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Study on optimization of mechanical peeling for sweet potato

Authors: null Vithu P; null Sanjaya K. Dash; null Kalpana Rayaguru; null Uma Sankar Pal;

Study on optimization of mechanical peeling for sweet potato

Abstract

The aim of this research work was to optimize the machine parameters of a commercially available tuber peeler for peeling of sweet potato to get maximum yield with minimum loss. The process was proposed for different parameters such as peeling efficiency, material loss and peeling effectiveness at different speeds of rotating disc (300, 400 and 500 rev/min or 5.4, 7.2 and 9 m/s), peeling durations (20, 40 and 60 s) and batch loads of 1 and 2 kg. The study revealed that the peeling parameters were greatly influenced by the speed of rotating disc, peeling duration and batch loads. The optimal conditions for peeling sweet potato were a peeling duration of 40 s and speed of rotating disc of 500 rev/min 2 kg batch loads. The corresponding peeling efficiency, peeling effectiveness and material loss were 83.8±2.0%, 74.2±1.3% and 11.45±0.71%, respectively. Further, the study showed that a batch load of 2 kg was suitable for commercial processing of sweet potato than 1 kg because of better performance indices of peeling.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
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