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While numerous studies explored the response of walnut plants to drought stress (DS), there remains a significant gap in the knowledge regarding the impact of heat stress (HS) and the combined effects of DS and HS on the recovery capacity of walnut trees. This study aimed to investigate the mechanism of Persian walnut (cv. Chandler) response to the combined DS and HS, focusing on various aspects including photosynthesis, water relations, and osmotic regulation. The treatments involved subjecting plants to DS (through a withholding method for 24 d), HS (gradually up to 40 °C for 8 d), and a combined DS and HS, which were compared to a control group (no stress) during the stress and recovery phases. The results showed that DS had significantly more negative effects on chlorophyll content, relative water content (RWC), leaf water potential (WP), osmotic potential (OP) compared to HS. Involvement of osmoregulation mechanism was detected more in DS and HS plants through the accumulation of proline, glycine Betaine and total soluble carbohydrates. The functionality of photosynthesis was significantly impacted by both HS and DS, respectively. While the HS accelerated the change of the abovementioned physiological processes in drought-stressed seedlings. Consistently, more pronounced damage was found in leaves under the combined stress, alongside the decrease RWC, chlorophyll content and fluorescence ratios. Based on the analysis of the linear mixed-effect model, the effects of combined stress and HS on photosynthesis parameters were detected in the early stages of stress compared to DS. Within a range of stresses, the abovementioned physiological processes of individual and combined-stressed plants recovered to levels comparable to those of the control. Our results also showed a substantial reduction in the expression of the photosynthetic genes (Fd, Cyt b6f, and PsbB) in Persian walnut saplings under abiotic stress conditions indicating significant damage to their photosynthetic apparatus. This study highlights that, under scenarios of aggravating drought occurring with heat, walnut seedlings could face a high risk of damage to physiological structures in relation to the synergistically increased hydraulic and thermal impairments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Masson SAS. All rights reserved.)

Breeding perennial tree crops often requires prediction of mature performance from juvenile data. To assess the utility of juvenile screens to predict salinity tolerance of mature pistachio trees, we compared performance of 3-month ungrafted seedlings and 4-year-old grafted rootstocks under salinity stress. The QTL allele associated with higher salt exclusion from seedling leaves conferred lower growth in saline field conditions, suggesting that mapping QTL in seedlings may be easier than discerning the optimal allele for field performance., (© 2023. Springer Nature Limited.)

Persian walnut is a drought-sensitive species with considerable genetic variation in the photosynthesis and water use efficiency of its populations, which is largely unexplored. Here, we aimed to elucidate changes in the efficiency of photosynthesis and water content using a diverse panel of 60 walnut families which were submitted to a progressive drought for 24 days, followed by two weeks of re-watering. Severe water-withholding reduced leaf relative water content (RWC) by 20%, net photosynthetic rate (P n ) by 50%, stomatal conductance (g s ) by 60%, intercellular CO 2 concentration (C i ) by 30%, and transpiration rate (T r ) by 50%, but improved water use efficiency (WUE) by 25%. Severe water-withholding also inhibited photosystem II functionality as indicated by reduced quantum yield of intersystem electron transport (φ Eo ) and transfer of electrons per reaction center (ET 0 /RC), also enhanced accumulation of Q A (V J ) resulted in the reduction of the photosynthetic performance (PI ABS ) and maximal quantum yield of PSII (F V /F M ); while elevated quantum yield of energy dissipation (φ Do ), energy fluxes for absorption (ABS/RC) and dissipated energy flux (DI 0 /RC) in walnut families. Cluster analysis classified families into three main groups (tolerant, moderately tolerant, and sensitive), with the tolerant group from dry climates exhibiting lesser alterations in assessed parameters than the other groups. Multivariate analysis of phenotypic data demonstrated that RWC and biophysical parameters related to the chlorophyll fluorescence such as F V /F M , φ Eo , φ Do , PI ABS , ABS/RC, ET 0 /RC, and DI 0 /RC represent fast, robust and non-destructive biomarkers for walnut performance under drought stress. Finally, phenotype-environment association analysis showed significant correlation of some photosynthetic traits with geoclimatic factors, suggesting a key role of climate and geography in the adaptation of walnut to its habitat conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Masson SAS. All rights reserved.)

Aims: The present study focused on identifying the current prevalence of diabetes mellitus (DM) in rural desert and rural agricultural areas of Egypt and comparing these findings to those of previous studies that reported lower prevalence rates of DM in rural desert versus rural agricultural areas., Methods: The study included a total of 15,000 participants aged 20 years or older; 10,000 were from rural agricultural areas and 5000 were from rural desert areas in Egypt. The prevalence of DM and impaired fasting glucose for each group was recorded, participants were interviewed, medical history was obtained, physical examinations were performed, and fasting plasma glucose was used for diagnosis of DM and IFG using American Diabetes Association criteria., Results: The prevalence of DM was 12.7% in agricultural areas and 4.7% in desert areas. The prevalence of newly diagnosed cases was 15.8% and 9.9% in agricultural and desert areas, respectively. The prevalence of IFG was 11.14% in agricultural and 8.04% in desert areas. These results suggest that living in a rural area makes patients at a higher risk of developing DM (OR = 2.968 CI (2.570-3.428) p < 0.001) and IFG (OR = 1.43, CI (1.272-1.616), p < 0.001). Logistic regression analysis revealed that increased age, living in agricultural areas, higher body mass index and positive family history of diabetes were the significant predictors affecting the prevalence of DM., Conclusions: The prevalence of DM, IFG, and overall dysglycemia (DM + IFG) in Egypt has generally increased in rural areas, with a lower prevalence in rural desert compared to rural agricultural areas., (© 2022. Springer-Verlag Italia S.r.l., part of Springer Nature.)

Uncovering the genetic basis of photosynthetic trait variation under drought stress is essential for breeding climate-resilient walnut cultivars. To this end, we examined photosynthetic capacity in a diverse panel of 150 walnut families (1500 seedlings) from various agro-climatic zones in their habitats and grown in a common garden experiment. Photosynthetic traits were measured under well-watered (WW), water-stressed (WS) and recovery (WR) conditions. We performed genome-wide association studies (GWAS) using three genomic datasets: genotyping by sequencing data (∼43 K SNPs) on both mother trees (MGBS) and progeny (PGBS) and the Axiom™ Juglans regia 700 K SNP array data (∼295 K SNPs) on mother trees (MArray). We identified 578 unique genomic regions linked with at least one trait in a specific treatment, 874 predicted genes that fell within 20 kb of a significant or suggestive SNP in at least two of the three GWAS datasets (MArray, MGBS, and PGBS), and 67 genes that fell within 20 kb of a significant SNP in all three GWAS datasets. Functional annotation identified several candidate pathways and genes that play crucial roles in photosynthesis, amino acid and carbohydrate metabolism, and signal transduction. Further network analysis identified 15 hub genes under WW, WS and WR conditions including GAPB, PSAN, CRR1, NTRC, DGD1 , CYP38 , and PETC which are involved in the photosynthetic responses. These findings shed light on possible strategies for improving walnut productivity under drought stress., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nanjing Agricultural University.)

Background: Optimizing plant tissue culture media is a complicated process, which is easily influenced by genotype, mineral nutrients, plant growth regulators (PGRs), vitamins and other factors, leading to undesirable and inefficient medium composition. Facing incidence of different physiological disorders such as callusing, shoot tip necrosis (STN) and vitrification (Vit) in walnut proliferation, it is necessary to develop prediction models for identifying the impact of different factors involving in this process. In the present study, three machine learning (ML) approaches including multi-layer perceptron neural network (MLPNN), k-nearest neighbors (KNN) and gene expression programming (GEP) were implemented and compared to multiple linear regression (MLR) to develop models for prediction of in vitro proliferation of Persian walnut (Juglans regia L.). The accuracy of developed models was evaluated using coefficient of determination (R 2 ), root mean square error (RMSE) and mean absolute error (MAE). With the aim of optimizing the selected prediction models, multi-objective evolutionary optimization algorithm using particle swarm optimization (PSO) technique was applied., Results: Our results indicated that all three ML techniques had higher accuracy of prediction than MLR, for example, calculated R 2 of MLPNN, KNN and GEP vs. MLR was 0.695, 0.672 and 0.802 vs. 0.412 in Chandler and 0.358, 0.377 and 0.428 vs. 0.178 in Rayen, respectively. The GEP models were further selected to be optimized using PSO. The comparison of modeling procedures provides a new insight into in vitro culture medium composition prediction models. Based on the results, hybrid GEP-PSO technique displays good performance for modeling walnut tissue culture media, while MLPNN and KNN have also shown strong estimation capability., Conclusion: Here, besides MLPNN and GEP, KNN also is introduced, for the first time, as a simple technique with high accuracy to be used for developing prediction models in optimizing plant tissue culture media composition studies. Therefore, selection of the modeling technique to study depends on the researcher's desire regarding the simplicity of the procedure, obtaining clear results as entire formula and/or less time to analyze., (© 2022. The Author(s).)

Introduction: Pulmonary thromboembolism (PTE) is one of the most prevalent medical disorders, with a notable annual fatality rate. This study aimed to evaluated the accuracy of serum pro-BNP and troponin I levels in PTE diagnosis., Methods: This cross-sectional study was implemented on 267 patients with suspected PTE (sudden chest pain or sudden dyspnea) in Imam Reza Hospital in Mashhad, Iran. All patients underwent pulmonary computed tomography (CT) angiography (as the gold standard test) and their serum levels of troponin I and pro-BNP were measured. The screening performance characteristics of pro-BNP in detection of PTE cases were measured and reported using receiver operating characteristic (ROC) curve analysis., Results: Two-hundred-sixty-seven patients with a mean age of 67.7 ±11.5 years were evaluated (60.1% male). PTE was confirmed via CT angiography in 121 patients. The area under the ROC curve of troponin I and pro-BNP in detection of PTE was 0.501 ng/mL and 0.972 pg/mL, respectively. The sensitivity and specificity of proBNP at the best cut-off point (100 pg/ml) were 85.4% and 80.2%, respectively. The sensitivity and specificity of troponin I at the best cut-off point (0.005 ng/ml) were 65.5% and 42%, respectively., Conclusion: Due to the comparatively good sensitivity and specificity of proBNP in diagnosis of pulmonary thromboembolism, it can be employed as a diagnostic determinant in patients with suspected pulmonary thromboembolism along with other laboratory tests., Competing Interests: The authors of this article did not mention any conflict of interest.

The production and consumption of nuts are increasing in the world due to strong economic returns and the nutritional value of their products. With the increasing role and importance given to nuts (i.e., walnuts, hazelnut, pistachio, pecan, almond) in a balanced and healthy diet and their benefits to human health, breeding of the nuts species has also been stepped up. Most recent fruit breeding programs have focused on scion genetic improvement. However, the use of locally adapted grafted rootstocks also enhanced the productivity and quality of tree fruit crops. Grafting is an ancient horticultural practice used in nut crops to manipulate scion phenotype and productivity and overcome biotic and abiotic stresses. There are complex rootstock breeding objectives and physiological and molecular aspects of rootstock-scion interactions in nut crops. In this review, we provide an overview of these, considering the mechanisms involved in nutrient and water uptake, regulation of phytohormones, and rootstock influences on the scion molecular processes, including long-distance gene silencing and trans-grafting. Understanding the mechanisms resulting from rootstock × scion × environmental interactions will contribute to developing new rootstocks with resilience in the face of climate change, but also of the multitude of diseases and pests.

Background and Aim: Fasciolosis is a cosmopolitan parasitic disease of food-producing animals and is typically caused by digenetic trematodes, Fasciola gigantica and Fasciola hepatica . It has a direct negative impact on the liver and consequently affects liver metabolism. It has indirect effects, including lowered milk production and effects on quality and general health conditions leading to extensive economic losses. This study aimed to focus on the link between clinical fasciolosis and some biochemical analysis of the hepatic profile of cattle in Chad., Materials and Methods: This study was initiated in response to emerging complaints from dairy cattle owners detecting a bitter milk cream and butter taste. Furthermore, those animals had shown poor health conditions by presenting with diarrhea. Preliminary surveillance for possible causes was performed, including fecal and serum biochemical analyses and clinical observation to diagnose the possible disease., Results: The results obtained, including the finding of parasite stages during the coprological examination, confirmed the role of fasciolosis. The independent sample t-test indicated highly significantly altered values of all biochemical liver indicators in the infected animals. All animals were treated with two doses of rafoxanide (3 mg/kg b.w.) S/C, at 21 days intervals, with vitamin supplements, mineral mixtures, and food additives. Surprisingly, the main complaint was restored after treatment. This is another evident clue of fasciolosis. To the best of our knowledge, this is the first recent study that diagnosed fasciolosis in Chad., Conclusion: This study emphasized the importance of fasciolosis, its negative impact on milk taste, and the necessity for veterinary advice regarding routine examination and prophylactic measures, especially before autumn, to minimize economic losses. However, regardless of the small sample size, this study could serve as a cornerstone for future studies on evaluating the accurate epidemiological status of fasciolosis in Chad. This study reported a close association between the alteration of liver enzymes and total protein levels in fasciolosis and the bitter milk cream taste, which could be used as a diagnostic tool for fasciolosis., (Copyright: © Elshahawy, et al.)

Simplified prediction of the interactions of plant tissue culture media components is of critical importance to efficient development and optimization of new media. We applied two algorithms, gene expression programming (GEP) and M5' model tree, to predict the effects of media components on in vitro proliferation rate (PR), shoot length (SL), shoot tip necrosis (STN), vitrification (Vitri) and quality index (QI) in pear rootstocks (Pyrodwarf and OHF 69). In order to optimize the selected prediction models, as well as achieving a precise multi-optimization method, multi-objective evolutionary optimization algorithms using genetic algorithm (GA) and particle swarm optimization (PSO) techniques were compared to the mono-objective GA optimization technique. A Gamma test (GT) was used to find the most important determinant input for optimizing each output factor. GEP had a higher prediction accuracy than M5' model tree. GT results showed that BA (Γ = 4.0178), Mesos (Γ = 0.5482), Mesos (Γ = 184.0100), Micros (Γ = 136.6100) and Mesos (Γ = 1.1146), for PR, SL, STN, Vitri and QI respectively, were the most important factors in culturing OHF 69, while for Pyrodwarf culture, BA (Γ = 10.2920), Micros (Γ = 0.7874), NH4NO3 (Γ = 166.410), KNO3 (Γ = 168.4400), and Mesos (Γ = 1.4860) were the most important influences on PR, SL, STN, Vitri and QI respectively. The PSO optimized GEP models produced the best outputs for both rootstocks., Competing Interests: The authors have declared that no competing interests exist.

Walnut production is challenged by climate change and abiotic stresses. Elucidating the genomic basis of adaptation to climate is essential to breeding drought-tolerant cultivars for enhanced productivity in arid and semi-arid regions. Here, we aimed to identify loci potentially involved in water use efficiency (WUE) and adaptation to drought in Persian walnut using a diverse panel of 95 walnut families (950 seedlings) from Iran, which show contrasting levels of water availability in their native habitats. We analyzed associations between phenotypic, genotypic, and environmental variables from data sets of 609 000 high-quality single nucleotide polymorphisms (SNPs), three categories of phenotypic traits [WUE-related traits under drought, their drought stress index, and principal components (PCs)], and 21 climate variables and their combination (first three PCs). Our genotype-phenotype analysis identified 22 significant and 266 suggestive associations, some of which were for multiple traits, suggesting their correlation and a possible common genetic control. Also, genotype-environment association analysis found 115 significant and 265 suggestive SNP loci that displayed potential signals of local adaptation. Several sets of stress-responsive genes were found in the genomic regions significantly associated with the aforementioned traits. Most of the candidate genes identified are involved in abscisic acid signaling, stomatal regulation, transduction of environmental signals, antioxidant defense system, osmotic adjustment, and leaf growth and development. Upon validation, the marker-trait associations identified for drought tolerance-related traits would allow the selection and development of new walnut rootstocks or scion cultivars with superior WUE., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

Background: Predicting impact of plant tissue culture media components on explant proliferation is important especially in commercial scale for optimizing efficient culture media. Previous studies have focused on predicting the impact of media components on explant growth via conventional multi-layer perceptron neural networks (MLPNN) and Multiple Linear Regression (MLR) methods. So, there is an opportunity to find more efficient algorithms such as Radial Basis Function Neural Network (RBFNN) and Gene Expression Programming (GEP). Here, a novel algorithm, i.e. GEP which has not been previously applied in plant tissue culture researches was compared to RBFNN and MLR for the first time. Pear rootstocks (Pyrodwarf and OHF) were used as case studies on predicting the effect of minerals and some hormones in the culture medium on proliferation indices., Results: Generally, RBFNN and GEP showed extremely higher performance accuracy than the MLR. Moreover, GEP models as the most accurate models were optimized using genetic algorithm (GA). The improvement was mainly due to the RBFNN and GEP strong estimation capability and their superior tolerance to experimental noises or improbability., Conclusions: GEP as the most robust and accurate prospecting procedure to achieve the highest proliferation quality and quantity has also the benefit of being easy to use., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2019.)

Persian plateau (including Iran) is considered as one of the primary centers of origin of walnut. Sampling walnut trees originating from this arena and exploiting the capabilities of next-generation sequencing (NGS) can provide new insights into the degree of genetic variation across the walnut genome. The present study aimed to explore the population structure and genomic variation of an Iranian collection of Persian walnut (Juglans regia L.) and identify loci underlying the variation in nut and kernel related traits using the new Axiom J. regia 700K SNP genotyping array. We genotyped a diversity panel including 95 walnut genotypes from eight Iranian provinces with a variety of climate zones. A majority of the SNPs (323,273, 53.03%) fell into the "Poly High Resolution" class of polymorphisms, which includes the highest quality variants. Genetic structure assessment, using several approaches, divided the Iranian walnut panel into four principal clusters, reflecting their geographic partitioning. We observed high genetic variation across all of the populations (H O  = 0.34 and H E  = 0.38). The overall level of genetic differentiation among populations was moderate (F ST  = 0.07). However, the Semnan population showed high divergence from the other Iranian populations (on average F ST  = 0.12), most likely due to its geographical isolation. Based on parentage analysis, the level of relatedness was very low among the Iranian walnuts examined, reflecting the geographical distance between the Iranian provinces considered in our study. Finally, we performed a genome-wide association study (GWAS), identifying 55 SNPs significantly associated with nut and kernel-related traits. In conclusion, by applying the novel Axiom J. regia 700K SNP array we uncovered new unexplored genetic diversity and identified significant marker-trait associations for nut-related traits in Persian walnut that will be useful for future breeding programs in Iran and other countries.

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 (NH 4 + , NO 3 - , Ca 2+ , 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 R 2 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 Ca 2+ (2.8), K + (36.7) and NH 4 + (4.3), K + (14.7) and NH 4 + (4.4) and K + (7.6) and NH 4 + (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.

The efficiency of a hybrid systems method which combined artificial neural networks (ANNs) as a modeling tool and genetic algorithms (GAs) as an optimizing method for input variables used in ANN modeling was assessed. Hence, as a new technique, it was applied for the prediction and optimization of the plant hormones concentrations and combinations for in vitro proliferation of Garnem (G × N15) rootstock as a case study. Optimizing hormones combination was surveyed by modeling the effects of various concentrations of cytokinin-auxin, i.e., BAP, KIN, TDZ, IBA, and NAA combinations (inputs) on four growth parameters (outputs), i.e., micro-shoots number per explant, length of micro-shoots, developed callus weight (CW) and the quality index (QI) of plantlets. Calculation of statistical values such as R 2 (coefficient of determination) related to the accuracy of ANN-GA models showed a considerably higher prediction accuracy for ANN models, i.e., micro-shoots number: R 2 = 0.81, length of micro-shoots: R 2 = 0.87, CW: R 2 = 0.88, QI: R 2 = 0.87. According to the results, among the input variables, BAP (19.3), KIN (9.64), and IBA (2.63) showed the highest values of variable sensitivity ratio for proliferation rate. The GA showed that media containing 1.02 mg/l BAP in combination with 0.098 mg/l IBA could lead to the optimal proliferation rate (10.53) for G × N15 rootstock. Another objective of the present study was to compare the performance of predicted and optimized cytokinin-auxin combination with the best optimized obtained concentrations of our other experiments. Considering three growth parameters (length of micro-shoots, micro-shoots number, and proliferation rate), the last treatment was found to be superior to the rest of treatments for G × N15 rootstock in vitro multiplication. Very little difference between the ANN predicted and experimental data confirmed high capability of ANN-GA method in predicting new optimized protocols for plant in vitro propagation.

Drought stress is the major limiting factor which affects turfgrass management in area with restricted rainfall or irrigation water supply. Trinexapac ethyl (TE), Paclobutrazol (PAC) and Abscisic acid (ABA) are three plant growth regulators (PGRs) that are commonly used on turf species for increasing their tolerance to different environmental stresses such as drought. However, little is known about the impact of PGRs on stress tolerance of Iranian Perennial ryegrass (Lolium perenne). The present study was conducted to examine the visual and physiological changes of Iranian Perennial ryegrass in response to foliar application of TE, PAC, and ABA under drought stress conditions. According to the obtained results, application of all three PGRs considerably restored visual quality of drought exposed plants. TE treatment increased chlorophyll content, proline content and resulted in less malondialdehyde (MDA) in drought stressed Perennial ryegrass. Application of all PGRs enhanced the relative water content (RWC) and decreased the electrolyte leakage (EL) and Hydrogen peroxide contents (H 2 O 2 content) of plants under drought stress, though the impact of TE was more pronounced. Throughout the experiment, TE- and ABA-treated plant showed greater soluble sugar (SSC) content as compared to the control. Antioxidant enzymes activities of drought exposed plants were considerably increased by PGRs application. Catalase (CAT) and Superoxide dismutase (SOD) activities were greater in TE-treated grasses followed by PAC-treated plants. Ascorbate peroxidase (APX) and peroxidase (POD) activities were significantly enhanced by TE and ABA application. The results of the present investigation suggest that application of TE, ABA and PAC enhances drought tolerance in Perennial ryegrass. TE, PAC and ABA were all effective in mitigating physiological damages resulting from drought stress, however the beneficial effects of TE were more pronounced. The result obtained of real time-PCR suggested that regulation of CAT, APX, POD and SOD genes expression at translational levels highly depended on the application of TE, PAC and ABA. Also, the results showed that deletion mutation in SOD and POD genes were not leading to enzyme inactivation., (Copyright © 2016 Elsevier Masson SAS. All rights reserved.)

One of the major obstacles to the micropropagation of Prunus rootstocks has, up until now, been the lack of a suitable tissue culture medium. Therefore, reformulation of culture media or modification of the mineral content might be a breakthrough to improve in vitro multiplication of G × N15 (garnem). We found artificial neural network in combination of genetic algorithm (ANN-GA) as a very precise and powerful modeling system for optimizing the culture medium, So that modeling the effects of MS mineral salts ([Formula: see text], [Formula: see text], [Formula: see text], Ca 2+ , K + , [Formula: see text], Mg 2+ , and Cl - ) on in vitro multiplication parameters (the number of microshoots per explant, average length of microshoots, weight of calluses derived from the base of stem explants, and quality index of plantlets) of G × N15. Showed high R correlation values of 87, 91, 87, and 74 between observed and predicted values were found for these four growth parameters, respectively. According to the ANN-GA results, among the input variables, [Formula: see text] and [Formula: see text] had the highest values of VSR in data set for the parameters studied. The ANN-GA showed that the best proliferation rate was obtained from medium containing (mM) 27.5 [Formula: see text], 14 [Formula: see text], 5 Ca 2 correlation values of 87, 91, 87, and 74 between observed and predicted values were found for these four growth parameters, respectively. According to the ANN-GA results, among the input variables, [Formula: see text] and [Formula: see text] had the highest values of VSR in data set for the parameters studied. The ANN-GA showed that the best proliferation rate was obtained from medium containing (mM) 27.5 [Formula: see text], 14 [Formula: see text], 5 Ca 2+ , 25.9 K + , 0.7 Mg 2+ . The performance of the medium optimized by ANN-GA, denoted as YAS (Yadollahi, Arab and Shojaeiyan), was compared to that of standard growth media for all - . The performance of the medium optimized by ANN-GA, denoted as YAS (Yadollahi, Arab and Shojaeiyan), was compared to that of standard growth media for all Prunus rootstock, including the Murashige and Skoog (MS) medium, (specific media) EM, Quoirin and Lepoivre (QL) medium, and woody plant medium (WPM) Prunus . With respect to shoot length, shoot number per cultured explant and productivity (number of microshoots × length of microshoots), YAS was found to be superior to other media for in vitro multiplication of G × N15 rootstocks. In addition, our results indicated that by using ANN-GA, we were able to determine a suitable culture medium formulation to achieve the best in vitro productivity.

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 (NO[Formula: see text], NH[Formula: see text], Ca(2+), K(+), Mg(2+), PO[Formula: see text], SO[Formula: see text], 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), NH[Formula: see text] (301.7), and NO[Formula: see text], NH[Formula: see text] (64), SO[Formula: see text] (54.1), K(+) (40.4), and NO[Formula: see text] (35.1) in OHF and Ca(2+) (23.7), NH[Formula: see text] (10.7), NO[Formula: see text] (9.1), NH[Formula: see text] (317.6), and NH[Formula: see text] (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 NO[Formula: see text], 5.7 NH[Formula: see text], 2.7 Ca(2+), 31.5 K(+), 3.3 Mg(2+), 2.6 PO[Formula: see text], 5.6 SO[Formula: see text], and 3.5 Cl(-) could lead to optimal PR for OHF and optimal PR for Pyrodwarf may be obtained with media containing 25.6 NO[Formula: see text], 13.1 NH[Formula: see text], 5.5 Ca(2+), 35.7 K(+), 1.5 Mg(2+), 2.1 PO[Formula: see text], 3.6 SO[Formula: see text], and 3 Cl(-).