Nutritional and Bioactive Seed Components in Chickpea Advanced Breeding Lines Assessed by Chemical Analysis and LC–MS Profiling

Abstract

Chickpea (Cicer arietinum L.) is an important legume, valued for its nutritional and bioactive components. In this study, seven chickpea advanced breeding lines, an elite line, and a cultivar were evaluated under field conditions to assess superior agronomic performance, seed quality traits, nutritional composition, and phenolic profile. A combined approach was used, integrating field phenotyping, seed quality assays, and LC–MS-based phenolic profiling. Significant genotype-dependent variation was observed in plant height, biomass yield, and 1000-seed weight, with P9/14 and P10/14 advanced lines performing strongly in yield-related traits. Seed functional properties also differed, with P8/14 showing superior hydration and seed coat characteristics, while cv. Blanco Sinaloa exhibited the highest hydration and swelling capacities. Protein content ranged from 22.6% to 25.4%, with P9/14 being the most protein-rich advanced line. Phytochemical and antioxidant analyses revealed substantial differences among genotypes: Blanco Sinaloa and M-15370 showed the highest total phenolics and ABTS activity, whereas P14/14 exhibited the strongest DPPH scavenging capacity. LC–MS profiling identified six major phenolic subclasses, with isoflavones predominating and biochanin A and its derivatives being the most abundant compounds. Overall, the integration of agronomic, nutritional, and phytochemical data highlights the advanced lines P14/14 and P9/14 as promising candidates for future breeding programs aimed at enhancing chickpea nutritional quality and functional seed attributes.

1. Introduction

Chickpea (Cicer arietinum L.) is the second most widely cultivated annual legume worldwide [1] and one of the most drought-tolerant legumes in the Fabaceae family, making it a key crop for warm and semi-arid climatic regions. As global demand for nutrient-dense and health-promoting foods increases, breeding programs are prioritizing developing genotypes that combine strong agronomic performance with enhanced nutritional and bioactive properties [2,3].

Chickpea seeds are nutritionally rich, containing carbohydrates, proteins, unsaturated fatty acids, minerals, vitamins, dietary fibers, and a diverse array of phytochemicals [2,3]. Their protein profile is considered superior to that of many other legumes [4], comprising 18 amino acids, including 8 essential ones [5]. Compared with lentils, red kidney beans, and cereals such as wheat and rice, chickpea seeds exhibit higher levels of dietary fiber, ash, and lipids [4], key minerals and macronutrients, such as potassium, calcium, sodium, and magnesium, as well as micronutrients, including copper, iron, and zinc, contributing substantially to human dietary requirements [5]. Recent advances in high-resolution mass spectrometry (HRMS) have revealed a broad spectrum of phenolic compounds in chickpea flour, including flavonoids, phenolic acids, and lignans, which constitute important health-promoting constituents [6]. According to Zalidis et al. [7], the identified compounds in chickpea flours using liquid chromatography time-of-flight tandem mass spectrometry (LC-QTOF-MS/MS) included (Epi)afzelechin, Apigenin-6-C-glucoside, Benzoic acid, Biochanin A, 7-O-β-D-glucopyranoside, Daidzein, Dihydroxybenzoic acid hexoside, Dihydroxybenzoic acid malonyl hexoside, Dihydroxybenzoic acid pentoside, Gallic acid hexoside, Genistein, Isorhamentin 3-O-β-D-glucopyranoside, Kaempferol 3-Orutinoside, Malvidin, Methyl isoflavone isomer I, Myricetin-3-O-rhamnoside, Naringenin, Orobol, p-hydroxybenzoic acid, Pratensein/Kaemferide, Prunin [naringenin 7-O-β-Dglucopyranoside], Quercetin-3-O-galactoside, and Quercetin-3-O-rhamnoside.

Beyond their nutritional value, chickpea seeds possess functional properties such as hydration capacity, swelling behavior, and seed coat characteristics, which influence cooking quality and industrial processing [8,9]. Nutritional studies have further documented variation in protein, fat, and mineral content across cultivars and landraces [4,10]. Phenolic compounds—including isoflavones such as calycosin, formononetin, genistein, trifolirhizin, ononin, and sissotrin—have been associated with antioxidant, antimicrobial, antifungal, and insecticidal activities, as well as potential roles in managing chronic diseases [11,12]. Despite their potential, the molecular mechanisms underlying these bioactivities remain insufficiently understood due to the structural diversity and complexity of chickpea phytochemicals [11]. Global consumption of chickpea has increased sharply in recent years, driving innovation in chickpea-based foods, including snacks, beverages, and dairy alternatives [13,14]. Modern processing approaches aim to enhance digestibility, reduce antinutritional factors, and exploit chickpea’s emulsifying and oil binding properties [11]. These developments underscore the importance of identifying genotypes with superior nutritional and functional profiles.

At the production level, chickpea cultivation faces increasing challenges due to climate-induced abiotic and biotic stresses that threaten yield stability. Breeding efforts therefore aim to develop new cultivars that combine high yield, enhanced nutritional value, and resilience to the adverse environmental conditions. Previous studies have provided valuable insights into chickpea agronomy, including plant growth, yield stability, and adaptation to diverse environments [15,16]. Both conventional and molecular breeding approaches, often used in combination, have contributed to genetic improvement.

However, important gaps remain. Most studies evaluate agronomic traits, seed functional properties, nutritional composition, or phenolic content separately, limiting our understanding of how these traits interact within breeding populations. Research on chickpea phenolics has often relied on bulk spectrophotometric assays that do not resolve individual compounds or phenolic subclasses, and only a limited number of studies have used high-resolution LC–MS to characterize the full phenolic spectrum [17,18]. Moreover, LC–MS studies typically focus on commercial cultivars or landraces, whereas advanced breeding lines, which represent the most relevant material for genetic improvement, remain underexplored. As a result, there is limited knowledge on how agronomic performance, seed functional traits, nutritional composition, and detailed phenolic profiles co-vary in breeding materials, information that is essential for selecting superior genotypes.

To address these gaps, the present study integrates field phenotyping, seed quality evaluation, nutritional analysis, antioxidant assays, and LC–MS-based phenolic profiling to characterize seven advanced chickpea breeding lines, an elite line, and a cultivar. By combining agronomic, functional, and phytochemical datasets, this work aims to identify genotypes with superior nutritional and bioactive potential and to provide breeders with comprehensive evidence to support the development of chickpea lines suited for functional food applications.

2. Materials and Methods

2.1. Field Experiment

2.1.1. Germplasm and Experimental Design

Seven advanced breeding lines of Cicer arietinum (P1/14, P7/14, P8/14, P9/14, P10/14, P13/14, and P14/14) and an elite line (M-15370—Orig. Institute of Industrial & Forage Crops/ELGO Dimitra) were evaluated. The advanced breeding lines were developed in the past through five years of intrapopulation pedigree selection using a honeycomb experimental design. The field experiment was conducted during the 2022 growing season at the farm of the Aristotle University of Thessaloniki (40°32′ N, 22°59′ E) under a conventional farming system. A Randomized Complete Block Design (RCBD) with four replications was used. Each experimental plot consisted of six rows, each 4 m in length, arranged with an interrow spacing of 0.25 m.

2.1.2. Observations and Measurements

Morphological, agronomic, and physiological traits were recorded from flowering to maturity using plants from the four central rows of each plot, excluding border rows. Flowering onset and disease symptoms were monitored. Furthermore, morphological traits were assessed according to the UPOV protocol for Cicer arietinum L. (TG/143/5, https://www.upov.int/en, accessed on 23 January 2026), which serves as a guideline for conducting tests related to the distinctness, stability, and uniformity of new plant varieties. According to TG/143/5 protocol guidelines, for each characteristic (char.) assessed, an ordinal scoring system based on visual evaluation was used. Measurements were taken from 10 randomly selected plants per plot from the four central rows, which included the following:

• Plant traits: Leaf type (char. 7), flowering time (char. 8), flower color (char. 9), pod size (char. 11), pod green color intensity (char. 12), beak length (char. 13), seeds per pod (char. 14), seed color (char. 15), shape and ribbing (char. 18 and 19).
• Physiological traits: Chlorophyll content index (CCI) was determined using a SPAD-502 Plus chlorophyll meter (Konica Minolta, Osaka, Japan), photosynthetic efficiency (Quantum yield, QY) was measured with a FluorPen FP 110 portable fluorometer (PSI Instruments, Drásov, Czech Republic), and leaf area index (LAI) was quantified using an AccuPAR LP-80 ceptometer (METER Group, formerly Decagon Devices, Pullman, WA, USA). Measurements were conducted twice during the growing season (vegetative and flowering stages), on 10 randomly selected plants per plot from the four central rows.
• Growth and yield components: Height at three developmental stages (cm), biomass yield (g/10 plants), seed yield (g/10 plants), and 1000-seed weight (g) were recorded.

2.1.3. Agronomic Practices, Harvesting, and Post-Harvest Management

Soil analysis prior to sowing characterized the soil as clay loam (30% sand, 25% silt, 35% clay), with 1% organic matter content, 5% calcium carbonate (CaCO₃), 11 mg/kg phosphorus (P), 0.095 g/100 g nitrogen (N), and pH 8.1 at 25 °C. The crop was covered with green mesh after sowing to prevent weed growth and bird predation. Weed control was performed mechanically, and no herbicides were used. Furthermore, no application of fungicide or insecticide was required. The crop was grown under rainfed conditions. During the growing season, daily temperatures ranged from 8 to 28 °C, with the warmest period occurring in late June, before harvest. Total rainfall amounted to approximately 160 mm, with most precipitation occurring during early vegetative growth. These conditions reflect typical Mediterranean dryland environments and allow for the evaluation of genotype performance under realistic field stress. Each plot row was harvested separately into large bags, and seeds were weighed at the Genetics Laboratory of the Aristotle University of Thessaloniki.

2.1.4. Data Analysis

Data was analyzed using the IBM SPSS Statistics software (version 29.0). Analysis of variance (ANOVA) was performed to detect differences among genotypes for morpho-logical and agronomic traits. Mean comparisons were conducted using Duncan’s multiple range test at p = 0.05. Moreover, the coefficient of variation (CV) and Pearson correlation coefficient (r) were also calculated.

2.2. Laboratory Experiment

2.2.1. Plant Genetic Material

Seeds from the seven chickpea advanced lines and the elite line M-15370 were analyzed. Additionally, a large-seeded cultivar (Blanco Sinaloa—Orig. Mexico) was included as a reference control for quality. For analyses requiring powdered material, whole chickpea seeds were ground using a laboratory mill to obtain seed flour.

2.2.2. Physicochemical Quality Traits

The physicochemical quality traits of both chickpea breeding lines and commercial cultivars were evaluated as follows:

• Hydration Capacity (HC) and Hydration Index (HI): Ten pre-weighed seeds were soaked in 40 mL of distilled water for 24 h at room temperature. After soaking, the seeds were drained, blotted to remove excess water, and weighed. HC was calculated as the increase in seed weight per g of dry seed, and HI was expressed as the ratio of HC to the weight of a single seed [19].
• Swelling Capacity (SC) and Swelling Index (SI): After hydration, the volume of seeds was measured using a graduated cylinder. SC was calculated as the increase in seed volume per g of dry seed, and SI was expressed as the ratio of SC to volume of a single seed [20].
• Seed Coat Percentage (% SCP): Seeds were manually dehulled, and the weight of the seed coat was recorded. % SCP was calculated as the ratio of seed coat weight to total seed weight × 100.

2.2.3. Proximate Composition

• Moisture content: 5 g of seed flour was oven-dried at 105 °C until a constant weight was achieved, and moisture content was expressed as a percentage of the initial weight.
• Protein content: It was determined using the Kjeldahl method, with a conversion factor of 6.25 applied to convert nitrogen content to protein [21].
• Fat content: Fat was extracted using a Soxhlet apparatus with petroleum ether as the solvent and expressed as a percentage of dry seed weight [21].
• Ash content: It was determined by dry ashing 5 g seed flour in a muffle furnace at 550 °C until a constant weight was obtained [21].
• Carbohydrate content: It was assessed by the difference: Carbohydrate % = 100 − (moisture% + protein% + fat% + ash%)

2.2.4. Bioactive Traits

The bioactive traits investigated in this research included the following:

• Phenolic seed extraction: 0.5 g of the seed flour sample was extracted with 10 mL of 70% aqueous acetone using a sonication bath for 20 min. Following sonication, the extracts were centrifuged at 4000 rpm for 10 min, and the supernatants were collected and stored at –20 °C for subsequent analysis of bioactive compounds.
• Total Phenolic Content (TPC): TPC was determined using the Folin–Ciocalteu method according to Singelton et al. [22]. Briefly, phenolic seed extract (200 μL) was mixed with Folin–Ciocalteu reagent diluted 1:10 with water (800 μL) and sodium carbonate solution (2 mL), incubated at room temperature for 60 min, and the absorbance was measured at 725 nm. Gallic acid was used as a standard, and results were expressed as mg gallic acid equivalents (GAE) per 100 g of dry seed.
• Total Tannins (TT): Total tannins were quantified by measuring the difference in TPC before and after treatment with polyvinylpyrrolidone (PVP). The seed extract was mixed with PVP, incubated, and centrifuged. The TPC of the supernatant was measured using the Folin–Ciocalteu method [23].
• Total Flavonoid Content (TFC): TFC was determined based on the reaction of the phenolic extract with NaNO₂, followed by aluminum chloride (AlCl₃) to form a flavonoid complex [24]. After incubation, absorbance was measured at 510 nm. Catechin was used as a standard, and results were expressed as mg catechin equivalents (CATE) per 100 g of dry seed.
• Antioxidant capacity was assessed using the ABTS, DPPH, and FRAP assays. For the ABTS assay, radical scavenging activity was measured using the ABTS•+ radical cation, with absorbance read at 734 nm. Results were expressed as Trolox equivalents (TE) per 100 g of dry seed [25]. For the DPPH assay, the ability of the seed extract to scavenge DPPH radicals was measured at 516 nm, with results expressed as TE/100 g dry seed [26]. Ferric reducing antioxidant power (FRAP) was determined by measuring the reduction of Fe³⁺ to Fe²⁺, with absorbance read at 593 nm, and results expressed as TE/100 g dry seed [27].
• Phenolic Composition/Phenolic Profile: 0.5 g of homogenized chickpea flour was mixed with 5 mL of 70% aqueous acetone and treated for 25 min in an ultrasonic bath. After spinning in a centrifuge at 4000 rpm, the supernatant was evaporated to dryness under a nitrogen stream, reconstituted in 0.3 mL of 50% aqueous methanol, and kept at −20 °C until analyzed. Analysis of phenolic compounds was performed according to the protocol described in Irakli et al. [28]. Briefly, LC–MS measurements were carried out using a Nexera HPLC system (Shimadzu, Kyoto, Japan) equipped with a diode array detector (DAD) and a single quadrupole mass spectrometer equipped with an electrospray ionization (ESI) source. The samples were injected (10 μL) into a reversed-phase column (Poroshell 120 EC-C₁₈, 4 μm, 4.6 × 150 mm, Agilent Technologies). The mobile phase consisted of a mixture of 0.1% formic acid (solvent A) and ACN (solvent B) at a flow rate of 0.4 mL/min. The linear gradient consisted of 15% B for 0 min, 10–25% B for 5 min, 25–35% B for 10 min, 35–60% B for 28 min, 60–100% B for 35 min, and back to 15% B for 40 min. The DAD was set to operate in full scan mode, while the ESI was operated in negative scan mode under the following conditions: interface voltage, +4.5 kV; curved desolvation line (CDL) voltage, 20 V; nebulizing gas (nitrogen) flow, 1.5 L/min; drying gas flow, 15 L/min; block heater temperature, 200 °C; CDL temperature, 250 °C. Lab Solutions LC-MS software (Ver. 5.128.2) was used for data acquisition and processing (Shimadzu, Kyoto, Japan). By contrasting the retention times, UV profiles, and mass spectra of unknown peaks with those of standards, the major phenolic compounds were identified. Both UV and MS spectra were compared with the available literature [29,30,31] to identify isoflavonoid derivatives in the extracts. Quantification was carried out in selective ion monitoring (SIM) mode, constructing calibration curves of corresponding standard solutions at five concentration levels. However, quantification of isoflavonoid isomers was based on standard curves generated by the galangin. All standards and reagents were of the LC-MS purity and purchased from Sigma-Aldrich (Steinheim, Germany). Each analysis was carried out thrice.

2.2.5. Data Analysis

ANOVA was performed to evaluate genotype effects on physicochemical properties, quality traits, and bioactive compounds. Duncan’s multiple range test (p ≤ 0.05) was used for mean comparisons. Pearson correlation coefficients (r) were calculated to assess relationships among traits. Correlation matrix heatmaps were generated using Microsoft Excel (Microsoft 365) for data visualization.

3. Results

3.1. Field Experiment

3.1.1. Analysis of Measurements According to UPOV

All advanced lines exhibited stable expression for most examined traits. Leaf type was consistently pinnate, and flower color was uniformly white across genotypes (Figure 1a). Pod size differentiated among the advanced lines (Figure 1b). Specifically, M-15370 exhibited a small pod size, whereas lines P1/14, P9/14, P10/14, and P14/14 produced medium-sized pods, while P7/14, P8/14, and P13/14 had larger pods. Pod coloration ranged from light to dark green across the lines. Line P8/14 displayed light green pods; P1/14, P9/14, P13/14, and P14/14 ranged from light to medium green; P7/14 and P10/14 showed medium green; and M-15370 exhibited medium to dark green coloration. Beak length was generally long except P9/14 and M-15370, which had medium beak length.

Seed number per pod varied between one and two. Single-seeded pods predominated in P1/14, P8/14, P9/14, P14/14, and M-15370, while P7/14 produced both one- and two-seeded pods. P10/14 and P13/14 were mainly single-seeded but occasionally produced two-seeded pods. Seed color was gray-brown in all advanced lines, contrasting with the brown seeds of M-15370. Seed shape was round with angular features in all lines, whereas M-15370 seeds were purely round. Finally, seed ribbing intensity further distinguished genotypes. M-15370 exhibited absent to very weak ribbing, P7/14 and P8/14 showed weak to medium ribbing, P1/14 and P9/14 displayed medium to strong ribbing, and P10/14, P13/14, and P14/14 had medium ribbing.

3.1.2. Comparative Analysis of Plant Height Across Three Growth Stages

At the vegetative stage (VS), significant differences (p ≤ 0.05) were observed among genotypes. Lines P14/14 and M-15370 differed significantly from P1/14, P7/14, P8/14, P10/14, and P13/14, while P9/14 did not differ statistically. The tallest plants were recorded in P7/14 whereas the shortest were in M-15370. The coefficient of variation (CV) for plant height at this stage was 15.6%. At the flowering stage (FS), no significant differences were detected among genotypes (p > 0.05). P7/14 exhibited the greatest height, while M-15370 remained the shortest. At the pod filling stage (PS), no statistically significant differences were also detected among genotypes (p > 0.05). P10/14 reached the maximum height, whereas P14/14 had the minimum. The CV was 11.4% at flowering and 10.5% at the pod filling stage. Figure 2 summarizes the mean plant height values across the three growth stages, highlighting genotype-specific variation.

3.1.3. Comparative Analysis of Physiological Measurements

The chlorophyll content index (CCI) showed statistically significant differences in both measurements during the growing season (

Table 1. Mean values of chlorophyll content (CCI), photosynthetic efficiency (QY), and leaf area index (LAI) across genotypes and developmental stages (vegetative stage, VS; flowering stage, FS).

Genotype	CCI		QY		LAI
	VS	FS	VS	FS	VS	FS
P1/14	57.7 a	64.9 a	0.73 a	0.71 a	0.67 a	1.4 a
P7/14	67.6 a	60.0 ab	0.72 a	0.69 ab	0.62 a	1.1 a
P8/14	66.8 a	66.5 a	0.74 a	0.71 a	0.98 a	2.1 a
P9/14	65.0 a	55.5 ab	0.72 a	0.70 ab	1.0 a	1.7 a
P10/14	68.3 a	66.4 a	0.73 a	0.72 a	0.88 a	1.9 a
P13/14	64.9 a	62.0 ab	0.72 a	0.70 ab	0.48 a	0.8 a
P14/14	63. 6 a	54.3 ab	0.72 a	0.67 b	0.71 a	1.8 a
M-15370	45.2 b	51.9 b	0.70 a	0.70 ab	0.82 a	1.7 a

Different letters indicate significant differences (p < 0.05).

). At the vegetative stage, M-15370 differed significantly from all advanced lines (p ≤ 0.05), recording the lowest chlorophyll value, while P10/14 exhibited the highest. In the second measurement (flowering stage), M-15370 again had the lowest values, differing significantly from P1/14, P8/14, and P10/14. The maximum CCI was observed on P8/14.

Photosynthetic efficiency (QY) did not differ significantly among genotypes in the first measurement (vegetative stage, p > 0.05). The highest value was recorded in line P8/14, while M-15370 was the lowest. In the second measurement (flowering stage), significant differences were detected between P14/14 and P1/14, P8/14, and P10/14 (p ≤ 0.05). P10/14 exhibited the maximum QY, whereas P14/14 recorded the minimum (Table 1).

Regarding the leaf area index (LAI), no statistically significant differences were observed in either measurement (p > 0.05). At the vegetative stage, P9/14 had the highest LAI and P13/14 the lowest. At flowering, P8/14 recorded the maximum value, while P13/14 remained the lowest. Table 1 presents the mean values of physiological trait measurements across genotypes and growth stages.

3.1.4. Comparative Analysis of Yield Components

Biomass yield varied significantly among genotypes (p ≤ 0.05). Specifically, lines P7/14 and P13/14 produced significantly lower biomass compared to lines P9/14, P14/14, and M-15370. Conversely, P9/14 and M-15370 differed significantly from P1/14, P8/14, and P10/14. The highest biomass yield was recorded in line P9/14, while P7/14 had the lowest. Seed yield did not differ significantly among genotypes (p > 0.05). M-15370 recorded the highest seed yield, whereas P13/14 had the lowest (

Table 2. Mean values of yield components (biomass yield, seed yield, and 1000-seed weight) across genotypes.

Genotype	Biomass Yield	Seed Yield	1000-Seed Weight
	(g/10 Plants)	(g/10 Plants)	(g)
P1/14	303.5 bc	84.5 a	457.1 c
P7/14	282.5 c	89.2 a	473.8 bc
P8/14	360 bc	101.5 a	490.8 abc
P9/14	981.8 a	131 a	436.7 c
P10/14	417.4 bc	104.6 a	534.6 a
P13/14	292.3 c	83.1 a	516.7 ab
P14/14	663.8 ab	133.7 a	461.3 c
M-15370	924.4 a	149.5 a	296.7 d

Different letters indicate significant differences (p < 0.05).

). In terms of 1000-seed weight, significant differences were observed among genotypes (p ≤ 0.05). M-15370 differed significantly from all advanced lines, while P1/14, P9/14, and P14/14 differed significantly from P13/14. The highest 1000-seed weight was recorded in P10/14, whereas M-15370 had the lowest (Table 2).

3.1.5. Correlation Coefficient (r) for Photosynthetic Efficiency and Yield Components

Figure 3 presents the correlation analyses conducted to evaluate the relationships between photosynthetic efficiency (QY) with yield components including biomass yield, seed yield, and 1000-seed weight. Correlation coefficients (r) were calculated at a significance level of α = 0.05. Biomass yield and seed yield were strongly positively associated (r = 0.815, p ≤ 0.01). In contrast, 1000-seed weight showed significant negative correlations with biomass yield (r = −0.41, p ≤ 0.05). Photosynthetic efficiency at the vegetative stage was weak but significantly correlated with 1000-seed weight (r = 0.356, p ≤ 0.05), whereas no significant correlations were observed for the second measurement at flowering.

3.2. Analytical Measurements

3.2.1. Comparative Analysis of Physicochemical Properties

Statistically significant differences were observed among the chickpea genotypes for all measured traits (HC, HI, SC, SI, and % SCP), as summarized in

Table 3. Mean values of hydration capacity (HC), hydration index (HI), swelling capacity (SC), swelling index (SI), and seed coat percentage (% SCP) of studied chickpea seed genotypes.

Genotype	HC	HI	SC	SI	%SCP
P1/14	0.588 bc	1.08 abc	0.50 c	1.0 d	4.7 abcd
P7/14	0.626 ab	1.12 ab	0.58 bc	1.4 bcd	5.0 ab
P8/14	0.645 ab	1.16 a	0.65 b	1.6 ab	5.2 a
P9/14	0.525 cd	1.02 bcde	0.50 c	1.3 cd	4.2 d
P10/14	0.658 ab	1.07 abcd	0.60 bc	1.2 cd	4. 8 abc
P13/14	0.655 ab	1.09 abc	0.60 bc	1.2 cd	4.7 abcd
P14/14	0.508 d	0.95 e	0.60 bc	1.5 abc	4.2 d
M-15370	0.331 e	0.97 de	0.35 d	1.8 a	4.4 bcd
Blanco Sinaloa	0.698 a	1.00 cde	0.85 a	1.7 ab	4.4 cd

Different letters indicate significant differences (p < 0.05).

. Concerning hydration capacity (HC), the cultivar M-15370 exhibited the lowest value (0.331), differing significantly from all other genotypes, whereas Blanco Sinaloa had the highest HC (0.698). Advanced lines P9/14 (0.525) and P14/14 (0.508) showed lower HC values, significantly differing from most other lines. Intermediate HC values were observed in P1/14, P7/14, P8/14, P10/14, and P13/14, with no significant differences among some of these lines. For the hydration index (HI), P8/14 had the highest value (1.16), while P14/14 had the lowest (0.95). In terms of swelling capacity (SC), Blanco Sinaloa showed the highest SC (0.85), and M-15370 the lowest (0.35). The swelling index (SI) was highest in M-15370 (1.8) and Blanco Sinaloa (1.7), while the lowest value was observed in P1/14 (1.0). Regarding % SCP, P8/14 presented the highest percentage (5.2%), and P9/14 and P14/14 the lowest (4.2%). Overall, M-15370 stands out for its low HI and HC but high SI, suggesting distinctive functional properties compared to the other genotypes. The advanced line P8/14 had the highest values for HI, SI, and % SCP, highlighting its superior overall functional quality. Meanwhile, the cultivar Blanco Sinaloa showed the highest HC and SC, making it particularly strong in hydration- and swelling-related traits.

3.2.2. Comparative Analysis of Nutritional Composition

Nutritional components measured in chickpea seeds included protein, fat, ash, and carbohydrate content on a dry weight basis (

Table 4. Mean values of nutritional composition of chickpea genotypes based on dry weight (DW).

Genotype	% Protein DW	% Fat DW	% Ash DW	% Carbohydrates DW
P1/14	24.3 ab	6.0 ab	4.3 a	65.5 bc
P7/14	22.6 d	5.7 ab	4.2 a	67.5 a
P8/14	24.7 ab	4.7 c	4.2 a	66.4 b
P9/14	25.4 a	6.2 a	3.9 a	64.5 c
P10/14	22.9 cd	5.8 ab	3.9 a	67.5 a
P13/14	23.8 bc	5.5 abc	4.3 a	66.4 b
P14/14	24.3 ab	5.7 ab	4.3 a	65.8 bc
M-15370	23.9 bc	5.1 bc	4.2 a	66.8 ab
Blanco Sinaloa	22.8 cd	6.4 a	4.2 a	66.7 ab

Different letters indicate significant differences (p < 0.05).

). Among the genotypes, protein content ranged from 22.6% to 25.4%, with P9/14 exhibiting the highest value. Fat content varied between 4.7% and 6.4%, being highest in Blanco Sinaloa and P9/14, while ash content was relatively uniform across all genotypes (3.9–4.3%), with no statistically significant differences among the genotypes. The carbohydrate content showed relatively limited variation among genotypes, with P7/14 and P10/14 exhibiting the highest values, while P9/14 had the lowest, reflecting expected trade-offs with protein and fat accumulation. These results highlight clear differences in the nutritional profiles of the chickpea lines, with some advanced lines, such as P9/14, standing out for the highest protein and high fat content, making it the most nutrient-dense line overall, and others, like P8/14, showing high protein but lower fat content.

3.2.3. Comparative Analysis of Bioactive Compounds

The phytochemical analysis of chickpea genotypes (

Table 5. Mean values of nutritional composition (total phenolic compounds, TPC; total tannins, TT; total flavonoid content, TFC) of chickpea genotypes. Results are expressed as mg gallic acid equivalents (GAE) per 100 g of dry seed (DW).

Genotype	TPC (mg GAE/100 g DW)	TT (mg GAE/100 g DW)	TFC (mg CATE/100 g DW)
P1/14	44.9 ab	17.0 b	20.8 a
P7/14	48.1 ab	23.1 a	18.8 ab
P8/14	47.7 ab	22.0 a	16.8 abc
P9/14	43.5 ab	23.8 a	13.0 cd
P10/14	46.7 ab	10.5 c	15.0 bcd
P13/14	43.9 ab	24.8 a	15.4 bcd
P14/14	42.0 b	24.5 a	12.1 cd
M-15370	46.8 ab	27.1 a	11.9 d
Blanco Sinaloa	49.2 a	24.6 a	11.2 d

Different letters indicate significant differences (p < 0.05).

) revealed notable differences in total phenolic compounds (TPC), total tannins (TT), and total flavonoid content (TFC). The cultivar Blanco Sinaloa exhibited the highest TPC (49.2 mg GAE/100 g DW), indicating strong overall antioxidant potential, but it had one of the lowest TFC (11.2 mg CATE/100 g DW). In contrast, M-15370 showed the highest TT (27.1 mg GAE/100 g DW), suggesting potential antinutritional effects despite its antioxidant contribution, while its TFC was relatively low (11.9 mg CATE/100 g DW). Advanced lines P1/14, P7/14, and P8/14 had the highest TFC (16.8–20.8 mg CATE/100 g DW), highlighting their potential for health-promoting bioactivity. Line P10/14 had notably lower TT (10.5 mg GAE/100 g DW), which may be advantageous for nutritional quality by reducing anti-nutritional effects. Overall, the results suggest that while some genotypes like Blanco Sinaloa and M-15370 are superior in TPC or TC, others, particularly P1/14, P7/14, and P8/14, offer a balance of bioactive compounds with higher TFC.

The antioxidant activity of the chickpea genotypes, measured by ABTS, DPPH, and FRAP assays, showed clear differences that largely corresponded with their phytochemical profiles (

Table 6. Mean values of antioxidant activity of chickpea genotypes measured by ABTS, DPPH, and FRAP assays. Results were expressed as Trolox equivalents (TE) per 100 g of dry seed weight (DW).

Genotype	ABTS (mg TE/100 g DW)	DPPH (mg TE/100 g DW)	FRAP (mg TE/100 g DW)
P1/14	46.0 d	9.7 bc	69.7 b
P7/14	45.5 d	6.3 c	61.3 bc
P8/14	49.3 d	6.2 c	58.8 c
P9/14	46.4 d	12.4 bc	63.1 bc
P10/14	52.8 cd	13.3 b	70.0 b
P13/14	47.3 d	15.0 ab	60.7 bc
P14/14	57.1 bc	19.9 a	67.0 bc
M-15370	63.1 ab	10.5 bc	78.6 a
Blanco Sinaloa	65.1 a	11.5 bc	68.2 b

Different letters indicate significant differences (p < 0.05).

). The cultivar Blanco Sinaloa and elite line M-15370 exhibited the highest ABTS values (65.1 and 63.1 mg TE/100 g DW, respectively), which aligns with their high TPC (49.2 and 46.8 mg GAE/100 g DW) and high TT levels, suggesting that phenolics and tannins significantly contribute to ABTS radical scavenging. P14/14 exhibited the strongest DPPH activity (19.9 mg TE/100 g DW), despite having lower TPC, indicating that other bioactive compounds or specific flavonoids may influence free radical scavenging in this assay. In the FRAP assay, M-15370 showed the highest FRAP value (78.6 mg TE/100 g DW), consistent with its high TPC and TT. Conversely, advanced lines such as P7/14 and P8/14, while relatively high in flavonoids, displayed lower overall antioxidant activities, suggesting that flavonoid content alone may not fully evaluate antioxidant capacity. Overall, these results highlight that both TPC and TT play a key role in chickpea antioxidant potential, but the contribution of flavonoids and other bioactive compounds can vary depending on the type of assay.

3.2.4. Correlation Coefficient (r) Among Physicochemical Properties, Quality Characteristics, and Bioactive Constituents of Chickpea Seeds

The correlation matrix in Figure 4 highlights several important relationships among physicochemical properties, nutritional traits, and bioactive constituents of chickpea seeds. HC was strongly and positively correlated with HI and SC, indicating that advanced lines with higher water absorption tend to exhibit greater swelling capacity and faster hydration efficiency during soaking. Protein content showed negative correlations with hydration-related traits, suggesting that higher protein levels may slightly reduce water uptake and swelling, while fat content negatively affected HI and SCP. Among phytochemicals, TFC was highly and positively correlated with HI and SCP, but negatively correlated with all antioxidant activity traits, highlighting its role in hydration-related functional properties rather than antioxidant activity. TT was positively correlated with SI, whereas TPC showed weak correlations with most traits.

Antioxidant assays showed complementary patterns: ABTS activity was positively correlated with SI but negatively correlated with HI; DPPH activity displayed negative associations with both HI and SCP; and FRAP exhibited negative correlations with HC and HI, while showing a positive association with ABTS. Overall, these results suggest that chickpea physicochemical properties, nutritional composition, and bioactive compounds are interconnected. Hydration and swelling traits appear to influence protein retention, whereas flavonoids and tannins contribute differently to the antioxidant potential.

3.2.5. Phenolic Profile of Chickpea Genotypes

Liquid chromatography coupled with mass spectrometry (LC-MS) was employed for the characterization and quantification of phenolic compounds in chickpea seeds. The phenolic compounds detected in each genotype (Table S1) were classified into phenolic acids, isoflavones, flavone glucosides, flavonol glucosides, flavanones, and flavanols. The identification was based on their retention time as well as their UV and mass spectral characteristics. Across all chickpea genotypes, LC–MS profiling revealed a consistent presence of key phenolic acids including protocatechuic, p-hydroxybenzoic, gentisic, and caffeic acid, which were detected in all genotypes. In contrast, p-coumaric and sinapic acids exhibited greater variability, appearing only in selected genotypes. Isoflavones, including biochanin A, biochanin B, and their derivatives, were detected across all genotypes, whereas galangin was not detected. Flavone glucosides (vicenin-2, myricetin luteolin, and apigenin derivatives) and flavonols (quercetin, kaempferol, and isorhamnetin derivatives) were also widespread, though certain compounds such as rutin, quercetin-3-O-glucoside, and hyperoside were restricted to specific genotypes. Among flavanones, hesperidin and naringenin were found across all genotypes, whereas naringin was present only in specific genotypes. Flavanols such as gallocatechin were present in all genotypes, whereas catechin and epicatechin were detected in selected genotypes. Together, these findings indicate that while the core phenolic profile is shared across chickpea genotypes, several subclasses of flavonoids show genotype-dependent variation that may influence antioxidant capacity and functional properties.

The primary compounds identified belong to the isoflavone class, and their quantitative results are presented in

Table 7. Quantitative results of compounds belonging to isoflavones expressed in μg/g.

Isoflavones	P1/14	P7/14	P8/14	P9/14	P10/14	P13/14	P14/14	BS 1	M-15370
biochanin B	4.6 ± 0.57 2	2.6 ± 0.44	2.1 ± 0.23	1.3 ± 0.20	3.4 ± 0.42	1.2 ± 0.17	3.5 ± 0.49	1.2 ± 0.20	3.2 ± 0.27
biochanin B derivative	2.7 ± 0.29	8.6 ± 0.55	1. 8 ± 0.28	2.2 ± 0.38	2.9 ± 0.47	2.8 ± 0.26	3.7 ± 0.34	3.4 ± 0.33	5.3 ± 0.61
biochanin A	15.6 ± 1.10	5.9 ± 0.66	11. 5 ± 0.83	16.0 ± 1.00	13.6 ± 0.46	13.7 ± 0.54	19.4 ± 0.25	24.3 ± 1.02	21.1 ± 0.54
biochanin A derivative	9.6 ± 0.44	21. 0 ± 1.04	2.8 ± 0.10	10.7 ± 0.30	15.1 ± 0.93	9.1 ± 0.54	20.6 ± 1.40	15.0 ± 0.88	30.6 ± 1.02
biochanin A 7-O-glucoside	4.2 ± 0.38	5.7 ± 0.66	3.2 ± 0.32	5.1 ± 0.06	4.4 ± 0.39	4.1 ± 0.41	5.5 ± 0.48	6.1 ± 0.83	6.1 ± 0.18
Total isoflavones	36.7	43.6	21.3	35.2	39.4	30.8	52.7	50.1	66.2

¹ BS = Blanco Sinaloa, ² values represent the mean and standard deviation of three replicates.

. Total isoflavone content ranged from 21.3 mg/100 g DW in genotype P8/14 to 66.2 mg/100 g DW in M-15370, indicating substantial genotype-dependent variation. Among the individual compounds, biochanin A and its derivative were generally the most abundant across genotypes, contributing the largest proportion to the total isoflavone content. Biochanin B and its derivative were present at lower levels but consistently detected in all genotypes, while biochanin A 7-O-glucoside showed moderate variability. These results demonstrate that chickpea genotypes differ in both total isoflavone content and the relative distribution of individual isoflavone compounds, which could influence their phytoestrogenic and antioxidant properties.

4. Discussion

Chickpea is widely recognized as a nutritionally valuable legume due to its high protein bioavailability and balanced nutritional profile. The nutritional quality of a genotype is determined by both its physicochemical properties but also by its bioactive composition, including phenolic compounds and antioxidant capacity. According to Boukid [32], chickpea exhibited the highest protein bioavailability among legumes, with protein content reaching approximately 21.07%. Furthermore, Sandu et al. [33] reported that the protein content of chickpea ranges from 18 to 26%. Koskosidis et al. [34] reported values of 21.57% for the cultivar cv. Amorgos under off-season sowing, 20.65%, for Blanco Sinaloa, and 21.17% for the advanced line 9/14. Similar ranges were documented across global germplasm collections [35,36,37]. In contrast, the present study revealed consistently higher protein levels across all evaluated genotypes, especially the advanced lines (22.6–25.4%), with P9/14 exhibiting the highest concentration. This finding underscores the nutritional potential of the breeding material examined and suggests that targeted selection within these lines could further enhance protein-rich chickpea cultivars.

Lipid and ash content in our study fell within the expected chickpea range [38], confirming the stability of these traits across diverse genetic backgrounds. Blanco Sinaloa exhibited the highest lipid content among the studied genotypes, consistent with earlier reports [36], while P9/14 combined high protein with moderate fat levels, an advantageous profile for both nutritional quality and processing applications. Total carbohydrate levels were also within the typical range for dried chickpeas, aligning with values previously reported [39]. Collectively, these results highlight the strong nutritional foundation of the evaluated breeding lines, with P9/14 and P14/14 emerging as particularly promising candidates.

The analysis of bioactive compounds revealed moderate levels of TPC, TT, and TFC were assessed, along with antioxidant capacity using three complementary analytical methods. Although the TPC values in this study (42.0–49.2 mg GAE/100 g) were lower than those reported by Xu et al. [40], Koskosidis et al. [34], and Kaur et al. [41], they remain within the broad range documented for kabuli chickpeas. Importantly, the moderate tannin levels (10.5 to 27.1 mg GAE/100 g) observed here, compared to Koskosidis et al. [34], and other legumes such as pea and faba bean [42,43,44] are nutritionally favorable, as excessive tannins can reduce protein digestibility and nutrient utilization [39,45]. The TFC values (11.2 to 20.8 mg CATE/100 g) confirm that the evaluated lines are a meaningful source of antioxidant flavonoids, consistent with previous findings on chickpea bioactive composition [4,37,43].

Antioxidant activity was evaluated using ABTS, DPPH, and FRAP assays and demonstrated clear genotype-dependent variation. Although ABTS values (45.5 to 65.1 mg TE/100 g) were lower than those reported by Koskosidis et al. [34], the relative ranking of genotypes was consistent, with M-15370 and Blanco Sinaloa exhibiting strong radical scavenging capacity. Notably, P14/14 exhibited the highest DPPH activity, indicating the presence of specific compounds with strong hydrogen-donating ability. These results align with the findings of Heiras-Palazuelos et al. [37], who also reported strong genotype-dependent differences across antioxidant assays, and highlight the importance of using multiple analytical methods to capture the full spectrum of antioxidant mechanisms.

Comparative studies on European chickpea germplasm have emphasized the diversity of phenolic compounds across kabuli and desi types [17,46,47]. Consistent with these findings, our LC–MS profiling identified a wide array of phenolic acids, flavonoids, and isoflavones. The detection of compounds such as 4-hydroxybenzoic acid, gentisic acid, and multiple flavones and flavonol glycosides aligns with earlier reports [17,41]. Importantly, the predominance of biochanin A (BCA) and its derivatives across all genotypes corroborates previous studies identifying BCA as the major isoflavone in chickpea [4,7,48]. The genotype-dependent variation observed in flavonol glycosides, flavanones, and flavanols further underscores the biochemical diversity present within advanced breeding material. Recent metabolomic studies using LC–MS have similarly highlighted substantial variation in chickpea phenolic subclasses [49], supporting the patterns observed here.

Seed functional traits such as hydration capacity, swelling behavior, and seed coat proportion also varied significantly among genotypes. These findings are consistent with earlier work demonstrating that seed coat thickness, composition, and microstructure strongly influence hydration behavior [8,13,41]. The superior hydration and seed coat characteristics of P8/14 and the high swelling capacity of Blanco Sinaloa reflect underlying structural differences that may be exploited in breeding programs targeting improved processing quality.

A key novelty of this study lies in the integration of agronomic, nutritional, functional, and LC–MS phenolic data within the same set of advanced breeding lines. While previous research has typically examined these traits separately, few studies have combined these datasets to identify genotypes with superior multi-trait performance. This holistic approach provides a more comprehensive understanding of trait interactions and supports more informed selection decisions in breeding programs.

When comparing field and laboratory results, two advanced breeding lines emerged as particularly noteworthy. P9/14 exhibited the highest biomass and seed yield, early maturity, and the highest protein content among genotypes; however, its elevated seed moisture after harvest, which negatively affects seed quality, may restrict its suitability for direct cultivar release. In contrast, P14/14 combined strong agronomic performance with favorable nutritional and bioactive traits. Its elevated protein and ash contents, moderate fat levels, strong antioxidant capacity, and notably high BCA concentration position it as a highly promising candidate for breeding programs targeting enhanced nutritional quality and functional food applications.

5. Conclusions

In this study, a combined approach integrating field phenotyping, seed quality assays, and LC–MS-based phenolic profiling was used to highlight substantial genetic variation in agronomic, nutritional, and phytochemical traits among Cicer arietinum genotypes. This methodology supports the effective selection of chickpea breeding lines with a superior nutritional profile. Among the evaluated genotypes, P14/14 consistently demonstrated the most favorable profile combining strong nutritional composition with high antioxidant capacity (ABTS 57.1 mg TE; DPPH 19.9 mg TE/100 g DW) and the highest biochanin A concentration (19.4 mg/g), underscoring its strong nutritive potential for functional food applications. Furthermore, the advanced breeding line P9/14 exhibited promising characteristics, including high yield, earliness, and elevated protein (25.4% DW) and fat (6.2% DW) contents. Overall, these findings emphasize the value of integrating detailed biochemical profiling for identifying multi-trait superior genotypes and strengthen breeders’ ability to select lines that meet both productivity and nutritional quality value, supporting the development of improved chickpea cultivars.