Ivan Bianchi

764 total citations
71 papers, 569 citations indexed

About

Ivan Bianchi is a scholar working on Agronomy and Crop Science, Small Animals and Animal Science and Zoology. According to data from OpenAlex, Ivan Bianchi has authored 71 papers receiving a total of 569 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Agronomy and Crop Science, 21 papers in Small Animals and 20 papers in Animal Science and Zoology. Recurrent topics in Ivan Bianchi's work include Reproductive Physiology in Livestock (20 papers), Animal Behavior and Welfare Studies (20 papers) and Genetic and phenotypic traits in livestock (15 papers). Ivan Bianchi is often cited by papers focused on Reproductive Physiology in Livestock (20 papers), Animal Behavior and Welfare Studies (20 papers) and Genetic and phenotypic traits in livestock (15 papers). Ivan Bianchi collaborates with scholars based in Brazil, United States and Poland. Ivan Bianchi's co-authors include Thomaz Lucia, Márcio Nunes Corrêa, João Carlos Deschamps, U Maugeri, Wiesław Jędrychowski, Rafael da Rosa Ulguim, Elżbieta Flak, Érico Kunde Corrêa, Carine Dahl Corcini and Antônio Sérgio Varela and has published in prestigious journals such as Bioresource Technology, Journal of Environmental Management and Journal of Animal Science.

In The Last Decade

Ivan Bianchi

62 papers receiving 531 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ivan Bianchi Brazil 12 157 156 127 125 110 71 569
Pierre Castro Soares Brazil 14 177 1.1× 157 1.0× 107 0.8× 90 0.7× 147 1.3× 120 735
J. Udała Poland 12 177 1.1× 148 0.9× 59 0.5× 86 0.7× 67 0.6× 61 512
Przemysław Sobiech Poland 13 67 0.4× 50 0.3× 68 0.5× 111 0.9× 106 1.0× 79 563
Hrvoje Valpotić Croatia 15 73 0.5× 43 0.3× 88 0.7× 134 1.1× 166 1.5× 67 682
Muniandy Sivaram India 13 58 0.4× 43 0.3× 120 0.9× 87 0.7× 185 1.7× 62 537
C.J. Hammer United States 19 43 0.3× 267 1.7× 176 1.4× 255 2.0× 169 1.5× 62 1.3k
Gemechis D. Djira United States 11 82 0.5× 115 0.7× 14 0.1× 122 1.0× 47 0.4× 39 504
M. Henry Brazil 16 349 2.2× 281 1.8× 73 0.6× 219 1.8× 65 0.6× 67 762
E.A. Amoah United States 13 38 0.2× 58 0.4× 131 1.0× 241 1.9× 311 2.8× 21 725
Atul Saxena India 13 189 1.2× 154 1.0× 26 0.2× 49 0.4× 22 0.2× 78 523

Countries citing papers authored by Ivan Bianchi

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Bianchi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Bianchi

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Bianchi. A scholar is included among the top collaborators of Ivan Bianchi 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 Ivan Bianchi. Ivan Bianchi 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.
Ibelli, A. M. G., Mônica Corrêa Ledur, Maurício Egídio Cantão, et al.. (2025). Genome-wide association analysis highlights genomic regions and genes potentially associated with anestrus in crossbred gilts. Mammalian Genome. 36(4). 1112–1125.
2.
3.
Gerber, M, et al.. (2024). Effect of Storage Time, Broiler Breeder Strain, and Age on Hatchability and First-Week Broiler Performance. Brazilian Journal of Poultry Science. 26(2).
4.
Lucia, Thomaz, et al.. (2024). Use of chorionic gonadotropins during lactation to optimize postpartum sow reproductive performance: a review. Animal Reproduction. 21(2). 2 indexed citations
5.
Irgang, R., et al.. (2023). Evaluation of different percentages of Duroc genes and gender on growth, carcass and meat quality traits for pigs. Meat Science. 205. 109314–109314. 3 indexed citations
6.
Peripolli, Vanessa, et al.. (2023). Risk factors associated with stillbirth in sows. Ciência Rural. 53(11). 3 indexed citations
7.
Peripolli, Vanessa, et al.. (2023). Pre-incubation storage time and in ovo injection with maltodextrin on Pekin duck incubation parameters. Ciência Rural. 54(3). 1 indexed citations
8.
Corrêa, Márcio Nunes, et al.. (2023). Metabolic profile of transition period in ewes and its influence on passive immunity transference in lambs. Tropical Animal Health and Production. 55(2). 112–112. 4 indexed citations
9.
Rizzoto, Guilherme, et al.. (2022). Socioeconomic and investment profile of environment control in a swine integration system. Revista Brasileira de Zootecnia. 51. 1 indexed citations
10.
Kich, Jalusa Deon, et al.. (2022). Salmonella enterica and enterobacteria in pig carcasses processed on different slaughter days. Pesquisa Agropecuária Brasileira. 57. 1 indexed citations
11.
Marques, Mariana Groke, et al.. (2021). In vitro and in vivo parameters for identification of landrace pigs with low reproductive performance. Semina Ciências Agrárias. 43(2). 573–584. 1 indexed citations
12.
Peripolli, Vanessa, et al.. (2021). Socioeconomic profile of producers and dairy technological of farms in the southern mesoregion of Santa Catarina. Semina Ciências Agrárias. 43(1). 107–120. 1 indexed citations
13.
Peripolli, Vanessa, et al.. (2021). Effects of in feed removal of antimicrobials in comparison to other prophylactic alternatives in growing and finishing pigs. Arquivo Brasileiro de Medicina Veterinária e Zootecnia. 73(6). 1381–1390. 1 indexed citations
14.
Costa, O. A. Dalla, et al.. (2020). Evaluation of reproductive and animal welfare parameters of swine females of different genetic lines submitted to different reproductive management and housing systems during pregnancy. Arquivo Brasileiro de Medicina Veterinária e Zootecnia. 72(5). 1675–1682. 4 indexed citations
15.
Rizzoto, Guilherme, et al.. (2016). Metabolic and reproductive parameters in prepubertal gilts after omega-3 supplementation in the diet. Animal Reproduction Science. 170. 178–183. 9 indexed citations
16.
Ulguim, Rafael da Rosa, Ivan Bianchi, & Thomaz Lucia. (2014). Female lifetime productivity in a swine integration system using segregated gilt development units. Tropical Animal Health and Production. 46(4). 697–700. 7 indexed citations
17.
Bianchi, Ivan, et al.. (2011). Efeito de diferentes métodos de congelamento, diluentes e tempos de resfriamento sobre a qualidade do sêmen suíno criopreservado. ACTA SCIENTIAE VETERINARIAE. 39(1). 1–7. 5 indexed citations
18.
Bianchi, Ivan, et al.. (2011). Effect of different freezing methods, extenders and duration of freezing on quality of frozen boar semen.. ACTA SCIENTIAE VETERINARIAE. 39(1). 1 indexed citations
19.
Schneider, Augusto, Eduardo Schmitt, Luiz Francisco Machado Pfeifer, et al.. (2011). Effect of prepartum somatotropin injection in late-pregnant Holstein heifers on metabolism, milk production and postpartum resumption of ovulation. animal. 6(6). 935–940. 8 indexed citations
20.
Cominacini, Luciano, et al.. (1977). Primi rilievi sull'utilità del dosaggio radioimmunologico del paratormone nella diagnosi di iperparatiroidismo primitivo. 267–275. 3 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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