ArticleHeliyon2020
Performance evaluation and optimization of a
Article in Heliyon, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Depodding of moringa which is still being carried out manually by removing with hand or by hitting a bag containing the pods is time-consuming, labour intensive and not economical. The demand for quality oil-bearing moringa seeds that have a wide area of industrial applications necessitates innovative deppoding techniques that will improve its market value. To ameliorate these problems, moringa depoddding machine has been developed but studies on performance evaluation and optimal parameter setting are sparsely reported. This study therefore, evaluated the effects of the processing factors (moisture content (MC) and speed of rotation (SR)) levels on the performance (throughput capacity (TP), effective throughput capacity (ETP), labour requirement (LR), depodding coefficient (DC), coefficient of wholeness (CW), depodding efficiency (DE), depodded kernel (DK), undepodded kernel (UK), small broken kernel (SBK), and big broken kernel (BBK)) of the designed and fabricated moringa depodding machine using the response surface methodology and test between subjects-effects. The experimental design used was a two factor, three levels i-optimal randomized design. Mathematical models relating the process factors to performance were developed. The predicted optimum results obtained were validated using the observed values of the experiment. MC and SR were found to have a significant effect on the performance of the machine. The predicted optimum performance of the machine were 113.73 kg/hr, 109.45 kg/hr, 0.85 man-hour required/Kg, 96.15 %, 0.96, 93.93 %, 0.98, 0.02, 10.64 %, and 1.24 % for TP, ETP, LR, DC, CW, DE, DK, UK, SBK, and BBK respectively at MC and SR of 10.10 % wet basis and 564 rpm. The experimental values at these processing conditions were close to the predicted optimum results obtained with little deviations which were statistically insignificant. The selected models sufficiently predicted the performance of the developed machine.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.