DaFiF: A complete dataset for fish's freshness problems

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2024-10-10 DOI:10.1016/j.dib.2024.111016

Eko Prasetyo , Nanik Suciati , Ni Putu Sutramiani , Adiananda Adiananda , Ayu Putu Wiweka Krisna Dewi

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引用次数: 0

Abstract

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.

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DaFiF：鱼类新鲜度问题的完整数据集

鱼在市场上出售时，会加入冰块保鲜。普通人只能通过一些基本的保鲜知识来检测其新鲜程度。因此，非破坏性鱼类新鲜度检测是一种创新的解决方案。该数据集为开发无损检测鱼类新鲜度的系统提供了媒介。有三种数据变化：传感器数据、图像和感官检查。该数据集包括三种鱼类：鲭鱼、罗非鱼和金枪鱼，每种鱼类 21 条。数据生成工作持续了 11 天，每天生成 800 个 MQ（金属氧化物）135 和 TGS（田口气体传感器）2602 传感器数据和 80 幅图像。使用印度尼西亚国家标准（SNI）2729-2013 对六个参数进行了感官检查：眼睛、鳃、体表粘液、肉、气味和身体质地。该数据集可用于开发鱼类新鲜度检测系统、建立回归模型以估算鱼类新鲜度的恶化程度，以及对新鲜度等级进行标准分组。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.