Information Processing in Agriculture

450 papers and 12.4k indexed citations i.

About

The 450 papers published in Information Processing in Agriculture in the last decades have received a total of 12.4k indexed citations. Papers published in Information Processing in Agriculture usually cover Plant Science (230 papers), Analytical Chemistry (79 papers) and Ecology (74 papers) specifically the topics of Smart Agriculture and AI (127 papers), Spectroscopy and Chemometric Analyses (79 papers) and Remote Sensing in Agriculture (51 papers). The most active scholars publishing in Information Processing in Agriculture are Archan Misra, V. K. Singh, Mohammad Sadegh Allahyari, Hamid El Bilali, D. Vydeki, S. Ramesh, Xi Qiao, Mohammed Abo‐Zahhad, Yadong Liu and Georgios Bartzas.

In The Last Decade

Fields of papers published in Information Processing in Agriculture

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Information Processing in Agriculture. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Information Processing in Agriculture.

Countries where authors publish in Information Processing in Agriculture

Since Specialization
Citations

This map shows the geographic impact of research published in Information Processing in Agriculture. 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 papers published in Information Processing in Agriculture with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Information Processing in Agriculture more than expected).

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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