Torbangun is a folk herb that has been used especially as a breast milk stimulant in North Sumatra, Indonesia. Plant bioactive compound composition is influenced by many factors such as genotype, geographical origin, and environment. Therefore, identifying plant clones with superior chemical composition is a necessity for optimal large-scale production. In this study, three clones of torbangun (hereafter referred to as A, B, and C clones) were analyzed through their phenotypic and foliar phenolic characteristics. The phenotypic results showed that the A clone was distinct from the B and C clones. Nevertheless, the result of multivariate analysis using phenolic data showed that these three clones had three distinct patterns of phenolic compounds. The B clone torbangun was identified as the best clone to be used in larger production scale due to its highest quantity of most phenolic compounds.
Torbangun (Plectranthus amboinicus (Lour.) Spreng) is a succulent aromatic perennial shrub plant which grows well in sub-tropical and tropical locations. This plant has many traditional uses such as the treatment of cough, sore throat and nasal congestion, and a range of other illnesses including infections, rheumatism and flatulence [
There are several potential efficacies associated with Torbangun’s bioactive compounds. Some recent studies have reported that torbangun contains bioactive components such as alkaloids, terpenoids, saponins, tannins, and flavonoids [
Three clones of torbangun plants (hereafter designated as A, B, and C) which have slightly different morphological appearance and are from different geographic origins were used in this research. These three clones were chosen based upon their rapid growth characteristics. The A and B clones were from a medicinal plants nursery at Bogor, Indonesia, while the C clone was from a home garden of a Bataknese family living at Bekasi, Indonesia. Several external factors such as climate, soil, and fertilization are known to affect variation of bioactivity compounds in plants, but internal genetic variation is often regarded as the most important factor [
The purpose of this study was to test our working hypothesis that torbangun clones vary in phenolic concentration and that it is possible to identify clones which have superior phenolic concentrations for future cultivation on a larger production scale. This study used univariate methods (Analysis of Variance, ANOVA) to compare concentration of compounds between samples and multivariate methods (Partial Least Square-Discrimina- tive Analysis, PLS-DA) to obtain further interpretation [
The three clones of Plectranthus amboinicus (Lour.) Spreng, a species of the Lamiaceae family, was identified by the Indonesian Institute of Science, Research Center of Biology, with Dr. Joeni Setijo Rahajoe as the Head of Botany. The plants were collected from Bekasi, Indonesia (6˚14'56.499''S latitude - 106˚59'49.028''E longitude) and Cipaku, Bogor, Indonesia (6˚35'60''S latitude - 106˚47'59.999''E longitude), then cultivated in the Medicinal Plants Conservation garden, Ciampea, Bogor, Indonesia (6˚34’31.012”S latitude - 106˚41'38.329''E longitude).
Each cutting of torbangun clones was cultivated within 30 cm radius from the other. Cuttings which had at least three nodes were planted in bags in order for rooting before transplanting to a bed with 60% shade. The cuttings were watered manually every two days. To make a suitable growing media, a mixture of soil, husk charcoal, and manure was used, with a ratio of 1:1:1. After 14 days, the cuttings were transplanted on raised- grounds carefully without replacing the roots-bound soil. The composition of growing medium in the planting beds was the same as in polybags. Pest control was accomplished manually, without using pesticides. Incident solar radiation on the three clones was measured on multiple occasions and was similar for all plantings. The plants were cultivated when the season changed from rainy to drought from March to May 2012. The rainfall rate per month in the plantation area was about 119 - 469 mm; the lowest rainfall rate was in March, while the highest rate was in April 2012.
For every five samples of each clone were collected and measured to get the data in order to fill the plant descriptor. The quantitative data were arranged from the smallest to the biggest one, while qualitative data were observed from the most samples.
Identification of torbangun’s phenotype was accomplished by thorough morphological observation at collecting time, about 8 weeks after transplanting. Variables of observation referred to as plant descriptors?mainly the morphology of leaf and stalk-were made based on guidelines from Bioversity International [
All reagents were of analytical or HPLC grade. Ethanol, methanol, Folin-Ciocalteu reagent, HCl, Na2CO3, Na2COOH, KCl, and KH2PO4 were purchased from Merck (Darmstadt, Germany). TBHQ (Tertiary Butyl Hydroquinone), gallic acid, quercetin, kaempferol, myricetin, apigenin, and luteolin standards from Sigma-Aldrich (St. Louis, MO, USA). Acetonitrile, methanol, and water for HPLC were obtained from JT Baker (Phillipsburg, NJ, USA).
Fresh leaves were collected and prepared the same day. The collected leaves grew about 10 cm from the tip of shoots and were free from blemish and defect. The clean leaves were immediately stored at −20˚C until lyophilized (neither washed nor chopped to avoid browning due to friction of short-hair on leaves). After lyophilization for 48 hours with a freeze dryer (FreeZone 6 l Console Freeze Dry System, Labconco, Kansas City, MO), the dried leaves were crushed to 30 mesh powder. The leaves were stored at −20˚C in darkness until analyzed.
This assay followed the methods used in a previous study by Shetty et al. [
Two methods of extraction were performed to quantify the amount of flavonoids in the samples, based upon methods previously reported by Hertog et al. [
Chromatographic separations were performed on a Develosil-3u-ODS-UG C18 (Nomura Chemical, Seto, Japan) column (4.6 mm i.d. × 75 mm). The column was placed ontoa LC-2040 HPLC (Shimadzu, Kyoto, Japan) and injected with 20 µL extract. The LC was equipped with a UV-Vis Hewlett?Packard Series 1100 detector (Agilent Technologies, Inc., Santa Clara, CA) and reverse-phase column as mentioned above. The isocratic mobile phase was a 25% acetonitrile in 0.025 M KH2PO4 (pH 2.4) solution, with a flow rate of 0.9 ml/min. Flavonoids were quantified based on peak area which compared with standards at 370 nm. Flavonoid standards were mixed in order to create conditions equivalent to flavonoids in nature. All compounds had linear calibration curves (peak area vs concentration;
Data are reported as mean ± standard deviation. Analysis of variance was performed with SPSS (Version 20.0, IBM, New York, USA) to evaluate differences among values of each clone. Tukey’s HSD test was used when samples exhibited significantly different values of each metabolite, with the significance level set at p < 0.05. Partial Least Square-Discriminant Analysis (PLS-DA) was applied to all peaks from LC chromatograms, using SIMCA-P software (Version 13.0, Umetrics AB, Umeå, Sweden). All peak areas were converted into an ASCII file using built-in program (LC Solution Version 1.22 SP 1, Shimadzu Corp), bucketed, and summed up by Mi-
Compounds | Standard curves equations |
---|---|
Myricetin | y = 103,833x − 1823.4 |
Luteolin | y = 31,160x + 426.73 |
Quercetin | y = 53,135x − 760.75 |
Apigenin | y = 69,610x − 8365 |
Kaempferol | y = 107,746x + 512.17 |
crosoft Excel (Microsoft Corp., USA), before transferring to SIMCA-P for PLS-DA analysis.
Each HPLC spectrum was reduced to fewer variables, calculated by integrating regions of equal bucket size of 0.08 minutes and variable bucket size where large variations in chemical shift could be reduced. Several spectral regions were excluded to eliminate misperceptions in PLS-DA results. Therefore, spectrum from regions after injection until the second minute which contained solvents was excluded. The data sets were arranged in such a way that the rows of each data matrix represent the subjects and the columns represent chemicals contained (variables). The size of the data was 276 × 12.
Three torbangun clones were identified using morphological plant descriptors. The results showed that although plants have the same scientific name, they still may have distinct clonal phenotypes. The A clone torbangun could be easily differentiated morphologically from the two other clones in several ways. The mature leaves of clone A were about 1.5 - 2.2 mm-thick, 5.2 - 6 cm long, had a sharper leaf tip, a green leaf stalk which was about 2 - 2.6 cm-length, and the aromatic smell was qualitatively strong. In contrast, the leaves of clones B and C were about 0.5 - 1.0 mm-thick, had a larger length of 7.1 - 8.9 cm, ovate leaves, a purplish-green stalk of about 3.1 - 4.4 cm length, and the aromatic smell was not qualitatively as strong as the A clone.
Among the three clones, the B clone torbangun had the highest phenolics content, followed by torbangun A and C clones. The C clone contained only about 70% of the total phenolics as compared to the B clone. The phenolic levels of torbangun plants observed in this study were in the range of total phenolic results reported by Marinova et al. [
Similar to results with phenolics content, the B clone of torbangun had the highest level of anthocyanins among the three clones, with 2.33 mg, followed by 1.82 and 1.69 mg cyanidin-3-glucoside equivalents/100 g DW, for clones A and C, respectively (
From the two methods performed in quantifying flavonoid content in plants, the results are only presented from the optimal method. The methods were previously optimized by Hertog et al. [
Results of the torbangun leaf analysis showed that the combination of two methods from Hertog et al. [
Clones | Total phenolics content | Total anthocyanins content | Flavonoid content | ||||
---|---|---|---|---|---|---|---|
Myricetin | Luteolin | Quercetin | Apigenin | Kaempferol | |||
A | 1770.57 ± 80.00 | 1.82 ± 0.08 | 2.35 ± 0.06 | 23.45 ± 1.23 | 5.34 ± 0.15 | 5.47 ± 0.40 | 6.99 ± 0.27 |
B | 1887.63 ± 16.65 | 2.33 ± 0.07 | 37.04 ± 0.24 | 86.87 ± 7.97 | 6.66 ± 0.04 | 5.22 ± 0.38 | 10.17 ± 0.27 |
C | 1357.67 ± 25.86 | 1.69 ± 0.10 | 17.1 ± 0.10 | 44.23 ± 2.83 | 3.82 ± 0.21 | 3.55 ± 0.22 | 8.36 ± 0.19 |
Flavonoids | Rt/retention time (min.) | A clone | B clone | C clone | |||
---|---|---|---|---|---|---|---|
Period of extraction & hydrolysis | |||||||
2 h | 4 h | 2 h | 4 h | 2 h | 4 h | ||
Myricetin | 3.82 - 4.05 | 2.35 ± 0.06 | 1.02 ± 0.03 | 37.04 ± 0.24 | 25.98 ± 0.68 | 17.10 ± 0.10 | 12.80 ± 0.93 |
Luteolin | 7.81 - 8.51 | 0.27 ± 0.02 | 23.45 ± 1.23 | 0.08 ± 0.01 | 86.87 ± 7.97 | nd | 44.23 ± 2.83 |
Quercetin | 8.33 - 8.99 | 5.34 ± 0.15 | nd | 6.66 ± 0.04 | nd | 3.82 ± 0.21 | nd |
Apigenin | 14.39 - 15.94 | nd | 5.47 ± 0.40 | 3.13 ± 0.34 | 5.22 ± 0.38 | nd | 3.55 ± 0.22 |
Kaempferol | 17.14 - 19.55 | 6.99 ± 0.27 | 7.99 ± 2.05 | 10.17 ± 0.27 | 7.06 ± 0.74 | 8.36 ± 0.19 | 7.37 ± 2.33 |
Total | 14.95 | 37.93 | 57.08 | 125.13 | 29.28 | 67.95 |
nd: not detected.
tween clones. However, an exception was for apigenin contents in A and B clones which were not significantly different.
PLS-DA was performed to probe the data comprehensively to distinguish clonal-based sample characteristics. Multivariate data analysis was intended to obtain a model with separation between observed classes, based on the X variable. This model of analysis was developed from a set of data observations based on previously known class memberships [
There are two types of PLS-DA outputs used: score scatter plot (part A of
scatter plot (part B of
PLS-DA score scatter plot of 2 h-extraction and hydrolysis method was shown in part A of
The quadrant part of the loading scatter plot which was used to observe the variables that affect the grouping of principal components can be determined by comparing the position of points in the loading plot with the clustered points in score plot. For example, with the 2 h-extraction and hydrolysis method, samples of A clone were clustered on the upper quadrant (part A of
Compound that was represented as “peak” at HPLC chromatogram serves as marker of a sample due to its significant presence (showed as high peak area) within the sample. From the loading plot (part B of
Part A of
From loading plot of the 4h method (part B of
17.08 - 17.58 (kaempferol) minutes.
Compared to katuk (Sauropus androgynus), a shrub plant which leaves are widely known for its ability to induce breast milk in Indonesia, the three clones of torbangun contained higher concentrations of the various flavonoids. An earlier study by Andarwulan et al. [
The identified unknown peaks (UP) were labeled by numbers 1 - 9 and each peak has an area of more than 10,000 mAU (
Flavonoid determination methods | Clone | Marker compounds |
---|---|---|
2 Hours hydrolysis with 1.2 M HCl (flavonol analysis) | A | UP-4, UP-6 |
B | Myricetin, quercetin | |
C | Kaempferol | |
4 Hours hydrolysis with 2 M HCl (flavone analysis) | A | Apigenin, UP-4, UP-6 |
B | Myricetin, luteolin | |
C | Kaempferol |
viously. There was an exception with UPs 6 and 9, which did not have a constant trend area betweenthe two methods. There are two possible explanations for this phenomenon: the extraction method was not optimal for the compound; or the compound was not flavonoid. As reported by previous author [
Most samples have a quite large percentage of unknown compound area, equivalent to about 47% - 89% if compared to total area of the detected compounds. The greatest unknown compounds were detected in the A clone with the 2 h-extraction and hydrolysis method. This substantial amount provides an interesting opportunity for further analysis, because it may contain unrevealed compounds. Such unknown compounds could be other flavonoids, because the analysis performed in this study using HPLC with UV-Vis detector at 370 nm, whereas flavonols and flavones have maximum absorption at this wavelength [
When comparing both loading scatter plots (part B of
This publication was produced under USAID Cooperative Agreement No. AID-497-A-11-00003. This report is made possible by the generous support of the American people through the United States Agency for International Development (USAID). The contents are the responsibility of Bogor Agricultural University & Texas A&M Borlaug Institute for International Agriculture, and do not necessarily reflect the views of USAID or the United States Government.