Masato Yayota
- Animal Science and Zoology top 5%
- Effects of Environmental Stressors on Livestock 14
- Animal Nutrition and Physiology 11
- Meat and Animal Product Quality 4
- Agronomy and Crop Science top 5%
- Ruminant Nutrition and Digestive Physiology 31
- Reproductive Physiology in Livestock 9
- Developmental Biology top 10%
- Small Animals top 10%
- Animal Behavior and Welfare Studies 8
- Forestry top 10%
- Agroforestry and silvopastoral systems 5
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- Genetic and phenotypic traits in livestock 21
Masato Yayota
61 papers receiving 304 citations
Peers
Comparison fields: 5 of 80
- Animal Science and Zoology 117
- Agronomy and Crop Science 100
- Developmental Biology 17
- Small Animals 43
- Forestry 16
Countries citing papers authored by Masato Yayota
This map shows the geographic impact of Masato Yayota'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 Masato Yayota with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masato Yayota more than expected).
Fields of papers citing papers by Masato Yayota
This network shows the impact of papers produced by Masato Yayota. 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 Masato Yayota. The network helps show where Masato Yayota may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masato Yayota, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 0 | |
| 9 | 2022 | 3 | |
| 10 | 2021 | 8 | |
| 11 | 2019 | 9 | |
| 12 | Monitoring Foraging Behavior in Ruminants in a Diverse Pasture | 2017 | 1 |
| 13 | Monitoring Spatial Heterogeneity of Pasture within Paddock Scale using a Small Unmanned Aerial Vehicle (sUAV) | 2017 | 2 |
| 14 | Hyperspectral Assessment for Legume Content and Forage Nutrient Status in Pastures | 2017 | 1 |
| 15 | 2013 | 18 | |
| 16 | 2008 | 2 | |
| 17 | 2007 | 2 | |
| 18 | 2003 | 6 | |
| 19 | 2002 | 2 | |
| 20 | Seasonal changes of area of dung patches under strip grazing for lactating dairy cows. | 2000 | 2 |
About Masato Yayota
Masato Yayota is a scholar working on Agronomy and Crop Science, Animal Science and Zoology, Forestry, Small Animals and Genetics, having authored 62 papers that have together received 313 indexed citations. Recurring topics across this work include Ruminant Nutrition and Digestive Physiology (31 papers), Genetic and phenotypic traits in livestock (21 papers), Effects of Environmental Stressors on Livestock (14 papers), Animal Nutrition and Physiology (11 papers), Reproductive Physiology in Livestock (9 papers), Animal Behavior and Welfare Studies (8 papers), Agroforestry and silvopastoral systems (5 papers) and Meat and Animal Product Quality (4 papers). The work is most often cited by research in Animal Science and Zoology (117 citations), Agronomy and Crop Science (100 citations), Developmental Biology (17 citations), Small Animals (43 citations) and Forestry (16 citations). Masato Yayota has collaborated with scholars based in Japan, China and Indonesia. Frequent co-authors include Shigeru OHTANI, Atsushi Iwasawa, S. Ohtani, Noriaki Nakajima, Mitsuhiro Shibata, Yasuyuki Yamada, Veerle Darras, Ikki Matsuda, Marcus Clauß and Julia Fritz. Their work appears in journals such as Animal Science Journal, Animal Feed Science and Technology, Livestock Science, Frontiers in Veterinary Science and Computers and Electronics in Agriculture.
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.