3.3. Distribution of Publications by Countries
If the results obtained are analyzed by country, a total of 159 countries have published on this topic.
Figure 4 shows the countries that have published on the subject and the intensity with which they published has been shown. It is observed that China and India stand out over the rest of the countries with more than 10,000 publications, perhaps influenced by traditional medicine, although their most cited works are related to antioxidant activity, both for China [
45], and for India [
46,
47], and in this last country also antidiabetic potential [
4]. The third place is the USA followed by Brazil, both with more than 5000 publications. The most frequently cited publications from these countries focus on antioxidant activity [
48], and antimicrobial activity [
49] for the USA and anti-inflammatory activity for Brazil [
50,
51].
As mentioned, the list of countries is very long, but those with more than 2000 publications are included: Japan, South Korea, Germany, Iran, United Kingdom, Pakistan, Italy, and France. If the overall results obtained are analyzed in their evolution by years, for this list of countries with more than 2000 publications,
Figure 5 is obtained. From this point onwards, three groups of countries can be identified.
The first group is the leaders of this research, China and India, with between 800 and 1100 publications per year. China led the research from 1996 to 2010, and from this year to 2016, the leader was India, after which it returned to China. The second group of five countries is formed in order in the last year of the study: Iran, Brazil, USA, South Korea and Pakistan. This group of countries has a sustained growth over time, with a rate of publications between 200 and 400 per year. It should be noted that Brazil led the third place for a decade, from 2007 to 2016, since then that position is for Iran. The third group of five countries is made up of: Japan, Germany, United Kingdom, Italy, and France. They are keeping the publications around 100 a year, with an upward trend, but at a very slight rate.
If the analysis of the publications by country is made according to the categories in which they publish,
Figure 6 is obtained, which shows the relative effort between the different themes or categories is shown. At first look, it might seem that they have a similar distribution. However, in relative terms the category of Pharmacology, Toxicology and Pharmaceutics is led by Brazil with 35% of its own publications followed by India with 33%. For the Medicine category, in relative terms it is led by China with 29 %, followed by Germany with 27 %. The category of Biochemistry, Genetics and Molecular Biology always takes second or third place for this ranking of countries, standing out especially for Japan and South Korea with 23% and for France with 22%. The fourth category for many countries is Agricultural and Biological Sciences, with Pakistan standing out with 20%, followed by Italy with 16%. The category of Chemistry occupies the fourth category for countries such as Japan with 20% or Iran with 14%. The other categories: Chemical Engineering, Immunology and Microbiology, Environmental Science, Multidisciplinary, or Engineering, are below 5 % in all countries.
According to these results, it can be seen the relative lack of relevance of the category of Agricultural and Biological Sciences for medicinal plants, compared to the categories of Pharmacology, Toxicology and Pharmaceutics, Medicine, or Biochemistry, Genetics and Molecular Biology.
3.4. Institutions (Affiliations)
So far, the distribution by country has been seen, but the research is done in specific research centers (institution or affiliations as are indexed in Scopus) and therefore, it is important to study them.
Table 1 shows the 25 institutions with more than 400 publications, of which 13 are from China (including the first 7), 3 from Brazil, 2 from South Korea, and now with 1: Saudi Arabia, Pakistan, Iran, Mexico, Cameroon, France, and Malaysia.
If the three main keywords of these affiliations are analyzed, it can be seen that there are no great differences, and in fact, they are often the same: Unclassified Drug, Drug Isolation, Drug Structure, Chemistry, Controlled Study, Isolation And Purification, Chemistry, and Plant Extract. They only call attention to “Drugs, Chinese Herbal” which appears in two affiliations: China Academy of Chinese Medical Sciences, and Beijing University of Chinese Medicine, which of course is a very specific issue in this country.
3.5. Authors
The main authors researching this topic are shown in
Table 2, which are those with more than 100 publications on this topic. It is observed that they are authors with a significantly high h-index. On the other hand, it is noteworthy that the first two are not from China or India, which as we have seen were the most productive countries, and also had the most relevant institutions in this area. The lead author is from South Africa, J. Van Staden, and the second from Bangladesh, M. Rahmatullah. The author with the highest h-index is from Germany, T. Efferth.
If the network of collaboration between authors with more than 40 documents is established,
Figure 7 is obtained. Here, there are 33 clusters, where the most important is the red one with 195 authors, where the central author is Huang, L.Q. The second more abundant cluster is the green one, composed of 69 authors. In this cluster, there is no central author, but instead, a collaboration between prominent authors such as Kim, J.S., Lee, K.R. or Park, J.S. The third cluster, in blue, is composed of 64 authors, led by the authors M.I. Choudhary and M. Ahmad.
The fourth cluster, of yellow color is composed of 63 authors, the central authors are Y. Li and H-D. Sun. The fifth cluster, in purple, is also composed of 51 authors, the central author is W. Villegas. It should be noted that this cluster is not linked to the whole network, so they must research very specific topics in their field. The sixth cluster is composed of 48 authors and is cyan colored, the central author is Rahmatullah, M. The cluster of the main author of
Table 2, Van Staden, J., is composed of 23 authors, and would be number 17 in order of importance by number of authors, is light brown, and is located next to that of W. Vilegas but without any apparent connection.
3.7. Clusters
The analysis of the clusters formed by the keywords allows the classification of the different groups into which the research trends are grouped. A first analysis has been made with the documents published between 2009 and 2019 and in two periods, from 2009 to 2014 and from 2015 to 2019.
Figure 9 shows the clusters obtained for the period 2009 to 2014, showing seven clusters, which can be distinguished by color, and in
Table 6 its main keywords have been collected.
The first of these clusters, in red (1-1), is linked to traditional medicine. This is reflected in the main keywords associated with this cluster: phytotherapy, herbaceous agent, traditional medicine, ethnobotany. Within this cluster, the most cited publications are related to the antioxidant function of plants. This includes the prevention of hyperglycemia hypertension [
52], and the prevention of cancer. Of the latter, studies suggest that a reduced risk of cancer is associated with high consumption of vegetables and fruits [
53]. Another topic frequently addressed is the antidiabetic properties, as some plants have hypoglycemic properties [
34]. It should be remembered that diabetes mellitus is one of the common metabolic disorders, acquiring around 2.8% of the world’s population and is expected to double by 2025 [
54].
The second cluster, in green (1-2), appears to be the central cluster, and is related to drugs—chemistry. The main keywords are: drug isolation, drug structure, chemistry, drug determination, and molecular structure. Here, the most cited publications are the search for new drugs [
55] or in natural antimicrobials for food preservation [
56].
The third cluster, in purple (1-3), is focused on in vivo study through studies with laboratory animals, as shown by keywords such as mouse and mice. As it is known that in vivo drug trials are initiated in laboratory animals such as mice, in general studies focused on anti-inflammatory effect [
57,
58].
The fourth cluster, in yellow (1-4), is engaged in the search for drugs. The main keywords in this regard are unclassified drug and drug screening. Within this cluster, the studies of flavonoids stand out [
59]. Flavonoids have been shown to be antioxidant, free radical scavenger, coronary heart disease prevention, hepatoprotective, anti-inflammatory and anticancer, while some flavonoids show possible antiviral activities [
60].
The fifth cluster, in blue (1-5), is focused on the effectiveness of some drugs, and their experimentation on animals. Some of the most cited publications of this cluster over this period are those focused on genus
Scutellaria [
61], Epimedium (
Berberidaceae) [
62] and Vernonia (
Asteraceae) [
63].
The sixth cluster, in cyan (1-6), is aimed at the effect of extraction solvent/technique on the antioxidant activity. One of the most cited publications in this regard studies the effects on barks of
Azadirachta indica,
Acacia nilotica,
Eugenia jambolana,
Terminalia arjuna, leaves and roots of
Moringa oleifera, fruit of
Ficus religiosa, and leaves of
Aloe barbadensis [
64]. Regarding neuroprotection, some publications are the related to genus
Peucedanum [
65] or
Bacopa monnieri [
66]. This cluster is among the clusters of traditional medicine (1-1) and drug efficacy (1-5).
Finally, the seventh orange cluster (1-7) is of small relative importance within this cluster analysis and is focused on malaria. As it is known, malaria is one of the most lethal diseases in the world every year [
67]. Malaria causes nearly half a million deaths and was estimated at over 200 million cases, 90 per cent of which occurred in African countries [
68]. Of the
Plasmodium species affecting humans,
Plasmodium falciparum causes the most deaths, although
Plasmodium vivax is the most widely spread except in sub-Saharan Africa [
69]. On the other hand, this cluster cites
Plasmodium berghei, which mainly affects mice, and is often used as a model for testing medicines or vaccines [
70].
The second period under study, from 2015 to 2019, is shown in
Figure 10, where five clusters have been identified,
Table 7, as opposed to the previous period which was seven. Now, there is no cluster focusing on malaria. In
Figure 10, the colors of the cluster have been unified with those of
Figure 9, when the clusters have the same topic as in the previous period.
The first cluster in order of importance (2-1), the red one in
Figure 10, can be seen to be that of unclassified drug, which has gone from fourth place (1-4) to first in this last period. In this period, research works include one on the therapeutic potential of spirooxindoles as antiviral agents [
71], or the antimicrobial peptides from plants [
72].
The second cluster of this last period (2-2), the one in green in
Figure 10, is the one assigned to traditional medicine, which has now moved up to second place (1-1) in decreasing order of significance. It seems that this cluster of traditional medicine is now the merging with the drug efficacy cluster of the previous period (1-4). This cluster includes research such as oxidative stress and Parkinson’s disease [
73].
The cluster from the previous period that was devoted to animals-in vivo study (1-3), we assume is now divided into three new clusters. The first of these would be the third cluster (2-3), blue in
Figure 10, which can be considered to be dedicated to cancer. One of the works in this cluster is “Anticancer activity of silver nanoparticles from Panax ginseng fresh leaves in human cancer cells” [
74]. Then, the other two are committed to in vivo studies or with animals. The first one seems to be more engaged in vivo study at antidiabetic activity [
75,
76], would be the cyan-colored cluster 4 (2-4). The other cluster (2-5) involved in testing anti-inflammatory activity, with plants such as Curcumin [
77],
Rosmarinus officinalis [
78], would be the purple cluster in
Figure 10.
3.8. Collaboration Network of Countries
Figure 11 shows the collaborative network between countries doing research on medicinal plants.
Table 8 lists the countries of each cluster identified and the main country of each cluster. The countries that are most central to this network of collaboration between countries are India, Iran, Indonesia, and the USA. The largest cluster is led by Brazil, which is also not restricted to its own geographical area as it has strong collaborative links with European countries as well as with neighboring countries such as Argentina. The second cluster led by South Africa also presents the same features as the previous one, some collaborations with nearby countries, Tanzania, Congo, or Sudan, but also with European countries such as France, Belgium, or the Netherlands.
The third cluster is led by India and has very strong collaboration with Iran, but it could also be considered as the central country in the whole international collaboration network. The cooperation with European countries comprises mainly Eastern countries like Poland, Serbia, or Croatia.
The fourth cluster, led by Germany and Pakistan, includes Middle Eastern countries such as Jordan, Saudi Arabia, and United Arab Emirates, which are quite related to the cluster led by China. The fifth cluster seems to have a geographical consideration within Asia by including countries such as Indonesia, Malaysia, Thailand, and Australia. The sixth cluster includes very technologically advanced countries such as USA, UK, Japan, Canada, or South Korea. The seventh cluster is very small in the number of countries. It is made up of very different countries like some in Africa: Cameroon and Kenya; some of Europe as Denmark, and some from Asia like Nepal. In this sense, most of the research linked to African countries in general and to Cameroon particularly is linked to the most frequent parasitic diseases [
79], such as African trypanosomiasis [
80], diarrhea [
81] or tuberculosis [
82]. Finally, the China cluster is made up of nearby areas of influence such as Taiwan, Singapore, Hong Kong, Macau, or Taiwan.