Dataset for Fish’s Freshness Problems

The dataset for fish freshness problem, included sensor data, images, and organoleptic examination. The sensor data is generated using MQ 135 and TGS 2602. The images has square in size. The organoleptic examination is generated by checking in fish body based on Standard National Indonesia (SNI) 2729:2013, the data is presented in the article below. The dataset consists of 3 fish species: mackerel, tilapia, and tuna. The number of MQ 135 and TGS 2602 sensor data for the three species is 9,401 data each, while the images are 859, 840, and 837, respectively. If you use this dataset, please cite related articles - Prasetyo et al. (2024), "DaFiF: A Complete Dataset for Fish's Freshness Problems", Data in Brief - Prasetyo et al (2024), "Standardizing the fish freshness class during ice storage using clustering approach", Ecological Informatics, Vol. 80, DOI: https://doi.org/10.1016/j.ecoinf.2024.102533

本数据集针对鱼类新鲜度研究场景构建，涵盖传感器数据、图像数据及感官检验数据三大类。其中传感器数据由MQ 135与TGS 2602两类传感器采集生成；所有图像数据均为正方形尺寸；感官检验环节依据印度尼西亚国家标准（Standard National Indonesia，SNI）2729:2013对鱼体进行检测，相关数据已在下文的研究文章中呈现。
本数据集共包含3种受试鱼类：鲭鱼、罗非鱼与金枪鱼。针对这三类鱼种，MQ 135与TGS 2602传感器数据各有9401条，对应的图像数据量分别为859张、840张与837张。
若使用本数据集，请引用以下相关文献：
1. Prasetyo等（2024），《DaFiF：面向鱼类新鲜度问题的完整数据集》，《Data in Brief》
2. Prasetyo等（2024），《基于聚类方法的冰藏鱼类新鲜度等级标准化》，《Ecological Informatics》第80卷，DOI: https://doi.org/10.1016/j.ecoinf.2024.102533