S. M. Nolasco

943 total citations
24 papers, 748 citations indexed

About

S. M. Nolasco is a scholar working on Plant Science, Nutrition and Dietetics and Food Science. According to data from OpenAlex, S. M. Nolasco has authored 24 papers receiving a total of 748 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Plant Science, 6 papers in Nutrition and Dietetics and 6 papers in Food Science. Recurrent topics in S. M. Nolasco's work include Sunflower and Safflower Cultivation (9 papers), Agricultural Engineering and Mechanization (6 papers) and Food composition and properties (5 papers). S. M. Nolasco is often cited by papers focused on Sunflower and Safflower Cultivation (9 papers), Agricultural Engineering and Mechanization (6 papers) and Food composition and properties (5 papers). S. M. Nolasco collaborates with scholars based in Argentina, Mexico and Ireland. S. M. Nolasco's co-authors include M. Capitani, Mabel C. Tomás, Viviana Graciela Spotorno, David Betancur‐Ancona, Luis Chel‐Guerrero, Luis Jorge Corzo‐Ríos, María B. Fernández, Luis Aguirrezábal, Guillermo H. Crapiste and César Mateo and has published in prestigious journals such as Molecules, Journal of Food Engineering and LWT.

In The Last Decade

S. M. Nolasco

24 papers receiving 730 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
S. M. Nolasco Argentina	12	485	379	246	65	59	24	748
María Cecilia Penci Argentina	18	601 1.2×	277 0.7×	359 1.5×	53 0.8×	17 0.3×	31	888
Sabah Mounir Egypt	17	680 1.4×	203 0.5×	138 0.6×	55 0.8×	40 0.7×	40	866
Pablo García‐Pascual Spain	8	454 0.9×	269 0.7×	124 0.5×	26 0.4×	27 0.5×	8	667
Manisha Guha India	15	528 1.1×	238 0.6×	629 2.6×	34 0.5×	28 0.5×	27	873
Cristina Arroqui Spain	14	412 0.8×	332 0.9×	113 0.5×	26 0.4×	44 0.7×	23	789
M.A. Salgado-Cervantes Mexico	18	526 1.1×	198 0.5×	75 0.3×	54 0.8×	37 0.6×	51	744
Warunee Varanyanond Thailand	17	573 1.2×	520 1.4×	582 2.4×	82 1.3×	22 0.4×	36	1.1k
M. Zhang China	7	831 1.7×	335 0.9×	96 0.4×	68 1.0×	52 0.9×	13	1.2k
Sukumar Debnath India	13	343 0.7×	238 0.6×	132 0.5×	85 1.3×	22 0.4×	35	660
Viviana Graciela Spotorno Argentina	7	511 1.1×	237 0.6×	255 1.0×	64 1.0×	10 0.2×	10	670

Countries citing papers authored by S. M. Nolasco

Since Specialization

Citations

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

Fields of papers citing papers by S. M. Nolasco

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. M. Nolasco. 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 S. M. Nolasco. The network helps show where S. M. Nolasco may publish in the future.

Co-authorship network of co-authors of S. M. Nolasco

This figure shows the co-authorship network connecting the top 25 collaborators of S. M. Nolasco. A scholar is included among the top collaborators of S. M. Nolasco 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 S. M. Nolasco. S. M. Nolasco 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

Fernández, María B., et al.. (2017). Artificial neural network model for the kinetics of canola oil extraction for different seed samples and pretreatments. Journal of Food Process Engineering. 41(1). 10 indexed citations

Nolasco, S. M., et al.. (2017). Dynamics of oil and tocopherol accumulation in sunflower grains and its impact on final oil quality. European Journal of Agronomy. 89. 124–130. 15 indexed citations

Mateo, César, et al.. (2016). Bidimensional modeling applied to oil extraction kinetics of microwave-pretreated canola seeds. Journal of Food Engineering. 192. 28–35. 26 indexed citations

Nolasco, S. M., et al.. (2016). Optimization of Microwave Pretreatment Variables for Canola Oil Extraction. Journal of Food Process Engineering. 40(3). 25 indexed citations

Rodríguez, Luis M., et al.. (2015). Loss of lipid material during the dehulling of oilseeds with different structural characteristics. Journal of Food Science and Technology. 52(12). 7934–7943. 6 indexed citations

Capitani, M., Luis Jorge Corzo‐Ríos, Luis Chel‐Guerrero, et al.. (2014). Rheological properties of aqueous dispersions of chia (Salvia hispanica L.) mucilage. Journal of Food Engineering. 149. 70–77. 163 indexed citations

Baümler, Erica R., María B. Fernández, S. M. Nolasco, & Ethel E. Pérez. (2014). Comparison of safflower oil extraction kinetics under two characteristic moisture conditions: statistical analysis of non-linear model parameters. Brazilian Journal of Chemical Engineering. 31(2). 553–559. 7 indexed citations

Izquierdo, Natalia G., et al.. (2012). Relationship between oil tocopherol concentration and oil weight per grain in several crop species. Crop and Pasture Science. 62(12). 1088–1097. 11 indexed citations

Rodríguez, Luis M., et al.. (2012). Performance analysis of a dehulling system for safflower grains. Industrial Crops and Products. 43. 311–317. 13 indexed citations

10.

Capitani, M., César Mateo, & S. M. Nolasco. (2011). Effect of temperature and storage time of wheat germ on the oil tocopherol concentration. Brazilian Journal of Chemical Engineering. 28(2). 243–250. 19 indexed citations

11.

Capitani, M., Viviana Graciela Spotorno, S. M. Nolasco, & Mabel C. Tomás. (2011). Physicochemical and functional characterization of by-products from chia (Salvia hispanica L.) seeds of Argentina. LWT. 45(1). 94–102. 248 indexed citations

12.

Ixtaina, Vanesa Y., et al.. (2011). Moisture-Dependent Physical Properties of Chia (Salvia hispanica L.) Seeds. Transactions of the ASABE. 54(2). 527–533. 7 indexed citations

13.

Baümler, Erica R., et al.. (2010). Moisture-dependent engineering properties of sunflower seeds with different structural characteristics. Journal of Food Engineering. 102(1). 58–65. 42 indexed citations

14.

Izquierdo, Natalia G., et al.. (2007). Temperature influence during seed filling on tocopherol concentration in a traditional sunflower hybrid. Grasas y Aceites. 58(2). 170–178. 11 indexed citations

15.

Nolasco, S. M., Luis Aguirrezábal, & Guillermo H. Crapiste. (2004). Tocopherol oil concentration in field‐grown sunflower is accounted for by oil weight per seed. Journal of the American Oil Chemists Society. 81(11). 1045–1051. 41 indexed citations

16.

Santalla, Estela, Guillermo A. A. Dosio, S. M. Nolasco, & Luis Aguirrezábal. (2002). The effects of intercepted solar radiation on sunflower (Helianthus annuus L.) seed composition from different head positions. Journal of the American Oil Chemists Society. 79(1). 69–74. 9 indexed citations

17.

Nolasco, S. M., et al.. (2001). Chemical characteristics of Solanum sisymbriifolium lam seed oil and residual seed meal. Grasas y Aceites. 52(2). 123–126. 1 indexed citations

18.

Nolasco, S. M., et al.. (2000). AIRFLOW RESISTANCE OF OAT SEEDS: EFFECT OF AIRFLOW DIRECTION, MOISTURE CONTENT AND FOREIGN MATERIAL. Drying Technology. 18(1-2). 457–468. 10 indexed citations

19.

Nolasco, S. M., et al.. (1995). Chemical composition ofRumex crispus L. seed. Journal of the American Oil Chemists Society. 72(9). 1077–1078. 2 indexed citations

20.

Santalla, Estela, et al.. (1993). Compositional data on sunflower seed grown in Argentine. Grasas y Aceites. 44(3). 175–178. 4 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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