Shraddha Karanth

572 total citations · 1 hit paper
14 papers, 339 citations indexed

About

Shraddha Karanth is a scholar working on Food Science, Molecular Biology and Biotechnology. According to data from OpenAlex, Shraddha Karanth has authored 14 papers receiving a total of 339 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Food Science, 6 papers in Molecular Biology and 5 papers in Biotechnology. Recurrent topics in Shraddha Karanth's work include Salmonella and Campylobacter epidemiology (8 papers), Listeria monocytogenes in Food Safety (5 papers) and Identification and Quantification in Food (4 papers). Shraddha Karanth is often cited by papers focused on Salmonella and Campylobacter epidemiology (8 papers), Listeria monocytogenes in Food Safety (5 papers) and Identification and Quantification in Food (4 papers). Shraddha Karanth collaborates with scholars based in United States, Sweden and Denmark. Shraddha Karanth's co-authors include Abani K. Pradhan, Debasmita Patra, Shuyi Feng, Jianghong Meng, Jinyao Chen, Patrick Murigu Kamau Njage, Jitendra Patel, Adel Shirmohammadi, Salina Parveen and Hsin‐Bai Yin and has published in prestigious journals such as Frontiers in Microbiology, Food Research International and LWT.

In The Last Decade

Shraddha Karanth

14 papers receiving 323 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Linking microbial contamination to food spoilage and food waste: the role of smart packaging, spoilage risk assessments, and date labeling

2023 149 citations Shraddha Karanth, Shuyi Feng et al. Frontiers in Microbiology profile →

Peers

Shraddha Karanth

FS

MB

BIOTE

PS

BE

Huaning Yu China

Jeyachchandran Visvalingam Canada

María Lorena Luna-Guevara Mexico

Arturo B. Soro Ireland

María S. Medina‐Martínez Venezuela

Kaidi Wang Canada

Suresh Menon United States

Jae‐Hyun Yoon South Korea

Nitin Dhowlaghar United States

Susana de Oliveira Elias Brazil

Huaning Yu China

Shraddha Karanth

197 ×1.3

FS

103 ×1.1

MB

70 ×1.1

BIOTE

43 ×0.8

PS

108 ×2.3

BE

Citations per year, relative to Shraddha Karanth Shraddha Karanth (= 1×) peers Huaning Yu

Countries citing papers authored by Shraddha Karanth

Since Specialization

Citations

This map shows the geographic impact of Shraddha Karanth's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shraddha Karanth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shraddha Karanth more than expected).

Fields of papers citing papers by Shraddha Karanth

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shraddha Karanth. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shraddha Karanth. The network helps show where Shraddha Karanth may publish in the future.

Co-authorship network of co-authors of Shraddha Karanth

This figure shows the co-authorship network connecting the top 25 collaborators of Shraddha Karanth. A scholar is included among the top collaborators of Shraddha Karanth based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shraddha Karanth. Shraddha Karanth is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

1.

Karanth, Shraddha, et al.. (2024). Machine learning to predict the relationship between Vibrio spp. concentrations in seawater and oysters and prevalent environmental conditions. Food Research International. 188. 114464–114464. 3 indexed citations

2.

Karanth, Shraddha & Abani K. Pradhan. (2024). Advanced data analytics and “omics” techniques to control enteric foodborne pathogens. Advances in food and nutrition research. 113. 383–422. 1 indexed citations

3.

Karanth, Shraddha, et al.. (2023). A machine learning approach to identifying Salmonella stress response genes in isolates from poultry processing. Food Research International. 175. 113635–113635. 11 indexed citations

4.

Karanth, Shraddha, Jitendra Patel, Adel Shirmohammadi, & Abani K. Pradhan. (2023). Machine learning to predict foodborne salmonellosis outbreaks based on genome characteristics and meteorological trends. Current Research in Food Science. 6. 100525–100525. 13 indexed citations

5.

Karanth, Shraddha, Shuyi Feng, Debasmita Patra, & Abani K. Pradhan. (2023). Linking microbial contamination to food spoilage and food waste: the role of smart packaging, spoilage risk assessments, and date labeling. Frontiers in Microbiology. 14. 1198124–1198124. 149 indexed citations breakdown →

6.

Karanth, Shraddha & Abani K. Pradhan. (2022). Development of a novel machine learning‐based weighted modeling approach to incorporate Salmonella enterica heterogeneity on a genetic scale in a dose–response modeling framework. Risk Analysis. 43(3). 440–450. 4 indexed citations

7.

Karanth, Shraddha, et al.. (2022). A Machine Learning Model for Food Source Attribution of Listeria monocytogenes. Pathogens. 11(6). 691–691. 31 indexed citations

8.

Karanth, Shraddha, et al.. (2022). Applications of advanced data analytic techniques in food safety and risk assessment. Current Opinion in Food Science. 48. 100937–100937. 19 indexed citations

9.

Karanth, Shraddha, et al.. (2022). Importance of artificial intelligence in evaluating climate change and food safety risk. Journal of Agriculture and Food Research. 11. 100485–100485. 30 indexed citations

10.

Karanth, Shraddha, et al.. (2021). Exploring the predictive capability of advanced machine learning in identifying severe disease phenotype in Salmonella enterica. Food Research International. 151. 110817–110817. 25 indexed citations

11.

Karanth, Shraddha, et al.. (2021). Machine learning-based predictive modeling to identify genotypic traits associated with Salmonella enterica disease endpoints in isolates from ground chicken. LWT. 154. 112701–112701. 27 indexed citations

12.

Yin, Hsin‐Bai, et al.. (2020). Effect of cultivars and irrigation waters on persistence of indicator bacteria on lettuce grown in high tunnel. Journal of Food Safety. 40(4). 5 indexed citations

13.

Chen, Jinyao, Shraddha Karanth, & Abani K. Pradhan. (2020). Quantitative microbial risk assessment for Salmonella: Inclusion of whole genome sequencing and genomic epidemiological studies, and advances in the bioinformatics pipeline. Journal of Agriculture and Food Research. 2. 100045–100045. 14 indexed citations

14.

Skariyachan, Sinosh, et al.. (2012). Structure based virtual screening of novel inhibitors against multidrug resistant superbugs. Bioinformation. 8(9). 420–425. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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