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Citation: Ali, K.A.M.; Li, S.T.; Li, C.;
Darwish, E.A.; Wang, H.;
Abdelwahab, T.A.M.; Fodah, A.E.M.;
Elsaadawi, Y.F. Optimization and
Prediction of Operational Parameters
for Enhanced Efficiency of a Chickpea
Peeling Machine. Agriculture 2024,14,
780. https://doi.org/10.3390/
agriculture14050780
Received: 13 April 2024
Revised: 13 May 2024
Accepted: 16 May 2024
Published: 18 May 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
agriculture
Article
Optimization and Prediction of Operational Parameters for
Enhanced Efficiency of a Chickpea Peeling Machine
Khaled Abdeen Mousa Ali 1,2 , Sheng Tao Li 1, Changyou Li 1, Elwan Ali Darwish 2, Han Wang 1,3 ,* ,
Taha Abdelfattah Mohammed Abdelwahab 2
, Ahmed Elsayed Mahmoud Fodah
2
and Youssef Fayez Elsaadawi
4
1College of Engineering, South China Agricultural University, Guangzhou 510642, China;
khaledabdeen@azhar.edu.eg (K.A.M.A.); lishengtao@stu.scau.edu.cn (S.T.L.); lichyx@scau.edu.cn (C.L.)
2College of Agricultural Engineering, Al-Azhar University, Cairo 11651, Egypt;
elwan.darwish2015@azhar.edu.eg (E.A.D.); tahaabdelfattah@azhar.edu.eg (T.A.M.A.);
ahmedfodah@azhar.edu.eg (A.E.M.F.)
3School of Intelligent Engineering, Shaoguan University, Shaoguan 512099, China
4College of Agricultural Engineering, Al-Azhar University, Assiut 28784, Egypt; dr.youssef@azhar.edu.eg
*Correspondence: wanghan603@scau.edu.cn
Abstract: Chickpeas hold significant nutritional and cultural importance, being a rich source of
protein, fiber, and essential vitamins and minerals. They are a staple ingredient in various cuisines
worldwide. Peeling chickpeas is considered a crucial pre-consumption operation due to the unde-
sirability of peels for some uses. This study aimed to design, test, and evaluate a small chickpea
seed peeling machine. The peeling prototype was designed in accordance with the chickpeas’ mea-
sured properties; the seeds’ moisture content was determined to be 6.96% (d.b.). The prototype was
examined under four different levels of drum revolving speeds (100, 200, 300, and 400 rpm), and
three different numbers of brush peeling rows. The prototype was tested with rotors of four, eight,
and twelve rows of brushes. The evaluation of the chickpea peeling machine encompassed several
parameters, including the machine’s throughput (kg/h), energy consumption (kW), broken seeds
percentage (%), unpeeled seeds percentage (%), and peeling efficiency (%). The obtained results
revealed that the peeling machine throughput (kg/h) exhibited an upward trend with increases in
the rotation speed of the peeling drum. Meanwhile, the throughput decreased as the number of
peeling brushes installed on the roller increased. The highest recorded productivity of 71.29 kg/h was
achieved under the operational condition of
400 rpm
and four peeling brush rows. At the same time,
the peeling efficiency increased with the increase in both of peeling drum rotational speed and num-
ber of peeling brush rows. The highest peeling efficiency (97.2%) was recorded at the rotational speed
of 400 rpm and twelve peeling brush rows. On the other hand, the lowest peeling efficiency (92.85%)
was recorded at the lowest drum rotational speed (100 rpm) and number of peeling brush rows
(4 rows). In the optimal operational condition, the machines achieved a throughput of
71.29 kg/h
,
resulting in a peeling cost of 0.001 USD per kilogram. This small-scale chickpea peeling machine is a
suitable selection for small and medium producers.
Keywords: chickpeas seeds; peeling efficiency; prediction model
1. Introduction
Chickpeas (Cicer arietinum L.) rank as the third most important cultivated legume
crop in the world after soybeans and dry beans [
1
,
2
]. Chickpeas exhibit an approximate
composition of 22% protein, 63% carbohydrates, 8% crude fiber, 4.5% fat, and 2.7% ash
on average [
3
]. Because of this rich content of nutrients, chickpeas are an essential ingre-
dient in many traditional dishes of native populations around the world [
4
]. The regular
consumption of chickpeas contributes to the promotion of human well-being through the
regulation of fatty acids [
5
]. Chickpeas represent an economical and significant protein
source, particularly for individuals with limited access to animal-based protein or those
Agriculture 2024,14, 780. https://doi.org/10.3390/agriculture14050780 https://www.mdpi.com/journal/agriculture
Agriculture 2024,14, 780 2 of 15
who follow a predominantly vegetarian dietary pattern. Moreover, chickpeas exhibit favor-
able attributes in their mineral content (including calcium, phosphorus, magnesium, zinc,
and iron), unsaturated fatty acids, dietary fiber, and
β
-carotene [
6
,
7
]. The leaves, stems, and
fruit peelings of chickpeas demonstrate an effective capacity for the adsorption of lead ions
from aqueous solutions, allowing for the successful accumulation of these ions onto their
surfaces [
8
]. According to the authors of Reference [
9
], activated carbon was synthesized
from chickpea peels using a series of carbonization and chemical processes.
Post-harvest operations, specifically the seed peeling process, have been recognized
as crucial procedures that enhance the quality and value of agricultural material [
10
,
11
].
The authors concluded that employing a mechanical approach to the peeling process can
reduce the time required by approximately 93% compared to manual peeling.
The authors of ref [
12
] concluded that peeling is a preliminary operation involving the
removal of the outer skin using different techniques such as mechanical, steam, chemical,
and manual peeling. Advanced methods include infrared and ohmic heating-assisted
peeling. Among these techniques, manual abrasive peeling is known to yield high-quality
products with minimal flesh loss. However, its suitability for large-scale production is
hindered by its labor-intensive and time-consuming nature. Among the various peeling
techniques, mechanical methods are deemed advantageous due to their ability to preserve
the freshness and integrity of the edible portions of the produce [13].
Emadi et al. [
14
] The pliability of brushes facilitates the peeling process. It makes use
of the maneuverability of the brushes’ protrusions across all regions of the treated prod-
uct. Each protrusion on the brush serves as a diminutive cutting apparatus, proficiently
excising and abrasively eliminating the peel pieces. In an investigation conducted by the
authors of [
15
], the impact of peeler speed (ranging from 350 to 750 rpm) and peeling
time (varying from five to twelve minutes) on machine performance was examined. The
evaluation was based on parameters such as peeling efficiency, percentage weight of peels,
and flesh loss. Their findings revealed a positive correlation between peeler rotational
speed and peeling efficiency across all tuber samples. In a study conducted by the au-
thors of Reference [
16
], the experimental results revealed a significant enhancement in
the performance of a reciprocating peanut sheller after implementing some modifications
(incorporating a feeding mechanism into the sheller, expanding the friction area of the
shelling box, and implementing rubber for enhanced shelling). Notably, following the
modifications, the reciprocating peanut sheller exhibited improved shelling efficiency and
throughput, achieving values of 98.85% and 155.98 kg/h, respectively. These results were
obtained under specific operating conditions, including a feeding rate of 160 kg/h, box
speed of 1.4 m/s, moisture content of approximately 17.12% (w.b.), and air velocity of
8.37 m/s
. In contrast, before the modifications, the shelling efficiency and productivity
were measured at 95.32% and 89.20 kg/h, respectively, under a feeding rate of 100 kg/h
and other comparable analyzed operating conditions. In the study conducted in ref [
17
],
the authors manufactured and tested a peanut sheller under different drum rotary speeds
of 150, 200, 250, and 300 rpm, feeding rates of 170, 210, and 250 kg/h, and air speeds of 4.9,
6.8, and 8.8 m/s. They summarized that shelling efficiency increased with a decrease in
both drum rotational speed and feeding rate, and the sheller’s throughput increased with
the increase in both drum rotational speed and feeding rate.
In the food industry, critical considerations encompass peeling losses, undesired
deformation, energy consumption, material wastage, total process cost, and the level of
food safety and quality. The prevalent challenges encountered in widely adopted designs
encompass challenges in equipment calibration, heightened product loss, and reduced
machine efficiency. Additionally, a majority of peeling machine designs are tailored to
specific crops, limiting their versatility [
13
,
18
,
19
]. Mousa and Darwish [
20
] evaluated a
newly developed shelling machine designed for peanut pod shelling. The study revealed
that the machine exhibited a remarkable level of efficiency in the shelling process. Through
a series of experiments conducted within a speed range of 100 to 400 rpm and a clearance
range of 9 to 12 mm, the optimal operating conditions for shelling peanut pods were
Agriculture 2024,14, 780 3 of 15
determined to be 200 rpm for speed and 10 mm for clearance. The primary drawback of
mechanical peeling resides in the propensity for material loss and deformations. Mitigating
material losses and enhancing process quality directly impact the overall efficiency of the
food processing industry [
21
]. To address this, further research is warranted to delve into
the technological aspects of these operations.
An economic analysis provides empirical evidence affirming the practical feasibility
and economic advantages of the novel design in comparison to traditional peeling methods.
In their study, the authors of ref [
22
] outlined the components of machinery costs, which
encompass ownership costs and operating costs.
The main objective of this study was to, develop, test, and evaluate the influence
of various operational parameters on the performance of a chickpea peeling prototype
and to identify the optimal operational conditions for this prototype according to the
following evaluation parameters: highest peeling efficiency, maximum machine throughput,
minimum consumed specific energy, lowest percentages of broken and unpeeled seeds,
and enhancement of the quality of the peeled chickpea seeds.
2. Materials and Methods
2.1. The Description of the Adopted Chickpea
The chickpea seeds utilized in the investment were obtained from a local market.
Then, their moisture content was determined according to the method described by the
authors of ref [
23
], yielding a measurement of 6.96% on a dry basis (d.b.). The development,
examination, and evaluation of the chickpea seed peeling prototype took place in the
workshop of the College of Agricultural Engineering, Al-Azhar University, Cairo, Egypt.
We took into consideration the physical, mechanical, and aerodynamic properties of seeds
listed in Table 1. Throughout the manufacturing process, particular attention was given to
ensuring the prototype’s operational safety, compact size, and lightweight characteristics,
aiming to enhance its mobility and maneuverability.
Table 1. Some physical, mechanical, and aerodynamic properties of chickpea seeds.
Property (Unit) Value S.D.
Length (mm) 7.65 0.40
Width (mm) 6.45 0.27
Thickness (mm) 5.71 0.20
Sphericity (%) 85.72 2.41
Geometrical diameter (mm) 6.55 0.24
The angle of repose (degree) 26.57 0.91
Friction coefficient 0.41 0.02
Compression force (N) 45.7 3.95
Critical airspeed (m/s) 7.65 0.52
1000 Seed mass (g) 173.85 2.43
2.2. Peeling Prototype Description
The main components of the chickpea seeds peeling machine included: a frame, feed
hopper, peeling chamber, outlet for seeds, outlet for shells, and a power source, as shown in
Figure 1. The design and endurance testing of the chickpea peeling machine was conducted
utilizing SolidWorks 2023 software, with careful consideration given to the distinct physical
and mechanical properties of chickpea seeds.
Agriculture 2024,14, 780 4 of 15
Agriculture 2024, 14, 780 4 of 15
2.2.1. Feeding Hopper
The feeding hopper was constructed using a 2 mm thick fiberglass sheet, forming a
conical shape. The top section of the hopper featured rectangular dimensions of 150 × 180
mm, while the boom section measured 80 × 60 mm, with a height of 160 mm.
Figure 1. A 3D module for chickpea seeds peeling prototype and photos of its parts.
2.2.2. Peeling Chamber
The peeling chamber, which was fabricated from wood in our design prototype,
plays a crucial role in effectively removing the outer shells from chickpea seeds. Inside is
a vertical cylinder made of PVC, with dimensions of 155 mm for the inner diameter and a
height of 300 mm.
To enhance the peeling process, four rubber fins are affixed to the inner surface of the
peeling chamber, parallel to the longitudinal axis. These fins measure 176 mm in length,
30 mm in width, and 10 mm in thickness. The presence of rubber fins within the peeling
chamber reduces the occurrence of seed vertexing, which increases the peeling efficiency.
Inside the cylinder, a vertical rotating drum made from Artalon (the peeling drum)
is directly aached to the power source of the peeling chamber. The drum features twelve
grooves (rows) along the longitudinal axis, allowing easy control of the number of peeling
brush rows in use. Positioned below the outlet opening for the chickpea seeds is a blower,
which is adjustable to control the airflow speed. Its purpose is to clean the seeds by re-
moving any remaining shell fragments and dust. An air speed of 4 m/s was used in ac-
cordance with the measured critical airspeed of chickpea seeds (7.65 m/s). The elevation
and plan of the peeling chamber can be observed in Figure 2. The peeling brushes are
composed of twelve metal bases, with plastic bristles affixed to each base. The plastic bris-
tles are 35 mm long.
2.2.3. Power Source
An electric motor (0.25 kW) was used as a power source for this peeling prototype. The
motor is connected to an inverter device to increase or reduce the rotary speed of the electric
motor.
Figure 1. A 3D module for chickpea seeds peeling prototype and photos of its parts.
2.2.1. Feeding Hopper
The feeding hopper was constructed using a 2 mm thick fiberglass sheet, forming a con-
ical shape. The top section of the hopper featured rectangular dimensions of
150 ×180 mm
,
while the bottom section measured 80 ×60 mm, with a height of 160 mm.
2.2.2. Peeling Chamber
The peeling chamber, which was fabricated from wood in our design prototype, plays
a crucial role in effectively removing the outer shells from chickpea seeds. Inside is a
vertical cylinder made of PVC, with dimensions of 155 mm for the inner diameter and a
height of 300 mm.
To enhance the peeling process, four rubber fins are affixed to the inner surface of the
peeling chamber, parallel to the longitudinal axis. These fins measure 176 mm in length,
30 mm in width, and 10 mm in thickness. The presence of rubber fins within the peeling
chamber reduces the occurrence of seed vertexing, which increases the peeling efficiency.
Inside the cylinder, a vertical rotating drum made from Artalon (the peeling drum) is
directly attached to the power source of the peeling chamber. The drum features twelve
grooves (rows) along the longitudinal axis, allowing easy control of the number of peeling
brush rows in use. Positioned below the outlet opening for the chickpea seeds is a blower,
which is adjustable to control the airflow speed. Its purpose is to clean the seeds by
removing any remaining shell fragments and dust. An air speed of 4 m/s was used in
accordance with the measured critical airspeed of chickpea seeds (7.65 m/s). The elevation
and plan of the peeling chamber can be observed in Figure 2. The peeling brushes are
composed of twelve metal bases, with plastic bristles affixed to each base. The plastic
bristles are 35 mm long.
Agriculture 2024,14, 780 5 of 15
Agriculture 2024, 14, 780 5 of 15
Figure 2. Elevation, plan, and isometric of the peeling chamber. Dims, mm.
2.3. Theoretical Basis
In the scenario in which the chickpea seed descends freely from the top to the boom
of the vertical peeling chamber, the duration of its residence inside the chamber is influ-
enced by the length of the peeling chamber. Consequently, the following equation can
determine the seed’s residence time:
𝑡=2𝑙
𝑔 (1)
where t is the theoretical residence time inside the peeling chamber (second), l is the peel-
ing chamber length (m), and g is the gravity (m/s
2
).
From Equation (1), the residence time of chickpea seeds inside the peeling chamber
can be calculated. In our prototype, the residence time was approximately 0.2 s. During
this short period, the seed will be hit by the peeling brushes multiple times, and the fre-
quency of these hits depends on both the rotational speed of the peeling drum and the
number of brushing rows aached to the peeling drum as presented in Figure 3.
Figure 3. Influence of peeling chamber length on chickpea seed residence time and brushing fre-
quency.
When the chickpeas were poured into the peeling machine, their shucks would be
scratched off by a roller stuck with brushes. The peeling efficiency determined the peeling
machine’s energy consumption, which was dictated by the drum rotation speed necessary
to match the peeling ability of each brush. The chickpeas were decorticated in a peeling
machine, invisibly and randomly. Therefore, a statistical model was necessary to provide
evidence of peeling efficiency.
The peeling process of chickpeas is random and difficult to observe. By counting the
number of peeling times and the overall peeling rate of the chickpeas in the peeling pro-
cess, the model predicted the single scratching peeling ability of the brush. The experi-
mental results show that the model can be used to evaluate the peeling ability of the
Isometric
Figure 2. Elevation, plan, and isometric of the peeling chamber. Dims, mm.
2.2.3. Power Source
An electric motor (0.25 kW) was used as a power source for this peeling prototype.
The motor is connected to an inverter device to increase or reduce the rotary speed of the
electric motor.
2.3. Theoretical Basis
In the scenario in which the chickpea seed descends freely from the top to the bottom of
the vertical peeling chamber, the duration of its residence inside the chamber is influenced
by the length of the peeling chamber. Consequently, the following equation can determine
the seed’s residence time:
t=s2l
g(1)
where tis the theoretical residence time inside the peeling chamber (second), lis the peeling
chamber length (m), and gis the gravity (m/s2).
From Equation (1), the residence time of chickpea seeds inside the peeling chamber
can be calculated. In our prototype, the residence time was approximately 0.2 s. During this
short period, the seed will be hit by the peeling brushes multiple times, and the frequency
of these hits depends on both the rotational speed of the peeling drum and the number of
brushing rows attached to the peeling drum as presented in Figure 3.
Agriculture 2024, 14, 780 5 of 15
Figure 2. Elevation, plan, and isometric of the peeling chamber. Dims, mm.
2.3. Theoretical Basis
In the scenario in which the chickpea seed descends freely from the top to the boom
of the vertical peeling chamber, the duration of its residence inside the chamber is influ-
enced by the length of the peeling chamber. Consequently, the following equation can
determine the seed’s residence time:
𝑡=2𝑙
𝑔 (1)
where t is the theoretical residence time inside the peeling chamber (second), l is the peel-
ing chamber length (m), and g is the gravity (m/s
2
).
From Equation (1), the residence time of chickpea seeds inside the peeling chamber
can be calculated. In our prototype, the residence time was approximately 0.2 s. During
this short period, the seed will be hit by the peeling brushes multiple times, and the fre-
quency of these hits depends on both the rotational speed of the peeling drum and the
number of brushing rows aached to the peeling drum as presented in Figure 3.
Figure 3. Influence of peeling chamber length on chickpea seed residence time and brushing fre-
quency.
When the chickpeas were poured into the peeling machine, their shucks would be
scratched off by a roller stuck with brushes. The peeling efficiency determined the peeling
machine’s energy consumption, which was dictated by the drum rotation speed necessary
to match the peeling ability of each brush. The chickpeas were decorticated in a peeling
machine, invisibly and randomly. Therefore, a statistical model was necessary to provide
evidence of peeling efficiency.
The peeling process of chickpeas is random and difficult to observe. By counting the
number of peeling times and the overall peeling rate of the chickpeas in the peeling pro-
cess, the model predicted the single scratching peeling ability of the brush. The experi-
mental results show that the model can be used to evaluate the peeling ability of the
Isometric
Figure 3. Influence of peeling chamber length on chickpea seed residence time and brushing frequency.
When the chickpeas were poured into the peeling machine, their shucks would be
scratched off by a roller stuck with brushes. The peeling efficiency determined the peeling
machine’s energy consumption, which was dictated by the drum rotation speed necessary
to match the peeling ability of each brush. The chickpeas were decorticated in a peeling
machine, invisibly and randomly. Therefore, a statistical model was necessary to provide
evidence of peeling efficiency.
The peeling process of chickpeas is random and difficult to observe. By counting the
number of peeling times and the overall peeling rate of the chickpeas in the peeling process,
Agriculture 2024,14, 780 6 of 15
the model predicted the single scratching peeling ability of the brush. The experimental
results show that the model can be used to evaluate the peeling ability of the chickpea
peeler, reduce the energy consumption of the peeler, and improve the peeler ’s working
energy efficiency.
We divided a chickpea’s shuck into 10 pieces and assumed that x(1
≤
x
≤
9) pieces
would be scratched off by each brushing. The probability that all of the shuck would be
scratched off was:
P∑10
i=1xi=1−C1
10 ×P(A1)n+C2
10 ×P(A2)n− · · · · · · +C8
10 ×P(A8)n−C9
10 ×P(A9)n(2)
where
P(Ak)n
was the possibility that kpieces would not be scratched off after n brushings.
Then
P(Ak)=Cx
10−k/Cx
10 (3)
The results of the prediction model are presented in Figure 4.
Agriculture 2024, 14, 780 6 of 15
chickpea peeler, reduce the energy consumption of the peeler, and improve the peeler’s
working energy efficiency.
We divided a chickpea’s shuck into 10 pieces and assumed that x (1 ≤ x ≤ 9) pieces
would be scratched off by each brushing. The probability that all of the shuck would be
scratched off was:
𝑃 𝑥
=1−𝐶
×𝑃(
𝐴
)+𝐶
×𝑃(
𝐴
)−⋯⋯+𝐶
×𝑃(
𝐴
)−𝐶
×𝑃(
𝐴
) (2)
where 𝑃(𝐴) was the possibility that k pieces would not be scratched off after n brush-
ings.
Then
𝑃(
𝐴
)=𝐶
𝐶
(3)
The results of the prediction model are presented in Figure 4.
Figure 4. The prediction results of the statistical and expectation models.
2.4. Experimental Design
The peeling prototype was tested at four different rotational speeds of the drum (100,
200, 300, and 400 rpm) (0.78, 1.57, 2.35, and 3.14 m/s). The rotational speed was determined
using a non-contact, digital photo tachometer with a laser photo mechanism; the meas-
urement range of the device spans from 2.5 to 99,999 rpm. Its precision is rated at 0.1 rpm
within the speed range of 2.5 to 999.9 rpm and increases to 1 rpm for values exceeding
1000 rpm. There are three different peeling rotors. Each rotor has a different number of
peeling (brush) rows, specifically 4, 8, and 12 rows. The study parameters’ influence on
the peeling machine’s performance was assessed using SPSS 20 software. The analysis in-
volved employing a two-way analysis of variance (ANOVA) method, followed by the least
significant difference (LSD) test (p < 0.05). The experimental setup and data analysis were
carried out using a randomized complete block design [24].
2.5. Measurement
2.5.1. Machine Throughput
The machine’s throughput was determined by evaluating the ratio between the quan-
tity of peeled chickpea seeds and the duration of the peeling process, as expressed by the
following mathematical equation:
𝑃=𝑀
𝑡 (4)
Figure 4. The prediction results of the statistical and expectation models.
2.4. Experimental Design
The peeling prototype was tested at four different rotational speeds of the drum
(100, 200, 300, and 400 rpm) (0.78, 1.57, 2.35, and 3.14 m/s). The rotational speed was
determined using a non-contact, digital photo tachometer with a laser photo mechanism;
the measurement range of the device spans from 2.5 to 99,999 rpm. Its precision is rated
at 0.1 rpm within the speed range of 2.5 to 999.9 rpm and increases to 1 rpm for values
exceeding 1000 rpm. There are three different peeling rotors. Each rotor has a different
number of peeling (brush) rows, specifically 4, 8, and 12 rows. The study parameters’
influence on the peeling machine’s performance was assessed using SPSS 20 software. The
analysis involved employing a two-way analysis of variance (ANOVA) method, followed
by the least significant difference (LSD) test (p< 0.05). The experimental setup and data
analysis were carried out using a randomized complete block design [24].
2.5. Measurement
2.5.1. Machine Throughput
The machine’s throughput was determined by evaluating the ratio between the quan-
tity of peeled chickpea seeds and the duration of the peeling process, as expressed by the
following mathematical equation:
Pm=Mt
t(4)
where P
m
represents the prototype throughput in (kg/h), M
t
denotes the total mass of seeds
in kilograms (kg), which was measured using a digital electric balance with an accuracy
Agriculture 2024,14, 780 7 of 15
of 0.01 g (g), and tsignifies the duration of the peeling process, measured in hours (h). A
stopwatch was employed to accurately measure the duration of the process.
2.5.2. Power Requirements
The power requirement (W) for the peeling process was determined using the follow-
ing equation [25]:
Power consumption =I×V×cos ×ηm(5)
where Iis the consumed current with load (Amperes), Vis the voltage difference (Volts),
cos ø is the power factor assumed as a 0.80 phase angle between current and voltage, and
ηmis the mechanical efficiency of the motor, assumed as 85%.
2.5.3. The Specific Energy
The specific energy (kWh/ton) was considered by dividing the consumed power (kW)
by the machine’s throughput (t/h).
2.5.4. Broken Seeds Percentage
The broken seeds percentage was calculated as follows:
BS(%) = MBS
Mt(6)
where B
s
refers to the broken seed percentage (%) and M
BS
is the mass of broken seeds (kg).
2.5.5. Unpeeled Seeds Percentage
The unpeeled seeds percentage was computed according to the following formula [
26
]:
Pu=Mu
Mt
×100 (7)
where P
u
is the percentage of seeds left unpeeled (%) and M
u
is the mass of the unpeeled
seeds (kg).
2.5.6. Peeling Efficiency
Peeling efficiency was computed according to the following formula [26]:
ηp(%)=Mt−Mu
Mt
×100 (8)
2.6. Operating Cost Calculation ($/h)
The comprehensive calculation of the total operating cost incorporated both fixed costs
and variable costs. The determined total cost was outlined as the following equation [27]:
Total cost ($/h) = Fixed cost ($/h) + Variable cost ($/h)
A.
Fixed costs:
1. Depreciation cost:
Depreciation of the machine was calculated according to the following equation:
D=(P−S)
L(9)
where Dis the machine depreciation ($/year), Pis the purchase price (manufacturing
price) $, Sis the salvage or selling price $ (0%), and Lis the time between the buying and
selling year.
Agriculture 2024,14, 780 8 of 15
2. Interest rate cost:
The interest rate was incorporated as a percentage of the machine’s purchase price in
Egypt. It was set to 5% per year.
3. Taxes, insurance, and shelter:
The cost of taxes, insurance, and shelter was incorporated as 2% of the machine’s
purchase price per year [22].
Fixed costs $/h=Depreciation cost+Interest r ate cost+Taxes,insurance,and shelter
hour s o f u se pe r year (10)
B. Variable costs:
1. Repair and maintenance costs were calculated using the following formula [28]:
Repair and maintenance costs $/h =100% Depreciation costs
hour s o f u se per ye ar (11)
2. The consumed power cost was calculated according to the following equation:
power cost $
h=consumed power (kW.h)×price o f power unit (kW)$ (12)
3. Labor costs were calculated as:
Labor costs =Salary o f one worker ×Number o f wo rkers
Variable costs were determined as:
Variable costs =repair and maintenance costs +power cost +Labor costs
3. Results and Discussions
3.1. Statistical Analyses
Table 2presents the results of the analysis of variance conducted to assess the statistical
significance of the study parameters (drum rotational speed, brush peeling rows, and their
interaction) impacting the performance metrics of the chickpea seed peeling machine.
The performance metrics evaluated include throughput, power requirements, broken
seeds, unpeeled seeds, and peeling efficiency. The statistical analysis indicated significant
impacts of the study variables and their interaction on the machine’s throughput and
the required power, both at a probability level of 1%. Among the study parameters, the
drum rotational speed exhibited a more substantial influence compared to the number
of rows and the interaction between the variables. The specific energy demonstrated a
significant sensitivity to the number of brush rows and the interaction between the study
parameters, with a probability level of 1%, while the drum rotational speed had a significant
impact at a probability level of 5%. The broken seed and unpeeled seed percentages were
significantly influenced by the study parameters at a probability level of 1%, although
their interaction was not found to be significant. Peeling efficiency, on the other hand,
exhibited significant effects at both probability levels of 1% and 5% due to the number
of rows and drum rotational speed, while the interaction between these factors was not
statistically significant.
Agriculture 2024,14, 780 9 of 15
Table 2. Analysis of variance table for main treatments and interactions.
Source of Variation df
F Value
Throughput
Power Specific
Energy Broken Seed Unpeeled
Seed
Peeling
Efficiency
Drum speed 3 549.647 ** 1054.786 ** 3.69 * 104.475 ** 24.068 ** 4.031 *
Rows number 2 412.129 ** 536.363 ** 558.95 ** 94.309 ** 46.227 ** 8.550 **
Drum speed ×rows number 6 9.805 ** 9.835 ** 4.93 ** 0.468 ns 1.574 ns 0.368 ns
Error 24
** Significant at 1%. * Significant at 5%. ns non-significant.
3.2. Machine’s Throughput
Figure 5illustrates the relationship between the machine’s throughput in (kg/h) and
the rotational speed of the drum for different configurations of brush peeling rows on
the drum. The obtained data showed that the increase in drum rotational speed from
100 to
400 rpm corresponded with an increase in machine throughput, in line with [
24
,
29
].
Meanwhile, an increase in the number of brush peeling rows on the drum was found
to be associated with a decrease in machine throughput. The highest recorded machine
throughput value was 71.29 kg/h, achieved at a drum rotational speed of 400 rpm and
using 4 peeling brush rows. In contrast, the lowest recorded machine throughput value was
29.39 kg/h, observed at a drum rotational speed of 100 rpm using 12 peeling brush rows.
The observed increase in the machine’s throughput at higher drum rotational speeds can
be attributed to the accelerated movement of seeds, resulting in a quicker expulsion from
the prototype. Conversely, the increase in brush peeling rows impedes the rapid descent of
seeds from the exit hole, thereby affecting the machine’s throughput.
Agriculture 2024, 14, 780 9 of 15
Table 2. Analysis of variance table for main treatments and interactions.
Source of Variation df
F Value
Throughput Power Specific Energy Broken Seed Unpeeled
Seed
Peeling
Efficiency
Drum speed 3 549.647 ** 1054.786 ** 3.69 * 104.475 ** 24.068 ** 4.031 *
Rows number 2 412.129 ** 536.363 ** 558.95 ** 94.309 ** 46.227 ** 8.550 **
Drum speed × rows
number 6 9.805 ** 9.835 ** 4.93 ** 0.468
ns
1.574
ns
0.368
ns
Error 24
** Significant at 1%. *
Significant at 5%.
ns
non-significant.
3.2. Machine’s Throughput
Figure 5 illustrates the relationship between the machine’s throughput in (kg/h) and
the rotational speed of the drum for different configurations of brush peeling rows on the
drum. The obtained data showed that the increase in drum rotational speed from 100 to
400 rpm corresponded with an increase in machine throughput, in line with [24,29]. Mean-
while, an increase in the number of brush peeling rows on the drum was found to be
associated with a decrease in machine throughput. The highest recorded machine
throughput value was 71.29 kg/h, achieved at a drum rotational speed of 400 rpm and
using 4 peeling brush rows. In contrast, the lowest recorded machine throughput value
was 29.39 kg/h, observed at a drum rotational speed of 100 rpm using 12 peeling brush
rows. The observed increase in the machine’s throughput at higher drum rotational
speeds can be aributed to the accelerated movement of seeds, resulting in a quicker ex-
pulsion from the prototype. Conversely, the increase in brush peeling rows impedes the
rapid descent of seeds from the exit hole, thereby affecting the machine’s throughput.
Figure 5. Machine’s throughput “kg/h” at different brush row numbers and different drum rota-
tional speed “rpm”.
3.3. Power Requirements and Consumed Specific Energy
Figure 6 illustrates the correlation between power requirements (shown as vertical
bars), consumed specific energy (shown as lines), and drum rotational speed for various
configurations of brush peeling rows. The results indicate a substantial increase in power
requirements at higher drum speeds and when using an increasing number of brush peel-
ing rows. This result agrees with [30]. The lowest recorded power requirement was 79.29
W, observed under the operational conditions of a drum rotational speed of 100 rpm and
four brush peeling rows. On the other hand, the highest power requirement of 187 W was
recorded at a drum speed of 400 rpm and twelve brush peeling rows. The observed in-
crease in power requirements with increasing drum rotational speed can be aributed to
the logical relationship between rotational speed and power consumption. The increase
Figure 5. Machine’s throughput “kg/h” at different brush row numbers and different drum rotational
speed “rpm”.
3.3. Power Requirements and Consumed Specific Energy
Figure 6illustrates the correlation between power requirements (shown as vertical
bars), consumed specific energy (shown as lines), and drum rotational speed for various
configurations of brush peeling rows. The results indicate a substantial increase in power
requirements at higher drum speeds and when using an increasing number of brush peeling
rows. This result agrees with [
30
]. The lowest recorded power requirement was 79.29 W,
observed under the operational conditions of a drum rotational speed of 100 rpm and
four brush peeling rows. On the other hand, the highest power requirement of 187 W
was recorded at a drum speed of 400 rpm and twelve brush peeling rows. The observed
increase in power requirements with increasing drum rotational speed can be attributed to
the logical relationship between rotational speed and power consumption. The increase in
power requirements with an increasing number of brush peeling rows may be attributed to
factors such as the additional weight of the drum and the increased friction between the
Agriculture 2024,14, 780 10 of 15
moving parts and the seeds. On the other hand, the data presented in the figure illustrate
that the number of brush peeling rows had a more pronounced impact on the consumed
specific energy than the drum rotational speed. Generally, there was a discernible increase
in the consumed specific energy with an increase in the number of peeling rows. The
substantial rise in the consumed specific energy observed with an increase in the number
of peeling brush rows can be attributed to the amplified power requirement and reduced
throughput associated with a higher number of brushes. Meanwhile, the slight effect the
drum’s rotational speed had on the consumed specific energy appears to be a positive
effect of increasing the rotational speed on the machine’s productivity; the effect mostly
disappeared with the increase in energy requirements that occurred at the same time.
Agriculture 2024, 14, 780 10 of 15
in power requirements with an increasing number of brush peeling rows may be at-
tributed to factors such as the additional weight of the drum and the increased friction
between the moving parts and the seeds. On the other hand, the data presented in the
figure illustrate that the number of brush peeling rows had a more pronounced impact on
the consumed specific energy than the drum rotational speed. Generally, there was a dis-
cernible increase in the consumed specific energy with an increase in the number of peel-
ing rows. The substantial rise in the consumed specific energy observed with an increase
in the number of peeling brush rows can be aributed to the amplified power requirement
and reduced throughput associated with a higher number of brushes. Meanwhile, the
slight effect the drum’s rotational speed had on the consumed specific energy appears to
be a positive effect of increasing the rotational speed on the machine’s productivity; the
effect mostly disappeared with the increase in energy requirements that occurred at the
same time.
Figure 6. Effect of drum rotational speed on the power requirements (columns) and consumed spe-
cific energy (lines) at different numbers of peeling brush rows.
3.4. Broken Seed Percentage
Figure 7 depicts the relationship between the percentage of broken seeds and drum
rotational speed at different numbers of brush peeling rows. The findings indicate a direct
correlation between the percentage of broken seeds and both drum speed and the number
of brush peeling rows. This result agrees with [13] and [24]. The lowest recorded value for
the percentage of broken seeds was 1.60%, observed under the operational conditions of
a drum rotational speed of 100 rpm and four brush peeling rows. The highest recorded
value for the percentage of broken seeds (5.75%) was obtained at a drum rotational speed
of 400 rpm and twelve brush peeling rows. The broken seed percentage increased as the
drum rotational speed and the number of brush peeling rows increased. This can be at-
tributed to the increase in the force and frequency of impacts on the seeds caused by the
higher drum rotational speed and the larger number of brush peeling rows.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
0
30
60
90
120
150
180
100 200 300 400
Power requirements W
Drum rotational speed rpm
4 8 12 4 8 12
Specific energy kW.h/ton
Figure 6. Effect of drum rotational speed on the power requirements (columns) and consumed
specific energy (lines) at different numbers of peeling brush rows.
3.4. Broken Seed Percentage
Figure 7depicts the relationship between the percentage of broken seeds and drum
rotational speed at different numbers of brush peeling rows. The findings indicate a direct
correlation between the percentage of broken seeds and both drum speed and the number
of brush peeling rows. This result agrees with [
13
,
24
]. The lowest recorded value for the
percentage of broken seeds was 1.60%, observed under the operational conditions of a
drum rotational speed of 100 rpm and four brush peeling rows. The highest recorded value
for the percentage of broken seeds (5.75%) was obtained at a drum rotational speed of
400 rpm
and twelve brush peeling rows. The broken seed percentage increased as the drum
rotational speed and the number of brush peeling rows increased. This can be attributed to
the increase in the force and frequency of impacts on the seeds caused by the higher drum
rotational speed and the larger number of brush peeling rows.
Agriculture 2024,14, 780 11 of 15
Agriculture 2024, 14, 780 11 of 15
Figure 7. Broken seed percentage “%” at different brush row numbers and different drum rotational
speeds “rpm”.
3.5. Unpeeled Seed Percentage
Figure 8 illustrates the correlation between the percentage of unpeeled seeds and the
drum rotational speed for varying numbers of rows on the drum. In general, an increase
in both drum rotational speed and the number of brush peeling rows was found to be
associated with a decrease in the percentage of unpeeled seeds. This result agrees with
[20]. The lowest recorded value for the percentage of unpeeled seeds was 2.90%, observed
at a drum rotational speed of 400 rpm and twelve brush peeling rows. Conversely, the
highest recorded value for the percentage of unpeeled seeds (7.15%) was obtained at a
drum rotational speed of 100 rpm and four brush peeling rows. When the drum rotational
speed is higher, there is a greater centrifugal force acting on the seeds, causing them to
experience stronger impacts against the brush surfaces. This increased impact force helps
to dislodge the outer peel from the seeds more effectively, resulting in a lower percentage
of unpeeled seeds. Similarly, increasing the number of brush peeling rows provides more
opportunities for the seeds to come into contact with the brushes. This increases the over-
all brushing action and improves the chances of removing the outer peel from the seeds.
Consequently, a higher number of brush peeling rows contributes to a reduced percentage
of unpeeled seeds. Overall, the combination of higher drum rotational speed and an in-
creased number of brush peeling rows enhances the peeling process, leading to a lower
percentage of unpeeled seeds.
Figure 8. Unpeeled seed percentage “%” at different brush row numbers and different drum rota-
tional speeds “rpm”.
3.6. Peeling Efficiency
The findings depicted in Figure 9 indicate a positive correlation between both drum
rotational speed and the number of brush peeling rows and peeling efficiency. Increasing
drum rotational speeds generally resulted in higher average peeling efficiencies. This result
agrees with refs [31,32]. The highest recorded value for peeling efficiency was 97.10%,
Figure 7. Broken seed percentage “%” at different brush row numbers and different drum rotational
speeds “rpm”.
3.5. Unpeeled Seed Percentage
Figure 8illustrates the correlation between the percentage of unpeeled seeds and the
drum rotational speed for varying numbers of rows on the drum. In general, an increase
in both drum rotational speed and the number of brush peeling rows was found to be
associated with a decrease in the percentage of unpeeled seeds. This result agrees with [
20
].
The lowest recorded value for the percentage of unpeeled seeds was 2.90%, observed
at a drum rotational speed of 400 rpm and twelve brush peeling rows. Conversely, the
highest recorded value for the percentage of unpeeled seeds (7.15%) was obtained at a drum
rotational speed of 100 rpm and four brush peeling rows. When the drum rotational speed
is higher, there is a greater centrifugal force acting on the seeds, causing them to experience
stronger impacts against the brush surfaces. This increased impact force helps to dislodge
the outer peel from the seeds more effectively, resulting in a lower percentage of unpeeled
seeds. Similarly, increasing the number of brush peeling rows provides more opportunities
for the seeds to come into contact with the brushes. This increases the overall brushing
action and improves the chances of removing the outer peel from the seeds. Consequently,
a higher number of brush peeling rows contributes to a reduced percentage of unpeeled
seeds. Overall, the combination of higher drum rotational speed and an increased number
of brush peeling rows enhances the peeling process, leading to a lower percentage of
unpeeled seeds.
Agriculture 2024, 14, 780 11 of 15
Figure 7. Broken seed percentage “%” at different brush row numbers and different drum rotational
speeds “rpm”.
3.5. Unpeeled Seed Percentage
Figure 8 illustrates the correlation between the percentage of unpeeled seeds and the
drum rotational speed for varying numbers of rows on the drum. In general, an increase
in both drum rotational speed and the number of brush peeling rows was found to be
associated with a decrease in the percentage of unpeeled seeds. This result agrees with
[20]. The lowest recorded value for the percentage of unpeeled seeds was 2.90%, observed
at a drum rotational speed of 400 rpm and twelve brush peeling rows. Conversely, the
highest recorded value for the percentage of unpeeled seeds (7.15%) was obtained at a
drum rotational speed of 100 rpm and four brush peeling rows. When the drum rotational
speed is higher, there is a greater centrifugal force acting on the seeds, causing them to
experience stronger impacts against the brush surfaces. This increased impact force helps
to dislodge the outer peel from the seeds more effectively, resulting in a lower percentage
of unpeeled seeds. Similarly, increasing the number of brush peeling rows provides more
opportunities for the seeds to come into contact with the brushes. This increases the over-
all brushing action and improves the chances of removing the outer peel from the seeds.
Consequently, a higher number of brush peeling rows contributes to a reduced percentage
of unpeeled seeds. Overall, the combination of higher drum rotational speed and an in-
creased number of brush peeling rows enhances the peeling process, leading to a lower
percentage of unpeeled seeds.
Figure 8. Unpeeled seed percentage “%” at different brush row numbers and different drum rota-
tional speeds “rpm”.
3.6. Peeling Efficiency
The findings depicted in Figure 9 indicate a positive correlation between both drum
rotational speed and the number of brush peeling rows and peeling efficiency. Increasing
drum rotational speeds generally resulted in higher average peeling efficiencies. This result
agrees with refs [31,32]. The highest recorded value for peeling efficiency was 97.10%,
Figure 8. Unpeeled seed percentage “%” at different brush row numbers and different drum rotational
speeds “rpm”.
3.6. Peeling Efficiency
The findings depicted in Figure 9indicate a positive correlation between both drum
rotational speed and the number of brush peeling rows and peeling efficiency. Increasing
drum rotational speeds generally resulted in higher average peeling efficiencies. This
result agrees with refs [
31
,
32
]. The highest recorded value for peeling efficiency was
Agriculture 2024,14, 780 12 of 15
97.10%, observed under the operational conditions of a drum speed of 400 rpm and twelve
brush peeling rows. Conversely, the lowest recorded value for peeling efficiency was
92.85%, observed at a drum rotational speed of 100 rpm and four brush peeling rows.
Increasing the drum rotational speed leads to a higher velocity of seed movement within
the machine. This increased speed enhances the kinetic energy of the seeds and the
interactions between the seeds and the brushes. As a result, a higher drum rotational
speed typically corresponds to an improved peeling efficiency. The increased kinetic energy
and more vigorous brushing action aid in the removal of the outer peel from the seeds,
leading to a higher peeling efficiency. Similarly, increasing the number of brush peeling
rows provides more opportunities for the seeds to come into contact with the brushes. This
increases the overall brushing action and improves the chances of removing the outer peel
from the seeds. Consequently, a higher number of brush peeling rows contributes to a
higher peeling efficiency.
Agriculture 2024, 14, 780 12 of 15
observed under the operational conditions of a drum speed of 400 rpm and twelve brush
peeling rows. Conversely, the lowest recorded value for peeling efficiency was 92.85%, ob-
served at a drum rotational speed of 100 rpm and four brush peeling rows. Increasing the
drum rotational speed leads to a higher velocity of seed movement within the machine. This
increased speed enhances the kinetic energy of the seeds and the interactions between the
seeds and the brushes. As a result, a higher drum rotational speed typically corresponds to
an improved peeling efficiency. The increased kinetic energy and more vigorous brushing
action aid in the removal of the outer peel from the seeds, leading to a higher peeling effi-
ciency. Similarly, increasing the number of brush peeling rows provides more opportunities
for the seeds to come into contact with the brushes. This increases the overall brushing ac-
tion and improves the chances of removing the outer peel from the seeds. Consequently, a
higher number of brush peeling rows contributes to a higher peeling efficiency.
Figure 9. Peeling efficiency “%” at different brush row numbers and different drum rotational
speeds “rpm”.
Figure 10 shows the chickpea seeds before and after the peeling process and the ex-
tracted peels.
Figure 10. Chickpea seeds before peeling (left), after peeling (middle), and the peels (right).
3.7. Prediction Results
Figure 11 illustrates the relationship between scratching times (number) and the
probability that the shuck will be scratched off. It can be noted that the results of the pre-
diction module match the experimental results. The figure illustrates that when the arith-
metic (experimental) frequency of chickpea seed impacts by the peeling brushes (depend-
ent on the peeling drum rotational speed and the number of rows of peeling brushes) is
equivalent or proximate, they reside within the same region as the probability of peel de-
tachment. For instance, at a seed impact frequency of 2.7, under two operational scenarios,
Figure 9. Peeling efficiency “%” at different brush row numbers and different drum rotational
speeds “rpm”.
Figure 10 shows the chickpea seeds before and after the peeling process and the
extracted peels.
Agriculture 2024, 14, 780 12 of 15
observed under the operational conditions of a drum speed of 400 rpm and twelve brush
peeling rows. Conversely, the lowest recorded value for peeling efficiency was 92.85%, ob-
served at a drum rotational speed of 100 rpm and four brush peeling rows. Increasing the
drum rotational speed leads to a higher velocity of seed movement within the machine. This
increased speed enhances the kinetic energy of the seeds and the interactions between the
seeds and the brushes. As a result, a higher drum rotational speed typically corresponds to
an improved peeling efficiency. The increased kinetic energy and more vigorous brushing
action aid in the removal of the outer peel from the seeds, leading to a higher peeling effi-
ciency. Similarly, increasing the number of brush peeling rows provides more opportunities
for the seeds to come into contact with the brushes. This increases the overall brushing ac-
tion and improves the chances of removing the outer peel from the seeds. Consequently, a
higher number of brush peeling rows contributes to a higher peeling efficiency.
Figure 9. Peeling efficiency “%” at different brush row numbers and different drum rotational
speeds “rpm”.
Figure 10 shows the chickpea seeds before and after the peeling process and the ex-
tracted peels.
Figure 10. Chickpea seeds before peeling (left), after peeling (middle), and the peels (right).
3.7. Prediction Results
Figure 11 illustrates the relationship between scratching times (number) and the
probability that the shuck will be scratched off. It can be noted that the results of the pre-
diction module match the experimental results. The figure illustrates that when the arith-
metic (experimental) frequency of chickpea seed impacts by the peeling brushes (depend-
ent on the peeling drum rotational speed and the number of rows of peeling brushes) is
equivalent or proximate, they reside within the same region as the probability of peel de-
tachment. For instance, at a seed impact frequency of 2.7, under two operational scenarios,
Figure 10. Chickpea seeds before peeling (left), after peeling (middle), and the peels (right).
3.7. Prediction Results
Figure 11 illustrates the relationship between scratching times (number) and the
probability that the shuck will be scratched off. It can be noted that the results of the
prediction module match the experimental results. The figure illustrates that when the
arithmetic (experimental) frequency of chickpea seed impacts by the peeling brushes
(dependent on the peeling drum rotational speed and the number of rows of peeling
brushes) is equivalent or proximate, they reside within the same region as the probability
Agriculture 2024,14, 780 13 of 15
of peel detachment. For instance, at a seed impact frequency of 2.7, under two operational
scenarios, namely 200 rpm with four rows of peeling brushes and 100 rpm with eight
rows of peeling brushes, the novel model predicts that the likelihood of chickpea peeling
is comparable.
Agriculture 2024, 14, 780 13 of 15
namely 200 rpm with four rows of peeling brushes and 100 rpm with eight rows of peeling
brushes, the novel model predicts that the likelihood of chickpea peeling is comparable.
Figure 11. Relationship between scratching times and the probability of shuck removal in chickpea peel-
ing.
3.8. Cost Analysis
Table 3 presents the consumption and operating costs associated with the chickpea
peeling unit. The table encompasses the total fixed costs (0.05 $/h), which encompass de-
preciation costs, interest costs, taxes, insurance, and shelter costs. It also includes variable
costs ($0.61) arising from machine operation, such as repair and maintenance costs, labor
costs, and power costs (at the optimal operational condition). According to the table, the
total cost is $0.66. With a 71.29 kg/h throughput in the optimal operational conditions, the
peeling cost for 1 kg is 0.01 U.S.D. (United States Dollar) which is equal to 0.4 E.L. (the
Egyptian currency).
Table 3. Fixed and variable costs of peeling module.
Item Cost $ (E.L is the Egyptian Currency)
Peeler price $ (U.S.D) $100 (4100 E.L)
Depreciation costs $/year 12.5 $/year (525 E.L/year)
Interest costs $/year 5 $/year (210 E.L/year)
Taxes, insurance, and shelter costs $/year 2 $/year (84 E.L/year)
Fixed costs in $/h 0.05 $/h (2.1 E.L/h)
Repair and maintenance costs $/h 0.005 $/h (0.22 E.L/h)
Labor costs $ 0.6 $/h (25 E.L/h)
Power cost $/h 0.0045 $/h (0.2 E.L/h)
Variable costs 0.61 $/h (25.6 E.L/h)
Total cost 0.66 $/h (27 E.L/h)
4. Conclusions
The peeling process is of paramount importance in evaluating the quality of the final
product, and the utilization of peeling machines brings forth notable advantages in terms
of improved product quality, shortened processing time, and reduced labor demands.
Based on the experimental findings of the tested model, the authors recommend consid-
ering operational conditions of 400 rpm for the drum rotational speed and four rows of
peeling brushes to be the optimal operation condition. This operating condition recorded
Figure 11. Relationship between scratching times and the probability of shuck removal in
chickpea peeling.
3.8. Cost Analysis
Table 3presents the consumption and operating costs associated with the chickpea
peeling unit. The table encompasses the total fixed costs (0.05 $/h), which encompass
depreciation costs, interest costs, taxes, insurance, and shelter costs. It also includes variable
costs ($0.61) arising from machine operation, such as repair and maintenance costs, labor
costs, and power costs (at the optimal operational condition). According to the table, the
total cost is $0.66. With a 71.29 kg/h throughput in the optimal operational conditions, the
peeling cost for 1 kg is 0.01 U.S.D. (United States Dollar) which is equal to 0.4 E.L. (the
Egyptian currency).
Table 3. Fixed and variable costs of peeling module.
Item Cost $ (E.L is the Egyptian Currency)
Peeler price $ (U.S.D) $100 (4100 E.L)
Depreciation costs $/year 12.5 $/year (525 E.L/year)
Interest costs $/year 5 $/year (210 E.L/year)
Taxes, insurance, and shelter costs $/year 2 $/year (84 E.L/year)
Fixed costs in $/h 0.05 $/h (2.1 E.L/h)
Repair and maintenance costs $/h 0.005 $/h (0.22 E.L/h)
Labor costs $ 0.6 $/h (25 E.L/h)
Power cost $/h 0.0045 $/h (0.2 E.L/h)
Variable costs 0.61 $/h (25.6 E.L/h)
Total cost 0.66 $/h (27 E.L/h)
4. Conclusions
The peeling process is of paramount importance in evaluating the quality of the final
product, and the utilization of peeling machines brings forth notable advantages in terms of
improved product quality, shortened processing time, and reduced labor demands. Based
on the experimental findings of the tested model, the authors recommend considering
operational conditions of 400 rpm for the drum rotational speed and four rows of peeling
brushes to be the optimal operation condition. This operating condition recorded the
Agriculture 2024,14, 780 14 of 15
highest productivity (71.29 kg/h) and achieved a peeling efficiency (95.95%) close to the
maximum recorded peeling efficiency (97.10).
The authors intend to conduct a simulation using specialized software programs
to predict the efficiency of the peeling process. Additionally, they plan to investigate
the impact of the blower’s airspeed on the separation of peels from seeds. Furthermore,
the authors aim to incorporate FNN (Feedforward Neural Network) machine learning
techniques to determine the optimal operational conditions as an electronic method in
this field.
Author Contributions: Conceptualization, K.A.M.A. and C.L.; methodology, E.A.D.; software, S.T.L.;
validation, T.A.M.A., A.E.M.F. and H.W.; formal analysis, S.T.L.; investigation, C.L.; resources,
E.A.D.; data curation, Y.F.E.; writing—original draft preparation, E.A.D.; writing—review and editing,
K.A.M.A.; visualization, H.W.; supervision, C.L.; project administration, C.L.; funding acquisition,
H.W. All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by the National Natural Science Foundation of China, grant
number 32171906.
Data Availability Statement: All data and materials are available upon request.
Conflicts of Interest: The authors declare no conflicts of interest.
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