor firmness was poorly predicted (r2 < 0.27) using the same technique. An elastic sphere model was developed that utilized an observed resonant frequency to predict the modulus of elasticity of the apple. These predictions were compared with measured values of Magness-Taylor firmness and modulus of elasticity.
This research investigated the maturity assessment of pomelo using acoustic properties obtained from an impact of fruit, optical properties of the peel and variables related to oil glands from peel images. Pomelo samples were harvested at 5.5, 6.0, 6.5 and 7.0 months after anthesis. All nondestructive variables were used to build qualitative models with partial least squares discriminant analysis. The classification model based on the nondestructive variables showed that fruits could be separated into immature, early-mature and late-mature groups with an accuracy of 96.7%. The important variables contributing to the classification were the impact response based on the second-order resonant frequency and the difference of green colour between the oil gland and the peel.
Ripening of climacteric fruit is accompanied by an increase in respiration and autocatalytic ethylene synthesis. In harvested melons, there is variation in the magnitude and duration of the respiratory climacteric depending on the cultivar. It has recently been reported that, while the ripening-associated increase in ethylene production is present, the respiratory climacteric is absent in ripening melon fruit attached to the plant, leading to the suggestion that climacteric respiration is an artifact of harvest. To address the universality of this phenomenon, ripening behaviour in the melon cultivar Charentais (Cucumis melo cv. Reticulatus F1 Alpha), was investigated and the results show that the respiratory climacteric occurs in fruit ripened both on and off the plant.