Effect of seasonal variations on the phytoconstituents of Aśvagandhā w.r. to lunar cycles

Abstract

Introduction:

Suśruta, Caraka and other ācāryas advocate the collection of medicinal plants keeping in view the part used, season, soil in which the herb grows and the desired pharmacological actions or therapeutic benefits. The logic behind such recommendations is being validated by modern scientific research.

Aim:

To assess the effect of seasonal variations on the phytoconstituents of Aśvagandhā (Withania somnifera L. Dunal) w.s.r. to lunar cycles.

Material and Methods:

The plant specimens were collected from Jamnagar identified pharmacognostically and cultivated under a defined habitat in a herbal garden of IPGT and RA on 7 Oct 2013. The root samples were collected on every paurṇimā (full moon) and amāvāsyā (new moon) days in śiśira and grīṣṃa ṛtu (as per classics) of the year 2013-14. The physicochemical parameters such as pH, ash values, extractive value, total alkaloid content, total flavonoids content (UV spectrometer with AlCl3 reagent), total phenolic content (Singleton and Rossi method), total carbohydrate content (UV spectroscopy with glucose as standard), UV-VIS-NIR and HPTLC were determined.

Result:

The results of the analytical studies clearly validate the logic of the recommendations of Suśruta and Cakrapāṇi. According to these recommendations, uṣṇa vīrya drugs must be collected during āgneya ṛtu i.e. grīṣṃa ṛtu. In present study, total phenolic, flavonide and carbohydrate content were found more in pournima samples. GAP samples showed maximum differentiation from rest of the samples with regards to TCA, TCW, TFW, MEx, WEX, pH etc. parameters. The Grīṣṃa Jyeṣṭha Paurṇimā (GJP) and Āṣāḍha Paurṇimā (GAP) samples were found to be superior than amāvāsyā samples w.r.t. functional groups and withanoloid content respectively on HPTLC.

Conclusion:

The observations of experimental studies validate the concept of seasonal as well as lunar collection of herb Ashwagandha to yield a drug of superior quality of active principles.

INTRODUCTION

Caraka in vimānasthāna summarizes technical excellence in the field of pharmacognostic, pharmaceutical and pharmatherapeutical sciences as “tasyāpīyaṃ parīkṣā idam evaṃ prakṛti” etc. Here, “evaṃ ṛtu” means that the season for collection of drugs plays an important role in the field of drug research.[1] To attain a good requisite therapeutic result it is mandatory to collect the drug bestowed with optimum Rasavīryādi qualities.[2] In Vedic and Ayurvedic literature, drug collection has been recommended for different parts of the plant in different seasons, asterisms (ṇakśatra), on the basis of vīryas and therapeutic uses.[3] The climate, temperature, rain fall, duration of day light, altitude, methods of cultivation, effect of lunar cycle, collection from wild area, soil condition and methods of collection, processing and storage have impacts on the secondary metabolites of the plant which ultimately affect the therapeutic efficiency of the drug.

In the recent years, there are increasing difficulties in securing sufficient supply of medicinal plants from natural sources. There has been drastic depletion in plant resources due to ruthless exploitation, human disturbances and difficulties in cultivation of plants. At present 90% collection of medicinal plant are from natural sources and 70% collection involves destructive harvesting.[4] Annual demand of Aśvagandhā is 7000 tonnes per year whereas its actual production is 1500 tonnes.[5] Such a big demand cannot be fulfilled by collecting the drug from wild sources and hence there is a need to apply proper harvesting techniques to achieve phytochemically better crops. This study was designed with the aim of studying the effect of lunar cycles on the phytoconstituents of Aśvagandhā (Withania somnifera L. Dunal.).

MATERIALS AND METHODS

The plant species from Jamnagar identified based on pharmacognostic parameters and cultivated in a defined place in herbal garden of the Institute of Post Graduate Training and Research in Ayurveda (IPG and TRA), Jamnagar, Gujarat, India. As mentioned in the classics, the root samples were collected on every full moon (paurṇimā) and new moon (amāvāsyā) day in śiśira and grīṣma ṛtu of year 2013-14. The features such as: Length of the plant; length, weight and cross section diameter of a root and diameter of pith were measured. The physicochemical parameters such as: pH, ash values, extractive value, total alkaloid content, total flavonoid content (using UV spectrometer with AlCl₃ reagent), Total phenolic content (using the Singleton and Rossi method), FTIR (Fourier transform infrared spectroscopy), free sugar estimation and HPTLC were determined.

Cultivation date: 7 Oct 2013.

First sample collection: 30 Jan 2014 (Approx. 3 months 21 days).

Last sample collection: 12 July 2014 (Approx. 9 months 5 days) [Table 1].

Table 1.

Time schedule for collection

The plants were collected within 1 hour after sunrise to keep the “time” variable constant.

OBSERVATIONS AND RESULTS

The study of physicochemical parameters like Loss on Drying (LOD), pH, ash value, extractive values were done as per standard methods of API [Table 2].

Table 2.

Observation of physicochemical parameters of Withania somnifera root according to lunar cycles

We conducted the quantitative analysis for total phenol (TP), total flavonoids (TF) and total carbohydrate (TC) of the root powder collected according to lunar cycles [Table 3].

Table 3.

Observation of quantitative analysis of Withania somnifera according to lunar cycles

All the plants were selected of same size and undergone same environmental conditions in a specified area, thus parameter changes are assumed to be equal. The results of quantitative tests were analyzed by Principle component analysis (PCA) through Unscrambler software version 9.7.[6]

PCA is a statistical procedure that uses orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. It is mathematically defined as an orthogonal linear transformation that transforms the data to a new co-ordinate system.

From Figure 1 results, it is seen that all 8 samples are different from each other. Samples SPhA, SMP and GAA resemble each other on the basis of Total flavonoids content values. SMP sample is different from all the samples and on the basis of TPW. Grīṣma month samples except Āṣāḍha amāvāsyā are separated from rest on the basis of TPA, WEx, LOD and total carbohydrate contents. From Māgha amāvāsyā to Māgha paurṇimā there is fall in TPW values which are again found higher in SPhA and maintained at constant level in grīṣma season. From SMA to SPhP, TFW values decreased. In grīṣma, there was increase in TFW values which slowly started decreasing at the end of grīṣma season. In grīṣma there was constant increase seen in TFA values. Higher values of LOD, TCA and TPA were seen when growth has taken place from GJA to GAP. Thus the variation seen between two seasons is due to flavonoids and phenol contents. The variation between paurṇimā and amāvāsyā observed can be attributed to flavonoid content [Figure 1]. In amāvāsyā, SMA is separated based on TPW values. GAA and SphA samples resemble each other on the basis of TPA, TFA, TPW and WEx thus showing differentiation. The GJA sample has maximum differentiation due to TCW and ash values [Figure 2].

Figure 1.

Phytochemical analysis of all parameters of 8 samples of Ashwagandha. TPA: Total phenol content alcohol extract, TPW: Total phenol content water extract. TFA: Total flavonoid content alcohol extract, TFW: Total flavonoid content water extract. TCA: Total carbohydrate content alcohol extract, TCW: Total carbohydrate content water extract

Figure 2.

All Amavasya samples w.r.t. all phytochemical parameters

Among paurṇimā samples, SMP sample gets differentiated due to TFA values. GJP and GAP samples resemble due to LOD and WEx. GJP and GAP showed maximum deflection due to MEx and TFW values respectively. SPhP sample is differentiated based on TPW value and ash value [Figure 3].

Figure 3.

All Pournima samples w.r.t. phytochemical constituents

Amongst śiśira all paurṇimā and amāvāsyā samples are well distinguished. SMA is separated from other samples on the basis of TFA and LOD. SPhP is distinguished based on TPA and TCA values. SPhA is differentiated by considering TFW values. TPW values didn’t show much differentiation for the separation of samples through PCA [Figure 4]. Among the grīṣma season samples, all samples are distinguishable from one other. Based on PC2, GAP sample is separated from śiśira samples in view of TCA, TCW, TPA, TFW, MEx, WEx, pH values. Samples for the Jyeṣṭha month do not show major difference in TPW, TFA, LOD values and thus fall in same quadrant. GAA sample is separated based on its ash value [Figure 5].

Figure 4.

All Shishir samples w.r.t all phytochemical parameters

Figure 5.

Greeshma season samples w.r.t all phytochemical parameters

The analysis of functional group variations of 117 data-points was done through UV-VIS-NIR test and plotted on Graph 1. The variations are significant in visible region. For HPTLC analysis, a sample of Aśvagandhā powder from IPGT and RA GAU Pharmacy was taken as a standard to compare and the 8 samples included in study were analyzed simultaneously.

Graph 1.

UV-VIS-NIR spectrum of W. somnifera powder drug. Plot of 8 samples of W. somnifera

All the 9 samples were spotted on precoated silica gel. Total 63 peaks were observed in the samples under 254 nm and 67 peaks were observed in the samples under 366 nm in HPTLC study [Table 4].

Table 4.

High performance thin layer chromatography profile observed under ultraviolet light

Withanoloid was used as reference standard for comparative quantitative study. The rf value of withanoloid standard was found as 0.65. Through TLC method an in-house withanoloid standard was developed using Aśvagandhā powder sample obtained from IPGT and RA, GAU, Jamnagar which had matched with the standard i.e. 0.63. The rf values from 8 samples which resembled the standard were selected The number of peaks obtained at specific rf interval in all 9 (8 samples + 1 standard sample were selected). The maximum peaks (11) were found in GJP samples at 254 nm while in GJP sample (15) at 366 nm [Tables 5 and 6].

Table 5.

Number of peaks observed at specific frequency at 254 nm

Table 6.

Number of peaks observed at specific frequency at 366 nm

Total withanoloid content at 0.6 rf was counted by maximum area covered by withanoloid at 254 and 366 nm [Table 7].

Table 7.

Maximum area covered by with anoloid at 0.6 Rf

The above table shows the rf values of 8 samples of Aśvagandhā which had compared with the standard and the area the sample has covered on HPTLC plate at 254 nm and 366 nm.

Maximum separation was found in GJP sample i.e. 11 spots at 254 nm and 12 spots at 366 nm. The peaks obtained at every 10 hrf were calculated. GJP sample was found to have high area in HPTLC plate in both at 254 nm and 366 nm. The hrf and respective area values suggest that the maximum area was covered by SPhA and GJP sample at 254 nm whereas by GAP sample at 366 nm.

DISCUSSION

Physicochemical parameters

In SMA and SMP samples the LOD values were in range of 40. The plant was in its growth phase in this period. In next cycles i.e. in samples of SPhaA and SphP a fall of 10% were noted. In grīṣma season the LOD values were high compared to śiśira season. In GJA, GJP, AAP samples the LOD values were almost 50% of the respective samples i.e. 51.96%, 54.62%, and 54.02% respectively. But in GAA sample it was 28.53% may be due to sudden environmental occurred because of 3 days rainfall during this cycle at Jamnagar. Otherwise the expected LOD values would have been in the same range as grīṣma season samples.

The pH values of śiśira season ranged between 5.5 and 6.5 whereas that of grīṣma was between 6.5 and 7.0. Thus the root shifts its acidic nature slowly towards basic. The minimum change was observed in SMP sample. In grīṣma the pH values was 7.0 except in GAA sample i.e. 6.5. This may be a slight variation in soil due to the heavy rainfall as mentioned above.

The ash values of śiśira samples ranged between 4.0 and 5.0 whereas the grīṣma samples was between 3.0 and 4.2. The Ash values fall during Jyeṣṭha month i.e. to 3.0 and again increases to the range of śiśira samples. From the data, a definite conclusion is difficult to draw about the variation in parameter Ash value as per lunar cycles.

Thus, based on physicochemical parameters, it is difficult to conclude effect of lunar on physicochemical parameters within short duration of study [Table 2].

Quantitative tests for various functional groups

The total phenol in alcohol extract was found maximum in GAP (18.18% w/w) followed by SPhaP (17.822% w/w) and GJP (12.53% w/w). In each month the values of TPA were seen higher on paurṇimā and this may be due to the influence of lunar phase. The TPA values were observed more during grīṣma season than śiśira. The maximum water extract of total phenol was observed in SphP (18.764% w/w) followed by SPhA (10.588% w/w). No variation was observed in rest samples as in the case of the alcohol extract. During Phālguna month, plants were affected by leaf spot disease causing damage to leaves, leading to synthesis of phenol compounds. Phenol compounds are secreted to improve resistance when plant undergoes any type of external stressor response.[6,7] No significant variation was observed in total phenol content as the synthesis of compounds takes place in the affected part i.e. leaf in the present case. The stressor responses continued in the whole of Phālguna month but synthesis of phenol was observed to be greater on paurṇimā indicating towards the influence of lunar phase.

The TFA values were high from SMP (2.4940% w/w), SPhA (1.8050% w/w) to SPhP (2.4900% w/w). During this month, the plants start flowering. Fruiting with colouration was observed on plants, all of these indicate the synthesis of flavonoids. The TFA synthesis response was equal both in SMP and SPhP but was less during SPhA but at the same time TFW values were high. The flavonoids synthesis increases in plants during fruiting, flowering and colouration of flowers stages.[8] During grīṣma season, the flavonoids content did not show much variation as there was no fruiting, flowering and coloration. TCA content of paurṇimā samples were higher than amāvāsyā samples in respective months. Overall the TCA content of grīṣma was higher than śiśira season samples. In grīṣma season the values of TCA was GJA (10.343), GJP (10.380), GAA (9.790) and GAP (14.098). The highest being GAP. TCA concentration had increased but it had decreased during GAA and elevated in GAP. This may be due to influence of lunar phase on TCA. The TCW concentration was higher in grīṣma than śiśira. In GAP, highest concentration of TCW was found [Table 3].

When all seasons are analyzed through all phytochemical parameters on PCA, The variations in śiśira samples were mainly due to flavonoids content (TFW). Grīṣma samples were different due to increase of carbohydrates (TCA, TCW) and phenol (TPA). The variation between two seasons seems to be due to flavonoids and phenol contents. But the variation between paurṇimā and amāvāsyā seems due to flavonoids content. Moisture content values help to differentiate grīṣma samples from śiśira on PCA [Figure 1].

When all amāvāsyā samples were analyzed through PCA for phytochemical parameters, the SPhA and GAA samples show maximum differentiation due to phenol (TPA, TPW) and flavonoids (TFW) content. Here, maturity of the plant is also a point to be considered. However, a linear correlation can’t be established and thus samples show variation in PCA. Even then, based upon phytochemical parameters SPhA and GAA separated in one quadrant, and GAA has higher values of phenol and flavonoids compounds. The variation in TPA values were found high in amāvāsyā samples at the beginning of both seasons which then decreased at the end of season. The elevation in phenol content may be due to protective reaction against the sudden change in environmental conditions at the beginning of season [Figure 2].

PCA for phytochemical parameters of all paurṇimā samples showed TFW, LOD and MEx values which were the cause of differentiation of grīṣma paurṇimā root samples. The positive differentiation of SPhP sample was on the basis of TPA and TCA values [Figure 3].

In śiśira season all four samples were differently placed in four different quadrants as they vary phytochemically. SPhP is distinguished by TPA and TCA values. TPW values didn’t show any significance for the differentiation of śiśira samples [Figure 4].

Among the grīṣma samples, GAP samples showed differentiation from the other three on the basis of its TCA, TCW, TPA, TFW, MEx., WEx, pH values. Among the two seasons SPhP and GAP samples were quantitatively distinguished but maximum differentiation was seen in GAP sample. Thus GAP sample is potent amongst all seasons and lunar phase [Figure 5]. The day length of grīṣma season days was more than śiśira days [Table 1]. Among grīṣma in comparison with amāvāsyā days, paurṇimā days received more day light which may be a factor responsible for more photosynthetic activity dependent on the sun and anabolism activity dependent on moon.

UV-VIS-NIR analysis

In NIR spectroscopy, the sample absorbs radiation in the range ultraviolet to near infra red (180- 2500 nm) resulting in the electronic transition within the samples. Near infrared spectroscopy is nondestructive type of analysis method which is useful to evaluate the whole drug. In this study,200 nm to 2500 nm spectral scan was done and reflectance found was further processed with PCA (Principal component analysis) for comparison of functional groups of 8 samples.

Most of the functional groups were separated in UV and visible region [Graph 1]. The differences between the samples are due to aromatic nitrogenous and secondary amide groups. The amide linkage is easily formed, confers structural rigidity, and resists hydrolysis. Amide linkages constitute a defining molecular feature of proteins. The variations found due to -NH2, -SH, -OH functional groups are antioxidant and free radical scavengers. The variation is caused due to varied concentration of nitrogenous compounds, free radical scavenger and antioxidant molecules.

HPTLC

High performance thin layer chromatography (HPTLC) helps for the analysis of many compounds both efficiently and cost effectively. Additionally, numerous samples can be run in a single analysis thereby dramatically reducing analysis time. With HPTLC, the same analysis can be viewed using different wavelengths of light thereby providing a more complete profile of the plant. UV based scanning after developing HPTLC plate not only provides opportunity for scanning at specific wavelengths but also is useful for quantifying the constituents. HPTLC enables the most complicated separations. In HPTLC profile, variable number of spots was found in different groups.

In Short UV (254 nm), total spots 63 were found in nine samples and total 67 spots in long UV (366 nm). In GJP sample three spots were found which resembles the standard sample at short UV and one spot at long UV [Table 4].

As the maximum separation of functional groups was observed in GJP sample in HPTLC analysis, a sample of Aśvagandhā powder from IPGT and RA GAU pharmacy was taken as a standard and the 8 samples included in study were analyzed simultaneously. Maximum separation was found in GJP sample with 11 spots at 254 nm and 12 spots at 366 nm. The peaks obtained at every 10 hrf were calculated. GJP sample was found to have high area in HPTLC plate both at 254 nm and 366 nm. The hrf and respective area values suggest that the maximum area was covered by SPhA and GJP sample at 254 nm whereas by GAP sample at 366 nm respectively. The paurṇimā samples were found to occupy more area of functional groups on HPTLC.

CONCLUSION

Lunar phases have not shown appreciable influence on ash values in the two seasons observed (grīṣma and śiśira) but the root has became more basic (pH 6.5-7.0) towards grīṣma ṛtu. In Principle component analysis, it was observed that total phenolic content was high in GAP sample. Total flavonoids content was higher in SMP and SPhP samples. Total carbohydrate content was high during paurṇimā (full moon day) of both the seasons. GAP samples showed maximum differentiation from rest of the samples with regards to TCA, TCW, TFW, MEx, WEX, pH values which confirms the potency of GAP (grīṣma Āṣāḍha paurṇimā sample). In HPTLC studies, the GJP and GAP samples were found superior to amāvāsyā samples w.r.t. functional groups and withanoloid content respectively.

The observations recorded in the analytical studies clearly validate the recommendation regarding drug collection of Suśruta and Cakrapāṇi viz. uṣṇa vīrya drugs to be collected during Āgneya ṛtu and Grīṣma ṛtu. The paurṇimā samples collected during Jyeṣṭha and Āṣāḍha month of Grīṣma ṛtu have shown perceivable differentiation in the maximum number of analytical parameters in comparison to śiśira samples. Collection of samples on full moon days (paurṇimā) have shown requisite influence on the phytoconstituents of Aśvagandhā root. Thus, Aśvagandhā being uṣṇa vīrya drug should be collected in grīṣma on full moon days for better therapeutic potency.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.