
==== Front
Food Chem (Oxf)
Food Chem (Oxf)
Food Chemistry: Molecular Sciences
2666-5662
Elsevier

S2666-5662(24)00024-8
10.1016/j.fochms.2024.100217
100217
Research Article
Metabolomics and microscopic profiling of flaxseed meal- incorporated Peda
Maurya Sachin a
Verma Tarun tarunverma@bhu.ac.in
a⁎
Aggarwal Ankur ankuraggarwal39@gmail.com
a⁎
Kumar Singh Manish b
Dutt Tripathi Abhishek a
Trivedi Ankur c
a Department of Dairy Science and Food Technology, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India
b Department of Food Technology, School of Engineering and Technology, Mizoram University, Aizawl, Mizoram, India
c Department of Dairy Technology, National Dairy Research Institute, Karnal, Haryana, India
⁎ Corresponding authors. tarunverma@bhu.ac.inankuraggarwal39@gmail.com
22 8 2024
30 12 2024
22 8 2024
9 1002178 4 2024
20 7 2024
17 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Graphical abstract

Highlights

• Metabolomics of optimized Peda was done using two different omics tools.

• Optimization (2% FMP) reveals high sensorial and textural properties.

• Enhanced level of fat, protein and antioxidants were seen in the best formulation.

• HR-MS and GC–MS identified 22 bioactives and six key fatty acids respectively.

• FMP added Peda can be functional dairy product with plant-based substitution.

Functional dairy foods are in high demand due to their convenience, enhanced nutrition, intriguing flavors, and natural ingredients. The valorization of flaxseed by-products can potentially boost the functionality of these foods. This work involves the optimization of flaxseed meal powder (2%, 2.5%, 3%) during Peda preparation based on sensory and textural attributes. The optimized Peda (2%) exhibited significantly reduction in moisture (39.6%) and water activity (18.9%), while significantly increasing crude fiber (1.88%), protein (26.4%), fat (8%) and DPPH inhibition (274.5%) as compared to control Peda. Scanning electron microscopy of the optimized Peda revealed the surface displayed a dense, uneven texture, heavily coated with fat, and intergranular spaces filled with milk serum. Twenty-three primary compounds were recognized in high-resolution mass spectrometry (HR-MS), including 6 organic acids, 6 amino acids, 3 fatty acids, 3 other metabolite derivatives, 2 lipids, 2 bioactive components, and 1 sugar. Besides gas chromatography mass spectrometry (GC–MS) found six separate types of fatty acids. These compounds have been proven to possess various bioactivities, such as promoting brain activity, antioxidant, anti-diabetic, anti-inflammatory, cardiovascular-protective effects, etc. Flaxseed meal, as a plant-based substitute for dairy ingredients, offers a sustainable and healthy alternative, making flaxseed-incorporated Peda a functional food.

Keywords

Functional food
Peda
Flaxseed meal
Metabolomics
Bioactive compounds
==== Body
pmc1 Introduction

A substantial amount of oilseed plant produce ends up as by-products and waste during processing, annually (Rao et al., 2021). Often, these by-products are either discarded or used as animal feed. Nevertheless, many of these by-products are rich in bioactive compounds that can be utilized to develop innovative food products through different valorization methods (Łopusiewicz et al., 2019).

Increasing consumer awareness of health issues has led to a higher demand for plant-based functional foods (Łopusiewicz et al., 2019). Food companies are increasingly seeking alternatives to address health and environmental challenges through the development of new plant-based functional foods. Transitioning to a fully plant-based diet can be difficult, so a partial substitution approach may benefit both consumers and the industry. Combining dairy and plant ingredients represents a promising alternative, offering potential health benefits and easing the transition to plant-based products. Desiccated dairy products like “Peda” could serve as an effective base for incorporating oilseed processing by-products through partial substitution (Ravindra et al., 2022).

Peda is a sweetened heat-desiccated traditional dairy product that is widely consumed in the Indian sub-continent, and has its roots in the culture of the region since ancient times (Asgar & Chauhan, 2019). This dairy product has its key base material, known as Khoa which is made by heat-concentrating the buffalo milk in an open pan until it achieves a dough-like consistency. Researchers have noted that khoa made from buffalo milk not only exhibits increased yield but also elucidates superior sensory quality and enhanced textural attributes (Choudhary et al., 2017).

Flaxseed (Linum usitatissimum L.) is an annual plant within the Linaceae family that has gathered attention from nutritionists and food scientists because of its immense potential for utilization in the functional food product development that carries active components like α-Linolenic acid, lignin, and dietary fiber (Kajla et al., 2023). With increasing consumer demand for functional foods that could offer enhanced health advantages, flaxseed has emerged as a promising ingredient that is gaining popularity in diets tailored to specific health objectives (Gul et al., 2016). The flaxseed oil processing industry generates a valuable by-product i.e., flaxseed meal (FM) which contains ∼ 40 % protein and is presently utilized for protein supplements, fertilizers, and feed development (Wu et al., 2019). The valorization of FM in the dairy product matrix could be the sustainable and nutritional alternative for the use of this by-product in functional food development.

Untargeted metabolomics is always an intriguing tool for analyzing the comprehensive primary and secondary metabolites in a product and was employed for metabolic activity analysis of these functional foods. The application of omics technology, particularly the high-resolution mass spectroscopy (HR-MS) approach is improving the detection of bioactive and putative markers in the valorized dairy-based products (Jaspal et al. (2024). Gas chromatography-mass spectroscopy (GC–MS) is also an effective and efficient tool for detailed volatile compound profiling of the food product. The application of such robust methodologies in the characterization of bioactive components of a valorized Indian dairy product could reveal the overall functionality of the product.

In the present study, flaxseed meal powder (FMP) was added to the base matrix of Peda in varying concentrations to develop functional dairy products. Furthermore, a specialized bioactive metabolite search based on high-resolution mass spectroscopy (HR-MS) and gas chromatography-mass spectrometry (GC–MS) were performed on FMP-incorporated Peda to highlight the functionality of the product.

2 Materials and methods

2.1 Reagents and materials

Mature whole flaxseed (10 kg) was sourced from the agricultural unit of the Banaras Hindu University, Varanasi followed by manually cleaned to remove impurities, cold-pressed to obtain oil defatted meal (Lee et al., 2023). The FM was broken and other ingredients were individually roasted with a small amount of oil in a frying pan for 5 min at 80 °C to remove any off-flavor. After cooling the meal was ground separately in a laboratory mixer (Kenstar, Mumbai) at room temperature to obtain FPM. Formic acid (FA) and methanol (MeOH) were both of LC–MS grade and sourced from Sigma Aldrich (Bengaluru, India). Additional materials such as syringes, polytetrafluoroethylene (PTEF) filters (25  mm × 0.22  µm), amber vials (2 ml), polypropylene falcon tubes (50  ml), test tubes, glass beakers, etc. were purchased from the Hi-Media (Mumbai, India).

2.2 Development of flaxseed meal powder added Peda

During the development of Peda, 5 L of milk (6.0 % fat, 9.0 % SNF) were sourced from the Dairy Farm, Banaras Hindu University. Following the methodology outlined by Badola et al. (2023) with slight alterations, four-set Peda treatments T1: (milk + 2 % FMP), T2: (milk + 2.5 % FMP), T3: (milk + 3 % FMP) and control T0: (milk only) were formulated, each replicated three times. The meal powder was limited to 3 % to maintain dough consistency (Fig. 1). The process involved heating the milk to ∼ 80 °C with continuous stirring, then cooling until the desired consistency was reached. The Peda was optimized using sensorial analysis (20 semi-trained panellists) and textural attributes (Model: CT3, Brookfield, Mumbai, India). The sample reveals formulation having 2 % FMP has high sensorial and textural properties.Fig. 1 The process flow diagram of flaxseed meal powder incorporated Peda making.

2.3 Physico-chemical analysis

In the To and T1 samples fat, moisture, protein, total carbohydrate, fiber, antioxidants (mg GAE), and ash content were determined using the method described by Pratap et al., 2019, while reducing and non-reducing sugars were analysed (Roy et al., 2024). Water activity (aw) (Rotronic AG, Switzerland) of control and optimized Peda samples were measured at 25 °C (Hirpara et al., 2015).

2.4 Microscopic examination of Peda structure

Scanning electron microscope (SEM) was utilized to check the morphological characteristics of both Peda samples that were controlled and those that had been incorporated with FMP. This analysis was conducted using a Zeiss SUPRA-40 model located in India’s Mumbai city and took place at 100 × magnification.

2.5 HR-MS metabolomics of Peda

Untargeted high-resolution mass spectrometry using Thermo Fisher equipment was conducted following the procedure outlined by Jaspal et al. (2024) with slight modification. For HR-MS sample preparation, 1.5 ml of an 80:20 methanol mixture was added to 100 mg of the optimized samples. The mixture was homogenized at a speed of 750 rpm for 30 min at 25 °C. It was then centrifuged at 3500 rpm for 10 min, also at 25 °C. The resulting supernatant was filtered using a PTFE syringe filter with 0.22 μm pores. For this purpose, 4 μl of the filtered sample were introduced into a Hypersil GOLD™ C18 RP-HPLC column holding particles of dimensions 1.9 μm in size, 2.1 mm in diameter and 100 mm in length. This resulted to chromatographic separation attained in a gradient system that varied from 5 % MeOH to 90 % MeOH within 30 min while flowing at 300 μL/min meanwhile maintaining 40 °C within the column. The Thermo Scientific Orbitrap Eclipse equipped with Ultra High Performance Liquid Chromatography UHPLC, and heated electrospray ionization (HESI) source were employed to conduct three measurements of the optimized Peda (T1). Data dependent analysis (DDA) was carried out using Compound Discoverer 3.3.2.31 and different online databases. The analysis was performed by means of a resolution of 15,000 under positive (3500 V) and negative (2500 V) ionization modes. With this approach, one could identify, identification, and grouping of unknown compounds, estimate chemical formulas, find similar spectra among their spectral similarity searches and what not; consequently, these findings could be utilized in creating molecular groups through corresponding connections within the molecular networks made out from them.

2.6 Analysis using gas chromatography-mass spectrometry (GC–MS)

We analyzed quantitatively the methanolic crude extract from the optimized Peda through a Shimadzu QP 2010 PLUS GC–MS system which was employed with a 30 m × 0.25 mm × 0.25 µm film thickness capillary column (Hossain & Rahman 2011). The injection was splitless with 1-minute purge time. The flow rate of helium carrier gas was 1 ml/min. After being set at 50 °C for 3 mins, the column temperature was raised to 80 °C at a pace of 5 °C/min, and then to 340 °C at a pace of 10 °C/min. The inlet temperature was 250 °C, detector temperature was 340 °C, and a 4 mins solvent delay was applied. In peak identification, mass spectra is matched against NIST 08 and NIST 08 s library and also compared with published data.

2.7 Statistical analysis

SPSS for Windows release 9.0 (SPSS.16, Chicago, USA) was employed to conduct the ANOVA tests. The means were compared using data from the least significant difference multiple range analysis. To assess variations between treatments multiple-range test was utilized. Statistical significance was evaluated at the 5 % level and each experiment was replicated three times (n = 3).

3 Results and discussion

The current study focuses on creating Peda enriched with FMP to enhance its functional properties and its foodomics metabolite profiling was done.

3.1 Proximate composition, sensory and textural attributes of Peda

Different concentrations of FMP were incorporated into the development of functional Peda for optimization purposes using sensory and textural attributes. The sample of Peda containing 2 % FMP (T1) treatment was the best optimized in terms of sensorial and textural attributes in present study. FMP-Peda when compared to the control (T0), has a higher fat content mainly due to FMP in a diet may contribute to increased healthy fat intake (Zhang et al., 2023). It also exhibits a significant increase in protein and fiber, making it a valuable plant-based protein source with digestive and potential weight management benefits (Xie et al., 2023). The organoleptic characterization of FMP Peda were acceptable when flaxseed powder was added to yoghurt as reported by Marand, et al., 2020. The addition of flaxseed meal powder significantly increased (P<0.05) the hardness of Peda, likely due to the high total solid content in the flaxseed meal powder. Suresh and Jha (1994) observed that increased total solids in milk were strongly correlated with greater hardness in khoa. Furthermore, adding flaxseed meal powder to Peda significantly (P<0.05) decrease adhesiveness. Bhat et al. (2018) also reported that flaxseed altered internal bonds in yogurt, reducing adhesiveness and enhancing cohesiveness. The optimization results of the physicochemical, sensory and textural attributes of FMP-Peda with control Peda are shown in Table 1.Table 1 Physicochemical sensory and textural attributes of the control and FMP incorporated Peda.

Treatment	Physico-Chemical Analysis	
Control Peda	FMP-Peda	
Parameter (percent)	T0	T1	
Fat	30.14 ± 0.21b	32.55 ± 0.08a	
Moisture	19.56 ± 0.22a	11.82 ± 0.31b	
Protein	15.93 ± 0.13a	20.13 ± 0.11b	
Fibre	0.00a	1.88 ± 0.31b	
Ash	2.82 ± 0.01a	2.80 ± 0.03a	
Reducing sugar	31.43 ± 1.10a	30.11 ± 1.01a	
Non-Reducing Sugar	0.49 ± 0.01a	0.54 ± 0.01a	
Total Solid	80.43 ± 1.31a	87.03 ± 1.21b	
Antioxidant (mg/GAE)	9.4 ± 0.31a	35.2 ± 2.11b	
Water Activity	0.8070 ± 0.01a	0.6548 ± 0.01b	


	
Sensory analysis	
Colour and Appearance	8.6 ± 0.31a	8.3 ± 0.17a	
Body and Texture	8.4 ± 0.34a	8.2 ± 0.15a	
Flavour and taste	8.5 ± 0.28a	8.2 ± 0.20a	
Overall Acceptability	8.48 ± 0.27a	8.3 ± 0.21a	


	
Texture analyser	
Hardness (g)	1516.87 ± 97.2b	1982.89 ± 148.32a	
Adhesiveness (g sec)	−13.66 ± 1.36b	−24.37 ± 2.13a	
Springiness	0.293 ± 0.02a	0.312 ± 0.05a	
Cohesiveness	0.123 ± 0.006a	0.144 ± 0.005a	
Note: The values are presented as mean ± standard deviation, based on three samples (n = 3). Significant differences at the p ≤ 0.05 level are indicated by different superscripts (a,b) within each column.

3.2 Micro-structure of the Peda

The microstructure analysis with SEM reveals that extended heat treatment in control Peda (Fig. 2a) caused the formation of complexes between casein and whey proteins that have undergone amalgamation with lactose and add sugar leading to thick protein bridges. Similar finding was also reported by Mehta, 2018. Commercially available plain Peda (control sample) showed large clusters of lactose crystals and increased void space may be due to non-uniform kneading processes during production (Das et al., 2018). In optimized sample T1 (Fig. 2b), the surface displayed a dense and uneven texture, heavily coated with fat with intergranular spaces filled with milk serum, mucilages, and fat mainly due to addition of FMP in Peda sample.Fig. 2 Illustration of the scanning electron micrographs (a) control Peda sample and (b) optimized Peda sample.

3.3 HR-MS and GC–MS analysis of optimized Peda

The metabolites profile study of optimized Peda represents an effort to perform liquid chromatography coupled with mass spectrometry-based omics for the bioactive compounds analysis in the optimized sample having a 2 % concentration of FMP as its primary constituent. We employed an untargeted approach utilizing an orbitrap mass spectrometer working in DDA acquisition mode with an electrospray ionization (ESI) process in both negative and positive modes. The resulting representative metabolome mass spectrum (Fig. 3) of this functional product revealed a distinctive variation pattern, suggesting differential alignment of metabolites in the various concentrations.Fig. 3 The comprehensive mass spectrum representing all the metabolites identified through HR-MS in the optimized Peda sample.

After completing the mass spectrometry omics analysis for the FMP- Peda, the results disclosed a sum of 1654 differential metabolites, formed from various interactions within the Peda matrix constituents. The representative mass spectrum shows 37 annotated peaks highlighting major metabolites of primary and secondary classifications, out of which 23 important bioactive metabolites are listed in Table 2. Six of which are organic acids, another six are amino acids, three are fatty acids, three are other derivatives of metabolites, two are lipids, two are bioactive substances, while one is a sugar. All these exhibiting diverse physiological functions in the human body including antioxidative, antimicrobial, antidiabetic, anti-inflammatory, anti-cardiovascular, brain activity, neurogenerative, and lipid metabolism roles. The list in Table 2 describes important metabolomic compounds accompanied by their detailed chemical formulas, molecular weights, retention times (RT), total areas covered by the mass spectral peaks and respective functions.Table 2 The major metabolites obtained from the HR-MS metabolomics analysis of the optimized Peda.

Name	Formula	Annot. Delta Mass [ppm]	Calc.
MW	m/z	RT
[min]	Area
(Max)	Compound property	References	
Fatty Acids and Derivatives	
Ethyl eicosapentaenoic acid	C22 H34 O2	−1.62	330.2554	329.248	24.755	2,222,550	Anti-CVD	Saberi et al., 2023	
Hexadecanamide	C16 H33 N O	−0.48	255.2561	256.2634	23.325	916,664,519	Anti-inflammatory, analgesic	Mazzari et al., 1996	
12-methyltridecanoate	C17 H34 O4	0.25	302.2458	285.2425	22.578	462230005.5	Lipid metabolism	Zhang et al., 2019	


	
Sugars	
Trehalose	C12 H22 O11	−2.1	342.1155	341.1082	1.276	14,122,600,563	Antioxidant	Chen et al., 2022	


	
Amino Acids and Derivatives	
D-Pyroglutamic Acid	C5 H7 N O3	1.2	129.0428	130.0501	0.895	463750859.4	Anti-fungal	Ai et al., 2022	
Creatine	C4 H9 N3 O2	1.59	131.0697	132.077	0.876	6,919,735,256	Anti-inflammatory	Cordingley et al., 2022	
Acetyl-L-carnitine	C9 H17 N O4	0.74	203.1159	204.1232	0.882	3,568,630,660	Brain activity	Ferreira and McKenna, 2017	
L-Glutamic acid	C5 H9 N O4	1.16	147.0533	148.0606	0.895	1,226,252,520	Brain activity	Coyle et al., 2002	
1-Stearoylglycerol	C21 H42 O4	0.56	358.3085	341.3052	24.47	375541062.3	Lipid metabolism	Mondul et al., 2014	
1-Oleoyl-2-hydroxy
−sn-glycero-3-PE	C23 H46 N O7 P	−1.12	479.3007	478.2934	23.864	332356025.7	Brain activity	Castilla-Ortega et al., 2014	


	
Organic Acids	
2-Furoic acid	C5 H4 O3	−2.26	112.0158	111.0085	0.918	1,662,984,851	Antioxidant	Zahirović et al., 2023	
Acetyl-β-methylcholine	C8 H17 N O2	1.08	159.1261	160.1334	0.896	464884416.7	Brain activity	Uutela et al., 2005	
Trans-Aconitic acid	C6 H6 O6	−0.37	174.0164	173.0091	0.877	440591315.2	Antioxidant	Piang-Siong et al., 2017	
Indole-3-carboxilic acid	C9 H7 N O5	−1.05	241.0042	239.997	6.873	404,777,580	Anti-inflammatory	Solanki et al., 2020	
Hippuric acid	C9 H9 N O3	0.51	179.0583	180.0656	5.195	436241230.9	Anti-bacterial	De Simone et al., 2021	
Orotic acid	C5 H4 N2 O4	−0.51	156.017	155.0098	0.918	336798390.2	Antioxidant	Hassani et al., 2019	


	
Lipids	
Sphinganine	C18 H39 N O2	0.82	301.2983	302.3056	17.008	10,544
184,010	Anti-aging	Wang et al., 2024	
1-palmitoyl-2-oleoyl-sn-glycero-3
−phosphocholine	C42 H82 N O8 P	0.64	759.5783	760.5856	24.252	386748300.8	Brain activity	Fogarty et al., 2015	


	
Bioactive Components	
Methyl picolinate	C7 H7 N O2	1.17	137.0478	138.0551	1.092	846,701,305	Antidiabetic	Sanna et al.,2014	
Palmitoyl Serinol	C19 H39 N O3	0.62	329.2932	330.3005	19.293	502,451,199	Anti-inflammatory	Seo et al., 2022	


	
Other Metabolites	
Betaine	C5H11 N O2	1.33	117.0791	118.0864	1.009	3,048,259,345	Anti-inflammatory	Zhao et al., 2018	
Adenosine	C10 H13 N5 O4	0.59	267.0969	268.1042	2.783	334064899.8	Brain activity	Boison, 2009	
D-Pyroglutamic Acid	C5 H7 N O3	1.2	129.0428	130.0501	0.895	463750859.4	Anti-fungal	Ai et al., 2022	
RT: Retention Time: CVD: Cardiovascular disease; Calc. MW: Calculated molecular weight; m/z: mass/charge.

This prior work (Zhao et al., 2019) publish study focus on flaxseed metabolomics where they identified physiologically significant metabolites including alkaloids and polyphenol compounds. Ethyl eicosapentaenoic acid which are important fatty acid was discovered by research on stirred yogurt manufactured using co‐microencapsulated flaxseed oil as a bioactive ingredient (Saberi et al., 2023). Among the observed major metabolites, few phospholipid derivatives such as 1-oleoyl-2-hydroxy-sn-glycero-3-PE and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine are an essential component of cell membranes which can affect neuronal signaling and communication (Castilla-Ortega et al., 2014, Fogarty et al., 2015). Other metabolites also present such as adenosine, acetyl-β-methyl choline, acetyl-L-carnitine, and L-glutamic acid, which regulate neurotransmitter release and neuronal activity (Boison, 2009, Uutela et al., 2005, Ferreira and McKenna, 2017, Coyle et al., 2002). Hippuric acid (possible detection method for COVID-19) is shown in the product due to the conjugation of benzoic acid, glycine and has antibacterial properties (De Simone et al., 2021). Presence of acetyl-L-carnitine in the optimized sample was found which is known as a biomarker of cyanocobalamin deficiency. The metabolite present in sample like orotic acid (Hassani et al., 2019), trans-aconitic acid (Piang-Siong et al., 2017), 2-furoic acid (Zahirović et al., 2023), trehalose (Chen et al., 2022) exert their antioxidant effects through various mechanisms including scavenging free radicals, enhancing antioxidant enzyme activity and reducing oxidative stress. As a result, they play a crucial role in protecting cells and tissues from damage induced by reactive oxygen species (ROS).

Presence of some bioactive compounds also found which have including indole-3-carboxylic acid (Solanki et al., 2020), palmitoyl serinol (Seo et al., 2022), hexadecanamide (Mazzari et al., 1996), betaine (Zhao et al., 2018) and creatine (Cordingley et al., 2022) ameliorates the action of controlling the inflammatory discomfort.

The FMP-incorporated Peda contains few metabolites present in its metabolome such as D-Pyroglutamic acid which have antifungal activity potential (Ai et al., 2022), that implies this developed Peda is attributing the overall functionality. Additionally. Sphinganine, which is a bioactive compound, is reported to have properties with anti-aging effects (Wang et al., 2024).

The compounds such as 1-stearoyl glycerol, 1–2-methyl tri decanoate, and betaine participate or regulate in lipid metabolism by serving as substrates or intermediates in lipid synthesis or breakdown pathways (Mondul et al., 2014, Yang et al., 2022, Zhang et al., 2019).

During the GC–MS-equipped metabolomics of the FMP-incorporated Peda (Fig. 4), the alignment revealed 92 annotated peaks by the end of the database search (Supplementary Table 1).Fig. 4 The obtained mass spectrum of the qualitatively fatty acid identification during GC–MS analysis of the optimized Peda.

Notably, six significant key fatty acids were identified, showing homology with the NIST library, as listed in Table 3. The application of GC–MS also revealed the presence of key bioactive compounds with broad-spectrum functionality, such as methyl alpha-D-glucopyranoside, which showed a high area percentage in the functional dairy product. This compound may result from the breakdown of carbohydrates present in FM (Mani et al., 2011) contributing to the overall sweetness of the product.Table 3 Major Fatty Acids Identified by GC–MS in Optimized Peda Incorporated with Flaxseed Meal Powder.

Peak	RT	Area	Area%	Name	
22	10.501	1,859,413	1.08	3,6,9,13,16-Pentaoxa-2,17-disilaoctadecane (tetracosanoic polyunsaturated fatty acid)	
33	12.538	12,595,757	7.29	Methyl alpha-D-Glucopyranoside	
60	18.262	842,450	0.49	Palmitic Acid	
68	18.829	318,010	4.47	9-Octadecenoic acid, (Linoleic acid)	
69	20.059	898,773	0.52	Stearic acid	
89	30.533	15,138,537	8.76	Methyl 2-hydroxytetracosanoate (hydroxylated fatty acid)	

In the optimized Peda, fatty acids such as palmitic acid (0.49 %), and stearic acid (0.52 %) exhibit relatively low area percentages, suggesting a moderate presence of these saturated acids compared to the control Peda. Additionally, 9-octadecenoic acid (4.47 %) and methyl 2-hydroxytetracosanoate (8.76 %) exhibit relatively high area percentages, indicating potential benefits for cardiovascular health (Zhang et al., 2023) from the FMP-added Peda. Specifically, the presence of 9-octadecenoic acid, a monounsaturated fat, is known for its positive impact on heart health.

Moreover, the identification of 3,6,9,13,16-Pentaoxa-2,17-disilaoctadecane, a tetracosanoic polyunsaturated fatty acid, although at a lower percentage (1.08 %), suggests its role in the nutritional enhancement of the Peda. The broad range of these fatty acids and their varying percentages highlight the nutritional richness and potential health benefits of the optimized Peda.

This work confirms the great importance of food chemistry and the other applied sciences due to their various applications in different fields as shown in a lot of papers published before (Al-Kamali et al., 2014, El Bakri et al., 2023, Mohamed et al., 2022).

4 Conclusion

This innovative approach holds substantial potential for creating a functional dairy product with a plant-based source. The incorporation of flaxseed meal powder in the development of Peda has resulted in a significant difference related to the physico-chemical and characteristics of the FMP-added Peda. The optimized Peda exhibited significantly lower levels moisture and water activity but at the same time higher fat, protein, dietary fibre, total solid and antioxidant levels as compared to the control Peda. This study also identified major bioactive compounds and fatty acid identification using HR-MS and GC–MS in the optimized Peda. The presence of 23 bioactive compounds having brain activity promotion, antioxidant, anti-diabetic, anti-inflammatory, cardiovascular-protective effects, etc. were the major metabolites in the HR-MS probe. The identification of 9-octadecenoic acid by GC–MS (linoleic acid) suggests potential cardiovascular health benefits in the optimized Peda. The optimized FMP-incorporated Peda can be a functional dairy food highlighted the nutritional richness and potential health benefits of the optimized Peda.

Funding

No funding was received.

CRediT authorship contribution statement

Sachin Maurya: Writing – original draft, Validation, Investigation, Formal analysis, Conceptualization. Tarun Verma: Validation, Supervision, Project administration, Methodology. Ankur Aggarwal: Writing – review & editing. Manish Kumar Singh: Writing – review & editing. Abhishek Dutt Tripathi: Writing – review & editing. Ankur Trivedi: Writing – review & editing.

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.

Appendix A Supplementary data

The following are the Supplementary data to this article:Supplementary Data 1

Data availability

Data will be made available on request.

Acknowledgments

We acknowledge Banaras Hindu University for their kind support and facilities provided. Sincere thanks are extended to Institution of Eminence (IoE) Scheme, Banaras Hindu University, Varanasi (UP) India for support under Incentive to Seed Grant under IoE Scheme (Devt scheme no. 6031 and PFMS scheme no. 3254), Sponsored Research & Industrial Consultancy Cell (SRICC), IoE, BHU and grateful is also extended to HRAMS Lab, DST-SATHI, Banaras Hindu University, for the HRAMS facility.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.fochms.2024.100217.
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