H. Spiekers

741 total citations
47 papers, 576 citations indexed

About

H. Spiekers is a scholar working on Agronomy and Crop Science, Animal Science and Zoology and Genetics. According to data from OpenAlex, H. Spiekers has authored 47 papers receiving a total of 576 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Agronomy and Crop Science, 16 papers in Animal Science and Zoology and 16 papers in Genetics. Recurrent topics in H. Spiekers's work include Ruminant Nutrition and Digestive Physiology (21 papers), Reproductive Physiology in Livestock (20 papers) and Genetic and phenotypic traits in livestock (15 papers). H. Spiekers is often cited by papers focused on Ruminant Nutrition and Digestive Physiology (21 papers), Reproductive Physiology in Livestock (20 papers) and Genetic and phenotypic traits in livestock (15 papers). H. Spiekers collaborates with scholars based in Germany, Austria and Switzerland. H. Spiekers's co-authors include E. Pfeffer, F. J. Schwarz, Karl‐Heinz Südekum, M. Rodehutscord, T. Ettle, M. Schuster, Stefan Thurner, Ulrich Meyer, E. Stamer and Patrick Guertler and has published in prestigious journals such as Journal of Agricultural and Food Chemistry, Journal of Dairy Science and Meat Science.

In The Last Decade

H. Spiekers

42 papers receiving 540 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
H. Spiekers Germany 15 346 171 166 156 83 47 576
K. A. Cassida United States 17 664 1.9× 106 0.6× 136 0.8× 193 1.2× 76 0.9× 51 918
R.J. Higgs United States 7 476 1.4× 156 0.9× 103 0.6× 94 0.6× 48 0.6× 10 552
P. Susmel Italy 17 551 1.6× 204 1.2× 191 1.2× 97 0.6× 52 0.6× 47 688
L. Holtshausen Canada 9 668 1.9× 176 1.0× 133 0.8× 107 0.7× 91 1.1× 20 786
Raul Franzolin Brazil 13 469 1.4× 138 0.8× 114 0.7× 106 0.7× 93 1.1× 57 613
Horacio Leandro Gonda Sweden 12 663 1.9× 180 1.1× 125 0.8× 86 0.6× 78 0.9× 31 842
S. Ramos South Korea 13 377 1.1× 95 0.6× 126 0.8× 73 0.5× 90 1.1× 29 483
C.P. Mathis United States 17 612 1.8× 244 1.4× 210 1.3× 64 0.4× 49 0.6× 39 815
Katrin Gerlach Germany 14 351 1.0× 100 0.6× 141 0.8× 95 0.6× 61 0.7× 28 545

Countries citing papers authored by H. Spiekers

Since Specialization
Citations

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

Fields of papers citing papers by H. Spiekers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of H. Spiekers

This figure shows the co-authorship network connecting the top 25 collaborators of H. Spiekers. A scholar is included among the top collaborators of H. Spiekers 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 H. Spiekers. H. Spiekers 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.
Dorn‐In, Samart, et al.. (2025). Quantitative PCR Detection of Clostridia and Evaluation of Feed Hygiene Across Different Manure Application Techniques. International Journal of Agronomy. 2025(1).
2.
Losand, B., et al.. (2024). Influence of fat-to-protein ratio and udder health parameters on the milk urea content of dairy cows. Journal of Dairy Science. 108(3). 2527–2546.
3.
Spiekers, H., et al.. (2022). System Design and Validation of a Wireless Sensor Monitoring System in Silage. Agronomy. 12(4). 892–892. 1 indexed citations
4.
Becker, Veith, E. Stamer, H. Spiekers, & Georg Thaller. (2022). Genetic parameters for dry matter intake, energy balance, residual energy intake, and liability to diseases in German Holstein and Fleckvieh dairy cows. Journal of Dairy Science. 105(12). 9738–9750. 6 indexed citations
5.
Spiekers, H., et al.. (2022). Content and gain of macro minerals in the empty body and body tissues of growing bulls. Meat Science. 194. 108977–108977. 2 indexed citations
6.
Becker, Veith, E. Stamer, H. Spiekers, & Georg Thaller. (2021). Residual energy intake, energy balance, and liability to diseases: Genetic parameters and relationships in German Holstein dairy cows. Journal of Dairy Science. 104(10). 10970–10978. 14 indexed citations
7.
Spiekers, H., et al.. (2020). Relationship between milk constituents from milk testing and health, feeding, and metabolic data of dairy cows. Journal of Dairy Science. 103(11). 10175–10194. 21 indexed citations
9.
Dale, Laura, et al.. (2019). Prediction of evaluated energy balance (NEL and ME) in dairy cows by milk mid-infrared (MIR) spectra.. 137–141. 1 indexed citations
10.
Taube, F., et al.. (2019). Dry‐matter losses and changes in nutrient concentrations in grass and maize silages stored in bunker silos. Grass and Forage Science. 74(2). 274–283. 13 indexed citations
11.
Ettle, T., et al.. (2018). Long-term study on the effects of different concentrates: roughage ratios in dairy cow feeding on performance and feed intake.. Züchtungskunde. 90(6). 417–429. 1 indexed citations
12.
Denissen, Jon F., et al.. (2018). Effects of energy density of forage and amount of concentrates on feed intake, rumination behaviour and performance of German Holstein cows during a whole lactation.. Züchtungskunde. 90(6). 430–452. 3 indexed citations
13.
Spiekers, H.. (2018). Improvement of the housing of dairy cows by breeding methods on feed intake and metabolic stability as well as environmental compatibility with optimized feeding intensity and use of metabolic indicators as well as sensors in herd management - optiKuh - introduction and project overview.. Züchtungskunde. 90(6). 411–416. 1 indexed citations
14.
Soosten, Dirk von, Ulrich Meyer, Liane Hüther, et al.. (2018). Changes of ruminal pH, rumination activity and feeding behaviour during early lactation as affected by different energy and fibre concentrations of roughage in pluriparous dairy cows. Archives of Animal Nutrition. 72(6). 458–477. 10 indexed citations
15.
Brinkmann, Jan, Solveig March, Kerstin Barth, et al.. (2011). Status quo der Tiergesundheitssituation in der ökologischen Milchviehhaltung in Deutschland - Ergebnisse einer repräsentativen bundesweiten Felderhebung. Organic Eprints (International Centre for Research in Organic Food Systems, and Research Institute of Organic Agriculture). 1 indexed citations
16.
Südekum, K.‐H., et al.. (2010). Evaluating the protein value of forages using a modified gas test.. 719–720. 1 indexed citations
17.
Losand, B., et al.. (2009). Determination of crude nutrient digestibilities and energy content of dried distillers grains and solubles (DDGS) from wheat and wheat/barley mixtures.. Züchtungskunde. 81(3). 173–179. 1 indexed citations
18.
Wiedemann, S., et al.. (2009). Effects of long-term feeding of genetically modified maize (Bt-maize, MON 810) on dairy cows. mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich). 349. 1 indexed citations
19.
Steingaß, H., et al.. (2001). Schätzung des nXP-Gehaltes mit Hilfe des modifizierten Hohenheimer Futterwerttests und dessen Anwendung zur Bewertung von Raps- und Sojaextraktionsschroten. 114. 12 indexed citations
20.
Spiekers, H., et al.. (1990). When to supplement trace elements.. 42(11). 491–493. 2 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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