A. Subeesh

1.6k total citations · 3 hit papers
35 papers, 862 citations indexed

About

A. Subeesh is a scholar working on Plant Science, Analytical Chemistry and Ecology. According to data from OpenAlex, A. Subeesh has authored 35 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Plant Science, 10 papers in Analytical Chemistry and 6 papers in Ecology. Recurrent topics in A. Subeesh's work include Smart Agriculture and AI (22 papers), Spectroscopy and Chemometric Analyses (9 papers) and Remote Sensing in Agriculture (6 papers). A. Subeesh is often cited by papers focused on Smart Agriculture and AI (22 papers), Spectroscopy and Chemometric Analyses (9 papers) and Remote Sensing in Agriculture (6 papers). A. Subeesh collaborates with scholars based in India, United States and Egypt. A. Subeesh's co-authors include C. R. Mehta, Narendra Singh Chandel, Dilip Jat, Nand Lal Kushwaha, Dinesh Kumar Vishwakarma, Yogesh Anand Rajwade, Subir Kumar Chakraborty, Abhishek Singh, K. V. Ramana Rao and Kumkum Dubey and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Environmental Management and Field Crops Research.

In The Last Decade

A. Subeesh

32 papers receiving 824 citations

Hit Papers

align trajectories

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.

Automation and digitization of agriculture using artificial intelligence and internet of things

2021 193 citations A. Subeesh et al. Artificial Intelligence in Agriculture profile →
Deep learning based computer vision approaches for smart agricultural applications

2022 153 citations A. Subeesh, Nand Lal Kushwaha et al. Artificial Intelligence in Agriculture profile →
Deep learning and computer vision in plant disease detection: a comprehensive review of techniques, models, and trends in precision agriculture

2025 53 citations Narendra Singh Chandel, Krishna Pratap Singh et al. Artificial Intelligence Review profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
A. Subeesh India	14	550	141	126	93	84	35	862
Xinxing Li China	17	365 0.7×	126 0.9×	117 0.9×	131 1.4×	107 1.3×	75	896
Uferah Shafi Pakistan	15	554 1.0×	126 0.9×	214 1.7×	182 2.0×	63 0.8×	18	1.2k
Nahina Islam Australia	11	386 0.7×	72 0.5×	190 1.5×	86 0.9×	56 0.7×	26	877
José Miguel Molina‐Martínez Spain	20	620 1.1×	247 1.8×	193 1.5×	145 1.6×	145 1.7×	68	1.0k
Naveed Iqbal Pakistan	10	410 0.7×	59 0.4×	176 1.4×	96 1.0×	43 0.5×	27	840
Zhongbin Su China	18	552 1.0×	133 0.9×	210 1.7×	116 1.2×	40 0.5×	71	1.1k
Sjoukje Osinga Netherlands	8	411 0.7×	87 0.6×	158 1.3×	60 0.6×	61 0.7×	19	908
Yadong Liu China	11	526 1.0×	121 0.9×	229 1.8×	134 1.4×	44 0.5×	20	860
Dhivya Elavarasan India	7	556 1.0×	132 0.9×	155 1.2×	83 0.9×	49 0.6×	8	840
Tanzeel U. Rehman United States	16	619 1.1×	255 1.8×	312 2.5×	88 0.9×	44 0.5×	46	1.1k

Countries citing papers authored by A. Subeesh

Since Specialization

Citations

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

Fields of papers citing papers by A. Subeesh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Subeesh

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Chandel, Narendra Singh, et al.. (2025). Deep learning assisted real-time nitrogen stress detection for variable rate fertilizer applicator in wheat crop. Computers and Electronics in Agriculture. 237. 110545–110545. 2 indexed citations

Chandel, Narendra Singh, Krishna Pratap Singh, Subir Kumar Chakraborty, et al.. (2025). Deep learning and computer vision in plant disease detection: a comprehensive review of techniques, models, and trends in precision agriculture. Artificial Intelligence Review. 58(3). 53 indexed citations breakdown →

Subeesh, A. & Naveen Chauhan. (2025). Deep learning based abiotic crop stress assessment for precision agriculture: A comprehensive review. Journal of Environmental Management. 381. 125158–125158. 2 indexed citations

Sehrawat, Rachna, et al.. (2025). Heat matters: role of thermal processing on millet composition, digestibility, bioaccessibility and bioavailability. European Food Research and Technology. 251(12). 4185–4213.

Subeesh, A. & Naveen Chauhan. (2025). Agricultural digital twin for smart farming: A review. SHILAP Revista de lepidopterología. 4(2). 100299–100299. 1 indexed citations

Subeesh, A., Naveen Chauhan, Narendra Singh Chandel, & Yogesh Anand Rajwade. (2025). Deep autoencoder-driven feature learning and meta-heuristic optimized machine learning modelling for crop water stress identification. Evolving Systems. 16(3).

Chandel, Narendra Singh, Subir Kumar Chakraborty, Abhilash K. Chandel, et al.. (2024). State-of-the-art AI-enabled mobile device for real-time water stress detection of field crops. Engineering Applications of Artificial Intelligence. 131. 107863–107863. 14 indexed citations

Rajwade, Yogesh Anand, Narendra Singh Chandel, Abhilash K. Chandel, et al.. (2024). Thermal–RGB Imagery and Computer Vision for Water Stress Identification of Okra (Abelmoschus esculentus L.). Applied Sciences. 14(13). 5623–5623. 3 indexed citations

Giri, Saroj Kumar, et al.. (2024). Optimization of Process Parameters for the Production of Soy Protein by Ultrafiltration Using ANN. Journal of Food Processing and Preservation. 2024. 1–10. 2 indexed citations

10.

Subeesh, A., et al.. (2024). Prediction of soil moisture using machine learning techniques: A case study of an IoT‐based irrigation system in a naturally ventilated polyhouse. Irrigation and Drainage. 73(3). 1138–1150. 4 indexed citations

11.

Subeesh, A., et al.. (2024). Implementation of IoT and Fuzzy Logic Driven Real-Time Smart Storage Monitoring System. 1–7. 2 indexed citations

12.

Mohapatra, Debabandya, et al.. (2023). Optimization of sequential ultrasound-microwave assisted extraction of polyphenols-rich concrete from tuberose flowers through modelling. Process Biochemistry. 134. 175–185. 8 indexed citations

13.

Rao, K. V. Ramana, et al.. (2023). Predictive Modelling of Reference Evapotranspiration Using Machine Learning Models Coupled with Grey Wolf Optimizer. Water. 15(5). 856–856. 14 indexed citations

14.

Rao, K. V. Ramana, et al.. (2023). Reference evapotranspiration estimation using machine learning approaches for arid and semi-arid regions of India. Climate Research. 91. 97–120. 2 indexed citations

15.

Jat, Dilip, Kumkum Dubey, Subir Kumar Chakraborty, et al.. (2023). Development of an automated mobile robotic sprayer to prevent workers' exposure of agro‐chemicals inside polyhouse. Journal of Field Robotics. 40(6). 1388–1407. 8 indexed citations

16.

Subeesh, A., et al.. (2023). Predictive modelling of sweep's specific draft using machine learning regression approaches. Soil Use and Management. 40(1). 1 indexed citations

17.

Chandel, Narendra Singh, Yogesh Anand Rajwade, Kumkum Dubey, et al.. (2022). Water Stress Identification of Winter Wheat Crop with State-of-the-Art AI Techniques and High-Resolution Thermal-RGB Imagery. Plants. 11(23). 3344–3344. 34 indexed citations

18.

Subeesh, A., Kuldeep Singh, Narendra Singh Chandel, et al.. (2022). Deep convolutional neural network models for weed detection in polyhouse grown bell peppers. Artificial Intelligence in Agriculture. 6. 47–54. 104 indexed citations

19.

Mohapatra, Debabandya, A. Subeesh, Adinath Kate, et al.. (2022). Oxidation kinetics and ANN model for shelf life estimation of pearl millet (Pennisetum glaucum L.) grains during storage. Journal of Food Processing and Preservation. 46(12). 13 indexed citations

20.

Subeesh, A., et al.. (2022). Deep learning based computer vision approaches for smart agricultural applications. Artificial Intelligence in Agriculture. 6. 211–229. 153 indexed citations breakdown →

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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