Skip to main content
Log in

Selection of Genipa americana L. seed trees by genetic divergence in fruit, seeds, and seedlings

  • Research Article
  • Published:
Genetic Resources and Crop Evolution Aims and scope Submit manuscript

Abstract

The understanding of the source’s genetic characteristics and their use in restoration projects is essential to maintaining restoration survival, mainly in tropical forests. Considering that genetics should be examined in forest restoration projects, analyses with phenotypic characters are more practical to implement in forest nurseries. Genipa americana L. is an essential species in producing seedlings for restoration purposes. This study aimed to select G. americana seed trees for seed collection in an area of the Atlantic Forest through the genetic divergence study in fruit, seeds, and seedlings. The study was conducted in the Saltinho Biological Reserve in Tamandaré - PE, Brazil. The ripe fruit of 11 G. americana seed trees were collected. The physical and physicochemical characterization of the fruit, biometric characterization of the seeds, and seed emergence analysis were performed. The Selegen REML/BLUP software, model 81, was used for genetic analyses, and the cluster analysis was performed by the unweighted pair group method with arithmetic mean (UPGMA) method. A seed tree selection index was also used. The effects of the seed tree determination coefficients were low because there was considerable interaction between the sites where each one was inserted. It is possible to state that each variable contributes to explaining the genetic dissimilarity between the seed trees. Seed trees 1, 4, and 6 had the best average ranks for most of the variables analyzed concerning genotypes. The Saltinho Biological Reserve proved to be a good source of genetic and reproductive material for the species G. americana for forest restoration purposes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Abud HF, Araujo RF, Pinto CMF et al (2018) Caraterização morfométrica dos frutos de pimentas malagueta e biquinho. Rev Bras Agropecuária Sustentável 8:29–39

    Google Scholar 

  • Agência Estadual de Meio Ambiente (CPRH) (2001) Diagnóstico socioambiental. Litoral sul de Pernambuco, Recife

  • Agência Estadual de Meio Ambiente (CPRH) (2011) Área De Proteção Ambiental De Guadalupe - ENCARTE, vol 3. Análise da Unidade de Conservação, Recife

    Google Scholar 

  • AOAC International (2016) Official methods of analysis of AOAC International

  • Atkinson RJ, Thomas E, Roscioli F et al (2021) Seeding resilient restoration: an indicator system for the analysis of tree seed systems. Diversity 13:367. https://doi.org/10.3390/d13080367

    Article  Google Scholar 

  • Arouisse B, Theeuwen TPJM, van Eeuwijk FA, Kruijer W (2021) Improving genomic prediction using high-dimensional secondary phenotypes. Front Genet 12:715. https://doi.org/10.3389/FGENE.2021.667358/BIBTEX

    Article  Google Scholar 

  • Azevedo AM (2021) ExpImage-package: ExpImage: experimental image analysis tools in ExpImage. Tool for analysis of images in experiments

  • Braga Filho JR, Naves RV, Chaves LJ et al (2014) Caracterização física e físico-química de frutos de araticum (Annona Crassiflora Mart). Biosci J 30:16–24

    Google Scholar 

  • Brandani JZ, Junglos MS, Santiago EF et al (2018) Are seeds of Genipa americana L. (Rubiaceae) tolerance to water submersion? Floresta e Ambient 25:20170764. https://doi.org/10.1590/2179-8087.170764

    Article  Google Scholar 

  • Carvalho AV, Chaves RPF, Alves RM (2017) Caracterização física e físico-química de frutos em matrizes de cajazeira no Estado do Pará. Belém

  • Chazdon R, Brancalion P (2019) Restoring forests as a means to many ends. Science (80-) 364:24–25. https://doi.org/10.1126/SCIENCE.AAX9539

    Article  Google Scholar 

  • Correia LAdaS, Felix FC, dos Araújo F et al (2019) Morphometric descriptors and physiological seed quality for selecting Aspidosperma pyrifolium Mart. Matrix trees. Rev Caatinga 32:751–759. https://doi.org/10.1590/1983-21252019V32N319RC

    Article  Google Scholar 

  • Costa RB, Resende MDV, de Gonçalves P et al (2010) Predição de parâmetros e valores genéticos para caracteres de crescimento e produção de látex em progênies de seringueira. Bragantia 69:49–56. https://doi.org/10.1590/S0006-87052010000100007

    Article  Google Scholar 

  • Cunha FLR, Bernhard R, Vogt RC (2020) Diet of an assemblage of four species of turtles (Podocnemis) in the Rio Uatumã, Amazonas, Brazil. 101643/CE-18-117 108:103–115. https://doi.org/10.1643/CE-18-117

  • da Santos PC S (2021) Divergência genética em progênies de Mimosa caesalpiniifolia Benth. Via análise de imagens e estresse salino em sementes. UFRPE

  • de Moraes CB, de Carvalho EV, Zimback L et al (2015) Variabilidade genética em progênies de meios-irmãos de eucaliptos para tolerância ao frio. Rev Árvore 39:1047–1054. https://doi.org/10.1590/0100-67622015000600007

    Article  Google Scholar 

  • de Vieira FA, Gusmão E (2008) Biometria, armazenamento de sementes e emergência de plântulas de Talisiaesculenta Radlk. (Sapindaceae). Ciência Agrotecnologia 32:1073–1079. https://doi.org/10.1590/S1413-70542008000400006

    Article  Google Scholar 

  • Fundação SOS Mata Atlântica (2020) Relatório anual 2020

  • Fundação SOSM, Atlântica, Instituto Nacional de Pesquisas Espaciais (2020) Atlas dos remanescentes florestais da Mata Atlântica: Período 2018–2019. São Paulo

  • Golunski CM, Miotto SPS, Junior CV et al (2015) Diversity and genetic structure in Ocotea odorifera (Vell.) Rohwer (Lauraceae) from southern Brazil. Perspectiva 39:41–52

    Google Scholar 

  • Holl KD, Brancalion PHS (2020) Tree planting is not a simple solution. Science 368:580–581. https://doi.org/10.1126/SCIENCE.ABA8232/SUPPL_FILE

    Article  CAS  PubMed  Google Scholar 

  • Hssaini L, Hanine H, Razouk R et al (2020) Diversity screening of fig (Ficus Carica L.) germplasm through integration of Morpho-agronomic and biochemical traits. Int J Fruit Sci 20:939–958. https://doi.org/10.1080/15538362.2019.1700871

    Article  Google Scholar 

  • IAL (2008) Métodos físico-químicos para análise de alimentos. Brasília

  • IBAMA (2003) Resumo executivo do plano de manejo da Reserva Biológica de Saltinho. Brasília

  • Jansson G, Hansen JK, Haapanen M et al (2016) The genetic and economic gains from forest tree breeding programmes in Scandinavia and Finland. Scand J For Res 32:273–286. https://doi.org/10.1080/02827581.2016.1242770

    Article  Google Scholar 

  • Kassambara A, Mundt F (2020) Factoextra: extract and visualize the results of multivariate data analyses

  • Kassambra A (2017) Practical guide to principal component methods in R, 1st edn

  • Kavaliauskas D, Šeho M, Baier R, Fussi B (2021) Genetic variability to assist in the delineation of provenance regions and selection of seed stands and gene conservation units of wild service tree (Sorbus torminalis (L.) Crantz) in southern Germany. Eur J For Res 140:551–565. https://doi.org/10.1007/S10342-020-01352-X

    Article  CAS  Google Scholar 

  • Kijowska-Oberc J, Staszak AM, Kamiński J, Ratajczak E (2020) Adaptation of forest trees to rapidly changing climate. Forests 11:123. https://doi.org/10.3390/F11020123

    Article  Google Scholar 

  • Lima EL (2006) Álgebra linear

  • Lima MAO, Mielke MS, Lavinsky AO et al (2010) Growth and phenotypic plasticity of three woody species with potential use in agroforestry systems. Sci For 38:527–534

    Google Scholar 

  • Lovatel QC, Navroski MC, Gerber TR et al (2021) Genetic variability in juvenile characters of progenies of Apuleia leiocarpa. Floresta 51:547–556. https://doi.org/10.5380/rf.v51

    Article  Google Scholar 

  • Madrera RR, Negrillo AC, Valles BS, Fernández JJF (2020) Characterization of extractable phenolic profile of common bean seeds (Phaseolus vulgaris L.) in a Spanish diversity panel. Food Res Int 138:109713. https://doi.org/10.1016/j.foodres.2020.109713

    Article  CAS  Google Scholar 

  • Mahalanobis PC (1936) On the generalized distance in statistics. In: National Institute of Science of India. pp 49–55

  • Manoel RO, Freitas MLM, Barreto MA et al (2014) Development and characterization of 32 microsatellite loci in Genipa americana (Rubiaceae). Appl Plant Sci 2:1300084. https://doi.org/10.3732/apps.1300084

    Article  Google Scholar 

  • Manoel RO, Freitas MLM, Júniro EF et al (2015) Individual, fruit, and annual variation in correlated mating in a Genipa Americana population. Silvae Genet 64:108–116. https://doi.org/10.1515/sg-2015-0010

    Article  Google Scholar 

  • Manoel RO, Freitas MLM, Tambarussi EV et al (2015) Mendelian inheritance, genetic linkage, and genotypic disequilibrium at microsatellite loci in Genipa americana L. (Rubiaceae). Genet Mol Res 14:8161–8169. https://doi.org/10.4238/2015.July.27.4

    Article  CAS  PubMed  Google Scholar 

  • Mazhula O, Fuchylo Y, Hayda Y et al (2021) Progeny testing of Pinus sylvestris L. of seed orchard in different environmental conditions. Ecol Quest 33:1–14. https://doi.org/10.12775/EQ.2022.002

    Article  Google Scholar 

  • Melo MF, de Sebbenn V, Rossini AM et al (2021) Estimating genetic diversity, mating system and pollen dispersal to inform ex situ conservation of the tree Genipa americana L. Plant Genet Resour 19:9–19. https://doi.org/10.1017/S1479262121000022

    Article  CAS  Google Scholar 

  • Oles A, Pau G, Smith M et al (2020) EBImage: image processing and analysis toolbox for R version 4.32.0 from Bioconductor

  • Pádua GP, Zito RK, Arantes NE, França Neto JD (2010) Influência do tamanho da semente na qualidade fisiológica e na produtividade da cultura da soja. Rev Bras Sementes 32:9–16. https://doi.org/10.1590/S0101-31222010000300001

    Article  Google Scholar 

  • Peng Y, Wang G, Cao F, Fu FF (2020) Collection and evaluation of thirty-seven pomegranate germplasm resources. Appl Biol Chem 63:15. https://doi.org/10.1186/s13765-020-00497-y

    Article  CAS  Google Scholar 

  • Pires HRA, Franco AC, Piedade MTF et al (2018) Flood tolerance in two tree species that inhabit both the amazonian floodplain and the dry Cerrado savanna of Brazil. AoB Plants 10:ply065. https://doi.org/10.1093/aobpla/ply065

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Potter KM, Jetton RM, Bower A et al (2017) Banking on the future: progress, challenges and opportunities for the genetic conservation of forest trees. New for 48:153–180. https://doi.org/10.1007/S11056-017-9582-8

    Article  Google Scholar 

  • Rabbani ARC, Silva-Mann R, Ferreira RA (2012) Variabilidade genética De Genipa americana L. Pertencente Ao Baixo Curso do Rio São Francisco. Rev Arvore 36:401–409. https://doi.org/10.1590/S0100-67622012000300002

    Article  CAS  Google Scholar 

  • Ragusa-Netto J (2015) Ecologia alimentar do aracuã-do-pantanal (Ortalis canicollis) em uma floresta ripária no Pantanal Sul. Braz J Biol 75:49–57. https://doi.org/10.1590/1519-6984.07113

    Article  CAS  PubMed  Google Scholar 

  • Resende MDV (2002) Genética biométrica e estatística no melhoramento de plantas perenes. Embrapa Florestas 975

  • Resende MD (2007) Matemática E estatística na análise de experimentos e no melhoramento genético. Embrapa Florestas, Colombo

    Google Scholar 

  • Resende MD (2015) Genética quantitativa e de populações, 1st edn. Suprema, Viçosa

    Google Scholar 

  • Resende MDV (2016) Software SENelegen-REML/BLUP: a useful tool for plant breeding. Crop Breed Appl Biotechnol 16:330–339

    Article  Google Scholar 

  • Resende MDV, Duarte JB (2007) Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesqui Agropecuária Trop 37:182–194

    Google Scholar 

  • Ruzza DAC, Rossi AAB, Bispo RB (2018) The genetic diversity and population structure of Genipa Americana (Rubiaceae) in Northern Mato Grosso, Brazil. Genet Mol Res 17:gmr18017. https://doi.org/10.4238/gmr18017

    Article  Google Scholar 

  • Sebbenn AM (2002) Número De árvores matrizes e conceitos genéticos na coleta de sementes para reflorestamentos com espécies nativas. Rev do Inst Florest 14:115–132

    Article  Google Scholar 

  • Sebbenn AM, Siqueira ACM de F, Kageyama PY, Machado JAR (1998) Parâmetros genéticos na conservação da cabreúva—Myroxylon peruiferum L.F. Allemão. Sci For 53:31–38

  • Silva AVC, Freire KCS, Lédo A, da S, Rabbani ARC (2014) Diversity and genetic structure of jenipapo (Genipa americana L.) Brazilian accessions. Sci Agric 71:387–393. https://doi.org/10.1590/0103-9016-2014-0038

    Article  Google Scholar 

  • Silva LGC, Moreira JFL, Holanda HBB et al (2018) Evaluation of carnauba progenies and estimates of genetic parameters in the juvenile phase. Rev Caatinga 31:917–925. https://doi.org/10.1590/1983-21252018V31N414RC

    Article  Google Scholar 

  • Silva AV, Silva AVC, Muniz EN et al (2015) Genetic diversity and sex identification in Genipa americana L. Trop Subtrop Agroecosysts 18:1

    Google Scholar 

  • Silveira GF, Aparecida A, Rossi B et al (2019) Análise biométrica de frutos e sementes de passiflora Cristalina Vanderplank & Zappi. Nativa 7:138–144. https://doi.org/10.31413/NATIVA.V7I2.6554

    Article  Google Scholar 

  • Siqueira MVBM, Bajay MM, Grando C et al (2021) Genetic diversity of reintroduced tree populations of Casearia sylvestris in Atlantic forest restoration sites. For Ecol Manag 502:119703. https://doi.org/10.1016/J.FORECO.2021.119703

    Article  Google Scholar 

  • Solís-Guillén I, Chaires-Pacheco M, Juárez-Gómez J et al (2017) Development of an ideotype-based selection tool for native tropical tree breeding by smallholder planters in Mexico’s Maya Forest. Small-Scale For 16:521–534. https://doi.org/10.1007/s11842-017-9368-z

    Article  Google Scholar 

  • Souza RR, Oliveira Paiva PD, Souza AR et al (2021) Morpho-anatomical changes and antioxidant enzyme activity during the acclimatization of Genipa americana. Acta Physiol Plant 43:1–10. https://doi.org/10.1007/S11738-021-03263-9

    Article  Google Scholar 

  • Team RC (2020) R: A language and environment for statistical computing

  • Thomas E, Jalonen R, Loo J et al (2014) Genetic considerations in ecosystem restoration using native tree species. For Ecol Manag 333:66–75. https://doi.org/10.1016/j.foreco.2014.07.015

    Article  Google Scholar 

  • UN (2021) Restoration decade: program of United Nations for the Environment Report. New York

  • Veloso HP, Rangel Filho AL, Lima JCA (1991) Classificação da vegetação brasileira, adaptada a um sistema universal. IBGE, Rio de Janeiro

    Google Scholar 

  • Wei T, Simko V (2017) R package corrplot: visualization of a correlation matrix

  • Wickham H (2016) ggplot2: Elegant graphics for data analysis

Download references

Acknowledgements

To Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), for the financial support to conduct the research. To the Forest Seeds Analysis Laboratory and the Laboratory of Physical-Chemical Food Analysis at UFRPE.

Funding

The authors state no funding involved.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Raquel Elvira Cola.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cola, R.E., da Penha Moreira Gonçalves, M., Maciel, M.I.S. et al. Selection of Genipa americana L. seed trees by genetic divergence in fruit, seeds, and seedlings. Genet Resour Crop Evol (2023). https://doi.org/10.1007/s10722-023-01798-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10722-023-01798-z

Keywords

Navigation