Home › Entities › academia › Detection of Salmonella Typhimurium contamination levels in fresh pork samples using electronic nose smellprints in tandem with support vector machine regression and metaheuristic optimization algorithms

Detection of Salmonella Typhimurium contamination levels in fresh pork samples using electronic nose smellprints in tandem with support vector machine regression and metaheuristic optimization algorithms

Research article (Journal of Food Science and Technology, 2020) · cited 43× · AI/ML
academia openalex:W3092858714
Press Enter · cited answer in seconds

Detection of Salmonella Typhimurium contamination levels in fresh pork samples using electronic nose smellprints in tandem with support vector machine regression and metaheuristic optimization algorithms

Summary

Detection of Salmonella Typhimurium contamination levels in fresh pork samples using electronic nose smellprints in tandem with support vector machine regression and metaheuristic optimization algorithms is a scholarly article[1].

Key Facts

  • Detection of Salmonella Typhimurium contamination levels in fresh pork samples using electronic nose smellprints in tandem with support vector machine regression and metaheuristic optimization algorithms's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Detection of Salmonella Typhimurium contamination levels in fresh pork samples using electronic nose smellprints in tandem with support vector machine regression and metaheuristic optimization algorithms. Retrieved May 24, 2026, from https://4ort.xyz/entity/detection-of-salmonella-typhimurium-contamination-levels-in-fresh-pork-samples-using-electronic-nose-smellprints-in-tand
MLA “Detection of Salmonella Typhimurium contamination levels in fresh pork samples using electronic nose smellprints in tandem with support vector machine regression and metaheuristic optimization algorithms.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/detection-of-salmonella-typhimurium-contamination-levels-in-fresh-pork-samples-using-electronic-nose-smellprints-in-tand.
BibTeX @misc{4ortxyz_detection-of-salmonella-typhimurium-contamination-levels-in-fresh-pork-samples-using-electronic-nose-smellprints-in-tand_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Detection of Salmonella Typhimurium contamination levels in fresh pork samples using electronic nose smellprints in tandem with support vector machine regression and metaheuristic optimization algorithms}}, year = {2026}, url = {https://4ort.xyz/entity/detection-of-salmonella-typhimurium-contamination-levels-in-fresh-pork-samples-using-electronic-nose-smellprints-in-tand}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Detection of Salmonella Typhimurium contamination levels in fresh pork samples using electronic nose smellprints in tandem with support vector machine regression and metaheuristic optimization algorithms — https://4ort.xyz/entity/detection-of-salmonella-typhimurium-contamination-levels-in-fresh-pork-samples-using-electronic-nose-smellprints-in-tand (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/detection-of-salmonella-typhimurium-contamination-levels-in-fresh-pork-samples-using-electronic-nose-smellprints-in-tand · Last refreshed: