Developing and evaluating a semi-industrial carrot peeling machine

This study developed and evaluated a semi-industrial mechanical carrot peeler designed for efficient, uniform peeling with minimal waste. The machine featured rubber rollers with cold foam coating, stainless-steel blades with a hinge system, and a grooved aluminum frame, designed in CATIA and fabricated using laser cutting and CNC machining. Power was supplied by two geared electromotors through a belt-pulley system. Performance was tested on carrots of two diameter ranges (2–3 cm and 3–4 cm) at two linear travel speeds (15 and 25 cm s -1 ), with three replications. Results showed that carrot diameter, speed, and their interaction significantly affected peeling percentage. The highest peeling efficiency occurred with larger carrots at lower speed, while smaller carrots at higher speed showed the lowest efficiency. Peeling thickness was influenced only by carrot diameter, with smaller carrots producing thinner peels. A strong correlation was observed between initial weight and peeling thickness. The machine achieved an average peeling thickness of 1.8 mm, compared to 2.4 mm for hand peeling, resulting in reduced waste. Additionally, hand peeling consumed approximately four times more energy than machine-assisted peeling per carrot sample. Overall, the developed machine offers an economical and efficient solution for small- and medium-scale production.

Authors

Institutions

Publication Details

Journal
Applied Food Research
Published
2026-10-03
DOI
https://doi.org/10.1016/j.afres.2026.102691
Primary Topic
Agricultural Engineering and Mechanization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Developing and evaluating a semi-industrial carrot peeling machine

Alireza Soleimanipour, Keyvan Asefpour Vakilian, Mohsen Azadbakht, Amir Jafarzadeh
Applied Food Research
Agricultural Engineering and Mechanization
article

Developing and evaluating a semi-industrial carrot peeling machine

Alireza Soleimanipour, Keyvan Asefpour Vakilian, Mohsen Azadbakht, Amir Jafarzadeh
article en

Abstract

This study developed and evaluated a semi-industrial mechanical carrot peeler designed for efficient, uniform peeling with minimal waste. The machine featured rubber rollers with cold foam coating, stainless-steel blades with a hinge system, and a grooved aluminum frame, designed in CATIA and fabricated using laser cutting and CNC machining. Power was supplied by two geared electromotors through a belt-pulley system. Performance was tested on carrots of two diameter ranges (2–3 cm and 3–4 cm) at two linear travel speeds (15 and 25 cm s -1 ), with three replications. Results showed that carrot diameter, speed, and their interaction significantly affected peeling percentage. The highest peeling efficiency occurred with larger carrots at lower speed, while smaller carrots at higher speed showed the lowest efficiency. Peeling thickness was influenced only by carrot diameter, with smaller carrots producing thinner peels. A strong correlation was observed between initial weight and peeling thickness. The machine achieved an average peeling thickness of 1.8 mm, compared to 2.4 mm for hand peeling, resulting in reduced waste. Additionally, hand peeling consumed approximately four times more energy than machine-assisted peeling per carrot sample. Overall, the developed machine offers an economical and efficient solution for small- and medium-scale production.

Applied Food ResearchVol. 6(2)
Gorgan University of Agricultural Sciences and Natural Resources (IR)
Openalex Percentile: Top 21%
Agricultural Engineering and Mechanization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.