TY - JOUR
T1 - DaFiF
T2 - A complete dataset for fish's freshness problems
AU - Prasetyo, Eko
AU - Suciati, Nanik
AU - Sutramiani, Ni Putu
AU - Adiananda, Adiananda
AU - Dewi, Ayu Putu Wiweka Krisna
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/12
Y1 - 2024/12
N2 - The fish are incorporated with ice to preserve their freshness when sold on the market. Ordinary people can only detect its freshness with some basic freshness knowledge. Therefore, non-destructive fish freshness inspection is an innovative solution to help. This dataset provides a medium to develop a system for non-destructive detection of fish freshness. There are three data variations: sensor data, images, and organoleptic examination. This dataset includes three fish species: mackerel, tilapia, and tuna, using 21 fish of each species. Data generation was carried out for 11 days, where 800 MQ (Metal Oxide) 135 and TGS (Taguchi Gas Sensor) 2602 sensor data and 80 images were generated every day. Organoleptic examinations were carried out using the Indonesian National Standard (SNI) 2729-2013 on six parameters: eyes, gills, body surface mucus, meat, smell, and body textures. This dataset can be used to develop a fish freshness detection system, regression modeling to estimate the deterioration in fish freshness, and standard grouping of freshness classes.
AB - The fish are incorporated with ice to preserve their freshness when sold on the market. Ordinary people can only detect its freshness with some basic freshness knowledge. Therefore, non-destructive fish freshness inspection is an innovative solution to help. This dataset provides a medium to develop a system for non-destructive detection of fish freshness. There are three data variations: sensor data, images, and organoleptic examination. This dataset includes three fish species: mackerel, tilapia, and tuna, using 21 fish of each species. Data generation was carried out for 11 days, where 800 MQ (Metal Oxide) 135 and TGS (Taguchi Gas Sensor) 2602 sensor data and 80 images were generated every day. Organoleptic examinations were carried out using the Indonesian National Standard (SNI) 2729-2013 on six parameters: eyes, gills, body surface mucus, meat, smell, and body textures. This dataset can be used to develop a fish freshness detection system, regression modeling to estimate the deterioration in fish freshness, and standard grouping of freshness classes.
KW - Fish
KW - Freshness
KW - Images
KW - Organoleptic
KW - Sensor Data
UR - http://www.scopus.com/inward/record.url?scp=85206518839&partnerID=8YFLogxK
U2 - 10.1016/j.dib.2024.111016
DO - 10.1016/j.dib.2024.111016
M3 - Article
AN - SCOPUS:85206518839
SN - 2352-3409
VL - 57
JO - Data in Brief
JF - Data in Brief
M1 - 111016
ER -