Late-spring frost is increasingly damaging walnut orchards worldwide, underscoring the urgent need for late-leafing cultivars adapted to climate instability. Despite extensive genomic resources in Juglans regia, additional robust markers for leafing date are still needed to enhance breeding efficiency. Here, we combine high-density genotyping-by-sequencing (GBS) with multi-model genome-wide association analysis (GWAS) to dissect the genetic architecture of leafing date in a uniquely diverse panel of 85 Iranian walnut genotypes and commercial cultivars evaluated over three consecutive years. Leafing date was defined as the stage when 50

Somatic embryogenesis (SE) is an important technique for clonal propagation and conservation of Juglans regia L.; however, its efficiency is limited by low embryo maturation and germination rates. Traditional optimization approaches often fail to capture the complex and nonlinear interactions among plant growth regulators (PGRs) and culture conditions. This study aimed to integrate machine learning (ML) modeling with multi-objective optimization to enhance SE development in Persian walnut cv. Chandler. Four ML algorithms (k-nearest neighbors (KNN), support vector machine (SVM), AdaBoost, and CatBoost) were evaluated for their ability to predict embryo size, maturation percentage, and germination percentage based on eight culture parameters. Among them, CatBoost demonstrated the highest predictive accuracy (R² = 0.95, 0.97, and 0.67 for embryo size, maturation, and germination, respectively) and the lowest error metrics across all traits. Using CatBoost as the predictive engine in combination with the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), an optimal culture protocol was identified for maximizing germination. The protocol consisted of basal DKW medium supplemented with 21.73 g L⁻¹ sucrose, 2.72 mg L⁻¹ abscisic acid (ABA), 4.06

This review summarizes major advances in Persian walnut biotechnology, emphasizing progress in propagation, somatic embryogenesis, genome editing, and computational tools while outlining key challenges for large-scale propagation and genetic improvement. In vitro culture is fundamental for uniform and large-scale propagation of Persian walnut. Over the past decades, significant improvements have enhanced plant adaptability and survival during transfer to ex vitro environments. Commonly used explants, such as shoot buds, nodal segments, and shoot tips, show variable success depending on genetic, physiological, and environmental factors, as well as culture media composition. Somatic embryogenesis and plant regeneration form the basis for several biotechnological approaches, including haploid production for genomic mapping, mutation analysis, and hybrid development. Recent advances in genome editing, particularly CRISPR/Cas9, have accelerated the creation of cultivars with improved rooting ability, enhanced resistance to biotic stresses, and better tolerance to drought and salinity. Moreover, the integration of machine learning and computational tools has facilitated high-throughput phenotyping, reducing experimental time and cost. Despite these achievements, challenges such as genotype-dependent recalcitrance, oxidative browning, and low transformation efficiency continue to limit large-scale applications. Addressing these obstacles through optimized culture systems and molecular tools will be essential for realizing the full potential of Persian walnut biotechnology. This review provides an integrated overview of recent advances, identifies persistent challenges, and highlights future directions for improving propagation efficiency and accelerating genetic enhancement in this valuable tree species.

Salinity and drought are key abiotic stresses limiting Persian walnut (Juglans regia) productivity worldwide, particularly in arid and semi-arid regions. To address these challenges and enhance stress tolerance, somatic embryos of J. regia cv. Chandler were co-transformed with flavodoxin (Fld) and betaine aldehyde dehydrogenase (BADH) genes using Agrobacterium tumefaciens harboring the binary vector pBI121. Putative transgenic embryos were selected on antibiotic media and directed to germination and plantlet regeneration. Polymerase chain reaction (PCR) analysis confirmed that transgene had successfully integration into the genomes of four lines 4, 6, 10, and 12 with a transformation efficiency of 4.44

Developing late-leafing genotypes is crucial for mitigating the impact of late-spring frosts in walnut cultivation. Marker-assisted selection (MAS) offers a rapid screening approach for walnut populations in breeding programs, addressing the long breeding cycle. This study aimed to validate Turkish molecular markers associated with leafing date in the Iranian walnut populations and to implement MAS to identify late-leafing genotypes. Two polymorphic SSR primers, ‘JRHR209732’ and ‘CUJ-RBO12’, were validated using 14 early- and late-leafing cultivars/genotypes. MAS was then implemented for a population of 91 Iranian walnuts from a breeding program. The results indicated the effective differentiation of the Iranian population using the markers from Turkey, suggesting genetic similarity between the walnut populations of the two countries. Furthermore, alleles with band sizes of 277 and 115 were associated with late-leafing, while band sizes of 289 and 92 indicated early-leafing. Phenological data over three consecutive years, along with SSR analysis, confirmed the validation and implementation of MAS. The SSR analysis identified 14 alleles across all accessions, with an average of 7 alleles per locus. High leafing time variation was observed in the studied population, and cluster analysis identified four major clusters, revealing similarities and dissimilarities among the accessions. Finally, genotypes ‘Ch35T12’, ‘ChLa1’, ‘ChFr2’, ‘ChFr3’, ‘Ped35T1’, ‘Ped35T4’, ‘PedLa1’, ‘PedLa3’, ‘PedOp1’, and ‘ChPed2’ were identified as late-leafing genotypes based on screening with late-leaf alleles.

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.

Root architecture critically influences plant growth and survival. Pistachio plants face challenges because of the limited lateral roots within a taproot system and the poor survival rates if the primary root tip is severed during transplantation. This study investigated the effects of radicle-tip cutting (RC) on lateral root formation and growth of Pistacia vera L. ‘Ohadi’ seedlings. A factorial experiment with varying radicle lengths (L1-L5) and cutting site portions (CS1-CS5) was conducted. Control plants had an intact radicle tip. Following treatment, seedlings were transferred to 2 L pots filled with perlite, and nourished weekly with half-strength Hoagland's solution. After nine weeks, growth parameters and root characteristics were assessed. Results indicated that optimal radicle-tip cutting occurred at a radicle length of 2–3 cm (L3), with an ideal cutting distance of 3 mm from the radicle-tip (CS3). This treatment (L3CS3) led to improved growth (plant height, leaf area, shoot fresh weight (FW), root FW, shoot dry weight (DW), root DW) and root architecture (number of lateral roots (NLR), network depth (NWDP), network volume (NWVL), network convex area (NWCA) parameters, enhancing plant vitality. These findings offer valuable insights for nurserymen aiming to produce pistachio seedlings with robust lateral roots and higher post-transplantation survival rates.

EDITORIAL article Front. Plant Sci., 21 August 2023Sec. Crop and Product Physiology Volume 14 - 2023 | https://doi.org/10.3389/fpls.2023.1264597

Plant tissue culture media composition prediction is valuable and can diminish the spending time and costs of releasing protocols. The present study assessed the possibility of using some imperative supervised Machine Learning (ML1) algorithms, including Support Vector Machine (SVM2), Gene Expression Programming (GEP3), and Gradient Boosting Decision Tree (GBDT4), in predicting optimized in vitro media composition for prolifer-ation and rooting of Salvia macrosiphon Boiss. and comparing them with a linear regression method, i.e., Bayesian Ridge Regression (BRR5). Input parameters included different concentrations of macro-and micro-nutrients, vitamins, and Plant Growth Regulators (PGRs6). The accuracy of constructed models' performance was inves-tigated according to Root Mean Square Error (RMSE7), Mean Absolute Percentage Error (MAPE8), and Coefficient of Determination (R2 9). Particle Swarm Optimization (PSO10) system was employed to optimize the developed formulations using superior prediction models. Results revealed that ML methods had higher prediction accuracy than BRR. The GEP models were subsequently selected for optimization by PSO. According to hybrid GEP-PSO models, modified MS medium including 0.54 x NH4NO3, 1.94 x KNO3, 0.93 x CaCl2, KH2PO4, MgSO4, 2.65 x minors, 1.28 x vitamins, and myoinositol and supplemented with 0.93 mg/L 6-benzylaminopurine (BAP11) and 0.05 mg/L indole-3-acetic acid (IBA12) could bring about optimal proliferation. Based on the same models, MS medium containing 0.72 x macros, 1.49 x minors, 1.23 x vitamins and myoinositol, 0.37 x sucrose and 1.73 x FeEDDHA and supplemented with 1.97 mg/L 1-naphthaleneacetic acid (NAA13) and 0.53 mg/L IBA could result in the optimized rooting. This study shows the effectiveness of GBDT as an advanced ML algorithm for predicting the formulation of plant tissue culture media. GEP-constructed models were selected for optimization due to the simplicity and clearness of their results as an entire formula. At the same time, two more ML models used in this study also have adequate accuracy to be selected by the researcher.

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 (Pn) by 50%, stomatal conductance (gs) by 60%, intercellular CO2 concentration (Ci) by 30%, and transpiration rate (Tr) 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 (φEo) and transfer of electrons per reaction center (ET0/RC), also enhanced accumulation of QA (VJ) resulted in the reduction of the photosynthetic performance (PIABS) and maximal quantum yield of PSII (FV/FM); while elevated quantum yield of energy dissipation (φDo), energy fluxes for absorption (ABS/RC) and dissipated energy flux (DI0/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 FV/FM, φEo, φDo, PIABS, ABS/RC, ET0/RC, and DI0/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.

In recent years, temperate nut tree breeding programmes have been accelerated as a result of the increasing demand for their production. High yield with desirable kernel characteristics and disease-resistance are the main breeding objectives of temperate nut trees cultivars. In addition, leading challenges especially global warming and climate change dictate new objectives such as low-chilling requirements and tolerance to late-spring and early-autumn frosts, etc. Various conventional and molecular strategies are used to achieve these breeding objectives. The utilisation of genetic resources and targeted hybridisation are the main conventional breeding strategies of temperate nut trees which along with molecular breeding can help to accelerate the breeding programmes. The advancement of genome sequencing technologies, high-quality and quantity of molecular data accelerated breeding programmes and lowered their price for temperate tree nut crops. Therefore, future researches in breeding of tree nut trees should be directed towards construction of fully annotated reference genomes, discovery of genes controlling traits of interest and finding molecular markers linked to these genes to be used for marker assisted selection (MAS) or genomic selection (GS), through constructing saturated linkage maps, QTLs mapping, genome-wide association mapping, along with omics techniques. In this chapter, some important breeding objectives and strategies of temperate nut trees including walnuts, pistachios, almonds, pecans, hazelnuts and chestnut have been discussed with emphasis on recent findings.

Nut tree species have a great economic and cultural value for many countries across the world. Their highly nutritious content makes them one of the most favourite healthy foods of the global population, with strong evidence of their positive impact on human health. Nut tree crops are very diverse in terms of nut chemical content and shape, growing climates, and domestication history. However, all of them have a very long juvenile phase thatmakes classical breeding challenging and time consuming. Also, their cultivation is very resource demanding. The application of genomic-assisted breeding can accelerate the development of adaptive cultivars of nut tree species. In this article, we summarize recent successes in genomics for nut tree crops, specifically almond, chestnut, hazelnut, pecan, pistachio, and walnut. We report the recent discoveries on the genetic control of target traits for the genetic improvement of these species, with suggestions for future directions and breeding applications.

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.

Simple sequence repeat (SSR) markers were used to authenticate ramets of 11 Persian walnut ( Juglans regia L.) varieties. All varieties and 28 of their ramets (n = 39) were genotyped with 17 SSR markers. The genetic profiles revealed two off-types: the ramets Serr 4 (S4) and Vina 1 (V1). SSR fingerprints individuating 11 walnut varieties were possible using 13 polymorphic SSRs that could be used in the future to identify clones of these varieties. Except for ‘Chandler’, each cultivar could be distinguished using a combination of two SSR loci. This result emphasizes the efficacy of the SSR markers in true-to-type validation of walnut orchards.

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 (R2), 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 R2 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.

Abstract 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 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.

As one of the main origin centers of nut trees, Iran is the fourth leading nut crops producer in the world (6% of total nut production). Due to the high genetic diversity, development of new varieties and rootstocks with desirable characteristics have been highly considered by fruit breeders in Iran. In this regard, molecular breeders concentrate on filling the gaps in the conventional breeding with the aim of accelerating breeding programs. Recent advancements in molecular breeding such as next-generation sequencing (NGS) techniques, high-throughput genotyping platforms and genomics-based approaches including genome wide association studies (GWAS), and genomic selection (GS) have opened up new avenues to enhance the efficiency of nut trees breeding. Over the past decades, Iranian nut crops breeders have successfully used advanced molecular and genomic tools such as molecular markers, genetic transformations and high-throughput genotyping to explore the genetic basis of the desired traits and eventually to develop new varieties and rootstocks. Due to a broad international cooperation, a clear perspective is envisaged for the nut breeding programs in Iran, especially based on new biotechnology techniques. The propagation of nut trees in Iran have also been dramatically improved. Different types of grafting and tissue culture (micropropagation or somatic embryogenesis) techniques for propagation of nut crops have been studied intensively in the last 30 years in Iran and the successful techniques have been commercialized. Several certified nurseries are producing grafted and micropropagation plants of walnut, pistachio and other nut crops commercially. A part of the grafted and micropropagaited plants of nut crops in Iran is being exported to the other countries. Establishing modern orchards of nut crops using new cultivars and rootsocks is presently being advised by professional consultants.

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.

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.