Minh Ha

2.9k total citations · 2 hit papers
65 papers, 2.1k citations indexed

About

Minh Ha is a scholar working on Animal Science and Zoology, Food Science and Insect Science. According to data from OpenAlex, Minh Ha has authored 65 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Animal Science and Zoology, 24 papers in Food Science and 14 papers in Insect Science. Recurrent topics in Minh Ha's work include Meat and Animal Product Quality (57 papers), Animal Nutrition and Physiology (18 papers) and Sensory Analysis and Statistical Methods (17 papers). Minh Ha is often cited by papers focused on Meat and Animal Product Quality (57 papers), Animal Nutrition and Physiology (18 papers) and Sensory Analysis and Statistical Methods (17 papers). Minh Ha collaborates with scholars based in Australia, New Zealand and United Kingdom. Minh Ha's co-authors include Robyn D. Warner, Frank R. Dunshea, Alaa El‐Din A. Bekhit, Alan Carne, Surinder S. Chauhan, David Hopkins, Rozita Vaskoska, P. A. Gonzalez-Rivas, Narelle Fegan and Zhongxiang Fang and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Minh Ha

64 papers receiving 2.0k citations

Hit Papers

Effects of heat stress on animal physiology, metabolism, ... 2019 2026 2021 2023 2019 2021 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Minh Ha Australia 23 1.4k 596 543 254 214 65 2.1k
Jianlian Huang China 28 1.1k 0.8× 867 1.5× 680 1.3× 246 1.0× 202 0.9× 75 2.1k
Wenge Yang China 25 811 0.6× 676 1.1× 615 1.1× 285 1.1× 204 1.0× 84 1.9k
Qinxiu Sun China 32 1.8k 1.2× 1.1k 1.8× 830 1.5× 266 1.0× 178 0.8× 91 2.6k
Eduardo Mendes Ramos Brazil 28 1.6k 1.1× 1.0k 1.7× 426 0.8× 223 0.9× 277 1.3× 129 2.4k
Liu Shi China 25 971 0.7× 721 1.2× 438 0.8× 187 0.7× 255 1.2× 63 1.6k
Yanwei Mao China 26 1.4k 1.0× 647 1.1× 451 0.8× 189 0.7× 96 0.4× 89 1.9k
Yulong Bao China 20 1.2k 0.9× 443 0.7× 590 1.1× 217 0.9× 142 0.7× 48 1.7k
R. Marino Italy 31 1.4k 1.0× 872 1.5× 650 1.2× 323 1.3× 372 1.7× 109 2.8k
Longteng Zhang China 35 2.0k 1.4× 878 1.5× 1.3k 2.4× 358 1.4× 337 1.6× 79 2.9k
Young-Hwa Hwang South Korea 27 2.0k 1.4× 911 1.5× 650 1.2× 203 0.8× 404 1.9× 83 2.8k

Countries citing papers authored by Minh Ha

Since Specialization
Citations

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

Fields of papers citing papers by Minh Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minh Ha

This figure shows the co-authorship network connecting the top 25 collaborators of Minh Ha. A scholar is included among the top collaborators of Minh Ha 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 Minh Ha. Minh Ha 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.
Ha, Minh, et al.. (2024). Plant‐based mince texture: A review of the sensory literature with view to informing new product development. Journal of Food Science. 89(12). 8197–8214. 2 indexed citations
2.
Ha, Minh, et al.. (2024). Machine Vision Requires Fewer Repeat Measurements than Colorimeters for Precise Seafood Colour Measurement. Foods. 13(7). 1110–1110. 2 indexed citations
3.
Ha, Minh, et al.. (2023). Genetic lines influenced the texture, collagen and intramuscular fat of pork longissimus and semimembranosus. Meat Science. 207. 109376–109376. 2 indexed citations
4.
Xu, Yan, Minh Ha, Hui Huang, & Robyn D. Warner. (2023). 51. Effect of 12-days ageing on texture and cooking loss of Australian pork silverside and loin. Animal - science proceedings. 14(7). 868–869. 1 indexed citations
5.
Warner, Robyn D., et al.. (2023). A review of some aspects of goat meat quality: future research recommendations. Animal Production Science. 63(14). 1361–1375. 6 indexed citations
6.
Vaskoska, Rozita, Minh Ha, Jason D. White, & Robyn D. Warner. (2023). Benefits of prolonged ageing for the quality of Australian pork depends on cooking temperature and meat pH. Animal Production Science. 63(8). 816–823. 1 indexed citations
8.
Ha, Minh, et al.. (2022). High consumer acceptance of mutton and the influence of ageing method on eating quality. Meat Science. 189. 108813–108813. 11 indexed citations
9.
Herrera, Roberto Villalobos, Emanuele Bevacqua, Andreia Ribeiro, et al.. (2021). Towards a compound-event-oriented climate model evaluation: a decomposition of the underlying biases in multivariate fire and heat stress hazards. Natural hazards and earth system sciences. 21(6). 1867–1885. 20 indexed citations
10.
Warner, Robyn D., Minh Ha, Frank R. Dunshea, et al.. (2021). Effect of slaughter age and post-mortem days on meat quality of longissimus and semimembranosus muscles of Boer goats. Meat Science. 175. 108466–108466. 24 indexed citations
11.
Naqvi, Zahra, Peter C. Thomson, Minh Ha, et al.. (2021). Effect of sous vide cooking and ageing on tenderness and water-holding capacity of low-value beef muscles from young and older animals. Meat Science. 175. 108435–108435. 46 indexed citations
12.
Ha, Minh, et al.. (2021). Meta-analysis of the relationship between collagen characteristics and meat tenderness. Meat Science. 185. 108717–108717. 42 indexed citations
13.
14.
Vaskoska, Rozita, Minh Ha, Zahra Naqvi, Jason D. White, & Robyn D. Warner. (2020). Muscle, Ageing and Temperature Influence the Changes in Texture, Cooking Loss and Shrinkage of Cooked Beef. Foods. 9(9). 1289–1289. 55 indexed citations
15.
Vaskoska, Rozita, Minh Ha, Lydia Ong, et al.. (2020). Ageing and cathepsin inhibition affect the shrinkage of fibre fragments of bovine semitendinosus, biceps femoris and psoas major during heating. Meat Science. 172. 108339–108339. 14 indexed citations
16.
Ha, Minh, et al.. (2019). Effects of different ageing methods on colour, yield, oxidation and sensory qualities of Australian beef loins consumed in Australia and Japan. Food Research International. 125. 108528–108528. 52 indexed citations
17.
Gonzalez-Rivas, P. A., Surinder S. Chauhan, Minh Ha, et al.. (2019). Effects of heat stress on animal physiology, metabolism, and meat quality: A review. Meat Science. 162. 108025–108025. 358 indexed citations breakdown →
18.
Torrico, Damir D., Scott C. Hutchings, Minh Ha, et al.. (2018). Novel techniques to understand consumer responses towards food products: A review with a focus on meat. Meat Science. 144. 30–42. 67 indexed citations
19.
Ha, Minh, Elizabeth J. Duncan, Peter A. Stockwell, et al.. (2015). In-Depth Characterization of Sheep (Ovis aries) Milk Whey Proteome and Comparison with Cow (Bos taurus). PLoS ONE. 10(10). e0139774–e0139774. 48 indexed citations
20.
Liu, Bin, Minh Ha, Xiao Meng, et al.. (2011). Molecular Mechanism of Species-Dependent Sweet Taste toward Artificial Sweeteners. Journal of Neuroscience. 31(30). 11070–11076. 58 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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