Solanum pseudocapsicum vs Capsicum annum; comparative phenolics profiling using green ultrasonic extraction and UHPLC analysis

Graphical abstract

Highlights

• •Fast, ecofriendly, and economical USUHPLC phenolics extraction and analysis.
• •Comparative evaluation of the fruit parts and colors.
• •More extract yields observed for the red and skin parts of the fruit.
• •PC- and CA-fruits green seeds exhibited more phenolic yield compared to the skin part.
• •Phenolics content was high in the green and seeds parts of the fruit, PC in particular.

Abstract

Background

Solanum pseudocapsicum (PC) and Capsicum annum (CA) belongs to the family of Solanaceae. CA have been reported a rich source of phenolics whereas, the phenolics content of GA (gallic acid), SC (scopoletin), RA (rosmarinic acid), and RV (resveratrol) are yet to be reported for the PC-fruit. This study comparatively evaluates the phenolics profile for different parts (seeds and skin) and colors (green and red) of the PC- and CA-fruits using the green solvents of ethanol (ET), acetone (AC), water (H₂O), and different combinations of these solvents.

Methodology

Ultrasonics extraction (US) and UHPLC analysis were employed for phenolics evaluation.

Results

The USMD (method development) revealed the highest extract yield of 62 mg/100 mg for the PC-skin in ET:AC (70:30) solvent whereas, more phenolics (ppm) were observed for PC-seeds in ET:AC (50:50) solvent, particularly the SC (29.46) and GA (16.92). The UHPLCMDMV exhibited significant accuracies (100.70–114.14 %) with r²-values (0.9993–0.9997) in the linearity range of 1–200 ppm. The USMV (method validation) in PC- and CA-fruit parts and colors revealed more extract yields for the red skin part of the PC- (180.5 mg) and CA-fruit (126.2 mg). The phenolics were seen more in the green seeds of the PC-fruit (ppm); SC (276), GA (147.36), RV (28.54), and RA (23.87) followed by the green PC-skin, and red/green CA-seeds. The statistical models of mean differences, ANOVA, and Pearson’s correlation showed significant differences for the PC-fruit parts (seeds and skin) and colors (red and green) vs extract yield and phenolics content (P = 0.05).

Conclusion

PC-and CA-fruits were successfully evaluated where the seeds for the green fruits exhibited more phenolics amount.

1. Introduction

Phenolic compounds, the pivotal secondary metabolites in plants have garnered significant attention for their role as essential contributors to the diverse array of bioactive compounds. This diverse group encompasses phenolic acids, stilbenes, lignans, tannins, and flavonoids, offering promising sources of bioactive compounds with applications against conditions such as cancer, diabetes, and inflammation. [1] In food science, the species of Solanaceae family such as Solanum pseudo-capsicum (PC) and Capsicum annum (CA) are gaining wide attention due to the presence of essential phytochemicals along with the potential health-promoting compounds including; vitamins, minerals, flavonoids, carotenoids, and capsaicinoids. [2] Peppers, represented by CA are particularly captivating subjects for investigation, given their rich phytochemical composition and widespread culinary use. [2], [3] Comparatively, CA-fruit has been extensively studied and explored for the phytochemical profile along with the potential pharmacological potential whereas, PC-fruit (synonyms; wild pepper, Jingili Mirch, and Jerusalem cherry) remains unexplored. The CA-fruit has been reported to contain alkaloids, volatile components [4], [5], and capsaicinoids whereas, PC-fruit lack the presence of capsaicinoids in any of its part. On contrary, PC is known to contain solanine in abundance. [6], [7], [8] Being the members form the same family with common characteristics of colorful fruit production for ornamental use, a thorough phytochemical investigation for the phenolics content is missing in PC. Herein, a comparative phenolics profiling for PC- and CA-fruit is aimed in order to gain in-depth insights for the similarities between the two fruits hence, the applications in same pharmacological models. Moreover, understanding the chemical diversity for these fruits may be a source of potential applications in the field of food science, medicine, agriculture, and nutrition. This study does not determine the nature of phenolics merely, but to explore the nature and amount of different phenolics in the whole fruit (skin and seeds) of green and red color PC-fruit as well as to compare it with CA-fruit using green extraction and analysis.

For green extraction, high frequency ultrasonics concept is utilized whereas, for green analysis the UHPLC-DAD (ultra-high pressure liquid chromatography with diode array detector) is applied. The selection of an appropriate extraction method is crucial in capturing the entire spectrum of the phenolic compounds in a matrix whereby the safety and applicability for the environment and human being is ensures. Hence, green extraction phenomenon was employed where the use of green, eco-, and huma-friendly, biodegradable, and renewable sources solvents of acetone, ethanol, and water will be used. Additionally, for phenolics quantification, green solvents of ethanol and water will be used to develop a green, fast, reliable, and reproducible analytical method for simultaneous determination of phenolics. The method proposed in this study are in-line with the paradigm of growing emphasis on eco-friendly practices in food and health science research. [9] By exploring the differences in the phenolics profile for these two fruits, our objective is to unravel the chemical basis underlying their composition and its potential implications for the food industry. Through this research, we aim to contribute an economical and ecofriendly research data to the expanding knowledge of the chemical diversity of plant species, fostering a deeper understanding of their applications in the development of functional foods and innovative food products. Furthermore, our commitment to sustainable practices in scientific research aligns with the global efforts towards environmentally conscious methodologies of green chemistry. [9], [10].

2. Methodology

2.1. Consumables and equipment’s

Standard chemicals (GA; gallic acid, SC; scopoletin, RA; rosmarinic acid, RV; resveratrol) and HPLC-grade solvents (Ethanol; ET, Acetone; AC) were purchased from Sigma Aldrich St Louis, MO, U.S.A. and Merck Darmstadt, Germany, respectively. For extraction; high-frequency waves (37 and 80 kHz) ultrasonics equipment (Elma Hans Schmid Bauer GMBH, Singen, Germany) was used. A binary pump and diode array detector (DAD) attached UHPLC (Thermo Scientific™ Vanquish™; Thermo Scientific, Germany) for phenolics quantification. Bauchi rotavapor (Bauchi, R-100, Switzerland) was used for drying of the samples.

2.2. Development of the extraction (USMD) and analysis (UHPLCMD) methods for phenolics

2.2.1. Development of US method for phenolics extraction (USMD)

The in-house and previously reported optimized ultrasonics-assisted extraction conditions[11], [12], were employed to extract phenolics form the sample using high frequency ultrasonic waves (20 kHz) at 40 %amplituude and 40:10 s pulse rate for a time period of five minutes. The method development (MD) consisted of three green solvents (100 %) of ET, AC, H₂O, and its mixtures at different ratio (30:70, 50:50, and 70:30). Two parts of the pseudocapsicum (PC) fruit (skin and seed) were used (100 mg) for USMD using 10 mL of the green solvents. A total of 18 PC-samples (9 for seeds and 9 for the skin part of the PC-fruit) were prepared using the green solvents; ET (100 %), AC (100 %), H₂O (100 %), ET and H₂O (30:70, 50:50, and 70:50) and, ET and AC (30:70, 50:50, and 70:30). The extracts were dried using Genevac, %yield calculated, and analyzed with UHPLC for the presence and quantification of phenolics.

2.2.2. Development of phenolics analysis method (UHPLCMD)

The USMD extracted samples were subjected to UHPLC-analysis for a simultaneous determination of the phenolics. Individual stock solutions (1 mg/mL) were prepared for the standard drugs (GA, SC, RA, and RV) in ET followed by the preparation of mix-standard dilutions in the linearity range of 1–200 ppm (1, 5, 10, 50, 100, and 200 ppm). All the solutions were filtered (0.2 μm syringe filter). For the chromatography development: Water XTerra RP-column (4.6X100mm; 3.5 μm), mobile phase consisting of H₂O(A) and ET(B) with gradient and isocratic elution, formic acid at various strengths (0.1, 0.5, and 1 %), column temperature at 30–40 °C, flow rate 0.5–1.8 mL/min, injection volume of 1–5 μL, and UV/Vis detector with a 3D-field (190–600 nm) along with specific wavelengths of 249, 260, 320, and 360 nm were tested during UHPLCMD.

2.3. Validation of the phenolics extraction (USMV) and analysis (UHPLCMV) methods

2.3.1. Validation of extraction method for phenolics (USMV)

The optimized phenolics extraction conditions were validated in two samples; Solanum pseudocapsicum (PC) and Capsicum anuum (CA). Two parts (skin and seed) with two different colors (red and green) for both the samples were extracted which makes a total of 8-samples; red skin and seeds (PC1, PC2) and, green skin and seeds (PC3, PC4) for PC along with red skin and seeds (CA1, CA2) and, green skin and seeds (CA3, CA4) for CA. For each sample, 2700 mg was weighed and extracted with 100 mL of the ET:AC (50:50) solvent. The extracts were centrifuged, the supernatant removed, filtered (0.4 μm filter paper), dried with the help of Genevac, redissolved in ET, filtered (0.2 μm syringe filter), and diluted for UHPLC-analysis with a final concentration of 2 mg/mL.

2.3.2. Validation of phenolics analysis method (UHPLCMV)

The UHPLCMD was validated in terms of specificity, linearity, accuracy, LOD, LOQ, and peak resolution (Rs). For specificity, blank samples were run using the UHPLCMD chromatographic conditions. No peak was detected at the retention times of the phenolics showing the specificity of the method. Linearity of the method was evaluated using 6-calibration points (1–200 ppm) and regression analysis where r²-values > 0.9990 reflected a good linearity for the developed method. Accuracy of the method was determined from the recovered concentrations/initial concentrations of the phenolics with the help of formula (recovered concentration/initial concentration)/100. The signal to noise ratio (S/N) of 3 for LOD and 10 for LOQ were used to find the concentrations limits. The formula used for LOD and LOQ were; 3.3*(SD intercept/slope) and 10*(SD intercept/slope), respectively. The UHPLC software (Chromeleon; V 7.2.2.6890) was used to acquire the data for Rs and %RSD of the phenolics based on the selected wavelength of 260 nm for CC and quantification of the phenolics.

3. Results

3.1. Extracts yield for USMD

3.1.1. General yield (extracts and phenolics) for PC samples

The total extract yield (sum) for the PC-samples (N = 18) was 159.4 mg/1.8 g with a mean (±SD) of 8.85(±14.20) mg. The lowest individual extract yield observed for these samples was 0.2 mg/100 mg whereas, the highest extract yield was seen to be 62 mg/100 mg. The sample with the highest extract yield (62 mg/100 mg) among the PC-samples (N = 18) was observed for ET:AC (70:30) solvent. The data for all the PC-samples with the extract yields, parts, and solvents used for extraction are shown in Table 1.

Table 1.

US-UHPLC-MD for RPC (red pseudo capsicum) seed and skin in different solvents.

S#	Part used	Solvent	Solvent volume	Sample amount	Extract yield (mg)	% Yield	GA (ppm)	SC (ppm)	RA (ppm)	US-conditions
PC1	Seed	AC	10 mL	100 mg	7.01	7.01	3.21	17.05	0.00	Pulse: (40:10 s), Amplitude: (40 %), Time: (5 min)
PC2		ET			3.3	3.3	5.59	16.30	0.00
PC3		H20			5.5	5.5	5.61	11.73	0.00
PC4	Skin	AC			10.9	10.9	16.44	3.02	3.71
PC5		ET			14.1	14.1	16.92	20.11	0.00
PC6		H20			9.6	9.6	5.53	7.74	0.00
PC7	Seed	ET:H20 (30:70)			0.5	0.5	4.88	10.79	0.00
PC8		ET:H20 (50:50)			0.2	0.2	8.23	12.76	0.00
PC9		ET:H20 (70:30)			1	1	5.91	12.50	0.00
PC10	Skin	ET:AC (30:70)			19.5	19.5	2.79	0.00	2.89
PC11		ET:AC (50:50)			6.8	6.8	12.56	24.71	3.73
PC12		ET:AC (70:30)			62	62	2.07	0.92	1.07
PC13	Seed	ET:AC (30:70)			1.5	1.5	5.39	15.69	0.00
PC14		ET:AC (50:50)			2.4	2.4	10.30	29.46	0.00
PC15		ET:AC (70:30)			2.1	2.1	7.09	20.55	0.00
PC16	Skin	ET:H20 (30:70)			3.9	3.9	0.79	0.00	0.00
PC17		ET:H20 (50:50)			5.1	5.1	7.17	15.91	0.00
PC18		ET:H20 (70:30)			4	4	2.66	0.00	0.00

Descriptive statistics
	Extract yield	GA	SC	RA
Mean	8.85	6.84	12.18	0.63
Std. Deviation	14.20	4.59	8.85	1.32
Minimum	0.2	0.8	0.0	0.0
Maximum	62	16.9	29.5	3.7
Sum	159.4	123.1	219.2	11.4

3.1.2. Yields for PC fruit-parts

The extract yield for the PC-fruit parts revealed the sum with a mean (±SD) of 135.90 mg/900 mg and 15.10(±18.32) for the skin (N = 9) and, 23.51 mg/900 mg and 2.61(±2.31) for the seeds part (N = 9). The highest individual yield (62.0 mg/100 mg) was observed for the skin part of the PC-fruit. The extracts yield for the fruit parts showed the order of; skin extract yield > seed extract yield. The extracts yield for the PC-fruit parts is shown in Table 2.

Table 2.

Individual with total yield for extract and phenolics amount/solvent in seed and skin parts of the PC-fruit.

Part	Solvent	Extract yield (mg)	Yield/ solvent (mg/200 mg)	GA (ppm)	SC (ppm)	RA (ppm)	Sum	Mean (±SD)	Phenolics/ solvent (ppm)
Seed	AC	7.01	AC (17.91)	3.21	17.05	0.00	20.26	10.13 (±9.06)	AC (43.44)
	ET	3.30		5.59	16.30	0.00	21.89	10.94 (±8.28)
	H20	5.50	ET (17.40)	5.61	11.73	0.00	17.34	8.67 (±5.87)	ET (58.92)
	ET:H20 (30:70)	0.50		4.88	10.79	0.00	15.67	7.83 (±5.40)
	ET:H20 (50:50)	0.20	H20 (15.10)	8.23	12.76	0.00	20.99	10.50 (±6.47)	H20 (30.61)
	ET:H20 (70:30)	1.00		5.91	12.50	0.00	18.42	9.21 (±6.25)
	ET:AC (30:70)	1.50	ET:H20 (30:70) (4.40)	5.39	15.69	0.00	21.09	10.54 (±7.97)	ET:H20 (30:70) (16.45)
	ET:AC (50:50)	2.40		10.30	29.46	0.00	39.76	19.88 (±14.95)
	ET:AC (70:30)	2.10		7.09	20.55	0.00	27.64	13.82 (±10.44)
	Sum	23.51	ET:H20 (50:50) (5.30)	56.22	146.83	0.00	Total yield for seed phenolics = 188.0 ppm		ET:H20 (50:50) (44.06)
	Mean	2.61		6.25	16.31	0.00
	SD	2.31		2.06	5.81	0.00
Skin	AC	10.90	ET:H20 (70:30) (5.0)	16.44	3.02	3.71	23.18	7.73 (±7.56)	ET:H20 (70:30) (21.08)
	ET	14.10		16.92	20.11	0.00	37.03	18.52 (±10.81)
	H20	9.60		5.53	7.74	0.00	13.27	6.63 (±3.99)
	ET:AC (30:70)	19.50	ET:AC (30:70) (21.0)	2.79	0.00	2.89	5.68	2.84 (±1.64)	ET:AC (30:70) (26.77)
	ET:AC (50:50)	6.80		12.56	24.71	3.73	41.00	13.67 (±10.53)
	ET:AC (70:30)	62.00		2.07	0.92	1.07	4.07	1.36 (±0.62)
	ET:H20 (30:70)	3.90	ET:AC (50:50) (9.20)	0.79	0.00	0.00	0.79	0.79 (±0.45)	ET:AC (50:50) (80.76)
	ET:H20 (50:50)	5.10		7.17	15.91	0.00	23.07	11.54 (±7.97)
	ET:H20 (70:30)	4.00		2.66	0.00	0.00	2.66	2.66 (±1.53)
	Sum	135.90	ET:AC (70:30) (64.10)	66.93	72.41	11.41	Total yield for skin phenolics = 165.7 ppm		ET:AC (70:30) (31.71)
	Mean	15.10		7.44	12.07	2.85
	SD	18.32		6.31	9.72	1.69

3.1.3. Yields for green solvents

The absolute (100 %) solvents exhibited the yields (mg/200 mg; N = 2) of 17.91 (AC), 17.40 (ET), and 15.10 (H₂0) with a descending order of; AC > ET > H₂0. The extracts yield (mg/200 mg; N = 2) for the solvent’s mixture were; 4.40 for ET:H20 (30:70), 5.30 for ET:H₂0 (50:50), 5.0 for ET:H₂0 (70:30), 21.0 for ET:AC (30:70), 9.20 for ET:AC (50:50), and 64.10 for ET:AC (70:30). The highest individual yield (64.10 mg/200 mg) was observed for the ET:AC (70:30) solvent with a descending order for the extracts yield; ET:AC (70:30) > ET:AC (30:70) > ET:AC (50:50) > ET:H₂0 (50:50) > ET:H₂0 (70:30) > ET:H₂0 (30:70). The data for the extracts yield in different solvents is given in Table 2.

3.2. Analytical method development and validation for phenolics quantification

The UHPLCMDMV resulted a simultaneous separation for the phenolics (GA, SC, RA, RV) within the runtime of 3 min, using the optimized chromatographic conditions of; mobile phase consisting of H₂0 (A; 65 %) with 0.5 %FA and ET (B; 35 %), FR of 1.8 mL, IV (1 μL), and column oven temperature at 40 °C. The UHPLMD was validated in the linearity range of 1–200 ppm where the Rt (min) observed were; 0.683(GA), 0.987(SC), 1.263(RA), and 2.187(RV). The method showed accuracies in the range of 100.70–114.14 %, with Rs > 1.5, and r²-values in the range of 0.9993–0.9997. The details regarding the chromatographic conditions and validation results consisting of regression equations, SE and SD of the intercept, LODs, LOQs, r²-values, and peak resolutions are provided in Table 3. A representative chromatogram at 249 nm and 260 nm showing the peak separations for the phenolics is shown in Fig. 1.

Table 3.

UHPLCMDMV data for simultaneous determination of the phenolics quantified in PC-fruit samples.

Parameters	GA	SC	RA	RV
Retention time (min)	0.683	0.987	1.263	2.187
Resolution	4.59	2.79	5.81	–
λ-max (nm)	249 and 260
Accuracy (%SD)	105.25(±25.8)	100.70(±7.10)	110.75(±17.07)	114.14(±27.64)
SE of intercept	0.018	0.006	0.013	0.007
SD of intercept	0.04	0.01	0.03	0.02
Rel. SD (%)	2.88	2.25	5.14	3.68
Linearity (ppm)	1–200
r2	0.9996	0.9997	0.9986	0.9993
LOD (ppm)	3.72	5.89	13.08	9.39
LOQ (ppm)	23.24	17.85	39.65	28.47
Regression equation	y = 0.0189x + 0.0394	y = 0.0082x + 0.0211	y = 0.0079x-0.0012	y = 0.0062x + 0.005
Chromatographic conditions
t-0.5min = column equilibration; t0min → t3min (isocratic gradient) mobile phase = 65 %H2O (A): 35 %ET (B) flow rate = 1.8 mL/min UV/Vis = 3D-field (190–600 nm) with specific wave lengths of 249 and 260 nm

Fig. 1.

Representative chromatograms (249 & 260 nm) showing separation of phenolics (Rs > 1.5).

3.3. Phenolics yield for UHPLCMD

3.3.1. General yield for PC-phenolics

The general yield for phenolics showed the sum with a mean (±SD) of 123.1 ppm and 6.84(±4.59) ppm for GA, 219.2 ppm and 12.18(±8.85) ppm for SC and, 11.4 ppm and 0.63(±1.32) ppm for RA. The ranges (minimum–maximum) for phenolics occurrence were 0.8–16.9 ppm (GA), 0–29.5 ppm (SC), and 0–3.7 ppm (RA). The USMD for phenolics exhibited a lack of RV in the PC-samples. On an individual basis; GA was observed more in ET (16.92 ppm) and AC (16.44 ppm) solvent for the skin part, SC in ET:AC (50:50) for the seeds (29.46 ppm) and skin part (24.71 ppm) whereas, RA in ET:AC (50:50) for the skin part (3.73 ppm) of the PC-sample. The descending order for the general yield of phenolics in these PC-samples (N = 18) was: SC > GA > RA. The data for phenolics yield with descriptive statistics is shown in Table 1.

3.3.2. Yield for phenolics in PC-parts

For an individual yield, the phenolics were observed with sum and mean(±SD) of 56.22 ppm and 6.25(±2.06) for GA and, 146.83 ppm and 16.31(±5.81) for SC in the seed part. The seed part showed a lack of presence for the RA and RV in PC-fruit. For the skin part of the PC-fruit, a sum with mean(±SD) of 66.93 ppm and 7.44(±6.31) for GA, 72.41 ppm and 12.07(±9.72) for SC and, 11.41 ppm and 2.85(±1.69) was observed for RA. The highest yield (N = 18) for the individual phenolics in the PC-fruit parts (skin and seed) was 16.92 ppm for GA (skin), 29.46 for SC (seed), and 3.73 ppm for RA (skin).

The descending order for the phenolics was; SC (seed > skin) > GA (skin > seed) > RA (only in skin). The details regarding the phenolics yield in different parts of the PC-fruit are shown in Table 2.

3.3.3. Yield for phenolics in green solvents

The PC-seeds revealed the phenolics yield of 188 ppm (N = 18) whereas, the skin part exhibited a yield of 165.7 ppm (N = 18). The yield (ppm) for PC-fruit (skin and seed) phenolics in absolute solvents (N = 2) was ET (58.92) > AC (43.44) > H₂0 (30.61). For the solvent mixture the phenolics yield was; 16.45 ppm for ET:H20 (30:70), 44.06 ppm for ET:H20 (50:50), 21.08 ppm for ET:H20 (70:30), 26.77 ppm for ET:AC (30:70), 80.76 ppm for ET:AC (50:50), and 31.71 ppm for ET:AC (70:30). The individual phenolics yield/individual solvent (N = 1) was observed with a mean and sum(±SD) of 20.26 ppm and 10.13(±9.06) for AC, 21.89 and 10.94(±8.28) for ET, 17.34 and 8.67(±5.87) for H₂0, 15.67 and 7.83(±5.40) for ET:H₂0 (30:70), 20.99 and 10.5(±6.47) for ET:H₂0 (50:50), 18.42 and 9.21(±6.25) for ET:H₂0 (70:30), 21.09 and 10.54(±7.97) for ET:AC (30:70), 39.76 and 19.88(±14.95) for ET:AC (50:50), and 27.64 and 13.82(±10.44) for ET:AC (70:30) in the seed part of PC-fruit. The sum with mean(±SD) for the skin part showed the yield of 23.18 and 7.73(±7.56) for AC, 37.03 and 18.52(±10.81) for ET, 13.27 and 6.63(±3.99) for H₂0, 5.68 and 2.84(±1.64) for ET:AC (30:70), 41.00 and 13.67(±10.53) for ET:AC (50:50), 4.07 and 1.36(±0.62) for ET:AC (70:30), 0.79 and 0.79(±0.45) for ET:H₂0 (30:70), 23.07 and 11.54(±7.97) for ET:H₂0 (50:50), and 2.66 and 2.66(±1.53) for ET:H₂0 (70:30). The highest total yield for phenolics/solvent was 41.0 ppm for the skin and 39.76 ppm in the seed part observed in ET:AC (50:50) solvent.

The descending order for the total phenolics yield was; seed > skin. For the phenolics yield/individual solvent the order for absolute green solvents was ET (skin > seed) > AC (skin > seed) > H₂0 (skin > seed) whereas, for the solvent mixtures the descending order for PC-fruit (skin and seed) was; ET:AC (50:50) > ET: H₂0 (50:50) > ET:AC (70:30) > ET:AC (30:70) > ET:H₂0 (70:30) > ET: H₂0 (30:70). The data for the total and individual yield in different green solvents for PC-fruit parts is shown in Table 2.

3.4. PC and CA extraction (USMV)

The descriptive statistics (N = 8) showed a sum with mean(±SD) of 680.4 mg/21.6 g and 85.05(±51.48) for PC and CA samples. The range (minimum–maximum) for the extracts yield was 22.3–180.5 mg. An individual highest yield for the extract (180.5 mg/2.7 g) was observed in the red skin part of the PC fruit. Both the fruits of PC and CA showed more extract yield for the red skin and green seeds. For the PC-fruit, the extract yields were 180.5 mg (red skin) and 82 mg (green seeds) whereas, for the CA-fruit the extract yields were 126.2 mg (red skin) and 88.6 mg (green seeds). The data for general extract yields with descriptive statistics is shown in Table 4. The general extract yield for PC and CA showed a descending order; PC (red skin > green seed > green skin > red seed) > CA (red skin > green seed > green skin > red seed).

Table 4.

USUHPLCMV (extract and phenolics yields) with descriptive statistics for PC and CA samples (red and green skin, and seed parts).

S#	Fruit type	Color	Part	Sample	Solvent (ratio) & Volume	Extract yield (mg)	GA (ppm)	SC (ppm)	RA (ppm)	RV (ppm)
PC1	PC	Red	Skin	2700 mg	ET:AC (50:50) & 100 mL	180.5	0.00	117.93	16.34	16.24
PC2			Seed			25.9	16.89	63.74	6.86	5.83
PC3		Green	Skin			68	129.06	134.74	18.76	26.15
PC4			Seed			82	147.36	276	20.2	28.54
CA1	CA	Red	Skin			126.2	16.1	0.00	6.15	0.00
CA2			Seed			22.3	5.53	14.52	23.87	0.00
CA3		Green	Skin			86.9	5.35	3.66	10.68	0.00
CA4			Seed			88.6	6.96	2.21	6.31	0.00

Descriptive statistics
	Minimum	Maximum	Sum	Mean (±SD)
Extract yield	22.3	180.5	680.4	85.05 (±51.48)
GA	0.0	147.4	327.3	40.90 (±60.51)
SC	0.0	276.0	612.8	76.60 (±96.79)
RA	6.2	23.9	109.2	13.64 (±7.02)
RV	0.0	28.5	76.8	9.59 (±12.30)

With regard to the extract yield vs fruit color, the red PC-fruit (N = 2; skin and seed) exhibited a total yield of 206.40 mg/5.4 g with a mean(±SD) of 103.20(±109.32) whereas, the red CA-fruit resulted a total yield of 148.50 mg/5.4 g (N = 2; skin and seeds) with a mean(±SD) of 74.25(±73.47).

The fruit part for PC and CA resulted an extract yield of 248.50 for the skin and 107.90 for the seed part of the PC-fruit whereas, an extract yield of 213.10 for the skin and 110.90 for the seeds part of the CA-fruit were observed.

The total extract yield (N = 4) resulted a descending order of; PC-fruit (356.40 mg) > CA-fruit (324.0 mg). For the extract yield vs fruit color (N = 8), the descending order was; PC-red skin > CA-red skin > CA-green seeds > CA-green skin > PC-green seed > PC-green skin > PC-red seed > CA-red seed whereas, for the extract yield vs fruit part (N = 4) the descending order was; PC-skin > CA-skin > CA-seeds > PC-seeds. The extract yield in red and green fruit parts of the PC and CA are shown in Table 5.

Table 5.

Yields (individual and total extract and phenolics yield/fruit part) for seed and skin parts of PC and CA.

Color	Part	Extract yield (mg)	Seeds yield (mg)	Skin yield (mg)	Total yield (mg)	GA	SC	RA	RV	Sum	Mean (±SD)
PC (red)	Skin	180.50				0.00	117.93	16.34	16.24	150.51	50.17 (±54.08)
	Seed	25.90				16.89	63.74	6.86	5.83	93.32	23.33 (±27.40)
	Sum	206.40				16.89	181.67	23.20	22.07
	Mean	103.20				16.89	90.84	11.60	11.04
	SD	109.32				11.94	38.32	6.70	7.36
PC (green)	Skin	68.00				129.06	134.74	18.76	26.15	308.71	77.18 (±63.30)
	Seed	82.00				147.36	276.00	20.20	28.54	472.10	118.03 (±120.27)
	Sum	150.00	107.90	248.50	356.40	276.42	410.74	38.96	54.69
	Mean	75.00				138.21	205.37	19.48	27.35
	SD	9.90				12.94	99.89	1.02	1.69
CA (red)	Skin	126.20				16.10	0.00	6.15	0.00	22.25	11.13 (±7.60)
	Seed	22.30				5.53	14.52	23.87	0.00	43.92	14.64 (±10.47)
	Sum	148.50				21.63	14.52	30.02	0.00
	Mean	74.25				10.82	14.52	15.01	0.00
	SD	73.47				7.47	10.27	12.53	0.00
CA (green)	Skin	86.90				5.35	3.66	10.68	0.00	19.69	6.56 (±4.44)
	Seed	88.60				6.96	2.21	6.31	0.00	15.48	5.16 (±3.33)
	Sum	175.50	110.90	213.10	324.00	12.31	5.87	16.99	0.00
	Mean	87.75				6.16	2.94	8.50	0.00
	SD	1.20				1.14	1.03	3.09	0.00

3.5. Phenolics profiling for PC and CA (UHPLCMV)

The general yield (N = 8) for the phenolics was observed with a sum and mean(±SD) of 327.3 ppm and 40.90(±60.51) for GA, 612.8 and 76.60(±96.79) for SC, 109.2 and 13.64(±7.02) for RA and, 76.8 and 9.59(±12.30) for RV. The ranges (minimum–maximum) for these phenolics were observed as 0.0–147.4 (GA), 0.0–276.0 (SC), 6.2–23.9 (RA), and 0.0–28.5 ppm (RV), as shown in Table 4. The individual high yield (N = 1) for GA (147.36), SC (276), and RV (28.54) was seen in green seeds of the PC-fruit except the RA (23.87) which was seen more in the green seeds of the CA-fruit. The descending order for the general yield (N = 8) of phenolics was; SC > GA > RA > RV whereas, for the individual yield (N = 1) the order observed was; SC > GA > RV > RA.

The phenolics yield (ppm) vs PC-fruit color (N = 2), the red color fruit showed the sum with a mean(±SD) of 16.89 and 16.89(±11.94) for GA, 181.67 and 90.84(±38.32) for SC, 23.20 and 11.60(±6.70) for RA, and 22.07 and 11.04(±7.36) for RV whereas, the green PC-fruit revealed the sum with a mean(±SD) of 276.42 and 138.21(±12.940 for GA, 410.74 and 205.37(±99.89) for SC, 38.96 and 19.48(±1.02) for RA and, 54.69 and 27.35(±1.69) for RV. For the CA-fruit, red color showed the sum with mean(±SD) of 21.63 and 10.82(±7.47) for GA, 14.52 and 14.52(±10.27) for SC and, 30.02 and 15.01(±12.53) for RA. Likewise, the green CA-fruit was observed with a sum and mean(±SD) of 12.31 and 6.16(±1.14) for GA, 5.87 and 2.94(±1.03) for SC and, 16.99 and 8.50(±3.09) for RA. The red and green fruit for CA was seen with a lack of RV. On an individual basis (N = 1), GA and SC were found with a highest yield in green PC-fruit seeds (147.36 and 276.0 ppm) and skin (129.06 and 134.74 ppm), respectively whereas, RA was seen more in red CA-fruit seeds (23.87 ppm). Only the red and green PC-fruit parts showed the presence of RV where, the highest yield was observed again in the seed (28.54 ppm) and seeds (26.15) parts of the green PC-fruit.

For the phenolics yield (ppm) vs fruit part (N = 1), the sum with mean(±SD) were observed as; 150.51 and 50.17(±54.08) for skin part of the red-PC fruit, 93.32 and 23.33(±27.40) seeds part of the red PC-fruit, 308.71 and 77.18(±63.30) skin part of the green PC-fruit, 472.10 and 118.03(±120.27) seeds part of the green PC-fruit, 22.25 and 11.13(±7.60) skin of the red CA-fruit, 43.92 and 14.64(±10.47) seeds of the red CA-fruit, 19.69 and 6.56(±4.44) skin of the green CA-fruit and, 15.48 and 5.16(±3.33) seeds of the green CA-fruit, as shown in Table 5.

For the total yield of phenolics in the red and green parts of the PC and CA fruits, a descending order was constructed; “SC” (green PC-seeds > green PC-skin > red PC-skin > red PC-seeds > red CA-seeds > green CA-skin > green CA-seeds)> “GA” (green PC-seed > green PC-skin > red PC-seeds > red CA-skin > green CA-seeds > red CA-seeds > green CA-skin)> “RA” (red CA-seeds > green PC-seeds > green PC-skin > red PC-skin > green CA-skin > red PC-seeds > green CA-seeds > red CA-skin). RV was seen with a descending order of; green PC-seeds > green PC-skin > red PC-skin > red PC-seeds. The descending order for the phenolics yield vs fruit part (N = 1) was; seeds green-PC > skin green-PC > skin red-PC > seeds red-PC > seeds red-CA > skin red-CA > skin green-CA > seeds red-CA.

3.6. Statistical models for analysis

3.6.1. Mean differences for PC- and CA-fruit parts and color

The mean differences were computed for the two models; Model-I (extract yields*GA*SC*RA*RV vs fruit parts) and Model-II (extract yields*GA*SC*RA*RV vs fruit colors). For Model-I a higher mean difference for the extract yield (461.6; 67.8 %) and RV (42.4; 55.2 %) was found in the skin part of the PC- and CA-fruit whereas, the mean differences for the GA (176.7; 54 %), SC (365.6; 58.2 %), and RA (57.2; 23.9 %) were found higher in the seeds part of the PC- and CA-fruit. With regard to Model-II, red color of the fruit showed higher mean difference for the extract yield (354.9; 52.2 %) only whereas, the phenolics i.e., GA (288.7; 88.2 %), SC (416.6; 68.0 %), RA (56.0; 51.3 %), and RV (54.7; 71.2 %) were seen with higher mean in green seeds of the fruits. The mean differences for the two models are shown in Table 6.

Table 6.

Mean differences for the extract and phenolics yields vs fruit parts and color used.

Mean differences for extract yields*GA*SC*RA*RV Vs fruit parts							Mean differences for extract yields*GA*SC*RA*RV Vs fruit colors
Part		Extract yield	GA	SC	RA	RV	Color		Extract yield	GA	SC	RA	RV
Skin (N = 4)	Mean	115.40	37.62	64.08	12.98	10.59	Red (N = 4)	Mean	88.72	9.63	49.04	13.30	5.51
	SD	49.71	61.32	72.22	5.67	12.88		SD	77.85	8.24	53.41	8.437	7.65
	Sum	461.6	150.5	256.3	51.9	42.4		Sum	354.9	38.5	196.2	53.2	22.1
	Minimum	68.0	0.0	0.0	6.2	0.0		Minimum	22.3	0.0	0.0	6.2	0.0
	Maximum	180.5	129.1	134.7	18.8	26.2		Maximum	180.5	16.9	117.9	23.9	16.2
	% of total sum	67.8	46.0	41.8	47.6	55.2		% of total sum	52.2	11.8	32.0	48.7	28.8
Seed (N = 4)	Mean	54.70	44.18	89.118	14.31	8.59	Green (N = 4)	Mean	81.375	72.18	104.1	13.98	13.6
	SD	35.46	68.96	127.39	9.04	13.57		SD	9.3454	76.61	130.3	6.614	15.81
	Sum	218.8	176.7	356.5	57.2	34.4		Sum	325.5	288.7	416.6	56.0	54.7
	Minimum	22.3	5.5	2.2	6.3	0.0		Minimum	68.0	5.4	2.2	6.3	0.0
	Maximum	88.6	147.4	276.0	23.9	28.5		Maximum	88.6	147.4	276.0	20.2	28.5
	% of total sum	32.2	54.0	58.2	52.4	44.8		% of total sum	47.8	88.2	68.0	51.3	71.2
Total (N = 8)	Mean	85.05	40.90	76.60	13.64	9.59	Total (N = 8)	Mean	85.050	40.90	76.60	13.64	9.59
	SD	51.48	60.51	96.79	7.02	12.30		SD	51.48	60.51	96.79	7.02	12.30
	Sum	680.4	327.3	612.8	109.2	76.8		Sum	680.4	327.3	612.8	109.2	76.8
	Minimum	22.3	0.0	0.0	6.2	0.0		Minimum	22.3	0.0	0.0	6.2	0.0
	Maximum	180.5	147.4	276.0	23.9	28.5		Maximum	180.5	147.4	276.0	23.9	28.5
	% of total sum	100	100	100	100	100		% of total sum	100	100	100	100	100

3.6.2. ANOVA with Pearson’s bivariate correlation

The ANOVA for the PC- and CA-fruits vs the colors*parts*extract yields*phenolics amount revealed significant differences for the; fruit type (PC or CA) vs extract yield (M = -80.55, P = 0.00), fruit type (PC or CA) vs RA (M = -9.14, P = 0.01), fruit part (skin or seeds) vs extract yield (M = -83.55, P = 0.00), fruit part (skin or seeds) vs RA (M = -12.14, P = 0.00), fruit color (red or green) vs extract yield (M = -83.55, P = 0.00), and fruit color (red or green) vs RA (M = -12.14, P = 0.00).

The bivariate correlation followed the ANOVA pattern where a positive correlation was constructed for GA, SC, and RV whereas, RA showed no correlation in any of the pairs with GA, SC, and RV. The data for ANOVA and bivariate correlation is shown in detail in Table 7.

Table 7.

Paired samples anova with bivariate pearson’s correlation for extract and phenolics yield of the parts and color of the pc and ca fruit.

ANOVA
Pairs	Variables	Mean	95 % CI of the difference		Sig
			Lower	Upper
Pair 1	Capsicum type - extract yield	−80.55	−124.13	−36.96	0.00
Pair 2	Capsicum type - GA	−36.40	−87.54	14.73	0.13
Pair 3	Capsicum type - SC	−72.10	−154.12	9.92	0.07
Pair 4	Capsicum type - RA	−9.14	−15.75	−2.53	0.01
Pair 5	Capsicum type - RV	−5.09	−16.71	6.52	0.33
Pair 6	Fruit part - extract yield	−83.55	−126.87	−40.22	0.00
Pair 7	Fruit part - GA	−39.40	−89.97	11.16	0.10
Pair 8	Fruit part - SC	−75.10	−155.96	5.76	0.06
Pair 9	Fruit part - RA	−12.14	−17.99	−6.29	0.00
Pair 10	Fruit part - RV	−8.09	−18.42	2.23	0.10
Pair 11	Fruit color - extract yield	−83.55	−126.63	−40.46	0.00
Pair 12	Fruit color - GA	−39.40	−89.75	10.94	0.10
Pair 13	Fruit color - SC	−75.10	−155.89	5.69	0.06
Pair 14	Fruit color - RA	−12.14	−18.01	−6.27	0.00
Pair 15	Fruit color - RV	−8.09	−18.23	2.04	0.10
Bivariate correlation
	Extract yield	GA	SC	RA	RV
Extract yield	1	0.0	0.0	0.0	0.0
GA	−0.15 0.72	1	0.0	0.0	0.0
SC	0.09 0.81	0.83 0.01	1	0.0	0.0
RA	−0.17 0.68	0.46 0.24	0.52 0.18	1	0.0
RV	0.15 0.72	0.87 0.00	0.93 0.00	0.53 0.17	1

3.6.3. Principle components and K-mean cluster analysis

The %variance for the extract and phenolics yield was calculated using the principal component analysis. The total %variability was 84.85 for the statistical model where two components were proposed with respective %variabilities of 62.5 and 22.33 for component 1 and 2. The major %variability (component 1) was loaded with the phenolics (GA, SC, RA, and RV). The extract yield exhibited less %variability and was loaded in component 2. The KMO and Bartlett’s test of sphericity showed a high X²-value (20.11) at P = 0.02. A detailed data for the component analysis is shown in Table 8 with loading shown in Fig. 2.

Table 8.

Principal component analysis with k-mean cluster distribution for the phenolics observed in CA and PC fruits.

DV	Component 1	Component 2	KMO and Bartlett's Test
Extract yield	0.01	0.97	Kaiser-Meyer-Olkin Measure of Sampling Adequacy		0.64
GA	0.91	−0.12	Bartlett's Test of Sphericity	Approx. Chi-Square	20.11
SC	0.95	0.12		df	10
RA	0.67	−0.33		Sig.	0.02
RV	0.96	0.16
Individual variance (%)	62.5	22.33
Cumulative variance (%)	62.5	84.85

K-mean cluster analysis
Factors	F-value	Significance	Clusters	Samples
Z-score: extract yield	3.36	0.13	1	1
Z-score: GA	122.53	0.00	2	1
Z-score: SC	5.47	0.06	3	4
Z-score: RA	29.82	0.00	4	2
Z-score: RV	48.50	0.00	Total	8

Fig. 2.

Components loading for extracts- and phenolics yields in PC and CA samples.

The K-mean suggested four clusters for the eight samples of PC- and CA-fruits. Cluster-1 consisted of 1 sample (PC1; red skin of the PC-fruit with the highest extract yield only), cluster-2 showed 1 sample (CA2, red seeds of the CA-fruit with the highest yield for RA only), cluster-3 showed 4 samples (CA1; red skin of the CA-fruit, CA3; green skin of the CA-fruit, and CA4; green seeds of the CA-fruit showing the least amount of extract- and phenolics-yield) whereas, cluster-4 was seen with 2 samples (PC3; green skin of the PC-fruit and PC4; green seeds of the PC-fruit showing the highest amount of phenolics only). The data for K-mean cluster analysis is shown in Table 8 and Fig. 3.

Fig. 3.

Clusters with respective loadings of the variables observed for extracts- and phenolics yields.

4. Discussion

The green extraction with phytochemical analysis for the S. pseudocapsicum specie was undertaken for the first time in this study to explore and compare its phenolics profile with C. annum, a well-known species from the same family of Solanaceae. As mentioned earlier, alkaloids and volatile profile for the PC-fruit have been reported however, no reports are available to comprehensively characterize the phenolics profile for this plant with regard to the seeds and skin parts of the green and red fruits. Herein, ultrasonic assisted extraction (US) with UHPLC analysis was employed to extract and quantify the phenolics in different parts of the PC-fruit (seeds and skin), at two different stages (green and red color) using the green solvents of acetone (AC), ethanol (ET), and water (H₂O). The extraction and analysis method were developed (USUHPLCMD) followed by validation (MV) and comparative evaluation for phenolics in the seeds and skin parts of the two different color fruits (red and color) of Solanum species (PC- and CA-fruits).

An in-house previously developed and validated US method was used to extract the PC-fruit samples. US technique was preferred due to the advantages it offers during extraction; short time, less solvents volume and samples amount used, and more yield observed for the targeted phytochemicals. [11], [12] To start with the experiment, six samples (N = 6) for the PC-fruit (3-seeds and 3-skin samples) were extracted in absolute solvents of ET, AC, and H₂O. More yields for the extracts and phenolics were observed in AC and ET solvents with a descending order of AC > ET > H₂0. Hence, the three solvents at different ratio were mixed and the PC-fruit parts (N = 12) were extracted again. The results showed more extract yield for ET:AC (70:30) and (30:70) solvent systems with a descending order of; ET:AC (70:30) > ET:AC (30:70) > ET:AC (50:50) > ET:H₂0 (50:50) > ET:H₂0 (70:30) > ET:H₂0 (30:70). However, the phenolics yield was seen more in the ET:AC (50:50) solvent system, for both the skin and seeds parts of the PC-fruit. This ratio of the ET:AC (50:50) validated the previous extraction step where more extract and phenolics yield were observed in absolute solvents of ET and AC. Henceforth, the solvent system of ET:AC (50:50) was chosen the optimum combination for the extraction of PC-fruit phenolics. The combination of AC:ET (50:50) solvent system have been reported in previous studies for extraction and analysis of capsicum phytochemicals. [13], [14].

In order to determine the phenolics content for the US-extracted samples, a green analytical method for simultaneous development of phenolics was developed using ET and H₂O. The developed UHPLCMD is a green, ecofriendly, economical, faster, and reproducible method reporting a runtime of 3 min for separation and identifications of the phenolics. This is the first time to report a green and fast method consisting a runtime of 3-min for simultaneous determination of four phenolics in general and in particular for the PC-fruit. Previous methods reported a long runtime with the use of non-green solvents for phenolics determination. [15], [16] The UHPLCMD was validated for its accuracy, LODs, LOQs, determination of coefficient-r², and Rs value of the peaks where significant results were observed, supporting the method to be applied for a large-scale determination of the tested phenolics. The analytical method revealed the presence of more amount of SC and GA in the skin and seeds part of the PC-fruit samples extracted with ET:AC (50:50). RA was found in the skin part only whereas, the RV was absent in all the extracted samples of seeds and skin parts with a descending order of SC > GA > RA. The results for the phenolics-UHPLCMDMV also suggested the use of ET:AC (50:50) as a solvent system for extraction. With regard to the fruit part, more extract yield was observed for the skin part of the PC-fruit; skin extract yield > seed extract yield whereas, the seed’s part revealed more amount for SC as compared to the skin part containing more GA; SC (seed > skin) > GA (skin > seed) > RA (only in skin). Our study is in-line with previous reports where the presence for phenolics compounds was shown in capsicum. [17], [18], [19], [20] Following the successful UHPLCMDMV, the USMD was validated in PC- and CA-fruits with an aim to comparatively evaluate the presence and quantify the phenolics amount in the seeds and skin parts of the two different color PC- and CA-fruit samples (red and green). More extract yield was observed for the PC-fruit compared to the CA-fruit where the skin part was dominant for the extract yield; PC (red skin > green seed > green skin > red seed) > CA (red skin > green seed > green skin > red seed). With respect to the extract yield in different parts of the fruit, PC-skin showed the highest yield followed by the CA-skin whereas, for the color of the fruit, red skin was reported with more extract yield in both the fruits with a descending order of; PC-red skin > CA-red skin > CA-green seeds > CA-green skin > PC-green seed > PC-green skin > PC-red seed > CA-red seed. The phenolics were seen more for the green color PC-fruit where more yield was exhibited by the seed’s parts; seeds green-PC > skin green-PC > skin red-PC > seeds red-PC > seeds red-CA > skin red-CA > skin green-CA > seeds red-CA. Alike USMD, SC was seen more followed by GA, RA and RV during USMV.

The presence of more phenolics in the seeds and green color fruit may be explained on the basis of maturation stage and cultivar type as reported previously. Though the debate still exists regarding the increase and decrease of phytochemicals in capsicum species, the researchers are of the opinion that the phenolics and flavonoids content is found more in the green and immature stages of the capsicum fruits. [21], [22], [23] For comparative analysis, PC-fruit revealed the presence for all the phenolics (GA, SC, RA, and RV) in high amount as compared to CA-fruit where less amount for the phenolics along with an absence of RV was reported. It is noteworthy to mention that RA was observed only in the skin part whereas, RV showed a lack of presence in any of the samples (N = 18) of the PC-fruit during USMD. On contrary, RA was seen in significant amount in PC- and CA-fruit samples during USMV however, RV was detected in the PC-fruit only. The difference may be due to the amount of sample extracted along with the concentration of the sample injected for detection. USMD employed a very less amount of sample (100 mg) for extraction which was further diluted for UHPLC detection making the RA and RV amount insufficient for UHPLC detection. Additionally, UHPLC is considered less sensitive compared to the LCMSMS system hence, making it inconvenient for the samples with low concentration of the targeted phytochemical. Likewise, the IV for the samples injected to the system was 1 μL which further decreases the amount of phytochemical injected into the system hence, further decreasing the quantification limits for the UV-detection. In contrast, the USMV used more amount of sample for extraction (2.7 g) as well as the sample for injection was prepared at a concentration of 2 mg/mL. This implicate a significant difference for distribution of different phenolics in a sample where, the phenolics distributed in huge amount are convenient to be detected with UHPLC however, it become difficult to quantify the phenolics in a sample with sparse distribution. A more sensitive technique of LCMSMS may be more helpful and authentic in this regard.

The USUHPLCMDMV suggested ET:AC (50:50) the optimum solvent system for more extract yield in the skin part of the red fruits as well as for the dense distribution of the phenolics (GA, SC, RA, and RV) in the seeds parts of the green PC- and CA-fruits. RA was seen with significant difference in the two fruits whereas, RV was found in the PC-fruit only. The lack of RV in CA-fruit may be due to a number of factors including; difference in geographical origins, maturation stage, improper collection and storage, deterioration or abstraction of the phenolics during shipment, and organic or conventional farming of the fruits and herbs. [3], [24], [25], [26] The data was further validated with the help of statistical models. Mean differences were computed for the PC- and CA-fruit parts and colors. For the extract yields, skin of the red color fruits exhibited more yields while seeds of the green color fruits exhibited more phenolics yield. The results for ANOVA were in concordance with the previous observations where type of the fruit (PC or CA), its parts (skin or seeds), and colors (red or green) exhibited significant differences for the extract yields and phenolics content i.e., GA and SC were found higher in all the samples, RA was found with significantly lower amount in both the fruits, and RV was not reported for CA-fruit samples. The bivariate correlation further confirmed the ANOVA data where no correlation was constructed for the RA-samples showing the sparse distribution for RA in PC- and CA-fruits. For the principal component analysis, more %variance was shown by the phenolics yield as compared to the extract yield. This employs a profound effect of fruit type upon the occurrence and distribution of phenolics in different fruit samples rather than the effect of fruit type upon extract yield. The K-mean analysis classified the samples on the basis of more extract yield and phenolics content present. Two samples only i.e., PC3 (green skin of PC-fruit) and PC4 (green seed of PC-fruit) exhibited the highest amount for phenolics content among the PC- and CA-fruit samples. These statistical models proved the enrichment of the green PC-fruit, seeds in particular, with phenolics content.

5. Conclusion

A green extraction and analysis method was developed for the comparatively profiling of the PC-fruit phenolics. The USMD showed more extract yields for the skin parts of the red whereas, the seeds part exhibited more yield for the green seeds of PC-fruit. SC was found the highest followed by GA. The USMD was validated for a comparative evaluation of the phenolics content in different parts and colors of the PC- and CA-fruit. The dataset generated were analyzed with statistical models. The skin part for the red PC-fruit revealed more extract yield whereas, the seeds part of the PC-fruit showed more phenolics compared to the CA-fruit. The USUHPLCMDMV in this study successfully compared and evaluated different parts and colors of the PC- and CA-fruit for the yields of extract and phenolics.

6. Author contribution

RA (conceptualization and design of the study); MR (collection and availability of the PC-samples); RA, MR, and MA (review of the literature, write-up for the introduction and discussion part); AA, WA, DA, AIA, and HZA (CA-samples collection, drying and preparation of the samples, US-extraction, and UHPLC samples preparation), RA and MA (UHPLCMDMV and phenolics quantification for US-samples); AA, WA, DA, AIA, and HZA (data generation and compiling for the excel and SPSS sheets); RA (SPSS-data analysis, results write-up, and finalizing the manuscript); RA, MR, MA, AA, WA, DA, AIA, and HZA (peer-review and final approval of the manuscript).

7. Fundin source

This research work received no funding from any government or private organization.

8. Consent to publish

The authors presented their consent to publish the data and manuscript in its current format.

9. Availability of data

The data used to generate results and conclusions is presented completely in this manuscript.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.