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<p>Nowadays everyone is prioritising their health and investing in maintaining it. People understand the value of a nutritious diet, with fruits being a key component due to their abundance of essential vitamins and minerals necessary for good health. However, there’s growing concern over using artificial ripening agents on fruits, which can cause health hazards. This paper examines various approaches to identify artificially ripened fruits, considering their effectiveness, limitations, and applicability in ensuring food safety and consumer health. The analysis aims to contribute to the enhancement of fruit quality control measures and the prevention of health hazards associated with the consumption of artificially ripened fruits. This paper proposes a novel approach which combines triad spectroscopy, TGS 2600 gas sensor and Raspberry Pi-based image processing to detect artificially ripened fruits, which has not been explored yet. This integration will offer a promising theoretical solution, with the potential for real-time detection of artificially ripened fruits. The proposed approach will improve detection accuracy and provide a cost-effective method.</p>

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An analysis on detection of artificially ripened fruits

  • 期刊论文

  • 发表日期：

    2025年3月7日

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  • N. Renugadevi,
  • Cherukuri V. L. N. Kartheek,
  • Karthik Nivedhan,
  • Raahath Shaik,
  • Vikash Baabhu

摘要

Nowadays everyone is prioritising their health and investing in maintaining it. People understand the value of a nutritious diet, with fruits being a key component due to their abundance of essential vitamins and minerals necessary for good health. However, there’s growing concern over using artificial ripening agents on fruits, which can cause health hazards. This paper examines various approaches to identify artificially ripened fruits, considering their effectiveness, limitations, and applicability in ensuring food safety and consumer health. The analysis aims to contribute to the enhancement of fruit quality control measures and the prevention of health hazards associated with the consumption of artificially ripened fruits. This paper proposes a novel approach which combines triad spectroscopy, TGS 2600 gas sensor and Raspberry Pi-based image processing to detect artificially ripened fruits, which has not been explored yet. This integration will offer a promising theoretical solution, with the potential for real-time detection of artificially ripened fruits. The proposed approach will improve detection accuracy and provide a cost-effective method.