|Abstract or Summary
- Hazelnut is one of the most important nuts in worldwide production and the European hazelnut (Corylus avellana L.) is the most economically important of the 11 recognized hazelnut species. Development of new cultivars is continuous, with emphasis on better nut quality, high yield and disease resistance. Hazelnuts are highly heterozygous, and clonally propagated. Traditional propagation methods in hazelnut are not rapid enough to provide the required nursery stock for newly released hazelnut cultivars, but micropropagation can provide rapid production of hazelnut planting stock. Several growth media are available for specific cultivars, but many are not suitable for the wide range of germplasm used in new cultivars.
Micropropagation of hazelnuts remains challenging due to the various responses of diverse genotypes to in vitro growth. Several studies incrimentally improved the growth medium, but determining exact nutrient requirements was difficult. The aim of this study was to determine which statistical methods would make the growth medium optimization process more practical and to develop an optimal micropropagation medium for diverse hazelnuts by testing salts and ions as factors within the experimental design. In addition an SSR fingerprinting set suitable for a diverse group of hazelnuts was developed.
The first study was designed to test the effect of salts on three hazelnut genotypes and compare two methods of data analysis. Driver and Kuniyuki Walnut medium (DKW) macro-salts (NH₄NO₃, Ca(NO₃)₂∙4H₂O, CaCl₂∙2H₂O, MgSO₄∙7H₂O, KH₂PO₄ and K₂SO₄) were varied from 0.5× to 3× DKW concentrations with 42 combinations in a IV-optimal design. Shoot quality, shoot length, multiplication and callus formation were rated and analyzed using Response Surface Methodology (RSM) and the Chi-Squared Automatic Interaction Detection (CHAID) data mining algorithm. Both analyses indicated that NH₄NO₃ was a predominant nutrient factor. RSM results were genotype dependent while CHAID included genotype as a factor in the analysis, allowing development of a common medium rather than several genotype-specific media. Overall, CHAID results were more specific and easier to interpret than RSM graphs. The optimal growth medium for diverse hazelnut genotypes was formulated as: 0.5× NH₄NO₃, 3× KH₂PO₄, 1.5× Ca(NO₃)₂ and and the rest of the macro salts set at 1× DKW with modified minor nutrients [4× H₃BO₃, 4× Na₂MoO₄∙2H₂O, 4× Zn(NO₃)₂∙6H₂O, 0.5× MnSO₄∙H₂O, 0.5× CuSO₄∙5H₂O].
The second study was to determine the effects of ions on tissue culture medium optimization. NH₄⁺, Ca²⁺, Mg²⁺, SO₄²⁻ and PO₄³⁻ ions were used as factors in a D-optimal design. K⁺ and NO₃⁻ ions were used to bring the pH level to neutral, and as factors in the statistical analysis. The CHAID data mining algorithm was used to analyze shoot growth responses of three hazelnut genotypes. The algorithm trees revealed significant variables and their interactions, and provided exact cut-off amounts for each of the ions for the related growth response by incorporating genotype as an independent factor. The critical cut-off values for good shoot quality, elongation, multiplication and medium callus formation were suggested to be: NO₃⁻ <88 mM, NH₄⁺ <20 mM, Ca²⁺ <5 mM, Mg²⁺ >5 mM and K⁺ <46 mM.
Another step of the research was to develop a reliable and economical fingerprinting set consisting of high core-repeat SSRs (≥3) for genotype identification of 102 hazelnut accessions. Identification of trueness-to-type by phenotypic observation is very difficult and labeling mistakes during the several steps of micropropagation can result in costly errors. The use of SSRs for plant identification is preferred over other molecular markers because they are reproducible across laboratories, exhibit co-dominant inheritance, have a large number of alleles per locus and are randomly distributed throughout the genome. Twenty SSRs containing repeat motifs of three or more nucleotides distributed throughout the hazelnut genome were screened on eight genetically diverse cultivars to assess polymorphism, allele size range, and ease of scoring. Six SSRs were discarded after genotyping 96 hazelnut samples, either due to large allele bin widths and/or alleles that do not match the motifs, complicating allele scoring. Fourteen polymorphic, easy-to-score SSRs with non-overlapping alleles were selected and amplified in a single multiplex. The multiplexed set generated the same alleles that were obtained when amplifying each SSR individually in the eight test accessions. SSR primer concentrations were then optimized to generate a clear signal for each locus. This 14-SSR fingerprinting set was used to genotype 102 hazelnut accessions, and distinguished unique accessions mainly according to parentage and in some cases based on geographic origin.
As a result of these studies, salt- and ion-based optimized tissue culture medium formulations were developed for diverse hazelnuts. The importance of salts and ions as factors within the experimental design and analysis was examined, and using salts as factors results in complexity within the design as the effects of ions can not be determined. Although salt optimization studies are still a powerful tool, and are experimentally easier, optimization at the ionic level provided a clearer evaluation of the ion-based growth responses, because the plants take up minerals as ions of the corresponding salts. Data mining (CHAID) was used to make the tissue culture optimization process more practical compared to analysis with the standard ANOVA, regression and RSM. CHAID delineated specific concentrations that were effective and allowed easier analysis of nutrient content for an improved medium. A reliable and cost-effective multiplexed fingerprinting set of 14 SSR markers was developed for confirming identity and paternity in diverse hazelnut cultivars and species and 102 accessions were fingerprinted.