A study of the variation in traditional knowledge in and

around Nagarkoodal Village, Tamil Nadu, India

Adam Dickinson

An undergraduate thesis in the International Development Studies Program at the University of

Toronto, Scarborough

Supervisors:

Dr. Steven G. Newmaster

University of Guelph

Dr. Subramanyam Ragupathy

University of Guelph

Dr. Ken MacDonald

University of Toronto

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List of Tables and Figures

Figure 1 – Map of study area 21

Figure 2 – Examples of herbarium specimens 26

Figure 3 – Map of studies used in canonical correspondence analysis 31

Figure 4 – Uses of medicinal plants in the Nagarkoodal area 40

Figure 5 – Change in the level of traditional knowledge by age and occupation 45

Figure 6 – Canonical correspondence analysis ordination 54

Figure 7 – Biplot of CCA ordination 54

Table 1 – Study areas included in the canonical correspondence analysis 36

Table 2 – Summary of interview responses 47

Table 3 – Summary of canonical correspondence analysis 52

Table 4 - Statistics for the CCA’s explanatory variables 53

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Table of Contents

Acknowledgements ............................................................................................................... 4

Chapter 1: Introduction and background ................................................................................ 6

1.1 Introduction .......................................................................................................................... 6

1.2 Traditional knowledge and ethnobotany: some background ............................................ 10

1.3 Study area: Nagarkoodal and the surrounding villages ...................................................... 16

1.4 Research Questions and Objectives.................................................................................... 17

Chapter 2: Methods ............................................................................................................. 20

Overview ................................................................................................................................... 20

2.1 Ethnobotanical survey of Nagarkoodal Panchayat ............................................................. 20

2.2 Comparison with nearby studies ........................................................................................ 29

2.3 Development of pedagogical tools ..................................................................................... 34

Chapter 3: Distribution of traditional knowledge in the Nagarkoodal area ........................... 37

Overview ................................................................................................................................... 37

3.1 Results of the ethnobotanical survey ................................................................................. 37

3.2 Demographic Trends ........................................................................................................... 41

Chapter 4: Spatial variation in traditional knowledge ........................................................... 51

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Overview ................................................................................................................................... 51

4.1 Results of canonical correspondence analysis .................................................................... 51

4.2 Discussion of results ............................................................................................................ 55

4.3 Limitations of the data sources .......................................................................................... 57

Chapter 5: Conclusion .......................................................................................................... 59

Overview ................................................................................................................................... 59

5.1 Where does traditional knowledge 'reside' in Nagarkoodal? ............................................ 60

5.2 How traditional knowledge varies over space .................................................................... 62

5.3 Ethnobotanical research, practice, and ways forward ....................................................... 63

Bibliography ........................................................................................................................ 65

Appendix A: Results of ethnobotanical survey ..................................................................... 69

Appendix B: Plant-use matrix used in canonical correspondence analysis ............................. 73

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Acknowledgements

First and foremost, my deepest gratitude goes to the men and women of Nagarkoodal,

Gudupatti, Kalanikattur, Avvai Nagar and Parapatti who took the time to meet with me and

share their knowledge, stories, and experience. It was humbling to converse with people who

had an immense amount of knowledge, and were so willing to share it with an interested

outsider such as myself.

Equal thanks must also be given to the teachers and principal of Puvidham Rural Development

Trust, the NGO and school where I worked from September 2010 to July 2011 on my co-op

work term. It was they who suggested this research to me, and who provided the contacts to

the individuals who shared their stories with me. When it came time to visit these informants,

teachers from the school accompanied me and acted as interpreters, since my own Tamil was

too poor to conduct the interviews myself. Finally, they provided the facilities for collecting

plants and storage for voucher specimens of the plants that were collected.

My research was supervised by Dr. Steven Newmaster and Dr. Subramanyam Ragupathy at the

University of Guelph. Dr. Ragupathy met with me in Chennai and provided advice on how to

proceed with finalizing my research in India. Dr. Newmaster supervised my thesis writing when

I returned to Canada. Furthermore, his advice and feedback were very useful in analyzing and

interpreting my results.

This thesis has been written as a component of the International Development Studies program

at the University of Toronto, Scarborough. Many individuals in the program provided help,

support, and suggestions at various parts in the writing process. I would like to thank, in

particular, Professor Ken MacDonald, who taught our thesis writing course, IDSD01. My peers,

who also took that course and wrote theses of their own, provided invaluable moral support

throughout.

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Finally, I am grateful to all the friends and family who listened to my ideas, provided

suggestions, and challenged my assumptions every step of the way. I am particularly thankful to

a few very talented friends who proofread sections of this thesis and provided detailed

feedback. Any errors that remain, however, are completely my own.

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Chapter 1: Introduction and background

1.1 Introduction

In January of 2011, I was asked to help with the development of a school herbarium at

Puvidham Rural Development Trust in Nagarkoodal, a village in the Dharmapuri District of Tamil

Nadu, India, where I had been working as an intern doing curriculum development since

September 2010. The school had been active in pioneering a new approach to rural education

that emphasized the importance of agriculture, respect for nature, and the traditional

knowledge of rural communities. Having a herbarium in the school would help them to teach

their students about the diversity of plant life in the community, and the importance of plants

in terms of food, medicine, and rituals.

After a few months of collecting plants and pressing them onto herbarium sheets, I had the

chance to sit down with the father of one of the teachers at the school. He told me the

different names of each of the plants, and explained which ones were useful for medicine. He

also showed me a number of other plants growing around the village that I had not collected,

which also had medicinal properties. I was amazed at the ease with which he was able to

identify dozens of species, and the detail in which he described their uses. From my experience

with the schoolteachers and villagers closer to my own age, I had found that most young people

were able to identify a comparatively small number of plants, and knew little about their uses.

It was from this experience that we decided to expand the herbarium project into a survey of

the medicinal uses of plants in the communities surrounding the school. I asked acquaintances

in the nearby villages if they knew people who were knew about medicinal plants. Through a

series of interviews, I found out which plants were used for medicinal purposes, and how

people had learned about them. I also learned why many people had stopped using these

medicinal plants as pharmaceutical medicine had become more popular. More surprisingly, I

found that the knowledge of traditional medicine was alive and well among villagers who

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tended to cows and sheep, since pharmaceutical veterinary medicine remained relatively

difficult to access.

This was not the first study to look at ethnobotanical knowledge in the region. Several studies

had been undertaken in the hilly areas in Dharmapuri and Salem Districts that were home to

indigenous peoples who were ethnically and linguistically distinct from the majority Tamil

population of the state. Interestingly, however, very few studies looked at traditional

knowledge among villagers who belonged to the 'mainstream' Tamil group. This became

especially puzzling once I examined the results of the existing studies. At first, I thought that the

focus on certain ethnic groups may have been due to their far more comprehensive knowledge

of traditional medicine, which would imply that nothing new would be learned from a survey of

a rural Tamil population such as Nagarkoodal’s. Alternately, villages in the area may not have

been considered particularly fruitful for ethnobotanical research because nearby populations

had already been surveyed. I found that neither of these explanations provided a satisfactory

justification for the exclusion of Nagarkoodal – or for that matter, other villages in the area –

from ethnobotanical research. I found informants in the Nagarkoodal area to be exceptionally

knowledgeable about traditional medicine and to have a strong practice of passing on this

information – albeit one that has changed in recent years, with increasing connection to market

towns and the prevalence of pharmaceutical drugs. Moreover, by examining the results of

various surveys from the region, I found that traditional knowledge was highly variable, even

within populations from the same ethnic group and geographic area.

A further limitation of ethnobotanical studies from this region is the negligible difference they

make in the communities they research. These studies collect knowledge from traditional

practitioners and turn that knowledge into academic papers that are neither useful nor

accessible to the communities in which the knowledge originated. Ironically, these studies

frequently lament that younger generations no longer take an interest in traditional practices.

They go on to speak at length about the importance of traditional medicine in the communities

they research, as well as to the wider academic community, without making a connection

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between the two. This study seeks to overcome this disconnect between ethnobotanical

research and the communities in which it is practiced. A key goal of this study is to make the

information available to the community from where it came as well as to the wider research

community, and collaborate with community members so that its results translate into

meaningful benefits.

1.1.1Outline of the study

This study is divided into five chapters. The introduction provides a brief background on the

concept of traditional knowledge, especially as it relates to ethnobotany. Furthermore, it

situates the current research in the literature on ethnobotany. A special emphasis is placed on

ethnoveterinary medicine, because of its importance in the Nagarkoodal area. Finally, the

research objectives are presented.

Chapter Two discusses the methods used in the research. Given the diversity of analyses

conducted, a number of methods were used. The first component of the research consisted of

field interviews with informants in Nagarkoodal and the surrounding areas. Second, traditional

knowledge in the Nagarkoodal area was compared with other nearby areas, which had been

surveyed in prior studies. This analysis was done in order to determine how traditional

knowledge was distributed over space. Finally, a key component of the methodology was an

ongoing collaboration with a local NGO, Puvidham Rural Development Trust. This collaboration,

and its relation to the research, is explained in the last section of the methodology chapter.

The following two chapters present and discuss the results. Chapter Three considers the

distribution of traditional knowledge within the study area. This analysis begins by examining

the responses to the interviews I conducted in May and June of 2011. These interviews yielded

a great deal of information about the different plants that are used for a variety of purposes,

mostly medicinal. Furthermore, informants provided information about themselves and how

they learned about medicinal plants. This discussion provided insight into the distribution of

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traditional knowledge in the society. In general, older respondents who were responsible for

taking care of the family’s livestock tended to hold the most diverse knowledge of medicinal

plants. The interviews also suggested that the concentration of traditional knowledge in the

older generation could be explained by local knowledge-sharing networks within and between

neighbouring villages. Respondents from younger generations, who went through the formal

education system, did not learn about traditional medicine through these networks. Younger

respondents’ knowledge of medicinal plants came primarily from observing how their parents

used traditional medicine in the house.

Chapter Four examines the distribution of traditional knowledge on a larger spatial scale. It

starts by presenting data from six ethnobotanical surveys that were carried out in nearby areas.

This ethnobotanical information is then compared across the six studies, as well as the

Nagarkoodal survey, in order to explore how traditional plant use changes from one community

to the next. In order to quantitatively measure this, a multivariate statistical method, canonical

correspondence analysis, is used. This analysis shows that there is a great deal of variation in

traditional knowledge, even between populations that are close together. It further shows that

certain environmental and demographic variables can influence how similar traditional

knowledge is in different communities.

The conclusion summarizes the main findings and suggests avenues for future research in the

area. Furthermore, it examines how this research can feed back into an ongoing process in the

community to re-value traditional knowledge within the educational system. It argues that

future studies should engage further with the communities in which they work. By doing so,

knowledge can be made available not only to researchers, but also to communities where, in

many cases, the knowledge is being undervalued or lost.

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1.2 Traditional knowledge and ethnobotany: some background

1.2.1 Traditional knowledge: definitions

Traditional knowledge has been defined as knowledge that is specific to one group, and is

situated within certain cultural, environmental, and social conditions (Warren 1991). It has

been characterized by its basis in observation and experience (Brokensha et al. 1980, Warren

1991). In addition to these general observations, three key aspects of traditional knowledge will

be important to its treatment in this study.

Firstly, traditional knowledge has been associated with rural livelihoods, as these have

historically required specialized knowledge systems to observe, understand, and adapt to

natural processes (Wester and Yongvanit 1995, Lasisi et al. 2011). This is especially true in the

case of traditional ecological knowledge, which relates to the familiarity of people with their

environment, including the names and uses of plants (Wester and Yongvanit 1995). Traditional

knowledge and rural livelihoods were seen to be linked in this study, both in terms of its

applications, as well as the way knowledge was gained and transferred.

Secondly, traditional knowledge, more than being a collection of facts or beliefs, is best

understood as a comprehensive system of knowledge, which includes mechanisms for decision-

making, adapting to change, and disseminating new knowledge and practices (Warren 2011).

This system also includes ways in which knowledge is transferred. This includes learning within

the family unit, as well as networks within and between communities (Wester and Yongvanit

1995, Ragupathy and Newmaster 2009). Traditional knowledge systems are contrasted with a

formal, ‘modern’ education system which, in many cases, is privileged over traditional

knowledge. This contrast, and the loss of traditional knowledge, forms a major part of the

justification for undertaking this study.

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Finally, while popular portrayals of traditional knowledge show it as static and unchanging,

research has shown it to be highly specialized and adaptive. Within a society, various groups

have knowledge that reflects their role in the family and society, which in turn is affected by

factors such as class, age, and gender (Wester and Yongvanit 1995, Brooks 2005). This study will

examine the variation in traditional knowledge among social groups, as well as exploring the

variation of traditional knowledge over varying spatial scales.

1.2.2 Knowledge loss in traditional societies

A central problem in the study of traditional knowledge is the loss of this knowledge in societies

across the world (Brokensha et al. 1980, Warren 1991, Sillitoe 1998). One significant reason for

this loss is a pervasive ideology that prioritizes a modern or scientific approach and devalues

traditional knowledge, which it sees as inferior. This ideology has many drivers on the societal

level. In some cases, the dominant education system has been a major mechanism by which

traditional knowledge systems have become devalued. In the Indian context, a state-led push

for universal, ‘modern’ education has resulted in a system that is often ill-equipped to adapt to

local conditions, especially in rural areas (Konantambigi 2011). Community organizations in

South India, such as the National Farming Institute (NFI) have recognized the impact of this bias

in Indian education. The state curricula privilege ‘modern’ lifestyles and occupations, which are

primarily urban, and treat traditional occupations, languages, and knowledge as ‘backward’

(Coelho 2012). These processes of knowledge loss are further exacerbated by rural-urban

migration (Lasisi et al. 2011) and the increased importance of technologies such as

biotechnology, agricultural inputs, and pharmaceutical drugs (Tobin and Swiderska 2001).

1.2.3 Traditional knowledge and research: some issues

Given these trends of knowledge loss, the role of research into traditional knowledge has

become controversial. Researchers such as Warren (1991) and Brokensha (1980) advocate for

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researchers to contribute to an international repository of traditional knowledge, which would

be available to researchers, development practitioners, and the general public. This, they argue,

would help to preserve knowledge that is being lost in traditional societies. They further

contest that this would help development workers in different contexts. Evidence suggests that

in certain situations, traditional knowledge from one area can be applied to development

practices in another. An example is given from Niger, where development workers encouraged

the use of folk pesticides common in India that used seed oil from the neem tree (Azadirachta

indica) which was readily available in Niger but was not used in the same way (Warren 1991).

Other scholars are more skeptical about the place for scientific research in traditional

knowledge. Agrawal (1995) notes that traditional knowledge is not a static entity which can

simply be documented and stored for posterity. Rather, it is a dynamic, changing body of

knowledge and attitudes that is most valuable to the people who use it in their daily life.

Storing traditional knowledge in archives is more likely to benefit academics, development

workers, and pharmaceutical companies, who would be able to access and use the information.

Briggs (2005) points out that by focusing on the facts of traditional knowledge, such as how a

certain plant is used, the underlying ways of knowing are ignored – such as how people learn

about nature. Moreover, such inquiry does nothing to counteract the loss of traditional

knowledge in the communities where it originated. Public databases of traditional knowledge

may be freely available, but they will be neither beneficial nor accessible to many traditional

groups. Only by gaining more control over their own resources, land, and educational systems

will communities be able to decide what role traditional knowledge should play in their

societies.

1.2.4 Ethnobotany and traditional knowledge

Ethnobotany is a branch of research that is concerned with the way in which people use plants

in different cultural and environmental settings. As such, it is a particular study of traditional

knowledge, with an emphasis on the ways in which different social groups use plants for a

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variety of purposes. There has been a push among researchers to focus not only on cataloguing

ethnobotanical knowledge, but also on studying the ways in which this knowledge is classified,

generated, and transferred in traditional societies (Brokensha et al. 1980, Newmaster et al.

2007). There is an emphasis on the ways in which research can contribute to the reinforcement

of traditional knowledge structures rather than simply record them. Put another way,

ethnobotanical research seeks to contribute not only to the academic literature on traditional

knowledge, but also to collaborate with local communities on wider goals of conservation and

development that are based on local environmental knowledge (Martin 1995).

Several studies have highlighted the importance of statistical analyses in determining the

distribution and characteristics of traditional ecological knowledge (Höft et al. 1999). Reports

on the traditional uses of plants can yield information such as species, habit, disease treated

and the parts of the plant that are used, among others. Information about the environments in

which these plants grow and are used can also yield interesting results. Because of the multiple

dimensions of data – plants, uses, and social and environmental factors, among others –

multivariate methods are often required. Salick et al (2009) examined the distribution of

medicinally useful species in the Tibetan Himalaya, relating medicinal plant abundance to

environmental factors such as elevation and rainfall. In order to quantify this, the researchers

used canonical correspondence analysis (ter Braak 1986) and non-metric multidimensional

scaling (Kenkel and Orlóci 1986) to show how the distributions of medicinally important plants

could be explained by changes in the environment. This knowledge can help in shaping

conservation goals and in environmental planning, since it shows areas that are important in

terms of biodiversity and human use.

Traditional medicine, in addition to its effectiveness in curing and preventing disease, has been

linked to a number of wider benefits. Communities that are able to successfully market

medicinal products have been able to generate a significant amount of income from these

products (Torri 2010a, 2010b). Use of traditional medicine has also been linked to sustainable

forest management, as communities must safeguard the ecosystems that produce these useful

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species (Martin 1995, Fabricius et al. 2007). Often, these conservation and economic benefits

are realized through partnerships with organizations that operate on a larger scale, rather than

being restricted to a single group or community. An example is presented by Torri (2010b) of

the Gram Mooligai Company Limited, who work with practitioners of traditional medicine in 58

villages to supply herbal products to companies across India.

1.2.5 Distribution of traditional knowledge

Studies and popular commentary of traditional knowledge have been criticized for generalizing

and romanticizing traditional knowledge. In popular portrayals, traditional knowledge has been

portrayed as unchanging and static – not only across time, but also over space. The popular

concept of collective community knowledge assumes that traditional knowledge is held

uniformly among all members of a society, and constant from one region to the next. This,

however, is not the case.

Knowledge of traditional medicine differs between groups within a society. Brooks (2005) lists

“age, experience, wealth, production priorities, household circumstances, political power,

and … gender” (105) as factors that influence how much, and what kinds of, traditional

knowledge community members may have. Researchers in Kenya, for example, found that

older women who tended gardens knew more about annual herbs, while young men who took

herd animals to pasture knew more about edible plants that grew in the wild (Brokensha and

Riley 1980). In most instances, older individuals have the most detailed ecological knowledge of

anyone in a society (Johannes 1989). Thus it is important to determine not only what plants are

used and how, but which people in the society have the knowledge, and how they learn it.

Traditional knowledge also varies over space. The plant species that are available for human

use change for a given site based on the ecology, relief, climate, and altitude, among other

factors. These factors will influence what plants are available for ethnomedicine. Even within

one ecological zone, inhabitants of different cultural groups may use the same plants in a

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variety of ways, or view certain plants as more useful. To date, however, little research has

been done on the spatial variation in traditional knowledge.

Some studies have, however, examined the effect of different environmental variables on the

distribution of medicinal plants. One study, by Santos et al. (2003) examined ethnobotanical

knowledge in the Nordeste state of Brazil at 36 sites. All of the study sites were part of the

semi-arid caatinga ecosystem, a tropical deciduous forest. The researchers examined the

relationship between the abundance of medicinal plants along precipitation and temperature

gradients. A study by Anderson et al. (2005) shows the change in the abundance and species of

plants at different sites at different elevations in the Tibetan Himalaya. Other studies from Tibet

(Salick et al 1999) and Bolivia (Thomas et al 2008) show the change in species abundance at

sites with varying levels of total biodiversity. These studies, however, do not make note of how

medicinal plants are used at each of these sites, or how their use changes from one place to

another.

1.2.6 Ethnoveterinary medicine

Ethnoveterinary medicine has, in many societies, developed alongside human ethnomedicine,

with practitioners of one being knowledgeable about the other. A review of African studies

indicates that ethnoveterinary knowledge extends into many different applications, such as

treating wounds and illnesses, herding strategies and disease prevention, and various uses in

superstition and magic (McCorkle and Mathias-Mundy 1992). Studies have also suggested that

unlike human ethnomedicine, ethnoveterinary medicine has not been replaced by Western

pharmaceutical cures. Rather, both Western and traditional methods have been employed,

either together or separately, with some effectiveness (McCorkle and Mathias-Mundy 1992,

Wanzala et al. 2005)

In recognition of the importance of this medicine, ethnobotanical surveys have examined

information relating to ethnoveterinary medicine. Martin et al. (2001) have published an

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annotated bibliography of these studies, with over 1200 citations listed from 118 countries.

While the importance and widespread nature of ethnoveterinary medicine is clear, most

studies have been limited to descriptive work such as surveys (Jain and Srivastava 1999).

Analytic or quantitative studies of ethnoveterinary medicine are lacking.

1.3 Study area: Nagarkoodal and the surrounding villages

This study took place in the villages of Nagarkoodal, Gudupatti, Avvai Nagar, Kalanikattur, and

Parapatti. These villages are located in the Dharmapuri District of Tamil Nadu, India.

Dharmapuri District is located between 11 47’ and 12 33’ north latitude, and 77 02’ and 78 40’

east longitude. The region is fairly dry and warm, with annual precipitation in the district

averaging 896 mm. Temperature reaches a maximum of 38 degrees Celsius in April, and a

minimum of 17 degrees in January (Ramya et al 2008). The study area is located on rolling hills

near the Servaroyan Hill Ranges, which are part of the Eastern Ghats.

Over the last three decades or so, these villages have become increasingly connected to the

areas around them. The growth of market towns such as Indur and Nallampalli, and their

connection by improved and paved roads, has facilitated the exchange and transport of

consumer goods and services. The extension of health networks has increased the availability

and social profile of Western medicine, to the point where it has become the first resort for

most families when treating a sick relative. Even a few decades prior, hospitals were present in

only the largest towns in the district. Currently, clinics are available even in small towns, less

than an hour away by bus.

Another relevant feature of the district's geography is the presence of hilly areas inhabited by

tribal communities who remain ethnically and linguistically distinct from Tamils, the majority

ethnic group of Tamil Nadu. These indigenous communities have their own ethnobotanical

traditions and their own knowledge systems, which have begun to be documented by surveys

in the area. What is less well-known is whether the ethnomedical practices of these indigenous

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groups are different from those of nearby villages such as Nagarkoodal. Newmaster et al (2007)

explored this question in their research with the Irulas in the Kodiakarrai Reserve Forest and

found that non-indigenous populations seemed to be unable to identify most medicinal plants

used by the Irulas. To my knowledge, no such comparison has been done among tribal and non-

tribal populations in the Dharmapuri District.

1.4 Research Questions and Objectives

1.4.1 Distribution of traditional knowledge in Nagarkoodal

Studies have shown that traditional knowledge is not shared equally within a population;

certain groups have specialized knowledge drawn from distinct experiences, based on

differentiating factors like age, occupation, sex, and household role (Briggs 2005). How, then, is

traditional knowledge of plants distributed among the villagers in Nagarkoodal and the

surrounding villages? Are there certain groups that know more about ethnomedicine than

others, or have certain specialized knowledge that others do not? What are possible

explanations for one group being more knowledgeable than another?

I will draw upon interviews that took place in May and June of 2011 in Nagarkoodal and the

surrounding villages to characterize the distribution of traditional knowledge in the

Nagarkoodal area. An examination of the interview responses will show which plants are

commonly used for ethnomedical purposes in the study area, and how these plants are used. I

will analyze the interview data to examine trends in the familiarity of informants with

traditional medicine, and what kinds of ethnomedical applications they are most familiar with –

for example, whether they know more cures for humans or for livestock.

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1.4.2 Variation of traditional knowledge over space

While tribal populations make up a small percentage of the population of Tamil Nadu,

ethnobotanical studies tend to disproportionately focus on these groups. Could this be because

non-tribal populations are thought to be lacking in traditional knowledge? Perhaps non-tribal

populations are assumed to use traditional medicine in the same way as tribal populations do.

At the root of these questions is the spatial distribution of traditional knowledge – how does

knowledge of medicinal plants vary over space? To what extent does variation exist? What

could explain this variation?

In order to determine the variation in traditional knowledge, the current study will be

compared with ethnobotanical surveys from nearby areas, most of which involved tribal

populations. This will give some indication of the extent of variation in traditional knowledge

between different populations. Once the extent of variation is known, the possible reasons

behind the variation will be explored. The environmental and demographic features of each site

will be determined, and the influence of each of these variables will be discussed. Is traditional

knowledge more similar in sites that have a similar environment, and where the same plants

are likely to grow? Or does variation in traditional knowledge depend more on social factors,

such as the ethnicity of respondents? What is the role of geographic variables, such as distance

between sites, or remoteness of these sites?

1.4.3 Relevance to local initiatives

This study was completed in partnership with Puvidham Rural Development Trust, an NGO that

runs a school in Nagarkoodal Village. Fostering a learning environment that values traditional

knowledge has been one of Puvidham’s central goals. Accordingly, this study has aimed to

support the work of organizations like Puvidham to give traditional knowledge a key place in

the classroom. For example, the plants we collected in the study went on to serve as specimens

in the school herbarium, a resource built to help expand students’ knowledge of local plants.

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We also used the ethnomedical information gathered from the study’s participants to create a

new set of teaching resources, such as multilingual reference cards about different plants and

their common uses.

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Chapter 2: Methods

Overview

This project was born out of a desire to learn more about the biological diversity and traditional

uses of plants in and around Nagarkoodal village in the Dharmapuri district of Tamil Nadu, India.

As such, it began with an effort to collect and identify plants and their uses, which led to the

ethnobotanical survey that took place between May and June of 2011. The goal of this survey

was to identify medicinal plants in Nagarkoodal and the surrounding villages. It also sought to

examine how this knowledge was distributed in the area – whether certain groups had a more

detailed knowledge of medicinal plants than others, and how this knowledge was passed on or

gained (Section 2.1).

In order to document the spatial distribution of knowledge, the study area was compared with

nearby communities in which ethnobotanical surveys had been carried out. The goal of this

analysis was to determine if there was a spatial component to traditional knowledge, and if so,

on what scale it operated and what the significant spatial factors were in how traditional

knowledge was distributed (Section 2.2).

Finally, this research project aims to produce an ongoing partnership between ethnobotanical

research in the area and local initiatives to retain traditional knowledge in the community. In

order to do so, a number of steps were taken to integrate the research outcomes of the project

with educational institutions in Nagarkoodal village (Section 2.3).

2.1 Ethnobotanical survey of Nagarkoodal Panchayat

The ethnobotanical survey consisted of in-person interviews with informants from the villages

around Nagarkoodal. Two informants were selected from each village, for a total of ten

participants from the five villages in the study area (Nagarkoodal, Kalanikattur, Gudupatti,

21

Parapatti, and Avvai Nagar; see Figure 1).The goal of the interviews was to get an idea of what

plants were traditionally used for medicine in the area, as well as how that knowledge had been

gained. Informants were also asked how their use of medicine had changed as the villages had

become more connected with the industrializing towns around them. In order to accomplish

this, I first selected informants based on referrals from people I knew in the villages. I then

interviewed these informants to get an idea of their background, their knowledge of medicinal

plants, and how they had learned about these plants.

2.1.1 Informant selection

There are a variety of opinions on the most effective way to choose informants in an

ethnobotanical study. Rao and Hajra (1987) argue that the best practice is to find local experts

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or gatekeepers, often elders. Conversely, Martin (1995) cautions against such an approach,

noting that the first informants one gains access to may not be representative of the local

population. In order to gain an understanding of the patterns of traditional knowledge within a

community, a variety of individuals should act as informants: individuals from different age

groups and walks of life, men and women, migrants and natives, or people with different

educational backgrounds. Such an approach would yield data not only about plants' names and

uses, but also on the social variables that determine how knowledgeable people tend to be

about plants within a community.

In the context of the study, I attempted to get as wide of a sample as possible while ensuring

that I prioritized interviews with local experts. Due to time constraints, a more complete,

random sample could not be obtained, and so I based my sampling on referrals from people I

knew in each village. I asked my acquaintances if they knew of individuals who were

knowledgeable about plants and medicine. Often, informants would indicate that there was

another individual in the community who was well-respected for their knowledge of medicinal

plants. This method of 'snowball' sampling led me to most of my informants.

2.1.2 Structure of interviews

The interviews consisted of three main parts. In the first part, informants looked at dried

specimens of plants and identified them by whichever name they knew, and talked about the

main uses of the plant. This had two outcomes – firstly, it established which species were well

known, since those that were more commonly used would be more consistently identified by

the same name and use. Secondly, this helped to gauge the informant's level of familiarity with

medicinal plants, as those who were more familiar would be able to identify more of the dried

specimens.

At the beginning of the study, I had very little idea of which plants were important in local use

and which were not. Therefore my choice of plant samples to be used in interviews was guided

23

by the informants themselves – one participant would point out a particular plant that they

believed to be useful, and I would collect it and present it to future informants. In this way, I

was able to use a sampling of specimens that was more representative of locally valuable plants.

It also allowed a greater degree of consensus for the plants that were sampled, as a number of

people would comment on the same plant.

The second part was a less-structured ‘walkaround’ in which I asked the informant to show me

plants growing in the vicinity that were useful as medicine, or were otherwise notable. We

would walk around the immediately surrounding area, usually the fields or forest near the

informant’s home. The informant would point out different plants and their uses. Where

collecting was possible, I collected a sample and pressed it so that I could show it to other

informants. By this point in the interview, most informants had seen that I was interested in

medicinal plants, and had thought of a few that I had 'missed' that they wanted to show me.

This was usually the most interesting portion of the interview, because it gave insights into the

degree of familiarity each informant had with their environment as well as the different places

and plants that they were drawn to. Indeed, both Martin (1995) and Rao and Hajra (1987)

indicate that less-structured field interactions form the basis of many of the ethnobotanical

insights that are gained in such a study, and help to guide future questions.

Finally, I sat down with each informant and asked them questions about how they learned

about the traditional uses of plants. This semi-structured interview focused on a number of

areas, the first of which were demographic characteristics such as age and occupation of the

informant. Martin (1995) notes that these factors can show which groups hold specialized

knowledge. Indeed, previous research has demonstrated that age, occupation, and gender,

among other factors, can determine what plants an individual is familiar with, and how they use

them (Brokensha and Riley 2009, Brooks 2005)

My initial interactions with community members showed that most people viewed older people

as being more knowledgeable about medicinal plants than younger people. During my first

24

interviews, I found that some informants who tended domestic animals like sheep and cows

knew of many cures that were specifically geared towards treating diseases among their flocks.

For these reasons, I singled out age and occupation as key demographic variables that I chose

to focus on in the last portion of the interview.

In the semi-structured interview, I explored the ways in which informants had learned about

the medicinal uses of plants. I asked informants about the different people they had learned

from, whether it was from relatives or other members of the community. These interviews also

explored the role of travel in gaining knowledge of medicinal plants – informants were asked

whether they had travelled to different villages to learn about different kinds of cures, or

whether they learned from people who had come from different villages. The purpose of these

questions was to shed light on the ways in which knowledge was transferred in these

communities, and what role travel played in the sharing of knowledge.

I also enquired about the extent to which informants had begun to use pharmaceutical

medicine. This was referred to variously as Western medicine, English medicine, or hospital

medicine. I asked about when informants had made the shift to Western medicine, and

whether they still used traditional medicine in any areas of their lives. The interview questions

focused on why and how the shift had taken place, asking informants to go into detail about

how Western medicine had become more available, and why they had chosen to adopt

pharmaceutical over traditional medicine.

2.1.3 Analysis of results

Overall, I found that the semi-structured format worked well for me and for the informants –

most informants participated enthusiastically and took pleasure in showing me the different

uses that they had for local plants. I also found that encouraging informants to speak at length

about subjects that they (and I) found fascinating resulted in a great deal of information being

shared, with interviews sometimes taking up an entire morning! As a result, there was a great

25

deal of information that had to be broken down into a format that could be easily used in

analysis. There were two main types of responses: those that dealt with the uses of specific

plants, and those that went into detail about how informants had gained their knowledge of

medicinal plants.

The responses relating to the uses of plants were tabulated for each interview with categories

matching the recommendations of Martin (1995) and Rao and Hajra (1987), as well as local

ethnobotanical surveys. This methodology was followed so as to ensure that the uses recorded

in these interviews could be easily compared with other surveys – surveys that had been

undertaken in the area were largely based on the methodology put forward by Rao and Hajra

(1987), in the Manual of Ethnobotany, edited by S. K. Jain. For each plant, the Tamil name that

the informant provided was recorded, along with the Latin binomial name. I also recorded the

part of the plant that was used, the mode of preparation, and the ailment that it was said to

treat. Plants were identified by their binomial Latin names using floral keys, specifically Fr.

Mathew's Flora of the Tamilnadu Carnatic and Gamble's Flora of the Madras Presidency. The

identities of the collected specimens were kindly verified by Dr. K. Ravikumar at the Foundation

for the Revitalization of Local Health Traditions in Bangalore, Karnataka, and by Fr. J. Britto at

the Rapinat Herbarium in Thiruchirapalli, Tamil Nadu. Herbarium sheets (voucher specimens)

were kept on-site at the Puvidham Rural Development Trust, where they could be used as a

learning aid in the village school (Figure 2).

Once each interview had been arranged into a table listing each plant and its uses, the

interviews were compiled into a table that recorded all the medicinal plants identified in the

study area. Any plant whose use was agreed upon by two or more informants was included in

the final table. The result was a list of all of the medicinal plants in the study area. This was

arranged in a manner consistent with studies such as Ramya et al. (2008), Kadhirvel et al. (2010),

and Sivaperumal et al. (2010), so that it could be easily compared with other studies later on.

26

27

The final part of the interview explored the ways informants had learned about traditional

medicine. While the interviews were all quite different, they focused on the same main

questions so that informants' responses could be easily compared. These were tabulated along

with basic demographic information – age, sex, village, and occupation. I also recorded the

'expertise' of each individual, which I based off of how many of the dried specimens they were

able to confidently identify. Since the number of specimens shown to each informant varied,

this was recorded as a percentage – so if an informant identified, say, 15 of 19 specimens they

were shown, their 'expertise' score was 78.95%.

2.1.4 Limitations

The clearest limitation of this study was linguistic. Since my Tamil was not adequate to carry out

the interviews myself, they were done through an interpreter, often one of the staff of

Puvidham Rural Development Trust. This had certain advantages, in that these individuals were

familiar to the informants, being from the same villages. However, since they were not trained

in interpretation, and since their experience in translating was not extensive, it is quite possible

that some responses were lost in translation – indeed, I observed many instances of back-and-

forth between interpreters, informants, and other individuals who were present that I did not

fully understand, and were not translated.

It should also be noted that there were other groups which, for various reasons, could not be

included in my analysis. The primary reason for this was the method of informant selection. I

depended entirely on referrals from my acquaintances in the villages, who introduced me to

people they viewed as being knowledgeable about traditional medicine. These referrals led

almost exclusively to male participants, most of whom were elderly. Almost no one directed me

toward female informants. However, I observed that when women were present in interviews –

often, informants' wives – they tended to know just as much as the men who were being

interviewed. The reluctance of informants to recommend that I interview women may have

been because of the social stigma attached to married or older women talking to men,

28

especially foreign men. Another reason why I was primarily referred to older men in the

community may have been because they were thought of as more knowledgeable due to their

elevated social status.

Another variable that could have been explored further was the effect of recent migration. A

number of families in each village had moved there quite recently, either from a neighbouring

village or, in one case, from the neighbouring state. In the situations I observed, people who

had migrated from elsewhere tended to be knowledgeable about some plants, but far fewer

than informants whose families had lived in the same village for generations. In one case,

however, the informant had learned a great deal about medicinal plants growing up in a

different village and had continued to practice veterinary medicine in his new home, learning

about new plants along the way. Indeed, several informants cited travel to different villages as

an important learning experience that taught them about new uses for medicinal plants.

However, no link could be drawn between migration and knowledge of medicinal plants, since

only three informants came from outside their villages, and all had different stories and

different levels of knowledge. It therefore remains to be seen what, if any, link can be drawn

between migration and traditional knowledge. Studies from Nigeria (Lasisi et al. 2011) and

Thailand (Wester and Yongvanit 1995), however, suggest that increased migration may

contribute to a decline in traditional knowledge, since many migrants work in urban areas,

where they have limited opportunities to use or learn about traditional knowledge. Future

studies that are successful in interviewing a more representative sample of the village

population will no doubt be able to shed light on the impact of migration on traditional

knowledge in Nagarkoodal.

29

2.2 Comparison with nearby studies

2.2.1 Overview

The interviews provided some insights into the way spatial variables played a role in learning

about medicinal plants: informants mentioned that they would travel to different villages

during festival times and would see other farmers and herders who would talk about the

different plants that they used for medicinal purposes. I also noticed similarities in the names

and uses people had for plants in villages that were several kilometres apart. In order to

examine the variation in traditional knowledge on a larger scale, the results were compared

with ethnobotanical surveys that had been done in the surrounding areas by researchers in the

nearby towns of Dharmapuri and Salem, as well as one more distant survey from Villupuram

District.

The survey data from Nagarkoodal and the surrounding areas was analyzed using a multivariate

statistical analysis commonly used in ecology, called canonical correspondence analysis (CCA)

(ter Braak 1986). Canonical analysis involves the simultaneous comparison of two or more data

tables, usually one response matrix and one explanatory matrix, though the two are treated

equally rather than as independent and dependent variables, as in redundancy analysis.

Additional explanatory matrices or covariate matrices may also be included (Legendre and

Legendre 1998). CCA has been used in spatial ecology to correlate species assemblages at

various sites with environmental variables at those sites (ter Braak 1987). For example, ter

Braak (1986) used data on hunting spider populations at different sites in a Dutch dune area.

Species presence at each site was recorded on the first matrix, while environmental variables at

each site were recorded on the second. A CCA ordination was able to determine the amount of

variation in spider habitat that was explained by the environmental variables. It also showed

the relative contributions of each environmental variable to habitat choice for the spider

species.

30

Quantitative research in ethnobotany uses many of the same tools as spatial ecology, including

correspondence analysis (Höft et al. 1999). Canonical correspondence analysis (CCA) and

detrended correspondence analysis (DCA) have been used more frequently in quantitative

ethnobotany in the past decade, for a wide variety of uses. Researchers have used CCA to

analyze species distributions in conjunction with ethnobotanical research (Salick et al. 2009).

Newmaster et al. (2006, 2007) used non-metric multidimensional scaling and CCA to explore

mechanisms in ethnobiological classifications. Ragupathy et al. (2009) used DCA in

morphometric classification analysis to differentiate between species identified by traditional

practitioners. Leduc et al. (2006) used correspondence analysis to show the degree of

association between ailments and plant species. However, to our knowledge, the use of this

approach to examine the spatial heterogeneity of knowledge is novel to this study.

There is also a growing trend in ethnobotanical research to measure the abundance of useful

plants as a function of biodiversity or environmental conditions. Studies have used spatial

analysis to compare variation in traditional knowledge with total biodiversity at study sites

(Salick et al. 1999, Thomas et al. 2008). Anderson et al. (2005) used DCA to show the change in

species composition at different sites. Santos et al. (2008) examined 36 years of ethnobotanical

studies from the northeast of Brazil to determine the relationship between useful species

abundance and environmental variables such as altitude or precipitation.

The present study suggests a novel quantitative method for examining the spatial distribution

of traditional knowledge. Data on the traditional uses of plants from the Nagarkoodal survey

were combined with ethnobotanical surveys from surrounding areas. These study areas were

then characterized based on environmental and demographic variables. Variation in traditional

knowledge between the study sites was measured, and CCA was used to determine how much

of this variation could be explained by the environmental and demographic variables.

31

2.2.2 Comparison of study areas with canonical correspondence analysis

Several ethnobotanical surveys have been carried out in Dharmapuri and Salem districts

(Mishra et al. 2008, Ramya et al. 2008, Kadhirvel et al. 2010, Sankaranarayanan et al. 2010,

Sivaperumal et al. 2010, Alagesaboopathi 2011, David and Sudarsanam 2011). Many of these

surveys were done by students and professors at the Arts Colleges in Salem and Dharmapuri,

following the methodology laid out in SK Jain's A Manual of Ethnobotany (1995). Most of the

studies have focused on tribal populations in the hill ranges in Salem and Dharmapuri districts

(Ramya et al. 2008, Kadhirvel et al. 2010, Sivaperumal et al. 2010, Alagesaboopathi 2011). In

contrast, two of the studies (Mishra et al. 2008, Sankaranarayanan et al. 2010) focused on rural

populations comprising both tribal and non-tribal respondents.

While the studies used a consistent methodology, they appeared to produce vastly different

results. There seemed to be many species that were identified at one site and not another, as

32

well as different uses of some plants between study areas. This was surprising, given the short

distances between the study areas. In order to quantitatively determine how similar

ethnobotanical knowledge was between nearby populations, I chose seven ethnobotanical

surveys for comparison: the present study, along with six others, namely Mishra et al. 2008,

Ramya et al. 2008, Kadhirvel et al. 2010, Sankaranarayanan et al. 2010, Sivaperumal et al. 2010,

Alagesaboopathi 2011 (see table 1). Studies were chosen for comparison based on their

proximity to the study area (the closest was about 15 km away, while the furthest was about

150 km from the study area; see Figure 3), as well as their methodology – all the studies were

general surveys that did not focus on any one group of plants or ailment.

To begin, I constructed a matrix that listed the study sites along with the 190 plants that were

mentioned in the studies. I then listed the uses according to 14 categories, namely

dermatological, diabetes, fever, gastrointestinal, general health, wounds, jaundice, leprosy,

pain, respiratory, antivenom, spiritual, ocular and veterinary use (see Appendix B). These

categories were consistent with those used in similar studies of traditional knowledge, such as

Ragupathy and Newmaster (2009). While the surveys under analysis did not use this

categorization, they did provide detailed descriptions of the ethnomedical cures they observed,

which allowed their information to be sorted into categories.

In order to determine the variation in uses between study sites, principal correspondence

analysis (PCA) was performed on the data, which was completed in CANOCO 4.5 (ter Braak

1985). Using PCA to order the data had the effect of spreading the variation along a single axis.

This showed considerable variation (>8 standard deviations) in the use of medicinal plants

between the study sites. The high amount of variation justified the use of a non-linear

ordination model, such as CCA.

In order to examine the effects of environmental and demographic variation on the distribution

of traditional knowledge, I created a second matrix of nine explanatory variables for each of the

study sites. This matrix characterized each site based on three spatial variables (latitude,

33

longitude, and elevation), as well as four biogeographic variables (ecosystem, relief, average

annual temperature and total annual precipitation), and two demographic variables (ethnicity

of respondents and remoteness of study area).

Latitude, longitude and elevation were obtained by manually geocoding each of the study areas

using Google Earth (version 6.1.0.5001). The study areas were then imported into ArcGIS 10

and the latitude and longitude were calculated for the central point (centroid) of each study

area. Average elevation was calculated from a Digital Elevation Model (DEM) of India obtained

from the CGIAR Consortium for Spatial Information at a 3-second (~90 m) grid cell resolution.

The dominant ecosystem type was obtained from the European Commission's Global Land

Cover 2000 dataset at a 30-second (~1km) resolution. The ecosystem type that was chosen

corresponded to the most common non-agricultural land use in the study area. Agricultural

land use was not considered, since most medicinal plants in the study areas grew in forested

areas. Temperature and precipitation data were obtained at 30s resolution from the Worldclim

dataset (Hijmans et al. 2005). Relief, remoteness, and ethnicity of respondents were based on

maps of the study areas provided in the reports, as well as personal familiarity with the study

areas based on my field experience. CANOCO 4.5 was used to complete a CCA that

incorporated the response matrix (uses of plants at each study site) and the matrix of

explanatory variables.

Finally, I applied a series of covariates to the data to see whether unrelated variables such as

researcher bias affected the results of the CCA ordination. Covariates are factors that are not

intrinsically related to either the dependent variable (use of medicinal plants) or independent

variables (the nine explanatory variables), but which may influence the distribution of data. For

example, studies by the same authors may use certain approaches that skew the results, such

as focusing disproportionately on a certain family of plants, a certain disease, or choosing a

small number of informants who may not be representative of traditional knowledge in the

population.

34

In order to quantify the covariates, I chose three metrics for ‘bias’ that may have been

incorporated into the research. The first was institutional affiliation, either of the lead author,

or of the majority of non-lead authors. This was designed to test whether researchers from the

same institution tended to reach the same conclusions when they did their research,

independent of differences in the study area. The second was the most frequent plant family

among the plants identified, and the third was the most frequent illness/use category. While all

the surveys purported to be general and comprehensive, the results of some studies were

skewed toward a certain illness or plant family.

When the covariates were applied to the data in CANOCO 4.5, they were not found to influence

the results, as they explained less than 0.2% of the variation in the use of medicinal plants.

However, this does not guarantee that factors such as researcher bias had no effect on the data.

Rather, it simply means that there was no quantitative difference in the results obtained by

different groups of researchers. It is still possible, for example, that the data collected by the

researchers were not entirely representative of the communities in which they were collected.

(For further discussion of possible data issues in these studies, see section 4.3.)

2.3 Development of pedagogical tools

A major impetus for this research project was the marginalization of local, rural knowledge in

the mainstream school system. Children in rural areas often find themselves in classrooms

where everything from the lesson material and course books to the methods and expectations

of the teachers are heavily biased in favour of urban ways of knowing and living (Coelho 2012).

In an environment where subsistence farmers are frequently denigrated as backward, illiterate,

and uneducated, children often learn to devalue traditional knowledge and ways of knowing

(Konantambigi 2011).

Research that recognizes the importance of traditional knowledge has a further obligation: to

actively contribute to preserving it. That is why an important part of the methodology of this

35

project is an ongoing co-operation between the researcher and the village school. The

specimens collected for this project were kept in the village for use by the teachers and children

of the school. As part of the collaboration with the village school, I worked with schoolteachers

to develop activities to encourage younger students to learn about how previous generations

used plants. A further product of this research will be a collection of reference cards, written in

Tamil and English, that explain the ways in which certain plants are traditionally used in the

surrounding villages. All of the information on these cards came from the interviews with

informants.

36 Table 1: Studies used in the canonical correspondence analysis, along with environmental and demographic variables.

Authors Study Area Number of

Respondents

Number of Species

Identified

Ethnicity of Respondents

Vegetation Type

Relief Elevation Temperature

(Annual mean)

Precipitation (Average

annual total) Remoteness

Ramya et al. Vattal Hills 7 27 Malayali Tropical moist

deciduous Hilly 736 m 25.0:C 958 mm High

Mishra et al.

Salem District (various

sites)

not given 61 Tamil Tropical

evergreen/ semievergreen

Hilly 483 m 26.6:C 967 mm Low

Kadhirvel et al. Chitteri Hills 12 55 Malayali Tropical

evergreen/ semievergreen

Hilly 761 m 24.9:C 1075 mm High

Sivaperumal et al. Kottur Hills 12 44 Malayali Tropical moist

deciduous Hilly 649 m 25.5:C 845 mm High

Sankaranarayanan et al.

Villupuram District (various

sites)

275 45 Tamil Tropical dry

deciduous Lowlands 38 m 28.4:C 1065 mm Low

Dickinson (present study)

Nagarkoodal Taluk

10 28 Tamil Tropical dry

deciduous Plateau 421 m 27.0:C 868 mm Low

Alagesaboopathi Pennagaram

Taluk not given 18 Kurumba

Tropical dry deciduous

Plateau 430 m 26.8:C 804 mm Low

37

Chapter 3: Distribution of traditional knowledge in the Nagarkoodal

area

Overview

Between May and June 2011, I carried out an ethnobotanical survey of the villages surrounding

Nagarkoodal, Tamil Nadu. The immediate objective was to create a herbarium for use in the

school at Puvidham Rural Development Trust in Nagarkoodal Village. The long-term objective

was to undertake a detailed ethnobotanical survey that would examine the traditional uses of

plants in the Nagarkoodal area. The survey would also determine how the knowledge of

traditional medicine was passed on, and which groups, if any, were more knowledgeable.

The results of the ethnobotanical survey are given in section 3.1. Here, details are given on the

identified plant species and their uses. In section 3.2, the interview responses are analyzed to

show interesting trends in traditional knowledge in the Nagarkoodal area. It was found that

older respondents tended to know more about traditional medicine (section 3.2.1). Family

members who were in charge of tending the family herds possessed a wealth of

ethnoveterinary knowledge that they used on a regular basis. They also tended to be more

familiar with traditional medicine in general, both for humans and for animals (section 3.2.2).

Finally, it was found that in previous generations, localized networks were present in which

knowledge of agricultural, medicinal, and veterinary practices were shared and developed.

While these networks played a role in the learning of the oldest informants, their importance

has diminished among younger generations (section 3.2.3).

3.1 Results of the ethnobotanical survey

Informants were asked to identify a number of plants that they knew to be medicinally useful.

This was done by showing informants dried plant specimens and asking them for the name and

use of these plants. Once this was done, I asked informants to show me plants growing in the

vicinity of where the interview took place that were medicinally useful. The result of these

38

interviews was a body of ethnobotanical data that included information on the local and

botanical name of each plant, the disease it was used to treat, the parts of the plant used in the

treatment, and the method of treatment. These responses were tabulated first for each

individual informant (see Appendix A). Once this had been done for all informants, plants

whose use was agreed upon by at least two informants were included in a species-use table

(Appendix B). This classified plants into fourteen categories after Ragupathy and Newmaster

(2009) based on usage, namely dermatological, diabetes, fever, gastrointestinal, general health,

wounds, jaundice, leprosy, pain, respiratory, antivenom, spiritual/magic, ocular and veterinary

use.

A total of 65 plants were identified by informants. However, only 28 of these were named more

than once. Plants that were only identified as useful by one respondent were no included in the

analysis (Appendix A). The 28 medicinally useful plants were collected and pressed, and

voucher specimens were kept at Puvidham Rural Development Trust in Nagarkoodal Village.

Their identities were confirmed in the field using Fr. Mathew's (1983) Flora of the Tamilnadu

Carnatic and Gamble and Fischer's (1921) Flora of the Madras Presidency, and further by Fr.

Britto at Rapinat Herbarium in Thiruchirapalli, Tamil Nadu, and Dr. K. Ravikumar at the

Foundation for the Revitalization of Local Health Traditions in Bangalore, Karnataka.

The most common medicinal usage was pain medication, especially for ulcers. Eleven plants

were used for pain relief, mostly members of Euphorbiaceae and Apocynaceae with milky sap

that were said to have analgesic properties. The next most common use categories (seven

reports each) were treatments for wounds – mostly leafy plants such as Tridax procumbens or

Lantana camara – and veterinary medicine, which encompassed a range of uses. Other uses

included treatments for poisonous bites (6), fever (4), dermatological conditions (3), general

health (3), gastrointestinal problems (2), religious ceremonies or magic (2), eyes (2), diabetes

(1), and respiratory illness (1) (Figure 4a).

39

Informants used many parts of the plant in traditional medicine, though there was a strong

preference for leaves in most cures. Nearly two-thirds of all cures involved plant leaves in some

form. Latex was also common, especially as an analgesic. Cures involving roots, seeds, bark or

twigs were less widespread (Figure 4b).

Useful plants came from a range of families. The most common was Apocynaceae, with five

plants from that family being reported as useful (18% of the total). Other common groups were

Leguminosae (4 plants, 14%), Euphorbiaceae (n=3; 11%) Convulvulaceae, Cucurbitaceae,

Meliaceae and Lamiaceae (n=2; 7%). Acanthaceae, Anacardiaceae, Compositae, Gentianaceae,

Moringaceae, Poaceae, Sapindaceae, and Verbenaceae were all represented by a single plant

each. Plants of various habits were used, with trees and creepers being the most common with

eight species of each being recorded in the survey. Herbs (n=7) and shrubs (n=5) were also

common (Figure 4c).

Many plants were used in a variety of cures. While the majority (15, 54%) had only one agreed-

upon use, a large proportion (10, 36%) had two uses, and a smaller percentage (3, 11%) had

three or more. The clear outlier was veppam, or the neem tree (Azadirachta indica), which was

commonly used in festivals and hung outside doorways to ward off snakes and evil magic. In

addition to these spiritual uses, its leaves were used as a fever medication and snakebite

remedy, while its seed oil was applied to wounds and rashes to accelerate healing and relieve

pain, and its twigs were used as toothbrushes.

Veterinary medicine has an important place in the ethnomedicine of the Nagarkoodal area.

Almost half (n=13, 46%) of all plants identified were used for veterinary medicine for cows,

chickens, and goats. A minority (3, 11%) were used solely for veterinary medicine (Figure 4d).

Veterinary applications were highly specialized, especially for cows. Several cures were

mentioned for kundu, a nose inflammation that was apparently quite common in cows in the

area , including one widely-reported decoction of thumbai (Leucas aspera), thovarai (toor dal,

Cajanus cajan) and chillies, which was chewed by the farmer and then blown into the cow's

40

41

nostrils. Interestingly, no mention of this disease could be found in ethnobotanical literature

from Tamil Nadu, which may indicate a cure that is unique to the area. Various plants were also

noted to be good for indigestion – if cows or goats were constipated or had diarrhea, they

would be grazed on various plants to counteract the indigestion.

3.2 Demographic Trends

3.2.1 Age of respondents

Overwhelmingly, the respondents who had the most detailed knowledge were older people,

which is consistent with a number of similar surveys done in the area. Based on surveys done

across Dharmapuri District, (Ramya et al. 2008, Kadhirvel et al. 2010, Sivaperumal et al. 2010), it

seems that knowledge that was once passed on from elders to younger generations is no longer

being communicated to the same extent. Similar findings have been recorded in other parts of

Tamil Nadu (Sankaranarayanan et al. 2010), suggesting that a lack of interest on the part of the

younger generation is causing the decline in traditional knowledge.

The informants in this study represented a wide range of age groups. The mean age of

respondents was 53 years old, and the median age was 50. Three respondents were 65 or older,

while four were 40 or younger (Table 2).

During the interviews, informants were shown a number of dried specimens, which they

identified by whatever name they had for the plant, and the uses they knew for it, if any. In

most interviews, there were a certain number of plants that the informants did not recognize.

This allowed me to create a metric of how knowledgeable informants were – the more dried

plants they recognized, the higher their 'score.' Informants were counted as not knowing a

plant if they indicated that they did not know what it was, or they gave a response that was

clearly incorrect.

42

This metric of informants’ knowledge varied between interviews. Informants recognized

anywhere from 37% to 100% of the plants they were shown, with an average score of 73% and

a median score of 77%. Two informants recognized all of the plants they were shown, and two

recognized fewer than half. The observed trend was for younger informants to be less

knowledgeable and for older informants to be more knowledgeable: respondents aged 40 or

younger identified 55% of the plants they were shown, on average, while those aged 65 or

older recognized an average of 91% of the dried samples. A regression analysis of the results

found that 41% of the variation in knowledge among the respondents was explained by their

age (Figure 5a).

Differences between age groups were observed during other sections of the interview as well.

After looking at the specimens I had brought, informants showed me the land around their

houses or village and indicated medicinal plants that had not been mentioned previously in our

interview. During this stage, older informants tended to identify more useful plants than

younger informants – those aged 65 or above showed me, on average, 17.7 new plants during

this part of the interview, while younger participants (40 or below) identified an average of 4.8

new plants at this stage. It should be noted that this likely overstates the difference between

the groups, since one of the older informants was my first interview; since I had not collected

many plants by that point, he was able to show me over three dozen species that I had not

encountered before. However, even if this interview is not counted, the older group still

observed an average of nearly double the younger group.

The variation in responses between different generations was underscored by the way in which

respondents had learned about the traditional uses of plants. Most younger respondents

indicated that they had acquired their knowledge by watching their fathers and older relatives

using medicinal plants around the home and with their livestock. Older respondents, in contrast,

had learned about medicinal plants through the same observation of relatives, but also through

travelling to different villages and seeing how others were using the same plants. Older

respondents also indicated that they were used to experimenting with different cures,

43

something they could do because they felt they understood the plants well enough to use them

in different ways. This indicates that certain methods of knowledge transfer and acquisition are

becoming less common, as less and less information is exchanged between families and villages

(see section 3.2.3).

Finally, age groups were divided in the frequency and ailments for which they used traditional

medicine. All of the younger informants said that their family's acute medicinal needs were

completely provided for by pharmaceutical medicine. If they used traditional medicine, it was

as a preventative measure to promote general good health, or for their animals. Most elderly

respondents, however, used traditional medicine for their household needs as well as for their

herds. Younger respondents tended to be of the opinion that traditional medicine would not

cure acute conditions quickly or effectively enough. They indicated that if they had the option

to obtain pharmaceutical medicine or hospital care for their family members, they would do so.

These results should be taken with a degree of caution because of the small sample size.

However, they are consistent with qualitative observations made by other studies in the area,

as well as the responses of the informants themselves – many younger respondents indicated

that they had never been able to learn about traditional medicine, and they did not feel a

pressing need to do so.

In addition, the reliability of the quantification of knowledge – as percentage of species

recognized – is limited. Some participants were shown as many as 27 plants, others as few as

eight. It possible that an informant with a score of 100% (8/8) may, in fact, be less

knowledgeable than an informant with a score of 37% (10/27). A further way to see whether an

informant was knowledgeable is by looking at the number of new plants they were able to

identify. In general, informants who were able to identify a greater percentage of dried

specimens were also able to identify a larger number of new plants. This suggests that there is

some credibility to the use of a percentage as a measure of overall knowledge.

44

A further limitation to this analysis is the possible sampling bias in my interviews. Since

interviews were based on referrals I received from people I knew in the villages, they tended to

be people who were well-respected for their use of traditional medicine. Whether these

individuals were, in fact, the most knowledgeable remains unknown, and would need to be

proven by a more random sampling method. It is also important to note that almost all of my

referrals led me to male respondents. A key group that was not considered was female

respondents – only one of the ten respondents was a woman. However, my observations did

not support the assertion that women were less knowledgeable. In fact, whenever participants'

wives or female relatives were present, they often chipped in with new information.

Unfortunately, this could not be documented in the present study, but suggests an avenue for

future studies in the area.

3.2.2 Importance of veterinary medicine

My interviews also indicated that members of the household who were responsible for

overseeing the family cows and goats were more knowledgeable about natural cures, and used

them more regularly. While clinics, and the bus transport to those clinics, had made Western

medicine more easily available for their families, veterinary medicine was not available to the

same extent for their herds. Informants told me that veterinary doctors would come to the

village only once or twice in a year, and there were large crowds to see them. Because of that,

veterinary doctors apparently made rushed diagnoses and were seen as unreliable. If the

informants wanted to bring their sick animals to a veterinary doctor outside of these times,

they would need to travel several kilometres to the nearest market town. For that reason,

informants tended to try out a variety of traditional cures on sick livestock before going to a

veterinary doctor.

45

46

The importance of veterinary medicine was reflected in the selection of informants. When I

asked people to identify villagers who were respected for their knowledge of medicinal plants, I

was consistently pointed to the 'cow doctors' in the village – that is, people who had

distinguished themselves by being able to take good care of livestock. This suggested that

ethnoveterinary medicine had a place of importance in the community.

Ethnoveterinary practitioners were also shown to be more knowledgeable about medicinal

plants in general. On average, respondents identified 16.8 plants with medicinal uses, of which

an average of 5.4 were for veterinary uses. Respondents who identified six or more plants with

veterinary uses also tended to be more knowledgeable overall – they were able to identify

87.05% of the dried specimens, on average (compared to an average of 59.43% for respondents

who identified 5 or fewer plants with veterinary uses). Indeed, a regression analysis showed

that respondents who identified more ethnoveterinary cures had a higher overall knowledge of

medicinal plants, with number of ethnoveterinary plants explaining 31% of the variation in

medicinal plant knowledge (Figure 5b).

47 Table 2: Summary of informants’ responses to interview questions

Village Age Sex

Percentage of specimens

recognized (number of specimens

identified/seen)

Number of new

specimens identified

Total number of

plants used

Number used for animals

Percentage used for animals

How they learned about

traditional medicine

What they use

traditional medicine for

What they use Western medicine for

Gudupatti – 1 30 Male 46%

(6/13) 8 9 2 22%

From father, elders

Mostly animals

Almost all medicine for their family

Parapatti – 2 40 Male 37%

(10/27) 0 9 5 56%

From father, elders

Mostly animals

Almost all medicine for their family

Avvai Nagar – 1

40 Male 61%

(11/18) 7 15 7 47%

From father, elders, travelling

Mostly animals

Very little

Kalanikattur – 1

40 Male 75%

(9/12) 4 16 4 25%

From father, elders

Mostly animals

Most medicine for their family

Nagarkoodal – 1

45 Male 79%

(15/19) 8 10 3 30%

From father, elders

Mostly animals

Almost all medicine for their family

Nagarkoodal – 2

55 Male &

Female (two respondents)

100% (14/14)

5 13 6 46% From father,

elders Mostly

animals

Almost all medicine for their family

Avvai Nagar – 2

60 Female 60%

(12/20) 2 10 0 0%

From father, elders

Mostly people Almost all

medicine for their family

Gudupatti – 2 65 Male 100% (8/8)

36 38 14 37% From father,

travelling

People and animals equally

Very little

Parapatti – 1 70 Male 92%

(24/26) 9 32 6 19%

From father, elders, travelling

Mostly animals

Almost all medicine for their family

Kalanikattur – 2

80 Male 82%

(9/11) 8 16 7 44% From travelling

People and animals equally

Very little

48 In addition, veterinary expertise cuts across age groups. Of the three self-described 'cow doctors' in the

villages, one was 40, another 65, and the third 80 years old. The five respondents who identified an above-

average number of plants with veterinary uses were, on average, 62 years old, higher than the overall group

average of 52.5. One could speculate that while all older respondents were able to learn about medicinal

plants through exchanges with other families and villages, younger respondents learned about traditional

medicine primarily through veterinary applications, since much of the family medicine was provided through

pharmaceutical drugs. It may not, however, be possible to completely disassociate the effects of age and

occupation – while older informants and herders have higher knowledge of traditional medicine, the group of

herders is also, on average, ten years older than the average.

As always, certain caveats must be made to these conclusions, much the same as in the previous section.

Firstly, the small sample size makes it difficult to generalize these findings, and they remain exploratory

analyses that suggest directions for future research. Second, the problems of selection bias are also present

here, given that taking care of the herds is a role that is primarily given to men in this community. My one

female informant, for example, was the only person who did not identify a single plant with veterinary uses. It

is quite possible, then, that if more female informants had been interviewed, they would have identified more

non-veterinary plants. Indeed, since women bear most of the responsibility for caring for the family, it is

logical that they would know more about medicine that could be used for people rather than animals.

3.2.3 Local networks

At the outset of this study, I was aware of the presence of tribal communities near the study area that had a

history of using traditional medicine and whose ethnomedical practice had been documented by researchers

such as Ramya et al. (2008), Kadhirvel et al. (2010), and Sivaperumal et al. (2010). As such, I was interested to

find out how much this knowledge had travelled. This question was the basis of the quantitative analyses

carried out in Chapter Four – it also influenced the questions that I asked in the interviews. Informants were

asked whether they had travelled to other villages, and what role that had played in the development of their

knowledge of medicinal plants.

Of the ten informants, four indicated that travel to other communities had influenced their knowledge of

medicinal plants. For the most part, the distances travelled were quite small – informants described situations

49 where they would travel to a neighbouring village for a celebration. These included celebrations such as the

Tamil New Year, Pongal, and the village festivals – in this region, each village has a yearly week-long festival

around March or April that is different for each village, so that people from neighbouring villages can visit.

These trips allowed them to leave their home villages for a few days at a time, and meet people in other

villages. In these meetings, people exchanged information about their experiences, including farming practices

and ethnobotanical information. Respondents indicated that they learned a great deal from these exchanges.

The effect of travel was related to the age of the informant. Of the four who identified travel as an important

factor in their learning, three were over the age of 65. The one who was not was a migrant from the

neighbouring state of Karnataka who had a very different experience from the other three, in that he had

travelled far away for work, and had developed his knowledge of medicinal plants in another community

before returning to his home village. This seems to imply that this mode of learning – of travel to other villages

and talking with other farmers and herders – has not been as important for younger generations. In these

villages, many young people have gone to market towns or urban centres to work in non-agricultural sectors

such as industry or construction. Since most of their time is spent working outside their villages in jobs that are

unrelated to agricultural or traditional knowledge, they do not have the same opportunities for exchange of

traditional knowledge. It is also possible that the traditional structures of learning have been replaced with

formal schooling, which has been common in the area for several decades.

In previous generations, rural Indians tended to be less mobile, and most of their travel was of the sort

previously mentioned – to nearby villages, without long-term departures from one's home. However,

migration has changed the face of modern India, including remote villages such as Nagarkoodal. Most families

have at least one member working in large cities such as Bangalore or Chennai. Even in the villages themselves,

migrants have settled from across the country. In Nagarkoodal itself, there are now inhabitants who have

migrated from as far away as Maharashtra and Uttar Pradesh, in the north of the country. One of the

informants in this study migrated from the neighbouring state of Karnataka, and credits his travel with much

of the specialized knowledge that he learned about ethnomedicine.

A further consideration for future studies is that women have a very different experience with travel than men.

In contrast to men, who tend to stay in the same village as their parents, women travel to their husband's

village once they are married. Among my acquaintances in the area, some women had moved from several

50 villages away to settle in their new home. In these situations, women bring the traditions and knowledge of

their previous village. This could result in a transfer of knowledge, with women having a very different

perspective from their husbands, since they were brought up in a different village.

51

Chapter 4: Spatial variation in traditional knowledge

Overview

In Chapter Three, the variation of traditional knowledge within the Nagarkoodal area was discussed. It was

suggested that certain groups had specialized knowledge, and that traditional knowledge had been shared, in

previous generations, among highly localized networks of villages. How, then, is knowledge distributed on an

even larger spatial scale? To answer this question, I compared the data I gathered in the Nagarkoodal area

with ethnobotanical surveys that had been completed in the surrounding regions.

These studies were compared using canonical correspondence analysis (CCA). The results showed that there

was significant variation in traditional knowledge between the study sites. It also showed a degree of

clustering between sites with similarities in their uses of medicinal plants, with certain environmental and

demographic variables playing a role in how these sites were grouped together (section 4.1). An analysis of

this clustering showed that certain variables, such as elevation, relief, and ethnicity of respondents, were the

most important in determining how similar the traditional use of plants was at different sites. This analysis

also discussed the high amount of variation in the results (section 4.2).

4.1 Results of canonical correspondence analysis

The Nagarkoodal survey was compared with ethnobotanical surveys that were conducted in nearby areas,

mostly in Salem and Dharmapuri Districts. This comparison was carried out using a canonical correspondence

analysis (CCA) (ter Braak 1986). The first four canonical axes explained 45.1% of the variation, with the

majority (42.5%) explained by the first two axes (Table 3).

52

Table 3: A summary of the canonical correspondence analysis of traditional knowledge of 190 medicinal plants and 24 study sites. The first and second axes explain the majority of variation.

Canonical Axes 1 2 3 4

Eigenvalues 0.812 0.793 0.723 0.657

Variable correlations 0.996 0.995 0.989 0.993

Cumulative percentage variance

explained 26.3 42.5 45.0 45.1

Significant correlation and canonical coefficients were observed in five of the explanatory variables. Of the

spatial variables – latitude, longitude, and elevation – elevation was significant (t-value > 2.1) along both

canonical axes, while neither latitude nor longitude was significant on either axis. Three of the biogeographic

variables – ecosystem type, relief, and average annual precipitation – were significant on both axes, while a

fourth, mean annual temperature, was not. Of the demographic variables, ethnicity was a significant factor

along both canonical axes, while remoteness was only significant along the first canonical axis (Table 4). The

variables that contributed the most to variation along the first canonical axis were elevation (Inter-set

Correlation = -0.8238, Canonical Coefficient = -1.7811), relief (ISC=0.8686, CC=-1.494), and precipitation

(ISC=0.5459, CC=2.006). Along the second canonical axis, the highest contributors were elevation (ISC=-0.5015,

CC=-3.1185), precipitation (ISC=0.4845, CC=-1.3853), and ethnicity of respondents (ISC=0.4620, CC=0.5308).

The study sites were then plotted along the first two canonical axes to show the variation in traditional

knowledge across all seven study sites (Figure 6). The CCA ordination shows significant variation in traditional

knowledge between study sites, with a spread of eight standard deviations (SDs) in the first canonical axis, and

seven standard deviations in the second. The analysis also generated a biplot also shows the degree to which

differences in the use of traditional medicine are explained by the spatial, biogeographical, and demographic

variables listed above (Figure 7).

Some clustering of study sites can be observed in the canonical axis plot (Figure 6). The studies from the

Kottur Hills (Sivaperumal et al. 2010) and Chitteri Hills (Kadhirvel et al. 2010) are located close together in the

plot, as are the studies from Salem District (Mishra et al. 2008) and the Vattal Hills (Ramya et al. 2008). The

53 present study in the Nagarkoodal area shows a high degree of similarity (within 1-2 SDs) with the Kottur and

Chitteri Hill studies, as well as the survey from Pennagaram Taluk (Alagesaboopathi 2011). The most 'distant'

study was the ethnobotanical survey that had been carried out in Villupuram district by Sankaranarayanan and

collaborators in 2010, which was separated from the nearest study by around five standard deviations.

Table 4: Statistics for nine explanatory variables used in canonical correspondence analysis (CCA) of 24 study sites and 190 medicinal plants. Bold values indicate variables with significant correlation and canonical coefficients.

Traits Inter-set Correlation

Canonical Coefficients

t-values

CCA 1 CCA 2 CCA 1 CCA 2 CCA 1 CCA 2

Spatial

Elevation -0.8238 -0.5015 -1.7811 -3.1185 -8.0779 -12.3306

Latitude -0.1187 0.7003 0.0021 0.0015 -0.0021 0.0053

Longitude 0.8469 -0.4181 0.0036 0.0022 0.0072 -0.0033

Biogeographic

Ecosystem -0.0864 -0.2785 -1.1751 0.4279 -10.6313 3.3751

Relief 0.8686 0.2436 -1.4954 -1.7442 -4.6130 -4.6907

Precipitation 0.5459 -0.4845 2.006 -1.3853 18.3835 -10.7421

Temperature 0.5459 0.3795 0.0062 0.0055 0.0025 0.0041

Ethnic Ethnicity 0.2346 0.4620 0.4889 0.5308 6.6003 6.2477

Remoteness 0.3416 -0.0352 2.2912 -0.3853 11.1272 -1.6315

54

55

4.2 Discussion of results

The canonical correspondence analysis showed a high degree of variation in traditional

knowledge between the study sites, though much of this variation (45.1%) was explained by the

spatial, biogeographical, and demographic variables chosen. Moreover, certain variables had a

greater influence than others, with elevation, relief, and precipitation having the highest

correlations on both axes. Ecosystem type and ethnicity of respondents also had an effect,

though their inter-set correlation values were not as high. Others, such as latitude, longitude,

and temperature, were not significant.

Certain study sites were clustered together, indicating that study sites that had similarities in

traditional knowledge shared certain environmental and social characteristics. The studies

carried out in the Kottur Hills (Sivaperumal et al. 2010) and Chitteri Hills (Kadhirvel et al. 2010)

were very closely clustered on the CCA plot. These studies show that the surveyed populations

have the same uses for 24 plants, representing 54.5% of the total uses identified by the Kottur

Hills survey (n=44), and 43.6% for the Chitteri Hills study (n=55). The two study areas were

similar in terms of relief (hilly), remoteness (difficult access), and elevation (2000-3000 feet

above sea level) moreover, both study areas were conducted with informants belonging to the

same ethnic group, Malayali tribals.

These results are surprising given the locations of the study sites – they are about 50 kilometres

from one another, and two other study areas (Pennagaram and Nagarkoodal) lie between them.

However, the Chitteri Hills and Kottur Hills study areas are more closely correlated with one

another than with the more nearby studies. This seems to suggest that similar environmental

and social characteristics play a more important role than the location of the study site. That is,

two sites that are far away but similar are more likely to have similarities in their traditional

knowledge than two sites that are closer to one another, but are different – say, have a

different relief or where respondents are from a different ethnic group.

56

Another obvious clustering in the CCA table is of the Vattal Hills (Ramya et al. 2008) and Salem

District (Mishra et al. 2008) studies. The two study areas were similar in remoteness (difficult

access), precipitation (900-1000mm), and elevation (>3000 feet above sea level). The position

of these two studies on the CCA plot indicates the influence of these variables, especially

elevation (high score) and relief (with ‘hilly' receiving the lowest score). The reliability of these

observations, however, is compromised by the fact that the Vattal Hills study is one of the most

data-poor of all the studies considered in this analysis, with only 27 species identified. As such,

the small sample size may overstate the similarity between the observed uses of medicinal

plants in the two study areas – while only two plants have similar uses in the two study sites,

this represents a 7.4% similarity in uses for the Vattal Hill study.

In the CCA ordination, the Nagarkoodal study is situated close to the Pennagaram study

(Alagesaboopathi 2011), as well as the Chitteri Hills and Kottur Hills – within 1-2 standard

deviations. The Pennagaram study listed three plants whose use was common between the two

study areas, while the Kottur Hills and Chitteri Hills both listed two similar uses. The

Pennagaram study, in addition to being the closest study area geographically, had similar

biogeographic and spatial features. The only difference was in the ethnicity of the respondents

– Kurumba tribals in the Pennagaram study, and ethnic Tamils in the Nagarkoodal area.

Conversely, the explanatory variables were all different between the Nagarkoodal study area

and the Chitteri and Kottur Hill regions. The position of the Nagarkoodal survey in the CCA

ordination appears to be influenced by the precipitation axis, which increases in the bottom-

right direction – the Nagarkoodal study area is one of the driest, with an average annual

precipitation of less than 900mm per year. The Pennagaram study also occupies the upper-left

of the CCA figure, which conforms to expectations, since it is the only other study with average

annual precipitation of less than 900mm.

The study from Villupuram District (Sankaranarayanan et al. 2010) shows the greatest distance

from the other studies in the CCA ordination. This study is the furthest away from the others,

and is located in a different bioregion – the coastal plains of eastern Tamil Nadu, as opposed to

57

the highlands and mountain ranges of Dharmapuri and Salem Districts. This study area had a

higher precipitation and temperature than any of the others. These environmental differences

were reflected in the species identified in the survey, two-thirds of which were not identified in

any other study area.

Finally, it is important that the high degree of variation in the data not be understated. Even in

study areas that were highly clustered within the CCA ordination, there was only 40-50%

overlap in traditional knowledge; the majority of medicinal plant use was unique to each study

area. Indeed, in the second most clustered area, only 7% of knowledge was shared between the

two sites. This points to a highly localized knowledge system, where traditional cures are the

subject of constant change and specialization, and where knowledge may only be shared

regularly over small distances. This is further supported by the interview responses mentioned

in the previous chapter, where respondents indicated that any information they had obtained

from outside their communities was the result of travel to the next village, with wider

exchanges being highly uncommon.

4.3 Limitations of the data sources

It was certainly fortunate for this study that a body of literature already existed on

ethnobotanical knowledge in the area, since this facilitated an analysis of the spatial

distribution of knowledge. However, some features of the data obtained from these studies

make them less than optimal for inclusion into the analysis. Common problems were a low

number of informants, a clearly non-exhaustive sampling of plants, and results that were

skewed toward one use type.

The present study, in the Nagarkoodal area, draws upon ten interviews in five villages. As

discussed in Chapter 3, this low sample size leads to problems in data interpretation, and a lack

of rigour. Comparable informant numbers, however, were also noted in the ethnobotanical

studies used in the CCA ordination. Two studies (Mishra et al. 2008 and Alagesaboopathi 2011)

58

did not disclose the number of respondents in their studies. Of the remaining four, one (Ramya

et al. 2008) interviewed seven respondents, and two (Sivaperumal et al. 2010 and Kadhirvel et

al. 2010) drew upon interviews from twelve informants. Only one (Sankaranarayanan et al.

2010) had a large number of informants, with 275 individuals interviewed. The low numbers of

informants may indicate that the studies are not representative of the population being

researched.

In addition, several of the studies identified relatively few plants. Ramya et al. (2008) identified

27 medicinal species in the Vattal Hills, while studies in the Chitteri Hills and Kottur Hills, which

have similar relief and vegetation, yielded 44 and 55 species, respectively. Similarly,

Alagesaboopathy encountered 18 species in a survey of the Pennagaram Taluk in 2011. The

present study, which took place near Nagarkoodal, less than ten kilometers away in a similar

ecozone, identified 28 medicinal plants. These fairly stark differences suggest that some of the

studies may not have recorded most, or even many, of the plants that are important in their

study areas.

Finally, some of the studies identified cures that fell disproportionately within a single use type.

For example, 25 of the plant uses (34%) identified by Kadhirvel et al. (2010) were cures for

diabetes. In the study by Misra et al. (2008), 28% of all uses were for gastrointestinal ailments.

These anomalies, which were not explained in the studies, suggest either a specialization on the

part of the areas being surveyed – which would be interesting if true – or a bias by the

researcher toward a certain type of ethnomedicine.

59

Chapter 5: Conclusion

Overview

A central finding of this study is that traditional knowledge is dynamic and highly variable in the

Nagarkoodal area, as well as the wider region. Within the Nagarkoodal area, this study

characterized the extent to which different groups knew about the traditional uses of plants.

Following this, the Nagarkoodal survey was compared with nearby regions to determine the

spatial distribution of traditional knowledge.

Chapter Three discussed the results of the interviews that took place in Nagarkoodal and the

surrounding villages in May and June of 2011. Informants were asked about the names and

uses of local plants. This information yielded data about how knowledgeable informants were,

and how this knowledge varied among different groups in the villages. I found that in general,

older informants were the most knowledgeable. Furthermore, informants who took care of

cows or goats had a wealth of knowledge of ethnoveterinary medicine, as well as a greater

knowledge of traditional medicine in general. Informants also discussed how they had learned

about traditional medicine. In addition to knowledge passed on by family members, some

informants mentioned local networks of farmers as sources of knowledge transfer, even though

the importance of such networks had decreased in recent years.

In Chapter Four, a multivariate statistical method, canonical correspondence analysis (CCA),

was used to examine the variation in traditional knowledge between several areas where

ethnobotanical studies had been carried out. The analysis determined that there was a great

deal of variation in traditional knowledge between the study sites. Moreover, upwards of 45%

of this variation was explained by the biogeographical, social, and spatial variables that were

chosen for the analysis. It was suggested that certain variables may be able to explain

similarities in traditional knowledge between study sites.

Lastly, this study was completed in collaboration with the Puvidham Rural Development Trust,

as part of its goal to incorporate traditional knowledge into the local curriculum. In addition to

60

supporting the current research, the ethnobotanical survey was used to create teaching

resources for the local school, including a herbarium that is now used as a teaching aid. It is

through partnerships such as this that this study aims to be relevant not only to the research

community, but also to the community in which the research was done.

5.1 Where does traditional knowledge 'reside' in Nagarkoodal?

In studies of traditional knowledge from across the world, older informants are identified as the

most knowledgeable (Brokensha and Riley 1980, Wester and Yongvanit 1995, Ragupathy and

Newmaster 2009, Sankaranarayanan et al. 2010). In the Nagarkoodal area, older informants

tended to be more knowledgeable about the traditional uses of plants than their younger

counterparts. The interviews yielded a number of possible explanations as to why this is the

case. First, many younger respondents were raised in families that used pharmaceutical

medicines for their relatives' needs. Older informants, on the other hand, still felt comfortable

treating most ailments with traditional cures. Secondly, several of the respondents who were

veterinary doctors were fairly old, meaning it was difficult to be sure of what explained their

knowledge – their work talking care of livestock, or the fact that they grew up using traditional

medicine. In reality, both likely play a role. Finally, many older respondents told me that they

had learned a great deal from travelling to other villages at certain points during the year and

conversing with other farmers and herd-keepers about different agricultural and medical

practices. As members of the younger generations leave the village to work in large towns and

cities, these knowledge networks become less important over time – indeed, only one

informant under the age of 65 noted travel as an experience that led to increased traditional

knowledge.

Ethnoveterinary medicine has been identified as an important source of traditional knowledge,

albeit one which has not been extensively studied (McCorkle and Mathias-Mundy 1992, Martin

et al. 2001). In the Nagarkoodal area, ethnoveterinary medicine is one of the leading uses of

traditional medicine, especially as traditional medicine for humans is being replaced by

pharmaceutical drugs. One key finding in this area was that, as suggested by McCorkle and

61

Mathias-Mundy (1992), overall knowledge of traditional medicine is higher among informants

who are well-versed in ethnoveterinary medicine. This suggests that ethnoveterinary

practitioners are an important group in the Nagarkoodal area, since they have some of the

most diverse traditional knowledge.

The analyses in this section, however, must be taken with a certain amount of caution. Firstly,

the sample size used was quite small (10 informants), and so the patterns observed may have

been due to sampling bias. Furthermore, the method used for quantifying how 'knowledgeable'

respondents were involved calculating a percentage of the total plants that they were shown.

However, the total changed from one informant to the next, as more plants were added into

the study. As such, it is difficult to compare the 'knowledge' scores of two participants. These

conclusions, then, should be seen as exploratory work that suggests possible directions for

future research.

The results may also have been atypical because of the selection method that I used in the

study. By necessity, all of my interviews were based on referrals from acquaintances in the

villages, who I had asked to introduce me to people who knew about traditional medicine.

These referrals were almost exclusively to men, and mostly older men. This likely had

something to do with the privileged status older men hold – because they were respected

members of the community, they were the first ones I was told to talk to. When I did get a

chance to interact with female informants, however, I noticed that their knowledge was just as

detailed as the men’s. Moreover, because of the women’s role in the household, and the fact

that most married women were born in different communities, their use of plants also had a

different character, a potentially interesting aspect of the study that I could not fully explore

with my limited sample.. I was also unable to obtain interviews with participants who had

migrated to the village, to see what the effect of leaving the village was on people's traditional

knowledge. Coupled with the low sample size, it is likely that this selection method led to bias

in the results. A more representative sample would have included, at a minimum, informants

62

from various age groups, men as well as women, and people who had migrated to the

community, or spent time in a larger city.

5.2 How traditional knowledge varies over space

An important contribution of this study is an application of canonical correspondence analysis

(ter Braak 1986) to quantify the variation of traditional knowledge over space. While a similar

methodology has been used to measure the variation in medicinal plant availability, the use of

CCA to measure variation in traditional knowledge is, to my knowledge, novel to this study.

This analysis was carried out by creating two data tables: one with the species and medicinal

uses of plant species that had been identified by ethnobotanical studies in the area, and a

second with explanatory variables at each of those study sites. The result was a measurement

of the variation in traditional knowledge between the study sites. The influence of the

explanatory variables on this variation was also measured, and it was found that the nine

variables explained over 45% of the variation in traditional knowledge between the study sites.

It was very fortunate for this study that data was available on traditional knowledge in nearby

communities. However, the methods used by these studies make their applicability

questionable. Most of the studies, for example, did not interview a wide selection of informants

– the clear outlier in this regard being Sankaranarayanan et al (2010), whose study incorporated

information from 275 respondents. Moreover, it was unclear what selection criteria they used

in choosing whom to interview. Studies varied widely in the number of plants surveyed, even in

areas with similar ecosystems. While the findings of the statistical analysis are certainly

interesting, they must be taken with some caution because of the data sources. It would be

interesting if this statistical analysis was repeated in an area that had been more extensively

surveyed. Ideally, such areas would include studies that involved more informants, and a more

comprehensive survey of useful plants. This would result in a more robust characterization of

the spatial variation in traditional knowledge.

63

5.3 Ethnobotanical research, practice, and ways forward

Numerous studies of traditional knowledge have called for the wholesale documentation of

traditional knowledge and the depositing of this information in international archives for the

public good (Brokenshaw et al. 1980, Warren 1991). This approach has been attacked by

researchers such as Agrawal (1995) and Brooks (2005), not least because these international

archives would not be accessible to the very populations from where the knowledge came.

However, this emphasis on documentation and preservation was evident in the studies that

have been carried out in the area. Researchers justified their research by claiming it would lead

to “conservation of biological resources” (Ramya et al. 2008 p. 1055). However, little is added

to the community's resources through these studies. The specimens collected by the

researchers are sent to herbaria in larger towns, and the research is published in academic

journals. In these repositories, information is likely to benefit academics, development

practitioners, and pharmaceutical companies (Agrawal 1995). If the conservation of biological

resources is to be successful at the local level, it is likely more important to build capacity

among local groups rather than far-off actors like universities or pharmaceutical companies.

Indeed, in the face of legal battles over the intellectual property rights of indigenous groups,

there is a global need to build bridges between traditional practitioners and formal academic

and legal systems (Tobin and Swiderska 2001). In this regard, a collaborative approach that

creates a lasting partnership is likely to be even more useful, since it increases the ability of

communities to take ownership of local resources. As Agrawal (1995) points out, if knowledge

structures are to be preserved within a community, it is important that the community have the

power to decide how that knowledge is preserved and used.

The current study suggests a different approach for ethnobotanical research in the area. This

research was carried out in partnership with a local NGO, Puvidham Rural Development Trust.

The organization has worked for several years on developing a curriculum that emphasizes

traditional knowledge. This research was undertaken in pursuit of that goal. Voucher specimens

were kept in the school herbarium, which was designed as a teaching aid. Resources were

64

developed in Tamil and English so that the responses of informants would be available to the

children and teachers of the school. It is hoped that these resources will help the organization

to strengthen traditional knowledge within its community, just as it is hoped that the current

research will add to the academic literature on ethnobotany.

65

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69

Appendix A: Results of ethnobotanical survey

Medicinal use of plants identified in Nagarkoodal and the surrounding villages.

Family Plant Name Local Name Habit Parts of

plant used

Used for cattle or humans?

Medical Properties

Acanthaceae Justicia

tranquebariensis Mutthipundu Herb

Leaves, twigs

Humans Used for toothache, eye problems

Anacardiaceae Lannea coromandelica Oodiyamaram Tree Bark Cattle/Humans Cattle and Humans – stomach ulcers

Cattle – diarrhea

Apocynaceae Pergularia daemia Kottikittalai,

Korathikittalai, Velliparatthi

Creeper Leaves Cattle/Humans Relief of fever, headaches, coughs,

colds, kundu and indigestion in cattle

Apocynaceae Wrightia tinctoria Veppalai, Veppalai

maram Tree Bark, latex Humans Boils and wounds, some pain

Apocynaceae Calotropis gigantea Yerangunchedi, Yerakkam chedi

Shrub Latex Humans Poisonous bites

Apocynaceae Cryptostegia grandiflora

Nagamalli Creeper Leaves Humans Bites

70

Apocynaceae Gymnema sylvestre Sirrikuriajalai,

Sirikurinjathalai Creeper Leaves Humans Diabetes, eye infections

Compositae Tridax procumbens Thannipundu Herb Leaves Humans Wounds

Convulvulaceae Ipomoea obscura Bombarakkakodi Creeper Leaves Humans Skin condition (selendi)

Convulvulaceae Ipomoea staphylina Unangudi Creeper Leaves Humans Stomach ulcers, skin problems

Cucurbitaceae Corallocarpus

epigaeus Giridinkelangu Creeper Root Cattle/Humans Snakebite, kundu in cattle

Cucurbitaceae Coccinia grandis Kovaikodi Creeper Leaves,

stem Cattle/Humans General health

Euphorbiaceae Euphorbia

heterophylla Paalpundu Herb Latex Humans Constipation

Euphorbiaceae Jatropha gossypiifolia Gothanahai, Gotanchedi, Kotanchedi

Shrub Latex, leaves

Humans Mouth ulcers, open wounds

71

Euphorbiaceae Croton bonplandianus Sintamanipundu Herb Latex Humans Wounds

Gentianaceae Enicostema axillare Vellu arugu, Vellai

arugu Herb Leaves Cattle/Humans

Skin problems (kadi), poisonous bites

Lamiaceae Leucas aspera Thumbatallai/Thumbai Herb Leaves Cattle/Humans Cough, cold, headache,

insect/scorpion bites, kundu in cattle

Lamiaceae Ocimum sanctum Thulasi (domestic) Shrub Leaves Humans General health

Leguminosae Abrus precatorius Sevapugundumani Creeper Leaves Cattle Nose inflammation

Leguminosae Pongamia glabra Pungam Tree Stem Cattle Wounds, pain

Leguminosae Senna auriculata Avarumpu Tree Leaves Cattle/Humans Shampoo, good health (Humans)

Indigestion (Cattle)

Leguminosae Cajanus cajan Cajanus cajan Shrub Leaves, seeds

Cattle/Humans Indigestion in cows

72

Meliaceae Melia azadirach Thulkaniveppai,

Tholakanimaram, Tholkani veppam

Tree Leaves Cattle Dementia, general health

Meliaceae Azadirachta indica Veppam Tree Leaves, seeds

Cattle/Humans Fever, wounds

Moringaceae Moringa oleifera Murungai Tree Leaves Humans Eye care

Poaceae Cynodon dactylon Arugupillu, Arugumbul Herb Whole plant

Humans Headache

Sapindaceae Dodonaea viscosa Vellerithellai, Velleri Tree Leaves Cattle/Humans Broken legs

Verbenaceae Lantana camara Ulimbil (Lantana) Shrub Leaves Humans Injuries

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Appendix B: Plant-use matrix used in canonical correspondence analysis

Uses of medicinal plants at different study sites in Tamil Nadu, India. Medicinal plant use is coded as indicated in the legend below.

1 – Dermatological 2 – Diabetes 3 – Fever 4 – Gastrointestinal 5 – General health

6 – Wounds 7 – Jaundice 8 – Leprosy 9 – Pain 10 – Respiratory

11 – Bites 12 – Spiritual 13 – Eyes 14 - Veterinary

Study Area

Plant Name Family Nagarkoodal 2011 Kottur

Hills 2010

Chitteri Hills 2010

Villupuram District 2010

Pennaga-ram 2011

Salem District 2008 Vattal Hills

2008

Abrus precatorius

Leguminosae 13 3 9 10

Abutilon indium Malvaceae 3 4

Acacia arabica Leguminosae 2 9

Acacia caesia Leguminosae 6

Acacia leucophloea

Leguminosae 6

Acalypha hispida

Euphorbiaceae 4

Acalypha indica Euphorbiaceae 9 14

Acalypha paniculata

Euphorbiaceae 4

Acampe praemorsa

Orchidaceae 6 10

74

Achyranthes aspera

Amaranthaceae 11 5

Acorus calamus Acoraceae 4

Adhathoda zeylanica

Acanthaceae 3 10 10 3

Adhatoda vasica Acanthaceae 5

Aegle marmelos Rutaceae 2 5

Ailanthus excelsa

Simaroubaceae 11

Alangium lamarbi

Cornaceae 11 11

Allamanda cathartica

Apocynaceae 5

Allium cepa Amaryllidaceae 2

Allium sativum Amaryllidaceae 5

Aloe vera Asparagaceae 6 6

Alpinia calcarata

Zingiberaceae 4 10

Alpinia galanga Zingiberaceae 4 10

Alternanthera sessilis

Amaranthaceae 13 14

Amaranthus viridis

Amaranthaceae 1

Andrographis lineata

Acanthaceae 2 2 11

75

Andrographis paniculata

Acanthaceae 4 7 10

Anisomeles malabarica

Lamiaceae 6

Annona squamosa

Annonaceae 5

Argemone mexicana

Papaveraceae 1 1 4 13

Aristolochia bracteolata

Aristolochiaceae 1

Aristolochia indica

Aristolochiaceae 11

Artabotrys hexapetalus

Annonaceae 5

Artemisia vulgaris

Compositae 6 10

Artocarpus hirsutus

Moraceae 10 10

Artocarpus hirsutus

Moraceae

Asparagus racemosus

Asparagaceae 6 5 4 5 10 1

Atalantia monophylla

Rutaceae 9

Azadirachta indica

Meliaceae 3 6 9 11 12 2 5 1

Barleria prionitis

Acanthaceae 3 9 10

Basella alba Basselaceae 4 6

Bauhinia purpurea

Leguminosae 4

76

Bauhinia variegata

Leguminosae 4 5

Belamcanda chinensis

Iridaceae 4 10

Boehmeria nivea Urticaceae 9

Boerhavia diffusa

Nyctaginaceae 7 9

Bombax ceiba Malvaceae 2

Borassus flabellifer

Arecaceae 13 13

Borreria verticillata

Rubiaceae 1

Brassica juncea Brassicaceae 2

Cadaba fruticosa

Capparaceae 4 9 11

Cajanus cajan Leguminosae 14 2

Calonyction muricatum

Convulvulaceae 5

Calophyllum inophyllum

Calophyllaceae 1 11

Calotropis gigantea

Apocynaceae 14 11 11 4 14

Camellia japonica

Theaceae 5

Cardiospermum canescens

Sapindaceae 4

Cassia fistula Leguminosae 4

77

Cassia senna Leguminosae 4 6

Celastrus paniculatus

Celastraceae 5

Centella asiatica Apiaceae 5 6 8 7

Chenopodium ambrosioides

Amaranthaceae 4

Cinnamomum camphora

Lauraceae 5

Cipadessa baccifera

Meliaceae 4

Cissampelos pareira

Menispermaceae

11

Cissus quadrangularis

Vitaceae 6

Citrus medica Rutaceae 5 6

Clausena dentata

Rutaceae 6

Cleome gynandra

Celeomaceae 9

Cleome viscosa Celeomaceae 11

Clerodendrum phlomidis

Lamiaceae 1

Coccinia grandis Cucurbitaceae 5 2 9

Cocculus hirsutus

Menispermaceae

1 9

Coffea arabica Rubiaceae 4 5

78

Coleus amboinicus

Lamiaceae 4 5 10

Coleus aromaticus

Lamiaceae 4 9 10

Colocasia esculenta

Araceae 1 1

Corallocarpus epigaeus

Cucurbitaceae 11 14

Costus speciosus Costaceae 2

Crescentia cujete

Bignoniaceae 5

Crinum asiaticum

Amaryllidaceae 4 5

Croton bonplandianus

Euphorbiaceae 6

Cryptolepis buchananii

Apocynaceae 6

Cryptostegia grandiflora

Apocynaceae 11

Cuminum cyminum

Apiaceae 2 5 9

Curcuma longa Zingiberaceae 5

Cycas circinalis Cycadaceae 4

Cynodon dactylon

Poaceae 9 5 9 5

Dioscorea oppositifolia

Dioscoraceae 9

Dodonaea viscosa

Sapindaceae 6 1 4 6

79

Dorstenia brasiliensis

Moraceae 9

Elettaria cardamomum

Zingiberaceae 9

Elytraria acaulis Acanthaceae 4

Enicostema axillare

Gentianaceae 1 11 9

Ervatamia heyneana

Apocynaceae 5 9

Erythrina indica Leguminosae 9 2 3 5 9

Eucalyptus globulus

Myrtaceae 5 9 9

Euphorbia antiquorum

Euphorbiaceae 9 2 9 9

Euphorbia heterophylla

Euphorbiaceae 4

Euphorbia hirta Euphorbiaceae 10

Evolvulus alsinoides

Convulvulaceae 3

Ficus benghalensis

Moraceae 6 2

Garcinia indica Clusiaceae 9

Gloriosa superba Colchicaceae 1 4

Gmelina arborea Lamiaceae 1

Gymnema sylvestre

Apocynaceae 2 13 2 2

80

Helicteres isora Malvaceae 6

Hemidesmus indicus

Apocynaceae 3

Henckelia incana

Gesneriaceae 9 3

Hibiscus rosa-sinensis

Malvaceae 2 9 9 10

Hibiscus sabdariffa

Malvaceae 5

Holoptelea integrifolia

Ulmaceae 1 6

Impatiens chinensis

Balsaminaceae 1 6

Indigofera aspalathoides

Leguminosae 1 9

Ipomoea batatas Convulvulaceae 2

Ipomoea obscura

Convulvulaceae 1

Ipomoea staphylina

Convulvulaceae 1 9

Ixora coccinea Rubiaceae 1 4 10

Jatropha curcas Euphorbiaceae 1 4

Jatropha glandulifera

Euphorbiaceae 9 5 9

Jatropha gossypiifolia

Euphorbiaceae 9

Justicia simplex Acanthaceae 6

81

Justicia tranquebariensi

s Acanthaceae 9 13

Lannea coromandelica

Anacardiaceae 9

Lantana camara Verbenaceae 6 4 2 4 6

Lawsonia inermis

Lythraceae 6 1 1

Leucas aspera Lamiaceae 9 11 14 9 5 9 3 9 1 5 10

Limnophila indica

Plantaginaceae 3 9

Mangifera indica

Anacardiaceae 4 2 4

Martynia annua Martyniaceae 5

Melia azadirach Meliaceae 14 4 5

Melothria maderaspatana

Cucurbitaceae 10

Mimosa pudica Leguminosae 3 4 9 11 1 4

Mirabilis jalapa Nyctaginaceae 6

Momordica charantia

Cucurbitaceae 2

Momordica dioica

Cucurbitaceae 4 5

Moringa oleifera Moringaceae 14

Mucuna pruriens

Leguminosae 5

82

Murraya koeingii

Rutaceae 2

Musa paradiciaca

Musaceae 11 2 11 11

Nelumbo nucifera

Nelumbonaceae 2

Nerium indicum Apocynaceae 1 5

Ocimum basilicum

Lamiaceae 3 5 9

Ocimum sanctum

Lamiaceae 5 12 3 2 10

Ocimum tenuifiorum

Lamiaceae 3 10

Oroxylum indicum

Bignoniaceae 10

Pandanus amaryllifolius

Pandanaceae 7 9

Pavetta indica Rubiaceae 4 7

Pergularia daemia

Apocynaceae 3 9 11 14 11

Phlebophyllum kunthianum

Acanthaceae 5

Phyllanthus amarus

Phyllanthaceae 7 7

Piper betle Piperaceae 1 1 5 9

Piper nigrum Piperaceae 3 10 4

Plectranthus coleoides

Lamiaceae 9

83

Plumbago zeylanica

Plumbaginaceae 9

Plumeria acutifolia

Apocynaceae 9

Plumeria obtusa Apocynaceae 9

Plumeria rubra Apocynaceae 6

Plumeria rubra Apocynaceae 6 5

Pogostemon heyneanus

Lamiaceae 10

Pongamia glabra

Leguminosae 6 9

Punica granatum

Lythraceae 4 2 4

Quisqualis indica

Combretaceae 3 4

Rhinacanthus nasutus

Acanthaceae 6 6 10 14

Ricinus communis

Euphorbiaceae 13 14

Rubia cordifolia Rubiaceae 5

Santalum album Santalaceae 4 5

Scoparia dulcis Plantaginaceae 2 4 10

Senna auriculata

Leguminosae 4 5 9

Sida cordifolia Malvaceae 10

84

Solanum nigrum Solanaceae 4 9 4 9 9 4 13 9

Solanum surattense

Solanaceae 9

Solanum trilobatum

Solanaceae 10 10

Sonchus oleraceus

Compositae 6

Syzygium cumini Myrtaceae 2

Tamarindus indica

Leguminosae 1 1

Tecoma stans Bignoniaceae 2 5

Tephrosia purpurea

Leguminosae 5

Terminalia chebula

Combretaceae 4 10 10

Thespesia populanea

Malvaceae 1 4

Toddalia asiatica

Rutaceae 9

Trema orientalis Cannabaceae 4 5

Tribulus terrestris

Zygophyllaceae 5 9 5

Trichodesma indicum

Boraginaceae 9 4

Tridax procumbens

Compositae 6

Trigonella foenum-graecum

Leguminosae 2

85

Tylophora indica

Apocynaceae 10 11 4 5

Vitex negundo Lamiaceae 3 9 9 10 1 3 4 5 9 10 10

Withania somnifera

Solanaceae 10 10 9 10 9

Wrightia tinctoria

Apocynaceae 6 9

Zingiber officinale

Zingiberaceae 4 10