Comparative Physicochemical and Mineral Profiling of Multifloral Honeys from Apis mellifera in Himachal Pradesh, India: Implications for Export and GI Tagging

Comparative Physicochemical and Mineral Profiling of Multifloral Honeys from Apis mellifera in Himachal Pradesh, India: Implications for Export and GI Tagging | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Comparative Physicochemical and Mineral Profiling of Multifloral Honeys from Apis mellifera in Himachal Pradesh, India: Implications for Export and GI Tagging Rohini Sharma Sharma, Meena Thakur meena, Sunita Devi sunita This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9222304/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract This study examined the physicochemical, mineral, and bacterial profiles of multifloral honeys from Apis mellifera L. collected from different agro-climatic zones in Himachal Pradesh, India. Out of all honey samples, twenty-six honeys were identified as multifloral honeys through melissopalynological studies. The physicochemical parameters varied among all the multifloral honeys with an average results for pollen density (42,000–5,45,000 pollen grains per 10g), pH (3.97–5.96), Electrical conductivity (0.13-0.74mS/cm), moisture content (14.34–20.13%), optical density (0.12, Extra White − 2.41, Amber), density (1.35-1.61g/cm3), glucose (25.23–37.06%), fructose (31.7-40.66%), sucrose (2.74–5.78%), F:G (0.93–1.5), acidity (17.40-49.36meq/kg), vitamin C (7.67-38.49mg/100g), ash (0.02–0.42%), hydroxy methyl furfural (HMF) (6.59-86 mg/kg), diastase (4.53-30.48DN), phenol (12.96-108.54mg/100g), proline (18.19-113.98mg/100g) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) (16.49–78.84%) content. The various minerals, viz., calcium, magnesium, phosphorus, potassium, zinc, sodium, iron, and manganese, were detected. No significant signs of adulteration were detected, and all multifloral honey samples met the FSSAI safety standards, confirming their purity and adherence to proper storage practices. Further, principal component analysis (PCA) and hierarchical cluster analysis (HCA) suggested that the quality parameters varied among multifloral honeys based on origin, and the studied area harboured rich floral diversity that facilitates the production of unique multifloral honeys that can be attributed as geographical indications (GI) specific to the region. Biological sciences/Biochemistry Earth and environmental sciences/Environmental sciences Biological sciences/Plant sciences Apis mellifera Beekeeping Melissopalynology Multifloral honey Pollens Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Honey is a complex natural substance produced by honey bees from floral nectar, has long been recognized as a functional food due to its rich composition of carbohydrates, enzymes, organic acids, and bioactive compounds. These constituents contribute to its pharmacological properties, including anti-inflammatory effects, antidiabetic properties, antimicrobial activity, wound healing, and potential anticancer effects (Parihar et al., 2020 ; Devi et al., 2021 ). The physicochemical characteristics of honey are influenced by factors like botanical origin, climatic conditions, and beekeeping practices, which in turn affect its quality and authenticity (Besharati et al., 2025 ; Grassi et al., 2025 ). It is known that based on botanical origin, honeys are categorised into unifloral and multifloral types; unifloral honey contains more than 45 per cent pollen from a single plant species, while multifloral honey comprises less than 45 per cent pollen from various plant species (Sharma et al., 2023 ). Multifloral honeys, due to their diverse floral sources, exhibit a wide range of physicochemical properties and bioactive compounds, contributing to their enhanced medicinal value (Larsen and Ahmed, 2022 ). However, the quality, composition, and nutraceutical characteristics of honey are strongly influenced by altitude, which determines ecological and geographical changes. Additionally, the quality of honey is influenced by microorganisms such as yeast and spore-forming bacteria; however, its natural properties and industry control measures keep microbial levels minimal (Thakur et al., 2024 ). Hence, monitoring honey quality parameters is of great importance to consumers’ health. These analyses are essential for detecting adulteration and ensuring authenticity, as improper processing or contamination can compromise the beneficial properties of honey. The present study was conducted in Himachal Pradesh, located in the northwestern Himalayas at elevations ranging from 350 to 2200 meters above mean sea level, and encompasses a diverse array of agro-climatic zones, each characterised by distinct climatic conditions conducive to the cultivation of varied flora (Thakur et al., 2021 ; Thakur et al., 2022 ). This ecological diversity facilitates the production of both unifloral and multifloral honeys, each exhibiting unique physicochemical properties. The temperate climatic zone of this state fosters the growth of unique plant species, such as Plectranthus and Thyme, which are not commonly found elsewhere in India. For instance, Plectranthus is renowned for producing white honey and possesses high antioxidant properties, whereas Thyme honey is noted for its antimicrobial and antioxidant properties (Sharma et al., 2022 ). The state's diverse flora supports migratory beekeeping practices, ensuring a continuous nectar flow throughout the year and contributing to the development of multifloral honeys. While numerous studies have examined the physicochemical parameters of multifloral honeys in India, there is a lack of research directly comparing the quality of multifloral honey produced by beekeepers in Himachal Pradesh. Therefore, this study is the first of its kind to assess the quality parameters, essential mineral content, and bacterial load of multifloral honey samples from various geographic regions of the northwestern Himalayas and verify their compliance with the Food Safety and Standards Authority of India (FSSAI) standards. The findings aim to provide valuable insights into the authenticity and quality of Himachal Pradesh's multifloral honeys, supporting their potential for Geographical Indication (GI) certification, enhancing market value and guiding beekeepers in conserving and cultivating multipurpose crops that serve as food plants for honey bees. Materials and Methods Study Area The present study was conducted in the state of Himachal Pradesh, situated between 32.1024° N latitude and 77.5619° E longitude. The study area included all four agro-climatic zones of the state, namely Zone-1 (Sub-Mountain and sub-tropical, low hills zone, 350-650m amsl), Zone-2 (Mid hills, sub-humid zone, 651-1840m amsl), Zone-3 (High hills, temperate wet zone, 1801-2200m amsl), and Zone-4 (High hills, temperate dry zone, 2200m amsl & above. Sample Collection A total of 36 Apis mellifera honey samples with three replications (108 samples) were obtained across all four agro-climatic zones of Himachal Pradesh. From each zone, three districts, viz., Hamirpur, Bilaspur, and Una from Zone-1; Kangra, Mandi, and Solan from Zone-2; Shimla, Sirmaur, and Kullu from Zone-3; Chamba, Kinnaur, and Lahaul Spiti from Zone-4 were selected for sample collection. Further, from each district, three apiaries were selected, and from each apiary, three samples were collected and processed further for melissopalynological, physicochemical, and mineral characteristics. Melissopalynological studies Honey samples were prepared for melissopalynological analysis following the procedure described by Louveaux et al., ( 1978 ) and the International Commission on Bee Botany (ICBB) (Von Der Ohe et al., 2004 ). The prepared pollen slides were then observed under a trinocular microscope (OLYMPUS CX41), and the microphotographs were taken by a camera (SONY Model SSC-E413P) attached to the trinocular microscope. Pollen grains were identified based on photomicrographs, shape, size, aperture type, exine surface, and aggregation pattern. To further authenticate their identification, identified pollen slides available in the Department of Entomology, College of Horticulture, Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan, HP, India; ICBB recommendations and standard works done by Erdtman ( 1969 ) and Nair ( 1985 ). For quantitative analysis, identified and counted pollen grains were assigned to different frequency classes viz., predominant pollen types (> 45% pollen count); secondary pollen types (16–45%); minor pollen types (3–15%) and rare pollen types (< 3%) according to the number of pollen grains in each sample (Louveaux et al., 1978 ; Von Der Ohe et al., 2004 ; Ozler 2015 ). Honey was termed as unifloral (if single pollen type of particular plant species > 45%) and multifloral (if several pollen types with less percentage) (Iwama and Melhem 1979 ; Sharma 1989 ). Based on their melissopalynological characteristics, twenty-six honey samples were identified as multifloral honeys (Table 1 ), and the locations from where these multifloral honeys were obtained are presented in Fig. 1 . This study is specifically dedicated to elucidating the physicochemical and mineral characteristics inherent to these specific multifloral honey samples. Physicochemical characteristics The physicochemical characteristics of honey samples were determined using standard analytical procedures. The pH of honey was assessed using a pH meter (EUTECH pH 700) following AOAC ( 2012 ) guidelines. The measurement of honey's electrical conductivity (EC) was conducted utilizing a conductivity meter (Thermo Scientific EUTECH CON 150) as per the method described by Jackson ( 2005 ). Moisture content was estimated by oven-drying approximately 5 g of honey at 103°C until constant weight was achieved (Bogdanov et al.,2004). Optical density was measured at 560 nm using a spectrophotometer without dilution, using distilled water as a blank (Townsend, 1969 ). The density of the honey sample was determined at 27°C according to the BIS (1994) procedures. For sugar determination (glucose, fructose, sucrose), the methods established by ISI, 1974 were used. Acidity and ash content were determined through the titrimetric approach outlined in the AOAC method 962.19 (AOAC, 2000 ). Vitamin C and diastase activity were estimated according to AOAC ( 2004 ), respectively. Hydroxymethylfurfural (HMF) content was determined using Fiehe’s test followed by spectrophotometric measurement at 540 nm as described by Schade et al. ( 1958 ). Total phenolic content was determined using the Folin–Ciocalteu method following Singleton et al. ( 1999 ), while proline content was estimated using standard AOAC ( 1984 ) methods. Antioxidant activity was assessed using the DPPH assay following the method of Isla et al. ( 2011 ). Mineral composition For mineral estimation, honey samples (1 g) were digested using a diacid mixture of nitric acid and perchloric acid (4:1). The concentrations of minerals were determined using standard analytical procedures as described by Jackson ( 1973 ) and Sarma et al. ( 1987 ). Bacterial load Microbial load was determined using the standard plate count method (Wollum, 1982 ). Results were expressed as log CFU g⁻¹ of honey using the formula: Log CFU/g = Log (CFU × dilution factor × 1/aliquot) Principal Component Analysis (PCA) Principal Component Analysis (PCA) was carried out using R software to evaluate the variability among honey samples and to identify the major contributing physicochemical and biochemical parameters. Prior to analysis, data were standardized by centering and scaling. Components with eigenvalues greater than 1 were retained according to the Kaiser criterion, and loading scores (factor loadings) were used to interpret the contribution of individual variables. Table 1 Information on multifloral honey samples from different regions of Himachal Pradesh Agroclimatic Zones Districts Regions Sample Code Zone-1 (Sub-Mountain and sub-tropical, low hills zone) Hamirpur Nadaun S1H Kharwar S2H Barsar S3H Bilaspur Lehri Sarail S4H Bhatoli S5H Berthin S6H Una Bangana S7H Zone-2 (Mid hills, sub-humid zone) Kangra Nurpur S8H Mandi Chachyot S9H Sandhol S10H Solan Arki S11H Kunihar S12H Zone-3 (High hills, temperate wet zone) Shimla Rohru S13H Jubbal S14H Sirmaur Nohradhar S15H Rajgarah S16H Shillai S17H Kullu Kharihar S18H Bajaura S19H Zone-4 (High hills, temperate dry zone) Chamba Lahal S20H Banikhet S21H Bakan S22H Kinnaur Karcham S23H Nichar S24H Lahaul Spiti keylong S25H Gondhla S26H Cluster analysis Hierarchical cluster analysis was performed using a binary presence–absence matrix of pollen types across honey samples. The analysis was conducted in R software, and the results were visualized using heatmaps and dendrograms to assess similarities among samples. Results and Discussion Melissopalynological analysis of honeys Among all the multifloral honey samples, a total of ninety-six pollen morphotypes were obtained. The results of the pollen spectrum, along with their frequency in all the multifloral honeys are provided in supplementary table 1 . All the multifloral honeys contained varied pollen frequencies with maximum frequency for secondary pollen types (16–45%), as they are the major source of pollen grains in these multifloral honeys and influenced the physicochemical property of particular honey. These secondary pollen sources varied in all the multifloral honeys depending upon their availability in a particular region and preference as nectar sources for honey bees. The majority of multifloral honeys belonged to the family Fabaceae, followed by Asteraceae. Harbouring a wide floral diversity of the Fabaceae family in Himachal Pradesh could be the probable reason for dominance in this zone (Rana et al., 2022 ). Findings of the present study corroborated with the findings of other research, for example, Saklani and Mattu (2022), and Ukanyirioha et al., ( 2021 ) reported greater floral diversity from Himachal Pradesh and Nigeria, respectively, with the highest pollen types from the Fabaceae family, followed by Asteraceae. The Zone-1 and Zone-2 of Himachal Pradesh are suitable for beekeeping due to wide diversity and availability of various types of bee flora during the spring-summer seasons (Feb.-April), thus contributing to mixed floral honeys during the spring-summer season. The major flora reported in the present study were Adhatoda sp., Dalbergia sp., Cassia sp., Eucalyptus sp., Syzygium sp., and Albizia sp. The availability of these floras from lower and mid hills as bee forage in the present study is supported by the previous documentation of Verma ( 2006 ), Singh and Sharma ( 2007 ), and Saklani and Mattu ( 2018 ) from Himachal Pradesh. Similarly, Sahney et al., ( 2016 ), Tripathi et al., ( 2017 ) documented these pollen grains from honeys of Varanasi (UP) and Assam, respectively. The Robinia , Aesculus , pome, and stone fruits pollens are found as major flora in Zone-3, as this zone is suitable for beekeeping due to the abundance of autumn honey-flow sources. Song et al., ( 2012 ) also reported predominant pollen grains of Robinia pseudoacacia and Vitex negundo from South China. The Zone-4 is not commercially practised for beekeeping; however, some autumn honey-flow forage plants are found in this region. During autumn, some beekeepers migrate their colonies to these areas to avail honey from different floral sources, viz., Thyme , Plectranthus , and Fagopyrum as Plectranthus known for white honey production provides surplus honey during Sept. – Oct. Nair ( 1964 ) also reported similar findings from the Himalayan region of India, and El Sohaimy et al., ( 2015 ) from Kashmir honey. Physicochemical characteristics Pollen density Pollen density is an important characteristic of honey that helps to detect adulteration and determine its geographical and botanical origin, with raw honey containing more pollens, while adulterated honey has far less than processed honey (Sharma et al., 2023 ). In the present study, the average pollen density varied from 42,000 (4.62) to 5,45,000 pollen grains per 10g (5.74), with a significant difference among the multifloral honeys (Table 2 ). The lowest pollen density was recorded for honey from S2H honey of Zone-1, low hills (42,000 pollen grains/10g), whereas the highest was reported from S10H honey of Zone 2, mid-hills (5,45,000 pollen grains/10g), respectively. The S2H honey contains Citrus sp. and Bauhinia sp. as secondary pollen types, which produce less nectar and thus attract fewer honey bees, resulting in lower pollen counts in the honey (Yao et al., 2006 ). In contrast, S10H honey contains pollens from Bombax sp., Grewia sp., and Syzygium sp. as these plants contained more nectar, thus more attractive to bees, resulting in high pollen count (Djonwangwe et al., 2011 ). Shishira et al., ( 2024 ) also reported high pollen density (99,000 pollens/10g) in Syzygium honey from Bangalore. However, all the studied samples contained pollen grains more than the minimum limit (> 5000/g of honey) of pollen grains per gram of honey set by FSSAI (2020). These findings are in alignment with studies of Shobham and Nayar ( 2017 ), Shukla and Kumar ( 2020 ), and Thakur et al., ( 2021 ), who reported a similar range of pollen density in honey from Telangana, Uttar Pradesh, and Himachal Pradesh, respectively. pH The pH of honey serves as a key indicator of its freshness and stability, affecting its texture, aroma, and shelf life (Hajian-Tilaki, 2014). Honey naturally exhibits acidity, with pH values ranging from about 3.5 to 5.5 due to the presence of organic acids, which contribute not only to its flavour but also its resistance to microbial spoilage (Da Silva, 2016). The pH values in the current study were found to be acidic, ranging from 3.97 to 5.96 (Table 2 ), indicating the freshness of all honeys. However, S3H multifloral honey from Zone-1 had significantly lower pH (3.97), indicating the freshness of the honey sample as compared to S2H multifloral honey (5.96) of a similar zone. The reason could be due to long-term storage of honey or variation in the floral source. As S3H honey with low pH contained Cassia sp. and Albizia sp. as important food sources, as compared to Citrus sp. and Bauhinia sp. as pollen sources in S2H honey. This variation may create pH variation for the same reason, as different floral sources contribute varying amounts of organic acids, minerals, and other compounds that affect the overall acidity (Pasca et al., 2021). Amir et al., ( 2010 ) observed that honey samples with a pH below 4 degrade more rapidly during storage, suggesting that samples exceeding this threshold are comparatively fresher. The pH results are in the range reported by Thakur et al., ( 2021 ) (4.65–5.94), Parihar et al., ( 2020 ) (3.60–4.80) for Himachal honeys, Kumar et al., (2018) (3.81–4.85), and Kamboj et al., ( 2024 ) (4.8–5.8) for North Indian honeys. The variations in honey pH levels can result from factors such as the floral sources of nectar, the salivary secretions of bees, enzymatic processes, and the fermentative conversion of raw materials during honey production. Electrical conductivity (EC) The electrical conductivity (EC) of honey is influenced by its content of inorganic salts, organic acids, proteins, complex sugars, and minerals; higher concentrations of these components result in increased EC (Dobrinas et al., 2022 ). EC is utilised to differentiate between honeydew and blossom honeys, with values exceeding 0.8 mS/cm indicating honeydew honey, and those below 0.8 mS/cm indicating blossom honey (Bogdanov et al., 2007 ). According to the EC values, the present analysed honey samples were blossom honey, as electrical conductivity ranged between 0.13–0.740 mS/cm. The lower EC (0.13mS/cm) was reported in S22H multifloral honey of Zone-4, which is statistically at par with S26H honey (0.14mS/cm) of similar zone and S16H honey (0.14mS/cm) of Zone-3, whereas the highest EC was reported in S2H honey (0.74mS/cm) of Zone-1 (Table 2 ). Zone 4 of Himachal Pradesh, characterized by high-altitude terrain exceeding 2200 meters above mean sea level, supports natural fauna with minimal anthropogenic disturbance and low pollution levels. This pristine environment likely contributes to lower electrical conductivity (EC) values in honey, as EC increases with higher concentrations of inorganic ions, acids, and minerals (Solayman et al., 2016 ). The S22H honey of Zone-4 detected the lowest in EC content. The S2H honey from Zone-1 exhibited the lowest electrical conductivity (EC), likely due to the zone's sub-mountain and sub-tropical low-hill characteristics (350–650 m amsl), which are significantly influenced by urbanization, agricultural activities, and agrochemical use. This aligns with reported EC values for honey from similar regions worldwide (Solayman et al., 2016 ; Thakur et al., 2022 ; Mongi, 2024 ; Yu et al., 2025 ). Moisture content In present study moisture content varied from 14.34–20.13 per cent with highest (20.13%) being recorded from S2H honey of Zone-1, which was statistically at par with S25H honey (20.07%) from Zone-4 and S3H honey (20.00%) of Zone-1, whereas lowest moisture content (14.34%) was recorded from S8H honey of Zone-2 which was statistically at par with S6H honey (14.77%) of Zone 1 (Table 2 ). According to the literature, moisture content plays a crucial role in determining its quality, stability, resistance to yeast fermentation, and tendency to granulate (Dung et al., 2005 ). In the present results, all the honeys had moisture content below the maximum permissible limit of moisture content (> 20%) set by FSSAI (2020), indicating proper maturity, except for S2H honey from Zone-1. The high moisture content in S2H honey may result from extracting unripe or unprocessed honey, harvesting during the rainy season, or fermentation caused by extended storage (Lavinas et al., 2025 ). The moisture content recorded in the present study aligned with the results of Parihar et al., ( 2020 ) and Attri ( 2011 ) in honey from Himachal Pradesh and Gairola et al., ( 2013 ) in honey from Uttarakhand. Optical density (colour) In the present study optical density of honey for different multifloral honeys varied from extra white to amber, with optical density from 0.12–2.41 (OD at 560nm) (Table 2 ). Thus, the highest absorbance (2.41OD, Amber) was recorded from S9H multifloral honey of Zone-2, whereas the lowest (0.12 OD, Extra White) was from S13H honey of Zone-3. The variation in optical density could be due to variation in floral sources; S9H honey contained Sapindus sp., Dalbergia sp. and Trifolium sp. as secondary pollen types, whereas S13H honey contained Malus × domestica and Medicago denticulateas secondary pollen types. The dark colour of S9H honey may be attributed to its pollen sources and high mineral content (Sharma et al., 2023 ) as well as darkening caused by heating (Ramly et al., 2021 ). The results of Escriche et al., ( 2017 ) also reported amber colour in Thyme honey from Spain, thus supporting the present results. The observations support the findings of Nayik and Nanda ( 2015 ) and Albu et al., ( 2023 ), where significant differences were observed in the optical densities of different multifloral honeys from Kashmir and Romania, respectively. Density The density of multifloral honeys in the present study varied from 1.35 to 1.61g/cm3, where the lowest density is recorded from S3H multifloral honey of Zone-1, though statistically at par with S4H honey of Zone-1, S8H and S11H honey of Zone-2, S13H and S16H honey of Zone-3, and S22H honey of Zone-4 (Table 2 ). Highest density was recorded from S20H honey of Zone-2, which was statistically at par with S2H honey of Zone-1, S9H honey of Zone-1, S17H and S18H honey of Zone-3, and S25H honey of Zone-4. The density is an important property of honey and is also used as a purity test by consumers at home (Testa et al., 2019 ). The observed variations in density among different multifloral honeys may be attributed to differences in floral sources, chemical composition, moisture content, and the temperature conditions during processing and storage (Parihar et al., 2020 ). However, the density of the present honey samples was within the range given by FSSAI (2020) (1.35g/cm3) and aligned with the results of Ahmed et al., ( 2007 ), who reported density in different multifloral honeys in the range from 1.33-1.56g/cm3 in different multifloral honeys from Karnataka. Table 2 Physical characteristics of multifloral honey samples from different regions of Himachal Pradesh S. No. Samples Regions Zones Pollen density (pollen grains per 10g) pH EC (mS/ cm) Moisture (%) Optical Density (OD at 560nm) Colour as per USDA colour standard Density (g/cm 3 ) 1 S1H Hamirpur Zone-1 80,000 (4.90) 4.92 0.69 15.46 0.46 Extra Light Amber 1.45 2 S2H 42,000 (4.62) 5.96 0.74 20.13 0.35 White 1.56 3 S3H 60,000 (4.78) 3.97 0.66 20.00 1.91 Amber 1.35 4 S4H Bilaspur 71,000 (4.85) 4.51 0.43 19.09 0.43 Extra Light Amber 1.36 5 S5H 1,24,000 (5.09) 5.34 0.68 18.61 0.18 Extra White 1.46 6 S6H 66,000 (4.82) 4.52 0.45 14.77 0.33 White 1.43 7 S7H Una 2,30,000 (5.36) 4.72 0.38 19.15 0.99 Light Amber 1.47 8 S8H Kangra Zone-2 1,80,000 (5.26) 4.74 0.37 14.34 0.32 White 1.42 9 S9H Mandi 82,000 (4.91) 5.76 0.20 16.09 2.41 Amber 1.60 10 S10H 5,45,000 (5.74) 4.55 0.51 15.48 0.16 Extra White 1.61 11 S11H Solan 48,000 (4.68) 4.54 0.29 19.37 0.20 White 1.39 12 S12H 1,95,000 (5.29) 5.03 0.38 15.62 0.61 Light Amber 1.41 13 S13H Shimla Zone-3 2,15,000 (5.33) 4.17 0.16 17.48 0.12 Extra White 1.44 14 S14H 4,10,000 (5.61) 4.77 0.17 16.30 0.17 Extra White 1.41 15 S15H Sirmaur 3,30,000 (5.52) 4.16 0.30 16.28 0.39 Extra Light Amber 1.51 16 S16H 1,00,000 (5.00) 3.97 0.14 16.35 0.19 Extra White 1.42 17 S17H 2,60,000 (5.41) 4.61 0.23 16.62 0.55 Extra Light Amber 1.57 18 S18H Kullu 50,000 (4.70) 4.45 0.55 16.78 0.38 Extra Light Amber 1.58 19 S19H 65,000 (4.81) 4.57 0.40 16.82 1.36 Light Amber 1.47 20 S20H Chamba Zone-4 77,000 (4.89) 4.15 0.65 16.04 0.18 Extra White 1.49 21 S21H 1,30,000 (5.11) 4.85 0.37 16.26 0.25 White 1.45 22 S22H 65,000 (4.81) 4.35 0.13 15.41 0.52 Extra Light Amber 1.40 23 S23H Kinnaur 2,20,000 (5.34) 5.33 0.47 15.97 0.38 Extra Light Amber 1.44 24 S24H 1,20,000 (5.08) 4.94 0.39 15.20 0.41 Extra Light Amber 1.48 25 S25H Lahaul Spiti 75,000 (4.88) 5.40 0.28 20.07 0.57 Extra Light Amber 1.59 26 S26H 58,000 (4.76) 4.86 0.14 16.61 0.41 Extra Light Amber 1.46 CD (0.05) 0.22 0.2 0.018 0.633 0.02 0.07 Sugars The honey comprises mainly fructose and glucose (monosaccharides), and additionally comprises around 25 different oligosaccharides (Bogdanov, 2004). In the present investigation, the sugars, viz., glucose, fructose, and sucrose, content in different multifloral honeys varied from 25.23–37.06 per cent, 31.7-40.66 per cent, and 2.74–5.78 per cent, respectively (Table 3 ). The S24H honey of Zone-4 has the highest glucose content (37.06%), whereas the lowest glucose content was observed in S12H honey from Zone-2 (25.23%). Among all multifloral honeys, the highest fructose content was recorded in S25H honey (40.66%) from Zone-4, whereas the lowest fructose content was found in S15H honey (31.7%) from Zone-3. In terms of sucrose content, S3H of Zone-1 had the highest sucrose content (5.78%), which was statistically at par with S24H (5.65%) honey from Zone-4, whereas the lowest was recorded from S25H (2.74%) honey from Zone-4, which differed non-significantly from other multifloral honeys. Significant differences in the sugar composition of honey can arise from its botanical and geographical origins, as well as from climatic conditions, processing methods, and storage practices (Kamboj et al., 2013 ). All the honeys had sugar content within permissible limit except for samples S3H and S24H both had high sucrose content (> 5%), reasons of high sucrose content in these honeys may be due to feeding of honeybees with sugar syrup, harvesting of unripe honey and overheating of honey as earlier reported by Kamal et al., ( 2019 ) and Parihar et al., ( 2020 ) from honeys of A. mellifera from Bangladesh and Himachal Pradesh, respectively. Honey crystallization can be assessed by examining the glucose-to-fructose ratio, as crystallization is associated with increased glucose and decreased fructose levels (Abselami et al., 2018 ). F: G ratio varied from 0.93–1.5 in different multifloral honeys, with the highest F: G ratio (1.5) reported in S25H honey of Zone-4 and S13H (1.5) honey from Zone-3, whereas the lowest F:G ratio was reported in S15H honey (0.93) of Zone-3 (Table 4 ). Honey crystallisation is faster when the F:G ratio is below 1.0, and it slows when this ratio is more than 1.0 (Ouchemoukh et al., 2007 ; Buba et al., 2013 , and Draiaia et al., 2015 ). Thus, most of the analyzed honey samples in the present study were of slow slow-crystallizing nature. The present study is supported by Kamboj et al., ( 2013 ), Thakur et al., ( 2021 ), who observed an F:G ratio within the range of (0.95–1.50) for the honey in the North Indian states of India. El Sohaimy et al., ( 2015 reported F: G ratio 0.42, 1.52, 1.63, and 2.35for Kashmiri, Yemeni, Egyptian, and Saudi honey, respectively, aligned with the present results. The variations in sugar content among different multifloral honeys may result from regional, seasonal, and floral differences, as well as extraction methods, while differences in the fructose–glucose ratio could be influenced by the type of nectar and the location of honey collection. Acidity Acidity influences honey’s flavour, microbial stability, chemical reactivity, and its antibacterial and antioxidant properties (Rani and Verma, 2025 ). Elevated acidity indicates sugar fermentation leading to organic acid formation (Chidi et al., 2018 ), whereas low acidity reflects the freshness of honey samples (Adenekan et al., 2010 ). The acidity of the analyzed honeys varied from 17.40-49.36meq/kg (Table 3 ). Among all the honeys, the highest acidity was recorded in S16H (49.36meq/kg) honey from Zone-2 which was statistically at par with S3H honey (48.59meq/kg), whereas the lowest was recorded in S2H honey (17.40meq/kg) of Zone-1, which was statistically at par with S25H honey of Zone-4 (19.65meq/kg) (Table 4 ). All the multifloral samples were below the maximum permissible limit of total acidity in honey samples (> 50meq/kg), indicating the freshness of all the honey samples. The floral sources for S2H honey were Citrus sp. and Bauhinia sp., which were responsible for lower acidity as reported earlier by Karabagias et al., ( 2017 ) reported 12.64-21.61meq/kg in different citrus honeys from different Mediterranean countries. Vitamin C Vitamin C is present in nearly all types of honey, with its concentration and antioxidant activity largely influenced by the floral source, since most foraged flowers contain vitamin C; other factors affecting vitamin content include honey processing and storage (Perna et al., 2013 ; Silva et al., 2016 ). In the present study, the vitamin C content varied from 7.67 to 38.49 mg/100 g (Table 3 ). The S12H honey of Zone-2 had the highest vitamin C content of 38.49 mg/100 g, whereas the lowest was recorded in S19H (7.67mg/100g) honey of Zone- Table 3 Chemical characteristics of multifloral honey samples from different regions of Himachal Pradesh S. No. Samples Regions Zones Glucose (%) Fructose (%) Sucrose (%) F: G Total Acidity (meq/kg) Vit.C (mg/100g) Ash Content (%) Fiehe’s Test HMF (mg/kg) Enzymes (Diastase /DN) Phenol content (mg/100g) Amino Acid (mg/100g) DPPH (%) 1 S1H Hamirpur Zone-1 31.84 34.06 4.01 1.07 32.55 27.44 0.34 -ve 13.92 21.40 76.39 57.81 65.51 2 S2H 30.27 37.17 3.24 1.23 17.40 26.37 0.42 -ve 18.91 20.67 52.75 46.52 50.07 3 S3H 31.68 35.08 5.78 1.11 48.59 30.85 0.30 +ve 86.00 04.53 97.21 73.41 70.36 4 S4H Bilaspur 32.34 36.12 4.61 1.12 37.57 12.55 0.14 -ve 36.50 15.44 70.39 25.88 61.75 5 S5H 31.05 36.30 5.26 1.17 20.48 14.61 0.33 -ve 25.20 19.31 25.16 31.69 32.76 6 S6H 28.85 34.54 4.31 1.20 36.67 11.54 0.20 -ve 23.25 19.47 37.82 69.36 45.59 7 S7H Una 33.12 34.46 4.07 1.04 34.43 26.79 0.12 -ve 34.75 17.47 82.72 21.12 66.24 8 S8H Kangra Zone-2 30.91 34.29 4.23 1.09 34.43 26.98 0.11 -ve 40.95 14.68 56.16 55.74 51.42 9 S9H Mandi 33.18 33.17 3.98 1.01 23.62 15.55 0.02 -ve 32.40 15.32 108.54 51.14 78.84 10 S10H 28.22 34.09 4.23 1.20 37.48 11.48 0.25 -ve 37.25 18.69 18.61 31.79 19.81 11 S11H Solan 30.74 35.19 3.00 1.16 37.19 23.29 0.07 -ve 7.50 23.41 24.99 18.19 31.07 12 S12H 25.23 36.23 4.38 1.44 25.80 38.49 0.17 -ve 32.78 18.48 70.07 53.41 60.61 13 S13H Shimla Zone-3 25.44 38.23 4.80 1.50 41.13 27.49 0.06 -ve 15.99 20.40 12.96 32.28 16.49 14 S14H 27.02 37.17 3.68 1.38 34.43 26.22 0.02 -ve 13.25 19.35 24.82 38.36 26.99 15 S15H Sirmaur 31.70 31.70 3.74 0.93 41.43 16.59 0.14 -ve 11.59 21.50 37.75 40.98 39.09 16 S16H 27.92 32.19 4.51 1.15 49.36 19.50 0.08 -ve 27.30 16.62 28.14 113.98 34.07 17 S17H 32.89 32.38 3.65 0.98 35.52 25.18 0.18 -ve 23.29 16.76 58.28 103.0 56.06 18 S18H Kullu 34.19 33.16 4.66 0.97 37.56 11.55 0.27 -ve 26.59 14.52 45.37 49.86 49.99 19 S19H 36.07 35.70 4.36 0.99 36.52 07.67 0.18 -ve 19.09 18.66 45.13 19.93 49.19 20 S20H Chamba Zone-4 29.58 36.48 3.73 1.23 41.38 22.71 0.36 -ve 30.24 19.51 24.95 33.26 29.14 21 S21H 33.33 36.42 5.07 1.09 33.40 26.57 0.13 -ve 29.92 18.23 38.64 41.93 46.66 22 S22H 31.84 32.91 3.36 1.03 38.74 25.66 0.06 -ve 9.75 28.29 85.90 45.48 66.95 23 S23H Kinnaur 31.09 34.15 4.96 1.10 20.28 18.75 0.18 -ve 25.59 21.56 57.16 83.74 54.46 24 S24H 37.06 35.27 5.65 0.95 31.57 22.50 0.13 -ve 29.00 21.43 57.72 57.24 54.48 25 S25H Lahaul Spiti 27.17 40.66 2.74 1.50 19.65 21.50 0.20 -ve 22.34 29.79 90.05 85.05 68.69 26 S26H 29.55 39.37 3.72 1.33 33.54 19.43 0.07 -ve 6.59 30.48 73.93 62.64 62.97 CD (0.05) 1.27 1.23 0.21 0.05 1.67 0.88 0.01 0.96 0.9 2.95 2.09 2.23 Table 4 Mineral composition of multifloral honey samples from different regions of Himachal Pradesh S. No. Samples Regions Zones Ca (mg/kg) Mg (mg/kg) P (mg/kg) K (mg/kg) Zn (mg/kg) Na (mg/kg) Fe (mg/kg) Mn (mg/kg) 1 S1H Hamirpur Zone-1 129.30 68.11 13.00 348.70 7.10 119.00 5.07 3.80 2 S2H 112.40 89.20 119.00 546.94 7.70 135.00 4.99 2.00 3 S3H 79.48 64.28 17.00 194.99 5.10 204.00 5.73 1.50 4 S4H Bilaspur 99.68 51.29 91.00 210.94 4.80 186.00 4.32 0.50 5 S5H 148.26 71.02 22.50 794.96 8.50 212.00 4.63 1.50 6 S6H 133.05 69.20 87.00 476.14 7.30 121.00 5.96 1.90 7 S7H Una 98.26 51.21 50.00 286.94 6.80 129.00 5.42 2.70 8 S8H Kangra Zone-2 104.26 40.62 71.50 403.94 7.30 121.00 4.70 2.60 9 S9H Mandi 183.20 32.05 31.50 536.24 6.50 156.00 4.66 0.90 10 S10H 94.26 74.17 30.50 499.20 24.20 138.00 4.57 0.50 11 S11H Solan 98.26 39.21 104.00 882.26 6.50 139.00 4.98 1.50 12 S12H 193.98 49.67 18.00 458.40 8.20 208.00 3.94 3.20 13 S13H Shimla Zone-3 103.36 50.13 7.00 343.92 6.50 116.00 5.08 0.80 14 S14H 112.48 61.11 20.10 522.19 7.30 130.00 5.54 2.60 15 S15H Sirmaur 85.06 69.90 33.10 870.73 5.50 133.00 5.91 2.80 16 S16H 99.53 46.05 19.50 670.70 7.60 136.00 6.08 2.20 17 S17H 143.96 38.91 59.50 800.24 7.30 189.00 4.62 3.50 18 S18H Kullu 182.24 44.99 27.50 894.24 5.20 166.00 4.91 4.70 19 S19H 89.12 48.16 30.00 199.20 8.20 120.00 3.90 2.40 20 S20H Chamba Zone-4 189.50 50.24 13.90 882.34 6.60 122.00 5.02 1.80 21 S21H 93.20 31.68 26.00 734.46 5.50 178.00 3.80 1.60 22 S22H 98.06 27.24 2.50 780.29 9.60 166.00 4.07 1.90 23 S23H Kinnaur 140.30 59.25 56.50 542.32 5.60 120.00 2.91 2.50 24 S24H 99.26 42.10 48.00 346.98 6.40 141.00 5.28 0.50 25 S25H Lahaul Spiti 134.21 63.06 10.00 594.66 8.30 151.00 4.16 2.90 26 S26H 95.43 22.44 11.90 933.24 6.60 131.00 4.85 2.30 CD (0.05) 1.90 1.96 24.11 5.79 0.41 6.36 0.21 0.11 3. The floral sources for S12H honey were Bauhinia sp., Lonicera sp., and Jacaranda sp ., whereas for S19H honey, the floral sources were Sapindus sp., Brassica sp., and Trifolium sp. Various studies by Ahmed et al., ( 2012 ), Naz et al., ( 2020 ), and Orsavova et al., (2022) reported Bauhinia , Jacaranda , and Lonicera plants as a high source of vitamin C, respectively; thus, these trees produce honey that has more vitamin content. Ash content The ash content in honey is generally small and depends on the nectar composition of predominant plants in their formation (Felsner et al., 2004 ). In the present study, ash content varied from 0.02–0.42 per cent, with the highest being recoded from S2H honey (0.42%) of Zone-1, whereas the lowest was from S9H (0.02%) and S14H (0.02%), from Zone-2 and 3, respectively (Table 3 ). The floral sources for S2H honey were Citrus sp. and Bauhinia sp., and for S9H honey were Sapindus sp., Dalbergia sp. and Trifolium sp., and for S14H honey were Prunus sp. and Trifolium sp. The soil type in which the original nectar-bearing plant was located also influences the quantity of minerals present in the ash (Da Silva et al., 2016 ). Felsner et al., ( 2004 ) and Nanda et al., ( 2009 ) also reported high Ash content for citrus honey from Brazil and Punjab, respectively. There was also a linear relationship between the ash content and the EC (El Sohaimy et al., 2015 ), which supports our results as S2H honey had also the highest EC content (0.74mS/cm), indicating good quality of Himachal multifloral honeys. 3.2.11 Hydroxy methyl furfuraldehyde HMF levels in honey serve as an indicator of excessive heating, prolonged storage, or adulteration with invert sugars (Godoy et al., 2022 ), with higher HMF content reflecting lower honey quality (Parihar et al., 2020 ). In the present analysis, HMF content varied from 6.59-86 mg/kg (Table 3 ), S3H honey of Zone-1 was recorded with the highest HMF content (86mg/kg), which was also reported positive in Fiehe’s test, whereas the lowest HMF content (6.59mg/kg) was reported from S36H honey of Zone-4. According to the results, the examined honey samples, except S3H honey, were within the legal permissible limit (> 80mg/kg) of FSSAI (2020). The reason of very high HMF of this sample is due to various reasons, viz., adulteration with sugar additives, severe heat treatment, and inadequate and prolonged storage (Choudhary et al., 2021 ). Iftikhar et al., ( 2011 ) and Afshari et al., ( 2022 ) also reported very high HMF from honey samples of Pakistan and Iran, respectively, indicating low quality of these honeys. Enzymes (Diastase/DN) The diastase content of all the analysed multifloral honeys in the current study varied from 4.53 to 30.48 DN (Table 3 ). The S26H Honey of Zone-4 was recorded with the highest diastase content (30.48 DN), though statistically at par with S25H honey (29.79 DN) of Zone-4, whereas the lowest diastase content was reported in S3H honey (4.53 DN) of Zone-1. The floral sources for S26H honey were Plectranthus sp., Nigella sp., and Fagopyrum sp., for S25H honey were Fagopyrum sp. and Plectranthus sp., whereas for S3H honey were Cassia sp. and Albizia sp. Diastase (alpha and beta amylase) is one of the predominant enzymes in honey, which is added to honey by the bee during the collection and ripening of flower nectar (Sharma et al., 2022 ). Variations in present results could be due to different floral sources, overheating, and long storage, as effects of these factors are already reported by Buba et al., ( 2013 ), Thakur et al., ( 2021 ), and Sireli et al., (2025). However, all the honeys had diastase above the minimum permissible limit fixed by FSSAI (2020), indicating the freshness of all the honey samples. Phenol content The phenolic compounds play a major role in the antioxidant activity, which depends on the species of plant from which bees collected the nectar (Yayinie et al., 2022 ). In the present study, phenol content varied from 12.96 to 108.54 mg/100 g (Table 3 ). The highest phenol content was recorded in S9H honey (108.54mg/100g) from Zone-2, whereas the lowest was in S13H honey (12.96mg/100g) of Zone-3. Floral sources for S9H honey were Sapindus sp. Dalbergia sp. and Trifolium sp., whereas for S13H honey, they were Malus × domestica and Medicago denticulate . Oroian and Ropciuc ( 2017 mentioned in their study that phenolic compounds play a major role in the antioxidant activity, and their content depends on the species of plant from which bees collected the nectar. The phenol content variations recorded in the present multifloral honeys supported by the findings of Pham et al., (2020) and Ikegbunam et al., ( 2025 ) reported phenol content from 89-110mg/100g and 3.75-90.12mg/100g from different multifloral honeys of Vietnam and Nigeria, respectively. In contrast, Yayinie et al., ( 2022 ) reported very low phenol content from 17.03-42.04mg/100g from different honeys of Ethiopia, thus stating that Himachal Pradesh honey had high phenol content, making it a good antioxidant source (Sharma et al., 2023 ). Amino acid (proline) content Amino acid content in present study varied from 18.19-113.98 mg/100g (Table 3 ), with highest being recorded in S16H honey (113.98mg/100g) of Zone-3, whereas lowest amino acid was reported in S11H honey (18.19mg/100g) of Zone-2 which was statistically at par with S19H honey (19.93mg/100g) of Zone-3. The floral sources for S16H honey were Prunus persica and Trifolium sp., whereas for S11H honey were Albizia sp., Woodfordia sp., and Jacaranda sp. Pollen represents the main source of proteins; therefore, the amino acid profile of honey could be characteristic of its botanical origin and geographical origins. Proline, the predominant amino acid in honey, accounting for 50–80 per cent of total amino acids (Sharma et al., 2022 ), is produced by honeybee salivary secretions during nectar conversion. Its levels gradually decline during storage, making proline a potential indicator of honey ripeness. Thus, the proline content varied among all the honeys, but all are within the permissible limit of FSSAI (Minimum content 180mg/kg of honey). Present values for proline content aligned with results of Tarapatskyy et al., ( 2021 ) reported proline (184.44–277.52 mg/100g) from Polish honey, Bouhlali et al., ( 2019 ) (441-1207mg/kg) from Moroccan honey, and Thakur et al., ( 2022 ) (3.83-79.53mg/100g) from Himachal honey. Various findings reported higher proline content reported by Khalil et al., ( 2012 ) from Algerian honey (3381.83 mg/kg), Afshari et al., ( 2022 ) (115-640mg/kg) from Iran honey, and Erdogan and Turan (2022) (530-710mg/kg) from Turkey honey. 1,1-diphenyl-2-picrylhydrazyl (DPPH) Content DPPH content in the present study varied from 16.49–78.84 per cent, with the highest DPPH content reported in S9H honey (78.84%) of Zone-2, whereas the lowest was reported from S13H honey (16.49%) of Zone-3 (Table 3 ). DPPH is a widely used assay that measures honey’s ability to neutralise free radicals, serving as a reliable indicator of its overall antioxidant potency (Lewoyehu and Amare, 2019 ). The antioxidant activity of honey is affected by the presence of polyphenols, enzymes, amino acids, proteins, α-tocopherol, and vitamins. The S9H honey had highest phenol (108.54mg/100g) and optical density (2.41, amber colour) as compared to S13H honey had lowest phenol (12.96mg/100g) and optical density (0.12, extra white colour), these findings are consistent with previous studies, which reported a strong positive correlation between honey colour, its antioxidant activity, and total phenolic content (TPC) (Bertoncelj et al., 2007 ; Nayik and Nanda 2015 ; Nayik et al., 2016). The antioxidant properties of honey are also affected by environmental conditions as well as its floral and geographical origins (Nayik et al., 2016). Therefore, variation in DPPH content in the present study due to varied floral sources and regions aligned with previous results of Saxena et al., ( 2010 ) and Kamboj et al., ( 2013 ). The pollen sources for S9H honey were Sapindus sp. Dalbergia sp. and Trifolium sp. contributed to high DPPH content in honey, as compared to S13H honey, which had Malus × domestica and Medicago denticulate as important pollen sources. Nayik et al., (2016) reported that the antioxidant properties of apple honey significantly decreased with an increase in pH and thermal treatment. Mineral composition Honey is rich in macro and microminerals, and analysis of these minerals is important in order to detect environmental pollution, especially to detect heavy metals, and is also an indicator of botanical and geographical origin (Soares et al., 2017 ). The mineral content in different multifloral honeys is presented in Table 4 . In the present study, the Calcium (Ca) content in all the analysed samples varied from 79.48 to 193.98mg/kg. Among all the multifloral honeys, the significantly highest Ca content was recorded in S12H (193.98 mg/kg) honey from Zone-2, though statistically at par with S20H honey (189.5mg/kg) of Zone-4, whereas the lowest Ca content was found in S3H honey (79.48mg/kg) of Zone-1. The Magnesium (Mg) content in the present samples varied from 22.44-89.20mg/kg. Among all the samples, the highest Mg content was recorded in S2H honey (89.20mg/kg) from Zone-1, whereas the lowest was in S26H (22.44mg/kg) honey from Zone-4. The Phosphorus (P) content varied from 2.5-119mg/kg, with the highest being recorded from S2H honey (119mg/kg) from Zone-1, whereas the lowest was from S22H honey (2.5mg/kg) of Zone-4. The potassium (K) content in all multifloral honeys varied from 194.99-933.24mg/kg. The highest K content was found in S26H honey (933.24mg/kg) from Zone-4, whereas the lowest K content (194.99mg/kg) was in S3H honey of Zone-1. The Zinc (Zn) content in all multifloral honeys varied from 4.8 to 24.2mg/kg. Among all multifloral honeys, S10H honey from Zone-2 was reported with the highest Zn content (24.2mg/kg), whereas the lowest was from S4H honey of Zone-1. The sodium (Na) content in the present investigation varied from 116 to 212mg/kg. Among all honeys, S5H honey from Zone-1 reported the highest Na content (212mg/kg), whereas S13H honey from Zone-3 reported the lowest in Na content (116mg/kg). The iron (Fe) content in all the multifloral honeys varied from 2.91-6.08mg/kg. The highest Fe content was recorded in S16H honey (6.08mg/kg), whereas the lowest was in S23H honey (2.91mg/kg) of Zone-4. The manganese (Mn) content varied from 0.5-4.7mg/kg, with the highest being recorded from S18H honey (4.7mg/kg) of Zone-3, whereas the lowest Mn content was in S4H honey (0.5mg/kg) of Zone-1. Our study found that honey samples contained several minerals, viz., Ca, Mg, K, P, Zn, Na, Fe, Mn, and P, with K, Mg, and Ca being the most abundant as reported earlier by Thakur et al., 2021 ; Muhammad and Sarbon, 2023 , and Mongi, 2024 . Mineral content in all honeys was within the range recommended by the USDA ( 1985 ). The present results for different mineral contents fall within those reported by Terrab et al., ( 2004 ) from different floral honey of Spanish and Bouhlali et al., ( 2019 ) from Moroccan honey. In contrast, Thakur et al., ( 2021 ) reported mineral content viz., Ca (43.43-81.04mg/kg), Mg (27.16-35.40mg/kg), P (43.57-62.93mg/kg), K (286.18-354.17mg/kg) and Na (97.44-216.74mg/kg) from different locations of Himachal Pradesh, our results showed significantly higher concentrations of these minerals. This elevation may be attributed to the distinct floral diversity of our sampling sites (as shown in Fig. 2 ), as well as geographic factors that influence mineral uptake (Pavlin et al., 2023 ). Although the overall trend of mineral concentration across all zones remains similar. This could be due to the reason that higher altitude areas (Zone-4) are less impacted by human activity and industrial zones, thus showing lower mineral content compared to lower zones (Zone-1 and 2) (Salim et al., 2020 ). The other reason may be greater pesticide usage and more intensive agriculture in the lower-altitude zones, which may also contribute to increased mineral uptake into honey (Vlad et al., 2025 ). Bacterial load Microbes are indicators of hygienic quality and their load in honey depends upon age, season, hygienic harvesting, packaging and harvesting (Snowdon and Cliver, 1996 ). The bacterial load in different multifloral honeys varied from 2.3 to 4.32 log CFU/g (Fig. 2 ). The highest bacterial load (4.31 log CFU/g) was recorded in S11H honey of Zone-2, whereas, significantly lower bacterial load was recorded in S22H honey (2.3 log CFU/g) of Zone-4. The bacterial load found in the present study was within the safety limits for consumption (< 10 5 CFU/g). The bacterial count of the present study was within the values, viz. , 1.47–4.6 Log CFU/g and 3.55–4.17, as reported by Hosny et al., ( 2018 ) and Thakur et al. ( 2024 ) for honeys from Egypt and North India, respectively. The bacterial load in present study is comparatively lower than as documented by Oshomah and Ummulkhair ( 2014 ), Adadi and Obeng ( 2017 ) and Pajor et al., ( 2018 ) viz. , 4.0–8.0 Log CFU/g, 5.5–24.0 Log CFU/g and 3.04–6.27 log CFU/g for honeys from Nigeria, Ghana and Poland, respectively indicating appropriate management of bee hives and hygienic conditions maintained by the beekeepers of Himachal Pradesh during harvesting, packaging of honey and environmental conditions. PCA The Principal Component Analysis (PCA) results revealed eight principal components with eigenvalues greater than 1, following the Kaiser Criterion. These components cumulatively accounted for approximately 80.33% of the total variance in the dataset (Table 5 ). Specifically, PC1 explained 17.0 per cent, PC2 14.8 per cent, PC3 13.0 per cent, and PC4 10.5 per cent of the variance, while PC5 to PC8 each contributed between 5.2 per cent and 8.3 per cent, respectively. The PCA biplot (Fig. 3 ) demonstrated the separation of honey samples based on their geographical zones, suggesting distinct physicochemical profiles. While some overlap was present, zone-wise grouping was evident, especially for samples with distinct physicochemical profiles. The individual plot provided further evidence of this natural separation, with tighter clustering seen in certain agro-climatic regions, indicating more consistent physicochemical traits within those zones. The factor loadings for the top 8 principal components given in Table 6 revealed that PC1was predominantly influenced by high positive loadings from total acidity, ash, HMF, and phosphorus, while showing strong negative associations with optical density (OD), fructose, sucrose, F:G ratio, amino acid, potassium, manganese, and diastase content. This contrast suggested that PC1 differentiates honey samples rich in minerals and acidity from those dominated by sugars and antioxidant-related compounds. PC2 revealed positive loadings from vitamin C, ash, DPPH, calcium, and magnesium, indicating antioxidant and mineral richness, whereas negative loadings from electrical conductivity, glucose, phenol, sodium, iron, and manganese imply a trade-off between mineral content and antioxidant properties. PC3 was positively loaded with EC, moisture, sucrose, amino acids, phosphorus, zinc, and iron, indicating a component related to hydrophilic and micronutrient-rich honey profiles. Conversely, it was negatively associated with fructose, OD, vitamin C, DPPH, calcium, and magnesium, separating samples by differences in sugar types and antioxidant contents. PC4 was shaped by positive contributions from density, total acidity, DPPH, and phosphorus, while negative loadings from moisture, HMF, magnesium, zinc, and manganese suggest a component that contrasts denser, acidic honeys with those prone to oxidative degradation. In PC5, vitamin C, ash, DPPH, magnesium, iron, and sodium contributed positively, highlighting nutrient-rich honeys. Negative loadings from OD, fructose, sucrose, and F:G imply that this component distinguishes between nutritional quality and sugar profiles. PC6 reflected a simpler contrast, with positive loadings for fructose, potassium, and amino acid and negative loadings from moisture, vitamin C, magnesium, phosphorus, zinc, sodium, and iron, suggesting a potassium-dominant component inversely related to water and antioxidant levels. PC7 was positively associated with EC, fructose, sucrose, enzymes, and potassium, linking it to metabolically active and floral-origin indicators, while negative contributions from total acidity, HMF, phenol, and manganese may reflect oxidative stability. PC8 was positively influenced by amino acids and pH, while negatively loaded on OD, glucose, HMF, enzymes, phenol, magnesium, potassium, and manganese, suggesting this component differentiates fresh, proteinaceous honey from those with high degradation or pigment concentrations. The visual separation of samples in the Principal Component Analysis (PCA) biplot and individual score plots highlighted a distinct zone-wise clustering of multifloral honey samples. This spatial grouping suggested that geographical origin significantly influences the physicochemical characteristics of honey. Specifically, honey samples from similar agro-climatic regions exhibited tighter clustering, implying consistency in floral sources and environmental factors affecting nectar composition. These findings support earlier research that links honey variability to environmental parameters such as floral diversity, soil mineral content, climate conditions, and beekeeping practices. The observed clustering is consistent with previous studies that used chemometric techniques to classify honey based on origin and composition (Chakir et al., 2016 , Sakac et al., 2019 and Thakur et al., 2021 ). These studies demonstrated that physicochemical parameters, when analyzed through multivariate methods, are reliable markers for honey authentication and can be effectively used to verify botanical or geographical origin. The present results corroborate that agro-climatic influence is a key determinant in honey composition, thus emphasizing the importance of regional profiling in quality assurance and traceability of honey products. Table 5 Eigenvalues and Explained Variance of Principal Components Principal Component Eigenvalue Variance Explained (%) Cumulative Variance (%) PC1 4.23 17.02 17.02 PC2 3.71 14.82 31.84 PC3 3.25 13.01 44.85 PC4 2.64 10.54 55.39 PC5 2.07 8.28 63.67 PC6 1.61 6.42 70.09 PC7 1.41 5.65 75.74 PC8 1.15 4.59 80.33 Table 6 Factor loadings for principal components pH PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 0.059 0.258 0.123 0.054 -0.092 0.175 -0.075 0.470 EC 0.168 -0.428 0.534 0.026 -0.102 -0.283 0.329 -0.053 Moisture 0.084 -0.074 0.586 -0.478 -0.349 -0.406 0.184 -0.296 OD -0.553 -0.261 -0.456 -0.245 -0.458 -0.218 -0.103 -0.523 Density 0.213 -0.276 0.282 0.555 -0.301 0.091 0.110 0.087 Glucose 0.128 -0.577 -0.238 0.192 -0.252 0.142 -0.085 -0.437 Fructose -0.421 0.442 -0.405 0.139 -0.451 0.418 0.369 0.083 Sucrose -0.331 -0.186 0.514 0.245 -0.562 -0.402 0.146 0.093 F:G -0.226 0.236 -0.147 -0.384 -0.570 -0.519 0.215 -0.056 Total Acidity 0.543 0.225 -0.341 0.537 0.277 -0.295 -0.344 0.022 Vitamin C -0.173 0.529 0.318 0.298 0.484 -0.500 0.063 0.101 Ash 0.539 0.530 0.359 0.157 0.449 -0.248 0.419 0.141 HMF 0.488 0.329 -0.200 -0.503 -0.111 -0.321 -0.441 -0.536 Enzymes -0.053 0.220 0.235 -0.260 -0.144 -0.383 0.346 -0.532 Phenol 0.175 -0.558 -0.084 0.012 0.043 0.218 -0.267 -0.445 Amino Acid -0.407 0.356 0.551 -0.050 0.109 0.429 -0.051 0.542 DPPH -0.118 0.515 -0.480 0.534 0.443 -0.055 -0.208 -0.321 Ca -0.012 0.587 -0.522 0.340 -0.254 -0.310 0.195 -0.305 Mg -0.244 0.590 -0.301 -0.473 0.541 -0.320 0.228 -0.530 P 0.301 0.239 0.562 0.593 -0.058 -0.515 -0.249 -0.417 K -0.228 -0.152 0.030 0.301 -0.200 0.509 0.435 -0.542 Zn -0.153 0.037 0.507 -0.493 -0.113 -0.571 -0.189 0.147 Na 0.349 -0.483 -0.070 0.024 0.233 -0.491 -0.327 -0.108 Fe -0.240 -0.407 0.464 -0.064 0.489 -0.408 0.193 -0.072 Mn -0.390 -0.206 0.216 -0.524 0.129 -0.027 -0.259 -0.314 Cluster analysis The hierarchical clustering and heatmap based on presence-absence data of pollen species effectively depicted a two-dimensional clustering of honey samples (columns) and pollen grain species (rows) (Fig. 4 ). The top (column) dendrogram divides honey samples into three clear clusters based on similar pollen profiles, among which the first cluster (blue) includes two honey samples, the second cluster (orange) contains six honey samples, and the third cluster (green) consists of eighteen honey samples. Similarly, the left dendrogram (row) groups plant species that co-occur across multiple honey samples, showing three major clusters. Among three, the first largest cluster (blue) contains ninety-two pollen types found in many honey samples and represents the most widespread pollens, the second cluster (orange) includes two pollen species that appear moderately across multiple samples, and the third (green) lists only two pollen species, which are very rare or sample-specific and found sporadically among all samples. Additionally, the red blocks in the heatmap show the presence of different pollen types (rows) across various honey samples (columns), with these blocks being more concentrated in the upper region than at the bottom. Thus, cluster analysis using hierarchical dendrograms unveiled complex relationships among honey samples from different geographical zones and botanical origins. The heatmap results suggest that floral diversity varies significantly across the different honey samples. Among the honey sample clusters (top), the first cluster predominantly included S20H and S22H honey samples, both from Zone-4. The reason for the occurrence of both types of honeys could be due to the similar climatic conditions, which favour some unique flora in this zone, which likely contributes to the similar pollen grains in these honeys. Clusters two and three contained samples from all four zones; this could be due to some common flora found in these honey samples. These findings align with Onyango ( 2019 ) and Escuredo et al., ( 2023 ), who used dendrograms to differentiate different polyfloral honeys, showing that pollen-based clustering sheds light on bee foraging behavior and seasonal flower availability. Examining pollen types more closely, the first cluster on the left side included many rare or location-specific pollens, likely from plants adapted to microclimates in certain regions. The second cluster contained moderately abundant pollen types, representing secondary nectar sources bees use when primary flowers are scarce. The third cluster had common pollen types such as Prunus, Trifloium, Brassica, Grewia, and Albizia across all samples, with their widespread availability and important floral source to the bees. Other species are found in only a few samples, which may reflect local vegetation differences or seasonal blooming. The clustering of samples into three groups shows that certain sites share similar floral profiles, possibly due to similar environmental conditions or land use patterns. These findings closely correlate with the above interpretations, showing that Fabaceae dominated all four zones, followed by Asteraceae in zones 1 and 2 and Rosaceae in zones 3 and 4, thereby supporting the present conclusions. These observations agree with Herrero et al., ( 2002 ) and Muresan et al., (2022), whose cluster analysis of different multifloral honey revealed groupings that corresponded to specific floral compositions and ecological zones. Further, heatmaps enhance the interpretability of clustering by integrating presence–absence data. The concentrated red blocks of heatmap at the top indicate that these pollen types were dominant across most honey samples, whereas scattered red blocks toward the bottom indicate rare, more specialized pollens. These patterns likely reflect flora that are restricted to specific agro climatic zones. As demonstrated by Ponnuchamy et al., ( 2014 ) and Hajian-Tilaki et al., ( 2024 ), visual matrices of pollen distribution can reveal high-density clusters of specific taxa, often linked to regional or seasonal foraging preferences. Such visual patterns often correspond to ecological traits, such as the dominance of nectariferous species in certain landscapes or the flowering synchronisation of co-occurring species. Conclusion This study revealed that Himachal Pradesh has a rich floral diversity, which contributes to various multifloral honeys with unique floral contents that boost their medicinal properties. The physicochemical and mineral characteristics of all the honeys were in accordance with FSSAI standards. The variations in physicochemical and mineral composition show how different floral and geographical origin influence their characteristics. The results also highlighted that all the honeys were pure, fresh, and well-stored, practices were adopted by beekeepers of the state. No signs of honey adulteration were observed in any of the samples analysed except for one sample recorded with high moisture content (> 20%), sucrose content (> 5%), and HMF content (> 80mg/kg) from Zone-1. The potassium, magnesium, and calcium found as the most abundant minerals in all the multifloral honeys indicate the high nutritional value of these honeys. Further, PCA revealed that floral origin significantly influences the physicochemical characteristics of honey. The Cluster analysis helped in understanding the botanical origin of honey, tracking pollinator foraging behaviour, and identifying potential areas for conserving diverse plant species. Declarations Acknowledgments The authors are also grateful to Dr. YS Parmar University, Nauni, Solan, and all beekeepers who assisted with the collection of honey samples. Author Contributions Author R. Sharma performed the research, statistical analysis, and wrote the manuscript, M. Thakur and S. Devi helped with review and editing. Conflict of interest The authors have no conflicts of interest to declare. All coauthors have seen and agree with the contents of the manuscript and certify that the submission is original work and is not under review at any other publication. Funding The authors declare that no external funding was received for the preparation and completion of this research paper. Data Availability Statement All data generated or analysed during this study are included in this published article and its supplementary information files. References Abselami A, tahani A, syndic M, fauconnier ML, bruneau E, elbachiri A. Physicochemical properties of some honeys produced from different flora of Eastern Morocco. Journal of Materials and Environmental Science 2018;9: 879-886. Adadi P and Obeng A K. 2017. Assessment of bacterial quality of honey produced in Tamale Metropolis (Ghana). Journal of Food and Drug Analysis 25:369-73. Adenekan, M.O., Amusa, N.A., Lawal, A.O. and Okpeze, V.E., 2010. Physico-chemical and microbiological properties of honey samples obtained from Ibadan. Journal of Microbiology and Antimicrobials , 2 (8), pp.100-104. Afshari, A., Ram, M. and Mohamadi, S., 2022. Quality evaluation of Iranian honey collected from Khorasan province, Iran. International Journal of Food Science, 2022(1), p.3827742. Ahmed, A.S., Elgorashi, E.E., Moodley, N., McGaw, L.J., Naidoo, V. and Eloff, J.N., 2012. The antimicrobial, antioxidative, anti-inflammatory activity and cytotoxicity of different fractions of four South African Bauhinia species used traditionally to treat diarrhoea. Journal of Ethnopharmacology , 143 (3), pp.826-839. Ahmed, J., Prabhu, S.T., Raghavan, G.S.V. and Ngadi, M., 2007. Physico-chemical, rheological, calorimetric and dielectric behavior of selected Indian honey. Journal of Food Engineering , 79 (4), pp.1207-1213. Albu, A., Simeanu, C., Pop, I.M., Pui, A., Tarcău, D. and Cucu-Man, S.M., 2023. Selected characteristics of multifloral honeys from North-Eastern Romania. Agriculture , 14 (1), p.26. Amir, Y., Yesli, A., Bengana, M., Sadoudi, R. and Amrouche, T., 2010. Physico-chemical and microbiological assessment of honey from Algeria. Electronic Journal of Environmental, Agricultural & Food Chemistry , 9 (9). AOAC (1984) Official Methods of Analysis. Association of official analytical chemists, 12th ed., Washington, D.C. p. 1141. AOAC (2000) Official Methods of Analysis.17th ed. (Horowitz W ed.). The association of official analytical cemists, Gaithersburg, MD, USA. AOAC (2004) Official Methods of Analysis. 17th ed. (Horowitz W ed.). The association of official analytical chemists, Gaithersburg, MD, USA. AOAC (2012) Official Methods of Analysis . 19th ed. (GW Latimer ed.). The association of official analytical chemists, Gaithersburg, MD, USA. Attri P K 2011 Physico-chemical investigation of honey samples of Apis ceranaindicaF. (Traditional Beekeeping) and Apis mellifera (Mordern Apiculture) from Chamba District, Himachal Pradesh. Biological Forum-An International Journal 3 67-73. Bertoncelj, J.; Dobersek, U.; Jamnik, M.; Golob, T. Evaluation of the Phenolic Content, Antioxidant Activity and Colour of Slovenian Honey. Food Chemistry 2007, 105, 822–828 Besharati, M., Far, M.N., Azhir, D., Palangi, V. and Lackner, M., 2025. Evaluation of Physicochemical Properties of Honey produced in East Azerbaijan Province, Iran. Applied Food Research , p.100933. BIS (Bureau of Indian Standards) (1994) Indian Standard Extracted Honey - Specifications2 nd revision. The National Standard Body of India, New Delhi. Bogdanov S, Ruoff K, Oddo LP (2004) Physico-chemical methods for the characterization of unifloral honeys. Apodologie 35:4-17. Bogdanov, S., Haldimann, M., Luginb€uhl, W. and Gallmann, P. (2007), “Minerals in honey: environmental, geographical and botanical aspects”, Journal of Apicultural Research and Bee World, Vol. 46, pp. 269-275. Bouhlali, E.D.T., Bammou, M., Sellam, K., El Midaoui, A., Bourkhis, B., Ennassir, J., Alem, C. and Filali-Zegzouti, Y., 2019. Physicochemical properties of eleven monofloral honey samples produced in Morocco. Arab Journal of Basic and Applied Sciences , 26 (1), pp.476-487. Buba, F., Gidado, A. and Shugaba, A., 2013. Analysis of biochemical composition of honey samples from North-East Nigeria. Biochem Anal Biochem , 2 (3), p.139. Buba, F., Gidado, A. and Shugaba, A., 2013. Physicochemical and microbiological properties of honey from North East Nigeria. Biochem Anal Biochem , 2 (142), pp.61-67. Chakir, A., Romane, A., Marcazzan, G.L. and Ferrazzi, P., 2016. Physicochemical properties of some honeys produced from different plants in Morocco. Arabian Journal of Chemistry , 9 , pp.S946-S954. Chidi, B.S., Bauer, F.F. and Rossouw, D., 2018. Organic acid metabolism and the impact of fermentation practices on wine acidity: A review. South African Journal of Enology and Viticulture , 39 (2), pp.1-15. Choudhary, A., Kumar, V., Kumar, S., Majid, I., Aggarwal, P. and Suri, S., 2021. 5-Hydroxymethylfurfural (HMF) formation, occurrence and potential health concerns: Recent developments. Toxin Reviews, 40(4), pp.545-561. Da Silva, P.M., Gauche, C., Gonzaga, L.V., Costa, A.C.O. and Fett, R., 2016. Honey: Chemical composition, stability and authenticity. Food chemistry , 196 , pp.309-323. Da Silva, P.M., Gauche, C., Gonzaga, L.V., Costa, A.C.O. and Fett, R., 2016. Honey: Chemical composition, stability and authenticity. Food chemistry , 196 , pp.309-323. Devi, S., Parihar, A., Thakur, M., Thakur, B. and Sharma, H.K., 2021. Antibacterial potential of hive bees honey from Himachal Pradesh, India. Archives of Microbiology , 203 , pp.5029-5041. Djonwangwe D, Tchuenguem Fohouo FN, Messi J, Bru¨ckner D. 2011. Foraging and pollination activities of Apis mellifera adansonii Latreille (Apidae) on Syzygium guineense var. guineense (Myrtaceae) flowers at Ngaounde´ re´ (Cameroon). Journal of Animal and Plant Sciences 10:1325–1333 Dobrinas, S., Soceanu, A., Birghila, S., Birghila, C., Matei, N., Popescu, V. and Constanda, L.M., 2022. Chemical analysis and quality assessment of honey obtained from different sources. Processes , 10 (12), p.2554. Draiaia, R., Dainese, N., Borin, A., Manzinello, C., Gallina, A. and Mutinelli, F., 2015. Physicochemical parameters and antibiotics residuals in Algerian honey. African Journal of Biotechnology , 14 (14), pp.1242-1251. Dung, N.T.P., Rombouts, F.M. and Nout, M.J.R., 2005. Development of defined mixed-culture fungal fermentation starter granulate for controlled production of rice wine. Innovative Food Science & Emerging Technologies , 6 (4), pp.429-441. El Sohaimy SA, Masry SHD, Shehata MG. 2015. Physicochemical characteristics of honey from different origins. Annals of Agricultural Science. 60:279-287. Erdoğan, Y. and Turan, M., 2022. Physicochemical properties of honey produced at different altitudes. Turkish Journal of Agriculture-Food Science and Technology , 10 (4), pp.710-718. Erdtman G. 1969. Handbook of palynology: morphology, taxonomy, ecology. An introduction to the study of pollen grains and spores. Hafner, New York. pp 1-486. Escriche, I., Sobrino-Gregorio, L., Conchado, A. and Juan-Borrás, M., 2017. Volatile profile in the accurate labelling of monofloral honey. The case of lavender and thyme honey. Food chemistry , 226 , pp.61-68. Escuredo, O., Rodríguez-Flores, M.S., Míguez, M. and Seijo, M.C., 2023. Multivariate statistical approach for the discrimination of honey Samples from Galicia (NW Spain) using physicochemical and pollen parameters. Foods , 12 (7), p.1493. Felsner, M.L., Cano, C.B., Bruns, R.E., Watanabe, H.M., Almeida-Muradian, L.B.D. and Matos, J.D.R., 2004. Characterization of monofloral honeys by ash contents through a hierarchical design. Journal of Food Composition and Analysis , 17 (6), pp.737-747. Gairola, A., Tiwari, P. and Tiwari, J.K., 2013. Physico-chemical properties of Apis cerana-indica F. honey from Uttarkashi district of Uttarakhand, India. Journal of Global Biosciences , 2 (1), pp.20-25. Godoy, C.A., Valderrama, P. and Boroski, M., 2022. HMF monitoring: Storage condition and honey quality. Food Analytical Methods , 15 (11), pp.3162-3176. Grassi, G., Capasso, G., Cillo, A., Miedico, O., Pompa, C., Nardelli, V. and Perna, A.M., 2025. Effect of Altitude on Polyphenol Content, Antioxidant Activity and Multi-Element Composition of Wildflower Honey. Applied Sciences , 15 (6), p.3255. Hajian-Tilaki, A., Kenari, R.E., Farahmandfar, R. and Razavi, R., 2024. Comparative study of physiochemical properties in Iranian multi-floral honeys: Local vs. commercial varieties. Heliyon , 10 (17). Hajian-Tilaki, A., Kenari, R.E., Farahmandfar, R. and Razavi, R., 2024. Comparative study of physiochemical properties in Iranian multi-floral honeys: Local vs. commercial varieties. Heliyon , 10 (17). Herrero, B., María Valencia-Barrera, R., San Martín, R. and Pando, V., 2002. Characterization of honeys by melissopalynology and statistical analysis. Canadian Journal of plant science , 82 (1), pp.75-82. Hosny A S, Sabbah F M and El-Bazza Z E. 2018. Studies on the microbial decontamination of Egyptian bee pollen by γ radiation. Egyptian Pharmaceutical Journal 17:190-200. Iftikhar, F., Masood, M.A. and Waghchoure, E.S. (2011), “Comparison of Apis cerana, Apis dorsata, Apis florea and Apis mellifera honey from different areas of Pakistan”, Society of Applied Sciences, Vol. 2, pp. 399-03. Ikegbunam, N.C., Okwong, J.W. and Anukwuorji, A.C., 2025. PHYSICOCHEMICAL PROPERTIES AND MINERAL COMPOSITION OF HONEY (Apis mellifera) FROM NORTH CENTRAL NIGERIA. The Bioscientist Journal , 13 (1), pp.34-46. ISI 1(974) Indian Standard Specification for Honey. 4941p. Isla MI, Craig A, Ordoñez R, Zampini C, Sayago J, Bedascarrasbure E, Maldonado L (2011) Physico chemical and bioactive properties of honeys from northwestern Argentina. LWT-Food Science and Technology 44:1922-30. Iwama S, Melhem TS. 1979. The pollen spectrum of the honey of Tetragonisca angustula angustula L. Apidologie. 10:275-295. Jackson ML (1973) Soil Chemical Analysis. Prentice Hall Publisher, New Delhi, pp. 111-.26 Jackson ML (2005) Soil Chemical Analysis. Prentice Hall Publisher, New Delhi, pp. 112- 27. Kamal MM, Rashid MHU, Mondal SC, EL Taj HF, Jung C. Physicochemical and microbiological characteristics of honey obtained through sugar feeding of bees. Journal of Food Science and Technology 2019;56:2267-2277. Kamboj, R., Bera, M. and Nanda, V., 2013. Chemometric classification of Northern India unifloral honey. Acta Alimentaria , 42 (4), pp.540-551. Kamboj, R., Bera, M.B. and Nanda, V., 2013. Evaluation of physico-chemical properties, trace metal content and antioxidant activity of Indian honeys. International Journal of Food Science and Technology , 48 (3), pp.578-587. Kamboj, R., Sandhu, R.S. and Nanda, V., 2024. Effect of heating and pH on hydroxymethylfurfural content, diastase and invertase activity of Dalbergia honey using response surface methodology. Food Chemistry Advances , 5 , p.100766. Karabagias, I.K., Louppis, A.P., Karabournioti, S., Kontakos, S., Papastephanou, C. and Kontominas, M.G., 2017. Characterization and geographical discrimination of commercial Citrus spp. honeys produced in different Mediterranean countries based on minerals, volatile compounds and physicochemical parameters, using chemometrics. Food Chemistry , 217 , pp.445-455. Khalil, M.I., Moniruzzaman, M., Boukraâ, L., Benhanifia, M., Islam, M.A., Islam, M.N., Sulaiman, S.A. and Gan, S.H., 2012. Physicochemical and antioxidant properties of Algerian honey. Molecules , 17 (9), pp.11199-11215. Kumar, A., Gill, J.P.S., Bedi, J.S., Manav, M., Ansari, M.J. and Walia, G.S. (2018b), “Sensorial and physicochemical analysis of Indian honeys for assessment of quality and floral origins”, Food Research International, Vol. 108, pp. 571-583. Larsen, P. and Ahmed, M., 2022. Evaluation of antioxidant potential of honey drops and honey lozenges. Food Chemistry Advances , 1 , p.100013. Lavinas, F.C., Gomes, B.A., Silva, M.V., Lima, R., Leitão, S.G., Moura, M.R., Simas, R.C., Barbosa, R.F., Silva, F.O., Carneiro, C.S. and Rodrigues, I.A., 2025. Rainy and Dry Seasons Are Relevant Factors Affecting Chemical and Antioxidant Properties of Meliponini Honey. Foods , 14 (2), p.305. Lewoyehu, M. and Amare, M., 2019. Comparative evaluation of analytical methods for determining the antioxidant activities of honey: A review. Cogent Food & Agriculture , 5 (1), p.1685059. Louveaux J, Maurizio A. Vorwohl G. 1978. Methods of melissopalynology. Bee World. 59:139-53. Mongi, R.J., 2024. Influence of botanical origin and geographical zones on physicochemical properties, mineral contents and consumer acceptance of honey in Tanzania. Food Chemistry Advances , 4 , p.100731. Mongi, R.J., 2024. Influence of botanical origin and geographical zones on physicochemical properties, mineral contents and consumer acceptance of honey in Tanzania. Food Chemistry Advances , 4 , p.100731. Muhammad, N.I.I. and Sarbon, N.M., 2023. Physicochemical profile, antioxidant activity and mineral contents of honey from stingless bee and honey bee species. Journal of Apicultural Research, 62(2), pp.394-401. Mureșan, C.I., Cornea-Cipcigan, M., Suharoschi, R., Erler, S. and Mărgăoan, R., 2022. Honey botanical origin and honey-specific protein pattern: Characterization of some European honeys. Lwt , 154 , p.112883. Nair P K K. 1964. A pollen analytical study of Indian honeys. The Journal of Indian Botanical Society 43 :179‐91. Nair PKK. 1985. Melittopalynology. In: Essentials of Palynology . New Delhi: Today and Tomorrow’s Publishers. pp 59-64. Nanda, V., Singh, B., Kukreja, V.K. and Bawa, A.S., 2009. Characterisation of honey produced from different fruit plants of northern India. International Journal of Food Science and Technology , 44 (12), pp.2629-2636. Nayik, G.A. and Nanda, V., 2015. Physico-chemical, enzymatic, mineral and colour characterization of three different varieties of honeys from Kashmir valley of India with a multivariate approach. Polish Journal of Food and Nutrition Sciences , 65 (2). Nayik, G.A. and Nanda, V., 2016. A chemometric approach to evaluate the phenolic compounds, antioxidant activity and mineral content of different unifloral honey types from Kashmir, India. LWT , 74 , pp.504-513. Nayik, G.A.; Nanda, V. Physico-Chemical, Enzymatic, Mineral, and Colour Characterization of Three Different Varieties of Honeys from Kashmir Valley of India with a Multivariate Approach. Polish Journal of Food Sciences and Nutrition 2015, 65, 101–108. 11. Naz, R., Roberts, T.H., Bano, A., Nosheen, A., Yasmin, H., Hassan, M.N., Keyani, R., Ullah, S., Khan, W. and Anwar, Z., 2020. GC-MS analysis, antimicrobial, antioxidant, antilipoxygenase and cytotoxic activities of Jacaranda mimosifolia methanol leaf extracts and fractions. PLoS One , 15 (7), p.e0236319. Onyango, P., 2019. Authentication of honey samples from Eastern Mau forest Kenya by principal component analysis and cluster analysis of quantitative melissopalynological variables. International Journal of Recent Research in Life Sciences (IJRRLS) , 6 , pp.1-7. Oroian, M.; Ropciuc, S. Honey Authentication Based on Physicochemical Parameters and Phenolic Compounds. Comput. Electron. Agric. 2017, 138 , 148–156 Orsavová, J., Sytařová, I., Mlček, J. and Mišurcová, L., 2022. Phenolic compounds, vitamins C and E and antioxidant activity of edible honeysuckle berries (Lonicera caerulea L. var. kamtschatica Pojark) in relation to their origin. Antioxidants , 11 (2), p.433. Oshomah M U and Ummulkhair M. 2014. Microbiological evaluation of commercial honey from Edo state, Nigeria. International Journal of Scientific and Engineering Research 5: 796-99. Ouchemoukh, S., Louaileche, H. and Schweitzer, P., 2007. Physicochemical characteristics and pollen spectrum of some Algerian honeys. Food control , 18 (1), pp.52-58. Ozler H. 2015. Melissopalynological analysis of honey samples belonging to different districts of Sinop, Turkey. Mellifera. 15:1-11. Pajor M, Worobo R W, Milewski S and Szweda P. 2018. The antimicrobial potential of bacteria isolated from honey samples produced in the apiaries located in Pomeranian Voivodeship in Northern Poland. International Journal of Environmental Research and Public Health 15:1-14. Parihar, A., Thakur, M., Rana, K. and Devi, S., 2020. Quality analysis of Apis cerana and Apis mellifera honey from Himachal Pradesh, India. Journal of Entomology and Zoology studies , 8 (6), pp.46-54. Pașca, C., Mărghitaș, L.A., Matei, I.A., Bonta, V., Mărgăoan, R., Copaciu, F., Bobiș, O., Campos, M.G. and Dezmirean, D.S., 2021. Screening of some Romanian raw honeys and their probiotic potential evaluation. Applied Sciences , 11 (13), p.5816. Pavlin, A., Kočar, D., Imperl, J., Kolar, M., Marolt, G. and Petrova, P., 2023. Honey origin authentication via mineral profiling combined with chemometric approaches. Foods , 12 (15), p.2826. Perna, A., Intaglietta, I., Simonetti, A. and Gambacorta, E., 2013. A comparative study on phenolic profile, vitamin C content and antioxidant activity of Italian honeys of different botanical origin. International Journal of Food Science and Technology , 48 (9), pp.1899-1908. Pham T N, Le H T, Nguyen Q V, Tran Q T and Tran M P. 2022. Physicochemical properties, phenolic contents and antioxidant activity of Vietnamese honey. Research and Innovation in Food Science and Technology 10:427-38. Ponnuchamy, R., Bonhomme, V., Prasad, S., Das, L., Patel, P., Gaucherel, C., Pragasam, A. and Anupama, K., 2014. Honey pollen: using melissopalynology to understand foraging preferences of bees in tropical South India. Plos one , 9 (7), p.e101618. Ramly, N.S., Sujanto, I.S.R., Abd Ghani, A., Huat, J.T.Y., Alias, N. and Ngah, N., 2021. The impact of processing methods on the quality of honey: A review. Malaysian Journal of Applied Sciences , 6 (1), pp.99-110. Rana K, Abhivivek RKN, Monika MRB, Singh N. 2022. Melissopalynological analysis of honey for assessment of nectariferous resources of European honey bees (Apis mellifera L.) in mid hills of Himachal Pradesh. Biological Forum. 14:1175-1181. Rani, A. and Verma, S., 2025. Phytochemical Composition, Antioxidant, and Antimicrobial Potential of Honey: A Comprehensive Review. INTERNATIONAL JOURNAL OF PLANT AND ENVIRONMENT , 11 (01), pp.10-19. Sahney M, Kumar A and Rahi S. 2016. Pollen analysis of honey from Varanasi district, Uttar Pradesh, India. Biological Forum-An International Journal 8 :126-33. Sakač, M.B., Jovanov, P.T., Marić, A.Z., Pezo, L.L., Kevrešan, Ž.S., Novaković, A.R. and Nedeljković, N.M., 2019. Physicochemical properties and mineral content of honey samples from Vojvodina (Republic of Serbia). Food chemistry , 276 , pp.15-21. Saklani S and Mattu V K. 2018. Pollen analysis of honey samples from Hamirpur district, Himachal Pradesh, India. The International Journal of Plant Reproductive Biology 10 :145-50. Saklani S, Mattu VK. 2020. Scanning electron microscopic study on pollens of 8 bee floral resources from Kangra Hills, Himachal Pradesh, India. International Journal of Biotech Trends and Technology. 10:67-71. Salim, Z., Khan, M.U. and Malik, R.N., 2020. Concentration, distribution and association of heavy metals in multi-matrix samples of Himalayan foothill along elevation gradients. Environmental Earth Sciences , 79 (20), p.479. Sarma VAK, Krishna P, Budihal SL (1987) Soil resource mapping of different states in India-A Laboratory manual. National Bureau of Soil Survey and Land Use Planning Nagpur. p. 49. Saxena, S., Gautam, S. and Sharma, A., 2010. Physical, biochemical and antioxidant properties of some Indian honeys. Food chemistry , 118 (2), pp.391-397. Schade JE, Marsh GL, Eckert JE (1958) Diastase activity and hydroxy‐methyl‐ furfural in honey and their usefulness in detecting heat alteration. Journal of Food Science 23:446-63. Sharma N. 1989. Melissopalynology and survey of honey plants in Himachal Pradesh. PhD Thesis, Himachal Pradesh University, Shimla, India. Sharma, A., Daroch, R.K., Kapoor, R. and Kumar, I., 2022. Status of bee keeping in Himachal Pradesh, India: A review. The Pharma Innovation Journal 2022; SP-11(3): 257-265 Sharma, R., Thakur, M., Rana, K., Devi, D. and Bajiya, M.R., 2023. Honey, its quality and composition and their responsible factors. International Journal of Bio-resource and Stress Management , 14 (1), pp.178-189. Shishira, D., Uthappa, A.R., Chavan, S.B., Kuberappa, G.C., Jinger, D. and Sringeswara, A.N., 2024. Pollen diversity in urban honey: implications for bee foraging behaviour and urban green space planning. Urban Ecosystems , 27 (6), pp.2487-2500. Shobham K K C and Nayar J. 2017. Physicochemical analysis of some commercial honey samples from Telangana. Indian Journal of Nutrition 4:1-4. Shukla V and Kumar A. 2020. Melissopalynological and physicochemical analysis of honey samples from Prayagraj district Uttar Pradesh. Acta Palaeobotanica 60:123-33. Singh M and Sharma K. 2007. Importance of bee flora of low hills of Himachal Pradesh. Insect Environment 13 :79-80. Singleton VL, Orthofer R, Lamuela-Raventos RM (1999) Analysis of total 403 phenols and other oxidation substrates and antioxidants by means of folin-ciocalteu 404 reagent. Methods in Enzymology 299:152-78. Sireli, H.D. and Saylak, Ü., 2025. The effect of storage temperature on some physicochemical properties of flower honey. Agrociencia , pp.1-11. Smith LI (2002) A tutorial on principal components analysis. Snowdon J A and Cliver D O. 1996. Microorganisms in honey. International Journal of Food Microbiology 31:1-26. Soares, S., Amaral, J.S., Oliveira, M.B.P. and Mafra, I., 2017. A comprehensive review on the main honey authentication issues: Production and origin. Comprehensive Reviews in Food Science and Food Safety , 16 (5), pp.1072-1100. Solayman, M., Islam, M.A., Paul, S., Ali, Y., Khalil, M.I., Alam, N. and Gan, S.H., 2016. Physicochemical properties, minerals, trace elements, and heavy metals in honey of different origins: a comprehensive review. Comprehensive reviews in food science and food safety , 15 (1), pp.219-233. Song XY, Yao YF, Yang WD. 2012. Pollen analysis of natural honeys from the central region of Shanxi, north China. PloS One. 7:e50329. Suharoschi, R., Erler, S. and Mărgăoan, R., 2022. Honey botanical origin and honey-specific protein pattern: Characterization of some European honeys. Lwt , 154 , p.112883. Tarapatskyy, M., Sowa, P., Zaguła, G., Dżugan, M. and Puchalski, C., 2021. Assessment of the botanical origin of polish honeys based on physicochemical properties and bioactive components with chemometric analysis. Molecules , 26 (16), p.4801. Terrab, A., Recamales, A.F., Hernanz, D. and Heredia, F.J., 2004. Characterisation of Spanish thyme honeys by their physicochemical characteristics and mineral contents. Food chemistry , 88 (4), pp.537-542. Testa, R., Asciuto, A., Schifani, G., Schimmenti, E. and Migliore, G., 2019. Quality determinants and effect of therapeutic properties in honey consumption. An exploratory study on Italian consumers. Agriculture , 9 (8), p.174. Thakur, B., Devi, S., Thakur, M., Parihar, A., Sagar, V. and Devi, D., 2024. Unraveling the microbial status of wild bee’s honey from North India. Biologia , 79 (6), pp.1919-1930. Thakur, M., Gupta, N., Devi, D., Bajiya, M.R., Sharma, R. and Sharma, D., 2022. Variations in physicochemical characteristics of honey: a review. The Pharma Innovation Journal , 11 (7), pp.337-348. Thakur, M., Gupta, N., Sharma, H.K. and Devi, S., 2021. Physicochemical characteristics and mineral status of honey from different agro-climatic zones of Himachal Pradesh, India. British Food Journal , 123 (11), pp.3789-3804. Townsend GF (1969) Optical density as a means of colour classification of honey. Journal of Apicultural Research 8:29-36. Tripathi S, Basumatary S K, Bera S K, Brahma M and Sarma G C. 2017. A palynological study of natural honeys from the Bongaigaon district of Assam, northeast India. Palynology 41 :389-400. Ukanyirioha CJ, Popoola AS, Erhabor TA, Janfa N, Chomini MS, Kambai C, Imoh JA, Ukwadi M, Sadiku Y, Francis MJ. 2021. Melissopalynological analysis of honey to detect melliferous plant species visited by Apis mellifera adansonii latereille (West African honeybee) in Guinea Savanna Zone of Nigeria. Ethiopian Journal of Environmental Studies & Management. 14:834-841. USDA. 1985. United States Standards for Grades of Extracted Honey (5 th ed.).Agricultural marketing service fruit and vegetable division processed products branch, United States, Department of Agriculture, Washington, DC. Verma K. 2006. Melissopalynological Analysis of Some Honeys from Hamirpur and adjoining areas of Himachal Pradesh . M. Phil. Dissertation. Himachal Pradesh University, Shimla, HP, India. 73p. Vlad, I.A., Bartha, S., Goji, G., Tăut, I., Rebrean, F.A., Burescu, L.I.N., Pășcuț, C.G., Moțiu, P.T., Tunduc, A., Bunea, C.I. and Bora, F.D., 2025. Comprehensive Assessment of Potentially Toxic Element (PTE) Contamination in Honey from a Historically Polluted Agro-Industrial Landscape: Implications for Agricultural Sustainability and Food Safety. Agriculture , 15 (11), p.1176. Von Der Ohe W, Oddo LP, Piana ML, Morlot M, Martin P. 2004. Harmonized methods of melissopalynology. Apidologie. 35(Suppl. 1):S18-S25. Wollum, A.G.: Cultural methods for soil microorganisms. In: Methods of Soil Analysis Part-2: Chemical and Microbiological Properties. American Society of Agronomy, Inc Publisher Madison, Wisconsin, USA. pp. 781-02 (1982). Yao, Y.F., Bera, S., Wang, Y.F. and Li, C.S., 2006. Nectar and pollen sources for honeybee (Apis cerana cerana Fabr.) in Qinglan mangrove area, Hainan Island, China. Journal of Integrative Plant Biology , 48 (11), pp.1266-1273. Yayinie M, Atlabachew M, Tesfaye A, Hilluf W, Reta C and Alemneh T. 2022. Polyphenols, flavonoids, and antioxidant content of honey coupled with chemometric method: Geographical origin classification from Amhara region, Ethiopia. International Journal of Food Properties 25:76-92. Yu, W., Zhang, Y., Li, J., Li, J., Li, K., Ning, F., Guo, X., Huang, X. and Luo, L., 2025. Physicochemical Properties, Chemical Composition, and against Klebsiella pneumoniae Mechanism of Scrophularia ningpoensis Honey. LWT , p.118157. Additional Declarations No competing interests reported. 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Sharma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYFACHoYDDAZgVvKDD0CSjZ0ELc8MZ4C0MBOhBQoYH0iD2YS0mLf3HjxcUHDY3lwiOcHY5tc2eT5mBsYPH3Nwa5E5cy7h8AyDw4k7Z6QlPM7tu23YxszALDlzG24tEhI5Bod5DA4nGNzISTDO7bnNCNTCxsxLhBZ7gxv5H6Qte27bE62FccONhARphh+3Ewlr4TkD0pKeuLPnQZphb8Pt5DZmxmb8fmHvMf7M88fa3pw9IfnBjz+3bee3Nx/88BGPFihohsQmYxuYbCCoHgjqoAngDzGKR8EoGAWjYKQBAM2lUUgGW4kkAAAAAElFTkSuQmCC","orcid":"","institution":"Dr. Yashwant Singh Parmar University of Horticulture and Forestry","correspondingAuthor":true,"prefix":"","firstName":"Rohini","middleName":"Sharma","lastName":"Sharma","suffix":""},{"id":622082971,"identity":"95cec6b3-97be-436f-8eed-f3a70900cd61","order_by":1,"name":"Meena Thakur meena","email":"","orcid":"","institution":"Dr. Yashwant Singh Parmar University of Horticulture and Forestry","correspondingAuthor":false,"prefix":"","firstName":"Meena","middleName":"Thakur","lastName":"meena","suffix":""},{"id":622082972,"identity":"ddda811f-145b-447f-9f73-ef8edcdb263f","order_by":2,"name":"Sunita Devi sunita","email":"","orcid":"","institution":"Dr. Yashwant","correspondingAuthor":false,"prefix":"","firstName":"Sunita","middleName":"Devi","lastName":"sunita","suffix":""}],"badges":[],"createdAt":"2026-03-25 11:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9222304/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9222304/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106919665,"identity":"20e1371f-748e-44c4-ab7b-561c5b89ce62","added_by":"auto","created_at":"2026-04-14 19:13:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":196314,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLocation map of multifloral honey samples\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9222304/v1/8505a28d3ff619f5f134c795.png"},{"id":106960803,"identity":"38ce347a-f47e-42ef-9362-404bdc5c5e5c","added_by":"auto","created_at":"2026-04-15 09:23:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27009,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBacterial load (Log CFU/g) present in multifloral honey samples\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9222304/v1/63f7375cc6b45afbc49d1850.png"},{"id":106919662,"identity":"92751fe6-6a7d-4808-90e9-f0d2d7e9fae2","added_by":"auto","created_at":"2026-04-14 19:13:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":165382,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of active variables and observations\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9222304/v1/1a6df98ae9cdd64f612a2183.png"},{"id":106919664,"identity":"a85ca140-6814-4490-9d84-3dc3f44987a0","added_by":"auto","created_at":"2026-04-14 19:13:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":342488,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHierarchical cluster analysis (HCA) dendrogram of all the pollen types found in multifloral honey samples from all zones of Himachal Pradesh\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9222304/v1/21c4f4f83d087f66db3ee052.png"},{"id":106963146,"identity":"d9ea96c1-e8a0-47d7-b901-676585349ba4","added_by":"auto","created_at":"2026-04-15 09:42:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2828582,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9222304/v1/b3743f18-a3b4-477a-a23a-a35911deb259.pdf"},{"id":106919661,"identity":"7b4c50db-c58f-43e2-b995-ebe3f59e0669","added_by":"auto","created_at":"2026-04-14 19:13:47","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":61198,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-9222304/v1/57819fc492a25d38d9bd6b8f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Physicochemical and Mineral Profiling of Multifloral Honeys from Apis mellifera in Himachal Pradesh, India: Implications for Export and GI Tagging","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHoney is a complex natural substance produced by honey bees from floral nectar, has long been recognized as a functional food due to its rich composition of carbohydrates, enzymes, organic acids, and bioactive compounds. These constituents contribute to its pharmacological properties, including anti-inflammatory effects, antidiabetic properties, antimicrobial activity, wound healing, and potential anticancer effects (Parihar et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Devi et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The physicochemical characteristics of honey are influenced by factors like botanical origin, climatic conditions, and beekeeping practices, which in turn affect its quality and authenticity (Besharati et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Grassi et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). It is known that based on botanical origin, honeys are categorised into unifloral and multifloral types; unifloral honey contains more than 45 per cent pollen from a single plant species, while multifloral honey comprises less than 45 per cent pollen from various plant species (Sharma et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Multifloral honeys, due to their diverse floral sources, exhibit a wide range of physicochemical properties and bioactive compounds, contributing to their enhanced medicinal value (Larsen and Ahmed, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, the quality, composition, and nutraceutical characteristics of honey are strongly influenced by altitude, which determines ecological and geographical changes. Additionally, the quality of honey is influenced by microorganisms such as yeast and spore-forming bacteria; however, its natural properties and industry control measures keep microbial levels minimal (Thakur et al., \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Hence, monitoring honey quality parameters is of great importance to consumers\u0026rsquo; health. These analyses are essential for detecting adulteration and ensuring authenticity, as improper processing or contamination can compromise the beneficial properties of honey.\u003c/p\u003e \u003cp\u003eThe present study was conducted in Himachal Pradesh, located in the northwestern Himalayas at elevations ranging from 350 to 2200 meters above mean sea level, and encompasses a diverse array of agro-climatic zones, each characterised by distinct climatic conditions conducive to the cultivation of varied flora (Thakur et al., \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Thakur et al., \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This ecological diversity facilitates the production of both unifloral and multifloral honeys, each exhibiting unique physicochemical properties. The temperate climatic zone of this state fosters the growth of unique plant species, such as Plectranthus and Thyme, which are not commonly found elsewhere in India. For instance, Plectranthus is renowned for producing white honey and possesses high antioxidant properties, whereas Thyme honey is noted for its antimicrobial and antioxidant properties (Sharma et al., \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The state's diverse flora supports migratory beekeeping practices, ensuring a continuous nectar flow throughout the year and contributing to the development of multifloral honeys.\u003c/p\u003e \u003cp\u003eWhile numerous studies have examined the physicochemical parameters of multifloral honeys in India, there is a lack of research directly comparing the quality of multifloral honey produced by beekeepers in Himachal Pradesh. Therefore, this study is the first of its kind to assess the quality parameters, essential mineral content, and bacterial load of multifloral honey samples from various geographic regions of the northwestern Himalayas and verify their compliance with the Food Safety and Standards Authority of India (FSSAI) standards. The findings aim to provide valuable insights into the authenticity and quality of Himachal Pradesh's multifloral honeys, supporting their potential for Geographical Indication (GI) certification, enhancing market value and guiding beekeepers in conserving and cultivating multipurpose crops that serve as food plants for honey bees.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Area\u003c/h2\u003e \u003cp\u003eThe present study was conducted in the state of Himachal Pradesh, situated between 32.1024\u0026deg; N latitude and 77.5619\u0026deg; E longitude. The study area included all four agro-climatic zones of the state, namely Zone-1 (Sub-Mountain and sub-tropical, low hills zone, 350-650m amsl), Zone-2 (Mid hills, sub-humid zone, 651-1840m amsl), Zone-3 (High hills, temperate wet zone, 1801-2200m amsl), and Zone-4 (High hills, temperate dry zone, 2200m amsl \u0026amp; above.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample Collection\u003c/h3\u003e\n\u003cp\u003eA total of 36 \u003cem\u003eApis mellifera\u003c/em\u003e honey samples with three replications (108 samples) were obtained across all four agro-climatic zones of Himachal Pradesh. From each zone, three districts, viz., Hamirpur, Bilaspur, and Una from Zone-1; Kangra, Mandi, and Solan from Zone-2; Shimla, Sirmaur, and Kullu from Zone-3; Chamba, Kinnaur, and Lahaul Spiti from Zone-4 were selected for sample collection. Further, from each district, three apiaries were selected, and from each apiary, three samples were collected and processed further for melissopalynological, physicochemical, and mineral characteristics.\u003c/p\u003e\n\u003ch3\u003eMelissopalynological studies\u003c/h3\u003e\n\u003cp\u003eHoney samples were prepared for melissopalynological analysis following the procedure described by Louveaux et al., (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1978\u003c/span\u003e) and the International Commission on Bee Botany (ICBB) (Von Der Ohe et al., \u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The prepared pollen slides were then observed under a trinocular microscope (OLYMPUS CX41), and the microphotographs were taken by a camera (SONY Model SSC-E413P) attached to the trinocular microscope. Pollen grains were identified based on photomicrographs, shape, size, aperture type, exine surface, and aggregation pattern. To further authenticate their identification, identified pollen slides available in the Department of Entomology, College of Horticulture, Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan, HP, India; ICBB recommendations and standard works done by Erdtman (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1969\u003c/span\u003e) and Nair (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1985\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor quantitative analysis, identified and counted pollen grains were assigned to different frequency classes viz., predominant pollen types (\u0026gt;\u0026thinsp;45% pollen count); secondary pollen types (16\u0026ndash;45%); minor pollen types (3\u0026ndash;15%) and rare pollen types (\u0026lt;\u0026thinsp;3%) according to the number of pollen grains in each sample (Louveaux et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1978\u003c/span\u003e; Von Der Ohe et al., \u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Ozler \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Honey was termed as unifloral (if single pollen type of particular plant species\u0026thinsp;\u0026gt;\u0026thinsp;45%) and multifloral (if several pollen types with less percentage) (Iwama and Melhem \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Sharma \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e1989\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on their melissopalynological characteristics, twenty-six honey samples were identified as multifloral honeys (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), and the locations from where these multifloral honeys were obtained are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. This study is specifically dedicated to elucidating the physicochemical and mineral characteristics inherent to these specific multifloral honey samples.\u003c/p\u003e\n\u003ch3\u003ePhysicochemical characteristics\u003c/h3\u003e\n\u003cp\u003eThe physicochemical characteristics of honey samples were determined using standard analytical procedures. The pH of honey was assessed using a pH meter (EUTECH pH 700) following AOAC (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) guidelines. The measurement of honey's electrical conductivity (EC) was conducted utilizing a conductivity meter (Thermo Scientific EUTECH CON 150) as per the method described by Jackson (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Moisture content was estimated by oven-drying approximately 5 g of honey at 103\u0026deg;C until constant weight was achieved (Bogdanov et al.,2004). Optical density was measured at 560 nm using a spectrophotometer without dilution, using distilled water as a blank (Townsend, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e1969\u003c/span\u003e). The density of the honey sample was determined at 27\u0026deg;C according to the BIS (1994) procedures. For sugar determination (glucose, fructose, sucrose), the methods established by ISI, 1974 were used. Acidity and ash content were determined through the titrimetric approach outlined in the AOAC method 962.19 (AOAC, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Vitamin C and diastase activity were estimated according to AOAC (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), respectively. Hydroxymethylfurfural (HMF) content was determined using Fiehe\u0026rsquo;s test followed by spectrophotometric measurement at 540 nm as described by Schade et al. (\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e1958\u003c/span\u003e). Total phenolic content was determined using the Folin\u0026ndash;Ciocalteu method following Singleton et al. (\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), while proline content was estimated using standard AOAC (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1984\u003c/span\u003e) methods. Antioxidant activity was assessed using the DPPH assay following the method of Isla et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eMineral composition\u003c/h3\u003e\n\u003cp\u003eFor mineral estimation, honey samples (1 g) were digested using a diacid mixture of nitric acid and perchloric acid (4:1). The concentrations of minerals were determined using standard analytical procedures as described by Jackson (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1973\u003c/span\u003e) and Sarma et al. (\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e1987\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBacterial load\u003c/h2\u003e \u003cp\u003eMicrobial load was determined using the standard plate count method (Wollum, \u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). Results were expressed as log CFU g⁻\u0026sup1; of honey using the formula:\u003c/p\u003e \u003cp\u003eLog CFU/g\u0026thinsp;=\u0026thinsp;Log (CFU \u0026times; dilution factor \u0026times; 1/aliquot)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePrincipal Component Analysis (PCA)\u003c/h3\u003e\n\u003cp\u003ePrincipal Component Analysis (PCA) was carried out using R software to evaluate the variability among honey samples and to identify the major contributing physicochemical and biochemical parameters. Prior to analysis, data were standardized by centering and scaling. Components with eigenvalues greater than 1 were retained according to the Kaiser criterion, and loading scores (factor loadings) were used to interpret the contribution of individual variables.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInformation on multifloral honey samples from different regions of Himachal Pradesh\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgroclimatic Zones\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistricts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRegions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample Code\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eZone-1 (Sub-Mountain and sub-tropical, low hills zone)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHamirpur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNadaun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS1H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKharwar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS2H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBarsar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS3H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBilaspur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLehri Sarail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS4H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBhatoli\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS5H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBerthin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS6H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBangana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS7H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eZone-2 (Mid hills, sub-humid zone)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKangra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNurpur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS8H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMandi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChachyot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS9H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSandhol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS10H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSolan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS11H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKunihar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS12H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eZone-3 (High hills, temperate wet zone)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eShimla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRohru\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS13H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJubbal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS14H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSirmaur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNohradhar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS15H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRajgarah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS16H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShillai\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS17H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKullu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKharihar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS18H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBajaura\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS19H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eZone-4 (High hills, temperate dry zone)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eChamba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLahal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS20H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBanikhet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS21H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBakan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS22H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKinnaur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKarcham\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS23H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNichar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS24H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLahaul Spiti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekeylong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS25H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGondhla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS26H\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eCluster analysis\u003c/h3\u003e\n\u003cp\u003eHierarchical cluster analysis was performed using a binary presence\u0026ndash;absence matrix of pollen types across honey samples. The analysis was conducted in R software, and the results were visualized using heatmaps and dendrograms to assess similarities among samples.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMelissopalynological analysis of honeys\u003c/h2\u003e \u003cp\u003eAmong all the multifloral honey samples, a total of ninety-six pollen morphotypes were obtained. The results of the pollen spectrum, along with their frequency in all the multifloral honeys are provided in supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All the multifloral honeys contained varied pollen frequencies with maximum frequency for secondary pollen types (16\u0026ndash;45%), as they are the major source of pollen grains in these multifloral honeys and influenced the physicochemical property of particular honey. These secondary pollen sources varied in all the multifloral honeys depending upon their availability in a particular region and preference as nectar sources for honey bees. The majority of multifloral honeys belonged to the family Fabaceae, followed by Asteraceae. Harbouring a wide floral diversity of the Fabaceae family in Himachal Pradesh could be the probable reason for dominance in this zone (Rana et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Findings of the present study corroborated with the findings of other research, for example, Saklani and Mattu (2022), and Ukanyirioha et al., (\u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported greater floral diversity from Himachal Pradesh and Nigeria, respectively, with the highest pollen types from the Fabaceae family, followed by Asteraceae.\u003c/p\u003e \u003cp\u003eThe Zone-1 and Zone-2 of Himachal Pradesh are suitable for beekeeping due to wide diversity and availability of various types of bee flora during the spring-summer seasons (Feb.-April), thus contributing to mixed floral honeys during the spring-summer season. The major flora reported in the present study were \u003cem\u003eAdhatoda\u003c/em\u003e sp., \u003cem\u003eDalbergia\u003c/em\u003e sp., \u003cem\u003eCassia\u003c/em\u003e sp., \u003cem\u003eEucalyptus\u003c/em\u003e sp., \u003cem\u003eSyzygium\u003c/em\u003e sp., and \u003cem\u003eAlbizia\u003c/em\u003e sp. The availability of these floras from lower and mid hills as bee forage in the present study is supported by the previous documentation of Verma (\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), Singh and Sharma (\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), and Saklani and Mattu (\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) from Himachal Pradesh. Similarly, Sahney et al., (\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), Tripathi et al., (\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) documented these pollen grains from honeys of Varanasi (UP) and Assam, respectively. The \u003cem\u003eRobinia\u003c/em\u003e, \u003cem\u003eAesculus\u003c/em\u003e, pome, and stone fruits pollens are found as major flora in Zone-3, as this zone is suitable for beekeeping due to the abundance of autumn honey-flow sources. Song et al., (\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) also reported predominant pollen grains of \u003cem\u003eRobinia pseudoacacia\u003c/em\u003e and \u003cem\u003eVitex negundo\u003c/em\u003e from South China. The Zone-4 is not commercially practised for beekeeping; however, some autumn honey-flow forage plants are found in this region. During autumn, some beekeepers migrate their colonies to these areas to avail honey from different floral sources, viz., \u003cem\u003eThyme\u003c/em\u003e, \u003cem\u003ePlectranthus\u003c/em\u003e, and \u003cem\u003eFagopyrum\u003c/em\u003e as \u003cem\u003ePlectranthus\u003c/em\u003e known for white honey production provides surplus honey during Sept. \u0026ndash; Oct. Nair (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1964\u003c/span\u003e) also reported similar findings from the Himalayan region of India, and El Sohaimy et al., (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) from Kashmir honey.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePhysicochemical characteristics\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003ePollen density\u003c/h2\u003e \u003cp\u003ePollen density is an important characteristic of honey that helps to detect adulteration and determine its geographical and botanical origin, with raw honey containing more pollens, while adulterated honey has far less than processed honey (Sharma et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In the present study, the average pollen density varied from 42,000 (4.62) to 5,45,000 pollen grains per 10g (5.74), with a significant difference among the multifloral honeys (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The lowest pollen density was recorded for honey from S2H honey of Zone-1, low hills (42,000 pollen grains/10g), whereas the highest was reported from S10H honey of Zone 2, mid-hills (5,45,000 pollen grains/10g), respectively. The S2H honey contains \u003cem\u003eCitrus\u003c/em\u003e sp. and \u003cem\u003eBauhinia\u003c/em\u003e sp. as secondary pollen types, which produce less nectar and thus attract fewer honey bees, resulting in lower pollen counts in the honey (Yao et al., \u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In contrast, S10H honey contains pollens from \u003cem\u003eBombax\u003c/em\u003e sp., \u003cem\u003eGrewia\u003c/em\u003e sp., and \u003cem\u003eSyzygium\u003c/em\u003e sp. as these plants contained more nectar, thus more attractive to bees, resulting in high pollen count (Djonwangwe et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Shishira et al., (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) also reported high pollen density (99,000 pollens/10g) in \u003cem\u003eSyzygium\u003c/em\u003e honey from Bangalore. However, all the studied samples contained pollen grains more than the minimum limit (\u0026gt;\u0026thinsp;5000/g of honey) of pollen grains per gram of honey set by FSSAI (2020). These findings are in alignment with studies of Shobham and Nayar (\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), Shukla and Kumar (\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and Thakur et al., (\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who reported a similar range of pollen density in honey from Telangana, Uttar Pradesh, and Himachal Pradesh, respectively.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003epH\u003c/h2\u003e \u003cp\u003eThe pH of honey serves as a key indicator of its freshness and stability, affecting its texture, aroma, and shelf life (Hajian-Tilaki, 2014). Honey naturally exhibits acidity, with pH values ranging from about 3.5 to 5.5 due to the presence of organic acids, which contribute not only to its flavour but also its resistance to microbial spoilage (Da Silva, 2016). The pH values in the current study were found to be acidic, ranging from 3.97 to 5.96 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating the freshness of all honeys. However, S3H multifloral honey from Zone-1 had significantly lower pH (3.97), indicating the freshness of the honey sample as compared to S2H multifloral honey (5.96) of a similar zone. The reason could be due to long-term storage of honey or variation in the floral source. As S3H honey with low pH contained \u003cem\u003eCassia\u003c/em\u003e sp. and \u003cem\u003eAlbizia\u003c/em\u003e sp. as important food sources, as compared to \u003cem\u003eCitrus\u003c/em\u003e sp. and \u003cem\u003eBauhinia\u003c/em\u003e sp. as pollen sources in S2H honey. This variation may create pH variation for the same reason, as different floral sources contribute varying amounts of organic acids, minerals, and other compounds that affect the overall acidity (Pasca et al., 2021). Amir et al., (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) observed that honey samples with a pH below 4 degrade more rapidly during storage, suggesting that samples exceeding this threshold are comparatively fresher. The pH results are in the range reported by Thakur et al., (\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) (4.65\u0026ndash;5.94), Parihar et al., (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) (3.60\u0026ndash;4.80) for Himachal honeys, Kumar et al., (2018) (3.81\u0026ndash;4.85), and Kamboj et al., (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) (4.8\u0026ndash;5.8) for North Indian honeys. The variations in honey pH levels can result from factors such as the floral sources of nectar, the salivary secretions of bees, enzymatic processes, and the fermentative conversion of raw materials during honey production.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eElectrical conductivity (EC)\u003c/h2\u003e \u003cp\u003eThe electrical conductivity (EC) of honey is influenced by its content of inorganic salts, organic acids, proteins, complex sugars, and minerals; higher concentrations of these components result in increased EC (Dobrinas et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). EC is utilised to differentiate between honeydew and blossom honeys, with values exceeding 0.8 mS/cm indicating honeydew honey, and those below 0.8 mS/cm indicating blossom honey (Bogdanov et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). According to the EC values, the present analysed honey samples were blossom honey, as electrical conductivity ranged between 0.13\u0026ndash;0.740 mS/cm. The lower EC (0.13mS/cm) was reported in S22H multifloral honey of Zone-4, which is statistically at par with S26H honey (0.14mS/cm) of similar zone and S16H honey (0.14mS/cm) of Zone-3, whereas the highest EC was reported in S2H honey (0.74mS/cm) of Zone-1 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Zone 4 of Himachal Pradesh, characterized by high-altitude terrain exceeding 2200 meters above mean sea level, supports natural fauna with minimal anthropogenic disturbance and low pollution levels. This pristine environment likely contributes to lower electrical conductivity (EC) values in honey, as EC increases with higher concentrations of inorganic ions, acids, and minerals (Solayman et al., \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The S22H honey of Zone-4 detected the lowest in EC content. The S2H honey from Zone-1 exhibited the lowest electrical conductivity (EC), likely due to the zone's sub-mountain and sub-tropical low-hill characteristics (350\u0026ndash;650 m amsl), which are significantly influenced by urbanization, agricultural activities, and agrochemical use. This aligns with reported EC values for honey from similar regions worldwide (Solayman et al., \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Thakur et al., \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mongi, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMoisture content\u003c/h2\u003e \u003cp\u003eIn present study moisture content varied from 14.34\u0026ndash;20.13 per cent with highest (20.13%) being recorded from S2H honey of Zone-1, which was statistically at par with S25H honey (20.07%) from Zone-4 and S3H honey (20.00%) of Zone-1, whereas lowest moisture content (14.34%) was recorded from S8H honey of Zone-2 which was statistically at par with S6H honey (14.77%) of Zone 1 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). According to the literature, moisture content plays a crucial role in determining its quality, stability, resistance to yeast fermentation, and tendency to granulate (Dung et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). In the present results, all the honeys had moisture content below the maximum permissible limit of moisture content (\u0026gt;\u0026thinsp;20%) set by FSSAI (2020), indicating proper maturity, except for S2H honey from Zone-1. The high moisture content in S2H honey may result from extracting unripe or unprocessed honey, harvesting during the rainy season, or fermentation caused by extended storage (Lavinas et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The moisture content recorded in the present study aligned with the results of Parihar et al., (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Attri (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) in honey from Himachal Pradesh and Gairola et al., (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) in honey from Uttarakhand.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eOptical density (colour)\u003c/h2\u003e \u003cp\u003eIn the present study optical density of honey for different multifloral honeys varied from extra white to amber, with optical density from 0.12\u0026ndash;2.41 (OD at 560nm) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Thus, the highest absorbance (2.41OD, Amber) was recorded from S9H multifloral honey of Zone-2, whereas the lowest (0.12 OD, Extra White) was from S13H honey of Zone-3. The variation in optical density could be due to variation in floral sources; S9H honey contained \u003cem\u003eSapindus\u003c/em\u003e sp., \u003cem\u003eDalbergia\u003c/em\u003e sp. and \u003cem\u003eTrifolium\u003c/em\u003e sp. as secondary pollen types, whereas S13H honey contained Malus \u0026times; domestica and Medicago denticulateas secondary pollen types. The dark colour of S9H honey may be attributed to its pollen sources and high mineral content (Sharma et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) as well as darkening caused by heating (Ramly et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The results of Escriche et al., (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) also reported amber colour in Thyme honey from Spain, thus supporting the present results. The observations support the findings of Nayik and Nanda (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and Albu et al., (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), where significant differences were observed in the optical densities of different multifloral honeys from Kashmir and Romania, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eDensity\u003c/h2\u003e \u003cp\u003eThe density of multifloral honeys in the present study varied from 1.35 to 1.61g/cm3, where the lowest density is recorded from S3H multifloral honey of Zone-1, though statistically at par with S4H honey of Zone-1, S8H and S11H honey of Zone-2, S13H and S16H honey of Zone-3, and S22H honey of Zone-4 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Highest density was recorded from S20H honey of Zone-2, which was statistically at par with S2H honey of Zone-1, S9H honey of Zone-1, S17H and S18H honey of Zone-3, and S25H honey of Zone-4. The density is an important property of honey and is also used as a purity test by consumers at home (Testa et al., \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The observed variations in density among different multifloral honeys may be attributed to differences in floral sources, chemical composition, moisture content, and the temperature conditions during processing and storage (Parihar et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the density of the present honey samples was within the range given by FSSAI (2020) (1.35g/cm3) and aligned with the results of Ahmed et al., (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), who reported density in different multifloral honeys in the range from 1.33-1.56g/cm3 in different multifloral honeys from Karnataka.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysical characteristics of multifloral honey samples from different regions of Himachal Pradesh\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRegions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZones\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePollen density (pollen grains per 10g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEC (mS/\u003c/p\u003e \u003cp\u003ecm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMoisture\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eOptical Density (OD at 560nm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eColour as per USDA colour standard\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDensity\u003c/p\u003e \u003cp\u003e(g/cm\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS1H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHamirpur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eZone-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80,000\u003c/p\u003e \u003cp\u003e(4.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS2H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42,000\u003c/p\u003e \u003cp\u003e(4.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS3H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60,000\u003c/p\u003e \u003cp\u003e(4.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAmber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS4H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBilaspur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71,000\u003c/p\u003e \u003cp\u003e(4.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS5H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,24,000\u003c/p\u003e \u003cp\u003e(5.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS6H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66,000\u003c/p\u003e \u003cp\u003e(4.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS7H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,30,000\u003c/p\u003e \u003cp\u003e(5.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLight Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS8H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKangra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eZone-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,80,000\u003c/p\u003e \u003cp\u003e(5.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS9H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMandi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82,000\u003c/p\u003e \u003cp\u003e(4.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAmber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS10H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,45,000\u003c/p\u003e \u003cp\u003e(5.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS11H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSolan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48,000\u003c/p\u003e \u003cp\u003e(4.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS12H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,95,000\u003c/p\u003e \u003cp\u003e(5.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLight Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS13H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eShimla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eZone-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,15,000\u003c/p\u003e \u003cp\u003e(5.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS14H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,10,000\u003c/p\u003e \u003cp\u003e(5.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS15H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSirmaur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,30,000\u003c/p\u003e \u003cp\u003e(5.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS16H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,00,000\u003c/p\u003e \u003cp\u003e(5.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS17H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,60,000\u003c/p\u003e \u003cp\u003e(5.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS18H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKullu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50,000\u003c/p\u003e \u003cp\u003e(4.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS19H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65,000\u003c/p\u003e \u003cp\u003e(4.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLight Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS20H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eChamba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eZone-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77,000\u003c/p\u003e \u003cp\u003e(4.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS21H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,30,000\u003c/p\u003e \u003cp\u003e(5.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS22H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65,000\u003c/p\u003e \u003cp\u003e(4.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS23H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKinnaur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,20,000\u003c/p\u003e \u003cp\u003e(5.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS24H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,20,000\u003c/p\u003e \u003cp\u003e(5.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS25H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLahaul Spiti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75,000\u003c/p\u003e \u003cp\u003e(4.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS26H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58,000\u003c/p\u003e \u003cp\u003e(4.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eExtra Light Amber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCD \u003csub\u003e(0.05)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eSugars\u003c/h2\u003e \u003cp\u003eThe honey comprises mainly fructose and glucose (monosaccharides), and additionally comprises around 25 different oligosaccharides (Bogdanov, 2004). In the present investigation, the sugars, viz., glucose, fructose, and sucrose, content in different multifloral honeys varied from 25.23\u0026ndash;37.06 per cent, 31.7-40.66 per cent, and 2.74\u0026ndash;5.78 per cent, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The S24H honey of Zone-4 has the highest glucose content (37.06%), whereas the lowest glucose content was observed in S12H honey from Zone-2 (25.23%). Among all multifloral honeys, the highest fructose content was recorded in S25H honey (40.66%) from Zone-4, whereas the lowest fructose content was found in S15H honey (31.7%) from Zone-3. In terms of sucrose content, S3H of Zone-1 had the highest sucrose content (5.78%), which was statistically at par with S24H (5.65%) honey from Zone-4, whereas the lowest was recorded from S25H (2.74%) honey from Zone-4, which differed non-significantly from other multifloral honeys.\u003c/p\u003e \u003cp\u003eSignificant differences in the sugar composition of honey can arise from its botanical and geographical origins, as well as from climatic conditions, processing methods, and storage practices (Kamboj et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). All the honeys had sugar content within permissible limit except for samples S3H and S24H both had high sucrose content (\u0026gt;\u0026thinsp;5%), reasons of high sucrose content in these honeys may be due to feeding of honeybees with sugar syrup, harvesting of unripe honey and overheating of honey as earlier reported by Kamal et al., (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Parihar et al., (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) from honeys of \u003cem\u003eA. mellifera\u003c/em\u003e from Bangladesh and Himachal Pradesh, respectively.\u003c/p\u003e \u003cp\u003eHoney crystallization can be assessed by examining the glucose-to-fructose ratio, as crystallization is associated with increased glucose and decreased fructose levels (Abselami et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). F: G ratio varied from 0.93\u0026ndash;1.5 in different multifloral honeys, with the highest F: G ratio (1.5) reported in S25H honey of Zone-4 and S13H (1.5) honey from Zone-3, whereas the lowest F:G ratio was reported in S15H honey (0.93) of Zone-3 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Honey crystallisation is faster when the F:G ratio is below 1.0, and it slows when this ratio is more than 1.0 (Ouchemoukh et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Buba et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, and Draiaia et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Thus, most of the analyzed honey samples in the present study were of slow slow-crystallizing nature. The present study is supported by Kamboj et al., (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), Thakur et al., (\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who observed an F:G ratio within the range of (0.95\u0026ndash;1.50) for the honey in the North Indian states of India. El Sohaimy et al., (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e reported F: G ratio 0.42, 1.52, 1.63, and 2.35for Kashmiri, Yemeni, Egyptian, and Saudi honey, respectively, aligned with the present results. The variations in sugar content among different multifloral honeys may result from regional, seasonal, and floral differences, as well as extraction methods, while differences in the fructose\u0026ndash;glucose ratio could be influenced by the type of nectar and the location of honey collection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eAcidity\u003c/h2\u003e \u003cp\u003eAcidity influences honey\u0026rsquo;s flavour, microbial stability, chemical reactivity, and its antibacterial and antioxidant properties (Rani and Verma, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Elevated acidity indicates sugar fermentation leading to organic acid formation (Chidi et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), whereas low acidity reflects the freshness of honey samples (Adenekan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The acidity of the analyzed honeys varied from 17.40-49.36meq/kg (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among all the honeys, the highest acidity was recorded in S16H (49.36meq/kg) honey from Zone-2 which was statistically at par with S3H honey (48.59meq/kg), whereas the lowest was recorded in S2H honey (17.40meq/kg) of Zone-1, which was statistically at par with S25H honey of Zone-4 (19.65meq/kg) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). All the multifloral samples were below the maximum permissible limit of total acidity in honey samples (\u0026gt;\u0026thinsp;50meq/kg), indicating the freshness of all the honey samples. The floral sources for S2H honey were Citrus sp. and Bauhinia sp., which were responsible for lower acidity as reported earlier by Karabagias et al., (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) reported 12.64-21.61meq/kg in different citrus honeys from different Mediterranean countries.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eVitamin C\u003c/h2\u003e \u003cp\u003eVitamin C is present in nearly all types of honey, with its concentration and antioxidant activity largely influenced by the floral source, since most foraged flowers contain vitamin C; other factors affecting vitamin content include honey processing and storage (Perna et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Silva et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In the present study, the vitamin C content varied from 7.67 to 38.49 mg/100 g (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The S12H honey of Zone-2 had the highest vitamin C content of 38.49 mg/100 g, whereas the lowest was recorded in S19H (7.67mg/100g) honey of Zone-\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChemical characteristics of multifloral honey samples from different regions of Himachal Pradesh\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRegions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZones\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFructose\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF: G\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTotal Acidity (meq/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eVit.C\u003c/p\u003e \u003cp\u003e(mg/100g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAsh Content\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eFiehe\u0026rsquo;s Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eHMF (mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eEnzymes\u003c/p\u003e \u003cp\u003e(Diastase\u003c/p\u003e \u003cp\u003e/DN)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003ePhenol content\u003c/p\u003e \u003cp\u003e(mg/100g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eAmino Acid (mg/100g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eDPPH (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS1H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHamirpur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eZone-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e27.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e13.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e21.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e76.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e57.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e65.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS2H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e18.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e20.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e52.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e46.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e50.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS3H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e30.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e+ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e86.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e04.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e97.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e73.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e70.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS4H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBilaspur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e37.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e36.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e15.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e70.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e25.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e61.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS5H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e25.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e19.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e25.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e31.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e32.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS6H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e36.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e23.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e19.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e37.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e69.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e45.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS7H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e34.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e34.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e17.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e82.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e21.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e66.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS8H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKangra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eZone-2\u003c/p\u003e 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align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e29.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e21.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e57.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e57.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e54.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS25H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLahaul Spiti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e21.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e22.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e29.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e90.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e85.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e68.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS26H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e19.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-ve\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e30.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e73.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e62.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e62.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCD \u003csub\u003e(0.05)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMineral composition of multifloral honey samples from different regions of Himachal Pradesh\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRegions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZones\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCa (mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMg (mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP (mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eK (mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eZn (mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNa (mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eFe (mg/kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMn (mg/kg)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS1H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHamirpur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eZone-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e129.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e348.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e119.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS2H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e112.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e119.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e546.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e135.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS3H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e194.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e204.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS4H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBilaspur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e210.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e186.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS5H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e148.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e 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align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS18H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKullu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e182.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e894.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e166.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS19H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e199.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e120.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS20H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eChamba\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eZone-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e882.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e122.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS21H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e734.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e178.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS22H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e780.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e166.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS23H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKinnaur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e140.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e542.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e120.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS24H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e346.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e141.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS25H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLahaul Spiti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e594.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e151.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS26H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e933.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e131.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD\u003csub\u003e(0.05)\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e3. The floral sources for S12H honey were \u003cem\u003eBauhinia\u003c/em\u003e sp., \u003cem\u003eLonicera\u003c/em\u003e sp., and \u003cem\u003eJacaranda sp\u003c/em\u003e., whereas for S19H honey, the floral sources were \u003cem\u003eSapindus\u003c/em\u003e sp., \u003cem\u003eBrassica\u003c/em\u003e sp., and \u003cem\u003eTrifolium\u003c/em\u003e sp. Various studies by Ahmed et al., (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), Naz et al., (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and Orsavova et al., (2022) reported \u003cem\u003eBauhinia\u003c/em\u003e, \u003cem\u003eJacaranda\u003c/em\u003e, and \u003cem\u003eLonicera\u003c/em\u003e plants as a high source of vitamin C, respectively; thus, these trees produce honey that has more vitamin content.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eAsh content\u003c/h2\u003e \u003cp\u003eThe ash content in honey is generally small and depends on the nectar composition of predominant plants in their formation (Felsner et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). In the present study, ash content varied from 0.02\u0026ndash;0.42 per cent, with the highest being recoded from S2H honey (0.42%) of Zone-1, whereas the lowest was from S9H (0.02%) and S14H (0.02%), from Zone-2 and 3, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The floral sources for S2H honey were \u003cem\u003eCitrus\u003c/em\u003e sp. and \u003cem\u003eBauhinia\u003c/em\u003e sp., and for S9H honey were \u003cem\u003eSapindus\u003c/em\u003e sp., \u003cem\u003eDalbergia\u003c/em\u003e sp. and \u003cem\u003eTrifolium\u003c/em\u003e sp., and for S14H honey were \u003cem\u003ePrunus\u003c/em\u003e sp. and \u003cem\u003eTrifolium\u003c/em\u003e sp. The soil type in which the original nectar-bearing plant was located also influences the quantity of minerals present in the ash (Da Silva et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Felsner et al., (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and Nanda et al., (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) also reported high Ash content for citrus honey from Brazil and Punjab, respectively. There was also a linear relationship between the ash content and the EC (El Sohaimy et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), which supports our results as S2H honey had also the highest EC content (0.74mS/cm), indicating good quality of Himachal multifloral honeys.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.2.11 Hydroxy methyl furfuraldehyde\u003c/b\u003e \u003c/p\u003e \u003cp\u003eHMF levels in honey serve as an indicator of excessive heating, prolonged storage, or adulteration with invert sugars (Godoy et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), with higher HMF content reflecting lower honey quality (Parihar et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In the present analysis, HMF content varied from 6.59-86 mg/kg (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), S3H honey of Zone-1 was recorded with the highest HMF content (86mg/kg), which was also reported positive in Fiehe\u0026rsquo;s test, whereas the lowest HMF content (6.59mg/kg) was reported from S36H honey of Zone-4. According to the results, the examined honey samples, except S3H honey, were within the legal permissible limit (\u0026gt;\u0026thinsp;80mg/kg) of FSSAI (2020). The reason of very high HMF of this sample is due to various reasons, viz., adulteration with sugar additives, severe heat treatment, and inadequate and prolonged storage (Choudhary et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Iftikhar et al., (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and Afshari et al., (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) also reported very high HMF from honey samples of Pakistan and Iran, respectively, indicating low quality of these honeys.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eEnzymes (Diastase/DN)\u003c/h2\u003e \u003cp\u003eThe diastase content of all the analysed multifloral honeys in the current study varied from 4.53 to 30.48 DN (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The S26H Honey of Zone-4 was recorded with the highest diastase content (30.48 DN), though statistically at par with S25H honey (29.79 DN) of Zone-4, whereas the lowest diastase content was reported in S3H honey (4.53 DN) of Zone-1. The floral sources for S26H honey were \u003cem\u003ePlectranthus\u003c/em\u003e sp., \u003cem\u003eNigella\u003c/em\u003e sp., and \u003cem\u003eFagopyrum\u003c/em\u003e sp., for S25H honey were \u003cem\u003eFagopyrum\u003c/em\u003e sp. and \u003cem\u003ePlectranthus\u003c/em\u003e sp., whereas for S3H honey were \u003cem\u003eCassia\u003c/em\u003e sp. and \u003cem\u003eAlbizia\u003c/em\u003e sp. Diastase (alpha and beta amylase) is one of the predominant enzymes in honey, which is added to honey by the bee during the collection and ripening of flower nectar (Sharma et al., \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Variations in present results could be due to different floral sources, overheating, and long storage, as effects of these factors are already reported by Buba et al., (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), Thakur et al., (\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and Sireli et al., (2025). However, all the honeys had diastase above the minimum permissible limit fixed by FSSAI (2020), indicating the freshness of all the honey samples. \u003cb\u003ePhenol content\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe phenolic compounds play a major role in the antioxidant activity, which depends on the species of plant from which bees collected the nectar (Yayinie et al., \u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the present study, phenol content varied from 12.96 to 108.54 mg/100 g (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The highest phenol content was recorded in S9H honey (108.54mg/100g) from Zone-2, whereas the lowest was in S13H honey (12.96mg/100g) of Zone-3. Floral sources for S9H honey were \u003cem\u003eSapindus\u003c/em\u003e sp. \u003cem\u003eDalbergia\u003c/em\u003e sp. and \u003cem\u003eTrifolium\u003c/em\u003e sp., whereas for S13H honey, they were \u003cem\u003eMalus\u003c/em\u003e \u0026times; \u003cem\u003edomestica\u003c/em\u003e and \u003cem\u003eMedicago denticulate\u003c/em\u003e. Oroian and Ropciuc (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e mentioned in their study that phenolic compounds play a major role in the antioxidant activity, and their content depends on the species of plant from which bees collected the nectar. The phenol content variations recorded in the present multifloral honeys supported by the findings of Pham et al., (2020) and Ikegbunam et al., (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) reported phenol content from 89-110mg/100g and 3.75-90.12mg/100g from different multifloral honeys of Vietnam and Nigeria, respectively. In contrast, Yayinie et al., (\u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported very low phenol content from 17.03-42.04mg/100g from different honeys of Ethiopia, thus stating that Himachal Pradesh honey had high phenol content, making it a good antioxidant source (Sharma et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eAmino acid (proline) content\u003c/h2\u003e \u003cp\u003eAmino acid content in present study varied from 18.19-113.98 mg/100g (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), with highest being recorded in S16H honey (113.98mg/100g) of Zone-3, whereas lowest amino acid was reported in S11H honey (18.19mg/100g) of Zone-2 which was statistically at par with S19H honey (19.93mg/100g) of Zone-3. The floral sources for S16H honey were \u003cem\u003ePrunus persica\u003c/em\u003e and \u003cem\u003eTrifolium\u003c/em\u003e sp., whereas for S11H honey were \u003cem\u003eAlbizia\u003c/em\u003e sp., \u003cem\u003eWoodfordia\u003c/em\u003e sp., and \u003cem\u003eJacaranda\u003c/em\u003e sp. Pollen represents the main source of proteins; therefore, the amino acid profile of honey could be characteristic of its botanical origin and geographical origins. Proline, the predominant amino acid in honey, accounting for 50\u0026ndash;80 per cent of total amino acids (Sharma et al., \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), is produced by honeybee salivary secretions during nectar conversion. Its levels gradually decline during storage, making proline a potential indicator of honey ripeness. Thus, the proline content varied among all the honeys, but all are within the permissible limit of FSSAI (Minimum content 180mg/kg of honey). Present values for proline content aligned with results of Tarapatskyy et al., (\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported proline (184.44\u0026ndash;277.52 mg/100g) from Polish honey, Bouhlali et al., (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) (441-1207mg/kg) from Moroccan honey, and Thakur et al., (\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) (3.83-79.53mg/100g) from Himachal honey. Various findings reported higher proline content reported by Khalil et al., (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) from Algerian honey (3381.83 mg/kg), Afshari et al., (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) (115-640mg/kg) from Iran honey, and Erdogan and Turan (2022) (530-710mg/kg) from Turkey honey.\u003c/p\u003e \u003cp\u003e \u003cb\u003e1,1-diphenyl-2-picrylhydrazyl (DPPH) Content\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDPPH content in the present study varied from 16.49\u0026ndash;78.84 per cent, with the highest DPPH content reported in S9H honey (78.84%) of Zone-2, whereas the lowest was reported from S13H honey (16.49%) of Zone-3 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). DPPH is a widely used assay that measures honey\u0026rsquo;s ability to neutralise free radicals, serving as a reliable indicator of its overall antioxidant potency (Lewoyehu and Amare, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The antioxidant activity of honey is affected by the presence of polyphenols, enzymes, amino acids, proteins, α-tocopherol, and vitamins. The S9H honey had highest phenol (108.54mg/100g) and optical density (2.41, amber colour) as compared to S13H honey had lowest phenol (12.96mg/100g) and optical density (0.12, extra white colour), these findings are consistent with previous studies, which reported a strong positive correlation between honey colour, its antioxidant activity, and total phenolic content (TPC) (Bertoncelj et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Nayik and Nanda \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Nayik et al., 2016). The antioxidant properties of honey are also affected by environmental conditions as well as its floral and geographical origins (Nayik et al., 2016). Therefore, variation in DPPH content in the present study due to varied floral sources and regions aligned with previous results of Saxena et al., (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and Kamboj et al., (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The pollen sources for S9H honey were \u003cem\u003eSapindus\u003c/em\u003e sp. \u003cem\u003eDalbergia\u003c/em\u003e sp. and \u003cem\u003eTrifolium\u003c/em\u003e sp. contributed to high DPPH content in honey, as compared to S13H honey, which had \u003cem\u003eMalus\u003c/em\u003e \u0026times; \u003cem\u003edomestica\u003c/em\u003e and \u003cem\u003eMedicago denticulate\u003c/em\u003e as important pollen sources. Nayik et al., (2016) reported that the antioxidant properties of apple honey significantly decreased with an increase in pH and thermal treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eMineral composition\u003c/h2\u003e \u003cp\u003eHoney is rich in macro and microminerals, and analysis of these minerals is important in order to detect environmental pollution, especially to detect heavy metals, and is also an indicator of botanical and geographical origin (Soares et al., \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The mineral content in different multifloral honeys is presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. In the present study, the Calcium (Ca) content in all the analysed samples varied from 79.48 to 193.98mg/kg. Among all the multifloral honeys, the significantly highest Ca content was recorded in S12H (193.98 mg/kg) honey from Zone-2, though statistically at par with S20H honey (189.5mg/kg) of Zone-4, whereas the lowest Ca content was found in S3H honey (79.48mg/kg) of Zone-1. The Magnesium (Mg) content in the present samples varied from 22.44-89.20mg/kg. Among all the samples, the highest Mg content was recorded in S2H honey (89.20mg/kg) from Zone-1, whereas the lowest was in S26H (22.44mg/kg) honey from Zone-4. The Phosphorus (P) content varied from 2.5-119mg/kg, with the highest being recorded from S2H honey (119mg/kg) from Zone-1, whereas the lowest was from S22H honey (2.5mg/kg) of Zone-4. The potassium (K) content in all multifloral honeys varied from 194.99-933.24mg/kg. The highest K content was found in S26H honey (933.24mg/kg) from Zone-4, whereas the lowest K content (194.99mg/kg) was in S3H honey of Zone-1. The Zinc (Zn) content in all multifloral honeys varied from 4.8 to 24.2mg/kg. Among all multifloral honeys, S10H honey from Zone-2 was reported with the highest Zn content (24.2mg/kg), whereas the lowest was from S4H honey of Zone-1. The sodium (Na) content in the present investigation varied from 116 to 212mg/kg. Among all honeys, S5H honey from Zone-1 reported the highest Na content (212mg/kg), whereas S13H honey from Zone-3 reported the lowest in Na content (116mg/kg). The iron (Fe) content in all the multifloral honeys varied from 2.91-6.08mg/kg. The highest Fe content was recorded in S16H honey (6.08mg/kg), whereas the lowest was in S23H honey (2.91mg/kg) of Zone-4. The manganese (Mn) content varied from 0.5-4.7mg/kg, with the highest being recorded from S18H honey (4.7mg/kg) of Zone-3, whereas the lowest Mn content was in S4H honey (0.5mg/kg) of Zone-1.\u003c/p\u003e \u003cp\u003eOur study found that honey samples contained several minerals, viz., Ca, Mg, K, P, Zn, Na, Fe, Mn, and P, with K, Mg, and Ca being the most abundant as reported earlier by Thakur et al., \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Muhammad and Sarbon, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, and Mongi, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2024\u003c/span\u003e. Mineral content in all honeys was within the range recommended by the USDA (\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). The present results for different mineral contents fall within those reported by Terrab et al., (\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) from different floral honey of Spanish and Bouhlali et al., (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) from Moroccan honey. In contrast, Thakur et al., (\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported mineral content viz., Ca (43.43-81.04mg/kg), Mg (27.16-35.40mg/kg), P (43.57-62.93mg/kg), K (286.18-354.17mg/kg) and Na (97.44-216.74mg/kg) from different locations of Himachal Pradesh, our results showed significantly higher concentrations of these minerals. This elevation may be attributed to the distinct floral diversity of our sampling sites (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), as well as geographic factors that influence mineral uptake (Pavlin et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Although the overall trend of mineral concentration across all zones remains similar. This could be due to the reason that higher altitude areas (Zone-4) are less impacted by human activity and industrial zones, thus showing lower mineral content compared to lower zones (Zone-1 and 2) (Salim et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The other reason may be greater pesticide usage and more intensive agriculture in the lower-altitude zones, which may also contribute to increased mineral uptake into honey (Vlad et al., \u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eBacterial load\u003c/h2\u003e \u003cp\u003eMicrobes are indicators of hygienic quality and their load in honey depends upon age, season, hygienic harvesting, packaging and harvesting (Snowdon and Cliver, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). The bacterial load in different multifloral honeys varied from 2.3 to 4.32 log CFU/g (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The highest bacterial load (4.31 log CFU/g) was recorded in S11H honey of Zone-2, whereas, significantly lower bacterial load was recorded in S22H honey (2.3 log CFU/g) of Zone-4. The bacterial load found in the present study was within the safety limits for consumption (\u0026lt;\u0026thinsp;10 \u003csup\u003e5\u003c/sup\u003e CFU/g). The bacterial count of the present study was within the values, \u003cem\u003eviz.\u003c/em\u003e, 1.47\u0026ndash;4.6 Log CFU/g and 3.55\u0026ndash;4.17, as reported by Hosny et al., (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Thakur et al. (\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) for honeys from Egypt and North India, respectively. The bacterial load in present study is comparatively lower than as documented by Oshomah and Ummulkhair (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), Adadi and Obeng (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Pajor et al., (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) \u003cem\u003eviz.\u003c/em\u003e, 4.0\u0026ndash;8.0 Log CFU/g, 5.5\u0026ndash;24.0 Log CFU/g and 3.04\u0026ndash;6.27 log CFU/g for honeys from Nigeria, Ghana and Poland, respectively indicating appropriate management of bee hives and hygienic conditions maintained by the beekeepers of Himachal Pradesh during harvesting, packaging of honey and environmental conditions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003ePCA\u003c/h2\u003e \u003cp\u003eThe Principal Component Analysis (PCA) results revealed eight principal components with eigenvalues greater than 1, following the Kaiser Criterion. These components cumulatively accounted for approximately 80.33% of the total variance in the dataset (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Specifically, PC1 explained 17.0 per cent, PC2 14.8 per cent, PC3 13.0 per cent, and PC4 10.5 per cent of the variance, while PC5 to PC8 each contributed between 5.2 per cent and 8.3 per cent, respectively. The PCA biplot (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) demonstrated the separation of honey samples based on their geographical zones, suggesting distinct physicochemical profiles. While some overlap was present, zone-wise grouping was evident, especially for samples with distinct physicochemical profiles. The individual plot provided further evidence of this natural separation, with tighter clustering seen in certain agro-climatic regions, indicating more consistent physicochemical traits within those zones. The factor loadings for the top 8 principal components given in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e revealed that PC1was predominantly influenced by high positive loadings from total acidity, ash, HMF, and phosphorus, while showing strong negative associations with optical density (OD), fructose, sucrose, F:G ratio, amino acid, potassium, manganese, and diastase content. This contrast suggested that PC1 differentiates honey samples rich in minerals and acidity from those dominated by sugars and antioxidant-related compounds. PC2 revealed positive loadings from vitamin C, ash, DPPH, calcium, and magnesium, indicating antioxidant and mineral richness, whereas negative loadings from electrical conductivity, glucose, phenol, sodium, iron, and manganese imply a trade-off between mineral content and antioxidant properties. PC3 was positively loaded with EC, moisture, sucrose, amino acids, phosphorus, zinc, and iron, indicating a component related to hydrophilic and micronutrient-rich honey profiles. Conversely, it was negatively associated with fructose, OD, vitamin C, DPPH, calcium, and magnesium, separating samples by differences in sugar types and antioxidant contents. PC4 was shaped by positive contributions from density, total acidity, DPPH, and phosphorus, while negative loadings from moisture, HMF, magnesium, zinc, and manganese suggest a component that contrasts denser, acidic honeys with those prone to oxidative degradation. In PC5, vitamin C, ash, DPPH, magnesium, iron, and sodium contributed positively, highlighting nutrient-rich honeys. Negative loadings from OD, fructose, sucrose, and F:G imply that this component distinguishes between nutritional quality and sugar profiles. PC6 reflected a simpler contrast, with positive loadings for fructose, potassium, and amino acid and negative loadings from moisture, vitamin C, magnesium, phosphorus, zinc, sodium, and iron, suggesting a potassium-dominant component inversely related to water and antioxidant levels. PC7 was positively associated with EC, fructose, sucrose, enzymes, and potassium, linking it to metabolically active and floral-origin indicators, while negative contributions from total acidity, HMF, phenol, and manganese may reflect oxidative stability. PC8 was positively influenced by amino acids and pH, while negatively loaded on OD, glucose, HMF, enzymes, phenol, magnesium, potassium, and manganese, suggesting this component differentiates fresh, proteinaceous honey from those with high degradation or pigment concentrations.\u003c/p\u003e \u003cp\u003eThe visual separation of samples in the Principal Component Analysis (PCA) biplot and individual score plots highlighted a distinct zone-wise clustering of multifloral honey samples. This spatial grouping suggested that geographical origin significantly influences the physicochemical characteristics of honey. Specifically, honey samples from similar agro-climatic regions exhibited tighter clustering, implying consistency in floral sources and environmental factors affecting nectar composition. These findings support earlier research that links honey variability to environmental parameters such as floral diversity, soil mineral content, climate conditions, and beekeeping practices. The observed clustering is consistent with previous studies that used chemometric techniques to classify honey based on origin and composition (Chakir et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Sakac et al., 2019 and Thakur et al., \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These studies demonstrated that physicochemical parameters, when analyzed through multivariate methods, are reliable markers for honey authentication and can be effectively used to verify botanical or geographical origin. The present results corroborate that agro-climatic influence is a key determinant in honey composition, thus emphasizing the importance of regional profiling in quality assurance and traceability of honey products.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEigenvalues and Explained Variance of Principal Components\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrincipal Component\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEigenvalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVariance Explained (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCumulative Variance (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactor loadings for principal components\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003epH\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePC1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePC2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePC3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePC4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePC5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePC6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePC7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePC8\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.092\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.075\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMoisture\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.296\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.523\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDensity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlucose\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.437\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFructose\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSucrose\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF:G\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal Acidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVitamin C\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAsh\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHMF\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.536\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEnzymes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.532\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhenol\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAmino Acid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDPPH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCa\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.530\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eK\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eZn\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNa\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFe\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMn\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eCluster analysis\u003c/h2\u003e \u003cp\u003eThe hierarchical clustering and heatmap based on presence-absence data of pollen species effectively depicted a two-dimensional clustering of honey samples (columns) and pollen grain species (rows) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The top (column) dendrogram divides honey samples into three clear clusters based on similar pollen profiles, among which the first cluster (blue) includes two honey samples, the second cluster (orange) contains six honey samples, and the third cluster (green) consists of eighteen honey samples. Similarly, the left dendrogram (row) groups plant species that co-occur across multiple honey samples, showing three major clusters. Among three, the first largest cluster (blue) contains ninety-two pollen types found in many honey samples and represents the most widespread pollens, the second cluster (orange) includes two pollen species that appear moderately across multiple samples, and the third (green) lists only two pollen species, which are very rare or sample-specific and found sporadically among all samples. Additionally, the red blocks in the heatmap show the presence of different pollen types (rows) across various honey samples (columns), with these blocks being more concentrated in the upper region than at the bottom. Thus, cluster analysis using hierarchical dendrograms unveiled complex relationships among honey samples from different geographical zones and botanical origins. The heatmap results suggest that floral diversity varies significantly across the different honey samples. Among the honey sample clusters (top), the first cluster predominantly included S20H and S22H honey samples, both from Zone-4. The reason for the occurrence of both types of honeys could be due to the similar climatic conditions, which favour some unique flora in this zone, which likely contributes to the similar pollen grains in these honeys. Clusters two and three contained samples from all four zones; this could be due to some common flora found in these honey samples. These findings align with Onyango (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Escuredo et al., (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), who used dendrograms to differentiate different polyfloral honeys, showing that pollen-based clustering sheds light on bee foraging behavior and seasonal flower availability.\u003c/p\u003e \u003cp\u003eExamining pollen types more closely, the first cluster on the left side included many rare or location-specific pollens, likely from plants adapted to microclimates in certain regions. The second cluster contained moderately abundant pollen types, representing secondary nectar sources bees use when primary flowers are scarce. The third cluster had common pollen types such as Prunus, Trifloium, Brassica, Grewia, and Albizia across all samples, with their widespread availability and important floral source to the bees. Other species are found in only a few samples, which may reflect local vegetation differences or seasonal blooming. The clustering of samples into three groups shows that certain sites share similar floral profiles, possibly due to similar\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eenvironmental conditions or land use patterns. These findings closely correlate with the above interpretations, showing that Fabaceae dominated all four zones, followed by Asteraceae in zones 1 and 2 and Rosaceae in zones 3 and 4, thereby supporting the present conclusions. These observations agree with Herrero et al., (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) and Muresan et al., (2022), whose cluster analysis of different multifloral honey revealed groupings that corresponded to specific floral compositions and ecological zones. Further, heatmaps enhance the interpretability of clustering by integrating presence\u0026ndash;absence data. The concentrated red blocks of heatmap at the top indicate that these pollen types were dominant across most honey samples, whereas scattered red blocks toward the bottom indicate rare, more specialized pollens. These patterns likely reflect flora that are restricted to specific agro climatic zones. As demonstrated by Ponnuchamy et al., (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Hajian-Tilaki et al., (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), visual matrices of pollen distribution can reveal high-density clusters of specific taxa, often linked to regional or seasonal foraging preferences. Such visual patterns often correspond to ecological traits, such as the dominance of nectariferous species in certain landscapes or the flowering synchronisation of co-occurring species.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed that Himachal Pradesh has a rich floral diversity, which contributes to various multifloral honeys with unique floral contents that boost their medicinal properties. The physicochemical and mineral characteristics of all the honeys were in accordance with FSSAI standards. The variations in physicochemical and mineral composition show how different floral and geographical origin influence their characteristics. The results also highlighted that all the honeys were pure, fresh, and well-stored, practices were adopted by beekeepers of the state. No signs of honey adulteration were observed in any of the samples analysed except for one sample recorded with high moisture content (\u0026gt;\u0026thinsp;20%), sucrose content (\u0026gt;\u0026thinsp;5%), and HMF content (\u0026gt;\u0026thinsp;80mg/kg) from Zone-1. The potassium, magnesium, and calcium found as the most abundant minerals in all the multifloral honeys indicate the high nutritional value of these honeys. Further, PCA revealed that floral origin significantly influences the physicochemical characteristics of honey. The Cluster analysis helped in understanding the botanical origin of honey, tracking pollinator foraging behaviour, and identifying potential areas for conserving diverse plant species.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003eThe authors are also grateful to Dr. YS Parmar University, Nauni, Solan, and all beekeepers who assisted with the collection of honey samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e Author R. Sharma performed the research, statistical analysis, and wrote the manuscript, M. Thakur and S. Devi helped with review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e The authors have no conflicts of interest to declare. All coauthors have seen and agree with the contents of the manuscript and certify that the submission is original work and is not under review at any other publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThe authors declare that no external funding was received for the preparation and completion of this research paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e All data generated or analysed during this study are included in this published article and its supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbselami A, tahani A, syndic M, fauconnier ML, bruneau E, elbachiri A. Physicochemical properties of some honeys produced from different flora of Eastern Morocco. Journal of Materials and Environmental Science 2018;9: 879-886. \u003c/li\u003e\n\u003cli\u003eAdadi P and Obeng A K. 2017. Assessment of bacterial quality of honey produced in Tamale Metropolis (Ghana). \u003cem\u003eJournal of Food and Drug Analysis\u003c/em\u003e 25:369-73.\u003c/li\u003e\n\u003cli\u003eAdenekan, M.O., Amusa, N.A., Lawal, A.O. and Okpeze, V.E., 2010. Physico-chemical and microbiological properties of honey samples obtained from Ibadan. \u003cem\u003eJournal of Microbiology and Antimicrobials\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(8), pp.100-104.\u003c/li\u003e\n\u003cli\u003eAfshari, A., Ram, M. and Mohamadi, S., 2022. Quality evaluation of Iranian honey collected from Khorasan province, Iran. International Journal of Food Science, 2022(1), p.3827742.\u003c/li\u003e\n\u003cli\u003eAhmed, A.S., Elgorashi, E.E., Moodley, N., McGaw, L.J., Naidoo, V. and Eloff, J.N., 2012. The antimicrobial, antioxidative, anti-inflammatory activity and cytotoxicity of different fractions of four South African Bauhinia species used traditionally to treat diarrhoea. \u003cem\u003eJournal of Ethnopharmacology\u003c/em\u003e, \u003cem\u003e143\u003c/em\u003e(3), pp.826-839.\u003c/li\u003e\n\u003cli\u003eAhmed, J., Prabhu, S.T., Raghavan, G.S.V. and Ngadi, M., 2007. Physico-chemical, rheological, calorimetric and dielectric behavior of selected Indian honey. \u003cem\u003eJournal of Food Engineering\u003c/em\u003e, \u003cem\u003e79\u003c/em\u003e(4), pp.1207-1213.\u003c/li\u003e\n\u003cli\u003eAlbu, A., Simeanu, C., Pop, I.M., Pui, A., Tarcău, D. and Cucu-Man, S.M., 2023. Selected characteristics of multifloral honeys from North-Eastern Romania. \u003cem\u003eAgriculture\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1), p.26.\u003c/li\u003e\n\u003cli\u003eAmir, Y., Yesli, A., Bengana, M., Sadoudi, R. and Amrouche, T., 2010. Physico-chemical and microbiological assessment of honey from Algeria. \u003cem\u003eElectronic Journal of Environmental, Agricultural \u0026amp; Food Chemistry\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(9).\u003c/li\u003e\n\u003cli\u003eAOAC (1984) Official Methods of Analysis. Association of official analytical chemists, 12th ed., Washington, D.C. p. 1141.\u003c/li\u003e\n\u003cli\u003eAOAC (2000) Official Methods of Analysis.17th ed. (Horowitz W ed.). The association of official analytical cemists, Gaithersburg, MD, USA.\u003c/li\u003e\n\u003cli\u003eAOAC (2004) Official Methods of Analysis. 17th ed. (Horowitz W ed.). The association of official analytical chemists, Gaithersburg, MD, USA.\u003c/li\u003e\n\u003cli\u003eAOAC (2012) Official Methods of Analysis\u003cem\u003e. \u003c/em\u003e19th ed. (GW Latimer ed.). The association of official analytical chemists, Gaithersburg, MD, USA.\u003c/li\u003e\n\u003cli\u003eAttri P K 2011 Physico-chemical investigation of honey samples of Apis ceranaindicaF. (Traditional Beekeeping) and Apis mellifera (Mordern Apiculture) from Chamba District, Himachal Pradesh. Biological Forum-An International Journal 3 67-73.\u003c/li\u003e\n\u003cli\u003eBertoncelj, J.; Dobersek, U.; Jamnik, M.; Golob, T. Evaluation of the Phenolic Content, Antioxidant Activity and Colour of Slovenian Honey. Food Chemistry 2007, 105, 822\u0026ndash;828\u003c/li\u003e\n\u003cli\u003eBesharati, M., Far, M.N., Azhir, D., Palangi, V. and Lackner, M., 2025. Evaluation of Physicochemical Properties of Honey produced in East Azerbaijan Province, Iran. \u003cem\u003eApplied Food Research\u003c/em\u003e, p.100933.\u003c/li\u003e\n\u003cli\u003eBIS (Bureau of Indian Standards) (1994) Indian Standard Extracted Honey - Specifications2\u003csup\u003end\u003c/sup\u003e revision. The National Standard Body of India, New Delhi.\u003c/li\u003e\n\u003cli\u003eBogdanov S, Ruoff K, Oddo LP (2004) Physico-chemical methods for the characterization of unifloral honeys. Apodologie 35:4-17.\u003c/li\u003e\n\u003cli\u003eBogdanov, S., Haldimann, M., Luginb\u0026euro;uhl, W. and Gallmann, P. (2007), \u0026ldquo;Minerals in honey: environmental, geographical and botanical aspects\u0026rdquo;, Journal of Apicultural Research and Bee World, Vol. 46, pp. 269-275.\u003c/li\u003e\n\u003cli\u003eBouhlali, E.D.T., Bammou, M., Sellam, K., El Midaoui, A., Bourkhis, B., Ennassir, J., Alem, C. and Filali-Zegzouti, Y., 2019. Physicochemical properties of eleven monofloral honey samples produced in Morocco. \u003cem\u003eArab Journal of Basic and Applied Sciences\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(1), pp.476-487.\u003c/li\u003e\n\u003cli\u003eBuba, F., Gidado, A. and Shugaba, A., 2013. Analysis of biochemical composition of honey samples from North-East Nigeria. \u003cem\u003eBiochem Anal Biochem\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(3), p.139.\u003c/li\u003e\n\u003cli\u003eBuba, F., Gidado, A. and Shugaba, A., 2013. Physicochemical and microbiological properties of honey from North East Nigeria. \u003cem\u003eBiochem Anal Biochem\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(142), pp.61-67.\u003c/li\u003e\n\u003cli\u003eChakir, A., Romane, A., Marcazzan, G.L. and Ferrazzi, P., 2016. Physicochemical properties of some honeys produced from different plants in Morocco. \u003cem\u003eArabian Journal of Chemistry\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e, pp.S946-S954.\u003c/li\u003e\n\u003cli\u003eChidi, B.S., Bauer, F.F. and Rossouw, D., 2018. Organic acid metabolism and the impact of fermentation practices on wine acidity: A review. \u003cem\u003eSouth African Journal of Enology and Viticulture\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(2), pp.1-15.\u003c/li\u003e\n\u003cli\u003eChoudhary, A., Kumar, V., Kumar, S., Majid, I., Aggarwal, P. and Suri, S., 2021. 5-Hydroxymethylfurfural (HMF) formation, occurrence and potential health concerns: Recent developments. Toxin Reviews, 40(4), pp.545-561.\u003c/li\u003e\n\u003cli\u003eDa Silva, P.M., Gauche, C., Gonzaga, L.V., Costa, A.C.O. and Fett, R., 2016. Honey: Chemical composition, stability and authenticity. \u003cem\u003eFood chemistry\u003c/em\u003e, \u003cem\u003e196\u003c/em\u003e, pp.309-323.\u003c/li\u003e\n\u003cli\u003eDa Silva, P.M., Gauche, C., Gonzaga, L.V., Costa, A.C.O. and Fett, R., 2016. Honey: Chemical composition, stability and authenticity. \u003cem\u003eFood chemistry\u003c/em\u003e, \u003cem\u003e196\u003c/em\u003e, pp.309-323.\u003c/li\u003e\n\u003cli\u003eDevi, S., Parihar, A., Thakur, M., Thakur, B. and Sharma, H.K., 2021. Antibacterial potential of hive bees honey from Himachal Pradesh, India. \u003cem\u003eArchives of Microbiology\u003c/em\u003e, \u003cem\u003e203\u003c/em\u003e, pp.5029-5041.\u003c/li\u003e\n\u003cli\u003eDjonwangwe D, Tchuenguem Fohouo FN, Messi J, Bru\u0026uml;ckner D. 2011. Foraging and pollination activities of Apis mellifera adansonii Latreille (Apidae) on Syzygium guineense var. guineense (Myrtaceae) flowers at Ngaounde\u0026acute; re\u0026acute; (Cameroon). Journal of Animal and Plant Sciences 10:1325\u0026ndash;1333\u003c/li\u003e\n\u003cli\u003eDobrinas, S., Soceanu, A., Birghila, S., Birghila, C., Matei, N., Popescu, V. and Constanda, L.M., 2022. Chemical analysis and quality assessment of honey obtained from different sources. \u003cem\u003eProcesses\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(12), p.2554. \u003c/li\u003e\n\u003cli\u003eDraiaia, R., Dainese, N., Borin, A., Manzinello, C., Gallina, A. and Mutinelli, F., 2015. Physicochemical parameters and antibiotics residuals in Algerian honey. \u003cem\u003eAfrican Journal of Biotechnology\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(14), pp.1242-1251.\u003c/li\u003e\n\u003cli\u003eDung, N.T.P., Rombouts, F.M. and Nout, M.J.R., 2005. Development of defined mixed-culture fungal fermentation starter granulate for controlled production of rice wine. \u003cem\u003eInnovative Food Science \u0026amp; Emerging Technologies\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(4), pp.429-441.\u003c/li\u003e\n\u003cli\u003eEl Sohaimy SA, Masry SHD, Shehata MG. 2015. Physicochemical characteristics of honey from different origins. Annals of Agricultural Science. 60:279-287.\u003c/li\u003e\n\u003cli\u003eErdoğan, Y. and Turan, M., 2022. Physicochemical properties of honey produced at different altitudes. \u003cem\u003eTurkish Journal of Agriculture-Food Science and Technology\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(4), pp.710-718.\u003c/li\u003e\n\u003cli\u003eErdtman G. 1969. Handbook of palynology: morphology, taxonomy, ecology. An introduction to the study of pollen grains and spores. Hafner, New York. pp 1-486. \u003c/li\u003e\n\u003cli\u003eEscriche, I., Sobrino-Gregorio, L., Conchado, A. and Juan-Borr\u0026aacute;s, M., 2017. Volatile profile in the accurate labelling of monofloral honey. The case of lavender and thyme honey. \u003cem\u003eFood chemistry\u003c/em\u003e, \u003cem\u003e226\u003c/em\u003e, pp.61-68.\u003c/li\u003e\n\u003cli\u003eEscuredo, O., Rodr\u0026iacute;guez-Flores, M.S., M\u0026iacute;guez, M. and Seijo, M.C., 2023. Multivariate statistical approach for the discrimination of honey Samples from Galicia (NW Spain) using physicochemical and pollen parameters. \u003cem\u003eFoods\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(7), p.1493.\u003c/li\u003e\n\u003cli\u003eFelsner, M.L., Cano, C.B., Bruns, R.E., Watanabe, H.M., Almeida-Muradian, L.B.D. and Matos, J.D.R., 2004. Characterization of monofloral honeys by ash contents through a hierarchical design. \u003cem\u003eJournal of Food Composition and Analysis\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(6), pp.737-747.\u003c/li\u003e\n\u003cli\u003eGairola, A., Tiwari, P. and Tiwari, J.K., 2013. Physico-chemical properties of Apis cerana-indica F. honey from Uttarkashi district of Uttarakhand, India. \u003cem\u003eJournal of Global Biosciences\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(1), pp.20-25.\u003c/li\u003e\n\u003cli\u003eGodoy, C.A., Valderrama, P. and Boroski, M., 2022. HMF monitoring: Storage condition and honey quality. \u003cem\u003eFood Analytical Methods\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(11), pp.3162-3176.\u003c/li\u003e\n\u003cli\u003eGrassi, G., Capasso, G., Cillo, A., Miedico, O., Pompa, C., Nardelli, V. and Perna, A.M., 2025. Effect of Altitude on Polyphenol Content, Antioxidant Activity and Multi-Element Composition of Wildflower Honey. \u003cem\u003eApplied Sciences\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(6), p.3255.\u003c/li\u003e\n\u003cli\u003eHajian-Tilaki, A., Kenari, R.E., Farahmandfar, R. and Razavi, R., 2024. Comparative study of physiochemical properties in Iranian multi-floral honeys: Local vs. commercial varieties. \u003cem\u003eHeliyon\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(17).\u003c/li\u003e\n\u003cli\u003eHajian-Tilaki, A., Kenari, R.E., Farahmandfar, R. and Razavi, R., 2024. Comparative study of physiochemical properties in Iranian multi-floral honeys: Local vs. commercial varieties. \u003cem\u003eHeliyon\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(17).\u003c/li\u003e\n\u003cli\u003eHerrero, B., Mar\u0026iacute;a Valencia-Barrera, R., San Mart\u0026iacute;n, R. and Pando, V., 2002. Characterization of honeys by melissopalynology and statistical analysis. \u003cem\u003eCanadian Journal of plant science\u003c/em\u003e, \u003cem\u003e82\u003c/em\u003e(1), pp.75-82.\u003c/li\u003e\n\u003cli\u003eHosny A S, Sabbah F M and El-Bazza Z E. 2018. Studies on the microbial decontamination of Egyptian bee pollen by \u0026gamma; radiation. \u003cem\u003eEgyptian Pharmaceutical Journal\u003c/em\u003e 17:190-200.\u003c/li\u003e\n\u003cli\u003eIftikhar, F., Masood, M.A. and Waghchoure, E.S. (2011), \u0026ldquo;Comparison of Apis cerana, Apis dorsata, Apis florea and Apis mellifera honey from different areas of Pakistan\u0026rdquo;, Society of Applied Sciences, Vol. 2, pp. 399-03.\u003c/li\u003e\n\u003cli\u003eIkegbunam, N.C., Okwong, J.W. and Anukwuorji, A.C., 2025. PHYSICOCHEMICAL PROPERTIES AND MINERAL COMPOSITION OF HONEY (Apis mellifera) FROM NORTH CENTRAL NIGERIA. \u003cem\u003eThe Bioscientist Journal\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(1), pp.34-46.\u003c/li\u003e\n\u003cli\u003eISI 1(974) Indian Standard Specification for Honey. 4941p.\u003c/li\u003e\n\u003cli\u003eIsla MI, Craig A, Ordo\u0026ntilde;ez R, Zampini C, Sayago J, Bedascarrasbure E, Maldonado L (2011) Physico chemical and bioactive properties of honeys from northwestern Argentina. LWT-Food Science and Technology 44:1922-30.\u003c/li\u003e\n\u003cli\u003eIwama S, Melhem TS. 1979. The pollen spectrum of the honey of Tetragonisca angustula angustula L. Apidologie. 10:275-295.\u003c/li\u003e\n\u003cli\u003eJackson ML (1973) Soil Chemical Analysis. Prentice Hall Publisher, New Delhi, pp. 111-.26\u003c/li\u003e\n\u003cli\u003eJackson ML (2005) Soil Chemical Analysis. Prentice Hall Publisher, New Delhi, pp. 112- 27.\u003c/li\u003e\n\u003cli\u003eKamal MM, Rashid MHU, Mondal SC, EL Taj HF, Jung C. Physicochemical and microbiological characteristics of honey obtained through sugar feeding of bees. Journal of Food Science and Technology 2019;56:2267-2277.\u003c/li\u003e\n\u003cli\u003eKamboj, R., Bera, M. and Nanda, V., 2013. Chemometric classification of Northern India unifloral honey. \u003cem\u003eActa Alimentaria\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(4), pp.540-551.\u003c/li\u003e\n\u003cli\u003eKamboj, R., Bera, M.B. and Nanda, V., 2013. Evaluation of physico-chemical properties, trace metal content and antioxidant activity of Indian honeys. \u003cem\u003eInternational Journal of Food Science and Technology\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(3), pp.578-587.\u003c/li\u003e\n\u003cli\u003eKamboj, R., Sandhu, R.S. and Nanda, V., 2024. Effect of heating and pH on hydroxymethylfurfural content, diastase and invertase activity of Dalbergia honey using response surface methodology. \u003cem\u003eFood Chemistry Advances\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e, p.100766.\u003c/li\u003e\n\u003cli\u003eKarabagias, I.K., Louppis, A.P., Karabournioti, S., Kontakos, S., Papastephanou, C. and Kontominas, M.G., 2017. Characterization and geographical discrimination of commercial Citrus spp. honeys produced in different Mediterranean countries based on minerals, volatile compounds and physicochemical parameters, using chemometrics. \u003cem\u003eFood Chemistry\u003c/em\u003e, \u003cem\u003e217\u003c/em\u003e, pp.445-455.\u003c/li\u003e\n\u003cli\u003eKhalil, M.I., Moniruzzaman, M., Boukra\u0026acirc;, L., Benhanifia, M., Islam, M.A., Islam, M.N., Sulaiman, S.A. and Gan, S.H., 2012. Physicochemical and antioxidant properties of Algerian honey. \u003cem\u003eMolecules\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(9), pp.11199-11215.\u003c/li\u003e\n\u003cli\u003eKumar, A., Gill, J.P.S., Bedi, J.S., Manav, M., Ansari, M.J. and Walia, G.S. (2018b), \u0026ldquo;Sensorial and physicochemical analysis of Indian honeys for assessment of quality and floral origins\u0026rdquo;, Food Research International, Vol. 108, pp. 571-583.\u003c/li\u003e\n\u003cli\u003eLarsen, P. and Ahmed, M., 2022. Evaluation of antioxidant potential of honey drops and honey lozenges. \u003cem\u003eFood Chemistry Advances\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e, p.100013.\u003c/li\u003e\n\u003cli\u003eLavinas, F.C., Gomes, B.A., Silva, M.V., Lima, R., Leit\u0026atilde;o, S.G., Moura, M.R., Simas, R.C., Barbosa, R.F., Silva, F.O., Carneiro, C.S. and Rodrigues, I.A., 2025. Rainy and Dry Seasons Are Relevant Factors Affecting Chemical and Antioxidant Properties of Meliponini Honey. \u003cem\u003eFoods\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(2), p.305.\u003c/li\u003e\n\u003cli\u003eLewoyehu, M. and Amare, M., 2019. Comparative evaluation of analytical methods for determining the antioxidant activities of honey: A review. \u003cem\u003eCogent Food \u0026amp; Agriculture\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(1), p.1685059. \u003c/li\u003e\n\u003cli\u003eLouveaux J, Maurizio A. Vorwohl G. 1978. Methods of melissopalynology. Bee World. 59:139-53.\u003c/li\u003e\n\u003cli\u003eMongi, R.J., 2024. Influence of botanical origin and geographical zones on physicochemical properties, mineral contents and consumer acceptance of honey in Tanzania. \u003cem\u003eFood Chemistry Advances\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e, p.100731.\u003c/li\u003e\n\u003cli\u003eMongi, R.J., 2024. Influence of botanical origin and geographical zones on physicochemical properties, mineral contents and consumer acceptance of honey in Tanzania. \u003cem\u003eFood Chemistry Advances\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e, p.100731.\u003c/li\u003e\n\u003cli\u003eMuhammad, N.I.I. and Sarbon, N.M., 2023. Physicochemical profile, antioxidant activity and mineral contents of honey from stingless bee and honey bee species. Journal of Apicultural Research, 62(2), pp.394-401.\u003c/li\u003e\n\u003cli\u003eMureșan, C.I., Cornea-Cipcigan, M., Suharoschi, R., Erler, S. and Mărgăoan, R., 2022. Honey botanical origin and honey-specific protein pattern: Characterization of some European honeys. \u003cem\u003eLwt\u003c/em\u003e, \u003cem\u003e154\u003c/em\u003e, p.112883.\u003c/li\u003e\n\u003cli\u003eNair P K K. 1964. A pollen analytical study of Indian honeys. \u003cem\u003eThe Journal of Indian Botanical Society\u003c/em\u003e \u003cstrong\u003e43\u003c/strong\u003e:179‐91. \u003c/li\u003e\n\u003cli\u003eNair PKK. 1985. Melittopalynology. In: \u003cem\u003eEssentials of Palynology\u003c/em\u003e. New Delhi: Today and Tomorrow\u0026rsquo;s Publishers. pp 59-64.\u003c/li\u003e\n\u003cli\u003eNanda, V., Singh, B., Kukreja, V.K. and Bawa, A.S., 2009. Characterisation of honey produced from different fruit plants of northern India. \u003cem\u003eInternational Journal of Food Science and Technology\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(12), pp.2629-2636.\u003c/li\u003e\n\u003cli\u003eNayik, G.A. and Nanda, V., 2015. Physico-chemical, enzymatic, mineral and colour characterization of three different varieties of honeys from Kashmir valley of India with a multivariate approach. \u003cem\u003ePolish Journal of Food and Nutrition Sciences\u003c/em\u003e, \u003cem\u003e65\u003c/em\u003e(2).\u003c/li\u003e\n\u003cli\u003eNayik, G.A. and Nanda, V., 2016. A chemometric approach to evaluate the phenolic compounds, antioxidant activity and mineral content of different unifloral honey types from Kashmir, India. \u003cem\u003eLWT\u003c/em\u003e, \u003cem\u003e74\u003c/em\u003e, pp.504-513.\u003c/li\u003e\n\u003cli\u003eNayik, G.A.; Nanda, V. Physico-Chemical, Enzymatic, Mineral, and Colour Characterization of Three Different Varieties of Honeys from Kashmir Valley of India with a Multivariate Approach. Polish Journal of Food Sciences and Nutrition 2015, 65, 101\u0026ndash;108. 11.\u003c/li\u003e\n\u003cli\u003eNaz, R., Roberts, T.H., Bano, A., Nosheen, A., Yasmin, H., Hassan, M.N., Keyani, R., Ullah, S., Khan, W. and Anwar, Z., 2020. GC-MS analysis, antimicrobial, antioxidant, antilipoxygenase and cytotoxic activities of Jacaranda mimosifolia methanol leaf extracts and fractions. \u003cem\u003ePLoS One\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(7), p.e0236319.\u003c/li\u003e\n\u003cli\u003eOnyango, P., 2019. Authentication of honey samples from Eastern Mau forest Kenya by principal component analysis and cluster analysis of quantitative melissopalynological variables. \u003cem\u003eInternational Journal of Recent Research in Life Sciences (IJRRLS)\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e, pp.1-7.\u003c/li\u003e\n\u003cli\u003eOroian, M.; Ropciuc, S. Honey Authentication Based on Physicochemical Parameters and Phenolic Compounds. \u003cem\u003eComput. Electron. Agric.\u003c/em\u003e 2017, \u003cem\u003e138\u003c/em\u003e, 148\u0026ndash;156\u003c/li\u003e\n\u003cli\u003eOrsavov\u0026aacute;, J., Sytařov\u0026aacute;, I., Mlček, J. and Mi\u0026scaron;urcov\u0026aacute;, L., 2022. Phenolic compounds, vitamins C and E and antioxidant activity of edible honeysuckle berries (Lonicera caerulea L. var. kamtschatica Pojark) in relation to their origin. \u003cem\u003eAntioxidants\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(2), p.433.\u003c/li\u003e\n\u003cli\u003eOshomah M U and Ummulkhair M. 2014. Microbiological evaluation of commercial honey from Edo state, Nigeria. \u003cem\u003eInternational Journal of Scientific and Engineering Research \u003c/em\u003e5: 796-99.\u003c/li\u003e\n\u003cli\u003eOuchemoukh, S., Louaileche, H. and Schweitzer, P., 2007. Physicochemical characteristics and pollen spectrum of some Algerian honeys. \u003cem\u003eFood control\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(1), pp.52-58.\u003c/li\u003e\n\u003cli\u003eOzler H. 2015. Melissopalynological analysis of honey samples belonging to different districts of Sinop, Turkey. Mellifera. 15:1-11.\u003c/li\u003e\n\u003cli\u003ePajor M, Worobo R W, Milewski S and Szweda P. 2018. The antimicrobial potential of bacteria isolated from honey samples produced in the apiaries located in Pomeranian Voivodeship in Northern Poland. \u003cem\u003eInternational Journal of Environmental Research and Public Health\u003c/em\u003e 15:1-14.\u003c/li\u003e\n\u003cli\u003eParihar, A., Thakur, M., Rana, K. and Devi, S., 2020. Quality analysis of Apis cerana and Apis mellifera honey from Himachal Pradesh, India. \u003cem\u003eJournal of Entomology and Zoology studies\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(6), pp.46-54.\u003c/li\u003e\n\u003cli\u003ePașca, C., Mărghitaș, L.A., Matei, I.A., Bonta, V., Mărgăoan, R., Copaciu, F., Bobiș, O., Campos, M.G. and Dezmirean, D.S., 2021. Screening of some Romanian raw honeys and their probiotic potential evaluation. \u003cem\u003eApplied Sciences\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(13), p.5816.\u003c/li\u003e\n\u003cli\u003ePavlin, A., Kočar, D., Imperl, J., Kolar, M., Marolt, G. and Petrova, P., 2023. Honey origin authentication via mineral profiling combined with chemometric approaches. \u003cem\u003eFoods\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(15), p.2826.\u003c/li\u003e\n\u003cli\u003ePerna, A., Intaglietta, I., Simonetti, A. and Gambacorta, E., 2013. A comparative study on phenolic profile, vitamin C content and antioxidant activity of Italian honeys of different botanical origin. \u003cem\u003eInternational Journal of Food Science and Technology\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(9), pp.1899-1908. \u003c/li\u003e\n\u003cli\u003ePham T N, Le H T, Nguyen Q V, Tran Q T and Tran M P. 2022. Physicochemical properties, phenolic contents and antioxidant activity of Vietnamese honey. \u003cem\u003eResearch and Innovation in Food Science and Technology\u003c/em\u003e 10:427-38.\u003c/li\u003e\n\u003cli\u003ePonnuchamy, R., Bonhomme, V., Prasad, S., Das, L., Patel, P., Gaucherel, C., Pragasam, A. and Anupama, K., 2014. Honey pollen: using melissopalynology to understand foraging preferences of bees in tropical South India. \u003cem\u003ePlos one\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(7), p.e101618.\u003c/li\u003e\n\u003cli\u003eRamly, N.S., Sujanto, I.S.R., Abd Ghani, A., Huat, J.T.Y., Alias, N. and Ngah, N., 2021. The impact of processing methods on the quality of honey: A review. \u003cem\u003eMalaysian Journal of Applied Sciences\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(1), pp.99-110.\u003c/li\u003e\n\u003cli\u003eRana K, Abhivivek RKN, Monika MRB, Singh N. 2022. Melissopalynological analysis of honey for assessment of nectariferous resources of European honey bees (Apis mellifera L.) in mid hills of Himachal Pradesh. Biological Forum. 14:1175-1181.\u003c/li\u003e\n\u003cli\u003eRani, A. and Verma, S., 2025. Phytochemical Composition, Antioxidant, and Antimicrobial Potential of Honey: A Comprehensive Review. \u003cem\u003eINTERNATIONAL JOURNAL OF PLANT AND ENVIRONMENT\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(01), pp.10-19. \u003c/li\u003e\n\u003cli\u003eSahney M, Kumar A and Rahi S. 2016. Pollen analysis of honey from Varanasi district, Uttar Pradesh, India. \u003cem\u003eBiological Forum-An International Journal\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e:126-33.\u003c/li\u003e\n\u003cli\u003eSakač, M.B., Jovanov, P.T., Marić, A.Z., Pezo, L.L., Kevre\u0026scaron;an, Ž.S., Novaković, A.R. and Nedeljković, N.M., 2019. Physicochemical properties and mineral content of honey samples from Vojvodina (Republic of Serbia). \u003cem\u003eFood chemistry\u003c/em\u003e, \u003cem\u003e276\u003c/em\u003e, pp.15-21.\u003c/li\u003e\n\u003cli\u003eSaklani S and Mattu V K. 2018. Pollen analysis of honey samples from Hamirpur district, Himachal Pradesh, India. \u003cem\u003eThe International Journal of Plant Reproductive Biology\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e:145-50.\u003c/li\u003e\n\u003cli\u003eSaklani S, Mattu VK. 2020. Scanning electron microscopic study on pollens of 8 bee floral resources from Kangra Hills, Himachal Pradesh, India. International Journal of Biotech Trends and Technology. 10:67-71. \u003c/li\u003e\n\u003cli\u003eSalim, Z., Khan, M.U. and Malik, R.N., 2020. Concentration, distribution and association of heavy metals in multi-matrix samples of Himalayan foothill along elevation gradients. \u003cem\u003eEnvironmental Earth Sciences\u003c/em\u003e, \u003cem\u003e79\u003c/em\u003e(20), p.479.\u003c/li\u003e\n\u003cli\u003eSarma VAK, Krishna P, Budihal SL (1987) Soil resource mapping of different states in India-A Laboratory manual. National Bureau of Soil Survey and Land Use Planning Nagpur. p. 49.\u003c/li\u003e\n\u003cli\u003eSaxena, S., Gautam, S. and Sharma, A., 2010. Physical, biochemical and antioxidant properties of some Indian honeys. \u003cem\u003eFood chemistry\u003c/em\u003e, \u003cem\u003e118\u003c/em\u003e(2), pp.391-397.\u003c/li\u003e\n\u003cli\u003eSchade JE, Marsh GL, Eckert JE (1958) Diastase activity and hydroxy‐methyl‐ furfural in honey and their usefulness in detecting heat alteration. Journal of Food Science 23:446-63.\u003c/li\u003e\n\u003cli\u003eSharma N. 1989. Melissopalynology and survey of honey plants in Himachal Pradesh. PhD Thesis, Himachal Pradesh University, Shimla, India.\u003c/li\u003e\n\u003cli\u003eSharma, A., Daroch, R.K., Kapoor, R. and Kumar, I., 2022. Status of bee keeping in Himachal Pradesh, India: A review. The Pharma Innovation Journal 2022; SP-11(3): 257-265\u003c/li\u003e\n\u003cli\u003eSharma, R., Thakur, M., Rana, K., Devi, D. and Bajiya, M.R., 2023. Honey, its quality and composition and their responsible factors. \u003cem\u003eInternational Journal of Bio-resource and Stress Management\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1), pp.178-189.\u003c/li\u003e\n\u003cli\u003eShishira, D., Uthappa, A.R., Chavan, S.B., Kuberappa, G.C., Jinger, D. and Sringeswara, A.N., 2024. Pollen diversity in urban honey: implications for bee foraging behaviour and urban green space planning. \u003cem\u003eUrban Ecosystems\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(6), pp.2487-2500.\u003c/li\u003e\n\u003cli\u003eShobham K K C and Nayar J. 2017. Physicochemical analysis of some commercial honey samples from Telangana. \u003cem\u003eIndian Journal of Nutrition\u003c/em\u003e 4:1-4.\u003c/li\u003e\n\u003cli\u003eShukla V and Kumar A. 2020. Melissopalynological and physicochemical analysis of honey samples from Prayagraj district Uttar Pradesh. \u003cem\u003eActa Palaeobotanica\u003c/em\u003e 60:123-33.\u003c/li\u003e\n\u003cli\u003eSingh M and Sharma K. 2007. Importance of bee flora of low hills of Himachal Pradesh. \u003cem\u003eInsect Environment \u003c/em\u003e\u003cstrong\u003e13\u003c/strong\u003e:79-80.\u003c/li\u003e\n\u003cli\u003eSingleton VL, Orthofer R, Lamuela-Raventos RM (1999) Analysis of total 403 phenols and other oxidation substrates and antioxidants by means of folin-ciocalteu 404 reagent. Methods in Enzymology 299:152-78.\u003c/li\u003e\n\u003cli\u003eSireli, H.D. and Saylak, \u0026Uuml;., 2025. The effect of storage temperature on some physicochemical properties of flower honey. \u003cem\u003eAgrociencia\u003c/em\u003e, pp.1-11.\u003c/li\u003e\n\u003cli\u003eSmith LI (2002) A tutorial on principal components analysis.\u003c/li\u003e\n\u003cli\u003eSnowdon J A and Cliver D O. 1996. Microorganisms in honey. \u003cem\u003eInternational Journal of Food Microbiology\u003c/em\u003e 31:1-26.\u003c/li\u003e\n\u003cli\u003eSoares, S., Amaral, J.S., Oliveira, M.B.P. and Mafra, I., 2017. A comprehensive review on the main honey authentication issues: Production and origin. \u003cem\u003eComprehensive Reviews in Food Science and Food Safety\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(5), pp.1072-1100.\u003c/li\u003e\n\u003cli\u003eSolayman, M., Islam, M.A., Paul, S., Ali, Y., Khalil, M.I., Alam, N. and Gan, S.H., 2016. Physicochemical properties, minerals, trace elements, and heavy metals in honey of different origins: a comprehensive review. \u003cem\u003eComprehensive reviews in food science and food safety\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(1), pp.219-233.\u003c/li\u003e\n\u003cli\u003eSong XY, Yao YF, Yang WD. 2012. Pollen analysis of natural honeys from the central region of Shanxi, north China. PloS One. 7:e50329.\u003c/li\u003e\n\u003cli\u003eSuharoschi, R., Erler, S. and Mărgăoan, R., 2022. Honey botanical origin and honey-specific protein pattern: Characterization of some European honeys. \u003cem\u003eLwt\u003c/em\u003e, \u003cem\u003e154\u003c/em\u003e, p.112883.\u003c/li\u003e\n\u003cli\u003eTarapatskyy, M., Sowa, P., Zaguła, G., Dżugan, M. and Puchalski, C., 2021. Assessment of the botanical origin of polish honeys based on physicochemical properties and bioactive components with chemometric analysis. \u003cem\u003eMolecules\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(16), p.4801.\u003c/li\u003e\n\u003cli\u003eTerrab, A., Recamales, A.F., Hernanz, D. and Heredia, F.J., 2004. Characterisation of Spanish thyme honeys by their physicochemical characteristics and mineral contents. \u003cem\u003eFood chemistry\u003c/em\u003e, \u003cem\u003e88\u003c/em\u003e(4), pp.537-542.\u003c/li\u003e\n\u003cli\u003eTesta, R., Asciuto, A., Schifani, G., Schimmenti, E. and Migliore, G., 2019. Quality determinants and effect of therapeutic properties in honey consumption. An exploratory study on Italian consumers. \u003cem\u003eAgriculture\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(8), p.174. \u003c/li\u003e\n\u003cli\u003eThakur, B., Devi, S., Thakur, M., Parihar, A., Sagar, V. and Devi, D., 2024. Unraveling the microbial status of wild bee\u0026rsquo;s honey from North India. \u003cem\u003eBiologia\u003c/em\u003e, \u003cem\u003e79\u003c/em\u003e(6), pp.1919-1930.\u003c/li\u003e\n\u003cli\u003eThakur, M., Gupta, N., Devi, D., Bajiya, M.R., Sharma, R. and Sharma, D., 2022. Variations in physicochemical characteristics of honey: a review. \u003cem\u003eThe Pharma Innovation Journal\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(7), pp.337-348.\u003c/li\u003e\n\u003cli\u003eThakur, M., Gupta, N., Sharma, H.K. and Devi, S., 2021. Physicochemical characteristics and mineral status of honey from different agro-climatic zones of Himachal Pradesh, India. \u003cem\u003eBritish Food Journal\u003c/em\u003e, \u003cem\u003e123\u003c/em\u003e(11), pp.3789-3804.\u003c/li\u003e\n\u003cli\u003eTownsend GF (1969) Optical density as a means of colour classification of honey. Journal of Apicultural Research 8:29-36.\u003c/li\u003e\n\u003cli\u003eTripathi S, Basumatary S K, Bera S K, Brahma M and Sarma G C. 2017. A palynological study of natural honeys from the Bongaigaon district of Assam, northeast India. \u003cem\u003ePalynology\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e:389-400.\u003c/li\u003e\n\u003cli\u003eUkanyirioha CJ, Popoola AS, Erhabor TA, Janfa N, Chomini MS, Kambai C, Imoh JA, Ukwadi M, Sadiku Y, Francis MJ. 2021. Melissopalynological analysis of honey to detect melliferous plant species visited by \u003cem\u003eApis mellifera\u003c/em\u003e \u003cem\u003eadansonii\u003c/em\u003e latereille (West African honeybee) in Guinea Savanna Zone of Nigeria. Ethiopian Journal of Environmental Studies \u0026amp; Management. 14:834-841.\u003c/li\u003e\n\u003cli\u003eUSDA. 1985. United States Standards for Grades of Extracted Honey (5\u003csup\u003eth\u003c/sup\u003e ed.).Agricultural marketing service fruit and vegetable division processed products branch, United States, Department of Agriculture, Washington, DC.\u003c/li\u003e\n\u003cli\u003eVerma K. 2006. \u003cem\u003eMelissopalynological Analysis of Some Honeys from Hamirpur and adjoining areas of Himachal Pradesh\u003c/em\u003e. M. Phil. Dissertation. Himachal Pradesh University, Shimla, HP, India. 73p.\u003c/li\u003e\n\u003cli\u003eVlad, I.A., Bartha, S., Goji, G., Tăut, I., Rebrean, F.A., Burescu, L.I.N., Pășcuț, C.G., Moțiu, P.T., Tunduc, A., Bunea, C.I. and Bora, F.D., 2025. Comprehensive Assessment of Potentially Toxic Element (PTE) Contamination in Honey from a Historically Polluted Agro-Industrial Landscape: Implications for Agricultural Sustainability and Food Safety. \u003cem\u003eAgriculture\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(11), p.1176.\u003c/li\u003e\n\u003cli\u003eVon Der Ohe W, Oddo LP, Piana ML, Morlot M, Martin P. 2004. Harmonized methods of melissopalynology. Apidologie. 35(Suppl. 1):S18-S25.\u003c/li\u003e\n\u003cli\u003eWollum, A.G.: Cultural methods for soil microorganisms. In: Methods of Soil Analysis Part-2: Chemical and Microbiological Properties. American Society of Agronomy, Inc Publisher Madison, Wisconsin, USA. pp. 781-02 (1982).\u003c/li\u003e\n\u003cli\u003eYao, Y.F., Bera, S., Wang, Y.F. and Li, C.S., 2006. Nectar and pollen sources for honeybee (Apis cerana cerana Fabr.) in Qinglan mangrove area, Hainan Island, China. \u003cem\u003eJournal of Integrative Plant Biology\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(11), pp.1266-1273.\u003c/li\u003e\n\u003cli\u003eYayinie M, Atlabachew M, Tesfaye A, Hilluf W, Reta C and Alemneh T. 2022. Polyphenols, flavonoids, and antioxidant content of honey coupled with chemometric method: Geographical origin classification from Amhara region, Ethiopia. \u003cem\u003eInternational Journal of Food Properties \u003c/em\u003e25:76-92.\u003c/li\u003e\n\u003cli\u003eYu, W., Zhang, Y., Li, J., Li, J., Li, K., Ning, F., Guo, X., Huang, X. and Luo, L., 2025. Physicochemical Properties, Chemical Composition, and against Klebsiella pneumoniae Mechanism of Scrophularia ningpoensis Honey. \u003cem\u003eLWT\u003c/em\u003e, p.118157.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Apis mellifera, Beekeeping, Melissopalynology, Multifloral honey, Pollens","lastPublishedDoi":"10.21203/rs.3.rs-9222304/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9222304/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examined the physicochemical, mineral, and bacterial profiles of multifloral honeys from \u003cem\u003eApis mellifera\u003c/em\u003e L. collected from different agro-climatic zones in Himachal Pradesh, India. Out of all honey samples, twenty-six honeys were identified as multifloral honeys through melissopalynological studies. The physicochemical parameters varied among all the multifloral honeys with an average results for pollen density (42,000\u0026ndash;5,45,000 pollen grains per 10g), pH (3.97\u0026ndash;5.96), Electrical conductivity (0.13-0.74mS/cm), moisture content (14.34\u0026ndash;20.13%), optical density (0.12, Extra White\u0026thinsp;\u0026minus;\u0026thinsp;2.41, Amber), density (1.35-1.61g/cm3), glucose (25.23\u0026ndash;37.06%), fructose (31.7-40.66%), sucrose (2.74\u0026ndash;5.78%), F:G (0.93\u0026ndash;1.5), acidity (17.40-49.36meq/kg), vitamin C (7.67-38.49mg/100g), ash (0.02\u0026ndash;0.42%), hydroxy methyl furfural (HMF) (6.59-86 mg/kg), diastase (4.53-30.48DN), phenol (12.96-108.54mg/100g), proline (18.19-113.98mg/100g) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) (16.49\u0026ndash;78.84%) content. The various minerals, viz., calcium, magnesium, phosphorus, potassium, zinc, sodium, iron, and manganese, were detected. No significant signs of adulteration were detected, and all multifloral honey samples met the FSSAI safety standards, confirming their purity and adherence to proper storage practices. Further, principal component analysis (PCA) and hierarchical cluster analysis (HCA) suggested that the quality parameters varied among multifloral honeys based on origin, and the studied area harboured rich floral diversity that facilitates the production of unique multifloral honeys that can be attributed as geographical indications (GI) specific to the region.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"Comparative Physicochemical and Mineral Profiling of Multifloral Honeys from Apis mellifera in Himachal Pradesh, India: Implications for Export and GI Tagging","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-14 19:13:42","doi":"10.21203/rs.3.rs-9222304/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-28T14:25:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-19T07:52:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T08:30:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"192869137779170487990605941848415765001","date":"2026-04-09T04:35:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"278436377253359018697298448134688847284","date":"2026-04-07T19:13:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-07T18:23:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-07T18:11:25+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-07T14:42:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-31T09:28:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-31T09:02:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6b9c2276-981d-4f20-b232-57d978ac3671","owner":[],"postedDate":"April 14th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":66195517,"name":"Biological sciences/Biochemistry"},{"id":66195518,"name":"Earth and environmental sciences/Environmental sciences"},{"id":66195519,"name":"Biological sciences/Plant sciences"}],"tags":[],"updatedAt":"2026-04-28T14:39:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-14 19:13:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9222304","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9222304","identity":"rs-9222304","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}