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Developing hazelnut tissue culture medium free of ion confounding

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Abstract

The general approach for tissue culture medium optimization is to use salts as factors in experimental design and analysis. However, using salts as factors leads to ion confounding, making it difficult to detect the effects of individual ions on particular growth responses. This study focused on testing ions as factors for the medium optimization process. NH4 +, Ca2+, Mg2+, SO4 2− and PO4 3− ions were used as factors in a D-optimal design. K+ and NO3 ions were used to bring the pH to neutral, and were also factors in the statistical analysis. The Chi-squared automatic interaction detection (CHAID) data mining algorithm was used to analyze shoot growth responses of ‘Barcelona’, ‘Jefferson’ and ‘Wepster’ hazelnuts. The CHAID analysis decision trees revealed significant variables and their interactions, and provided exact cut-off amounts for optimizing each of the ions. K+, NO3 , and NH4 + had significant effects on shoot quality. NH4 + was of primary significance for shoot length followed by Mg2+, NO3 and Ca2+. Multiplication was mainly affected by Ca2+ and genotype. For the least callus formation, NH4 + >33.3 mM was required, but this higher concentration range did not provide good shoot quality or elongation. The critical cut-off values for good shoot quality, elongation, multiplication and medium callus formation for hazelnut are suggested to be: NO3 ≤88 mM, NH4 + ≤20 mM, Ca2+ ≤5 mM, Mg2+ >5 mM and K+ ≤46 mM.

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References

  • Akin M, Eyduran E, Reed BM (2016) Use of RSM and CHAID data mining algorithm for predicting mineral nutrition of hazelnut. Plant Cell Tissue Organ Cult 128(2):303–316. doi:10.1007/s11240-016-1110-6

    Article  Google Scholar 

  • Anderson MJ, Whitcomb PJ (2005) RSM simplified: optimizing processes using response surface methods for design of experiments. Productivity Press, New York

    Google Scholar 

  • Design-Expert (2010) Stat-Ease, Inc., Minneapolis, MN

  • Díaz-Pérez FM, Bethencourt-Cejas M (2016) CHAID algorithm as an appropriate analytical method for tourism market segmentation. J Destin Mark Manag 5:275–282

    Google Scholar 

  • Driver JA, Kuniyuki AH (1984) In vitro propagation of Paradox walnut rootstock. HortScience 19(4):507–509

    Google Scholar 

  • Evens TJ & Niedz RP (2008) Are hofmeister series relevant to modern ion-specific effects research? Sch Res Exch 2008:1–9

    Google Scholar 

  • George E & de Klerk G-J (2008) The components of plant tissue culture media I: macro- and micro-nutrients. In: George EF, Hall MA, de Klerk G-J (eds) Plant propagation by tissue culture, 3rd edn. Springer, Dordrecht, pp 65–113

  • Hand C (2013) Improving initiation and mineral nutrition for hazelnut (Corylus avellana) micropropagation. Dissertation:Oregon State University, Corvallis, USA

  • Hand C, Reed BM (2014) Minor nutrients are critical for the improved growth of Corylus avellana shoot cultures. Plant Cell Tissue Organ Cult 119(2):427–439

    Article  CAS  Google Scholar 

  • Hand C, Maki S, Reed B (2014) Modeling optimal mineral nutrition for hazelnut micropropagation. Plant Cell Tissue Organ Cult 119(2):411–425

    Article  CAS  Google Scholar 

  • Hébert M, Collin-Vézina D, Daigneault I, Parent N, Tremblay C (2006) Factors linked to outcomes in sexually abused girls: a regression tree analysis. Compr Psychiatry 47:443–455

    Article  PubMed  Google Scholar 

  • Machado M, da Silva A, Biasi L, Deschamps C, Filho J, Zanette F (2014) Influence of calcium content of tissue on hyperhydricity and shoot tip necrosis of in vitro regenerated shoots of Lavandula angustifolia Mill. Braz Arch Biol Technol 57(5):636–643

    Article  CAS  Google Scholar 

  • Nas MN, Read PE (2004) A hypothesis for the development of a defined tissue culture medium of higher plants and micropropagation of hazelnuts. Sci Hortic 101(1–2):189–200

    Article  CAS  Google Scholar 

  • Niedz RP (2016) ARS-media for excel: a spreadsheet tool for calculating media recipes based on ion-specific constraints. PLoS ONE 11:e0166025

    Article  Google Scholar 

  • Niedz RP, Evens TJ (2006) A solution to the problem of ion confounding in experimental biology. Nat Methods 3(6):417

    Article  CAS  PubMed  Google Scholar 

  • Niedz RP, Evens TJ (2008) The effects of nitrogen and potassium nutrition on the growth of nonembryogenic and embryogenic tissue of sweet orange (Citrus sinensis (L.) Osbeck). BMC Plant Biol 8:126

    Article  PubMed  PubMed Central  Google Scholar 

  • Niedz RP, Hyndman SE, Evens TJ (2007) Using a gestalt to measure the quality of in vitro responses. Sci Hortic 112(3):349–359

    Article  Google Scholar 

  • Ramage C, Williams R (2002) Mineral nutrition and plant morphogenesis. Cell Dev Biol Plant 38:116–124

    Article  CAS  Google Scholar 

  • Rashidi S, Ranjitkar P, Hadas Y (2014) Modeling bus dwell time with decision tree-based methods. Transp Res Rec 2418:74–83

    Article  Google Scholar 

  • Reed BM, Wada S, DeNoma J & Niedz RP (2013) Improving in vitro mineral nutrition for diverse pear germplasm. In Vitro Cell Dev Biol 49:343–355

    Article  CAS  Google Scholar 

  • Singha S, Townsend EC, Oberly GH (1990) Relationship between calcium and agar on vitrification and shoot-tip necrosis of quince (Cydonia oblonga Mill.) shoots in vitro. Plant Cell Tissue Organ Cult 23(2):135–142

    Article  Google Scholar 

  • SPSS (2013) Statistics for Windows, Version 22.0. IBM Corp, Armonk

    Google Scholar 

  • Verbruggen N, Hermans C (2013) Physiological and molecular responses to magnesium nutritional imbalance in plants. Plant Soil 368(1):87–99

    Article  CAS  Google Scholar 

  • Wada S, Niedz RP, Reed BM (2015) Determining nitrate and ammonium requirements for optimal in vitro response of diverse pear species. In Vitro Cell Dev Biol 51(1):19–27

    Article  CAS  Google Scholar 

Download references

Acknowledgements

Funding for this study was provided by the U.S. Department of Agriculture, Agricultural Research Service CRIS project 5358-21000-033D. M. Akin was supported by a Higher Education Scholarship from the government of Turkey during Ph.D. studies at Oregon State University.

Author contributions

MA planned and executed the experiment, collected and evaluated the data, assisted with data analysis and drafted the manuscript. EE performed the CHAID statistical analysis. RPN planned the experimental design and calculated the solution recipes. BMR assisted with planning and analysis, supervised the study, and edited the manuscript.

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Correspondence to Meleksen Akin.

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Communicated by Maurizio Lambardi.

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Akin, M., Eyduran, E., Niedz, R.P. et al. Developing hazelnut tissue culture medium free of ion confounding. Plant Cell Tiss Organ Cult 130, 483–494 (2017). https://doi.org/10.1007/s11240-017-1238-z

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  • DOI: https://doi.org/10.1007/s11240-017-1238-z

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