Investigation of Flower Yield and Quality in Different Color Safflower Genotypes

Abstract

The present study was carried out to determine variations in flower and dye yield and chemical contents of safflower genotypes with different flower colors in 2017–2018. The flower and dyestuff yields of the genotype ranged between 6.6–12.0 kg da⁻¹ and 218.1–421.7 g da⁻¹, respectively. The TPC and high antioxidant capacity values were listed according to flower color as yellow > orange > red > white. Gallic, rosmarinic and chlorogenic acid were higher in orange-flowered genotypes, kaempferol in red-flowered and catechin in yellow and orange-flowered. The oil content ranged between 4.32–6.12%. In flowers, linoleic acid ranged between 32.77–48.27%, α-linolenic acid 1.85–3.38% and γ-linolenic acid 14.76–18.50%. According to the Headspace Solid Phase Microextraction (HS-SPME) technique; the main scent molecules of flowers were β-caryophyllene, α-pinene, 1-tetradecene, β-cedrene, α-cedrene and β-myrcene. The C* value of flowers was positively correlated with the total phenolic content and dyestuff content in both years, and genotypes with high C value showed high antioxidant activity. Askon-42 can be recommended for high flower yield, dyestuff content and yield among genotypes, and US-10 genotype for the total phenolic content and antioxidant activity. For further research, it will guide the use of different colored safflower flower extracts, which are natural dye sources, in natural cosmetic products.

1. Introduction

Safflower (Carthamus tinctorius L.) (2n = 24), a member of the Compositeae family, is an ancient oil crops cultivated in the Middle East about 3000 years ago. According to the world’s 2021 safflower production data, safflower was cultivated in an area of 850.431 hectares and 631.051 tons of seeds were produced. India, USA, Mexico, Ethiopia and Argentina are the world’s largest safflower producing countries, and 95% of safflower production is in these countries [1]. Safflower is mostly grown in dry agricultural areas for cooking oil due to its higher adaptability to arid regions with low rainfall compared to other oil crops, and it has relatively good cold resistance [2]. The oil content of safflower seeds varies between 25–45% depending on the genotype, ecology, physiology, morphology and agricultural practices. There are high oleic, high linoleic and medium oleic/linoleic acid types of safflower oils in the world. Besides the production of margarine, mayonnaise and salad oil, safflower oil is also used in the production of high quality paint resistant to wrinkling and high humidity due to its quick drying feature. The pulp remaining after the oil is extracted is a valuable animal feed [2,3].

One of the most important parts of the safflower plant, apart from the seeds and fixed oils, is the flowers. Safflower flowers were cultivated in Egypt, Morocco, China and India as early as 4500 BC [4]. It is stated that it was known as a dye plant in 1600 BC, and in archaeological studies in Egypt, the linen, wrapping and textiles used in King Amenhotep’s mummy and other mummies were dyed with safflower flowers [4]. Safflower flowers are still used traditionally in many countries (especially Egypt, Arabia, Iran, India, China, Korea and Japan) as food, food coloring, health, cosmetics or cut flowers [5,6]. In a study on safflower petals, it was reported that the dye content of safflower flowers was 0.83%, oil content was 5%, protein content was 1.9%, fiber content was 12.2%, Ca content was 530 mg, Mg content was 287 mg and Fe content was 7.3 mg 100 g⁻¹ [7]. Medically, the dye components in safflower flowers are used in traditional medicine, the treatment of cardiovascular diseases, menopausal problems, pain relief, swelling caused by trauma and reducing fever [8,9]. It also reduces hypertension, accelerates blood flow and lowers cholesterol levels in the blood [10].

Secondary metabolites in safflower are diverse, producing a wide range of plant metabolites such as organic acids, alkaloids, flavonoids, and quinochalcone C-glycosides, all of which have chemotaxonomical relevance. Among quinochalcones, the major components (safflomins) contained in safflower are hydroxysafflor yellow A and its “dimer” anhydrosafflower yellow B, and safflor yellow A [11,12,13,14]. Conjugation of the two quinocalchone moieties results in the red pigment carthamin, which is likewise unique to this matrix [15]. Compared to carthamin (red), large quantities of yellow pigments are present in safflower. The light fastness of the yarns dyed using safflower and mordant is also high [15]. However, safflower yellow pigments are more stable under ultraviolet (UV) light than carthamin. Because of these components, the commercial value of dyes and dyed products obtained from safflower flowers is very high. However, with the discovery of synthetic dyes in the middle of the 19th century, natural dyes and natural dyeing have lost their importance until today [16]. When cheaper synthetic aniline colors were invented in 1856, the traditional use of natural dyes was further pushed into the background. Today, there is a tendency to use natural resources instead of synthetic dye compounds in the preparation of raw materials in pharmaceuticals, food, cosmetics and textile products [17,18]. The reason for this is that issues such as synthetic materials being harmful to human health, direct contact of fabrics with skin causing allergies, their disintegration in water, and polluting the environment through waste water are taken seriously around the world [19]. It has been reported that artificial food colorings may adversely affect children’s behavior or cause carcinogenic or allergic effects [17,20]. Due to a ban on the use of synthetic colors in foods in some European countries and other countries, the use of safflower flowers as a color source in food and textile products, as in other dye plants, has gained great importance [21]. Colorants obtained from safflower flowers have some advantages over other colorants in the textile industry, especially in terms of light, temperature and pH value, and are cheaper than saffron [22,23].

Safflower’s phenolic compounds play an important antioxidant role. Safflower petals’ phenolic composition and antioxidant activity have previously been investigated [12,13]. Gallic acid was found to be the most abundant phenolic acid in Carthamus tinctorius flowers, followed by chlorogenic acid, syringic acid, quercetin-3-galactoside, and epicatechin [13]. These phenolic compounds play important roles for antibacterial and anticarcinogenic functions in reducing the risks of various health problems such as cardiovascular diseases, diabetes, atherogenesis and cancer [24,25,26]. Antioxidant activity is also demonstrated by hydroxysafflor yellow B [27], hydroxysafflor yellow C [28], safflor yellow A [29], and carthamin [30]. The bioactive properties of hydroxysafflor yellow A, used in Chinese medicine for the treatment of cerebrovascular and cardiovascular diseases, have been previously studied [31,32,33,34]. Anti-inflammatory properties [33] and neuroprotective effects have been reported [31]. Moreover, hydroxysafflor yellow A significantly inhibits the abnormal proliferation of tumor cells in the culture, without affecting normal endothelial cell growth [35].

The cultivation of the safflower plant for its flowers around the world is currently limited. It is still mainly grown in Asian countries for its flowers. The flower yield is normally 7–14 kg da⁻¹ in Bangladesh, and the crop is harvested when it is fully grown, thus yielding both dye and oilseeds [36]. However, the amount of safflower flowers produced in Asia will no longer be sufficient to meet the growing demand of the food coloring industry, especially in Europe and other Western countries. For this purpose, it is necessary to increase the agriculture for flower production in other countries where safflower production is made, such as Turkey. For flower production, safflower is mainly harvested by hand, which is very slow, laborious and expensive. Production efficiency is very low due to the absence of an industrially produced harvester for this type of use so far. This economically constrains large-scale flower production [37,38,39]. However, with the opening of new areas of use in safflower flowers, the solution of harvesting problems in safflower flowers can be investigated and safflower flower harvesting can be done in larger areas. Apart from harvest mechanization, first of all, genotypes with high flower yield and quality should be developed for safflower, and the suitability of these genotypes for food, health and textile industry should be tested. In our study, the flower yield and quality of safflower genotypes with different flower colors, which have potential in these areas of use, were examined.

2. Materials and Methods

2.1. Material

The present study was conducted in the Department of Field Crops, Faculty of Agriculture, Isparta Applied Sciences University, Isparta-Türkiye (37°45′ N and 30°33′ E, 997 m) in 2017 and 2018. Remzibey-05 (2) and US-10 (8) genotypes with yellow flower; Dinçer 5-18-1 (1), Yenice 5-38 (3), Leed (7) and Askon-42 (Bay-Er 14) (5) genotypes with orange flower; AC Sunset (6), Olein (Bay-Er 13) (10) and Gelendost (4) genotypes with red flower; Arizona Safflower Composite III (9) genotypes with white flower were used as plant material (Figure 1). Olein (Bay-Er 13) and Askon-42 (Bay-Er 14) were obtained by hybridization with Dinçer 5-18-1 × Montola 2000, and these cultivar candidates were applied for cultivar registration in 2016. On the other hand, the Gelendost line was developed by selection from safflower fields in the Isparta province.

2.2. Methods

2.2.1. Soil and Climate Characteristics of the Research Field

Soil characteristics of the research field were assessed according to the method proposed by Rowell [40]. The soil texture was clay loam; lime was 7.2% by Scheibler calcimeter (Lita Analytical, Ankara, Turkey); the organic matter was 1.1% by the Walkley–Black method; exchangeable K (potassium) was 119 mg kg⁻¹ by 1N NH₄OAc (ammonium acetate); total salt was 0.38%; the pH in a soil saturated extract was 7.5 and extractable P (phosphorus) was 3.9 mg kg⁻¹ by 0.5N NaHCO₃ (sodium bicarbonate) extraction. The total precipitation, mean humidity, minimum and maximum temperatures and long term averages for the experimental area were given in

Table 1. The climatic data for long years and 2017–2018 in Isparta (Turkish State Meteorological Service).

Month	Total Precipitation, L m2			Mean Temperature, °C							Mean Humidity, %
	1950–2018	2017	2018	1950–2018	2017			2018			1950–2018	2017	2018
					Min.	Max.	Mean	Min.	Max.	Mean
March	57.3	74.4	69.3	6.1	−4.4	21.8	7.3	−1.6	20.4	9.2	65.6	64.1	65.9
April	51.6	25.6	6.3	10.7	−0.9	25.5	10.6	0.0	28.3	14.2	60.8	59.6	51.0
May	55.7	149.5	62.9	15.2	4.0	31.9	14.9	5.8	29.6	16.8	58.7	63.7	62.3
June	32.6	30.9	69.4	19.8	6.6	35.8	20.1	10.3	32.6	20.0	52.1	58.9	62.4
July	16.5	13.1	4.1	23.3	12.6	34.3	24.3	13.8	38.6	25.2	45.4	41.9	46.9
August	13.4	20.4	14.2	23.1	12.1	36.9	23.8	12.1	34.4	24.3	46.3	52.1	47.6
TOTAL	227.1	313.9	226.2
MEAN				16.4	5.2	31.8	17.0	6.5	29.9	18.1	54.8	56.7	56.0

. According to the climate data, there was not very high or low temperature and precipitation during the vegetation period (March–August) that would seriously affect the normal growth and development of the genotypes. In 2017, 280.4 mm of total precipitation fell from the sowing of seeds to the flowering time of the plants (beginning of March–end of June), while it was 207.9 mm of precipitation in 2018. On the other hand, 25.6 mm of precipitation was falling in April 2017; the amount of precipitation was 6.3 mm in 2018. During the seed maturing period, differences of 0.9 °C in July and 0.5 °C in August were observed in both experimental years.

2.2.2. Trial Fields

The genotypes were evaluated in a randomized complete block design with three replications. Seeds of genotypes were sown by hand on March 12 and 26, 2017 and 2018, respectively. Sowing norm was 0.50 × 0.15 m. The plot length was 5 m and each plot contained 5 rows. Experimental areas were fertilized with 8 kg da⁻¹ of P (18% N, 46% P) and 10 kg da⁻¹ of N (33% N). Weed control was performed by mechanical rotary tillage and manual weeding. Experimental areas were not irrigated. The flowers of the genotypes were harvested when dry on the head about 3 weeks after pollination and fertilization. The dry flowers of genotypes were harvested in the three middle rows except for the outer rows of the plot by hand on 20–27 July 2017 and 24–31 July 2018. All genotypes were harvested after the flowers dried on the head. The flowers were dried for 2 weeks in shade room conditions until they reached constant humidity (6.3%). Agronomic characters such as flowering day and flower yield (kg da⁻¹), quality characters such as scent molecules by HS-SPME GC-MS, dyestuff content (%), dyestuff yield (kg da⁻¹), total phenolic content (TPC) and compounds, antioxidant activity (DPPH and CUPRAC), the color values (L*, a*, b*, C* and h° values), oil content (%) and fatty acid composition (%) were examined in dried safflower flowers.

2.2.3. Chemical Analysis of Flowers

Color values: The color value in the flower was measured with a colorimeter (Minolta CR 300, Ramsey, NJ, USA). Color measurements were performed at two points on both surfaces of petals selected randomly in each replication and given as the mean value of both surfaces. The colorimeter apparatus was calibrated according to standard white plate (Y = 93.9, x = 0.313 and y = 0.321). The values were evaluated according to CIE L* (represents brightness–darkness changing from 0 to 100), a (+ a^*: red, − a^*: green) b (+ b^*: yellow, − b^*: blue), C* (represents vividity of color) and h° (represents perceived color) system. The chroma (C*) and hue angle (h°) values were calculated with the following formulas; h° = tan⁻¹ (b*/a*), C* = [(a*)² + (b*)²]^1/2 [41,42].

HS-SPME-GC-MS analysis: The dry flowers of safflower were subjected to solid phase microextraction (SPME, Supelco, Interlab, İstanbul, Turkey) with a fiber precoated with a 75 μm-thick layer of Carboxen/Polydimethylsiloxane (CAR/PDMS). Then, 2.0 g of newly hand-picked flowers were put into a 10 mL vial, which was then immediately sealed with a silicone septum and a crimp cap. After incubation for 30 min at 60 °C, SPME fiber was pushed through the headspace of a sample vial to adsorb the volatiles, and then inserted directly into the injection port of the GC-MS (Shimadzu, Ant Teknik, Ankara, Turkey, 2010 Plus GC-MS with the capillary column, Restek Rxi^®-5Sil MS 30 m × 0.25 mm, 0.25 μm) at a temperature of 250 °C for desorption (5 min) of the adsorbed volatile compounds for analysis. Identification of constituents was carried out with the help of retention times of standard substances by composition of mass spectra with the data given in the Wiley, NIST Tutor, FFNSC library. LRIs (Linear Retention Indices) were calculated by using a series of the standards of C₇-C₃₀ saturated n-alkanes (Sigma-Aldrich Chemical Co., Darmstadt, Germany) for reference in the same column and conditions as described above for GC-MS analysis.

Dyestuff content (%): 3 g of ground safflower flowers were placed in tubes containing 2 M HCl and the tubes were boiled in a water bath at 100 °C for 30 min After the tubes were cooled at room temperature, the dyestuff was extracted with ethyl acetate. Ethyl acetate was removed in a rotary evaporator at 40 °C, the remaining extract was weighed and the amount of dyestuff was calculated as % [43].

Total phenolic content (TPC) and compounds: Safflower flowers (0.2 g) were powdered in liquid nitrogen, mixed with 10 mL of 80% cold methanol for 15 min at 120 rpm with a magnetic stirrer and centrifuged at 6.000× g for 10 min at 4 °C. The supernatant was removed and the same procedure was repeated twice. The collected supernatant was filtered through Whatman no. 1 filter paper and the volume was made up to 25 mL with 80% cold methanol. Soluble phenolic content was determined from the extracts. The soluble phenolic content was determined by the modified Folin–Ciocalteau method [44]. The reaction mixture contained 0.1 mL Folin–Ciocalteu reagent (Sigma) (2 N), 0.5 mL 20% sodium carbonate, 2.5 mL deionized water and 0.1 mL of the methanolic extract. The reaction mixture was incubated in the dark for 30 min to develop color, and absorbance was determined at 760 nm. The standard curve was prepared using gallic acid. For phenolic compounds of flowers, 3 g of safflower genotypes were mixed with 30 mL of methanol and extracted for 1 h in an ultrasonic bath. Subsequently, the homogenates filtered through a Whatman no. 4 filter paper and evaporated in a rotary evaporator at 40 °C, and the extract dissolved in methanol was prepared for injection into high-performance liquid chromatography (HPLC). Separation was performed on a 250 × 4.6 mm, 5 μm Agilent Eclipse XDB-C18 (Sem Laboratory Devices, İstanbul, Turkey) reversed phase column and the column temperature was 30 °C and the flow rate was maintained at 0.8 mL min⁻¹. The injection volume was 20 μL, and peaks were observed at 278 nm. The gradient program was as follows: 72% A/28% B 0–20 min, 70% A/30% B 20–50 min, 67% A/33% B 50–60 min, 58% A/42% B 60–62 min, 50% A/50% B 62–70 min, 30% A/70% B 70–73 min, 20% A/80% B 73–75 min and 100% B 75–80 min. The mobile phase consisted of acetic acid (solvent A) and methanol (solvent B). The mobile phase composition was reset to baseline after 85 min and allowed to run for an additional 10 min before another sample was injected. The peaks of the petal samples were identified based on the matching retention times compared to those of the authentic standards. The phenolic compound content was expressed in µg g⁻¹ dry weight.

Antioxidant Activity Assays:

1,1-diphenyl-2-picryl-hydrazyl (DPPH), free radical scavenging activity: The free-radical-scavenging capacity of the flower extracts was evaluated, using the DPPH stable radical and following the methodology described by Gulcin [45]. Briefly, 0.1 mM solution of DPPH in ethanol was prepared and 1 mL of this solution was added to 3 mL of flower extract solution in ethanol at different concentrations (10–20 µgmL⁻¹). After 30 min, the absorbance was measured at 517 nm against ethanol as a blank in a spectrophotometer (Perkin Elmer Lambda 20 UV VIS Spectrophotometer, PerkinElmer Health and Environmental Sciences Co. Ltd., İstanbul, Turkey). The lower the measured absorbance value of the reaction mixture, the higher the free radical scavenging potential. The DPPH concentration (mM) in the reaction medium was calculated from the calibration curve determined by linear regression (R² = 0.9978):

Absorbance = 10.345 × [DPPH•] + 0.0601

The ability to sweep the DPPH• radical was counted up using the following equation:

DPPH scavenging effect (%) = [(A_Control − A_Sample/A_Control) × 100]

where A_Control is the absorbance of the control reaction (ethanol solution containing 0.1 mM DPPH) and A_Sample is the absorbance in the presence of flower extracts and standards (butylated hydroxytoluene and butylated hydroxyanisole).

Cupric reducing antioxidant capacity (CUPRAC): The CUPRAC activity of flower extracts was performed according to the method of Apak et al. [46] CUPRAC reactions were set up as follows: 1 mL of 0.01 M copper (II) chloride, 1 mL of 0.0075 M neocuproine solution and 1.0 mL of 1 M ammonium acetate buffer solution (pH 7.0) were added successively into a glass tube. All solutions were prepared in absolute ethanol. Subsequently, X mL of extract solution and “1.1 − X” mL absolute ethanol were added to obtain a total volume of 4.1 mL and mixed well. Absorbance against a reagent solution without a sample was measured at 450 nm after 30 min Analysis tests were performed in triplicate and CUPRAC activity was calculated as Trolox equivalents per g of flower extract (µmol TR g⁻¹ g dry flower), through a calibration curve with Trolox standard.

$$CUPRAC \left({\mathsf{\mu }\mathrm{mol}\mathrm{TR}\mathrm{g}}^{-1}\right)=\frac{A}{{\epsilon }_{TR}}\times \frac{V_m}{V_s}\times D_f\times \frac{V_E}{m}\times 1000$$

where A: Sample absorbance measured at 450 nm; ε_TR: molar absorption coefficient of Trolox compound in the CUPRAC method (1.67 × 10⁴ L mol⁻¹ cm⁻¹); V_m: Total volume of CUPRAC method measuring solution; V_s: Sample volume (mL); D_f: Dilution factor (if needed); V_E: Volume of the prepared extract (mL); and m: The amount of flower extract taken in the extraction process (g).

The oil content and fatty acid composition: The oil content of dry flowers was analyzed by nuclear magnetic resonance (NMR, Bruker, Ant Teknik, Ankara, Turkey) and gas chromatography (GC-FID, Shimadzu GC-2025, Ant Teknik, Ankara, Turkey), respectively [2]. The oil content of 2.0 g of flower was detected in NMR. To analyze the fatty acid composition, dry flowers (3 g) were mixed with 20 mL chloroform:methanol (2:1) solution and incubated for 4 h at room temperature on a rotary shaker. The homogenates filtered through a Whatman no. 4 filter paper were evaporated in a rotary evaporator at 40 °C, and the extracts were added to methanol-HCL solution and incubated for 90 min at 80 °C. Then, the samples were mixed with hexane and incubated overnight. The hexane phase (1 μL), where the esterified fatty acids (FAME) were collected, was injected into the GC-FID. The injector and detector temperatures were 250 °C and 260 °C, respectively. Separation was performed on a 100 × 0.25 mm, 0.20 μm Teknokroma TR-CN100 select-FAME column. Nitrogen was used as the carrier gas at an internal pressure of 10 psi. After waiting for 10 min at 140 °C, the temperature was increased to 240 °C with an increase of 3 °C per min and maintained at this temperature for 10 min. Peak identification was conducted by comparing the relative retention times with those of a commercial standard mix of fatty acid methyl esters (Sigma, Supelco^® 37 Component FAME Mix, Ant Teknik, Ankara, Turkey). The concentration of a fatty acid in the chromatogram obtained as a result of GC-FID analysis was determined by the ratio of the area of that fatty acid in the chromatogram to the area of all peaks and were calculated on a relative percent basis.

2.3. Statistical Analysis

All data were analyzed using GLM producers of SAS 9.0 [47] and means were compared using Tukey Test at the probability level of 0.05. The mean values of the examined characters of genotype were used for multivariate principal component analysis (PCA). Hierarchical cluster analysis (HCA) and the corresponding heatmap for phenolic compounds, fatty acids and floral scent compositions of genotype flowers were performed using the ClustVis online tool [48]. Unit variance scaling is used for normalized and approximated data. Pearson correlation was used for distance measurements for HCA and average cluster analysis method was used over the tightest cluster first for phylogenetic relationship. To show the relationship between the measured characters, Pearson linear correlation analysis (Heatmap correlation) for the examined characters was calculated using OriginPro software (version 2021, OriginLab, Northampton, MA, USA).

3. Results and Discussion

According to the results of ANOVA, the differences among the years (except for dyestuff content, dyestuff yield, b* value and TPC), genotypes and year × genotype were significant for all characteristics (

Table 2. The ANOVA results of variance on the flower yield and quality characteristics of genotypes.

Sources of Variance	DF	Flower Yield (kg da−1)	Dyestuff Content (%)	Dyestuff Yield (g da−1)	L* Value	a* Value	b* Value	Chroma Value (C*)	Hue Angle (h°)	Total Phenolic Content (µg g−1)	DPPH	CUPRAC	Oil Content (%)
Block	2	0.43 a	0.01	1332.77	0.02	1.11	2.44	1.27	0.24	0.04	0.02	0.41	0.001
Year (Y)	1	2.89 *	0.02	2483.26	174.14 **	26.40 **	7.76	30.37 **	16.08 **	32.25 **	11.58 **	486.89 **	30.64 **
Genotype (G)	9	18.26 **	0.58 **	29,000.80 **	327.78 **	639.54 **	166.75 **	176.96 **	1257.65 **	36.86 **	35.25 **	1173.35 **	0.11 **
Y × G	9	1.83 *	0.05 **	2670.05 **	6.68 *	5.77 **	9.15 **	6.94 **	13.05 **	1.34 **	0.47 **	19.53 **	0.03 **
Error	38	0.68	0.01	885.98	2.41	0.70	2.44	2.29	1.58	0.34	0.12	5.09	0.001
CV (%)		8.62	3.16	9.34	3.50	4.54	4.23	3.56	1.96	3.27	3.24	3.21	0.68

^a, mean squares of characters; DF, degree of freedom; CV, coefficient of variation; * p < 0.05; ** p < 0.01.

). The mean values of all the traits examined in the study in both years were presented in Figure 2.

3.1. Flower Yield

The flower yields of the genotypes were higher (9.8 kg da⁻¹) in 2017. The flower yields were between 7.3–12.0 kg da⁻¹ in 2017 and 6.6–11.7 kg da⁻¹ in 2018. The highest flower yield was obtained in the Gelendost, Askon-42 and Yenice genotypes in both years. The lowest flower yields were determined in the Leed and US-10 genotypes (Figure 2a). It was thought that because there was more precipitation in 2017 during the plant’s growing season (April to June), the plants grew more successfully and produced more flowers. The very low amount of precipitation in the month (April) after the establishment of the experiment in 2018 could have caused poor growth in the plants while they were still in the seedling stage. At the same time, planting 20 days earlier than 2018 in the first year of the study could be one of the reasons for the increase in flower yield. The genotype differences in safflower can affect the flower yield. Kırıcı [36] reported that the flower yield in genotypes with yellow and red flower color varies between 8.19–12.07 kg da⁻¹ in the base land and 4.05–5.47 kg da⁻¹ in the barren land. Similarly, it was reported that different plant densities and sowing times also change flower yields, and that flower yields decrease in dense plantings and increase in early sowing [49]. In different genotypes, El-Hamidi et al. [50] reported that the flower yield of safflower ranged between 12.1–13.7 kg da⁻¹ and Dajue and Mündel [10] ranged between 7–14 kg da⁻¹.

3.2. Dyestuff Content

The dyestuff content in flowers varied between 2.55–3.76% in 2017 and 2.62–3.65% in 2018. The dyestuff content of the genotypes was higher in 2017. In our study, sowing earlier in 2017 compared to 2018 might be the reason for the increase in flower yields and also the increase in the synthesis of dyestuffs in flowers (Figure 2b). Patanè et al. [49] found significant increases in the number of heads and flower yield, as well as the amount of carthamin and safflomins, in early sown safflower plants. Thus, the delay in sowing time suppressed the biosynthesis or caused the degradation of the pigments in the safflower flower. On the other hand, in the location where our study was carried out, higher temperatures were experienced in July, which was the time of flowering, in 2018 compared to 2017 (Table 1). This might have affected the dyestuff synthesis and might be the reason for the decrease in the dyestuff content in flowers in 2018. Indeed, it had been reported that natural colorants were very sensitive to external factors such as temperature, light, pH, etc. In particular, carthamin was found to be more unstable than yellow pigments at high temperature and in daylight [51]. However, Patane et al. [49] found negative and significant correlations at low (r = −0.94**) and high (r = −0.86**) air temperatures for both color pigments. It was obvious that the total dyestuff content was affected by the sowing time and air temperatures [49], and this literature supports our study. In our study, the highest dyestuff content was detected in the orange-flowered Dinçer 5-18-1, Yenice 5-38, Askon-42 and red-flowered AC Sunset genotypes in both years, and the lowest in the white-flowered Arizona SC III genotype (Figure 2b). Safflower has seven different flower colors, from white to red. In some types, a color change was also observed towards drying after flowering. For example, the flower color was yellow immediately after flowering and may gradually turn red. An oxidative enzyme (β-glucose oxidase) contributes to the yellow to red color transition of safflower petals during the ripening stage of the flowers, and this enzyme activity affects the dye content [52]. In our study, the dyestuff content was found to be higher especially in orange colored flowers. Since plants with this flower color are especially yellow (hydroxysafflor yellow A and its “dimer” anhydrosafflor yellow B) and contain carthamidin, it was possible that the accumulation of dyestuffs was high. Safflower flowers contain about 30% yellow pigments [21] and 0.83% red pigments [7,53]. As a matter of fact, Kırıcı and Inan [9] reported that the varieties with orange flowers contained higher dyestuffs in safflowers grown on the bottom and barren lands. Since the Arizona SC III genotype had white flowers, the synthesis of the pigment would be less; therefore, low dyestuff was an expected result. The natural dye obtained from the safflower flower shows excellent fastness properties when dyeing cotton, silk and wool. The dye was extracted from the flower petals with alkaline solution keeping the pH between 8 and 9 [54]. Therefore, safflower dye has commercial natural dyeing potential and can be considered a safe alternative to azoic direct yellow dye.

3.3. Dyestuff Yield

The dyestuff yield per unit area was directly proportional to the flower yield and dyestuff content. The dye yield of the genotypes varied between 218.1–421.7 g da⁻¹. The highest dyestuff yield was in Dinçer 5-18-1 (413.2 g da⁻¹) and Askon-42 (420.3 g da⁻¹) genotypes in 2017. In 2018, it was detected in Yenice 5-38 (421.7 g da⁻¹) and Askon-42 (416.7 g da⁻¹) genotypes. In these three genotypes, both the flower yield and dyestuff content were high. The lowest dye yield was determined in the US-10, Olein and Leed genotypes in both years (Figure 2c).

3.4. Color Values

The mean color values of the safflower genotypes were obtained by measuring the chromatic parameters L*, a*, b*, c* and h° as shown Figure 2d–h. The L*, a*, b*, c* and h° values in the red-flowered safflower genotypes were between 37.8–44.0, 20.2–29.3, 29.7–38.1, 38.1–46.8 and 51.2–62.0, respectively, between 36.4–46.7, 14.9–28.9, 32.3–43.0, 41.1–46.1 and 41.1–46.8 in orange flowers, between 45.1–49.7, 4.2–8.8, 41.0–45.6, 41.8–46.5 and 79.0–84.6 in yellow flowers and between 63.1–62.4, 1.6–1.7, 27.5–28.1, 27.6–28.2 and 86.4–86.8 in white flowers, respectively (Figure 2d–h). The Arizona SC III genotype had the highest gloss value on surfaces (Figure 2d), Yenice 5-38 and Askon-42 have the highest redness value (Figure 2e), US-10 had the highest yellowness value (Figure 2f), Yenice 5-38 and Leed had the highest vitality value (Figure 2g), and US-10 and Arizona SC III have the highest exhibited high h° value (Figure 2h). It was seen that the h° value increases and the C* value decreases as the flower colors of the genotypes go from red to white. Although differences were observed in genotypes in terms of dyestuff contents, the differences observed in terms of color values according to years were so small. Pu et al. [55] used biological and color analysis to conduct a comprehensive assessment of safflowers in various production areas. Based on color measurements, all safflower samples were classified as class I or class II. The L*, a*, and b* values in the safflower samples ranged from 30.9–53.5, 19.6–34.5, and 25.9–55.6, respectively. Thus, the authors proposed that class I safflowers were brighter, redder, more yellow, more orange-yellow, and more vivid to the eye than class II safflowers. In our study, all genotypes showed a similar trend in L*, a* and b* values except for the Arizona SC III, US-10 and Remzibey-05 genotypes. Although carthamin has a limited use in the food industry due to its low water solubility, it is used in the production of chocolate in countries such as Japan and China [56,57].

3.5. The TPC and Antioxidant Capacity

Average TPC values of safflower genotypes ranged from 12.3–21.3 µg g⁻¹ dry flower. The highest TPC value was detected in yellow flowered genotypes (Remzibey-05 and US-10) in both years. The TPC value varied between 16.2–20.6 µg g⁻¹ dry flower in orange-flowered genotypes and between 16.0–18.6 µg g⁻¹ dry flower in red-flowered genotypes. Arizona SC III genotype had the lowest TPC value. The TPC value in 2017 was higher than in 2018 (p < 0.01) (Figure 2i). The high temperature value in July 2017, when flowering occurs, can be the reason for the increase in phenolic substance synthesis in flowers. Erbas et al. [58] also reported that high temperatures could increase the synthesis of phenolic compounds in plants. In terms of antioxidant activity results, the DPPH values and CUPRAC values of the genotypes showed a similar variation with the TPC values of the genotypes. The highest DPPH and CUPRAC values were again detected in the US-10 (respectively, mean 14.0% and 95.1 mg TE g⁻¹ dry flower) and Remzibey-05 (respectively, mean 13.3 and 90.4 mg TE g⁻¹ dry flower) genotypes. These genotypes were followed by Leed (respectively, mean 11.5 and 76.2 mg TE g⁻¹ dry flower). On the other hand, the DPPH and CUPRAC values of both years of the Arizona SC III genotype were at the lowest level compared to the other genotypes (Figure 2j,k). There is limited research on the TPC, DPPH and CUPRAC properties of safflower flowers. In chronological order; Baydar and Özkan [59] reported that the TPC values in petals of the safflower cultivars Dinçer 5-18-1, Yenice-05 and 5-154 in 80% aqueous methanol (v:v) were 9.06, 20.92 and 16.62 mg GAE g⁻¹ dry matter, respectively.

Hiramatsu et al. [60] reported that yellow-flowered safflower contains lower levels of carthamin than orange-flowered plants, and that no carthamin was detected in white-flowered plants. Salem et al. [13] showed that safflower flowers had 15.09 mg GAE g⁻¹ dry weight TPC content as a result of extraction with 2% aqueous acetone (v:v). Karimkhani et al. [61] reported that the TPC and antioxidant capacities of methanolic extracts of the flowers of four different safflower genotypes ranged from 46.2 to 62.3 mg GAE g⁻¹ dry matter. The TPC results determined in their study were higher than our study. The differences in the results may be explained by differences in the type of extraction solvent, extraction conditions, as well as plant varieties. However, according to Ozkan et al. [62], it could be said that the TPC, DPPH and CUPRAC results obtained in three different safflower varieties show more similarity to the values determined in our study. This similarity could be due to the fact that the safflower varieties used in their study were grown in the same environment (Isparta-Turkey) in 2016 with our study. On the other hand, it had been reported that flowers with high TPC content have high antioxidant activity [60]. Moreover, in our study, the results on the antioxidant activity values measured by the CUPRAC method were higher with respect to the DPPH method. Additionally, the difference between the results of CUPRAC and DPPH can be attributed to the transfer mechanism [63]. Although both CUPRAC and DPPH are assays based on “Mixed transfer” (single electron transfer, hydrogen atom transfer, and chelation mechanisms of transition metals can play a role in relatively variable ratios), the DPPH reaction can be formulated according to the hydrogen atom transfer mechanism [64], while CUPRAC is mainly based on the electron transfer mechanism. This observation might be related to the fact that, while DPPH uses a radical dissolved solely in the organic solvent and therefore applies to hydrophobic systems, the CUPRAC assay may measure both the lipophilic and hydrophilic antioxidant activity of the extracts since the reagent is soluble in both aqueous and organic solvents [65].

3.6. Oil Content

In addition to being grown for safflower seed oil, its flowers also contain relatively high oil and high α- and γ-linolenic acids, indicating that it is extremely beneficial oil for health [66]. In our study, the oil content of safflower genotypes ranged between 4.87–5.36%. The highest average oil content was determined in Leed and Askon-42 genotypes and the lowest in AC Sunset genotype. In 2018, the oil content was found to be higher in flowers. The highest oil content was determined in the Leed (6.12%) and Askon-42 (6.11%) genotypes in 2018. The lowest oil content was determined in the Dinçer 5-18-1, Yenice 5-38, Gelendost, AC Sunset, US-10 and Olein genotypes in 2017 (Figure 2l). The higher precipitation in 2018, especially in June, and the lower temperatures in July, might have extended the flowering period and thus increased the oil synthesis in flowers. It was reported that the oil content of safflower flowers contains 4.8% [67]. In another study, it was reported that the oil content of safflower with yellowish orange flowers was 5.4%, and it was between 4.1-5.8% in three safflower varieties with red flowers [66]. In our study, it was observed that there was no difference in oil content according to the flower color.

3.7. Principal Component Analysis (PCA) of Characters

A principal component analysis of the characters examined in the flowers of safflower genotypes in 2017 (A) and 2018 (B) is shown in Figure 3. According to the PCA of 2017, three PCA axes greater than 1 were obtained. However, the two main components, PC1 and PC2, explained 81.34% of the total variation for 2017 and 82.25% for 2018. The clustering of genotypes in both years is partly closely related to flower color. Three main clusters were identified as yellow-flowered, orange-red-flowered and white-flowered genotypes. In 2017, the dye content, dye yield, a*, C*, total phenolic content and DPPH properties in the PCA1 axis and the b*, h°, total phenolic content and DPPH-CUPRAC properties in the PCA2 axis were more than 3/2 of the total variation. In 2018, the b*, C*, total phenolic content, DPPH and CUPRAC properties on the PCA1 axis and the dyestuff content, dyestuff yield, a* and C* properties on the PCA2 axis were more than 32 of the total variation. Eigenvector values greater than 0.25 are taken into account [68]. According to the PCA results; the Dinçer-5-18-1, Yenice 5-38, Gelendost, Askon-42 and AC-Sunset genotypes for flower yield and dyestuff yield, Remzibey-05 and Leed genotypes for antioxidant activity (DPPH and CUPRAC), total phenolic content and b* value formed one cluster.

3.8. Correlation Analysis of Characters

The relationships and correlations between characters examined in genotypes in 2017 (A) and 2018 (B) are shown in Figure 4. Of the 66 coefficients, 22 were significant in 2017, and 15 were positively and seven were negatively correlated; 21 were significant in 2018, and 13 were positively and eight were negatively correlated with each other. In both years, the flower yield and dyestuff yield were positively correlated (r² = 0.90 in 2017 and r² = 0.89 in 2018). However, there is a negative correlation between the flower yield and the total phenolic content and antioxidant activity (DPPH and CUPRAC) in 2018. The dyestuff content was positively correlated with the C* value and negatively correlated with the L* value in both years. In addition, in 2017, the colorant content was negatively correlated with the h° value (r² = 0.75). The total phenolic content was positively correlated with b* and C* values and antioxidant activity (DPPH and CUPRAC) in both years, with insignificant correlations with the remaining properties. No significant correlation was observed between oil content and other properties in either year (Figure 4). When we look at the correlation data in our study, it is seen that interesting results are obtained. According to the results, it is expected that flower and dyestuff yield and total phenolic content and antioxidant activity show positive and significant relationships. It is reported that safflower flowers with high phenolic content show high antioxidant activity [60,62]. However, what are particularly interesting are the relationships with color values because it is seen that genotypes with high C* values have high phenolic content and show strong antioxidant activity. On the contrary, a high b* value showed the opposite effect. According to reports, there is a correlation between the active substance contents and the intensity of the flower’s color. Flowers with more intense color (vivid red and bright yellow or bright orange) were characterized by higher hydroxysafflor A, anhydrosafflor yellow B, quercetin, safflomin C and kaempferol, 6-hydroxykaempferol-3–0-β-d-glucoside and kaempferol-3-O-rutinoside content compared to less colorful flowers [55,64]. This information can guide us in an important way. In breeding studies, the b* and C* color values of the flowers of the genotypes can give us a preliminary idea in the selection of plants with high phenolic content and antioxidant activity. At the same time, high a* and C* values and low L* and h° values are also indicators of high dyestuff content and may increase the chance of success in pre-selection based on dyestuff content.

3.9. Phenolic Compounds

Phenolic compounds showed significant differences in the flowers of Safflower genotypes. Nine polyphenol compounds were determined in flower extract: gallic acid, chlorogenic acid, syringic, rutine, quercetin, catechin, kaempferol, luteolin, and rosmarinic acid. The phenolic component contents of the genotypes did not differ much according to the years. Gallic acid was the highest component of all genotypes in safflower flowers in both years. The gallic acid content of the genotypes ranged between 63.5–159.3 μg g⁻¹ DW in 2017 and 66.0–165.7 μg g⁻¹ DW in 2018. The highest gallic acid content was determined in the Yenice 5-38 genotype in both years. The most abundant phenolic compound after gallic acid in flowers was rosmarinic acid, and it ranged between 26.1–91.1 μg g⁻¹ DW in genotypes in both years. Rosmarinic acid was highest in the Leed genotype in both years. When classified according to flower color, generally, the gallic and rosmarinic acid contents of orange flowers were higher than the others. In terms of these two compounds, the order according to flower color was as follows; orange > red > yellow > white (

Table 3. The phenolic (HPLC) compounds (μg g⁻¹ DW) in flower of safflower genotypes.

RTa	Phenolic Compound	2017
		1	2	3	4	5	6	7	8	9	10
5.2	Gallic	142.1 ± 3.3	71.3 ± 1.2	159.3 ± 4.6	83.0 ± 1.9	145.2 ± 2.5	89.0 ± 2.6	147.9 ± 3.4	66.2 ± 1.9	63.5 ± 1.5	110.0 ± 1.9
12.0	Catechin	21.4 ± 0.5	14.4 ± 0.2	16.9 ± 0.5	10.1 ± 0.2	13.5 ± 0.2	10.1 ± 0.3	17.4 ± 0.4	18.3 ± 0.5	3.6 ± 0.1	8.9 ± 0.2
14.0	Chlorogenic	19.7 ± 0.5	8.3 ± 0.1	24.7 ± 0.7	19.5 ± 0.4	36.1 ± 0.6	17.3 ± 0.5	29.6 ± 0.7	9.5 ± 0.3	4.3 ± 0.1	19.4 ± 0.3
20.0	Syringic	2.0 ± 0.0	4.2 ± 0.1	2.0 ± 0.1	2.7 ± 0.1	4.7 ± 0.1	3.5 ± 0.1	3.4 ± 0.1	3.6 ± 0.1	-	6.8 ± 0.1
45.0	Rutine	1.4 ± 0.0	3.1 ± 0.1	1.4 ± 0.0	1.1 ± 0.0	2.0 ± 0.0	2.0 ± 0.1	1.3 ± 0.0	4.1 ± 0.1	3.4 ± 0.1	3.9 ± 0.1
57.0	Rosmarinic	78.3 ± 1.8	69.3 ± 0.9	73.7 ± 2.5	54.8 ± 1.7	82.1 ± 1.4	78.0 ± 2.0	85.5 ± 2.1	75.7 ± 1.9	26.9 ± 0.6	45.7 ± 1.4
72.0	Quercetin	19.9 ± 0.5	9.8 ± 0.2	19.9 ± 0.6	16.4 ± 0.4	26.4 ± 0.5	14.2 ± 0.4	18.8 ± 0.4	12.0 ± 0.3	6.7 ± 0.2	14.2 ± 0.2
74.0	Luteolin	1.3 ± 0.0	5.3 ± 0.1	1.3 ± 0.0	2.5 ± 0.1	1.3 ± 0.0	3.4 ± 0.1	1.8 ± 0.0	4.4 ± 0.1	-	3.7 ± 0.1
77.0	Kaempferol	34.5 ± 0.8	33.2 ± 0.6	42.6 ± 1.2	51.6 ± 1.2	41.5 ± 0.7	52.2 ± 1.5	47.3 ± 1.1	29.5 ± 0.9	16.2 ± 0.4	55.8 ± 1.0
RT*	Phenolic Compound	2018
		1	2	3	4	5	6	7	8	9	10
5.2	Gallic	147.8 ± 3.4	74.1 ± 1.3	165.7 ± 4.8	86.3 ± 2.0	151.0 ± 2.6	92.6 ± 2.7	153.9 ± 3.6	68.9 ± 2.0	66.0 ± 1.5	114.4 ± 2.0
12.0	Catechin	19.9 ± 0.5	13.4 ± 0.2	15.7 ± 0.5	9.4 ± 0.2	12.5 ± 0.2	9.4 ± 0.3	16.2 ± 0.4	17.0 ± 0.5	3.4 ± 0.1	8.3 ± 0.1
14.0	Chlorogenic	19.1 ± 0.4	8.0 ± 0.1	23.9 ± 0.7	18.9 ± 0.4	35.1 ± 0.6	16.7 ± 0.5	28.7 ± 0.7	9.2 ± 0.3	4.1 ± 0.1	18.8 ± 0.3
20.0	Syringic	2.2 ± 0.0	4.5 ± 0.1	2.2 ± 0.1	2.9 ± 0.1	5.1 ± 0.1	3.7 ± 0.1	3.7 ± 0.1	3.8 ± 0.1	-	7.3 ± 0.2
45.0	Rutine	1.3 ± 0.0	2.9 ± 0.1	1.3 ± 0.0	1.0 ± 0.0	1.9 ± 0.0	1.9 ± 0.1	1.2 ± 0.0	3.9 ± 0.1	3.2 ± 0.1	3.6 ± 0.1
57.0	Rosmarinic	75.9 ± 1.8	67.2 ± 0.9	71.5 ± 2.4	53.2 ± 1.7	79.6 ± 1.4	75.7 ± 1.9	82.9 ± 2.0	88.3 ± 1.8	26.1 ± 0.6	43.8 ± 1.3
72.0	Quercetin	21.8 ± 0.5	10.8 ± 0.2	21.8 ± 0.6	18.1 ± 0.4	29.0 ± 0.5	15.6 ± 0.5	20.7 ± 0.5	13.2 ± 0.4	7.3 ± 0.2	15.6 ± 0.3
74.0	Luteolin	1.4 ± 0.0	5.9 ± 0.1	1.5 ± 0.0	2.7 ± 0.1	1.5 ± 0.0	3.8 ± 0.1	2.0 ± 0.0	5.0 ± 0.1	-	4.1 ± 0.1
77.0	Kaempferol	36.9 ± 0.9	35.5 ± 0.6	45.5 ± 1.3	55.2 ± 1.3	44.4 ± 0.8	55.9 ± 1.6	50.6 ± 1.2	31.5 ± 0.9	17.3 ± 0.4	59.7 ± 1.0

^a RT: Retention Time, [1 = Dinçer-5-18-1, 2 = Remzibey-05, 3 = Yenice 5-38, 4 = Gelendost, 5 = Askon-42 (Bay-Er 14), 6 = AC-Sunset, 7 = Leed, 8 = US-10, 9 = Arizona Safflower Composite III, 10 = Olein (Bay-Er 13)].

).

Gallic and rosmarinic acid are the most abundant phenolic compounds that form a linear correlation between their content and antioxidant capacity, which indicates that these compounds may be the main compounds responsible for antioxidant capacity [69]. As previously reported, a study of vitamin C equivalent antioxidant capacity (VCEAC) in relation to its molecular structure showed that gallic and rosmarinic acid had the highest antioxidant capacity among all tested phenolic compounds [70]. In this study, kaempferol was another phenolic compound found high in genotypes. The highest kaempferol content in genotypes was higher in genotypes with red flower color in both years and ranged between 51.6–55.8 μg g⁻¹ DW in 2017 and 55.2–59.7 μg g⁻¹ DW in 2018 in these genotypes. For kaempferol content, the order by flower color was red > orange > yellow > white. Catechin was found mostly in safflower genotypes with yellow and orange flowers. Of these genotypes, Dinçer 5-18-1 was the genotype with the highest content (21.4 and 19.9 μg g⁻¹ DW, respectively) in both years (Table 3). Flavonols are the most common type of flavonoids in foods, and their main representatives are kaempferol and quercetin [71]. Rich sources of flavonols include dried parsley, saffron, kale, and onion. These compounds play a key role such as antimutagenic, anticancer, and antihypertensive activities [72]. Kaempferol also reduces the occurrence of brain vascular diseases in humans [73]. Furthermore, kaempferol prevents and mitigates the effects of atherosclerosis by reducing vascular inflammation, thrombus formation, and low-density lipoprotein oxidation [74]. In both years, chlorogenic acid content in safflower genotypes was higher in orange flowers (19.7–36.1 μg g⁻¹ DW in 2017, 19.1–35.1 μg g⁻¹ DW in 2018) in our study. According to these results, safflower flowers can also be evaluated as a source of chlorogenic acid. On the other hand, syringic, rutine and luteolin compounds were detected in low amounts in the genotypes flower. The phenolic contents of the Arizona SC III genotype were the lowest among the genotypes (Table 3). When the DPPH and CUPRAC values of this genotype were also examined, it showed a low antioxidant capacity (Figure 2). Salem et al. [13] reported gallic acid and quercetin in orange flowers, chlorogenic acid in red flowers, syringic acid and rutine in yellow flowers in safflower genotypes with different flower colors at different harvest times. Although the location and genotypes used were different, our results showed similarities to those of Salem et al. [13]. On the other hand, Zheng et al. [24] determined phenolic acid such as p-coumaric at 69.6 μg g⁻¹ DW level and ferulic acid at 9.67 μg g⁻¹ DW level in safflower flowers.

In order to better evaluate the variation in phenolic compounds of different flower colors in our study, a heat map based on the relative density of nine phenolic compounds was analyzed (Figure 5). The heat map showed that some phenolic compounds in flower of safflower genotypes could be better characterized genotypes. For example, the concentrations of phenolic compounds of the genotypes show similarities over the years. It is more clearly seen that the Dinçer-5-18-1, Yenice 5-38, Askon-42 and Leed genotypes have similar concentrations in terms of gallic acid, luteolin and rutine content. However, the heat map and dendogram provided a guide to better reveal the effects on phenolic compounds during the developmental period in the flowers of R. damascena [75].

3.10. Fatty Acid Composition

The composition of fatty acids in flowers of safflower genotypes were presented in

Table 4. The fatty acid (GC-FID) composition in flower of safflower genotypes.

RTa	Fatty Acids	2017										2018
		1	2	3	4	5	6	7	8	9	10	1	2	3	4	5	6	7	8	9	10
18.6	C8:0	-	-	0.16	-	-	-	-	-	1.26	-	-	-	-	0.21	-	-	-	-	-	-
24.3	C10:0	3.21	3.58	3.70	4.11	3.47	3.40	4.07	3.75	3.46	3.39	2.47	2.98	3.46	3.47	3.13	3.07	3.67	3.38	3.81	2.93
26.4	C11:0	-	0.26	0.72	0.43	0.71	-	0.26	0.45	0.59	0.23	0.25	0.29	0.64	-	0.61	-	0.22	0.39	0.65	0.24
30.2	C12:0	1.72	1.59	2.08	1.55	1.54	1.10	1.93	1.51	2.71	2.13	1.13	1.88	1.98	1.42	1.63	1.17	2.05	1.60	2.99	2.05
33.4	C13:0	-	0.19	0.55	-	-	-	1.18	-	-	0.24	-	-	0.44	0.21	-	-	1.13	-	-	0.21
36.1	C14:0	2.93	3.62	4.39	3.95	4.63	3.76	3.48	3.43	5.77	3.21	4.93	4.23	4.21	3.22	4.09	3.32	3.07	3.03	5.10	3.47
38.9	C15:0	0.66	0.43	0.46	0.65	2.99	0.35	0.47	0.29	0.46	0.51	0.79	0.47	0.65	0.41	3.23	0.38	0.51	0.31	0.50	0.53
41.3	C15:1	-	0.94	0.69	0.51	0.75	-	0.52	0.20	0.78	0.42	-	1.01	0.35	0.68	0.78	-	0.54	0.21	0.81	0.40
41.7	C16:0	18.96	14.62	13.37	17.90	18.28	13.56	13.80	13.34	20.37	15.49	19.45	14.55	14.37	16.66	17.20	15.49	12.98	12.55	19.17	17.45
43.1	C16:1	-	0.53	1.09	0.98	0.86	0.43	0.47	1.11	1.97	0.55	-	0.53	0.64	1.00	1.08	0.54	0.59	1.39	2.47	0.61
46.9	C18:0	1.95	4.94	4.41	2.19	3.92	1.82	2.96	3.80	2.87	3.30	2.24	3.49	3.66	3.38	4.32	2.01	3.26	4.19	3.16	2.98
48.2	C18:1 n9c	7.52	5.63	6.33	6.97	6.03	5.08	4.56	4.72	5.01	6.05	6.45	6.64	5.98	5.22	5.44	4.58	4.12	4.26	4.52	5.23
50.1	C18:2 n6c	40.30	38.47	35.24	38.05	33.63	48.27	40.49	43.47	32.77	39.27	42.35	41.25	38.56	41.79	37.08	46.36	44.12	46.26	35.49	41.66
51.3	C18:3 n6	2.85	3.54	2.84	2.32	2.24	2.94	3.18	2.74	3.07	3.24	1.85	2.98	2.77	3.24	2.47	3.24	3.51	3.02	3.38	3.11
52.5	C20:1 c1	0.82	0.99	0.45	0.34	0.20	0.83	0.65	0.12	0.47	0.98	0.42	0.49	0.75	-	0.22	0.92	0.72	0.13	0.52	0.88
53.6	C18:3 n3	16.43	16.54	18.50	17.56	18.16	16.87	18.46	17.39	16.36	17.18	15.29	16.65	17.42	16.84	16.39	15.23	16.66	15.69	14.76	14.86
55.1	C21:0	0.49	0.76	0.38	0.38	-	-	0.89	0.72	-	0.84	0.35	0.69	0.48	-	-	-	0.77	0.62	-	0.89
55.9	C20:2 c11	0.44	0.28	0.53	0.80	0.22	0.51	0.55	-	0.53	0.16	0.52	0.33	0.61	0.93	0.23	0.54	0.58	-	0.56	0.15
57.2	C20:3 n3 c11	0.40	0.23	0.22	0.55	0.37	0.43	0.16	0.10	0.41	0.10	0.19	0.14	0.46	-	0.36	0.41	0.15	0.10	0.39	0.09
59.1	C23:0	0.55	0.83	-	0.22	-	0.18	-	0.18	-	0.09	0.42	0.52	0.04	0.34	-	0.16	-	0.16	-	0.10
59.4	C22:2	-	0.32	2.18	-	-	-	0.28	0.44	-	-	-	-	1.64	0.26	-	-	0.30	0.48	-	-
60.8	C20:5 n3	0.16	-	0.42	-	0.62	-	-	0.35	-	0.91	0.09	0.23	0.14	-	0.65	-	-	0.36	-	0.86
61.8	C24:1	0.61	0.78	0.37	0.26	0.75	0.47	0.50	0.81	0.22	0.66	0.54	0.49	0.09	0.33	0.71	0.44	0.47	0.76	0.21	0.83
61.9	C22:6 n3	-	0.25	-	0.12	-	-	0.41	0.27	-	0.25	-	0.02	0.32	0.27	-	-	0.51	0.34	-	0.28
ΣSFA		30.5	30.8	30.2	31.4	35.5	24.2	29.0	27.5	37.5	29.4	32.0	29.1	29.9	29.3	34.2	25.6	27.7	26.2	35.4	30.9
ΣMUFA		9.0	8.9	8.9	9.1	8.6	6.8	6.7	7.0	8.5	8.7	7.4	9.2	7.8	7.2	8.2	6.5	6.4	6.8	8.5	8.0
ΣPUFA		60.6	59.6	59.9	59.4	55.2	69.0	63.5	64.8	53.1	61.1	60.3	61.6	61.9	63.3	57.2	65.8	25.8	66.3	54.6	61.0
ΣTUFA/ΣSFA		2.0	1.9	2.0	1.9	1.6	2.9	2.2	2.4	1.4	2.1	1.9	2.1	2.1	2.2	1.7	2.6	0.9	2.5	1.5	2.0

^a RT: Retention Time; ΣSFA: Saturated Fatty Acids; ΣMUFA: Monounsaturated Fatty Acids; ΣPUFA: Polyunsaturated Fatty Acids. [1 = Dinçer-5-18-1, 2 = Remzibey-05, 3 = Yenice 5-38, 4 = Gelendost, 5 = Askon-42 (Bay-Er 14), 6 = AC-Sunset, 7 = Leed, 8 = US-10, 9 = Arizona Safflower Composite III, 10 = Olein (Bay-Er 13)]. C_8:0: Caprylic; C_10:0: Capric; C_11:0: Undecanoic; C_12:0: Lauric; C_13:0: Tridecanoic; C_14:0: Myristic; C_15:0: Pentadecanoic; C_15:1: c-10-Pentadecenoic; C_16:0: Palmitic; C_16:1: Palmitoleic; C_18:0: Stearic; C_{18:1 n9c}: Oleic; C_{18:2 n6c}: Linoleic; C_{18:3 n6}: γ-Linolenic; C_{20:1 c1}: Eicosenoic; C_{18:3 n3}: α-Linolenic; C_21:0: Heneicosanoic; C_{20:2 c11}: cis-11,14-Eicosadienoic; C_{20:3 n3 c11}: 11,14,17-Eicosatrienoic; C_23:0: Tricosanoic; C_22:2: cis-13 16-Docosadienoic; C_{20:5 n3}: Eicosapentaenoic; C_24:1: Nervonic; C_{22:6 n3}: Docosahexaenoic.

. A total of 24 fatty acids were determined between the chains of C_8:0-C_24:1 fatty acids, although their numbers varied according to genotypes in flowers. The saturated fatty acid (SFA) content of the genotypes varied between 27.5–37.5% in 2017 and 26.2–35.4% in 2018. A high concentration of SFA composition was C_16:0. The palmitic acid content of Arizona SC III was high in both years and this genotype was followed by Dinçer 5-18-1, Gelendost-1, Askon-42 and Olein genotypes. The lowest palmitic acid content was determined in the US-10 genotype in both years. The stearic acid content in the flowers varied between 1.82% (AC-Sunset in 2017) and 4.94% (Remzibey-05 in 2017). In our study, in addition to C_16:0 and C_18:0 fatty acids, low molecular weight fatty acids such as C_10:0, C_12:0 and C_14:0 were also determined in flowers (Table 4).

Srinivas et al. [66] reported a variation of 3.20–4.72% for C_10:0, 1.68–1.80% for C_12:0 and 2.61–5.20% for C_14:0. However, the C_10:0 concentration of the Dinçer-5-18-1, Remzibey-05, Askon-42 and Olein genotypes was lower compared to the C_10:0 and C_14:0 values of Srinivas et al. [66], and the C_14:0 concentration is higher. In our study, only the C_12:0 values of the Dinçer 5-18-1 genotype in 2017 are consistent with the results of Srinivas et al. [66]. The differences are thought to be due to soil, climate and genotype differences. The monounsaturated fatty acid (MUFA) values in safflower flowers ranged from 6.4–9.2% (Leed-Remzibey-05). The most abundant MUFA was oleic acid. The polyunsaturated fatty acids (PUFA) were the fatty acids most found in flowers. The linoleic acid ranged from 32.77–48.27% in 2017 and 35.49–46.36% in 2018. There did not appear to be a correlation between linoleic acid content and flower color. Arizona SC III had the lowest (mean 34.13%) and AC-Sunset the highest (47.27%) linoleic acid content in both years. Srinivas et al. [66] reported higher linoleic acid content than our results. These differences are thought to be due to genotype differences. A high heritability had been reported for linoleic acid content (0.99) in safflower [76,77]. While the oleic acid contents of flowers were higher in 2017 compared to 2018, the linoleic acid contents were found to be lower. Temperatures occurring during oil synthesis can especially effect oleic and linoleic acid synthesis. It had been reported that high temperatures experienced during the seed development period in safflower increase oleic acid synthesis, while low temperatures increase linoleic acid synthesis [78]. In our study, it is thought that the average temperature was higher at the time of flowering in 2017, and therefore, the oleic acid content was high and the linoleic acid content was low.

Significant amounts of α- and γ-linolenic acids were detected in safflower genotypes. The γ-linolenic acid content of the genotypes varied between 1.85% and 3.38% in both years. Leed, Arizona SC III and Olein genotypes showed γ-linolenic acid values over 3% in both years. However, other genotypes such as Askon-42 in 2017 showed the lowest γ-linolenic acid content, while Dinçer 5-18-1 had the lowest content in 2018. On the other hand, the α-linolenic acid content was found to be between 16.43–18.50% in 2017 (Dinçer 5-18-1—Yenice 5-38) and 14.76–17.42% in 2018 (Arizona SC III—Yenice 5-38) (Table 4). Our results are similar to those of Srinivas et al. [66] However, higher α- and γ-linolenic acids were determined in some genotypes than the variation indicated in this research. We can say that this is due to climate, soil and genotype differences. Evening primrose (Oenothera biennis) oil (EPO), blackcurrant seed oil, borage seed oil, and hemp seed oil are all sources of γ-linolenic acid [79]. γ-Linolenic acid was also found in varying amounts in edible hemp seeds, oats, barley and spirulina [80]. Safflower flowers are also an important source of α- and γ-linolenic acids. α- and γ-Linolenic acid are also required for normal nerve cell membranes and blood flow. Omega-3 fatty acids have been shown to have neuroprotective benefits against experimental diabetic neuropathy, as well as to lower neuropathic pain, proinflammatory cytokine production, and other metabolites, as well as to improve macrovascular and microvascular functioning in diabetics [81]. It is also useful in the treatment of skin infections such as atopic eczema, so it has been reported that the medicinal value attributed to the petals may be due in part to the presence of this fatty acid in combination with medium chain fatty acids (C_10:0 and C_12:0) [82]. On the other hand, C_10:0 and C_12:0 medium chain fatty acids contribute little to plasma or adipose tissue lipids, are rapidly oxidized in the liver, and have antimicrobial properties [82]. As a result, the Leed and Arizona Safflower Composite III genotypes seem to be richer in fatty acids with the therapeutic effect mentioned above.

The heat map showed that fatty acids in flowers of safflower genotypes could be better characterized genotypes (Figure 6). The heat intensity of the fatty acid content of the genotypes seems stable over the years. However, the Gelendost genotype differed according to years. It is seen that the Gelendost genotype is closely related to the Yenice 5-18 genotype in 2017 and the AC-Sunset genotype in 2018. Although this seems to be a difference, in fact, the main fatty acids of all genotypes seem to be proportionally close to each other in profile.

3.11. Floral Scent Compositions

The floral scent compositions (HS-SPME GC-MS) of flowers of genotypes were presented in

Table 5. The scent (HS-SPME GC-MS) analysis in flower of safflower genotypes (2018).

LRI a	Compound	Formula	Class	1	2	3	4	5	6	7	8	9	10
902	Hept-2(E)-enal	C7H12O	AA	0.45	0.30	0.26	0.12	1.02	0.49	0.49	0.26	0.12	0.98
936.1	α-pinene	C10H16	MH	14.95	4.65	13.74	15.23	9.95	14.36	16.59	6.84	22.05	17.65
964	Benzaldehyde	C7H6O	AA	0.84	-	0.74	0.49	1.56	0.14	0.74	-	-	0.35
973	(+)-Sabinene	C10H16	MH	0.66	-	0.59	-	0.78	-	0.46	0.12	-	-
977.1	β-Pinene	C10H16	MH	2.50	1.00	1.86	1.14	2.96	2.59	2.79	1.12	3.12	3.17
978.2	Sulcatone	C8H14O	AK	-	0.28	0.04	-	-	-	-	0.14	-	-
989.2	β-Myrcene	C10H16	MH	6.09	3.51	4.52	2.25	6.64	1.98	5.91	4.35	6.37	2.71
1030	dl-Limonene	C10H16	MH	2.15	1.36	1.12	0.49	1.74	0.14	1.98	1.45	1.15	0.79
1041	Phenylacetaldehyde	C8H8O	AA	1.38	0.67	0.96	0.77	2.25	1.78	0.97	0.78	1.03	0.14
1046	β-Ocimene	C10H16	MH	0.58	-	0.41	-	2.05	1.14	1.02	-	-	0.99
1059.7	γ-Terpinene	C10H16	MH	0.98	-	1.18	1.32	2.24	0.74	0.74	0.14	0.92	0.33
1103.3	n-nonanal	C9H18O	AA	0.46	0.36	0.39	0.26	-	0.88	1.00	-	0.12	0.33
1148	methyl-Caprylate	C9H18O2	OC	0.45	0.43	0.14	-	-	0.88	0.33	-	-	0.12
1179	Verbenone	C10H14O	OC	0.75	0.37	1.04	1.19	0.12	-	0.42	0.62	0.24	-
1205.4	n-Decanal	C10H20O	AA	0.42	0.35	0.54	0.77	0.89	0.49	0.59	0.40	0.09	0.44
1408.6	α-Gurjunene	C15H24	SH	2.72	-	2.86	2.28	1.16	-	1.14	0.15	0.49	2.14
1412.2	α-Cedrene	C15H24	SH	-	6.91	4.21	4.75	2.21	3.49	0.78	4.36	2.76	-
1412.2	β-Cedrene	C15H24	SH	8.12	19.29	9.58	14.35	11.12	16.49	6.36	16.47	13.13	14.26
1419	β-Caryophyllene	C15H24	SH	23.40	34.75	26.79	31.42	21.59	33.00	24.21	33.49	27.85	29.47
1425.6	β-Ionone (E)	C13H20O	AK	-	0.34	0.47	-	0.26	-	-	0.14	-	-
1445.9	β-Farnesene	C15H24	SH	-	1.04	0.98	1.19	0.96	-	0.49	1.06	0.89	1.79
1453.1	α-Humulene	C15H24	SH	1.02	1.01	1.25	0.47	-	1.16	0.68	2.12	1.12	1.19
1457.2	β-Patchoulene	C15H24	SH	3.34	2.58	2.34	0.49	4.41	1.55	4.33	3.14	1.96	-
1486.1	β-Selinene	C15H24	SH	-	1.31	1.26	3.01	1.05	2.31	0.49	1.12	0.75	2.78
1493.4	α-Selinene	C15H24	SH	0.43	0.44	-	-	-	-	-	0.35	-	-
1572	1-Tetradecene	C14H28	ALH	12.43	11.24	11.22	9.99	14.25	7.89	11.29	13.45	10.84	12.28
1590.8	Viridiflorol	C15H26O	SA	0.79	0.99	1.26	1.17	-	-	0.36	1.00	0.63	1.16
1630	α-Acorenol	C15H26O	SA	1.86	1.78	1.21	-	0.85	0.99	1.24	1.56	1.14	0.94
1688	Eudesma-4(14),11-diene	C15H24	SH	1.42	-	0.47	1.14	1.03	-	2.00	0.83	0.41	1.49
1692	α-Santalol	C15H24O	SAL	1.12	1.07	-	-	0.33	0.44	1.86	1.23	1.01	0.51
1708.2	Germacrene B	C15H24	SH	1.12	1.26	1.04	1.99	0.96	2.29	2.01	1.12	0.42	2.33
1753.5	α-Sinensal	C15H22O	SALD	0.45	0.39	0.97	0.67	-	0.12	0.09	0.41	0.12	-
1760	Linolenyl alcohol	C18H32O	SAL	0.93	-	1.14	0.22	1.26	-	1.79	-	-	0.37
1800	1-Tetralol	C20H22O	AH	6.90	0.89	3.78	1.48	4.57	3.02	4.59	-	-	1.03
1986.2	Caryophyllene oxide	C15H24O	OS	1.26	1.41	0.99	0.77	1.56	1.65	1.74	1.78	0.84	-
TOTAL (%)				99.9	99.9	99.3	99.4	99.8	100.0	99.5	100.0	99.6	99.7
				1	2	3	4	5	6	7	8	9	10
AA: Aromatic aldehyde:				3.55	1.68	2.89	2.41	5.72	3.78	3.79	1.44	1.36	2.24
MH: Monoterpene hydrocarbone:				27.91	10.52	23.42	20.43	26.36	20.95	29.49	14.02	33.61	25.64
AK: Aromatic ketone:				-	0.62	0.51	-	0.26	-	-	0.28	-	-
OC: Organic compound:				1.20	0.80	1.18	1.19	0.12	0.88	0.75	0.62	0.24	0.12
SH: Sesquiterpene hydrocarbone:				40.15	68.59	50.31	59.95	43.46	60.29	40.49	63.38	49.37	53.96
ALH: Aliphatic hydrocarbone:				12.43	11.24	11.22	9.99	14.25	7.89	11.29	13.45	10.84	12.28
SA: Sesquiterpene alkene:				2.65	2.77	2.47	1.17	0.85	0.99	1.60	2.56	1.77	2.10
SAL: Sesquiterpene alcohol:				2.05	1.07	1.14	0.22	1.59	0.44	3.65	1.23	1.01	0.88
SALD: Sesquiterpene aldehyde:				0.45	0.39	0.97	0.67	-	0.12	0.09	0.41	0.12	-
AH: Aromatic hydrocarbone:				6.90	0.89	3.78	1.48	4.57	3.02	4.59	-	-	1.03
OS: Oxygenated sesquiterpene:				1.26	1.41	0.99	0.77	1.56	1.75	1.74	1.78	0.84	-

^a LRI: Linear Retention Indices, as determined on a Restek Rxi^®-5Sil MS column using a series of the standards of C₇-C₃₀ saturated n-alkanes, -: not detected. [1 = Dinçer-5-18-1, 2 = Remzibey-05, 3 = Yenice 5-38, 4 = Gelendost, 5 = Askon-42 (Bay-Er 14), 6 = AC-Sunset, 7 = Leed, 8 = US-10, 9 = Arizona Safflower Composite III, 10 = Olein (Bay-Er 13)].

. While there were studies on essential oil compositions of safflower flowers, our study is probably the first report on floral scent composition. The floral scent compositions differed significantly according to the genotypes. According to the HS-SPME GC-MS analysis in flowers, a total of 16–24 scent molecules were determined in genotypes. Sesquiterpene hydrocarbon (40.49–68.59%), monoterpene hydrocarbon (10.52–33.61%) and aliphatic hydrocarbon (7.89–14.25%) group compositions were detected in the flowers. The sesquiterpene hydrocarbon group was higher in yellow-flowered genotypes according to flower colors, followed by red-, white- and orange-flowered genotypes, respectively. The monoterpene hydrocarbon group was determined mostly in the Arizona SC III genotype with white flowers. It showed a high value in orange-flowered genotypes for this component group. When the scent molecules were examined; β-caryophyllene, α-pinene, 1-tetradecene, β-cedrene, α-cedrene and β-myrcene in safflower flowers were the most dominant molecules. However, the content of these molecules differed according to the genotypes. β-caryophyllene was the compound with the highest content, and the content of this compound among genotypes varied between 23.40–34.75% (Dinçer 5-18-1—Remzibey-05). Interestingly, β-caryophyllene was found to be higher in yellow and red flowered safflowers. β-Caryophyllene shows important activities in terms of health. Studies have shown that β-caryophyllene shows anticarcinogenic activity [83], blocks calcium channels in cardiovascular cell membranes, and also strongly inhibits potassium ion fluxes when converted to β-caryophyllene oxide form [84]. In this study, α-pinene content in flowers ranged between 4.65–22.05%. This scent molecule was detected the most in the white-flowered Arizona SC III genotype and the lowest in the yellow-flowered genotypes. Safflower flowers also appear to be a source of α- and β-cedrene. Although α-cedrene was not detected in Dinçer 5-18-1 and Olein genotypes, it was detected in 6.91% in Remzibey-05 and 4.75% in Gelendost. On the other hand, the highest β-cedrene was detected in the yellow-flowered safflower genotypes (19.29% in Remzibey-05 and 16.47% in US-10). In orange-flowered genotypes, β-cedrene was determined at a lower concentration (between 6.36–11.12%). 1-Tetradecene was another dominant component in flowers and it ranged between 7.89–14.25% (AC Sunset—Askon-42) in genotypes. The minor scent molecules of genotypes were β-pinene (1.00–3.17%), dl-limonene (0.14–2.15%), phenylacetaldehyde (0.14–2.25%), α-gurjunene (1.14–2.86%), α-humulene (0.47–2.12%), and β-patchoulene (0.00–4.41%) (Table 5).

Studies on scent molecules in safflower flowers were carried out by obtaining essential oil. In these studies, 20 [85] and 29 [86] fragrance molecules were determined in flowers. According to Turgumbayeva et al. [85] heptacosan (34.75%), nonanoic acid (17.90%), dec-2-en-1-ol (14.30%) and undecanoic acid (7.79%) were dominant compounds in the essential oil found in 1.6% of yellow safflower flowers. Ziarati et al. [86] reported 1.2% essential oil in yellow safflower flowers and 1-hydroxy-3-propyl-5-(4-methyl-pentene)-2-methylbenzene (25.2%), 2.5,5 trimethyl 3-n propyl, tetrahydro1-naphthol (19.8%), benzaldehyde (8%), caryophyllene oxide (5.6%) and β-caryophyllene (2.8%) were the dominant compounds. On the other hand, daily changes in essential oil composition of flowers of different genotypes of C. tinctorius L. grown in Sichuan Province of China were analyzed [87]. Among the total 48 compounds, caryophyllene, p-allyltoluene, 1-acetoxytetralin and heneicosane were the main components with percent content relative to total essential oil between 51.66% and 76.69%. The results we obtained in our study were different in the results of these two researchers. As the differences in the chemical composition of the scent of the current study and previous studies can be due to geographical and climatic factors, genotype, drying conditions and distillation method.

In our study, a heat map analysis based on the relative density of the components between the genotypes was performed for a total of 35 floral scent molecules (Figure 7). The heat map showed that the scent molecules in flowers of safflower genotypes could be better characterized genotypes. The AC-Sunset and Olein, Yenice 5-38 and Gelendost, Remzibey-05 and US-10, Dinçer-5-18-1 and Leed genotypes showed close relationships with each other according to the relative density in the heat map. When the genotypes were compared with each other according to heat density, it was more clearly seen that the β-caryophyllene concentrations of the Remzibey-05 and US-10 genotypes, α- and β-cedrene of the Remzibey-05 genotype, benzaldehyde, phenylacetaldehyde, γ-terpinene of the Askon-42 genotype, and β-Farnesene of the Olein genotype were higher (Figure 7).

4. Conclusions

Today, safflower flowers are used especially as food, food coloring, beverage and cosmetic additives or in the field of health. There are four main color flowers in safflower from white to red. If the color changes in flowers after fertilization are taken into account, this color variation increases to seven. This research represented the investigation of the variation of agronomic and chemical contents in different flower colors in safflower. According to the data of two years, the Yenice 5-38, Askon-42 and Gelendost genotypes can economically produce flower and dyestuff yields. Genotypes with yellow flowers showed high antioxidant activity that can be recommended as a source of TPC. However, as a source of high gallic and rosmarinic acid, orange flowers were generally higher than others. The Leed and Yenice 5-38 genotypes were prominent in terms of α- and γ-linolenic acids. On the other hand, β-caryophyllene was especially higher in yellow and red flowered genotypes. The white-flowered genotype had a low potential for almost all traits. As a result, there are genotypes that have the potential to be used in food, health and cosmetics according to flower colors, agricultural characteristics and chemical contents. The variety candidate Askon-42 can be recommended for high flower yield, dyestuff content and yield among genotypes, and the US-10 genotype for total phenolic content and antioxidant activity. Our results will help breeders make selections according to the flower yield and chemical content of the flower in safflower breeding. For further research, it will guide the use of different colored safflower flower extracts, which are natural dye sources, in natural cosmetic products.