James M. McKinion

2.3k total citations
57 papers, 1.3k citations indexed

About

James M. McKinion is a scholar working on Plant Science, Soil Science and Global and Planetary Change. According to data from OpenAlex, James M. McKinion has authored 57 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Plant Science, 11 papers in Soil Science and 7 papers in Global and Planetary Change. Recurrent topics in James M. McKinion's work include Greenhouse Technology and Climate Control (17 papers), Plant responses to elevated CO2 (12 papers) and Research in Cotton Cultivation (10 papers). James M. McKinion is often cited by papers focused on Greenhouse Technology and Climate Control (17 papers), Plant responses to elevated CO2 (12 papers) and Research in Cotton Cultivation (10 papers). James M. McKinion collaborates with scholars based in United States, India and Israel. James M. McKinion's co-authors include K. Raja Reddy, Harry F. Hodges, H. F. Hodges, D. N. Baker, John J. Read, Lee Tarpley, F. D. Whisler, Jeffrey L. Willers, Johnie N. Jenkins and J. R. Lambert and has published in prestigious journals such as IEEE Transactions on Automatic Control, Agriculture Ecosystems & Environment and Journal of Environmental Quality.

In The Last Decade

James M. McKinion

52 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James M. McKinion United States 21 987 355 190 163 143 57 1.3k
Marcelo Bento Paes de Camargo Brazil 17 706 0.7× 261 0.7× 261 1.4× 291 1.8× 74 0.5× 78 1.3k
David Butler Australia 15 643 0.7× 280 0.8× 208 1.1× 135 0.8× 55 0.4× 38 1.4k
Olga M. Grant United Kingdom 18 1.0k 1.0× 566 1.6× 318 1.7× 169 1.0× 104 0.7× 32 1.4k
A.J.S. McDonald Sweden 22 1.2k 1.3× 556 1.6× 395 2.1× 276 1.7× 278 1.9× 60 1.9k
K. Schölte Netherlands 21 730 0.7× 149 0.4× 254 1.3× 70 0.4× 116 0.8× 50 1.2k
Terry A. Wheeler United States 20 1.4k 1.4× 262 0.7× 108 0.6× 151 0.9× 106 0.7× 106 1.8k
H. D. Barrs Australia 18 728 0.7× 394 1.1× 78 0.4× 164 1.0× 47 0.3× 30 961
W. Kühbauch Germany 13 754 0.8× 142 0.4× 362 1.9× 76 0.5× 62 0.4× 59 1.0k
Hilton Silveira Pinto Brazil 17 299 0.3× 219 0.6× 190 1.0× 196 1.2× 83 0.6× 53 845
D. W. Stewart Canada 23 1.6k 1.6× 322 0.9× 161 0.8× 300 1.8× 52 0.4× 46 2.0k

Countries citing papers authored by James M. McKinion

Since Specialization
Citations

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

Fields of papers citing papers by James M. McKinion

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James M. McKinion

This figure shows the co-authorship network connecting the top 25 collaborators of James M. McKinion. A scholar is included among the top collaborators of James M. McKinion 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 James M. McKinion. James M. McKinion 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.
McKinion, James M., Jeffrey L. Willers, & Johnie N. Jenkins. (2010). Comparing high density LIDAR and medium resolution GPS generated elevation data for predicting yield stability. Computers and Electronics in Agriculture. 74(2). 244–249. 7 indexed citations
2.
McKinion, James M., Jeffrey L. Willers, & Johnie N. Jenkins. (2009). Spatial analyses to evaluate multi-crop yield stability for a field. Computers and Electronics in Agriculture. 70(1). 187–198. 24 indexed citations
3.
Willers, Jeffrey L., et al.. (2006). Remote Sensing, Sampling and Simulation Applications in Analyses of Insect Dispersion and Abundance in Cotton. 42. 1 indexed citations
4.
Reddy, K. Raja, H. F. Hodges, John J. Read, et al.. (2001). SOIL-PLANT-ATMOSPHERE-RESEARCH (SPAR) FACILITY: A TOOL FOR PLANT RESEARCH AND MODELING. Kyushu University Institutional Repository (QIR) (Kyushu University). 30. 27–50. 107 indexed citations
5.
Willers, Jeffrey L., et al.. (2000). APPLICATION OF COMPUTER INTENSIVE METHODS TO EVALUATE THE PERFORMANCE OF A SAMPLING DESIGN FOR USE IN COTTON INSECT PEST MANAGEMENT. Conference on Applied Statistics in Agriculture. 3 indexed citations
6.
Reddy, K. Raja, Harry F. Hodges, & James M. McKinion. (1998). A Comparison of Scenarios for the Effect of Global Climate Change on Cotton Growth and Yield. Australian Journal of Plant Physiology. 24(6). 707–713. 81 indexed citations
7.
Reddy, K. Raja, et al.. (1998). Interactions of CO2 enrichment and temperature on cotton growth and leaf characteristics. Environmental and Experimental Botany. 39(2). 117–129. 78 indexed citations
8.
Reddy, K. Raja, A. Ramachandra Reddy, H. F. Hodges, & James M. McKinion. (1997). Water and nutrient deficits, crop yields, and climate change. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 6 indexed citations
9.
Reddy, K. Raja, H. F. Hodges, & James M. McKinion. (1995). Carbon dioxide and temperature effects on pima cotton growth. Agriculture Ecosystems & Environment. 54(1-2). 17–29. 49 indexed citations
10.
Reddy, K. Raja, et al.. (1995). Developing and Validating a Model for a Plant Growth Regulator. Agronomy Journal. 87(6). 1100–1105. 24 indexed citations
11.
Reddy, K. Raja, H. F. Hodges, & James M. McKinion. (1993). A TEMPERATURE MODEL FOR COTTON PHENOLOGY. Kyushu University Institutional Repository (QIR) (Kyushu University). 22. 47–59. 29 indexed citations
12.
Reddy, K. Raja, H. F. Hodges, & James M. McKinion. (1993). Temperature Effects on Pima Cotton Leaf Growth. Agronomy Journal. 85(3). 681–686. 24 indexed citations
13.
Baker, D. N., V. R. Reddy, James M. McKinion, & F. D. Whisler. (1993). An analysis of the impact of lygus on cotton. Computers and Electronics in Agriculture. 8(2). 147–161. 2 indexed citations
14.
Goodenough, J. L. & James M. McKinion. (1992). Basics of insect modeling. 18 indexed citations
15.
Reddy, K. Raja, et al.. (1992). Temperature Effects on Pima Cotton Growth and Development. Agronomy Journal. 84(2). 237–243. 65 indexed citations
16.
Acock, B., V. R. Reddy, H. F. Hodges, D. N. Baker, & James M. McKinion. (1985). Photosynthetic Response of Soybean Canopies to Full‐Season Carbon Dioxide Enrichment1. Agronomy Journal. 77(6). 942–947. 57 indexed citations
17.
Marani, A., D. N. Baker, Vangimalla R. Reddy, & James M. McKinion. (1985). Effect of Water Stress on Canopy Senescence and Carbon Exchange Rates in Cotton1. Crop Science. 25(5). 798–802. 29 indexed citations
18.
McKinion, James M., et al.. (1983). Design and operation of the SPAR cooling system. 1 indexed citations
19.
Parsons, John E., et al.. (1980). Microprocessor-Based Data Acquisition and Control Software for Plant Growth Chambers (Spar System). Transactions of the ASAE. 23(3). 589–595. 10 indexed citations
20.
Hesketh, J. D., James M. McKinion, James W. Jones, & D. N. Baker. (1974). Simcot: A computer simulation of cotton growth and yield. IEEE Transactions on Automatic Control. 12(12). 337.

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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