Seong Heo

838 total citations · 1 hit paper
27 papers, 460 citations indexed

About

Seong Heo is a scholar working on Plant Science, Molecular Biology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Seong Heo has authored 27 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Plant Science, 6 papers in Molecular Biology and 6 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Seong Heo's work include Plant Physiology and Cultivation Studies (8 papers), Horticultural and Viticultural Research (7 papers) and Postharvest Quality and Shelf Life Management (4 papers). Seong Heo is often cited by papers focused on Plant Physiology and Cultivation Studies (8 papers), Horticultural and Viticultural Research (7 papers) and Postharvest Quality and Shelf Life Management (4 papers). Seong Heo collaborates with scholars based in South Korea, United States and India. Seong Heo's co-authors include Yong Suk Chung, E. M. B. M. Karunathilake, Anh Tuan Le, Sheikh Mansoor, Steven Kim, Yoon-Ha Kim, Chae‐In Na, Woo Taek Kim, Young Sam Seo and Daeil Kim and has published in prestigious journals such as Nature Communications, Frontiers in Plant Science and Postharvest Biology and Technology.

In The Last Decade

Seong Heo

25 papers receiving 429 citations

Hit Papers

The Path to Smart Farming: Innovations and Opportunities ... 2023 2026 2024 2025 2023 100 200 300
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.

  1. The Path to Smart Farming: Innovations and Opportunities in Precision Agriculture
    2023 334 citations E. M. B. M. Karunathilake, Anh Tuan Le et al. Agriculture profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Seong Heo South Korea 6 284 59 36 33 29 27 460
Komal Sharma India 13 244 0.9× 31 0.5× 36 1.0× 23 0.7× 20 0.7× 56 667
Anh Tuan Le South Korea 4 228 0.8× 57 1.0× 22 0.6× 27 0.8× 25 0.9× 17 376
Chris Cavalaris Greece 10 268 0.9× 114 1.9× 21 0.6× 69 2.1× 41 1.4× 24 555
Fatemeh Kalantari Malaysia 6 501 1.8× 61 1.0× 22 0.6× 44 1.3× 62 2.1× 16 749
K P Ragunath India 8 227 0.8× 63 1.1× 11 0.3× 24 0.7× 46 1.6× 48 451
Anna Vatsanidou Greece 8 196 0.7× 55 0.9× 10 0.3× 59 1.8× 22 0.8× 17 386
D Muthumanickam India 4 208 0.7× 48 0.8× 10 0.3× 27 0.8× 35 1.2× 33 414
Borja Espejo-García Greece 15 540 1.9× 182 3.1× 28 0.8× 53 1.6× 54 1.9× 24 765
Faisal Rasheed Lone India 5 276 1.0× 57 1.0× 10 0.3× 44 1.3× 20 0.7× 10 438
Pingzeng Liu China 11 157 0.6× 25 0.4× 19 0.5× 20 0.6× 28 1.0× 45 374

Countries citing papers authored by Seong Heo

Since Specialization
Citations

This map shows the geographic impact of Seong Heo'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 Seong Heo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seong Heo more than expected).

Fields of papers citing papers by Seong Heo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seong Heo. 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 Seong Heo. The network helps show where Seong Heo may publish in the future.

Co-authorship network of co-authors of Seong Heo

This figure shows the co-authorship network connecting the top 25 collaborators of Seong Heo. A scholar is included among the top collaborators of Seong Heo 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 Seong Heo. Seong Heo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kim, Steven & Seong Heo. (2025). Effects of genotype-by-environment and analysis of potential management interaction on vase life in cut lisianthus. Frontiers in Plant Science. 16. 1578100–1578100. 1 indexed citations
2.
3.
Heo, Seong, et al.. (2024). Classification of Vase Life Day Based on Petal Colorimetric Data in Cut Lisianthus Using AutoML. Horticulturae. 10(10). 1033–1033. 2 indexed citations
4.
Heo, Seong, et al.. (2024). Predicting Vase Life of Cut Lisianthus Based on Biomass-Related Characteristics Using AutoML. Agriculture. 14(9). 1543–1543. 4 indexed citations
5.
Kim, Steven & Seong Heo. (2024). An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture. Nature Communications. 15(1). 1561–1561. 34 indexed citations
6.
Kim, Steven, et al.. (2023). ShinyCore: An R/Shiny program for establishing core collection based on single nucleotide polymorphism data. Plant Methods. 19(1). 106–106. 2 indexed citations
7.
Karunathilake, E. M. B. M., Anh Tuan Le, Seong Heo, Yong Suk Chung, & Sheikh Mansoor. (2023). The Path to Smart Farming: Innovations and Opportunities in Precision Agriculture. Agriculture. 13(8). 1593–1593. 334 indexed citations breakdown →
8.
9.
Khan, Mudasir Hafiz, et al.. (2023). Plant Growth Hormones and Micro-Tuberization in Breaking the Seed Dormancy of Bunium persicum (Boiss.) Fedts. Plants. 12(17). 3163–3163. 1 indexed citations
10.
Chung, Yong Suk, et al.. (2022). Classification of Tree Composition in the Forest Using Images from SENTINEL-2: A Case Study of Geomunoreum Forests Using NDVI Images. Applied Sciences. 13(1). 303–303. 2 indexed citations
11.
12.
Chung, Yong Suk, et al.. (2020). Image-Based Machine Learning Characterizes Root Nodule in Soybean Exposed to Silicon. Frontiers in Plant Science. 11. 520161–520161. 20 indexed citations
13.
Heo, Seong & Yong Suk Chung. (2019). Validation of MADS-box genes from apple fruit pedicels during early fruit abscission by transcriptome analysis and real-time PCR. Genes & Genomics. 41(11). 1241–1251. 6 indexed citations
14.
Heo, Seong. (2019). Changes in Chemical Properties of Greenhouse Soils Collected from Ganghwa. Korean Journal of Soil Science and Fertilizer. 52(3). 226–234. 2 indexed citations
15.
Heo, Seong, et al.. (2015). Classification of apple genetic resources using early fruit abscission pattern.. Journal of American Pomological Society. 69(2). 102–108. 2 indexed citations
16.
Heo, Seong, et al.. (2010). Analysis of genetic diversity of apple cultivars using RAPD and SSR markers.. Korean Journal of Breeding Science. 42(5). 525–533. 4 indexed citations
17.
Heo, Seong, et al.. (2010). Identifying genes related with self-thinning characteristics in apple by differential display PCR.. Korean Journal of Breeding Science. 42(5). 565–573. 1 indexed citations
18.
Kim, Jeong-Hee, et al.. (2009). Analysis of Genetic Relationships of Grapevine Cultivars (Vitis ssp.) in Korea Using RAPD Markers. Korean Journal of Breeding Science. 41(4). 437–443. 1 indexed citations
19.
Kim, Jeong-Hee, et al.. (2009). Analysis of genetic relationship of pear (Pyrus spp.) germplasms using AFLP matters.. Korean Journal of Breeding Science. 41(4). 444–450. 1 indexed citations
20.
Seo, Young Sam, et al.. (2008). Structure and expression of MdFBCP1, encoding an F-box-containing protein 1, during Fuji apple (Malus domestica Borkh.) fruit ripening. Plant Cell Reports. 27(8). 1291–1301. 10 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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