Dilip Jat

672 total citations
25 papers, 424 citations indexed

About

Dilip Jat is a scholar working on Plant Science, Ecology and Analytical Chemistry. According to data from OpenAlex, Dilip Jat has authored 25 papers receiving a total of 424 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Plant Science, 7 papers in Ecology and 7 papers in Analytical Chemistry. Recurrent topics in Dilip Jat's work include Smart Agriculture and AI (13 papers), Spectroscopy and Chemometric Analyses (7 papers) and Remote Sensing in Agriculture (6 papers). Dilip Jat is often cited by papers focused on Smart Agriculture and AI (13 papers), Spectroscopy and Chemometric Analyses (7 papers) and Remote Sensing in Agriculture (6 papers). Dilip Jat collaborates with scholars based in India and United States. Dilip Jat's co-authors include Narendra Singh Chandel, Yogesh Anand Rajwade, Kumkum Dubey, Subir Kumar Chakraborty, A. Subeesh, Mukesh Tiwari, Satya Prakash Kumar, K. V. Ramana Rao, Kuldeep Singh and Deepak Kumar and has published in prestigious journals such as Field Crops Research, Computers and Electronics in Agriculture and Neural Computing and Applications.

In The Last Decade

Dilip Jat

21 papers receiving 412 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dilip Jat India 10 332 121 89 32 29 25 424
Hongbao Ye China 10 243 0.7× 102 0.8× 71 0.8× 38 1.2× 17 0.6× 24 356
Kumkum Dubey India 10 227 0.7× 84 0.7× 59 0.7× 29 0.9× 25 0.9× 19 306
Lie Deng China 13 372 1.1× 77 0.6× 139 1.6× 31 1.0× 36 1.2× 46 550
Narendra Singh Chandel India 14 484 1.5× 172 1.4× 121 1.4× 43 1.3× 49 1.7× 41 645
Khadijeh Alibabaei Portugal 9 212 0.6× 58 0.5× 43 0.5× 34 1.1× 36 1.2× 17 327
Md Nasim Reza South Korea 12 265 0.8× 89 0.7× 42 0.5× 55 1.7× 14 0.5× 63 441
Abhilash K. Chandel United States 15 370 1.1× 172 1.4× 64 0.7× 68 2.1× 38 1.3× 45 507
Walter Maldonado Brazil 9 230 0.7× 58 0.5× 49 0.6× 36 1.1× 46 1.6× 23 334
Anil Bhujel South Korea 12 263 0.8× 52 0.4× 57 0.6× 35 1.1× 24 0.8× 20 481
Zhihao Liu China 7 311 0.9× 62 0.5× 91 1.0× 30 0.9× 15 0.5× 15 474

Countries citing papers authored by Dilip Jat

Since Specialization
Citations

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

Fields of papers citing papers by Dilip Jat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dilip Jat

This figure shows the co-authorship network connecting the top 25 collaborators of Dilip Jat. A scholar is included among the top collaborators of Dilip Jat 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 Dilip Jat. Dilip Jat 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.
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
2.
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
3.
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
4.
Rajwade, Yogesh Anand, et al.. (2023). Assessment of water stress in rainfed maize using RGB and thermal imagery. Arabian Journal of Geosciences. 16(2). 11 indexed citations
5.
Chakraborty, Subir Kumar, A. Subeesh, Kumkum Dubey, et al.. (2023). Development of an optimally designed real-time automatic citrus fruit grading–sorting machine leveraging computer vision-based adaptive deep learning model. Engineering Applications of Artificial Intelligence. 120. 105826–105826. 42 indexed citations
6.
7.
8.
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
9.
Singh, Dushyant, et al.. (2022). Metallurgical Requirements of Soil Engaging Component under Conservation Agriculture Practices. Journal of Agricultural Engineering (India). 59(4). 1 indexed citations
10.
Chandel, Abhilash K., Narendra Singh Chandel, Kumkum Dubey, et al.. (2022). State-of-the-art computer vision techniques for automated sugarcane lodging classification. Field Crops Research. 291. 108797–108797. 13 indexed citations
11.
Chakraborty, Subir Kumar, Narendra Singh Chandel, Dilip Jat, et al.. (2022). Deep learning approaches and interventions for futuristic engineering in agriculture. Neural Computing and Applications. 34(23). 20539–20573. 39 indexed citations
12.
Chandel, Narendra Singh, et al.. (2021). Indices for comparative performance evaluation of seed drills. 1 indexed citations
13.
Jat, Dilip, et al.. (2020). Performance of pneumatic loader for loose straw handling on a farm yard. Range Management and Agroforestry. 41(1). 116–125. 2 indexed citations
14.
Chandel, Narendra Singh, et al.. (2020). Canopy spectral reflectance for crop water stress assessment in wheat (Triticum aestivum, L.)*. Irrigation and Drainage. 70(2). 321–331. 13 indexed citations
15.
Chandel, Narendra Singh, Subir Kumar Chakraborty, Yogesh Anand Rajwade, et al.. (2020). Identifying crop water stress using deep learning models. Neural Computing and Applications. 33(10). 5353–5367. 106 indexed citations
16.
Jat, Dilip, Yogesh Anand Rajwade, Narendra Singh Chandel, Kumkum Dubey, & K. V. Ramana Rao. (2019). Embedded system for regulating abiotic parameters for Capsicum cultivation in a polyhouse with comparison to open-field cultivation. International Journal of Vegetable Science. 26(5). 487–497. 5 indexed citations
17.
Saha, Krishna Pada, Dushyant Singh, Dilip Jat, & Karan Singh. (2018). Performance Evaluation of Tractor Operated Rotary Assisted Broad Bed Former-cum-seeder for Wheat Sowing. Journal of Agricultural Engineering (India). 55(3). 1–11.
18.
Singh, Karan, et al.. (2018). Assessment of Engineering Properties of Proso Millet (Panicum miliaceum). Journal of Agricultural Engineering (India). 55(2). 42–51. 4 indexed citations
19.
Jat, Dilip, et al.. (2017). Effect of two stage fertilizer application on growth and yield of soybean crop in permanent broad beds. Bhartiya Krishi Anusandhan Patrika. 32(1). 19–22.
20.
Singh, Kishan, et al.. (2016). Design, development and evaluation of furrow opener for differential depth fertilizer application. The Indian Journal of Agricultural Sciences. 86(2). 6 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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