Potential of soybean [Glycine max (L.) Merrill] progenies from southern Brazil
ABSTRACT This work aims to characterize and estimate soybean genotypes’ productive potential and industrial quality, understand the associations between traits and identify genotypes for a breeding program. Four collections totaling 301 genotypes were used, and ten quantitative characteristics were...
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Universidade de São Paulo
2025-05-01
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| Series: | Scientia Agricola |
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| author | Rafael Paulo da Silva Cosme Damião Cruz Ivan Ricardo de Carvalho |
| author_facet | Rafael Paulo da Silva Cosme Damião Cruz Ivan Ricardo de Carvalho |
| author_sort | Rafael Paulo da Silva |
| collection | DOAJ |
| description | ABSTRACT This work aims to characterize and estimate soybean genotypes’ productive potential and industrial quality, understand the associations between traits and identify genotypes for a breeding program. Four collections totaling 301 genotypes were used, and ten quantitative characteristics were analyzed, including the mass of one hundred seeds (100 SW, where SW stands for seed weight), protein content (PC), oil content (OIL), fiber (FIB), ash content (ASH), palmitic acid (PA), stearic acid (SA), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA). Descriptive analysis, Tukey's test, Lilliefors statistics, and Pearson correlation were applied. The Euclidean distance matrix generated a network of correlations, and Venn Diagrams analyzed the most promising genotypes. The analyses showed that 100 SW, an average of 15.66 %, was low. Among the seed constituents, only PC was less, with an average of 33.40 % associated with a variability of 2.02. PC and OIL presented possible polygenic control of an additive nature. The strongest correlation was between PC and OIL, with a value of −0.7. The 100 SW correlated positively with PC but negatively with FIB, indicating negligible and weak correlations, with values of 0.18 and 0.31, respectively. Collections 3 and 4 individually presented the lowest and the highest number of high-intensity interactions, respectively. The diagrams underscored the difficulty of simultaneously highlighting genotypes with superior performance considering multiple characteristics. It is concluded that except for collection 3, the genotypes presented low PC and low variability requiring the inclusion of favorable allelic forms, and genotypes with superior performance were identified on account of the characteristics 100 SW and PC or 100 SW and OIL. |
| format | Article |
| id | doaj-art-d5edc190ae4447669bdaf2f431360c29 |
| institution | OA Journals |
| issn | 1678-992X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Universidade de São Paulo |
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| series | Scientia Agricola |
| spelling | doaj-art-d5edc190ae4447669bdaf2f431360c292025-08-20T01:57:01ZengUniversidade de São PauloScientia Agricola1678-992X2025-05-018210.1590/1678-992x-2024-0018Potential of soybean [Glycine max (L.) Merrill] progenies from southern BrazilRafael Paulo da Silvahttps://orcid.org/0000-0002-3039-7593Cosme Damião Cruzhttps://orcid.org/0000-0003-3513-3391Ivan Ricardo de Carvalhohttps://orcid.org/0000-0001-7947-4900ABSTRACT This work aims to characterize and estimate soybean genotypes’ productive potential and industrial quality, understand the associations between traits and identify genotypes for a breeding program. Four collections totaling 301 genotypes were used, and ten quantitative characteristics were analyzed, including the mass of one hundred seeds (100 SW, where SW stands for seed weight), protein content (PC), oil content (OIL), fiber (FIB), ash content (ASH), palmitic acid (PA), stearic acid (SA), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA). Descriptive analysis, Tukey's test, Lilliefors statistics, and Pearson correlation were applied. The Euclidean distance matrix generated a network of correlations, and Venn Diagrams analyzed the most promising genotypes. The analyses showed that 100 SW, an average of 15.66 %, was low. Among the seed constituents, only PC was less, with an average of 33.40 % associated with a variability of 2.02. PC and OIL presented possible polygenic control of an additive nature. The strongest correlation was between PC and OIL, with a value of −0.7. The 100 SW correlated positively with PC but negatively with FIB, indicating negligible and weak correlations, with values of 0.18 and 0.31, respectively. Collections 3 and 4 individually presented the lowest and the highest number of high-intensity interactions, respectively. The diagrams underscored the difficulty of simultaneously highlighting genotypes with superior performance considering multiple characteristics. It is concluded that except for collection 3, the genotypes presented low PC and low variability requiring the inclusion of favorable allelic forms, and genotypes with superior performance were identified on account of the characteristics 100 SW and PC or 100 SW and OIL.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162025000101104&lng=en&tlng=encommercial characteristicscollectionsvariability |
| spellingShingle | Rafael Paulo da Silva Cosme Damião Cruz Ivan Ricardo de Carvalho Potential of soybean [Glycine max (L.) Merrill] progenies from southern Brazil Scientia Agricola commercial characteristics collections variability |
| title | Potential of soybean [Glycine max (L.) Merrill] progenies from southern Brazil |
| title_full | Potential of soybean [Glycine max (L.) Merrill] progenies from southern Brazil |
| title_fullStr | Potential of soybean [Glycine max (L.) Merrill] progenies from southern Brazil |
| title_full_unstemmed | Potential of soybean [Glycine max (L.) Merrill] progenies from southern Brazil |
| title_short | Potential of soybean [Glycine max (L.) Merrill] progenies from southern Brazil |
| title_sort | potential of soybean glycine max l merrill progenies from southern brazil |
| topic | commercial characteristics collections variability |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162025000101104&lng=en&tlng=en |
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