The main aim of the present investigation is modeling and optimization of a new culture medium for in vitro rooting of G×N15 rootstock using an artificial neural network-genetic algorithm (ANN-GA). Six experiments for assessing different media culture, various concentrations of Indole – 3- butyric acid, different concentrations of Thiamine and Fe-EDDHA were designed. The effects of five ionic macronutrients (NH4+, NO3−, Ca2+, K+ and Cl−) on five growth parameters [root number (RN), root length (RL), root percentage (R%), fresh (FW) and dry weight (DW)] were evaluated using the ANN-GA method. The R2 correlation values of 0.88, 0.88, 0.98, 0.94 and 0.87 between observed and predicted values were acquired for all five growth parameters, respectively. The ANN-GA results indicated that among the input variables, K+ (7.6) and NH4+ (4.4), K+ (7.7) and Ca2+ (2.8), K+ (36.7) and NH4+ (4.3), K+ (14.7) and NH4+ (4.4) and K+ (7.6) and NH4+ (4.3) had the highest values of variable sensitivity ratio (VSR) in the data set, for RN, RL, R%, FW and DW, respectively. ANN-GA optimized LS medium for G×N15 rooting contained optimized amounts of 1 mg L−1 IBA, 100, 150, or 200 mg L−1 Fe-EDDHA and 1.6 mg L−1 Thiamine. The efficiency of the optimized culture media was compared to other standard media for Prunus rooting and the results indicated that the optimized medium is more efficient than the others.

Pistachio, one of the important tree nuts, is cultivated in arid and semi-arid regions where salinity is the most common abiotic stress encountered by this tree. However, the mechanisms underlying salinity tolerance in this plant are not well understood. In the present study, five 1-year-old pistachio rootstocks (namely Akbari, Badami, Ghazvini, Kale-Ghouchi, and UCB-1) were treated with four saline water regimes (control, 8, 12, and 16 dS m) for 100 days. At high salinity level, all rootstocks showed decreased relative water content (RWC), total chlorophyll content (TCHC), and carotenoids in the leaf, while ascorbic acid (AsA) and total soluble proteins (TSP) were reduced in both leaf and root organs. In addition, the total phenolic compounds (TPC), proline, glycine betaine, total soluble carbohydrate (TSC), and HO content increased under salinity stress in all studied rootstocks. Three different ion exclusion strategies were observed in the studied rootstocks: (i) Na exclusion in UCB-1, because most of its Na is retained in the roots; (ii) Cl exclusion in Badami, in which most of its Cl remained in the roots; and (iii) similar concentrations of Na and Cl were observed in the leaves and roots of Ghazvini, Akbari, and Kale-Ghouchi. Transport capacity (ST value) of K over Na from the roots to the leaves was more observable in UCB-1 and Ghazvini. Overall, the root system cooperated more effectively in UCB-1 and Badami for retaining and detoxifying an excessive amount of Na and Cl. The results presented here provide important inputs to better understand the salt tolerance mechanism in a tree species for developing more salt-tolerant genotypes. Based on the results obtained here, the studied rootstocks from tolerant to susceptible are arranged as follows: UCB-1 > Badami > Ghazvini > Kale-Ghouchi > Akbari.

The effects of gamma irradiation (GR) on total phenol, anthocyanin and antioxidant activity were investigated in three different Persian pistachio nuts at doses of 0, 1, 2 and 4 kGy. The antioxidant activity, as determined by FRAP and DPPH methods, revealed a significant increase in the 1-2 kGy dose range. Total phenol content (TPC) revealed a similar pattern or increase in this range. However, when radiation was increased to 4 kGy, TPC in all genotypes decreased. A radiation dose of 1 kGy had no significant effect on anthocyanin content of Kale-Ghouchi (K) and Akbari (A) genotypes, while it significantly increased the anthocyanin content in the Ghazvini (G) genotype. In addition, increasing the radiation to 4 kGy significantly increased the anthocyanin content of K and G genotypes. To conclude, irradiation could increase the phenolic content, anthocyanin and antioxidant activity of pistachio nuts.

Spatio-temporal co-occurrence patterns represent subsets of object types which are located together in both space and time. Existing algorithms for co-occurrence pattern mining cannot handle complex applications such as air pollution in several ways. First, the existing models assume that spatial relationships between objects are explicitly represented in the input data, while the new method allows extracting implicitly contained spatial relationships algorithmically. Second, instead of extracting cooccurrence patterns of only point data, the proposed method deals with different feature types that is with point, line and polygon data. Thus, it becomes relevant for a wider range of real applications. Third, it also allows mining a spatio-temporal co-occurrence pattern simultaneously in space and time so that it illustrates the evolution of patterns over space and time. Furthermore, the proposed algorithm uses a Voronoi tessellation to improve efficiency. To evaluate the proposed method, it was applied on a real case study for air pollution where the objective is to find correspondences of air pollution with other parameters which affect this phenomenon. The results of evaluation confirm not only the capability of this method for co-occurrence pattern mining of complex applications, but also it exhibits an efficient computational performance. Spatio-temporal co-occurrence patterns represent subsets of object types which are located together in both space and time. Existing algorithms for co-occurrence pattern mining cannot handle complex applications such as air pollution in several ways. First, the existing models assume that spatial relationships between objects are explicitly represented in the input data, while the new method allows extracting implicitly contained spatial relationships algorithmically. Second, instead of extracting co-occurrence patterns of only point data, the proposed method deals with different feature types that is with point, line and polygon data. Thus it becomes relevant for a wider range of real applications. Third, it also allows mining a spatio-temporal co-occurrence pattern simultaneously in space and time so that it illustrates the evolution of patterns over space and time. Furthermore, the proposed algorithm uses a Voronoi tessellation to improve efficiency. To evaluate the proposed method, it was applied on a real case study for air pollution where the objective is to find correspondences of air pollution with other parameters which affect this phenomenon. The results of evaluation confirm not only the capability of this method for co-occurrence pattern mining of complex applications, but also it exhibits an efficient computational performance.

Salinity substantially affects plant growth and crop productivity worldwide. Plants adopt several biochemical mechanisms including regulation of antioxidant biosynthesis to protect themselves against the toxic effects induced by the stress. One-year-old pistachio rootstock exhibiting different degrees of salinity tolerance were subjected to sodium chloride induced stress to identify genetic diversity among cultivated pistachio rootstock for their antioxidant responses, and to determine the correlation of these enzymes to salinity stress. Leaves and roots were harvested following NaCl-induced stress. The results showed that a higher concentration of NaCl treatment induced oxidative stress in the leaf tissue and to a lesser extent in the roots. Both tissues showed an increase in ascorbate peroxidase, superoxide dismutase, catalase, glutathione reductase, peroxidase, and malondialdehyde. Responses of antioxidant enzymes were cultivar dependent, as well as temporal and dependent on the salinity level. Linear and quadratic regression model analysis revealed significant correlation of enzyme activities to salinity treatment in both tissues. The variation in salinity tolerance reflected their capabilities in orchestrating antioxidant enzymes at the roots and harmonized across the cell membranes of the leaves. This study provides a better understanding of root and leaf coordination in regulating the antioxidant enzymes to NaCl induced oxidative stress.