Ian J. Yule

2.8k total citations · 1 hit paper
87 papers, 2.1k citations indexed

About

Ian J. Yule is a scholar working on Plant Science, Ecology and Civil and Structural Engineering. According to data from OpenAlex, Ian J. Yule has authored 87 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Plant Science, 26 papers in Ecology and 25 papers in Civil and Structural Engineering. Recurrent topics in Ian J. Yule's work include Remote Sensing in Agriculture (25 papers), Soil Mechanics and Vehicle Dynamics (18 papers) and Spectroscopy and Chemometric Analyses (15 papers). Ian J. Yule is often cited by papers focused on Remote Sensing in Agriculture (25 papers), Soil Mechanics and Vehicle Dynamics (18 papers) and Spectroscopy and Chemometric Analyses (15 papers). Ian J. Yule collaborates with scholars based in New Zealand, Malaysia and Germany. Ian J. Yule's co-authors include Reddy Pullanagari, C. Hedley, Gábor Kereszturi, M. P. Tuohy, Redmond R. Shamshiri, Cornelia Weltzien, Ibrahim A. Hameed, Siva K. Balasundram, Girish Chowdhary and Tony E. Grift and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Geoderma.

In The Last Decade

Ian J. Yule

84 papers receiving 2.0k 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.

Research and development in agricultural robotics: A perspective of digital farming

2018 345 citations Redmond R. Shamshiri, Cornelia Weltzien et al. International journal of agricultural and biological engineering profile →

Peers

Countries citing papers authored by Ian J. Yule

Since Specialization

Citations

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

Fields of papers citing papers by Ian J. Yule

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ian J. Yule. 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 Ian J. Yule. The network helps show where Ian J. Yule may publish in the future.

Co-authorship network of co-authors of Ian J. Yule

This figure shows the co-authorship network connecting the top 25 collaborators of Ian J. Yule. A scholar is included among the top collaborators of Ian J. Yule 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 Ian J. Yule. Ian J. Yule 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

#	Work	Indexed citations
1	The Relative Importance of Herbage Nutritive Value and Climate in Determining Daily Performance per Cow in a Pasture-Based Dairy Farm 2021 ·Agriculture ·(unknown), Nicola M. Shadbolt, (unknown), N. López‐Villalobos, Ian J. Yule, Stephen T. Morris	1
2	Variation of nutritive value, measured by proximal hyperspectral sensing, of herbage offered to grazing dairy cows 2021 ·New Zealand Journal of Agricultural Research ·(unknown), Nicola M. Shadbolt, (unknown), N. López‐Villalobos, Ian J. Yule, Stephen T. Morris	1
3	The Deviation between Dairy Cow Metabolizable Energy Requirements and Pasture Supply on a Dairy Farm Using Proximal Hyperspectral Sensing 2021 ·Agriculture ·(unknown), N. López‐Villalobos, Nicola M. Shadbolt, (unknown), Ian J. Yule, Stephen T. Morris	3
4	Early Detection of Ganoderma boninense in Oil Palm Seedlings Using Support Vector Machines 2020 ·Remote Sensing ·(unknown), Siti Khairunniza Bejo, Mahirah Jahari, Farrah Melissa Muharam, Ian J. Yule, (unknown)	34
5	Using Proximal Hyperspectral Sensing to Predict Herbage Nutritive Value for Dairy Farming 2020 ·Agronomy ·(unknown), Ian J. Yule, N. López‐Villalobos, Nicola M. Shadbolt, (unknown), Stephen T. Morris	15
6	Integrating Airborne Hyperspectral, Topographic, and Soil Data for Estimating Pasture Quality Using Recursive Feature Elimination with Random Forest Regression 2018 ·Remote Sensing ·Reddy Pullanagari, Gábor Kereszturi, Ian J. Yule	115
7	Simulation software and virtual environments for acceleration of agricultural robotics: Features highlights and performance comparison 2018 ·International journal of agricultural and biological engineering ·Redmond R. Shamshiri, Ibrahim A. Hameed, Lenka Pitonakova, Cornelia Weltzien, Siva K. Balasundram, Ian J. Yule, Tony E. Grift, Girish Chowdhary	15
8	Simulation software and virtual environments for acceleration of agricultural robotics: Features highlights and performance comparison 2018 ·International journal of agricultural and biological engineering ·Redmond R. Shamshiri, Ibrahim A. Hameed, Lenka Pitonakova, Cornelia Weltzien, Siva K. Balasundram, Ian J. Yule, Tony E. Grift, Girish Chowdhary	36
9	Simulation software and virtual environments for acceleration of agricultural robotics: Features highlights and performance comparison 2018 ·International journal of agricultural and biological engineering ·Redmond R. Shamshiri, Ibrahim A. Hameed, Lenka Pitonakova, Cornelia Weltzien, Siva K. Balasundram, Ian J. Yule, Tony E. Grift, Girish Chowdhary	2
10	A Review Of Practices In Precision Application Of Granular Fertilisers 2017 ·Zenodo (CERN European Organization for Nuclear Research) ·(unknown), Ian J. Yule, (unknown)	0
11	Deploying four optical UAV-based sensors over grassland: challenges and limitations 2015 ·Biogeosciences ·(unknown), Andreas Burkart, Andreas Hueni, Uwe Rascher, M. P. Tuohy, Ian J. Yule	138
12	Comparative validation of UAV based sensors for the use in vegetation monitoring 2014 ·(unknown), Andreas Burkart, Andreas Hueni, Uwe Rascher, M. P. Tuohy, Ian J. Yule	10
13	Case studies which demonstrate the financial viability of precision dairy farming. 2013 ·UKnowledge (University of Kentucky) ·Ian J. Yule, (unknown), Catrina A. MacKenzie, C. Hedley, (unknown), Reddy Pullanagari	1
14	Developing variable rate application technology: Economic impact for farm owners and topdressing operators 2007 ·New Zealand Journal of Agricultural Research ·(unknown), Ian J. Yule	13
15	Developing variable rate application technology: Modelling annual pasture production on hill country 2007 ·New Zealand Journal of Agricultural Research ·(unknown), Ian J. Yule, A. G. Gillingham	12
16	Estimation of the in‐field variation in fertiliser application 2007 ·New Zealand Journal of Agricultural Research ·(unknown), Ian J. Yule	14
17	Developing variable rate application technology: Scenario development and agronomic evaluation 2007 ·New Zealand Journal of Agricultural Research ·(unknown), Ian J. Yule	11
18	A statistical analysis of international test methods used for analysing spreader performance 2006 ·New Zealand Journal of Agricultural Research ·(unknown), Ian J. Yule, (unknown)	2
19	Testing the viability of existing ground spread fertiliser spreaders to perform variable rate fertilisation 2005 ·(unknown), Ian J. Yule, J. B. Jones, Mark Hedley	2
20	Model of moisture uptake by wheat seeds germinating in free water 1994 ·International Agrophysics ·(unknown), J.F. Favier, Ian J. Yule	1

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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