Predicting minor nutrient requirements of hazelnut shoot cultures using regression trees

Tissue culture data is non-linear in nature. Decision tree algorithms stand out in revealing the non-linear interactions and relationships between the predictors and responses. Classification and regression tree (CART), chi squared automatic interaction detector (CHAID) and exhaustive CHAID are the common decision tree algorithms. These three models were employed to predict and optimize the effect of minor mineral nutrients on shoot cultures of Corylus avellana L. cultivars. H3BO3, CuSO4·5H2O, MnSO4·H2O, Na2MoO4·2H2O and Zn(NO3)2·6H2O were tested in a range of 0.5 × to 4 × Driver and Kuniyuki (DKW) medium within a RSM optimal design. NiSO4·6H2O was also an input within the design with varying levels of 0 to 6 µM. Shoot quality and length were affected by genotype, B and Mo amounts. Multiplication rate depended on genotype, B, Zn and Cu levels. Callus formation was affected by genotype and B. Leaf size depended on genotype, Zn and Mn concentrations. Cu was a significant predictor of leaf color and Ni slightly improved SPAD readings (chlorophyll content). CART in general outperformed CHAID and exhaustive CHAID in terms of the predictive performance. Both CHAID and exhaustive CHAID failed to generate a tree model for a leaf size response. The optimal minor nutrients for hazelnuts based on the predictions of the CART algorithm were suggested to be: B 2.3 × DKW, Cu 0.5×, Mn 0.5×, 2 × Mo and Zn 2×. © 2017, This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection.Agricultural Research Service, USDA ARS: 5358-21000-033DFig. 9 ‘Jefferson’ shoot cultures grown on three growth medium formulations a 1995 Yu and Reed medium (DKW with glucose as the carbon source), b 2013 Hand and Reed medium and c CART algorithm predicted minor nutrients 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 of Turkey. We appreciate the assistance of Dr. Sugae Wada in providing the photographs of ’Jefferson’