Agronomic characteristics, mineral nutrient content, antioxidant capacity, biochemical composition, and fatty acid profile of Iranian pistachio (Pistacia vera L.) cultivars

Abstract

Background

Pistachio (Pistacia vera L.) nuts are among the most popular nuts. The pistachio cultivars are tolerant to both drought and salinity, which is why they are extensively grown in the arid, saline, and hot regions of the Middle East, Mediterranean countries, and the United States.

Results

This study evaluated the agronomic and chemical characteristics of 10 pistachio cultivars (‘Abbasiali’, ‘AhmadAghaei’, ‘Akbari’, ‘Chrook’, ‘Fandoghi’, ‘KalehGhoochi’, ‘Momtaz’, ‘Rezaei’, ‘Sefied’, and ‘Shahpasand’). Total phenolic content, antioxidant capacity, fruit mineral elements, soluble protein content, kernel-oil content, and fatty-acid composition were determined in 60 fruits (20 fruits per replication). Leaf mineral elements were determined in 450 leaves (150 leaves per replication). Significant differences were observed (p < 0.05) among the cultivars, with the coefficient of variation (CV) ranging from 1.03 (unsaturated fatty acids) to 115.16% (early nut splitting). Flower buds varied from 4 (‘AhmadAghaei’) to 7 (‘Momtaz’), and fruit per bunch ranged from 11 (‘Abbasiali’) to 21 (‘Momtaz’). Hull percentage ranged from 36.8 (‘KalehGhoochi’) to 43.1% (‘Chrook’), and nut percentage ranged from 56.3 (‘Chrook’) to 62.4% (‘KalehGhoochi’). Iron content in leaves ranged from 267 (‘Chrook’) to 367 mg/kg (‘Rezaei’), while iron in fruits ranged from 65.72 (‘Fandoghi’) to 81.90 mg/kg (‘Sefied’). Total phenolic content varied from 99.9 (‘Rezaei’) to 184.30 mg/g (‘Fandoghi’), and antioxidant activity ranged from 39.14 (‘Shahpasand’) to 82.89% (‘Sefied’). Oil content ranged from 49.26 (‘Rezaei’) to 67.72% (‘AhmadAghaei’), with oleic acid between 48.4 (‘Rezaei’) and 55.55% (‘KalehGhoochi’). Leaf phosphorus positively correlated with split nut percentage (r = 0.669) and negatively with blank nut percentage (r = -0.734). Fruit potassium strongly correlated with total phenolics (r = 0.917) and oleic acid (r = 0.654). Multiple regression analysis showed that blank nut percentage was negatively correlated with leaf zinc (β = -0.77) and positively with antioxidants (β = 0.77). Early nut splitting showed a negative correlation with antioxidants (β = -0.72). The first three principal components (PC1 = 22.48%, PC2 = 18.15%, PC3 = 15.82%) explained 56.45% of the total variation. Heat map analysis using Ward clustering revealed cultivar groupings based on traits like nutrient content and fatty acid composition.

Conclusions

The findings obtained in this study allow producers to select the most suitable cultivars for obtaining more efficient and high-quality products. Additionally, choosing cultivars based on environmental factors and market demands contributes to the development of more effective production strategies. The ultimate goal is to provide insights that guide the selection of pistachio cultivars optimized for both agricultural sustainability and market-specific requirements.

Introduction

Pistachio (Pistacia vera L.), a perennial tree from the Anacardiaceae family, is valued not only for its economic significance but also for its exceptional nutritional and health-promoting properties, driving high global demand [42, 43]. The pistachio kernel is a versatile food, consumed in dried, fresh, or salted roasted forms. It is rich in unsaturated fatty acids like oleic and linoleic acids, known for their health benefits, along with protein, carbohydrates, dietary fiber, and essential micronutrients such as calcium, potassium, phosphorus, iron, and copper [8, 62]. Additionally, pistachios provide vitamins and phenolic compounds that enhance their antioxidative properties [38, 70]. Natural antioxidants, including carotenoids, flavonoids, and phytoestrogens, contribute to reduced oxidative stress and inflammation, supporting cardiovascular health and potentially reducing chronic disease risks [1, 53].

The pistachio tree has deep historical roots, with cultivation dating back to ancient Asia Minor, particularly in Iran, Türkiye, Lebanon, Syria, and Afghanistan, where it adapted to arid and semi-arid climates [71]. Pistachios require hot summers for fruit development and chilling winters for dormancy. Its resilience to poor-quality soils has enabled its spread beyond Asia Minor into the Mediterranean and parts of Asia, making it a valuable crop for resource-limited regions [17]. According to 2022 FAO data, global pistachio production totals 1,108,502.7 tons annually. The United States leads with 400.070 tons (36.09%), followed by Iran (241.668,58 tons, 21.80%), Türkiye (239.289 tons, 21.59%), China (163.399,6 tons, 14.74%), and Syria (45.467 tons, 4.1%), collectively accounting for 98.3% of global output [16].

Iran’s role in pistachio cultivation is notable for its remarkable genetic diversity, with over 70 cultivars exhibiting a wide range of morphological, physiological, and biochemical traits. Popular cultivars like Kaleh-Ghoochi, Ahmad-Aghaei, and Rezaei are valued for their unique characteristics, including variations in nut size, shape, shell split percentage, and yield potential. The Kaleh-Ghoochi cultivar, in particular, is prized for its large, round kernels, light green color, and high yield, contributing to its popularity in both domestic and international markets [15]. These cultivar-specific traits are key in breeding programs aimed at improving yield, quality, and tolerance to environmental stress, thereby helping producers meet the global market’s diverse demands.

Nutritionally, pistachios are rich in fats, with 50–70% of their composition being lipid-based. These fats are mostly unsaturated fatty acids, primarily oleic and linoleic acids, which make up about 80%, contributing to the nut’s reputation as a heart-healthy food. Research shows that regular consumption of pistachios can improve lipid profiles by increasing high-density lipoprotein (HDL) levels and reducing low-density lipoprotein (LDL) levels, thus lowering overall cardiovascular risk [22, 25]. In addition to their beneficial fat profile, pistachios are a dense source of high-quality protein, essential amino acids, and vitamins (especially A, E, B1, and B6), along with minerals that support various bodily functions. Pistachios also contain phytochemicals like phenolic compounds, flavonoids, and carotenoids, which enhance their antioxidative properties, making them a valuable dietary source for managing oxidative stress and inflammation.

Recent studies have highlighted the medicinal potential of pistachio extracts, particularly the gum, which has shown antiviral, antimicrobial, antifungal, and anti-cancer properties, expanding pistachio’s use beyond nutrition into pharmaceutical applications [22]. These bioactive compounds offer potential therapeutic benefits and contribute to the development of functional foods and nutraceuticals derived from pistachio, addressing the growing demand for natural, health-promoting products.

Despite extensive research on pistachio’s nutritional and health benefits, few studies focus on the comparative agro-morphological and biochemical characteristics of multiple cultivars, particularly Iranian cultivars grown under similar conditions. This study aims to fill this gap by analyzing the agro-morphological, nutritional, and biochemical profiles of selected Iranian pistachio cultivars. By characterizing traits such as kernel size, shell split percentage, mineral content, and fatty acid profile, the research seeks to provide insights for cultivar selection and breeding, supporting advancements in pistachio cultivation that meet both agronomic and nutritional needs. The findings are expected to help agronomists, nutritionists, and industry stakeholders improve their understanding of cultivar-specific traits and develop strategies to enhance production, quality, and market competitiveness in pistachio agriculture.

Materials and methods

Plant material

The research was conducted in 2022 and 2023 at a commercial orchard located in Jafariyeh City, Qom province (34˚50’24"N, 50˚45’03"E, and 946 m height above sea level), Iran (Fig. 1), characterized by a semi-arid climate, an average annual rainfall of 136 mm, and an average annual temperature of 19˚C. Agronomic and chemical characterizations of 10 pistachio cultivars (‘Abbasiali’, ‘AhmadAghaei’, ‘Akbari’, ‘Chrook’, ‘Fandoghi’, ‘KalehGhoochi’, ‘Momtaz’, ‘Rezaei’, ‘Sefied’, and ‘Shahpasand’) were evaluated. The cultivars were average 20 years old and were healthy and in full fruiting stage. The orchard management operations, including nutrition, irrigation, and pest and disease control, were performed regularly and uniformly for the cultivars. The formal identification of the specimens was performed by Prof. Dr. Ali Khadivi. A herbarium voucher specimen with sediment number PV-66,533 has been donated to the public available herbarium of the Faculty of Agriculture and Natural Resources of Arak University, Iran.

Fig. 1

Geographic location of the collection site of the studied pistachio cultivars

Pomological characteristics

The evaluation of cultivars was carried out using 16 pomological characters. The evaluated traits include flower bud number, abscised bud flower number, fruit number in bunch, hull percentage, nut percentage, dry nut to fresh nut ratio, split nut percentage, blank nut percentage, unsplit nut percentage, kernel percentage, shell percentage, tendency to early nut splitting, endocarp lesion, nut number per ounce, 1000-nut weight, and yield. Firstly, in the growing season, four branches in each cultivar were randomly selected in four directions of the tree, and flower bud number and abscised bud flower number were counted. Secondly, after fruit ripening, all the bunches were collected from each tree and then their fresh weight was measured with a digital scale and calculated in kg per hectare as yield. Thirdly, after harvesting, 10 bunches were randomly selected for each cultivar, then 100 fruits were collected, and were used to evaluate the quality characteristics after harvesting from different directions. The total number of fruits was separated from the bunches, and the average number of fruits per bunch the percentage of endocarp lesion, and the percentage of tendency to early nut splitting were counted, and then the green hull of the ripe fruits was separated, and weighed, and after drying, the dry nut percentage was calculated. From each cultivar, the number of 100 nuts was counted, and split nut percentage, blank nut percentage, and unsplit nut percentage were recorded, and then the ratio of kernel weight to dry nut weight in 100 g of nut was considered as kernel percentage. To determine the size of the nut, the number of nuts in one ounce (each ounce equals 28.3 g) was counted. 1000-nut weight was measured using a digital scale.

Chemical characteristics

Total phenolic content

For extract preparation, 1 g of kernel tissue was homogenized in 80% methanol and centrifuged at 6000 g for 10 min. The Total phenolic content was determined by mixing 0.1 ml of the obtained extract with 2 ml of 7% sodium carbonate and 0.1 ml of Folin-Ciocalteu reagent. Absorbance was recorded at 720 nm [56]. Total phenolic content of pistachio cultivars was determined in 60 fruits, with three replications and 20 fruits in each replication.

Antioxidant capacity

Antioxidant activity was evaluated using the DPPH (1,1-diphenyl-2-picrylhydrazyl) assay according to the method of Dehghan and Khoshkam [13]. The methanolic extract was added to 2 ml of DPPH solution (0.1 mM in methanol), and the reaction mixture was vortexed for 2 min at 1000 rpm (DLAB MX-S Vortex Mixer, 100–3000 rpm). The mixtures were then incubated in the dark at room temperature for 30 min. Finally, the inhibition of DPPH radical activity was determined by measuring the reduction in DPPH absorbance at 517 nm (Abs sample) using a spectrophotometer (ONDA VIS-10 Plus, VIS 325–1000 nm, ONDA Laboratori s.r.l., Perugia, Italy). As a control, the absorbance of a blank DPPH solution (2 ml) was also measured at 517 nm (Abs control). The percentage of radical scavenging activity (% inhibition) was calculated using the following formula:

The DPPH activity (% inhibition) = [(Abs control - Abs sample) / Abs control] ×100.

Antioxidant capacity of pistachio cultivars was determined in 60 fruits, with three replications and 20 fruits in each replication.

Antioxidant capacity

Antioxidant activity was assessed using the DPPH assay following the method of Dehghan and Khoshkam [13]. Methanolic extract was added to DPPH solution, and the inhibition of DPPH radical activity was calculated as a percentage using the formula:

The DPPH activity (% inhibition) = [(Abs control - Abs sample) / Abs control] ×100.

Leaf mineral elements

To measure the leaf mineral elements in the leaves, first, the leaves were collected from the middle of the branches without spikes from the treated trees, and to remove the dust, fertilizers, and toxins on the surface of the leaves, they were washed with ordinary water containing 1% dishwashing liquid and after washing with distilled water, we dried the samples in an oven at a temperature of 60 ˚C until they reached a constant weight, and then they were powdered by a grinder. Then, each of the food elements was used in a more digestible method. In this method, 5 ml of concentrated nitric acid (65%) was added to 0.5 g of leaf powder, and the samples were placed in a Bain-Marie for 2 h at a temperature of 65 ˚C. After removing the samples and cooling them to the laboratory temperature, 1.3 ml of 20% hydrogen peroxide was added to each of the samples. After performing this reaction and cooling the samples, they were filtered using Whatman 42 filter paper and brought to a volume of 25 ml with distilled water. Before starting the work, we diluted the control sample and the plant extract in the ratio of 3 + 1 with distilled water. We zeroed the film photometer with distilled water, then gave the standard 50 to the device and set the device to 100. This process was repeated several times to ensure that the device was set between zero and 100. In the next step, we gave the other standards to the device and noted the read number, then we gave one cc of each sample to the device and recorded the read number.

The zinc content in leaves was measured by the method of Chapman and Pratt (1961). In this method, we weigh one g of the obtained sample powder into a porcelain mug and place it in an electric furnace at a temperature of 55 ˚C for 5 to 6 h until they are burned and turn into a white-gray color. After cooling down, add 5 ml of 6 normal hydrochloric acids to the obtained ash, and after stirring for half an hour and several times with a plastic tube in a 100 ml volumetric flask with distilled water, mix again. We hit about 30 min later, we filtered the obtained solution with Whatman No. 42 paper. The zinc content in the leaf was directly measured using an atomic absorption device (AA.932, GBC) and after calibrating the device with standards related to this element, it was expressed as ppm in the results.

For Fe measurement, one g of the plant sample was placed in a 50 ml Erlenmeyer flask, and 10 ml of a normal hydrochloric acid solution was added to it, and then it was placed on a shaker for 16 h. Finally, the solution was passed through filter paper and the concentration of active Fe was read by atomic absorption (Spectra 220 model, Varian, USA). Leaf mineral elements of pistachio cultivars were determined in 450 leaves, with three replications and 150 leaves in each replication.

Fruit mineral elements

To measure phosphorus, after acid digestion, the samples were filtered and brought to volume without adding hydrogen peroxide. Phosphovanadium molybdate complex formation method was used to measure the mentioned element. The absorbance value of the samples was read at the wavelength of 430 nm using a spectrophotometer [20]. To measure calcium, a laboratory kit (REF model, 506 − 10, Zit Chem Company, made in Iran) was used using 0.50 g of each powdered sample. The basis of this method is that calcium ions in an alkaline medium create a purple complex with cresol phthalein reagent. The intensity of the resulting color is proportional to the amount of calcium in the sample, which was measured at a wavelength of 580 –550 nm. Fruit mineral elements of pistachio cultivars were determined in 60 fruits, with three replications and 20 fruits in each replication.

Soluble protein content

To measure total soluble protein content, first 0.50 of the kernel was extracted with 5 ml of extraction buffer, completely crushed in a Chinese mortar and this mixture was centrifuged for 20 min at 6000 rpm. Soluble protein content was determined using the Bradford colorimetric method [6], and its absorbance was read with a spectrophotometer (model Kerry 100, Australia) at a wavelength of 595 nm. Using the standard curve prepared from different concentrations of bovine serum albumin, the soluble protein content was expressed as mg/g of fresh weight. Soluble protein content of pistachio cultivars was determined in 60 fruits, with three replications and 20 fruits in each replication.

Kernel-oil content and fatty-acid composition

The fat content of kernels was extracted using hexane as solvent. A 1 g sample of grounded kernels was mixed with 3 mL of n-hexane. The mixture was sonicated in an ultrasonic bath with a constant frequency of 40 kHz at room temperature for 3 h before being centrifuged at 15,000 rpm for 10 min. The fat portion was recuperated by n-hexane evaporation using a stream of nitrogen. Fatty-acid methyl esters (FAMEs) were prepared according to the method described by Carbonell-Barrachina et al. [9] using identical chromatography setup and conditions. Identification of FAMEs was carried out on 50 mg of extracting oil by comparison with authentic standards from Sigma-Aldrich. This analysis was run in triplicate, and results were expressed as percent of the total area.

Kernel oil extraction was performed using hexane as a solvent and a soxhlet apparatus. Dried kernels were ground, weighed, and introduced in soxhlet cartridges before immersion in hexane for 72 min at 130 C, solvent washing for 20 min, and finally solvent recovery for 30 min. After complete evaporation of the solvent, the buckets containing the oil were weighed. The percent of fat content (FC) relative to dry matter was calculated. Kernel-oil content and fatty-acid composition of pistachio cultivars were determined in 60 fruits, with three replications and 20 fruits in each replication.

Statistical analysis

In this study, a randomized block design was followed, which helps to control for potential environmental variations. Total phenolic content, antioxidant capacity, fruit mineral elements, soluble protein content, kernel-oil content, and fatty-acid composition of pistachio cultivars were determined in 60 fruits, with three replications and 20 fruits in each replication. Additionally, leaf mineral elements of pistachio cultivars were determined in 450 leaves, with three replications and 150 leaves in each replication. Analysis of variance (one-way ANOVA, p < 0.05) using JMP^® Pro 17 software [27] was used to determine the phenotypic variation among cultivars based on the recorded traits. Pearson correlation coefficients (r) were used to determine the relationship between the recorded traits using JMP^® Pro 17 software. To identify the most important influencing traits in the grouping of cultivars, principal component analysis (PCA) was applied using JMP^® Pro 17 software. Heat map analysis (HMA) based on Ward’s method and Euclidean distance coefficients using Origin Pro^® 2024b software [46] was used to classify cultivars and variables. The first and second principal components (PC1/PC2) were used to draw a two-dimensional biplot by determining the distribution of cultivars and variables using Origin Pro^® 2024b software. Moreover, fruit-related traits were considered as a dependent variable and the traits affecting these characters were determined using multiple regression analysis (MRA). The MRA was conducted using ‘‘stepwise’’ method of ‘‘linear regression analysis’’ option of SPSS^® (SPSS Inc., Chicago, IL, USA) statistics [44].

Results and discussion

Descriptive statistics among cultivars

Statistical descriptive parameters for agronomic and chemical traits used to study pistachio cultivars, along with detailed TUKEY results, are presented in Tables 1 and 2, respectively. Accordingly, one-way ANOVA (p < 0.05) showed significant differences among the examined cultivars. The highest variation was observed in tendency to early nut splitting (115.16%), followed by unsplit nut percentage (99.42%), abscised bud flower number (45.76%), blank nut percentage (45.22%), and rest fatty acids (36.58%). In contrast, the lowest variation was recorded in kernel percentage (4.69%), palmitic acid (4.51%), oleic acid (4.50%), nut percentage (3.42%), and unsaturated fatty acids (1.03%). This dataset offers a detailed profile of agronomic, biochemical, and nutritional traits, reflecting the crop’s versatility and potential for targeted improvements. The wide ranges in various traits suggest significant genetic variability or environmental influences, providing opportunities for optimization in cultivation, breeding, and product quality.

Table 1 Statistical descriptive parameters for agronomic and chemical traits used to study pistachio cultivars

Table 2 Detailed TUKEY results of statistical descriptive parameters for agronomic and chemical traits used to study pistachio cultivars

The data reveal variability in flower bud numbers ranging from 4 (‘AhmadAghaei’) to 7 (‘Momtaz’) and abscised flower bud counts ranging from 0.77 (‘AhmadAghaei’) to 2.52 (‘Akbari’). These parameters are critical indicators of reproductive efficiency and the plant’s ability to sustain flowering under varying environmental conditions. The abscission process in pistachio trees, involving the shedding of flower buds, is influenced by various biochemical and hormonal factors. This process begins with increased respiration, signaling the onset of abscission [55, 65]. Although research has shown that ethylene and gibberellins play a role in abscission, they are not the main factors involved in the shedding of pistachio flower buds [60, 66]. Additionally, factors like auxins and respiration rates also influence this process, highlighting that flower bud shedding is an important indicator of tree health and productivity. By shedding weak or non-viable buds, the tree conserves resources, ensuring that energy is redirected toward the growth of healthy, productive buds and fruits. This not only leads to improved yield and fruit quality but also promotes overall tree health by minimizing stress and the risk of disease or pest infestations. Flower bud shedding, therefore, ensures that the tree’s resources are utilized efficiently, maximizing both its vitality and productivity [60, 66]. The fruit number per bunch, ranging from 11 (‘Abbasiali’) to 21 (‘Momtaz’), indicates moderate productivity in pistachio trees. This could be influenced by factors such as successful pollination and nutrient availability, both of which are crucial for proper fruit set and development [7, 30]. The moderate fruit yield suggests that while the tree can produce a reasonable number of fruits, external factors such as pollination failure or nutrient limitations could be limiting factors in achieving higher yields. Rezaei et al. [50] reported that the fruit number in a bunch ranged from 4.33 to 46. Our findings fall within the range identified in their study. In terms of resource allocation, the hull percentage of 36.8 (‘KalehGhoochi’) to 43.1 (‘Chrook’) and nut percentage of 56.3 (‘Chrook’) to 62.4 (‘KalehGhoochi’) indicate that pistachio trees prioritize nut production. This allocation is critical because the nut is the commercially valuable part of the pistachio, which determines the economic return [19, 26]. The tree’s strategy of investing energy in nut development aligns with the need to maximize production of the economically valuable component of the pistachio crop, which is crucial for the overall yield and market value.

The dry nut to fresh nut ratio, ranging from 31.1% (‘Fandoghi’) to 40.2% (‘Shahpasand’), reflects post-harvest processing considerations, where higher values may indicate lower moisture content, which is beneficial for storage and shelf life. The split nut percentage, ranging from 28.3% (‘KalehGhoochi’) to 88.4% (‘AhmadAghaei’), and unsplit nut percentage, ranging from 5.1% (‘Rezaei’) to 57.7% (‘KalehGhoochi’), exhibit substantial variability, pointing to differences in genetic traits or environmental stresses that affect kernel accessibility and market value. Similarly, the blank nut percentage, ranging from 4.5% (‘Momtaz’) to 16.3% (‘Sefied’), signals potential issues with pollination or nutrient deficiencies. The kernel percentage, ranging from 51.9% (‘KalehGhoochi’) to 58.9% (‘Momtaz’), and shell percentage, ranging from 40.2% (‘Momtaz’) to 47.7% (‘KalehGhoochi’), highlight a favorable kernel-to-shell ratio, an important factor for consumer preference and profitability. In a similar study conducted in Iran on pistachios, the split nut percentage ranged from 0 to 97.37, the blank nut percentage ranged from 2.63 to 98.46, and the kernel percentage ranged from 27.84 to 92.17 [50].

The tendency for early nut splitting, ranging from 1% (‘Abbasiali’) to 12% (‘Shahpasand’), could be linked to specific environmental stresses or genetic predispositions, which may affect harvest timing and quality [34]. Endocarp lesions ranging from 27% in ‘Rezaei’ to 56% in ‘KalehGhoochi’ suggest challenges related to pest resistance or environmental stress, impacting nut quality and marketability [41]. Yield data ranging from 3000 kg/ha in ‘Shahpasand’ to 5300 kg/ha in ‘KalehGhoochi’ kg/ha highlight the crop’s potential under optimal conditions but also reveal room for improvement through agronomic practices or genetic advancements [10]. Additionally, the number of nuts per ounce, ranging from 22 (in ‘Rezaei’) to 28 (in ‘Fandoghi’), provides a measure of nut size and quality, offering further insights into the crop’s overall productivity and the potential impacts of cultivation practices on harvest outcomes. Our findings are parallel to the findings of the study conducted by Rezaei et al. [50]. In our study, the 1000-nut weight was detected to range from 998 g (in ‘Fandoghi’) to 1278 g (in ‘Chrook’). Pourian et al. [48] determined that the 1000-nut weight ranged from 460 to 1420 g. Our findings fall within the value range determined by the researchers.

The study highlights the notable differences in nutrient content between fruits and leaves, showcasing the vital role of leaves as reservoirs of essential minerals. Iron levels, for instance, are substantially higher in leaves, ranging from 267 (‘Chrook’) to 367 (‘Rezaei’) mg/kg DW, compared with fruits, which range from 65.76 (‘Fandoghi’) to 81.95 (‘Sefied’) mg/kg DW. This indicates the significant bioaccumulation of this mineral in foliage [61]. Tavallali and Rahemi [61] in a similar study found that the iron content in leaves ranged from 89.16 to 133.64 mg/kg, while in fruits it ranged from 7.29 to 25.89 mg/kg. Our findings are higher than those reported by the researchers. Iron is crucial for preventing anemia and supporting oxygen transport in the body. Similarly, calcium levels in leaves ranged from 0.57 (‘Abbasiali’) to 1.20 (‘Momtaz’) mg/kg DW, while in fruits, these values ranged from 0.05 (‘Akbari’) to 0.1 (‘Chrook’) mg/kg DW. Tavallali and Rahemi [61] detected that calcium levels in leaves ranged from 3.15 to 5.62 mg/kg, while in fruits, they ranged from 0.39 to 1.31 mg/kg. Our findings are lower than those of the researchers. Calcium plays a vital role in bone health and cellular functions.

Interestingly, zinc content exhibited a more balanced distribution, in fruits ranging from 22.91 (‘Akbari’) to 42.38 (‘Abbasiali’) mg/kg DW and in leaves ranging from 20.75 (‘Fandoghi’) to 30.01 (‘AhmadAghaei’) mg/kg DW. Zinc is essential for immune function and wound healing, underscoring the nutritional value of both plant parts for this trace element. Meanwhile, the phosphorus and potassium levels were exclusive to fruits, with ranges of 0.10 (‘Rezaei’) to 0.28 (‘Chrook’) mg/kg DW and 0.15 (‘Rezaei’) to 0.41 (‘Fandoghi’) mg/kg DW, respectively. Our zinc findings are similar to those of Kazankaya et al. [32], who conducted studies on similar topics, while our phosphorus and potassium findings align with those of Tavallali and Rahemi [61]. The potassium content in the fruit is lower than the findings of Pourian et al. [48]. The differences in some nutrients in fruits and leaves compared with previous studies are due to variations across species, cultivars, and ecological conditions [63]. Phosphorus and potassium minerals are vital for energy metabolism and maintaining healthy muscle and nerve functions [2].

These findings underline the nutritional richness of both fruits and leaves, emphasizing not only their agricultural and nutritional potential but also their contributions to human health. Leaves, in particular, could serve as an excellent source of essential minerals for dietary supplementation or functional food applications.

The crop demonstrates a notable antioxidant potential, with total phenolic content ranging from 99.9 (‘Rezaei’) to 184.30 (‘Fandoghi’) mg/g DW and total antioxidant activity spanning 39.14% (‘Shahpasand’) to 82.89% (‘Sefied’). These findings underscore its strong ability to combat oxidative stress, making it a promising candidate for functional food products and nutraceutical applications. In terms of nutritional value, the crop’s protein content ranges from 14.37 (‘Sefied’) to 18.50 (‘Abbasiali’) mg/g DW, further enhancing its significance, especially for addressing protein deficiencies in plant-based diets. Pourian et al. [48] similarly identified protein content values between 13.70 and 23.63 mg/g DW, corroborating that the protein levels observed in this study fall comfortably within the established range. Together, these attributes reaffirm the crop’s potential for applications in both health-focused and dietary contexts, supported by robust antioxidant properties and consistent nutritional profiles.

The high fruit oil content varies between 49.26% (‘Rezaei’) and 67.72% (‘AhmadAghaei’), positioning this crop as a valuable source of edible oil, supported by its favorable fatty acid profile. In a similar study conducted in Algeria, the fruit oil content ranged from 50.23 to 65.42 [5]. The predominance of palmitic acid, ranging from 9.53% (‘Rezaei’) to 10.96% (‘Chrook’), oleic acid, ranging from 48.4% (‘Rezaei’) to 55.55% (‘KalehGhoochi’), and linoleic acid, ranging from 29.88% (‘KalehGhoochi’) to 36.39% (‘Rezaei’), along with unsaturated fatty acids, ranging from 86.01% (‘Rezaei’) to 89.10% (‘Shahpasand’), underscores the health benefits of the oil, making it suitable for dietary applications and a competitive product in the market. The contribution to the saturated fatty acid fraction is relatively low, ranging from 10.72% (‘Shahpasand’) to 13.83% (‘Rezaei’), while the high unsaturated-to-saturated fatty acid ratio, ranging from 6.00 (‘Rezaei’) to 8.10 (‘Shahpasand’), further enhances its nutritional value, catering to consumer demands for healthier fat sources. Ouni et al. [47] conducted a study in Tunisia and found that the levels of palmitic acid ranged from 10.23 to 10.50%, oleic acid from 65.58 to 69.58%, and linoleic acid from 16.61 to 21.03%. Similar results were reported in studies conducted in Iran [37] and Algeria [5]. Comparing our findings to these previous studies, it is evident that our palmitic acid and linoleic acid levels are higher, while the oleic acid level is lower. Abdoshahi et al. [1] reported oleic acid levels ranging from 48.96 to 55.24%, which is in line with our findings for oleic acid. Additionally, Abdoshahi et al. [1] found that the saturated fatty acid content ranged from 12.0 to 13.1%, unsaturated fatty acids from 87 to 88%, and the unsaturated-to-saturated fatty acid ratio ranged from 6.7 to 9.6. In this case, our findings align only with the unsaturated-to-saturated fatty acid ratio. However, Abdoshahi et al. [1] concluded that these fatty acid parameters were statistically insignificant, whereas in our study, these values were found to be statistically significant.

Additionally, high oil cultivars (‘AhmadAghaei’, ‘Akbari’, ‘Momtaz’, and ‘Chrook’) with oil content above 60% offer significant opportunities for industrial applications including edible oil production. The global shift toward health-focused and plant-based diets increases the demand for pistachios with high unsaturated fatty acid content, positioning them as premium options for health-conscious consumers. Cultivars with elevated oleic acid levels, ‘KalehGhoochi’ (55.55), ‘AhmadAghaei’ (55.54), ‘Akbari’ (55.25), ‘Fandoghi’ (54.92), ‘Momtaz’ (53.86), and ‘Chrook’ (52.81), are recognized for their cardiovascular benefits, meeting the demand for heart-healthy food products.

Kernel percentage, an important determinant of market value, ranged from 51.9% (‘KalehGhoochi’) to 58.9% (‘Momtaz’). Cultivars with higher kernel percentages increase profitability by yielding more edible product per unit and cater to consumer preferences for high-kernel varieties. Low blank nut percentages, 4.5% for ‘Momtaz’ and 4.5% for ‘AhmadAghaei’ make these cultivars desirable for export markets that emphasize quality and uniformity.

Antioxidant capacity, particularly total phenolics and total antioxidant activity, creates additional economic opportunities. Cultivars with high antioxidant activity, ‘Sefied’ (82.89%), ‘Abbasiali’ (81.01%), and ‘Fandoghi’ (79.69%), are suitable for functional food and nutraceutical markets. These traits enhance the perception of pistachios as a superfood, enabling higher market pricing and the development of value-added products.

The variation in nut size and weight also influences economic decisions. For example, ‘Fandoghi,’ with a 1000-nut weight of 998 g, is suited for bulk trade and cost-sensitive markets, while larger nuts, including those of ‘Chrook’ (1278 g), cater to premium segments that prioritize size and visual appeal. The yield variation from 3000 kg/ha (‘Shahpasand’) to 5300 kg/ha (‘KalehGhoochi’) demonstrates the importance of selecting cultivars optimized for high productivity in commercial orchards to maximize revenue potential.

By connecting these traits to specific market demands and revenue streams, this study highlights the economic value of cultivar-specific attributes. Producers can use this information to align cultivation practices with consumer preferences and market trends, enhancing profitability and market competitiveness.

By linking these traits to specific market demands and revenue streams, this study also highlights the economic value of cultivar-specific traits. Producers can use this information to align breeding practices with consumer preferences and market trends, increasing profitability and market competitiveness.

The wide ranges observed in most traits highlight the crop’s genetic and phenotypic plasticity, providing avenues for breeding programs to enhance specific characteristics. However, traits such as high variability in split nut percentages, blank nuts, and endocarp lesions also point to challenges in uniformity and quality, which may require targeted interventions through genetic or agronomic means. Overall, the dataset suggests a high-value crop with significant potential for agricultural, nutritional, and commercial applications. Efforts to optimize its traits through breeding, improved cultivation practices, and quality control measures could unlock greater productivity, market competitiveness, and consumer satisfaction. The variations in the pistachio cultivars examined are shown in Fig. 2.

Fig. 2

The pictures of bunch, leaf, fruits, nut, and kernel of pistachio cultivars studied

Correlation matrix analysis (CMA)

Correlation matrix analysis (CMA) is a statistical technique used to examine the relationships between multiple variables simultaneously. This analysis clearly illustrates the relationships of each variable with others in a dataset, quantifying the strength and direction of these relationships using correlation coefficients. A correlation matrix is typically presented in a table format, where each cell contains the correlation coefficient between two variables. These coefficients range from − 1 (perfect negative correlation) to + 1 (perfect positive correlation), with 0 indicating no linear relationship. By highlighting the degrees of association between variables, this method helps researchers detect multicollinearity, guide variable selection, and improve the accuracy of predictive models [58].

The simple correlations between agronomic and chemical traits in the studied pistachio cultivars are shown in detail in Fig. 3. A negative correlation was identified between hull percentage and nut percentage (r = -1.000**, p < 0.01), indicating a trade-off between these two components; as the hull percentage increases, the nut percentage proportionally decreases. This finding underscores the physical constraints on the allocation of biomass within the fruit structure. Similarly, split nut percentage and unsplit nut percentage exhibited a strong negative correlation (r = -0.976**, p < 0.01), reflecting a direct and predictable relationship between the proportions of split and unsplit nuts. Interestingly, split nut percentage showed a positive correlation with leaf phosphorus (r = 0.669*, p < 0.05), suggesting a potential role of phosphorus in promoting nut splitting. The relationship between blank nut percentage, leaf phosphorus, and total antioxidant activity highlights intriguing dynamics in plant physiology and reproductive success. The negative correlation between blank nut percentage and leaf phosphorus (r = -0.734*, p < 0.05) indicates that as leaf phosphorus levels increase, the occurrence of blank nuts decreases. Phosphorus is a crucial element for plant metabolism, facilitating energy transfer and supporting key processes like photosynthesis and cellular growth [59]. This suggests that higher phosphorus availability may enhance the plant’s ability to produce fully developed nuts, potentially by ensuring sufficient resources for seed formation. On the other hand, the positive correlation between blank nut percentage and total antioxidant activity (r = 0.659*, p < 0.05) suggests a more complex interaction. Elevated antioxidant activity, often a response to oxidative stress, could reflect the plant’s adaptive mechanisms to challenging environmental conditions [18]. While high antioxidant levels indicate a robust defense system, their association with a higher percentage of blank nuts might imply that increased oxidative stress, even if mitigated, can still impact reproductive outcomes. Alternatively, the correlation may highlight an indirect relationship where plants allocating resources to stress management might compromise seed development. Kernel percentage demonstrated significant negative correlations with shell percentage (r = -1.000**, p < 0.01), endocarp lesion (r = -0.634*, p < 0.05), and fruit phosphorus (r = -0.661*, p < 0.05). This suggests that higher kernel yield may be associated with reduced shell thickness and fewer endocarp lesions, possibly due to better nutrient partitioning and fruit development. Shell percentage also negatively correlated with endocarp lesion (r = -0.634*, p < 0.05) and fruit phosphorus (r = -0.661*, p < 0.05), reinforcing the importance of phosphorus in improving nut quality by mitigating structural defects. Moreover, a negative correlation was noted between the tendency for early nut splitting and yield (r = -0.694*, p < 0.05), as well as total antioxidant activity (r = -0.716*, p < 0.05), indicating that early splitting might adversely affect both productivity and antioxidant capacity. First, the very strong negative correlation between nut number per ounce and 1000-nut weight (r = -0.998**, p < 0.01) underscores the expected trade-off between nut size and weight per unit count. As nut size increases, fewer nuts are needed to reach a given weight, reflecting an inherent balance between quantity and individual nut mass. This inverse relationship is consistent with findings that larger seeds or fruits often result in reduced numbers per unit weight due to the physical and biological constraints of resource allocation [52]. Second, the negative correlation between yield and leaf iron content (r = -0.767**, p < 0.01) suggests that elevated iron levels in the leaves may adversely affect yield. While iron is an essential micronutrient for plants, excessive levels could disrupt the uptake or balance of other critical nutrients such as phosphorus, potassium, or zinc. This imbalance may impair physiological processes like photosynthesis or reproductive development, leading to reduced productivity. Such effects are well-documented in studies on micronutrient toxicities and their impacts on nutrient uptake and plant performance [40, 51]. The observed positive correlations among fruit iron and leaf calcium (r = 0.652*, p < 0.05), fruit calcium and fruit phosphorus (r = 0.703*, p < 0.05), and fruit calcium and palmitic acid content (r = 0.859**, p < 0.01) underscore the intricate relationships between nutrient dynamics and fruit quality, including its fatty acid composition. The correlation between fruit iron and leaf calcium suggests a potential interplay in nutrient transport and storage mechanisms. Iron and calcium are both crucial for cellular processes, including metabolic regulation and structural stability in plants. The movement and accumulation of these nutrients may be influenced by shared transport pathways or signaling processes, linking foliar nutrient levels to fruit development [68]. The stronger correlations involving fruit calcium, particularly with fruit phosphorus and palmitic acid content, further emphasize calcium’s central role in fruit quality. Calcium and phosphorus are known to work synergistically in cell wall strengthening and membrane stability, which can enhance fruit texture and nutrient composition [40]. Moreover, the significant relationship between calcium and palmitic acid content may indicate calcium’s role in lipid metabolism. As a secondary messenger in signal transduction, calcium regulates enzymatic pathways involved in fatty acid biosynthesis, thereby influencing the profile of fatty acids like palmitic acid in the fruit [45]. The observed positive correlations between fruit phosphorus and palmitic acid (r = 0.700*, p < 0.05), as well as fruit potassium with total phenolics (r = 0.917**, p < 0.01) and oleic acid (r = 0.654*, p < 0.05), reveal significant interactions between these nutrients and fruit composition, particularly regarding fatty acid profiles and antioxidant properties. Phosphorus, known for its role in energy transfer and membrane integrity, likely contributes to the synthesis of palmitic acid, a saturated fatty acid that plays a key role in plant membrane structure [40]. This suggests that higher phosphorus levels may enhance lipid biosynthesis in fruit tissues. The strong correlation between fruit potassium and total phenolics underscores potassium’s involvement in boosting the plant’s antioxidant defenses, as potassium is crucial for cellular processes that regulate stress response and metabolic activity [67]. Potassium may influence the production of secondary metabolites, such as phenolics, which protect plants from oxidative damage. Additionally, the positive relationship between fruit potassium and oleic acid suggests that potassium could play a role in regulating unsaturated fatty acid composition, enhancing fruit nutritional quality by promoting the accumulation of beneficial fats like oleic acid [21]. These findings collectively highlight the interconnected roles of phosphorus and potassium in fruit quality, underscoring their importance for both antioxidant capacity and fatty acid metabolism. The negative correlations between protein content and both palmitic acid (r = -0.656*, p < 0.05) and the unsaturated-to-saturated fatty acid ratio (r = -0.637*, p < 0.05) suggest an inverse relationship between protein levels and certain aspects of fatty acid composition. Specifically, higher protein content appears to be associated with a higher proportion of saturated fatty acids, such as palmitic acid, and a lower proportion of unsaturated fatty acids. This could be explained by the fact that plants, under certain growth conditions, might prioritize protein biosynthesis over lipid biosynthesis, or modify lipid metabolism to favor the production of saturated fatty acids. Proteins and fatty acids, while both essential for plant growth and function, are synthesized through different metabolic pathways, and the balance between them can be influenced by environmental and physiological factors [36]. For instance, during periods of stress or nutrient limitation, plants may alter their metabolic processes to conserve energy or allocate resources to processes like protein synthesis rather than the production of unsaturated fatty acids, which are energetically more expensive to produce [24]. Additionally, the shift towards more saturated fatty acids could be an adaptive response to environmental stressors. Saturated fatty acids are more stable and less prone to oxidation than unsaturated ones, potentially offering better membrane stability under unfavorable conditions [54]. Therefore, the negative correlation between protein content and the unsaturated-to-saturated fatty acid ratio could indicate a trade-off between protein synthesis and the composition of fatty acids, with plants favoring more stable, saturated forms under certain circumstances. The observed correlations among the fatty acid profiles suggest a finely tuned regulation of lipid biosynthesis in nuts. The negative correlation between unsaturated and saturated fatty acids (r = -1.000**, p < 0.01) indicates a metabolic trade-off, where an increase in one type of fatty acid is linked to a decrease in the other. This suggests that the plant may have a preferential pathway for the synthesis of either unsaturated or saturated fatty acids, which could be influenced by external factors such as nutrient availability or environmental stresses. The positive correlation between unsaturated fatty acids and the unsaturated-to-saturated fatty acid ratio (r = 0.995**, p < 0.01) further supports this idea, indicating that higher levels of unsaturated fatty acids tend to increase the proportion of unsaturated fats in the overall fatty acid profile. This balance is crucial for maintaining cell membrane fluidity, which is essential for plant resilience under stress [14, 64]. On the other hand, the negative correlation between saturated fatty acids and the unsaturated-to-saturated ratio (r = -0.995**, p < 0.01) suggests that as the amount of saturated fatty acids increases, the ratio of unsaturated fats decreases. This relationship emphasizes the regulatory mechanisms that control the composition of fatty acids within plant cells, likely to ensure membrane stability, energy storage, and stress tolerance. Research indicates that the balance between saturated and unsaturated fatty acids plays a vital role in plant adaptation to fluctuating environmental conditions, including temperature stress and water availability [4, 57]. These findings collectively highlight the complexity of lipid metabolism in plants, where fatty acid composition is tightly regulated to maintain cellular function and to adapt to environmental challenges.

Fig. 3

Simple correlations between agronomic and chemical traits in the studied pistachio cultivars. For the explanation of the abbreviations, see Table 1. *, **. Correlation is significant at p ≤ 0.05 and 0.01 levels, respectively

Overall, these findings reveal critical relationships that could inform breeding strategies aimed at optimizing nut quality, yield, and nutritional composition. They also emphasize the interconnectedness of nutrient dynamics, structural traits, and biochemical pathways in determining nut performance and quality.

Multiple regression analysis (MRA)

Multiple regression analysis (MRA) is a statistical technique used to examine the relationship between one dependent variable and two or more independent variables. This method allows researchers to assess the impact of multiple predictors simultaneously while controlling for potential confounding factors. The goal of multiple regression is to create a mathematical model that best fits the data, providing estimates for the effect of each predictor on the dependent variable. The results are typically expressed in terms of regression coefficients, which indicate the strength and direction of the relationship [12, 23].

Initially, after calculating the simple correlation coefficients, blank nut percentage, tendency to early nut splitting, nut number per ounce, 1000-nut weight, and yield were considered as dependent variables, and the direct and indirect effects of the independent variables on these key traits were examined. The MRA results revealed that blank nut percentage is associated with three traits, tendency to early nut splitting with three traits, nut number per ounce with five traits, 1000-nut weight with four traits, and yield with four traits (Table 3).

Table 3 The agronomic and chemical traits associated with fruit related traits in pistachio cultivars as revealed using MRA and coefficients

A strong negative correlation was observed between blank nut percentage and leaf zinc (β = -0.77, P < 0.00) as well as fruit potassium (β = -0.29, P < 0.04). Zinc plays a vital role in enzymatic functions and reproductive development, while potassium contributes to nutrient transport and cellular regulation. Deficiencies in these nutrients can impair normal nut development, leading to higher blank nut percentages. This underscores the importance of maintaining optimal zinc and potassium levels to enhance nut quality. Conversely, blank nut percentage exhibited a strong positive correlation with antioxidants (β = 0.77, P < 0.00), suggesting that elevated oxidative stress might be contributing to nut formation issues. While antioxidants are critical for mitigating stress, their increase could reflect underlying physiological imbalances that compromise nut viability.

For the tendency to early nut splitting, negative correlations were found with antioxidant levels (β = -0.72, P < 0.00), rest fatty acids (β = -0.60, P < 0.00), and fruit oil content (β = -0.34, P < 0.01). This suggests that oxidative stress and reduced lipid reserves could impair structural integrity, causing early splitting. The findings emphasize the need to manage stress and lipid profiles to prevent premature nut splitting.

The nut number per ounce showed significant negative correlations with 1000-nut weight (β = -0.98, P < 0.00) and fruit iron (β = -0.04, P < 0.00). Larger and heavier nuts naturally decrease the count per ounce, while reduced iron levels might indicate suboptimal nutrient translocation affecting nut formation. In contrast, positive correlations were identified with kernel percentage (β = 0.03, P < 0.00), split nut percentage (β = 0.04, P < 0.00), and flower bud number (β = 0.02, P < 0.01), indicating that nut size and splitting are linked to both nutrient availability and reproductive output.

1000-nut weight was negatively correlated with shell percentage (β = -0.03, P < 0.00) and fruit iron (β = -0.04, P < 0.00), highlighting the importance of nutrient allocation for larger nuts. Positive correlations with split nut percentage (β = 0.04, P < 0.00) and flower bud number (β = 0.02, P < 0.01) further underline the trade-off between nut size, splitting tendencies, and reproductive potential.

Finally, yield was strongly negatively correlated with leaf iron (β = -0.97, P < 0.00), suggesting that iron distribution to leaves might detract from overall productivity. However, positive correlations with fruit number per bunch (β = 0.45, P < 0.00), antioxidants (β = 0.36, P < 0.00), and kernel percentage (β = 0.26, P < 0.01) indicate that both fruit clustering and kernel quality are critical determinants of yield. The bold values (*) are supported by the correlation matrix analysis.

In summary, the study found several key correlations that highlight the complex interactions between nutrient levels, stress factors, and nut development. Negative correlations between blank nut percentage and leaf zinc, fruit potassium, as well as early nut splitting with antioxidants and fatty acids, suggest that nutrient deficiencies and oxidative stress can impair nut formation and quality. Positive correlations between antioxidant levels and blank nut percentage indicate a potential response to oxidative stress. Additionally, correlations between nut number, 1000-nut weight, and fruit iron suggest that larger nuts may reduce the count per ounce, while nutrient availability and reproductive output influence nut size and splitting. Iron distribution to leaves was found to negatively impact yield, while fruit number, antioxidants, and kernel percentage were positively correlated with yield. These findings emphasize the importance of managing nutrient levels and stress to optimize nut quality and productivity.

Due to the lack of a study that examines these traits together, the results in this study have been evaluated independently of each other. Since no research in the literature has analyzed these parameters collectively in pistachio cultivars, each trait has been addressed individually and analyzed in a way that reveals meaningful relationships on its own. This approach led to the evaluation of the results not in an interactive manner, but independently in terms of the effect of each parameter. This study provides a foundation for future research that will examine the interactions of these traits together, enabling a more comprehensive and interactive assessment of the same parameters.

Principal component analysis (PCA)

Principal component analysis (PCA) is a technique used to reduce the dimensionality of data while preserving its variance [28]. In this study, the interpretability of the components was enhanced by applying Varimax rotation with Kaiser normalization. Varimax rotation simplifies the factor structure by maximizing the variance of each factor, while Kaiser normalization standardizes the factors to unit variance [29]. The rotation process converged in 9 iterations, allowing for a clearer interpretation of the factor loadings (Table 4).

Table 4 Eigenvalues of the principal component axes from the PCA of the agronomic and chemical traits in the studied pistachio cultivars

PC1, representing 22.48% of the total variance, was primarily influenced by unsaturated fatty acids (0.92), unsaturated/saturated fatty acids ratio (0.92), nut number per ounce (0.72), 1000-nut weight (-0.74), rest fatty acids (-0.89), and saturated fatty acids (-0.92). These factors highlight the importance of fatty acid composition, with unsaturated fatty acids and the unsaturated/saturated ratio being critical for nut quality, particularly in terms of oil composition. However, the negative correlations for 1000-nut weight, rest fatty acids and saturated fatty acids suggest a trade-off: larger nuts with higher saturated fat content may result in lower unsaturated fats, which could impact oil quality. This indicates the need for balancing fatty acid composition and nut size to optimize quality. PC2, accounting for 18.15% of the total variance, was dominated by shell percentage (0.99), endocarp lesion (0.61), fruit number in bunch (-0.60), and kernel percentage (-0.99). A strong positive loading for shell percentage and a negative loading for kernel percentage point to an inverse relationship between shell development and kernel size. Thicker shells may limit kernel growth, suggesting that shell thickness needs to be carefully managed to ensure optimal kernel development. Additionally, the negative correlation with fruit number in bunch indicates that reducing the number of fruits per bunch might allow more resources to be allocated to individual fruits, enhancing kernel size and overall nut quality. The positive correlation with endocarp lesion suggests that slight internal damage could coincide with improved shell strength, although this could also signify a trade-off between fruit protection and kernel development. PC3, which explains 15.82% of the total variance, was most influenced by oleic acid (0.94), fruit oil (0.76), fruit Zn (-0.70), and linoleic acid (-0.94). The strong positive correlation between oleic acid and fruit oil underscores their crucial role in determining the oil quality of the nuts. However, the negative correlations with fruit zinc and linoleic acid suggest that increased oil content and higher oleic acid levels may be associated with lower zinc and linoleic acid content. Zinc is essential for plant health and enzymatic functions, while linoleic acid is an essential fatty acid. This negative relationship indicates that optimizing oil content and oleic acid levels may come at the expense of other key nutrients, which could affect the overall nutritional value of the nuts. Thus, the first three principal components (PC1 = 22.48%, PC2 = 18.15%, PC3 = 15.82%) together represent 56.45% of the total variation.

In conclusion, the PCA results illustrate the complex trade-offs between various traits that influence both the quality and yield of nuts. While fatty acid composition, particularly unsaturated fatty acids and oleic acid is essential for enhancing nutritional quality, these improvements may be accompanied by reductions in other important traits such as kernel percentage, zinc content, and linoleic acid. These findings underscore the need to carefully manage the balance between oil content, fatty acid composition, and essential nutrients to optimize both the quality and yield of nuts.

In the studies conducted by Karimi et al. [31] and Rezaei et al. [50], PC1, PC2, and PC3 were supported by partly the same characteristics, representing 73.93% and 32.25% of the total variance of the first three principal components, respectively. The differences are believed to have originated from the plant material used and environmental factors.

Biplot analysis is a method for visualizing multivariate datasets, combining observations (as points) and variables (as vectors) in the same graph. It is commonly used with dimensionality reduction techniques like principal component analysis (PCA). The length of vectors indicates variable contributions, while angles between them show relationships (e.g., small angles indicate positive correlations). Biplot analysis helps explore variable relationships, assess similarities among observations, and reduce dimensionality. Biplots can also be enhanced with tools like a 95% confidence ellipse, which summarizes the direction and strength of the relationship by outlining the area where 95% of the points are expected to fall. Narrow ellipses indicate strong relationships, while wider ones suggest weaker correlations [11, 35].

Accordingly, the biplot for the studied pistachio cultivars based on PC1/PC2 of agronomic and chemical traits is shown in Fig. 4. According to the analysis, PC1 (22.48%) and PC2 (18.15%) together account for 40.63% of the total variation. The 35 traits and 10 cultivars are distributed across the four regions of the scatter plot. This clustering analysis presents clear patterns that group the cultivars based on specific traits. In Cluster 1, cultivars ‘Rezaei’ and ‘Abbassiali’ appear to share characteristics related to nut size and quality, such as nut percentage, 1000-nut weight, and essential nutrients like zinc and protein. This suggests that these cultivars may be more suited for environments where higher yields and nutrient content are desired. Cluster 2 involves cultivars like ‘KalehGhoochi’, ‘Chrook’, and ‘Sefied’, which are associated with a broader range of characteristics, including fruit development, antioxidant activity, and mineral content. The diversity in traits suggests that these cultivars may be more adaptable to various growing conditions, and their potential antioxidant properties (e.g., total antioxidant activity, oleic acid) might also make them attractive for health-conscious consumers or for processing into value-added products. Cluster 3 groups cultivars like ‘Momtaz’ and ‘Shahpasand’, which are associated with various leaf nutrients and the tendency for early nut splitting. These cultivars show a combination of traits that suggest they may perform well under specific agronomic conditions that prioritize leaf and fruit quality. However, the tendency for early nut splitting could be an issue for their commercial viability, particularly in terms of storage and transport. Lastly, Cluster 4 consists of ‘AhmadAghaei’, ‘Akbari’, and ‘Fandoghi’, which are associated with features like nut number per ounce and fruit oil content. These cultivars appear to be more oil-rich, and their traits might be ideal for oil extraction purposes, where the oil content is a key determinant of commercial value. The fact that most of the cultivars fall within the 95% confidence ellipse indicates that they generally exhibit a high degree of similarity in terms of their overall traits. However, the exclusion of certain characteristics like unsaturated fatty acids, saturated fatty acids, unsaturated/saturated fatty acids, and unsplit nut percentage from this confidence region suggests that these features might vary more widely across the cultivars or may not have a strong influence on grouping them in the current analysis.

Fig. 4

Scatter plot for the studied pistachio cultivars based on PC1/PC2 of agronomic and chemical traits. For the explanation of the abbreviations, see Table 1

In conclusion, the clustering highlights distinct sets of characteristics that define these cultivars. Future studies could explore how these clusters influence performance under different agricultural practices or environmental conditions. A similar biplot has also been observed in the studies by Kendirci and Onoğur [33], Rezaei et al. [50], Antonucci et al. [3], Boualem et al. [5], and Rahmani et al. [49].

Heat map analysis (HMA)

Heat map analysis (HMA) using Ward clustering and Euclidean distances is an effective method for visualizing patterns and relationships in complex datasets. In this analysis, similarities between observations and variables are calculated using Euclidean distances, hierarchically clustered with Ward’s method, and visualized through a heat map with color coding. The heat map facilitates the identification of cultivars or variable groups with similar characteristics, while dendrograms illustrate hierarchical relationships [69]. In this context, the study employed Ward cluster analysis of the studied pistachio cultivars and variables based on agronomic and chemical traits using Euclidean distances, which was visualized through a heat map analysis, providing a comprehensive representation of the clustering patterns (Fig. 5).

Fig. 5

Visualization of clustering patterns of pistachio cultivars and variables based on agronomic and chemical traits using heat map. For the explanation of the abbreviations, see Table 1

The classification of characteristics into two main groups, A and B, and their subsequent division into subgroups, demonstrates the diverse range of traits that define the analyzed pistachio cultivars. The A1 subgroup, which includes flower bud number, unsaturated fatty acids, saturated fatty acids, protein content, palmitic acid, blank nut percentage, unsplit nut percentage, rest fatty acids, and fruit number in bunch, highlights characteristics primarily associated with reproductive performance and nut composition. This suggests that the traits in A1 may play a significant role in determining the overall productivity and nut quality of the cultivars. In contrast, the A2 subgroup encompasses leaf calcium, fruit calcium, fruit phosphorus, fruit potassium, tendency to early nut splitting, and abscised bud flower number, indicating its importance in nutritional content and post-harvest characteristics.

Similarly, the B1 subgroup includes 17 characteristics: hull percentage, shell percentage, endocarp lesion, dry nut to fresh nut ratio, linoleic acid, fruit zinc, nut number per ounce, leaf zinc, nut percentage, fruit oil, kernel percentage, oleic acid, total antioxidant activity, split nut percentage, fruit iron, unsaturated fatty acids, and total phenolics. This underscores the multifaceted nature of this group in contributing to both agronomic and nutritional traits. The traits in B1 are highly relevant to cultivars aimed at providing health-promoting benefits. On the other hand, the B2 subgroup, with only three characteristics—1000-nut weight, leaf iron, and yield—reflects traits directly related to productivity and crop output. The concentrated nature of B2 traits indicates their critical role in large-scale agricultural practices and commercial considerations.

The grouping of cultivars into two primary clusters (C and D) and the further division of the D group into D1 and D2 subgroups provides valuable insights into the unique and shared features among the cultivars. The ‘Shahpasand’ cultivar, as the sole member of the C group, likely possesses distinct traits that set it apart from the other cultivars, suggesting its potential as a unique genetic resource for specific breeding programs or niche markets. Similarly, the separation of ‘KalehGhoochi’ into the D1 subgroup highlights its distinctive profile, which may stem from its high kernel yield, large nut size, or other unique attributes commonly associated with this cultivar. The clustering of the remaining eight cultivars into the D2 subgroup indicates a closer similarity in their characteristics, which could facilitate collective management practices or targeted breeding strategies aimed at enhancing shared traits, such as yield, nut quality, or resistance to environmental stressors.

The distribution of traits among subgroups also provides insights into which datasets influence specific cultivars. For instance, the traits in the B1 subgroup, including antioxidant activity, oleic acid, and kernel percentage, may significantly impact the cultivars grouped in D2, given their broader applicability to multiple cultivars. Conversely, the unique traits in A2, such as mineral content and early nut splitting, might be more relevant to cultivars like ‘Shahpasand,’ emphasizing its potential niche adaptation. Similarly, traits in B2, particularly yield and nut weight, are likely critical for commercial cultivars like ‘KalehGhoochi,’ which is well-known for its high productivity and market demand.

In summary, the heat map and hierarchical clustering provide a comprehensive framework for understanding the relationships among traits and cultivars. These findings can inform breeding programs, cultivar selection, and management practices by identifying key traits that align with agronomic, nutritional, and market-driven goals. Additionally, the distinct clustering of certain cultivars underscores the importance of maintaining genetic diversity and exploring unique traits to enhance the resilience and competitiveness of pistachio production systems. Our findings are similar to those of Manthos et al. [39].

Conclusion

In this study, we comprehensively analyzed the fruit characteristics, mineral nutrient content, antioxidant capacity, biochemical composition, and fatty acid profile of various Iranian pistachio cultivars. The results indicate significant variation among cultivars in terms of key traits, including nut size, kernel percentage, mineral content (iron, zinc, calcium, and phosphorus), and antioxidant properties. These variations highlight the potential for selecting cultivars based on specific agronomic or commercial goals, such as improving nut quality, enhancing nutrient content, or optimizing oil extraction processes.

The study further demonstrated that antioxidant capacity, particularly total phenolics and oleic acid content plays a crucial role in the nutritional value and health benefits of pistachios. Mineral content, including fruit and leaf iron, phosphorus, and calcium, was found to influence nut development and overall yield, suggesting that proper nutrient management can enhance pistachio productivity.

The biochemical composition, including fatty acid profiles, also varied significantly among the cultivars, with unsaturated fatty acids being particularly prominent in certain cultivars. These findings underscore the importance of considering both nutritional and biochemical factors when selecting pistachio cultivars for different markets, especially those aimed at health-conscious consumers or for specialized industrial purposes such as oil production.

While this study highlights the intrinsic genetic differences among the cultivars, it is also important to consider the role of environmental factors, such as soil composition, water availability, and climatic conditions, in shaping these traits. Environmental factors can significantly impact traits like mineral uptake, fatty acid composition, and antioxidant capacity. For example, variations in soil nutrients and pH levels may influence the bioavailability of minerals, thereby affecting nut quality. Furthermore, climatic factors such as temperature and humidity during critical growth stages are likely to impact both fatty acid composition and antioxidant levels, potentially altering the health benefits and marketability of pistachios.

Future research should focus on developing methodologies to systematically assess these environmental variables and their interactions with cultivar-specific traits. This could involve controlled experiments in varying environmental conditions, as well as advanced analytical techniques to measure the impact of environmental stressors on pistachio composition. Such studies would provide valuable insights into the precise environmental conditions necessary for optimizing cultivar traits and enhancing pistachio quality for diverse applications.

Overall, this research provides a foundation for future studies on cultivar improvement and management practices. By integrating genetic, biochemical, and environmental perspectives, researchers and growers can develop strategies to optimize pistachio production for specific end-use purposes, such as food, oil, and other value-added products.