A Review on the Organic and Non-Organic Fruits and Vegetable Detection Methods

被引:0
|
作者
Natarajan, Sowmya [1 ]
Ponnusamy, Vijayakumar [1 ]
机构
[1] SRM Inst Sci & Technol, Elect & Commun Engn, Chennai, Tamil Nadu, India
来源
2021 SIXTH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET) | 2021年
关键词
Deep Learning; Non-organic compounds; Organic compounds; Spectroscopic methods; CHEMOMETRIC ANALYSIS; QUALITY PARAMETERS; SPECTROSCOPY; DISCRIMINATION; PRODUCTIONS; PREDICTION; RESONANCE; RESIDUES; PEPPERS; SYSTEMS;
D O I
10.1109/WISPNET51692.2021.9419397
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The growth of organic fruits and vegetables is becoming a challenging task nowadays. In markets, there is a problem exist in differentiating between organic and in-organic products. The qualitative spectroscopic analysis combined with Ma-chine learning techniques provides good results for finding the internal compositional information. The nutritional and fraudulent examinations deliver qualitative classification knowledge to the consumers. The vitamins, antioxidants, phenolic nitrate ion compounds, nitrogen - 15, Volume, and Colors are categorized as organic compounds during the discrimination process. This review paper discusses various Visible, NIR-MIR analysis and various imaging analysis methods for discriminating organic and non-organic compounds in different fruits and vegetables. Some of the deep learning and Machine learning techniques are also discussed in this literature review analysis.
引用
收藏
页码:1 / 5
页数:5
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