Manuel Marcaida

990 total citations
10 papers, 305 citations indexed

About

Manuel Marcaida is a scholar working on Plant Science, Environmental Engineering and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Manuel Marcaida has authored 10 papers receiving a total of 305 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Plant Science, 4 papers in Environmental Engineering and 3 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Manuel Marcaida's work include Rice Cultivation and Yield Improvement (6 papers), Remote Sensing in Agriculture (3 papers) and Remote Sensing and LiDAR Applications (3 papers). Manuel Marcaida is often cited by papers focused on Rice Cultivation and Yield Improvement (6 papers), Remote Sensing in Agriculture (3 papers) and Remote Sensing and LiDAR Applications (3 papers). Manuel Marcaida collaborates with scholars based in United States, Philippines and China. Manuel Marcaida's co-authors include Tao Li, Olivyn Angeles, Ando M. Radanielson, Samarendu Mohanty, Anitha Raman, Arvind Kumar, Jauhar Ali, Zhikang Li, Jianlong Xu and Yongming Gao and has published in prestigious journals such as PLoS ONE, Climatic Change and Agricultural and Forest Meteorology.

In The Last Decade

Manuel Marcaida

9 papers receiving 296 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Manuel Marcaida United States 6 237 157 54 51 49 10 305
Xiu Yang China 8 207 0.9× 88 0.6× 24 0.4× 37 0.7× 61 1.2× 14 321
Eric J. Zurcher Australia 5 128 0.5× 119 0.8× 76 1.4× 91 1.8× 63 1.3× 9 277
Shuang Sun China 12 251 1.1× 196 1.2× 153 2.8× 68 1.3× 91 1.9× 25 382
Chenyao Yang Portugal 10 232 1.0× 110 0.7× 53 1.0× 51 1.0× 127 2.6× 25 341
Maman Garba Niger 10 109 0.5× 90 0.6× 61 1.1× 118 2.3× 41 0.8× 24 294
Asmat Ullah Pakistan 8 195 0.8× 109 0.7× 72 1.3× 49 1.0× 66 1.3× 14 300
K. Pannangpetch Thailand 12 282 1.2× 106 0.7× 108 2.0× 62 1.2× 55 1.1× 24 355
Dipankar Barman India 8 220 0.9× 74 0.5× 59 1.1× 36 0.7× 42 0.9× 17 298
Zongzheng Yan China 8 286 1.2× 56 0.4× 95 1.8× 107 2.1× 68 1.4× 13 396
A. Ferrer Philippines 7 283 1.2× 161 1.0× 53 1.0× 80 1.6× 41 0.8× 9 356

Countries citing papers authored by Manuel Marcaida

Since Specialization
Citations

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

Fields of papers citing papers by Manuel Marcaida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manuel Marcaida

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

All Works

10 of 10 papers shown
1.
Marcaida, Manuel, et al.. (2025). Implication of soil grid sampling on lime, phosphorus, and potassium management of corn. Agronomy Journal. 117(3).
2.
Marcaida, Manuel, et al.. (2024). Exploring the Use of High-Resolution Satellite Images to Estimate Corn Silage Yield Within Field. Remote Sensing. 16(21). 4081–4081. 2 indexed citations
3.
Sunoj, S., et al.. (2024). Corn grain and silage yield class prediction for zone delineation using high-resolution satellite imagery. Agricultural Systems. 218. 104009–104009. 2 indexed citations
4.
Sunoj, S., et al.. (2023). Maize grain and silage yield prediction of commercial fields using high-resolution UAS imagery. Biosystems Engineering. 235. 137–149. 7 indexed citations
5.
Marcaida, Manuel, Lyda Hok, Gordon W. Holtgrieve, et al.. (2021). A spatio-temporal analysis of rice production in Tonle Sap floodplains in response to changing hydrology and climate. Agricultural Water Management. 258. 107183–107183. 4 indexed citations
6.
Li, Tao, et al.. (2017). From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments. Agricultural and Forest Meteorology. 237-238. 246–256. 152 indexed citations
7.
Li, Tao, Jauhar Ali, Manuel Marcaida, et al.. (2016). Combining Limited Multiple Environment Trials Data with Crop Modeling to Identify Widely Adaptable Rice Varieties. PLoS ONE. 11(10). e0164456–e0164456. 20 indexed citations
8.
Li, Tao, et al.. (2015). Drought stress impacts of climate change on rainfed rice in South Asia. Climatic Change. 133(4). 709–720. 49 indexed citations
9.
Marcaida, Manuel, Tao Li, Olivyn Angeles, et al.. (2014). Biomass accumulation and partitioning of newly developed Green Super Rice (GSR) cultivars under drought stress during the reproductive stage. Field Crops Research. 162. 30–38. 28 indexed citations
10.
Li, Tao, Anitha Raman, Manuel Marcaida, et al.. (2013). Simulation of genotype performances across a larger number of environments for rice breeding using ORYZA2000. Field Crops Research. 149. 312–321. 41 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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