Matthew M. Conley

1.7k total citations · 1 hit paper
30 papers, 1.3k citations indexed

About

Matthew M. Conley is a scholar working on Plant Science, Global and Planetary Change and Ecology. According to data from OpenAlex, Matthew M. Conley has authored 30 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Plant Science, 14 papers in Global and Planetary Change and 13 papers in Ecology. Recurrent topics in Matthew M. Conley's work include Plant Water Relations and Carbon Dynamics (14 papers), Greenhouse Technology and Climate Control (11 papers) and Remote Sensing in Agriculture (9 papers). Matthew M. Conley is often cited by papers focused on Plant Water Relations and Carbon Dynamics (14 papers), Greenhouse Technology and Climate Control (11 papers) and Remote Sensing in Agriculture (9 papers). Matthew M. Conley collaborates with scholars based in United States, Canada and China. Matthew M. Conley's co-authors include Bruce A. Kimball, Jeffrey W. White, Gerard W. Wall, Kelly R. Thorp, Andrew N. French, Douglas J. Hunsaker, Pedro Andrade-Sánchez, Jack A. Morgan, Xingwu Lin and K. F. Bronson and has published in prestigious journals such as SHILAP Revista de lepidopterología, New Phytologist and Global Change Biology.

In The Last Decade

Matthew M. Conley

27 papers receiving 1.3k citations

Hit Papers

Field-based phenomics for plant genetics research 2012 2026 2016 2021 2012 100 200 300 400
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.

  1. Field-based phenomics for plant genetics research
    2012 429 citations Jeffrey W. White, Pedro Andrade-Sánchez et al. Field Crops Research profile →

Peers

Matthew M. Conley
Olga M. Grant United Kingdom
Llorenç Cabrera‐Bosquet France
Mats Høglind Norway
Michaël Chelle France
G. S. Zhou China
Carla Cesaraccio Italy
Tom De Swaef Belgium
Gemma Molero Mexico
Matthew E. Gilbert United States
Delphine Luquet France
Olga M. Grant United Kingdom
Matthew M. Conley
Citations per year, relative to Matthew M. Conley Matthew M. Conley (= 1×) peers Olga M. Grant

Countries citing papers authored by Matthew M. Conley

Since Specialization
Citations

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

Fields of papers citing papers by Matthew M. Conley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew M. Conley. 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 Matthew M. Conley. The network helps show where Matthew M. Conley may publish in the future.

Co-authorship network of co-authors of Matthew M. Conley

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew M. Conley. A scholar is included among the top collaborators of Matthew M. Conley 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 Matthew M. Conley. Matthew M. Conley 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.
Conley, Matthew M., et al.. (2025). Impacts of Nitrogen Fertilization on Hybrid Bermudagrass During Deficit Irrigation. SHILAP Revista de lepidopterología. 4(2). 25–25.
2.
Conley, Matthew M., et al.. (2024). Mowing Height Effects on ‘TifTuf’ Bermudagrass during Deficit Irrigation. Agronomy. 14(3). 628–628. 4 indexed citations
3.
Williams, Clinton F., et al.. (2023). Hybrid Bermudagrass Responses to Impaired Water Sources. HortScience. 58(8). 907–914. 3 indexed citations
4.
5.
Thompson, Alison L., Kelly R. Thorp, Matthew M. Conley, & Duke Pauli. (2023). A proximal sensing cart and custom cooling box for improved hyperspectral sensing in a desert environment. Frontiers in Agronomy. 5. 3 indexed citations
6.
Thompson, Alison L., et al.. (2022). Response of upland cotton (Gossypium hirsutum L.) leaf chlorophyll content to high heat and low-soil water in the Arizona low desert. Photosynthetica. 60(2). 280–292. 9 indexed citations
7.
8.
Thompson, Alison L., et al.. (2020). A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system. Plant Methods. 16(1). 97–97. 8 indexed citations
9.
Bronson, K. F., Andrew N. French, Matthew M. Conley, & Edward M. Barnes. (2020). Use of an ultrasonic sensor for plant height estimation in irrigated cotton. Agronomy Journal. 113(2). 2175–2183. 15 indexed citations
10.
Bronson, K. F., Matthew M. Conley, Andrew N. French, et al.. (2020). Which active optical sensor vegetation index is best for nitrogen assessment in irrigated cotton?. Agronomy Journal. 112(3). 2205–2218. 11 indexed citations
11.
Thompson, Alison L., Kelly R. Thorp, Matthew M. Conley, et al.. (2019). Comparing Nadir and Multi-Angle View Sensor Technologies for Measuring in-Field Plant Height of Upland Cotton. Remote Sensing. 11(6). 700–700. 31 indexed citations
12.
Thompson, Alison L., Kelly R. Thorp, Matthew M. Conley, et al.. (2018). Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping. Frontiers in Plant Science. 9. 507–507. 28 indexed citations
13.
Thompson, Alison L., et al.. (2018). Professor: A motorized field-based phenotyping cart. HardwareX. 4. e00025–e00025. 11 indexed citations
14.
Pauli, Duke, Jeffrey W. White, Pedro Andrade-Sánchez, et al.. (2017). Investigation of the Influence of Leaf Thickness on Canopy Reflectance and Physiological Traits in Upland and Pima Cotton Populations. Frontiers in Plant Science. 8. 1405–1405. 31 indexed citations
15.
Bronson, K. F., D. J. Hunsaker, Jarai Mon, et al.. (2017). Improving Nitrogen Fertilizer Use Efficiency in Surface‐ and Overhead Sprinkler‐Irrigated Cotton in the Desert Southwest. Soil Science Society of America Journal. 81(6). 1401–1412. 19 indexed citations
16.
White, Jeffrey W., Pedro Andrade-Sánchez, Michael A. Gore, et al.. (2012). Field-based phenomics for plant genetics research. Field Crops Research. 133. 101–112. 429 indexed citations breakdown →
17.
Kimball, Bruce A., Matthew M. Conley, & Keith F. Lewin. (2011). Performance and energy costs associated with scaling infrared heater arrays for warming field plots from 1 to 100 m. Theoretical and Applied Climatology. 108(1-2). 247–265. 26 indexed citations
18.
Grant, R. F., Bruce A. Kimball, Gerard W. Wall, et al.. (2004). Modeling Elevated Carbon Dioxide Effects on Water Relations, Water Use, and Growth of Irrigated Sorghum. Agronomy Journal. 96(6). 1693–1705. 17 indexed citations
19.
Triggs, J., Bruce A. Kimball, Paul J. Pinter, et al.. (2004). Free-air CO2 enrichment effects on the energy balance and evapotranspiration of sorghum. Agricultural and Forest Meteorology. 124(1-2). 63–79. 64 indexed citations
20.
Kimball, Bruce A., Michael J. Ottman, Paul J. Pinter, et al.. (1994). Data from the Arizona FACE (Free-Air CO2 Enrichment) Experiments on Sorghum at Ample and Limiting Levels of Water Supply. 7. 1–10. 1 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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