Lachlan Lake

781 total citations
29 papers, 527 citations indexed

About

Lachlan Lake is a scholar working on Plant Science, Agronomy and Crop Science and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Lachlan Lake has authored 29 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Plant Science, 12 papers in Agronomy and Crop Science and 1 paper in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Lachlan Lake's work include Genetic and Environmental Crop Studies (26 papers), Agricultural pest management studies (15 papers) and Agronomic Practices and Intercropping Systems (11 papers). Lachlan Lake is often cited by papers focused on Genetic and Environmental Crop Studies (26 papers), Agricultural pest management studies (15 papers) and Agronomic Practices and Intercropping Systems (11 papers). Lachlan Lake collaborates with scholars based in Australia, Argentina and Chile. Lachlan Lake's co-authors include Víctor O. Sadras, Karine Chenu, L. McMurray, Antonio Leonforte, Yongle Li, J. G. Paull, Tim Sutton, Garry M. Rosewarne, Daniel F. Calderini and Hélène Marrou and has published in prestigious journals such as Journal of Experimental Botany, Frontiers in Plant Science and Agricultural and Forest Meteorology.

In The Last Decade

Lachlan Lake

27 papers receiving 517 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lachlan Lake Australia 14 476 215 79 28 26 29 527
Benoît Clerget France 9 254 0.5× 104 0.5× 94 1.2× 15 0.5× 24 0.9× 18 326
Dechang Sheng China 10 355 0.7× 244 1.1× 69 0.9× 6 0.2× 19 0.7× 11 405
Antonio Leonforte Australia 12 378 0.8× 111 0.5× 87 1.1× 8 0.3× 18 0.7× 19 498
R.A. Ruiz Argentina 8 294 0.6× 222 1.0× 54 0.7× 91 3.3× 42 1.6× 11 404
Vladimir Shvidchenko Kazakhstan 4 351 0.7× 106 0.5× 40 0.5× 12 0.4× 13 0.5× 9 395
Lyudmila Zotova Kazakhstan 6 369 0.8× 110 0.5× 41 0.5× 10 0.4× 16 0.6× 13 431
Francois Koekemoer Australia 2 314 0.7× 102 0.5× 38 0.5× 11 0.4× 11 0.4× 4 355
Adriana G. Kantolic Argentina 9 444 0.9× 216 1.0× 52 0.7× 6 0.2× 11 0.4× 11 471
Mark A. Boudreau United States 12 440 0.9× 237 1.1× 54 0.7× 8 0.3× 16 0.6× 16 535
F. F. Bebawi Sudan 12 339 0.7× 122 0.6× 115 1.5× 8 0.3× 36 1.4× 56 431

Countries citing papers authored by Lachlan Lake

Since Specialization
Citations

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

Fields of papers citing papers by Lachlan Lake

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lachlan Lake

This figure shows the co-authorship network connecting the top 25 collaborators of Lachlan Lake. A scholar is included among the top collaborators of Lachlan Lake 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 Lachlan Lake. Lachlan Lake 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.
Denton, Matthew D., et al.. (2025). An integrated, multivariate characterisation of water and photothermal regimes for faba bean in Australia. Agricultural and Forest Meteorology. 363. 110426–110426. 1 indexed citations
2.
Giménez, Rafael, Lachlan Lake, C. Mariano Cossani, et al.. (2024). Linking phenology, harvest index, and genetics to improve chickpea grain yield. Journal of Experimental Botany. 76(6). 1658–1677.
3.
Adhikari, Kedar, Matthew D. Denton, Lachlan Lake, et al.. (2024). Genetic gain in yield of Australian faba bean since 1980 and associated shifts in the phenotype: Growth, partitioning, phenology, and resistance to lodging and disease. Field Crops Research. 318. 109575–109575. 2 indexed citations
4.
Lake, Lachlan, Julie E. Hayes, Muhammad Javid, et al.. (2024). Genetics of phenological development and implications for seed yield in lentil. Journal of Experimental Botany. 75(16). 4772–4783. 2 indexed citations
5.
Chauhan, Y. S., Muhuddin Rajin Anwar, Lachlan Lake, et al.. (2023). Effect of soil water on flowering and pod-set in chickpea: implications for modelling and managing frost and heat stress. Agronomy for Sustainable Development. 43(4). 6 indexed citations
6.
7.
Sadras, Víctor O., Garry M. Rosewarne, & Lachlan Lake. (2021). Australian Lentil Breeding Between 1988 and 2019 Has Delivered Greater Yield Gain Under Stress Than Under High-Yield Conditions. Frontiers in Plant Science. 12. 674327–674327. 14 indexed citations
8.
Lake, Lachlan & Víctor O. Sadras. (2021). Lentil yield and crop growth rate are coupled under stress but uncoupled under favourable conditions. European Journal of Agronomy. 126. 126266–126266. 18 indexed citations
9.
Lake, Lachlan, et al.. (2021). Critical developmental period for grain yield and grain protein concentration in lentil. Field Crops Research. 270. 108203–108203. 10 indexed citations
10.
Lake, Lachlan, Yash Chauhan, Jonathan J. Ojeda, et al.. (2020). Modelling phenology to probe for trade-offs between frost and heat risk in lentil and faba bean. European Journal of Agronomy. 122. 126154–126154. 23 indexed citations
11.
Lake, Lachlan, et al.. (2019). Yield determination and the critical period of faba bean (Vicia faba L.). Field Crops Research. 241. 107575–107575. 29 indexed citations
12.
Sadras, Víctor O., Lachlan Lake, Sukhjiwan Kaur, & Garry M. Rosewarne. (2019). Phenotypic and genetic analysis of pod wall ratio, phenology and yield components in field pea. Field Crops Research. 241. 107551–107551. 15 indexed citations
13.
Lake, Lachlan & Víctor O. Sadras. (2017). Associations between yield, intercepted radiation and radiation-use efficiency in chickpea. Crop and Pasture Science. 68(2). 140–147. 11 indexed citations
14.
Cossani, C. Mariano, et al.. (2017). Impact of sowing date on phenology and yield of lentil and faba bean.. 1–4. 2 indexed citations
15.
Sadras, Víctor O., et al.. (2016). Phenotypic plasticity and its genetic regulation for yield, nitrogen fixation and δ13C in chickpea crops under varying water regimes. Journal of Experimental Botany. 67(14). 4339–4351. 46 indexed citations
16.
Lake, Lachlan, et al.. (2015). The critical period for yield determination in chickpea. 1 indexed citations
17.
Sadras, Víctor O., Vincent Vadez, P. Ramamoorthy, Lachlan Lake, & Hélène Marrou. (2015). Unscrambling confounded effects of sowing date trials to screen for crop adaptation to high temperature. Field Crops Research. 177. 1–8. 37 indexed citations
18.
Lake, Lachlan & Víctor O. Sadras. (2014). The critical period for yield determination in chickpea (Cicer arietinum L.). Field Crops Research. 168. 1–7. 59 indexed citations
19.
Sadras, Víctor O., Lachlan Lake, Karine Chenu, L. McMurray, & Antonio Leonforte. (2012). Water and thermal regimes for field pea in Australia and their implications for breeding. Crop and Pasture Science. 63(1). 33–44. 50 indexed citations
20.
Lake, Lachlan, et al.. (2009). Radiant frost tolerance in pulse crops—a review. Euphytica. 172(1). 1–12. 63 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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