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<title>DEVELOPMENT AND OPTIMISATION OF AN INTEGRATED SEMI-AUTOMATED GRADING MACHINE FOR COWPEA (Vigna unguiculata (L.) WALP) SEEDS</title>
<link>http://hdl.handle.net/123456789/2303</link>
<description/>
<pubDate>Tue, 07 Apr 2026 17:20:27 GMT</pubDate>
<dc:date>2026-04-07T17:20:27Z</dc:date>
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<title>DEVELOPMENT AND OPTIMISATION OF AN INTEGRATED SEMI-AUTOMATED GRADING MACHINE FOR COWPEA (Vigna unguiculata (L.) WALP) SEEDS</title>
<link>http://hdl.handle.net/123456789/2304</link>
<description>DEVELOPMENT AND OPTIMISATION OF AN INTEGRATED SEMI-AUTOMATED GRADING MACHINE FOR COWPEA (Vigna unguiculata (L.) WALP) SEEDS
AUDU, John
Nigeria is the largest producer of cowpea. Despite this relatively large production, its export&#13;
has been hindered by poor seed grading and inefficient processing. Existing cowpea grading&#13;
machines are mostly for unit operations. Integrated grading machine are needed for&#13;
improved seed grading and efficient processing. Therefore, this study was designed to&#13;
develop an integrated semi-automated cowpea grading machine.&#13;
Standard methods were used to determine the optical and electrical parameters of three&#13;
indigenous cowpea seed varieties (NG/AD/11/08/0033, NG/OA/11/08/063 and&#13;
NGB/OG/0055) for the automation unit design considerations. This was carried out at seed&#13;
moisture levels (8.0, 10.0, 12.0, 14.0 and 16.0%), light wavelength (320, 420, 520, 620 and&#13;
720 nm) and current frequency (1, 500, 1000, 1500, 2000 kHz). Thereafter, an integrated&#13;
semi-automated machine with three separating units was developed and automated using&#13;
machine vision technology. Operational parameters used for evaluation were speed of drum&#13;
(40, 60 and 80) rpm, bucket conveyor speed (250, 300 and 350) rpm and metering disc (12,&#13;
16 and 20) rpm; seed variety and grade (9.8%, 16.0% and 21.0%) of impurity. The total&#13;
machine system output was evaluated and optimised in terms of efficiency, throughput,&#13;
maximum capacity, actual utilisation and backlog, using response surface methodology.&#13;
Prediction interval and multiple regression analysis were used for validation at α 0.05.&#13;
The optical properties ranged from: 0-1.8%, 0-1.0%, 0-12.0%, ([38-92.2%] [0.7-9.0%]&#13;
[13.6-27.3%]) for absorbance, reflectance, transmittance and colour (L* a* b*),&#13;
respectively; while electrical properties ranged from 1.926-15.625 Ω, 0.272-2.209 Ωm,&#13;
0.064–0.519 S, 0.453–3.671 S/m, 1.800x10-11–1.380x10-7 F, 0.500-4928.570, 6.020 x107-&#13;
9.040x1021 H) and 1.150x106–1.450x107 Ω, for resistance, resistivity, conductance,&#13;
conductivity, inductance and impedance, respectively. The two separating units (sieve&#13;
drums) removed impurities &gt; 12 mm and &lt; 2 mm with efficiency of 76.6±9.343% and&#13;
85.3±11.1%; throughput of 0.220±0.139kg/hr and 0.144±0.111kg/hr, respectively. The third&#13;
digital automated sorting unit separated diseased and insect damaged seeds by colour with&#13;
efficiency of 82.1±7.2% and throughput of 1.386± 0.758kg/hr. Operational parameters were&#13;
found to have significant effect on all evaluation terms. The efficiency, throughput,vi&#13;
maximum capacity, actual utilisation and backlog of the total system output ranged from&#13;
63.5-80.4%, 0.574–3.732 kg/hr, 6.882-44.778 kg/12hr, 0.083-0.083 (8.3%) and 0.03–0.182&#13;
kg, respectively. At 80.4% efficiency, the impurity of grade 3 was reduced to grade 2, and 2&#13;
to 1 based on the standard export grade range. The integrated machine system optimisation&#13;
achieved two best solutions. The first and second having maximum total system impurity&#13;
separating efficiency of 81.3 and 79.9%, maximum total system throughput of 3.470 and&#13;
5.077 kg/hr and minimal total system backlog of 0.064 and 0.07 kg, respectively. The&#13;
validation data were within 95% low and high prediction intervals. The evaluation terms&#13;
had coefficient of determinations (R2) values &gt; 0.9 showing no significance between&#13;
predicted and validation data.&#13;
The developed integrated semi-automated grading machine for cowpea reduced the&#13;
impurity in indigenous cowpea varieties to exportable grade.
</description>
<pubDate>Sun, 01 Jan 2023 00:00:00 GMT</pubDate>
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<dc:date>2023-01-01T00:00:00Z</dc:date>
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