Mariia Pukalchik

652 total citations
31 papers, 461 citations indexed

About

Mariia Pukalchik is a scholar working on Plant Science, Pollution and Soil Science. According to data from OpenAlex, Mariia Pukalchik has authored 31 papers receiving a total of 461 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Plant Science, 7 papers in Pollution and 7 papers in Soil Science. Recurrent topics in Mariia Pukalchik's work include Smart Agriculture and AI (10 papers), Heavy metals in environment (5 papers) and Spectroscopy and Chemometric Analyses (5 papers). Mariia Pukalchik is often cited by papers focused on Smart Agriculture and AI (10 papers), Heavy metals in environment (5 papers) and Spectroscopy and Chemometric Analyses (5 papers). Mariia Pukalchik collaborates with scholars based in Russia, Czechia and India. Mariia Pukalchik's co-authors include В. А. Терехова, Dmitrii Shadrin, Olga Yakimenko, Filip Mercl, Pavel Tlustoš, Kamila Kydralieva, Ivan Oseledets, Andrey Somov, Svetlana Illarionova and Maxim V. Fedorov and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Environmental Pollution.

In The Last Decade

Mariia Pukalchik

30 papers receiving 450 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mariia Pukalchik Russia 14 154 103 91 64 55 31 461
Zhaodong Liu China 16 151 1.0× 143 1.4× 120 1.3× 37 0.6× 35 0.6× 44 665
Houxi Zhang China 11 143 0.9× 87 0.8× 69 0.8× 129 2.0× 151 2.7× 19 479
Simona Mariana Popescu Romania 12 153 1.0× 66 0.6× 74 0.8× 43 0.7× 65 1.2× 32 583
Shihao Zhang China 13 149 1.0× 59 0.6× 46 0.5× 44 0.7× 140 2.5× 62 666
Leonel Ernesto Amábilis-Sosa Mexico 13 142 0.9× 81 0.8× 21 0.2× 80 1.3× 45 0.8× 39 604
Jan Popelka Czechia 16 120 0.8× 236 2.3× 87 1.0× 48 0.8× 61 1.1× 45 782
Mohammad Salehi Iran 16 174 1.1× 105 1.0× 122 1.3× 196 3.1× 60 1.1× 50 648
Vahid Khosravi Iran 14 186 1.2× 53 0.5× 45 0.5× 220 3.4× 60 1.1× 51 613
Guoxiang Sun China 15 322 2.1× 107 1.0× 66 0.7× 110 1.7× 148 2.7× 40 672

Countries citing papers authored by Mariia Pukalchik

Since Specialization
Citations

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

Fields of papers citing papers by Mariia Pukalchik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mariia Pukalchik

This figure shows the co-authorship network connecting the top 25 collaborators of Mariia Pukalchik. A scholar is included among the top collaborators of Mariia Pukalchik 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 Mariia Pukalchik. Mariia Pukalchik 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.
Jana, Raghavendra B., et al.. (2022). Bayesian Aggregation Improves Traditional Single-Image Crop Classification Approaches. Sensors. 22(22). 8600–8600. 3 indexed citations
2.
Shadrin, Dmitrii, et al.. (2022). Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data. Scientific Reports. 12(1). 6128–6128. 14 indexed citations
3.
Shadrin, Dmitrii, et al.. (2021). Optimization of Water Quality Monitoring Networks Using Metaheuristic Approaches: Moscow Region Use Case. Water. 13(7). 888–888. 13 indexed citations
4.
Illarionova, Svetlana, et al.. (2021). MixChannel: Advanced Augmentation for Multispectral Satellite Images. Remote Sensing. 13(11). 2181–2181. 19 indexed citations
5.
6.
Pukalchik, Mariia, et al.. (2021). Deep Learning for Postharvest Decay Prediction in Apples. 1–6. 7 indexed citations
7.
Shadrin, Dmitrii, et al.. (2021). Regulation-based probabilistic substance quality index and automated geo-spatial modeling for water quality assessment. Scientific Reports. 11(1). 23822–23822. 3 indexed citations
8.
9.
Shadrin, Dmitrii, et al.. (2021). Apple Trees Diseases Detection Through Computer Vision in Embedded Systems. 1–6. 5 indexed citations
10.
Shadrin, Dmitrii, et al.. (2021). Image Compression and Plants Classification Using Machine Learning in Controlled-Environment Agriculture: Antarctic Station Use Case. IEEE Sensors Journal. 21(16). 17564–17572. 32 indexed citations
11.
Shadrin, Dmitrii, et al.. (2020). Artificial intelligence models to predict acute phytotoxicity in petroleum contaminated soils. Ecotoxicology and Environmental Safety. 194. 110410–110410. 26 indexed citations
12.
Patsaeva, Svetlana V., et al.. (2020). Effect of Exogenic Humic Substances on Various Growth Endpoints of Alternaria alternata and Trichoderma harzianum in the Experimental Conditions. Waste and Biomass Valorization. 12(1). 211–222. 9 indexed citations
13.
Pukalchik, Mariia, et al.. (2019). Machine learning methods for estimation the indicators of phosphogypsum influence in soil. Journal of Soils and Sediments. 19(5). 2265–2276. 13 indexed citations
14.
Shadrin, Dmitrii, et al.. (2019). Bayesian optimization for seed germination. Plant Methods. 15(1). 43–43. 5 indexed citations
15.
Yakimenko, Olga, et al.. (2019). Comparison of Two Integrated Biotic Indices in Assessing the Effects of Humic Products in a Model Experiment. Eurasian Soil Science. 52(7). 736–746. 9 indexed citations
16.
Pukalchik, Mariia, Filip Mercl, В. А. Терехова, & Pavel Tlustoš. (2018). Biochar, wood ash and humic substances mitigating trace elements stress in contaminated sandy loam soil: Evidence from an integrative approach. Chemosphere. 203. 228–238. 43 indexed citations
17.
Pukalchik, Mariia, et al.. (2017). Using humic products as amendments to restore Zn and Pb polluted soil: a case study using rapid screening phytotest endpoint. Journal of Soils and Sediments. 18(3). 750–761. 20 indexed citations
18.
Pukalchik, Mariia, et al.. (2017). The improvement of multi-contaminated sandy loam soil chemical and biological properties by the biochar, wood ash, and humic substances amendments. Environmental Pollution. 229. 516–524. 43 indexed citations
19.
Pukalchik, Mariia, et al.. (2016). About the Use of Enzymatic Activity in Environmental Regulation in the Evaluation of the Oil-Contaminated Soils. Ecology and Industry of Russia. 20(11). 26–31. 4 indexed citations
20.
Терехова, В. А., et al.. (2014). The triad approach to ecological assessment of urban soils. Eurasian Soil Science. 47(9). 952–958. 18 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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