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Paper ID:IJSREM65950

An Integrated System for Mineral Content Analysis and Pesticide Residue Management in Fruits and Vegetables

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65950

Volume:

10 |

7 |

Jul 2026

Pages:

1-7

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

KC

Krithika C

Computer Science And Engineering

Avinashilingam Institute for Home Science and Higher Education for Women

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HKK

Harini K K

Computer Science And Engineering

Avinashilingam Institute for Home Science and Higher Education for Women

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PBR

Pradeepaa B R

Computer Science And Engineering

Avinashilingam Institute for Home Science and Higher Education for Women

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SSK

Samyuktha S K

Computer Science And Engineering

Avinashilingam Institute for Home Science and Higher Education for Women

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Mentors

MRD

Mrs R Divya

Computer Science And Engineering

Avinashilingam Institute for Home Science and Higher Education for Women

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Abstract

Fruits and vegetables may carry pesticide residues that are invisible to the naked eye, while consumers currently have no fast, affordable way to verify either the safety or the nutritional value of their produce before consumption. Existing laboratory methods, such as chromatography-based residue testing, are accurate but expensive, time-consuming, and inaccessible for everyday use. This paper presents an integrated web-based system, “The Green Trace,” that analyses mineral content and detects pesticide residues in fruits and vegetables using real-time image scanning rather than predefined datasets. The system allows a user to register, log in, and capture or upload an image of a fruit or vegetable through a browser interface; the captured image is processed to identify the produce, estimate key mineral values such as iron, calcium, potassium, magnesium and phosphorus, and flag the likely presence and severity of common pesticide classes, including organophosphates, pyrethroids and neonicotinoids. Results, along with a safety recommendation, are displayed to the user and stored in a MySQL-backed history log for future reference. By combining nutrient evaluation and pesticide screening within a single lightweight, dynamic-processing pipeline, the proposed system reduces dependency on manual laboratory testing, promotes food-safety awareness, and supports more sustainable, consumer-driven agricultural practices.

KEYWORDS

Food Safety Pesticide Residue Detection Mineral Content Analysis Image Processing Web-Based Scanning Sustainable Agriculture Food Quality Assessment

Cite This Article

Krithika C, Harini K K, Pradeepaa B R, Samyuktha S K, Mrs R Divya, "An Integrated System for Mineral Content Analysis and Pesticide Residue Management in Fruits and Vegetables," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 7, pp. 1-7, Jul 2026.

Full Article/Conclusion

This paper presented “The Green Trace”, a web-based system that integrates mineral-content analysis and pesticide-residue detection for fruits and vegetables using real-time image scanning and dynamic data processing rather than reliance on large predefined datasets. The system supports user authentication, image-based produce scanning, combined nutrient and pesticide-risk reporting, and persistent scan history, all delivered through a lightweight, browser-accessible interface. By bringing together two evaluations, nutrient content and pesticide safety, that are typically handled separately, the system offers a quicker and more accessible alternative to manual laboratory testing for everyday consumers. Future work can extend the system in several directions. Incorporating more advanced computer-vision and spectral-analysis models could improve the precision of both mineral estimation and pesticide-residue detection across a wider variety of produce. Connecting the system with agricultural or public-health databases could allow it to issue region-specific safety advisories, while integration with a mobile application would make the tool considerably more convenient for everyday, on-the-go use compared with a website alone. Overall, the proposed approach demonstrates a practical, scalable path toward accessible, consumer-facing food-safety and nutrition screening.

References

[1]  H. Kim and E. Omia, “Recent Advances in the Integration of Deep Learning and Spectral Analysis for Non-Destructive Quality Assessment of Fruits and Vegetables,” Journal of Biosystems Engineering, 2025. [2]  D. D. Wilson and R. L. Ray, “Organic Production of Fruits and Vegetables in the US,” Sustainability, 2025. [3]  N. Bibi and N. A. Tahrim, “Pesticide Residue Analysis and Health Risk Assessment in Vegetables from Conventional Farms in Cameron Highlands, Malaysia,” Chromatographia, 2025. [4]   F. Malhat and F. Eissa, “Pesticide Residues in Egyptian Vegetables: A Comprehensive Analysis of Compliance, Co-occurrence of Multiple Residues, and Health Risk Assessment,” Journal of Food Composition and Analysis, 2026. [5]  Tariq Masood and Zafar Ali Shah, “Soil Fertility Management and Insect Pest Dynamics in Organic Vegetable Systems of Peshawar: An Integrated Approach,” Global Research Journal of Natural Science and Technology, 2026.

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Publication Date

7/9/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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