Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline in Peninsular Malaysia

*Choong Yew Keong, Nor Syaidatul Akmal Mohd Yousof, Jamia Azdina Jamal and Mohd Isa Wasiman*

## **Abstract**

Herbs from different geographical regions may differ qualitatively and quantitatively, hence it is crucial to determine the active components of herbs from different regions and build a reference database. This study focused on the database establishment for the authentication of the raw material of roselle (*Hibiscus sabdariffa*) collected at seven selected locations of the western coastline in Peninsular Malaysia. The validation on the unknown sample at the end of the study is to verify the accuracy of the established database. The inter-material distance (IMD) was presented as the mean distance of each sphere created by each batch of data from different locations. They were clustered with different folders and discriminated by Soft independent modelling by class analogy (SIMCA) algorithm. All materials from seven farms achieved 100% separation rate. The average IMD of these seven locations was 9.04. The FTIR techniques established in this study can be used to distinguish the geographical origin of the selected *H. sabdariffa* farm samples.

**Keywords:** *Hibiscus sabdariffa*, FTIR, database, geographical origin

## **1. Introduction**

The genus *Hibiscus* (*Malvaceae*) is distributed in tropical and subtropical zones [1]. *Hibiscus sabdariffa* (L.) planted in Malaysia endures high humidity and warmer climates. The main part of the plant with medicinal use is the edible red to pale yellow calyces or sepals that contain anthocyanin [2]. The various colour tones of the calyx rely on the location of planting and the composition of the soil. The factors such as genotype, types and intensity of light, orchard temperature, crop load and agronomic factors, including agrochemical application, irrigation, pruning and fertilisation, play certain roles in the quality of growth and products of roselle plant. Most of the roselle plantations are planted on Beach Ridges Interspersed with Swales (BRIS) soil in Malaysia [3]. Basically, this type of soil is not suitable for planting due to its high surface soil temperature and infiltration rate with low organic matter, nutrients content and water retention. Naimah et al. [4] reported that 20% of regulated deficit irrigation (80% irrigation) courses were required to enhance the roselle yield and preserve plant growth progression without adversely affecting calyx quality on BRIS soil.

According to statistics of industrial crops of roselle in 2016 [5], mostly shortlisted for western coastline of Peninsular Malaysia, Johor was the largest state with planted area of roselle and also achieved the highest production of roselle, followed by Penang, Selangor, Perak and Kedah. Roselle can be commercially grown throughout the year in Malaysia. Many constraints limit roselle production, including climatic variability such as flood and draught in certain district. The limited suitable land is also another factor.

*H. sabdariffa* is a potential herbal medicine in the treatment of hypertension [6, 7], by inhibiting the production of angiotensin converting enzyme [8] and exert an angioprotective effect in rat [9]. The identified anthocyanin contents of *H. sabdariffa* included delphinidin-3-sambubioside, cyanidin-3-sambubioside, delphinidin-3-monoglucoside and cyanidin-3-monoglucoside.

Juhari et al. reported that the discrepancies of anthocyanin contents of *H. sabdariffa* reflected the difference in geographic origin of the plants which were selected randomly in the experiments, as the composition of anthocyanin was based on the geographic origin of the plants [10]. The anthocyanin content, however, reached 1.7–2.5% of dry weight of the calyces in all the strains examined [11]. Therefore, both biomass and production and anthocyanin biosynthesis rely on the nutritional factors which include type and concentration of carbon, nitrogen source and phosphate level [12].

Commercial *H. sabdariffa* products in various forms have been mushrooming in the market. The quality in term of the content of anthocyanin in these commercial products is a major concern since herbs from different geographical regions may differ qualitatively and quantitatively [13]. In addition, different processing methods including the harvest period, material of sample used and the time of delivery could be the factors affecting the quality of the roselle products. Hence, it is crucial to determine the active components of herbs qualitatively from different regions and build a reference database. There are many quality control technologies in this new era. Commonly, the types of chromatography consist of high performance liquid chromatography, gas chromatography mass spectroscopy and liquid chromatography-mass spectrometry. Fourier transform infrared (FTIR) is widely used as a new technology for many purposes [14–16], such as analysis of anthocyanin [17]. The advantages of FTIR are rapid, less-destructive and cost saving. Such information acquired can be utilised for the development of reference database of *H. sabdariffa* to provide basic information on the product for the purpose of authentication, as the spectrum of a product can be rapidly matched for validation of its geographical origin and to predict the anthocyanin contents. This study therefore focused on the database establishment for the authentication of roselle raw materials collected from seven selected locations of western coastline in Peninsular Malaysia.

## **2. Materials and methods**

### **2.1 Plant material**

Only one variety of *H. sabdariffa* L. was obtained from seven different farms recognised by the State Agriculture Department along the western coastline in Peninsular Malaysia. The calyces of each individual plant were randomly collected (**Table 1**). The number of individual plants chosen depended on the size of farm and an average of 15–20 pieces of calyces from each individual plant were collected. A voucher specimen (PID 050515-05) was submitted to the Forest Biodiversity Unit at Forest Research Institute Malaysia (FRIM).

**109**

**Location** Date of collection

Sample type Weather Soil type

Soil pH Humidity

UV level Longitudes

Latitudes

**Table 1.** *Geographical condition when collecting roselle samples from different locations in Malaysia.*

1°44′14.3″N

2°45′0.58″N

5°3′32.656″N

7.

5°3′40.2984″N

5°42′48″N

5°31′12.4″N

8.5°3′19.9152″N

9.0°51′11.8008″N

High (index 6)

103°05′27.9″E

77%

68% Very high (index 7)

103°30′52.3″E

95% Moderate (index 4)

100°59′3.2384″E

84% Moderate (index 4)

4.103°0′57.9456″E

5.

102°59′21.3116″E

6.100°23′40.9632″E

82% Moderate (index 3)

102°38′20″E

83%

Moderate (index 4)

100°28′49.9″E

31.1°C

Bris

6.3

32°C Bris/sandy

4.8

32°C Bris/sandy

5.8

24.5°C

Bris 1. 5.2 2. 5.4 3. 5.0

27°C Bris

6.3

29°C Bris/sandy

6.0

UMKL-1 (Grade A and B)

UMKL-1 (Grade B)

UMKL-2 (Grade A and B)

**Batu Pahat (Johor)**

26 April 2016

**Kuala Rompin (Pahang)**

02 August 2016

**Lenggong (Perak)**

09 August 2016

**Hulu Terengganu (Terengganu)**

06 October 2016

1.UMKL1 2.UMKL 1 3.UMKL 1

UMKL-2

**Setiu (Terengganu)**

25 October 2016

**Kepala Batas (Penang)**

15 September 2014

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline…*

*DOI: http://dx.doi.org/10.5772/intechopen.84837*

UMKL-2


## *Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline… DOI: http://dx.doi.org/10.5772/intechopen.84837*

**Table**

**1.** *Geographical condition when collecting roselle samples from different locations in Malaysia.*

*Fourier Transforms - Century of Digitalization and Increasing Expectations*

delphinidin-3-monoglucoside and cyanidin-3-monoglucoside.

suitable land is also another factor.

and phosphate level [12].

Peninsular Malaysia.

**2.1 Plant material**

**2. Materials and methods**

at Forest Research Institute Malaysia (FRIM).

According to statistics of industrial crops of roselle in 2016 [5], mostly shortlisted for western coastline of Peninsular Malaysia, Johor was the largest state with planted area of roselle and also achieved the highest production of roselle, followed by Penang, Selangor, Perak and Kedah. Roselle can be commercially grown throughout the year in Malaysia. Many constraints limit roselle production, including climatic variability such as flood and draught in certain district. The limited

*H. sabdariffa* is a potential herbal medicine in the treatment of hypertension [6, 7], by inhibiting the production of angiotensin converting enzyme [8] and exert an angioprotective effect in rat [9]. The identified anthocyanin contents of *H. sabdariffa* included delphinidin-3-sambubioside, cyanidin-3-sambubioside,

Juhari et al. reported that the discrepancies of anthocyanin contents of *H. sabdariffa* reflected the difference in geographic origin of the plants which were selected randomly in the experiments, as the composition of anthocyanin was based on the geographic origin of the plants [10]. The anthocyanin content, however, reached 1.7–2.5% of dry weight of the calyces in all the strains examined [11]. Therefore, both biomass and production and anthocyanin biosynthesis rely on the nutritional factors which include type and concentration of carbon, nitrogen source

Commercial *H. sabdariffa* products in various forms have been mushrooming in the market. The quality in term of the content of anthocyanin in these commercial products is a major concern since herbs from different geographical regions may differ qualitatively and quantitatively [13]. In addition, different processing methods including the harvest period, material of sample used and the time of delivery could be the factors affecting the quality of the roselle products. Hence, it is crucial to determine the active components of herbs qualitatively from different regions and build a reference database. There are many quality control technologies in this new era. Commonly, the types of chromatography consist of high performance liquid chromatography, gas chromatography mass spectroscopy and liquid chromatography-mass spectrometry. Fourier transform infrared (FTIR) is widely used as a new technology for many purposes [14–16], such as analysis of anthocyanin [17]. The advantages of FTIR are rapid, less-destructive and cost saving. Such information acquired can be utilised for the development of reference database of *H. sabdariffa* to provide basic information on the product for the purpose of authentication, as the spectrum of a product can be rapidly matched for validation of its geographical origin and to predict the anthocyanin contents. This study therefore focused on the database establishment for the authentication of roselle raw materials collected from seven selected locations of western coastline in

Only one variety of *H. sabdariffa* L. was obtained from seven different farms recognised by the State Agriculture Department along the western coastline in Peninsular Malaysia. The calyces of each individual plant were randomly collected (**Table 1**). The number of individual plants chosen depended on the size of farm and an average of 15–20 pieces of calyces from each individual plant were collected. A voucher specimen (PID 050515-05) was submitted to the Forest Biodiversity Unit

**108**


**Figure 1.**

*The construction of the database model with method editor. Spectral of roselle raw material from seven locations of Western coastline in Peninsular Malaysia were imported to the functional icon 'Materials'.*

### **2.2 Sample processing**

Each of the individual calyces collected were processed individually. After removing the seed, the calyces were washed and air-dried at room temperature. After about 80% of dryness was achieved, the calyces were continually dried in the oven at 50°C for 3–4 days. The dried calyces were pulverised with a blender to the finest size for further use. The processing was repeated for all the individual calyces collected from the seven locations.

## **2.3 FTIR method**

The measurements were carried out using a Fourier Transform infrared (FTIR) spectrometer Spectrum GX, Perkin-Elmer Ltd., England, equipped with a deuterated triglycine sulphate (DTGS) detector. Infrared spectra were recorded at 32 scans at a range of 4000–400 cm<sup>−</sup><sup>1</sup> with a resolution of 4 cm<sup>−</sup><sup>1</sup> [18]. The dried calyces were ground with potassium bromide (KBr) powder in the ratio of 1:200 under the lowest humidity environment. The KBr and sample mixture were pressed not more than 10 psi to form a thin disc to be scanned for mid-infrared spectrum. The spectrum that achieved more than 60% transmission was chosen for further use [19]. Three discs were produced from each plant calyces and scanned.

### **2.4 Assured ID for chemometric analysis**

Software Assured ID (Assured ID Method Explorer 2015, PerkinElmer) was used for chemometric analysis. The chemometric SIMCA was chosen by selecting wave number in the range of 1900–515 cm<sup>−</sup><sup>1</sup> (**Figure 1**) instead of function with icon

**111**

**Figure 2.**

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline…*

"COMPARE" in the software. The outlaying spectrum was excluded in the developed method (**Figure 2**) when troubleshooting under the Coomans skill (**Figures 3** and **4**).

Validation was done on three batches of roselle given by a colleague for testing the established database. These roselle samples were labelled as A, B, C, D, E and F. The validation was also done on a roselle sample purchased from a Chinese shop

The sample was in the dried form and pulverised with blender. The finest samples were obtained by sieving with a 150-μm sieve (Standard Test Sieve, "CE"). The finest powder form of sample was mixed with KBr and followed the similar procedure of FTIR method, as mentioned in Section 2.3. The spectrum of unknown sample was copied to seven sets and labelled in a series (such as A-1, A-2, A-3, A-4, A-5, A-6 and A-7) and imported into the established database. Later, each copy of the spectrum was given a location based on the location of the established database. The specified material total distance ratios (SMTDR) of the generated results were used to predict its geographical origin. The system has a default of specific material distance ratio limit with a value of 1.000 estimated by a ratio of the edge of the sphere with the diameter of the sphere. In fact, the SMTDR was less than 1.000, and the position of the spectrum was considered located in the area of the sphere.

*Pre-processing step in the system. The wavenumber of the spectral was selected in the range of 1900–515 cm<sup>−</sup><sup>1</sup>*

*.*

*DOI: http://dx.doi.org/10.5772/intechopen.84837*

**2.5 Validation on unknown location sample**

in Georgetown, Penang, Malaysia.

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline… DOI: http://dx.doi.org/10.5772/intechopen.84837*

"COMPARE" in the software. The outlaying spectrum was excluded in the developed method (**Figure 2**) when troubleshooting under the Coomans skill (**Figures 3** and **4**).

## **2.5 Validation on unknown location sample**

*Fourier Transforms - Century of Digitalization and Increasing Expectations*

Each of the individual calyces collected were processed individually. After removing the seed, the calyces were washed and air-dried at room temperature. After about 80% of dryness was achieved, the calyces were continually dried in the oven at 50°C for 3–4 days. The dried calyces were pulverised with a blender to the finest size for further use. The processing was repeated for all the individual calyces

*The construction of the database model with method editor. Spectral of roselle raw material from seven locations of Western coastline in Peninsular Malaysia were imported to the functional icon 'Materials'.*

The measurements were carried out using a Fourier Transform infrared (FTIR) spectrometer Spectrum GX, Perkin-Elmer Ltd., England, equipped with a deuterated triglycine sulphate (DTGS) detector. Infrared spectra were recorded at 32 scans

with a resolution of 4 cm<sup>−</sup><sup>1</sup>

were ground with potassium bromide (KBr) powder in the ratio of 1:200 under the lowest humidity environment. The KBr and sample mixture were pressed not more than 10 psi to form a thin disc to be scanned for mid-infrared spectrum. The spectrum that achieved more than 60% transmission was chosen for further use [19].

Software Assured ID (Assured ID Method Explorer 2015, PerkinElmer) was used for chemometric analysis. The chemometric SIMCA was chosen by selecting

Three discs were produced from each plant calyces and scanned.

[18]. The dried calyces

(**Figure 1**) instead of function with icon

**110**

**2.2 Sample processing**

**Figure 1.**

**2.3 FTIR method**

collected from the seven locations.

at a range of 4000–400 cm<sup>−</sup><sup>1</sup>

**2.4 Assured ID for chemometric analysis**

wave number in the range of 1900–515 cm<sup>−</sup><sup>1</sup>

Validation was done on three batches of roselle given by a colleague for testing the established database. These roselle samples were labelled as A, B, C, D, E and F. The validation was also done on a roselle sample purchased from a Chinese shop in Georgetown, Penang, Malaysia.

The sample was in the dried form and pulverised with blender. The finest samples were obtained by sieving with a 150-μm sieve (Standard Test Sieve, "CE"). The finest powder form of sample was mixed with KBr and followed the similar procedure of FTIR method, as mentioned in Section 2.3. The spectrum of unknown sample was copied to seven sets and labelled in a series (such as A-1, A-2, A-3, A-4, A-5, A-6 and A-7) and imported into the established database. Later, each copy of the spectrum was given a location based on the location of the established database. The specified material total distance ratios (SMTDR) of the generated results were used to predict its geographical origin. The system has a default of specific material distance ratio limit with a value of 1.000 estimated by a ratio of the edge of the sphere with the diameter of the sphere. In fact, the SMTDR was less than 1.000, and the position of the spectrum was considered located in the area of the sphere.

#### **Figure 2.**

*Pre-processing step in the system. The wavenumber of the spectral was selected in the range of 1900–515 cm<sup>−</sup><sup>1</sup> .*

### **Figure 3.**

*Individual sphere of each location sample spectra and their overlapping to other location by Coomans graph. This figure showed the example of samples from Pulau Pinang (Kepala Batas) under 'review' of ID model.*

#### **Figure 4.**

*Process of troubleshooting of sample from Pulau Pinang (Kepala Batas). The right-hand side indicated the sample leverage and the left-hand side indicated the residual distance. The cross spot above the dashed-line is considered extreme and would be excluded.*

## **3. Results and discussion**

## **3.1 Authentication of roselle sample**

Voucher specimen (PID 050515-05) of roselle was authenticated as *Hibiscus sabdariffa* var. *UMKL-1*.

## **3.2 Classification and performance report**

The software "Assured ID" has successfully separated the spectra of the seven *H. sabdariffa* location samples based on different cluster of spheres. The analysis consisted of samples with extreme data (1.04% of excluded data) that were excluded from the system. All the materials from the seven farms achieved 100% rejection rate (**Figure 5**), showing that each of the *H. sabdariffa* spectra from the same location was distinguishable from the other locations when the software made a border line for the group of spectra from the same location. The 125 roselle

**113**

**Figure 5.**

*Western coastline in Peninsular Malaysia.*

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline…*

samples spectra from Penang derived a mean spectrum and used as reference, whereas 88 samples from Kedah were incorporated into another mean spectrum. Roselle sample spectra from other locations were also included in this database. All the raw data were tested with chemometric SIMCA. Analysis of the sample shown only the group of spectra from Johor (Muar) achieved 100% (69/69) recognition rate. The lowest recognition rate (92%) was the samples from Perak (Lenggong), as out of a total of 108 spectra of samples from Lenggong, 99 spectra were recognised to the cluster of Lenggong. The other nine spectra were considered different from the Lenggong spectra cluster. This different spectrum was not overlapping with another cluster; nevertheless, they were not incorporated into the cluster of Lenggong. Samples from Sabak Bernam, Dengkil and Batu Pahat reported 3–6% elimination of perfect recognition rate. **Figure 5** showed the tabulated IMD of all the locations at western coastline in Peninsular Malaysia.

Inter-material distance is the mean model distance created by the software based on the cluster of spectra which include the residual and compared with the other cluster of spectra in the same model. IMD indicated the average separation distance of two clusters of spectra. IMD with greater value suggested each cluster was separated far apart and their components were possibly different. On the other hand, IMD with zero value represented each cluster possessed similar components. The 3D principal component graph (**Figure 6**) illustrated the position of each cluster of spheres, which was viewed from different direction since their intermaterial distances varied. The 3D graph was established by three axes: PC1, PC2 and PC3. Each of the spheres was developed by the group of samples from their different locations. The spectrum of each sample was transferred to a particular dot form. They were surrounded by the residues and the whole sphere represented the mean of all spectra of the group. They were separated based on the intermaterial distance from the centre of the sphere. When the inter-material distance

*Inter-material distances and classification performance report of seven roselle farm locations in* 

*DOI: http://dx.doi.org/10.5772/intechopen.84837*

**3.3 Inter-material distances (IMD)**

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline… DOI: http://dx.doi.org/10.5772/intechopen.84837*

samples spectra from Penang derived a mean spectrum and used as reference, whereas 88 samples from Kedah were incorporated into another mean spectrum. Roselle sample spectra from other locations were also included in this database. All the raw data were tested with chemometric SIMCA. Analysis of the sample shown only the group of spectra from Johor (Muar) achieved 100% (69/69) recognition rate. The lowest recognition rate (92%) was the samples from Perak (Lenggong), as out of a total of 108 spectra of samples from Lenggong, 99 spectra were recognised to the cluster of Lenggong. The other nine spectra were considered different from the Lenggong spectra cluster. This different spectrum was not overlapping with another cluster; nevertheless, they were not incorporated into the cluster of Lenggong. Samples from Sabak Bernam, Dengkil and Batu Pahat reported 3–6% elimination of perfect recognition rate. **Figure 5** showed the tabulated IMD of all the locations at western coastline in Peninsular Malaysia.

## **3.3 Inter-material distances (IMD)**

*Fourier Transforms - Century of Digitalization and Increasing Expectations*

**112**

**3. Results and discussion**

*is considered extreme and would be excluded.*

**Figure 4.**

**Figure 3.**

*sabdariffa* var. *UMKL-1*.

**3.1 Authentication of roselle sample**

**3.2 Classification and performance report**

Voucher specimen (PID 050515-05) of roselle was authenticated as *Hibiscus* 

*Process of troubleshooting of sample from Pulau Pinang (Kepala Batas). The right-hand side indicated the sample leverage and the left-hand side indicated the residual distance. The cross spot above the dashed-line* 

*Individual sphere of each location sample spectra and their overlapping to other location by Coomans graph. This figure showed the example of samples from Pulau Pinang (Kepala Batas) under 'review' of ID model.*

The software "Assured ID" has successfully separated the spectra of the seven *H. sabdariffa* location samples based on different cluster of spheres. The analysis consisted of samples with extreme data (1.04% of excluded data) that were excluded from the system. All the materials from the seven farms achieved 100% rejection rate (**Figure 5**), showing that each of the *H. sabdariffa* spectra from the same location was distinguishable from the other locations when the software made a border line for the group of spectra from the same location. The 125 roselle

Inter-material distance is the mean model distance created by the software based on the cluster of spectra which include the residual and compared with the other cluster of spectra in the same model. IMD indicated the average separation distance of two clusters of spectra. IMD with greater value suggested each cluster was separated far apart and their components were possibly different. On the other hand, IMD with zero value represented each cluster possessed similar components.

The 3D principal component graph (**Figure 6**) illustrated the position of each cluster of spheres, which was viewed from different direction since their intermaterial distances varied. The 3D graph was established by three axes: PC1, PC2 and PC3. Each of the spheres was developed by the group of samples from their different locations. The spectrum of each sample was transferred to a particular dot form. They were surrounded by the residues and the whole sphere represented the mean of all spectra of the group. They were separated based on the intermaterial distance from the centre of the sphere. When the inter-material distance


#### **Figure 5.**

*Inter-material distances and classification performance report of seven roselle farm locations in Western coastline in Peninsular Malaysia.*

## *Fourier Transforms - Century of Digitalization and Increasing Expectations*

was closer, the two spheres would be overlapped. Since most of the inter-material was more than zero, the software was able to differentiate each group of samples. The areas of the spheres varied and relied on the derivative of the spectra from the main spectrum. When the size of sphere was smaller, the differences of each dot in the group from the mean spectrum were less and vice versa. **Figure 6** illustrated that the seven area spheres were associated closely in a three-dimensional graph, which was viewed from different direction since the inter-material distances varied. The IMD with high value reflected the far distance of the sphere's separation. Some of the spheres overlapped at certain portion meaning they were having very small value of IMD.

#### **Figure 6.**

*(A–F) were the 3D principle component graph of seven locations of collected roselle spectral rotated from different degree of axis-X and axis-Y. = Penang (Kepala Batas), = Kedah (Sik), = Perak (Lenggong), = Selangor (Dengkil), =Johor (Muar), = Johor (Batu Pahat), and = Selangor (Sabak Bernam).*

**115**

root rots.

**3.4 Validation of unknown sample**

Therefore, exclusion plays a key in validation.

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline…*

The average inter-material distance of these seven locations was 9.04. The highest inter-material distance was 20.1 between samples from Kedah (Sik) and Selangor (Sabak Bernam). The prediction of this scenario was that the development of *H. sabdariffa* from Sik in Kedah and Sabak Bernam in Selangor could be different in terms of their growing environment. The IMD from the Perak (Lenggong) and Johor (Batu Pahat) samples were lowest (4.07), showing that they shared 97.84% similarities of components in roselle grown under similar conditions of soil, water, pH and weather (**Table 1**). The analysis by software "Assured ID" indirectly also indicated that the sample from these two locations showed very similar spectra and the ingredients of the calyces were produced under similar conditions. Samples from Kepala Batas showed IMD of less than 5.00 similar to samples from Lenggong, Muar and Batu Pahat. Samples of *H. sabdariffa* from Kepala Batas might have produced comparable chemical content as samples from these three locations. The IMD value of Muar and Batu Pahat was almost similar, as both locations are only 60 km apart. The soil condition, water and climate are less different. The IMD value of more than 10 for samples from Selangor (Sabak Bernam) showed that samples from Kepala Batas had different quality compared with them. Samples from Sik showed lowest IMD (6.52) similar to Batu Pahat when compared with other locations. Samples from Lenggong scored higher IMD value compared with sample from Dengkil and could possibly be due to the organic fertiliser and soil used in Dengkil farm. Higher rate of organic fertiliser increased the stem diameter and stem height, leaves number and leaves area as well as the biomass and number of calyx [20]. This could explain why the samples from Dengkil achieved higher IMD among all the samples even though samples from Sabak Bernam were obtained from same state. In comparison, samples from Muar showed lower IMD compared with Batu Pahat and Sabak Bernam, as these two locations are located in the middle of western coastline of Peninsular Malaysia. However, samples from Batu Pahat and Sabak Bernam still produced IMD greater than 10. This could be due to other factors such as the expanding of roselle disease [21] in two different locations. This kind of disease affected the yields and products of roselle as they caused leaf spot, stem rots and

Three batches of raw roselle sample showed the SMTDR value of more than 1.000 (**Table 2**). This could be due to the raw material used included many overlapping spectral points. The spectra used for database have wide range of variation. Thus, the sphere was built by covering varied sizes. The exclusion process was done to eliminate the variation. During the trouble shooting step, the rare spectrum points discarded from the system also affected the average of the sphere size and diameter, and another spectra point could appear and needs to be excluded.

Since the SMTDR would not achieve less than 1.000, the prediction of the validation was based on the lowest value of SMTDR for the best result. By right, the range of SMTDR value of more than 1.000 was not mentioned in the system. There is no setting of SMTDR greater than 1.000, as the variation of database is built up by pure compound and theoretically the SMTDR of less than 1.000 for sample is validated within that specific sphere area. The validation of the sample needs to be conducted in a case by case manner. In the first batch of the sample, only sample F was predicted correctly. It is from Batu Pahat (Johor) with lowest SMTDR (5.6660). The prediction of the rest of the samples was inaccurate with SMTDR within the range of 6.000–9.000. Only sample B was predicted with

*DOI: http://dx.doi.org/10.5772/intechopen.84837*

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline… DOI: http://dx.doi.org/10.5772/intechopen.84837*

The average inter-material distance of these seven locations was 9.04. The highest inter-material distance was 20.1 between samples from Kedah (Sik) and Selangor (Sabak Bernam). The prediction of this scenario was that the development of *H. sabdariffa* from Sik in Kedah and Sabak Bernam in Selangor could be different in terms of their growing environment. The IMD from the Perak (Lenggong) and Johor (Batu Pahat) samples were lowest (4.07), showing that they shared 97.84% similarities of components in roselle grown under similar conditions of soil, water, pH and weather (**Table 1**). The analysis by software "Assured ID" indirectly also indicated that the sample from these two locations showed very similar spectra and the ingredients of the calyces were produced under similar conditions. Samples from Kepala Batas showed IMD of less than 5.00 similar to samples from Lenggong, Muar and Batu Pahat. Samples of *H. sabdariffa* from Kepala Batas might have produced comparable chemical content as samples from these three locations. The IMD value of Muar and Batu Pahat was almost similar, as both locations are only 60 km apart. The soil condition, water and climate are less different. The IMD value of more than 10 for samples from Selangor (Sabak Bernam) showed that samples from Kepala Batas had different quality compared with them. Samples from Sik showed lowest IMD (6.52) similar to Batu Pahat when compared with other locations. Samples from Lenggong scored higher IMD value compared with sample from Dengkil and could possibly be due to the organic fertiliser and soil used in Dengkil farm. Higher rate of organic fertiliser increased the stem diameter and stem height, leaves number and leaves area as well as the biomass and number of calyx [20]. This could explain why the samples from Dengkil achieved higher IMD among all the samples even though samples from Sabak Bernam were obtained from same state. In comparison, samples from Muar showed lower IMD compared with Batu Pahat and Sabak Bernam, as these two locations are located in the middle of western coastline of Peninsular Malaysia. However, samples from Batu Pahat and Sabak Bernam still produced IMD greater than 10. This could be due to other factors such as the expanding of roselle disease [21] in two different locations. This kind of disease affected the yields and products of roselle as they caused leaf spot, stem rots and root rots.

### **3.4 Validation of unknown sample**

Three batches of raw roselle sample showed the SMTDR value of more than 1.000 (**Table 2**). This could be due to the raw material used included many overlapping spectral points. The spectra used for database have wide range of variation. Thus, the sphere was built by covering varied sizes. The exclusion process was done to eliminate the variation. During the trouble shooting step, the rare spectrum points discarded from the system also affected the average of the sphere size and diameter, and another spectra point could appear and needs to be excluded. Therefore, exclusion plays a key in validation.

Since the SMTDR would not achieve less than 1.000, the prediction of the validation was based on the lowest value of SMTDR for the best result. By right, the range of SMTDR value of more than 1.000 was not mentioned in the system. There is no setting of SMTDR greater than 1.000, as the variation of database is built up by pure compound and theoretically the SMTDR of less than 1.000 for sample is validated within that specific sphere area. The validation of the sample needs to be conducted in a case by case manner. In the first batch of the sample, only sample F was predicted correctly. It is from Batu Pahat (Johor) with lowest SMTDR (5.6660). The prediction of the rest of the samples was inaccurate with SMTDR within the range of 6.000–9.000. Only sample B was predicted with

*Fourier Transforms - Century of Digitalization and Increasing Expectations*

very small value of IMD.

was closer, the two spheres would be overlapped. Since most of the inter-material was more than zero, the software was able to differentiate each group of samples. The areas of the spheres varied and relied on the derivative of the spectra from the main spectrum. When the size of sphere was smaller, the differences of each dot in the group from the mean spectrum were less and vice versa. **Figure 6** illustrated that the seven area spheres were associated closely in a three-dimensional graph, which was viewed from different direction since the inter-material distances varied. The IMD with high value reflected the far distance of the sphere's separation. Some of the spheres overlapped at certain portion meaning they were having

*(A–F) were the 3D principle component graph of seven locations of collected roselle spectral rotated from different degree of axis-X and axis-Y. = Penang (Kepala Batas), = Kedah (Sik), = Perak (Lenggong), = Selangor (Dengkil), =Johor (Muar), = Johor (Batu Pahat), and = Selangor (Sabak Bernam).*

**114**

**Figure 6.**

highest SMTDR and totally out of the range, indicating that the sample was not in the list of the database. The result showed more than half of the sample was related to Batu Pahat (Johor).


**117**

5.000–9.000.

far away.

SMTDR which is calculated by the software.

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline…*

**Sample batch 2**

**Special material total distance ratio**

A-6 7.2980 A-6 8.7694 A-6 31.2373 B-6 31.6953 B-6 5.8974 B-6 4.9123 C-6 10.3410 C-6 5.6070 C-6 6.9651 D-6 7.8224 D-6 7.3348 D-6 7.8226 E-6 7.8653 E-6 7.6492 E-6 5.8147 F-6 5.6660 F-6 36.3964 F-6 7.0601

A-7 24.6931 A-7 20.9941 A-7 46.7027 B-7 51.7277 B-7 29.6644 B-7 14.3989 C-7 12.6569 C-7 16.9875 C-7 18.2554 D-7 29.4725 D-7 24.2281 D-7 28.2599 E-7 41.6178 E-7 22.0678 E-7 18.9226 F-7 20.8477 F-7 58.2088 F-7 14.8515

**Sample batch 3**

**Special material total distance ratio**

**Special material total distance ratio**

S-6 10.2300

S-7 13.3286

Sample E in the second batch of the samples was correctly validated from Batu Pahat (Johor). Sample B was validated from Johor also, but from Mersing another district, but the SMTDR was lower than sample E, showing that the established database was not able to distinguish the sample from another district ever though the SMTDR was lower. The prediction of the location of the unknown sample was 100% relied on the value of SMTDR. Sample F was validated with highest SMTDR of 28.9541 and was absolutely as a sample not from the western coastline. The other samples were validated with SMTDR of around

*Testing the sample purchased from Penang (S) and three batches of roselle samples from different locations.*

*Yellow highlight refers to the samples that correctly validated the location. Blue highlight refers to the samples with* 

The pattern of results for the third batch of the validation sample was similar to first and second batch samples. Sample B was validated correctly from Batu Pahat (Johor). Sample A which originated from Kuala Rompin (Pahang) was validated with highest SMDR. The rest of the samples were validated in the range of SMTDR 3.000–8.000. In summary, most of the result of validation referred to the sphere with bigger size, in this case, Batu Pahat (Johor) and Kepala Batas (Penang). The average of the SMTDR was around 3.000–9.000 for these batches of roselle samples. Calculated SMTDR not within this range is considered roselle sample located

Validation of certain samples based on the established database showed the limitation and the reliability of the method. The database of samples from different locations with great variations caused the different sizes of the sphere in 3D graph. This phenomenon could affect the outcome, as it is preferable to possess bigger size sphere. The limitation of the established database includes the inaccuracy of determining the actual origin of the sample, since the outcome is only based on the

*DOI: http://dx.doi.org/10.5772/intechopen.84837*

**Sample batch 1**

**Special material**

Johor (Batu Pahat)

Selangor (Sabak Bernam)

*stranger SMTDR.*

**Table 2.**

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline… DOI: http://dx.doi.org/10.5772/intechopen.84837*


*Yellow highlight refers to the samples that correctly validated the location. Blue highlight refers to the samples with stranger SMTDR.*

#### **Table 2.**

*Fourier Transforms - Century of Digitalization and Increasing Expectations*

**Special material total distance ratio**

S-1 9.7776

S-3 10.2886

S-4 20.2622

Johor (Muar) S-5 7.8401

to Batu Pahat (Johor).

**Sample batch 1**

Kedah (Sik) S-2 32.3659

**Special material**

Perak (Lenggong)

Selangor (Dengkil)

Penang (Kepala Batas)

highest SMTDR and totally out of the range, indicating that the sample was not in the list of the database. The result showed more than half of the sample was related

> **Sample batch 2**

**Special material total distance ratio**

A-1 8.8082 A-1 9.5434 A-1 24.8195 B-1 25.8999 B-1 9.8203 B-1 5.3455 C-1 9.7891 C-1 7.5025 C-1 3.7961 D-1 9.5658 D-1 5.5987 D-1 9.4683 E-1 9.2071 E-1 12.1207 E-1 5.3179 F-1 9.0800 F-1 28.9541 F-1 6.7045

A-2 22.2249 A-2 25.7125 A-2 59.8511 B-2 57.9594 B-2 16.1543 B-2 19.8495 C-2 30.0014 C-2 29.5158 C-2 16.5201 D-2 20.2289 D-2 15.9132 D-2 12.5893 E-2 18.5137 E-2 28.1610 E-2 16.1842 F-2 23.5354 F-2 63.4393 F-2 23.2004

A-3 14.5125 A-3 12.8746 A-3 38.6313 B-3 42.7954 B-3 15.4265 B-3 9.6765 C-3 17.8026 C-3 10.5554 C-3 11.1555 D-3 16.9881 D-3 14.1552 D-3 14.1690 E-3 16.8321 E-3 12.4323 E-3 10.6477 F-3 11.5372 F-3 45.9675 F-3 10.7965

A-4 23.4421 A-4 23.1840 A-4 33.5551 B-4 35.3000 B-4 28.0679 B-4 17.5194 C-4 16.1456 C-4 22.9176 C-4 11.4110 D-4 26.1163 D-4 19.5813 D-4 30.7206 E-4 32.4657 E-4 29.7071 E-4 14.2706 F-4 25.6752 F-4 38.4939 F-4 16.9643

A-5 11.6067 A-5 8.3794 A-5 26.2286 B-5 28.0251 B-5 12.2636 B-5 5.9889 C-5 12.2153 C-5 6.7131 C-5 7.8547 D-5 13.0211 D-5 9.8193 D-5 10.4310 E-5 13.9058 E-5 11.4562 E-5 7.0655 F-5 8.8815 F-5 31.1604 F-5 5.8570

**Sample batch 3**

**Special material total distance ratio**

**116**

*Testing the sample purchased from Penang (S) and three batches of roselle samples from different locations.*

Sample E in the second batch of the samples was correctly validated from Batu Pahat (Johor). Sample B was validated from Johor also, but from Mersing another district, but the SMTDR was lower than sample E, showing that the established database was not able to distinguish the sample from another district ever though the SMTDR was lower. The prediction of the location of the unknown sample was 100% relied on the value of SMTDR. Sample F was validated with highest SMTDR of 28.9541 and was absolutely as a sample not from the western coastline. The other samples were validated with SMTDR of around 5.000–9.000.

The pattern of results for the third batch of the validation sample was similar to first and second batch samples. Sample B was validated correctly from Batu Pahat (Johor). Sample A which originated from Kuala Rompin (Pahang) was validated with highest SMDR. The rest of the samples were validated in the range of SMTDR 3.000–8.000. In summary, most of the result of validation referred to the sphere with bigger size, in this case, Batu Pahat (Johor) and Kepala Batas (Penang). The average of the SMTDR was around 3.000–9.000 for these batches of roselle samples. Calculated SMTDR not within this range is considered roselle sample located far away.

Validation of certain samples based on the established database showed the limitation and the reliability of the method. The database of samples from different locations with great variations caused the different sizes of the sphere in 3D graph. This phenomenon could affect the outcome, as it is preferable to possess bigger size sphere. The limitation of the established database includes the inaccuracy of determining the actual origin of the sample, since the outcome is only based on the SMTDR which is calculated by the software.

## **4. Conclusion**

*H. sabdariffa* is the herbal plant adaptable to almost every state in Malaysia. It is easy to grow and prefers mineral soil with lower acidic pH. The calyces of *H. sabdariffa* are made into herbal tea and consumed by local Malaysians. Their anthocyanin contents have been reported as the key component in therapeutic studies. This project was sampled of the roselle farm in the western coastline of Peninsular Malaysia. There are some considerations when establishing the database with Assured ID. The preparation of the sample is important in ensuring accurate determination. Firstly, the sample size of the KBr disc should be minimum above 50. The exclusion of extreme spectrum may minimise the sample size. This is crucial to ensure the data are representative of the actual condition of the sample in the area. Secondly, the sample processing procedures must be simple and time saving. The selection of region of wavenumber must include the range of fingerprint of the sample, which is exhibited in the raw material spectrum. The IMD of the sample must be more than one. It is preferable to collect the sample over a wide area in order to minimise the error of determining the location of unknown sample. When the location of an unknown sample could not be determined from the established database, it is possible that its SMTDR value could be out of the range of the average.

In this study, roselle raw material spectrum database was established by importing the spectrum of each individual plant into the system. Each of the sample spectrum from different locations has formed their own position in the 3-D principle component graphs and combined to form the sphere separated by IMD. Validation of given simples was used to test the established database for its accuracy. The validation showed that only one out of six samples from each batch of sample was validated correctly, indicating a success rate of only 17%. On the other hand, the method successfully discriminated sample location in western coastline. It is concluded that with this established database, more than 50% of the validation detected the sample within the range of western coastline.

The established method of Assured ID database of roselle can be used as a reference database for roselle sample from unknown geographical locations in Malaysia with few limitations, but further improvement is needed.

## **Acknowledgements**

The authors thank the Director General of Health, Malaysia, for the permission to publish and the Director of Institute for Medical Research (IMR), Kuala Lumpur for the support. This work was financially supported by the NKEA AGRICULTURE (EPP#1) and NKEA Research Grant Scheme (NRGS) (Grant No: NH1014D060).

**119**

**Author details**

Choong Yew Keong1

and Mohd Isa Wasiman1

Shah Alam, Selangor, Malaysia

Malaysia, Kuala Lumpur, Malaysia

provided the original work is properly cited.

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline…*

\*, Nor Syaidatul Akmal Mohd Yousof<sup>1</sup>

1 Phytochemistry Unit, Herbal Medicine Research Centre, Institute for Medical

2 Drug and Herbal Research Centre, Faculty of Pharmacy, Universiti Kebangsaan

\*Address all correspondence to: yewkeong@imr.gov.my; yewkeong11@yahoo.co.uk

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

Research, National Institute of Health, Minister of Health Malaysia,

, Jamia Azdina Jamal<sup>2</sup>

*DOI: http://dx.doi.org/10.5772/intechopen.84837*

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline… DOI: http://dx.doi.org/10.5772/intechopen.84837*

## **Author details**

*Fourier Transforms - Century of Digitalization and Increasing Expectations*

*H. sabdariffa* is the herbal plant adaptable to almost every state in Malaysia. It is easy to grow and prefers mineral soil with lower acidic pH. The calyces of *H. sabdariffa* are made into herbal tea and consumed by local Malaysians. Their anthocyanin contents have been reported as the key component in therapeutic studies. This project was sampled of the roselle farm in the western coastline of Peninsular Malaysia. There are some considerations when establishing the database with Assured ID. The preparation of the sample is important in ensuring accurate determination. Firstly, the sample size of the KBr disc should be minimum above 50. The exclusion of extreme spectrum may minimise the sample size. This is crucial to ensure the data are representative of the actual condition of the sample in the area. Secondly, the sample processing procedures must be simple and time saving. The selection of region of wavenumber must include the range of fingerprint of the sample, which is exhibited in the raw material spectrum. The IMD of the sample must be more than one. It is preferable to collect the sample over a wide area in order to minimise the error of determining the location of unknown sample. When the location of an unknown sample could not be determined from the

established database, it is possible that its SMTDR value could be out of the range of

In this study, roselle raw material spectrum database was established by import-

The established method of Assured ID database of roselle can be used as a reference database for roselle sample from unknown geographical locations in Malaysia

The authors thank the Director General of Health, Malaysia, for the permission to publish and the Director of Institute for Medical Research (IMR), Kuala Lumpur for the support. This work was financially supported by the NKEA AGRICULTURE (EPP#1) and NKEA Research Grant Scheme (NRGS) (Grant No: NH1014D060).

ing the spectrum of each individual plant into the system. Each of the sample spectrum from different locations has formed their own position in the 3-D principle component graphs and combined to form the sphere separated by IMD. Validation of given simples was used to test the established database for its accuracy. The validation showed that only one out of six samples from each batch of sample was validated correctly, indicating a success rate of only 17%. On the other hand, the method successfully discriminated sample location in western coastline. It is concluded that with this established database, more than 50% of the validation

detected the sample within the range of western coastline.

with few limitations, but further improvement is needed.

**4. Conclusion**

the average.

**Acknowledgements**

**118**

Choong Yew Keong1 \*, Nor Syaidatul Akmal Mohd Yousof<sup>1</sup> , Jamia Azdina Jamal<sup>2</sup> and Mohd Isa Wasiman1

1 Phytochemistry Unit, Herbal Medicine Research Centre, Institute for Medical Research, National Institute of Health, Minister of Health Malaysia, Shah Alam, Selangor, Malaysia

2 Drug and Herbal Research Centre, Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia

\*Address all correspondence to: yewkeong@imr.gov.my; yewkeong11@yahoo.co.uk

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

## **References**

[1] Ma'arup R, Aziz MA, Osman M. Development of a procedure for production of haploid plants through microspore culture of roselle (*Hibiscus sabdariffa* L.). Scientia Horticulturae. 2012;**145**:52-61

[2] Sua C-C, Wang C-J, Huang K-H, Lee Y-J, Chan W-M, Chang Y-C. Anthocyanins from *Hibiscus sabdariffa* calyx attenuate *in vitro* and *in vivo* melanoma cancer metastasis. Journal of Functional Foods. 2018;**48**:614-631

[3] Roslan I, Shamshuddin J, Fauziah CI, Anuar AR. Fertility and suitability of the Spodosols formed on sandy beach ridges interspersed with swales in the Kelantan—Terengganu Plains of Malaysia for kenaf production. Malaysian Journal of Soil Science. 2011;**15**(1):1-24

[4] Naimah R, Nur Amirah Y, Adzemi MA, Wan Zaliha WS. Quality and growth development of roselle grown on Bris soil in relation to regulated deficit irrigation. Journal of Tropical Plant Physiology. 2014;**6**:23-34

[5] Industrial Crops Statistics, Malaysia. 2016. Department of Agriculture Putrajaya, Malaysia. Available from: http://www.doa.gov. my/index/resources/aktiviti\_sumber/ sumber\_awam/maklumat\_pertanian/ perangkaan\_tanaman/perangkaan\_ tnmn\_industri\_2016.pdf

[6] Wahabi HA, Alansary LA, Al-Sabban AH, Glasziuo P. The effectiveness of *Hibiscus sabdariffa* in the treatment of hypertension: A systematic review. Phytomedicine. 2010;**17**(2):83-86

[7] Hopkins AL, Lamm MG, Funk JL, Ritenbaugh C. *Hibiscus sabdariffa* L. in the treatment of hypertension and hyperlipidemia: A comprehensive review of animal and human studies. Fitoterapia. 2013;**85**:84-95

[8] Actis-Goretta L, Ottaviani JI, Keen CL, Fraga CG. Inhibition of angiotensin converting enzyme (ACE) activity by flavan-3-ols and procyanidins. Federation of European Biochemical Societies Letters. 2003;**555**:597-600

[9] Ojeda D, Jiménez-Ferrer E, Zamilpa A, Herrera-Arellano A, Tortoriello J, Alvarez L. Inhibition of angiotensin convertin enzyme (ACE) activity by the anthocyanins delphinidin- and cyanidin-3-Osambubiosides from *Hibiscus sabdariffa*. Journal of Ethnopharmacology. 2010;**127**:7-10

[10] Juhari NH, Bredie WLP, Toldam-Andersen TB, Peterse MA. Characterization of *Roselle* calyx from different geographical origins. Food Research International. 2018;**112**:376-389

[11] Emmy H, Amin I, Normah H, Mohd-Esa N, Ainul ZAB. Effects of defatted dried roselle (*Hibiscus sabdariffa* L.) seed powder on lipid profiles of hypercholesterolemia rats. Journal of Science and Food Agriculture. 2008;**88**:1043-1050

[12] Adegunloye BJ, Omoniyi JO, Owolabi OA, Ajagbonna OP, Sofola OA, Coker HA. Mechanisms of the blood pressure lowering effect of the calyx extract of *Hibiscus sabdariffa* in rats. African Journal of Medicine and Medical Sciences. 1996;**25**:235-238

[13] Hua R, Sun S-Q, Zhou Q, Noda I, Wang B-Q. Discrimination of fritillary according to geographical origin with Fourier transform infrared spectroscopy and two-dimensional correlation IR spectroscopy. Journal of Pharmaceutical and Biomedical Analysis. 2003;**33**:199-209

[14] Hussain K, Ismail Z, Sadikun A, Ibrahim P. Evaluation of metabolic

**121**

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline…*

cold and hot water extracts of spices against fungal pathogens of Roselle (*Hibiscus sabdariffa*) in vitro. Microbial Pathogenesis. 2012;**52**(2):125-129

*DOI: http://dx.doi.org/10.5772/intechopen.84837*

changes in fruit of *Piper sarmentosum*in various seasons by metabolomics using Fourier transform infrared (FTIR) spectroscopy. International Journal of Pharmaceutical and Clinical Research.

[15] Zhou Q, Sun S-Q, Yu L, Xu C-H, Noda I, Zhang X-R. Sequential changes of main components in different kinds of milk powders using two-dimensional infrared correlation analysis. Journal of Molecular Structure. 2006;**799**:77-84

[16] Zuo L, Sun S-q, Zhou Q, Tao J-x, Noda I. 2D-IR correlation analysis of deteriorative process of traditional Chinese medicine 'Qing Kai Ling' injection. Journal of Pharmaceutical and Biomedical Analysis. 2003;**30**:1491-1498

[17] Keong CY. Chapter 8: Fourier Transform infrared and two dimension infrared correlation spectroscopy for substance analysis. In: Nikolic G, Cvetkovic D, Cakic M, editors. Ebook: Fourier Transform. Rijeka, Croatia: InTechOpen; 2017. DOI: 10.5772/66584

[18] Choong Y-K, Sun S-Q, Zhou Q, Lan J, Lee H-L, Chen X-D. Verification of *Ganoderma* (*lingzhi*) commercial products by Fourier transform infrared spectroscopy and two-dimensional IR correlation spectroscopy. Journal of Molecular Structure. 2014;**1069**:60-72

[19] Choong YK, Xu CH, Lan J, Chen XD, Jamal JA. Identification of geographical origin of Lignosus samples using Fourier transform infrared and two-dimensional infrared correlation spectroscopy. Journal of Molecular Structure. 2014;**1069**:188-195

[20] Norhayati Y, Ng WH, Adzemi MA. Effects of organic fertilizers on growth

and yield of r Roselle (*Hibiscus sabdariffa* L.). Malaysian Applied Biology. 2019;**48**(1):177-184

[21] Eslaminejad T, Zakaria M, Tahereh E. Anti-fungal activity of

2009;**1**(2):68-71

*Establishment of FTIR Database of Roselle Raw Material Originated From Western Coastline… DOI: http://dx.doi.org/10.5772/intechopen.84837*

changes in fruit of *Piper sarmentosum*in various seasons by metabolomics using Fourier transform infrared (FTIR) spectroscopy. International Journal of Pharmaceutical and Clinical Research. 2009;**1**(2):68-71

[15] Zhou Q, Sun S-Q, Yu L, Xu C-H, Noda I, Zhang X-R. Sequential changes of main components in different kinds of milk powders using two-dimensional infrared correlation analysis. Journal of Molecular Structure. 2006;**799**:77-84

[16] Zuo L, Sun S-q, Zhou Q, Tao J-x, Noda I. 2D-IR correlation analysis of deteriorative process of traditional Chinese medicine 'Qing Kai Ling' injection. Journal of Pharmaceutical and Biomedical Analysis. 2003;**30**:1491-1498

[17] Keong CY. Chapter 8: Fourier Transform infrared and two dimension infrared correlation spectroscopy for substance analysis. In: Nikolic G, Cvetkovic D, Cakic M, editors. Ebook: Fourier Transform. Rijeka, Croatia: InTechOpen; 2017. DOI: 10.5772/66584

[18] Choong Y-K, Sun S-Q, Zhou Q, Lan J, Lee H-L, Chen X-D. Verification of *Ganoderma* (*lingzhi*) commercial products by Fourier transform infrared spectroscopy and two-dimensional IR correlation spectroscopy. Journal of Molecular Structure. 2014;**1069**:60-72

[19] Choong YK, Xu CH, Lan J, Chen XD, Jamal JA. Identification of geographical origin of Lignosus samples using Fourier transform infrared and two-dimensional infrared correlation spectroscopy. Journal of Molecular Structure. 2014;**1069**:188-195

[20] Norhayati Y, Ng WH, Adzemi MA. Effects of organic fertilizers on growth and yield of r Roselle (*Hibiscus sabdariffa* L.). Malaysian Applied Biology. 2019;**48**(1):177-184

[21] Eslaminejad T, Zakaria M, Tahereh E. Anti-fungal activity of cold and hot water extracts of spices against fungal pathogens of Roselle (*Hibiscus sabdariffa*) in vitro. Microbial Pathogenesis. 2012;**52**(2):125-129

**120**

*Fourier Transforms - Century of Digitalization and Increasing Expectations*

[8] Actis-Goretta L, Ottaviani JI, Keen CL, Fraga CG. Inhibition of angiotensin converting enzyme (ACE) activity by flavan-3-ols and procyanidins. Federation of European Biochemical Societies Letters. 2003;**555**:597-600

sambubiosides from *Hibiscus sabdariffa*.

[9] Ojeda D, Jiménez-Ferrer E, Zamilpa A, Herrera-Arellano A, Tortoriello J, Alvarez L. Inhibition of angiotensin convertin enzyme (ACE) activity by the anthocyanins delphinidin- and cyanidin-3-O-

Journal of Ethnopharmacology.

[11] Emmy H, Amin I, Normah H, Mohd-Esa N, Ainul ZAB. Effects of defatted dried roselle (*Hibiscus sabdariffa* L.) seed powder on lipid profiles of hypercholesterolemia rats. Journal of Science and Food Agriculture. 2008;**88**:1043-1050

[12] Adegunloye BJ, Omoniyi JO, Owolabi OA, Ajagbonna OP, Sofola OA, Coker HA. Mechanisms of the blood pressure lowering effect of the calyx extract of *Hibiscus sabdariffa* in rats. African Journal of Medicine and Medical Sciences. 1996;**25**:235-238

[13] Hua R, Sun S-Q, Zhou Q, Noda I, Wang B-Q. Discrimination of fritillary according to geographical origin with Fourier transform infrared spectroscopy and two-dimensional correlation IR spectroscopy. Journal of Pharmaceutical and Biomedical

[14] Hussain K, Ismail Z, Sadikun A, Ibrahim P. Evaluation of metabolic

Analysis. 2003;**33**:199-209

[10] Juhari NH, Bredie WLP, Toldam-Andersen TB, Peterse MA. Characterization of *Roselle* calyx from different geographical origins. Food Research International.

2010;**127**:7-10

2018;**112**:376-389

**References**

2012;**145**:52-61

2011;**15**(1):1-24

[4] Naimah R, Nur Amirah Y,

[5] Industrial Crops Statistics, Malaysia. 2016. Department of Agriculture Putrajaya, Malaysia. Available from: http://www.doa.gov. my/index/resources/aktiviti\_sumber/ sumber\_awam/maklumat\_pertanian/ perangkaan\_tanaman/perangkaan\_

tnmn\_industri\_2016.pdf

Fitoterapia. 2013;**85**:84-95

[6] Wahabi HA, Alansary LA,

Al-Sabban AH, Glasziuo P. The effectiveness of *Hibiscus sabdariffa* in the treatment of hypertension: A systematic review. Phytomedicine. 2010;**17**(2):83-86

[7] Hopkins AL, Lamm MG, Funk JL, Ritenbaugh C. *Hibiscus sabdariffa* L. in the treatment of hypertension and hyperlipidemia: A comprehensive review of animal and human studies.

Adzemi MA, Wan Zaliha WS. Quality and growth development of roselle grown on Bris soil in relation to regulated deficit irrigation. Journal of Tropical Plant Physiology. 2014;**6**:23-34

[1] Ma'arup R, Aziz MA, Osman M. Development of a procedure for production of haploid plants through microspore culture of roselle (*Hibiscus sabdariffa* L.). Scientia Horticulturae.

[2] Sua C-C, Wang C-J, Huang K-H, Lee Y-J, Chan W-M, Chang Y-C. Anthocyanins from *Hibiscus sabdariffa* calyx attenuate *in vitro* and *in vivo* melanoma cancer metastasis. Journal of Functional Foods. 2018;**48**:614-631

[3] Roslan I, Shamshuddin J, Fauziah CI, Anuar AR. Fertility and suitability of the Spodosols formed on sandy beach ridges interspersed with swales in the Kelantan—Terengganu Plains of Malaysia for kenaf production. Malaysian Journal of Soil Science.

Chapter 8

in Mice

Abstract

and artificial intelligence.

spectroscopy, memory

123

Application of Fourier Analysis of

Cerebral Glucose Metabolism in

Potentiation: A Novel Functional

PET Spectroscopy ( f PETS) Study

Fourier time-series analysis could be used to segregate changes in the ventral and dorsal streams of the visual system in male and female mice. Color memory processes of long-term potentiation and long-term depression could be identified through spectral analysis. We used small animal positron emission tomography and magnetic resonance imaging (PET/MRI) to measure the accumulation of [18F] fluorodeoxyglucose ([18F]FDG) in the mouse brain during light stimulation with blue and yellow filters compared to darkness condition. The mean standardized uptake values (SUV) of [18F]FDG for each stimulus condition was analyzed using standard Fourier analysis software to derive spectral density estimates for each condition. Spectral peaks were identified as originating from the subcortical region (S-peak) by subcortical long-term potentiation (SLTP) or depression (SLTD), and originating from the cortical region (C-peak) by cortical long-term potentiation (CLTP) or depression (CLTD). Luminance opponency occurred at S-peak by SLTP in the dorsal stream in the left visual cortex in male mice. On the other hand, chromatic opponency occurred by wavelength-differencing at C-peak by CLTP in the cortico-subcortical pathways in the ventral stream in the left visual cortex in male mice. In contrast in female mice, during luminance processing, there was resonance phenomenon at C-peak in the ventral stream in the right visual cortex. Chromatic opponency occurred at S-peak by SLTP in the dorsal stream in the right visual cortex in female mice. Application of Fourier analysis improved spatial and temporal resolutions of conventional fPET/MRI methods. Computation of color processing as a conscious experience has wide range applications in neuroscience

Keywords: chromatic opponency, brain, light stimulation, sex, asymmetry,

Color-Induced Long-Term

Philip C. Njemanze, Mathias Kranz and Peter Brust

## Chapter 8
