Kai‐Wei Juang

1.5k total citations
48 papers, 1.3k citations indexed

About

Kai‐Wei Juang is a scholar working on Pollution, Plant Science and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Kai‐Wei Juang has authored 48 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Pollution, 19 papers in Plant Science and 12 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Kai‐Wei Juang's work include Heavy metals in environment (22 papers), Plant Stress Responses and Tolerance (13 papers) and Soil Geostatistics and Mapping (11 papers). Kai‐Wei Juang is often cited by papers focused on Heavy metals in environment (22 papers), Plant Stress Responses and Tolerance (13 papers) and Soil Geostatistics and Mapping (11 papers). Kai‐Wei Juang collaborates with scholars based in Taiwan, United States and China. Kai‐Wei Juang's co-authors include Dar‐Yuan Lee, Bo-Ching Chen, Hung−Yu Lai, Chien-Hui Syu, Yung‐I Lee, T. R. Ellsworth, Tzu-Huei Lin, Chunhui Yu, Zueng‐Sang Chen and Chien‐Chih Chiu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and The Science of The Total Environment.

In The Last Decade

Kai‐Wei Juang

47 papers receiving 1.2k citations

Peers

Kai‐Wei Juang

POLLU

HTM

Marija Romić Croatia

Jiachun Shi China

Chunfa Wu China

Davor Romić Croatia

Tamás Hermann Hungary

Weifang Hu China

Isdaryanto Iskandar Indonesia

Jingtao Wu China

Xiuying Zhang China

Marija Romić Croatia

Kai‐Wei Juang

770 ×1.5

POLLU

421 ×1.1

211 ×0.6

176 ×0.8

HTM

343 ×1.7

Citations per year, relative to Kai‐Wei Juang Kai‐Wei Juang (= 1×) peers Marija Romić

Countries citing papers authored by Kai‐Wei Juang

Since Specialization

Citations

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

Fields of papers citing papers by Kai‐Wei Juang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kai‐Wei Juang. 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 Kai‐Wei Juang. The network helps show where Kai‐Wei Juang may publish in the future.

Co-authorship network of co-authors of Kai‐Wei Juang

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

All Works

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20 of 20 papers shown

Juang, Kai‐Wei, et al.. (2023). Changes in soil organic carbon and nitrogen stocks in organic farming practice and abandoned tea plantation. Botanical studies. 64(1). 28–28. 3 indexed citations

Juang, Kai‐Wei, Ting‐Fen Tsai, Chien-Hui Syu, & Bo-Ching Chen. (2023). Screen for low-arsenic-risk rice varieties based on environment–genotype interactions by using GGE analysis. Environmental Geochemistry and Health. 46(1). 4–4. 3 indexed citations

Juang, Kai‐Wei, et al.. (2022). Coupling phytotoxicity and human health risk assessment to refine the soil quality standard for As in farmlands. Environmental Science and Pollution Research. 30(13). 38212–38225. 1 indexed citations

Chen, Bo-Ching, et al.. (2020). Aspects of cultivar variation in physiological traits related to Cd distribution in rice plants with a short-term stress. Botanical studies. 61(1). 27–27. 10 indexed citations

Juang, Kai‐Wei, et al.. (2020). Assessing human health risk of arsenic for rice consumption by an iron plaque based partition ratio model. The Science of The Total Environment. 763. 142973–142973. 11 indexed citations

Juang, Kai‐Wei, et al.. (2019). Effects of Copper on Root Morphology, Cations Accumulation, and Oxidative Stress of Grapevine Seedlings. Bulletin of Environmental Contamination and Toxicology. 102(6). 873–879. 18 indexed citations

Syu, Chien-Hui, et al.. (2018). Cadmium in rice grains from a field trial in relation to model parameters of Cd-toxicity and -absorption in rice seedlings. Ecotoxicology and Environmental Safety. 169. 837–847. 21 indexed citations

Chen, Bo-Ching, et al.. (2017). Nonlinear biotic ligand model for assessing alleviation effects of Ca, Mg, and K on Cd toxicity to soybean roots. Ecotoxicology. 26(7). 942–955. 11 indexed citations

Syu, Chien-Hui, et al.. (2017). Field experiment for determining lead accumulation in rice grains of different genotypes and correlation with iron oxides deposited on rhizosphere soil. The Science of The Total Environment. 610-611. 845–853. 27 indexed citations

10.

Syu, Chien-Hui, et al.. (2016). The growth and uptake of Ga and In of rice (Oryza sative L.) seedlings as affected by Ga and In concentrations in hydroponic cultures. Ecotoxicology and Environmental Safety. 135. 32–39. 25 indexed citations

11.

Juang, Kai‐Wei, Yung‐I Lee, Hung−Yu Lai, & Bo-Ching Chen. (2014). Influence of magnesium on copper phytotoxicity to and accumulation and translocation in grapevines. Ecotoxicology and Environmental Safety. 104. 36–42. 38 indexed citations

12.

Chen, Bo-Ching, et al.. (2012). Alleviation effects of magnesium on copper toxicity and accumulation in grapevine roots evaluated with biotic ligand models. Ecotoxicology. 22(1). 174–183. 32 indexed citations

13.

Juang, Kai‐Wei, et al.. (2011). Copper accumulation, translocation, and toxic effects in grapevine cuttings. Environmental Science and Pollution Research. 19(4). 1315–1322. 51 indexed citations

14.

Juang, Kai‐Wei, Hung−Yu Lai, & Bo-Ching Chen. (2011). Coupling bioaccumulation and phytotoxicity to predict copper removal by switchgrass grown hydroponically. Ecotoxicology. 20(4). 827–835. 18 indexed citations

15.

Juang, Kai‐Wei, et al.. (2011). Short-term effects of compost amendment on the fractionation of cadmium in soil and cadmium accumulation in rice plants. Environmental Science and Pollution Research. 19(5). 1696–1708. 46 indexed citations

16.

Lin, Tzu-Huei, et al.. (2008). The effectiveness of ferrous iron and sodium dithionite for decreasing resin-extractable Cr(VI) in Cr(VI)-spiked alkaline soils. Journal of Hazardous Materials. 164(2-3). 510–516. 34 indexed citations

17.

Lee, Dar‐Yuan, et al.. (2008). PHYTOTOXICITY OF SOIL TRIVALENT CHROMIUM TO WHEAT SEEDLINGS EVALUATED BY CHELATING RESIN EXTRACTION METHOD. Soil Science. 173(9). 638–648. 6 indexed citations

18.

Juang, Kai‐Wei, et al.. (2007). Additional sampling based on regulation threshold and kriging variance to reduce the probability of false delineation in a contaminated site. The Science of The Total Environment. 389(1). 20–28. 34 indexed citations

19.

Juang, Kai‐Wei, et al.. (2003). Using sequential indicator simulation to assess the uncertainty of delineating heavy-metal contaminated soils. Environmental Pollution. 127(2). 229–238. 135 indexed citations

20.

Juang, Kai‐Wei & Dar‐Yuan Lee. (1998). A Comparison of Three Kriging Methods Using Auxiliary Variables in Heavy‐Metal Contaminated Soils. Journal of Environmental Quality. 27(2). 355–363. 46 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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