Abstract:
Nigeria is the largest producer of cowpea. Despite this relatively large production, its export
has been hindered by poor seed grading and inefficient processing. Existing cowpea grading
machines are mostly for unit operations. Integrated grading machine are needed for
improved seed grading and efficient processing. Therefore, this study was designed to
develop an integrated semi-automated cowpea grading machine.
Standard methods were used to determine the optical and electrical parameters of three
indigenous cowpea seed varieties (NG/AD/11/08/0033, NG/OA/11/08/063 and
NGB/OG/0055) for the automation unit design considerations. This was carried out at seed
moisture levels (8.0, 10.0, 12.0, 14.0 and 16.0%), light wavelength (320, 420, 520, 620 and
720 nm) and current frequency (1, 500, 1000, 1500, 2000 kHz). Thereafter, an integrated
semi-automated machine with three separating units was developed and automated using
machine vision technology. Operational parameters used for evaluation were speed of drum
(40, 60 and 80) rpm, bucket conveyor speed (250, 300 and 350) rpm and metering disc (12,
16 and 20) rpm; seed variety and grade (9.8%, 16.0% and 21.0%) of impurity. The total
machine system output was evaluated and optimised in terms of efficiency, throughput,
maximum capacity, actual utilisation and backlog, using response surface methodology.
Prediction interval and multiple regression analysis were used for validation at α 0.05.
The optical properties ranged from: 0-1.8%, 0-1.0%, 0-12.0%, ([38-92.2%] [0.7-9.0%]
[13.6-27.3%]) for absorbance, reflectance, transmittance and colour (L* a* b*),
respectively; while electrical properties ranged from 1.926-15.625 Ω, 0.272-2.209 Ωm,
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-
9.040x1021 H) and 1.150x106–1.450x107 Ω, for resistance, resistivity, conductance,
conductivity, inductance and impedance, respectively. The two separating units (sieve
drums) removed impurities > 12 mm and < 2 mm with efficiency of 76.6±9.343% and
85.3±11.1%; throughput of 0.220±0.139kg/hr and 0.144±0.111kg/hr, respectively. The third
digital automated sorting unit separated diseased and insect damaged seeds by colour with
efficiency of 82.1±7.2% and throughput of 1.386± 0.758kg/hr. Operational parameters were
found to have significant effect on all evaluation terms. The efficiency, throughput,vi
maximum capacity, actual utilisation and backlog of the total system output ranged from
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
kg, respectively. At 80.4% efficiency, the impurity of grade 3 was reduced to grade 2, and 2
to 1 based on the standard export grade range. The integrated machine system optimisation
achieved two best solutions. The first and second having maximum total system impurity
separating efficiency of 81.3 and 79.9%, maximum total system throughput of 3.470 and
5.077 kg/hr and minimal total system backlog of 0.064 and 0.07 kg, respectively. The
validation data were within 95% low and high prediction intervals. The evaluation terms
had coefficient of determinations (R2) values > 0.9 showing no significance between
predicted and validation data.
The developed integrated semi-automated grading machine for cowpea reduced the
impurity in indigenous cowpea varieties to exportable grade.
