AUTHOR=Jamshidi S. , Yadollahi A. , Ahmadi H. , Arab M. M. , Eftekhari M. TITLE=Predicting In vitro Culture Medium Macro-Nutrients Composition for Pear Rootstocks Using Regression Analysis and Neural Network Models JOURNAL=Frontiers in Plant Science VOLUME=7 YEAR=2016 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2016.00274 DOI=10.3389/fpls.2016.00274 ISSN=1664-462X ABSTRACT=

Two modeling techniques [artificial neural network-genetic algorithm (ANN-GA) and stepwise regression analysis] were used to predict the effect of medium macro-nutrients on in vitro performance of pear rootstocks (OHF and Pyrodwarf). The ANN-GA described associations between investigating eight macronutrients (NO3-, NH4+, Ca²⁺, K⁺, Mg²⁺, PO42-, SO42-, and Cl⁻) and explant growth parameters [proliferation rate (PR), shoot length (SL), shoot tip necrosis (STN), chlorosis (Chl), and vitrification (Vitri)]. ANN-GA revealed a substantially higher accuracy of prediction than for regression models. According to the ANN-GA results, among the input variables concentrations (mM), NH4+ (301.7), and NO3-, NH4+ (64), SO42- (54.1), K⁺ (40.4), and NO3- (35.1) in OHF and Ca²⁺ (23.7), NH4+ (10.7), NO3- (9.1), NH4+ (317.6), and NH4+ (79.6) in Pyrodwarf had the highest values of VSR in data set, respectively, for PR, SL, STN, Chl, and Vitri. The ANN-GA showed that media containing (mM) 62.5 NO3-, 5.7 NH4+, 2.7 Ca²⁺, 31.5 K⁺, 3.3 Mg²⁺, 2.6 PO42-, 5.6 SO42-, and 3.5 Cl⁻ could lead to optimal PR for OHF and optimal PR for Pyrodwarf may be obtained with media containing 25.6 NO3-, 13.1 NH4+, 5.5 Ca²⁺, 35.7 K⁺, 1.5 Mg²⁺, 2.1 PO42-, 3.6 SO42-, and 3 Cl⁻.