Kirk Howatt

1.2k total citations · 1 hit paper
45 papers, 846 citations indexed

About

Kirk Howatt is a scholar working on Plant Science, Molecular Biology and Analytical Chemistry. According to data from OpenAlex, Kirk Howatt has authored 45 papers receiving a total of 846 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Plant Science, 11 papers in Molecular Biology and 11 papers in Analytical Chemistry. Recurrent topics in Kirk Howatt's work include Weed Control and Herbicide Applications (21 papers), Smart Agriculture and AI (18 papers) and Spectroscopy and Chemometric Analyses (11 papers). Kirk Howatt is often cited by papers focused on Weed Control and Herbicide Applications (21 papers), Smart Agriculture and AI (18 papers) and Spectroscopy and Chemometric Analyses (11 papers). Kirk Howatt collaborates with scholars based in United States, China and Canada. Kirk Howatt's co-authors include Xin Sun, Cengiz Koparan, Michael Ostlie, C. Igathinathane, Billy G. Ram, Yu Zhang, Philip Westra, Peter G. Oduor, Mohammed Raju Ahmed and David A. Mortensen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Agricultural and Food Chemistry and Food Chemistry.

In The Last Decade

Kirk Howatt

43 papers receiving 801 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.

A systematic review of hyperspectral imaging in precision agriculture: Analysis of its current state and future prospects

2024 95 citations Billy G. Ram, C. Igathinathane et al. Computers and Electronics in Agriculture profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kirk Howatt United States	15	688	129	129	123	102	45	846
Shaun M. Sharpe United States	16	796 1.2×	66 0.5×	106 0.8×	121 1.0×	53 0.5×	58	892
Gerassimos G. Peteinatos Germany	20	1.0k 1.5×	57 0.4×	81 0.6×	199 1.6×	167 1.6×	44	1.2k
Nathan S. Boyd United States	25	1.6k 2.4×	99 0.8×	114 0.9×	191 1.6×	365 3.6×	141	1.9k
Lutz Damerow Germany	20	768 1.1×	25 0.2×	154 1.2×	129 1.0×	25 0.2×	72	1.1k
Jun Ni China	17	540 0.8×	26 0.2×	139 1.1×	396 3.2×	63 0.6×	59	868
Jianye Huang China	16	730 1.1×	82 0.6×	30 0.2×	44 0.4×	76 0.7×	63	1.1k
Huizhe Chen China	19	778 1.1×	27 0.2×	43 0.3×	51 0.4×	116 1.1×	64	989
R. N. Edmondson United Kingdom	17	487 0.7×	125 1.0×	20 0.2×	46 0.4×	47 0.5×	38	822
Angelo Petrozza Italy	18	958 1.4×	19 0.1×	92 0.7×	111 0.9×	39 0.4×	43	1.3k

Countries citing papers authored by Kirk Howatt

Since Specialization

Citations

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

Fields of papers citing papers by Kirk Howatt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kirk Howatt

This figure shows the co-authorship network connecting the top 25 collaborators of Kirk Howatt. A scholar is included among the top collaborators of Kirk Howatt 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 Kirk Howatt. Kirk Howatt 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

Igathinathane, C., et al.. (2025). A practical guide to UAV-based weed identification in soybean: Comparing RGB and multispectral sensor performance. Journal of Agriculture and Food Research. 20. 101784–101784.

Howatt, Kirk, et al.. (2025). Edge-deployable segmentation and prescription mapping of post-emergence weeds in sugar beet crops for UAV-based precision spraying. Journal of Agriculture and Food Research. 24. 102422–102422. 1 indexed citations

Das, Sanjoy, et al.. (2025). Multiclass weed and crop detection using optimized YOLO models on edge devices. Journal of Agriculture and Food Research. 22. 102144–102144. 1 indexed citations

Howatt, Kirk, et al.. (2025). Weed-crop dataset in precision agriculture: Resource for AI-based robotic weed control systems. Data in Brief. 60. 111486–111486. 2 indexed citations

Geddes, Charles M., et al.. (2025). Protoporphyrinogen oxidase (PPO)-inhibitor resistance in kochia (Bassia scoparia). Weed Science. 73. 1 indexed citations

Ram, Billy G., et al.. (2025). Addressing computation resource exhaustion associated with deep learning training of three-dimensional hyperspectral images using multiclass weed classification. Artificial Intelligence in Agriculture. 15(2). 131–146. 1 indexed citations

Zhang, Yu, et al.. (2024). Field-based multispecies weed and crop detection using ground robots and advanced YOLO models: A data and model-centric approach. SHILAP Revista de lepidopterología. 9. 100538–100538. 12 indexed citations

Zhang, Yu, et al.. (2024). Multi-Species Weed and Crop Classification Comparison Using Five Different Deep Learning Network Architectures. Journal of the ASABE. 67(2). 275–287. 4 indexed citations

Zhang, Yu, Cengiz Koparan, Nitin Rai, et al.. (2024). Advances in ground robotic technologies for site-specific weed management in precision agriculture: A review. Computers and Electronics in Agriculture. 225. 109363–109363. 45 indexed citations

10.

Koparan, Cengiz, et al.. (2024). A novel automated cloud-based image datasets for high throughput phenotyping in weed classification. Data in Brief. 57. 111097–111097. 1 indexed citations

11.

Koparan, Cengiz, Yu Zhang, Kirk Howatt, et al.. (2024). Evaluation of Dicamba Drift Injury and Yield Loss on Soybean Using Small Unmanned Aircraft Systems (sUAS) and Multispectral Imaging Technologies. 2(2). 63–76. 2 indexed citations

12.

Ram, Billy G., Yu Zhang, Cristiano André da Costa, et al.. (2023). Palmer amaranth identification using hyperspectral imaging and machine learning technologies in soybean field. Computers and Electronics in Agriculture. 215. 108444–108444. 17 indexed citations

13.

Rai, Nitin, et al.. (2023). Multi-format open-source weed image dataset for real-time weed identification in precision agriculture. Data in Brief. 51. 109691–109691. 13 indexed citations

14.

Rai, Nitin, Yu Zhang, María B. Villamil, et al.. (2023). Agricultural weed identification in images and videos by integrating optimized deep learning architecture on an edge computing technology. Computers and Electronics in Agriculture. 216. 108442–108442. 49 indexed citations

15.

Costa, Cristiano André da, Kirk Howatt, Billy G. Ram, et al.. (2022). Palmer Amaranth (Amaranthus palmeri S. Watson) and Soybean (Glycine max L.) Classification in Greenhouse Using Hyperspectral Imaging and Chemometrics Methods. Journal of the ASABE. 65(1). 179–188. 2 indexed citations

16.

Koparan, Cengiz, et al.. (2021). UAV-Assisted Thermal Infrared and Multispectral Imaging of Weed Canopies for Glyphosate Resistance Detection. Remote Sensing. 13(22). 4606–4606. 24 indexed citations

17.

Malalgoda, Maneka, Jae‐Bom Ohm, Kirk Howatt, Andrew Green, & Şenay Şimşek. (2020). Effects of pre-harvest glyphosate use on protein composition and shikimic acid accumulation in spring wheat. Food Chemistry. 332. 127422–127422. 14 indexed citations

18.

Shirzadifar, Alimohammad, Sreekala G. Bajwa, Seyed Ahmad Mireei, Kirk Howatt, & John Nowatzki. (2018). Weed species discrimination based on SIMCA analysis of plant canopy spectral data. Biosystems Engineering. 171. 143–154. 38 indexed citations

19.

Howatt, Kirk, Philip Westra, & Scott J. Nissen. (2006). Ethylene effect on kochia (Kochia scoparia) and emission following dicamba application. Weed Science. 54(1). 31–37. 10 indexed citations

20.

Howatt, Kirk, et al.. (2005). Rimsulfuron Controls Hairy Nightshade, but not Eastern Black Nightshade, in Tomato. HortScience. 40(7). 2076–2079. 3 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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