SciELO - Scientific Electronic Library Online

 
vol.52 issue1Performance and sustainability of commercial cooperatives and sole proprietorships citrus farms in Mpumalanga Province, South AfricaAssessment of factors influencing the adoption of improved crop management practices (ICMP) by smallholder farmers in the Boane District, Mozambique author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Article

Indicators

Related links

  • On index processCited by Google
  • On index processSimilars in Google

Share


South African Journal of Agricultural Extension

On-line version ISSN 2413-3221
Print version ISSN 0301-603X

S Afr. Jnl. Agric. Ext. vol.52 n.1 Pretoria  2024

http://dx.doi.org/10.17159/2413-3221/2024/v52n1a14410 

ARTICLES

 

How Sensitive Are South African Postgraduate Research to Pandemic Lockdowns? A Case of Agricultural Economics and Extension Dissertations

 

 

Zantsi S.I; Sotsha K.II; Nkunjana T.III

IAgricultural Economist, Economic Analysis Unit, Agricultural Research Council-Central Office, 1134 Park St, Hatfield, Pretoria, 0028, South Africa Corresponding author E-mail siphezantsi@yahoo.com 0000-0001-9787-3913
IISenior economist, Smallholder Market Access division, National Agricultural Marketing Council, 536 Francis Baard Street, Meintjiesplein Building, Block A, 4th Floor, Arcadia, 0007 Pretoria; ksotsha@namc.co.za
IIISenior Economist, Markets and Economic Research Centre, National Agricultural Marketing Council, 536 Francis Baard Street, Meintjiesplein Building, Block A, 4th Floor, Arcadia, 0007, Pretoria; thabile@namc.co.za

Correspondence

 

 


ABSTRACT

The key to avoiding the next pandemic catastrophe is to be prepared. This research represents an attempt to understand the potential effects of lockdowns on completing Masters and PhD dissertations that focus on smallholder farmer's primary data, taking the example of COVID-19. A sample of four South African universities (Fort Hare, Limpopo, KwaZulu Natal, and Western Cape), which mainly research smallholder farmers using primary data, addresses the study objective. Dissertations completed in 2014-2019 (pre-pandemic) were retrieved from the respective universities' repositories. An abstract appraisal was done to identify dissertations that focused on smallholders and used smallholder primary data. Hence, a smallholder dissertation index (SDI) was computed to measure the susceptibility of each university to lockdown interruptions. The results indicated that the master's and PhD research in the selected universities rely heavily on smallholder primary data (shown by >0.50 SDI), with varying proportions between the universities. Dissertations that used smallholder primary data obtained the data using face-to-face field interviews. This implies that in these institutions, the lockdowns could have negatively affected the writing of master's and PhD dissertations. Consequently, the study concluded that adopting online survey methods might help minimise the impact of lockdowns.

Keywords: Research and Development, Smallholder Farming, Agricultural Economics


 

 

1. INTRODUCTION

There is a general agreement among scholars that research and development (R&D) plays a crucial part in a country's economic growth and development, which in turn leads to a reduction in poverty (Alston, Beddow & Pardey, 2009; Chaminuka, Beintema, Flaherty & Liebenberg, 2019; Liebenberg, Pardey & Kahn, 2011; Pardey et al., 2016). This is particularly true for the agricultural R&D of developing regions, such as sub-Saharan Africa, where agriculture still contributes a relatively larger share of the GDP than developed regions' GDPs (Pardey et al., 2016). In the sub-Saharan region, South Africa has the second-largest expenditure on R&D (Chaminuka et al., 2019).

The impressive R&D returns on investment in agricultural productivity in South Africa have been well-documented by Liebenberg (2013). However, the aforementioned study also notes that before 1994, R&D expenditure and benefits were not evenly distributed across the dual South African agriculture due to colonial policies, which sought to suppress black agriculture and maintain it to a subsistence level (Lipton, 1977). Poor-resource and low-productive smallholder farming still lags in virtually all respects compared to well-advanced and internationally competitive commercial farming (Karaan & Vink, 2014; Sihlobo, 2023).

In addressing this gap between the two "agricultures" in the words of Merle Lipton (1977), the first democratically elected government set out to shift support and expenditure from commercial farming to the development of smallholder farming (Vink, 2001). Several funding bodies, such as the National Research Foundation, have made funding grants available to research institutions and universities (HSRC, 2020). The latter has an advantage because it contributes in at least two ways to the R&D: building human capacity through postgraduate degrees and generating new knowledge to advance agriculture and extension.

While agriculture, particularly agricultural economics and extension, are offered in many institutions of higher learning in South Africa (Vink, 2012), primarily specialised universities and those situated in the rural parts of the country because of proximity to smallholders, focusing on smallholder research. According to Statistics South Africa's 2016 Agricultural Household Survey (AHS), more than two-thirds of smallholder farming households are in three provinces: Limpopo, Eastern Cape, and KwaZulu Natal (StatsSA, 2016). The StatsSA's AHS is one of the few national data sets on smallholder agriculture in the country, which contains general information on smallholder agriculture. Therefore, researchers need a more detailed data set for other specific research questions. Such detailed data sets are often obtained through field surveys by either face-to-face interviews or focus group discussions with smallholder households, among other methods. For these reasons, smallholder agricultural research is primarily data-dependent, and field surveys are the biggest data source.

The outbreak of the COVID-19 pandemic has posed a threat to this ongoing research work on smallholder agriculture because of travel restrictions and prohibitions of large gatherings, including classroom learning (Republic of South Africa, 2020). Some of these factors directly or indirectly affected obtaining primary data on smallholders, thus hindering research and postgraduate completion of master and doctoral dissertations (Stephens et al., 2020). In today's 4th Industrial Revolution and the digital world, where possible, researchers are already using online surveys through platforms such as SurveyMonkey, QuestionPro, Google Forms, Survey Sparrow and others to gather data from farmers (Eastwood et al., 2020). However, this might not be possible for smallholders for at least three reasons. First, smallholders are usually poor and have low literacy levels (StatsSA, 2019). As technology adoption is not prevalent, online platforms as an alternative to data collection are challenging (Bontsa et al., 2023). Secondly, some smallholders are in remote areas with problematic infrastructure and signal connections are typically poor or inaccessible (Rey-Moreno et al., 2016). Thirdly, while 99% of South African households have mobile phone access, only half of these smallholders are estimated to have smartphones (StatsSA, 2019). For these reasons, field surveys are likely to be the main option for obtaining primary data. Consequently, although the impact the COVID-19 pandemic has had on conducting research is yet to be understood and quantified, research specific to smallholders is likely to be severely affected.

Therefore, this article intends to make a small contribution to this emerging problem by first quantifying PhDs and master's dissertations produced within agricultural economics and extension departments in selected South African universities. This is achieved by retrieving dissertations from selected university repositories. Since publishing master's and PhD dissertations online is a more recent activity, this study only focuses on the last six years from which we compute an index under normal circumstances. This forms the basis of our argument for understanding the potential effect COVID-19 has had on dissertations, focusing their research on smallholders. Given the known lockdown restrictions, we argued that we will be in a better position to predict the potential effect once the output under normal circumstances is known. The data and the literature on the impact and effect of the lockdowns have been widely published. In the case of smallholder data, Statistics South Africa and the Human Sciences Research Council have already published some surveys, which assist us in achieving the objective of this study. Although many factors are at play in completing dissertations, this study only focuses on access to data.

The remainder of this paper is structured as follows: the immediate section contextualises the study's research problem by providing a brief overview of the impact of COVID-19 and unpacking investment R&D in agriculture. Section 3 describes the study methods and data. Results are presented in Section 4, while Section 5 discusses the results, offers concluding remarks, and highlights some areas for future work.

 

2. A BRIEF OVERVIEW OF THE EFFECT OF COVID-19 AND AGRICULTURAL R&D

The purpose and objective of this section are to contextualise the central argument and contribution of this study to the broader literature. Hence, it reviews the state of the COVID-19 pandemic in South Africa and its impact on people's lives and livelihoods, including those of researchers and smallholder farmers. Later, the section unpacks the R&D investment and expenditure on agriculture in South Africa. These two subjects are important in understanding the impact of the COVID-19 pandemic on acquiring primary data for smallholder research because investment in research sought to improve the participants' quality of life, i.e., smallholder farmers in this case. At the same time, COVID-19 poses a threat to research contributions.

2.1. The COVID-19 Pandemic and its General Effect

South Africa recorded its first case of COVID-19 on 5 March 2020 from a couple on holiday in Italy. The virus then spread, making the country the pandemic's epicentre in Africa and the Southern African Development Community region. A national state of disaster was declared on 16 March 2020, with partial travel bans, closing of schools, and prohibiting gatherings of m ore than 100 people, among other measures (Republic of South Africa, 2020). In Africa, South Africa leads not only in the number of confirmed infections but also in the number of recorded deaths, possibly due to more advanced technology and better regional record-keeping. Various analyses suggested that COVID-19 mostly affected the more vulnerable population groups, the elderly and people with comorbidities (Figure 1).

Gauteng, KwaZulu Natal, Western Cape, and Eastern Cape in March 2021 were the hardest hit provinces (Table 1). On the economic impact, it is said that the COVID-19 pandemic affected the most vulnerable population groups, blacks, low-income earners, and people living in rural and informal settlements, among others (Bassier et al., 2021; Turok & Visagie, 2020). Such characteristics are similar to those defining smallholder farmers in South Africa, implying that smallholders were likely to be more affected by the pandemic. To address the impact of COVID-19 on smallholder agriculture, the Department of Agriculture, Rural Development, and Land Reform issued support totalling 1.2 billion rands to qualifying smallholders (Department of Agriculture, Rural Development and Land Reform, 2020).

 

 

2.2. R&D Agricultural Investment

The government is by far the most important funder of agricultural research in South Africa. According to Liebenberg et al. (2011), agricultural investment analysis from 1910-2007 showed that the government has been responsible for much of the investment. Recently, the report on agricultural R&D expenditure in the 2010/11 financial year from the Human Sciences Research Council shows that 98% of the expenditure came from the government and the remainder from the private sector (Table 2). More than three-quarters of the expenditure on agricultural R&D was spent in four provinces. KwaZulu Natal had the highest expenditure share (28%), followed by the Western Cape (17.8%), Gauteng (15.2%), and the Eastern Cape (15.1%). Limpopo had the least expenditure (2.5%). The government spent more than 79 million rands on basic higher education research - a category in which agricultural economics and extension research fall (Table 2).

 

 

Those who benefit from the research funds are postgraduate students directly or through their supervisors' block grants from funding bodies such as the National Research Foundation. More Masters' students enrol and graduate with agricultural-related degrees than doctoral studies (Table 3). While all farmers benefit from agricultural research, smallholders benefit more by far from agricultural research. Three-quarters of farmers who benefit from agricultural research are smallholders (HSRC, 2020).

 

 

3. METHODOLOGY

3.1. Conceptualisation

Cousins and Chikazunga (2013) defined smallholder farmers as households that produce for home consumption and sell their surplus for cash income. Small-scale farmers rely primarily on family labour and differing levels of mechanisation, capital intensity, and credit (Hlatshwayo et al., 202; Zantsi et al., 2021). According to Leedy and Ormrod (2018), research is collecting, analysing, and interpreting data to understand a phenomenon. Masters and doctoral theses also follow the research process. Research is usually categorised by the approach taken to collect and interpret data. For example, inquiries that deal with qualitative data are referred to as qualitative research studies, while those that use quantitative data are referred to as quantitative research studies. However, because there are often limitations between these two approaches, some studies apply a mixture of the two (Queirós, Faria & Almeid, 2017). In our sample, we include all smallholder dissertations based on primary data analysis from field surveys.

3.2. Selection of Sample Size

This study collected data from four South African universities that offer agricultural economics and extension within their faculties. We selected universities based in rural parts of South Africa, where most smallholders live and farm (Pienaar & von Vintel, 2014; StatsSA, 2016). These universities included the University of Fort Hare (Eastern Cape), the University of Limpopo (Limpopo), and the University of KwaZulu Natal (KwaZulu Natal). The exception to this rule was the University of the Western Cape (UWC). While UWC is not located within the three provinces that house a majority of smallholders, it has largely focused on smallholder farming research within the Eastern Cape, Limpopo, and KwaZulu Natal.

3.3. Collection and Analysis of Data

From this sample of universities, we collected master's and doctoral dissertations completed in the last six years (2014 - 2019). The reason for going a year back in our range is that some of the selected universities have not yet updated their repositories to include studies completed in 2020. In the first step, all dissertations completed in a given year were collected per university, focusing on agricultural economics dissertations. However, because agricultural economics is mixed with other disciplines in some universities, it is not always named "Department of Agricultural Economics" (Vink, 2012). Nonetheless, in the results, we provide the name of each university's department/college/institute. In the second step, from the list in step one, we differentiate dissertations that have used primary data from the list of all dissertations found in the research repository. The selected dissertations were retrieved from each university's repository of dissertations and the national ETD portal of South African theses and dissertations, where they appear under the heading "recent submissions". The initial abstract appraisal was done, and then, if the dissertation was found to meet the inclusion criteria, the data was recorded. An index was developed from the total of studies collected to quantify the outputs of the period under review. The smallholder dissertation index (SDI) was calculated as follows:

 

4. RESULTS

This section presents the repository search results for PhD theses and Master's dissertations in the four universities considered in this study. The section starts with doctoral theses in all four universities and later looks at master's dissertations.

4.1. Doctoral Dissertation

The results of the number of completed PhD theses are presented in Table 4. Detailed information about the selected theses in each institution is presented in the Appendix. The University of KwaZulu Natal (UKZN) has 12 theses, the highest number of completed theses in the period under review, followed by the University of the Western Cape with half the number (6) of theses produced at UKZN. At the University of Limpopo, no doctoral theses were identified for the period under review. Whereas at the University of Fort Hare (UFH), only one PhD thesis was found. Regarding the SDI index, the UFH and UKZN had the highest, 0.96 and 0.92, respectively, implying that these two universities heavily depend on primary data (Table 4). The UWC PLAAS had half of their completed theses using primary smallholder data (SDI=0.50) (Table 5).

 

 

4.2. Masters Dissertations

The results of completed masters' dissertations from the institutions under study are presented in Table 4. While the UFH and UL had only one and no PhD theses, UL led the way both in the number of completed masters dissertations (30), and UFH had the highest SDI (0.94) followed by UL. These institutions are followed by UKZN (0.58) and UWC (0.44), universities in provinces that have the highest expenditure on R&D (HSRC, 2020). The issue of closeness to smallholder farmers being mostly situated in former homelands (Pienaar & von Vintel, 2014) and proximity to rural areas is visible in this case because UKZN is close to the KwaZulu former homeland and the UL is close to the former homeland of Lebowa and UFH closer to former Ciskei and Transkei; while UWC is far from any former homeland.

 

5. DISCUSSION AND CONCLUDING REMARKS

The COVID-19 pandemic has caused numerous disruptions in many spheres of life, including the area and research procedures. This study attempted to understand the effect of the pandemic on doctoral theses and masters' dissertations conducted by students. Four South African universities offering agricultural economics degrees were used as a reference point to understand this effect.

The results indicate that, generally, PhD and Masters' research in the selected universities mostly focuses on smallholder farming in South Africa. This is due to the developmental gap between smallholder farming and commercial farming or dualism in South African agriculture caused by historical structural imbalances. Furthermore, we found that PhD and master dissertations conducted on smallholders in the selected universities rely heavily on primary data, as shown by a high SDI.

When zooming in on each university, the results indicate that not all universities have the same reliance and dependence on smallholder primary data. This means that, although there is a general focus on smallholder research, some of this research is not necessarily dependent on primary data. Hence, the index differs - apart from the number of dissertations recorded.

According to the SDI, the UFH relies more heavily on smallholder primary data than the other universities. The SDI of 1 and 0,94 for PhD theses and Masters' dissertations, respectively. In terms of Masters, the UL is ranked second (SDI = 0,83), followed by the UKZN (SDI = 0,58) and the UWC (SDI = 0,44). This implies that 94% of the Masters' dissertations completed in the UFH between 2014 and 2019 relied on smallholder primary data, compared to 83%, 58%, and 44% of the Masters' dissertations completed in the UL, UKZN, and UWC respectively. In terms of the PhD theses, the UFH (SDI =1) again relies on smallholder primary data compared to the UKZN (SDI = 0,92) and the UWC (SDI = 0,50). This implies that 100% of the PhD theses completed at the UFH between 2014 and 2019 relied on smallholder primary data, compared to 92% and 50% of the PhD theses completed in the UKZN and UWC, respectively. No PhD theses were found in the UL during the period under review.

Furthermore, the dissertations completed using the smallholder primary data were found (through abstract appraisal) to have used the traditional method of face-to-face interviews, and none indicated using online interviews. This implies that intense lockdown regulations and other COVID-19 restrictions on travelling and gatherings could have seriously affected the completion of theses and dissertations. However, we acknowledge that other factors contribute to the completion of the theses and dissertation other than access to data. For example, student determination, good health, and a healthy relationship between students and supervisors (Hofstee, 2006).

Therefore, it is recommended that new methods of gathering smallholder data should be found soon to reduce the potential disruptions and delays caused by the COVID-19 pandemic. The options include:

Adding variables in the few national data sets such as the StatsSA's Agricultural Household Surveys. This will reduce the requirements of collecting smallholder data through face-to-face field interviews. However, this requires strong collaboration between the universities and StatSA in consultation with the community of agricultural economists to determine the inclusion of certain variables and which variables are necessary.

Considering various online data collection methods such as Google Docs, SurveyMonkey, and others. However, there are several limitations in this regard, which include the literacy level of smallholder farmers (which may affect the understanding of questions and formulation of answers) and access to means such as smartphones, good signals, and data. In this case, the study recommends a strong collaboration between the universities and extension officers who have access to farmers on a day-to-day basis. The feasibility of this recommendation could be studied in future research.

The long-term impact of COVID-19 will still be felt in the coming years. It is only then that the true impact could be assessed and quantified. Perhaps this study could be used as a benchmark study as it only assessed the short-term impact of this pandemic.

 

REFERENCES

ALSTON, J.M., BEDDOW, J.M. & PARDEY, P.G., 2009. Agricultural research, productivity, and food prices in the long run. Science., 325(5945): 1209-1210.         [ Links ]

BASSIER, I., BUDLENDER, J., ZIZZAMIA, R., LEIBBRANDT, M., & RANCHHOD, V., 2021. Locked down and locked out: Repurposing social assistance as emergency relief to informal workers. World Devel., 139: 105271.         [ Links ]

BONTSA, NV., MUSHUNJE, A., NGARAVA, S. & ZHOU, L., 2023. Utilisation of Digital Technologies by Smallholder Farmers in South Africa. S. Afr. J. Agric. Ext., 51(4): 104-146.         [ Links ]

COUSINS, B. & CHIKAZUNGA, D., 2013. Defining smallholder farmers in South Africa. Handout for SSCA project, Innovation Lab.         [ Links ]

CHAMINUKA, P., BEINTEMA, N., FLAHERTY, K. & LIEBENBERG, F., 2019. Public agricultural research and development spending in South Africa - update. Agrekon., 58(1): 7-20.         [ Links ]

DEPARTMENT OF AGRICULTURE, RURAL DEVELOPMENT AND LAND REFORM., 2020. Minister Didiza announces the outcome of the COVID-19 agricultural disaster fund application process. Media statement, 17 May.         [ Links ]

EASTWOOD, C., RUE, B.D. & KERSLAKE, J., 2020. Developing an approach to assess farmer perceptions of the value of pasture assessment technologies. Grassl. Forage. Sci., 75: 474-48        [ Links ]

HUMAN SCIENCES RESEARCH COUNCIL [HSRC]., 2020. National survey on R&D and other S&T-related activities in agriculture in South Africa, 2010/11. Pretoria: Department of Agriculture, Forestry and Fisheries. Available from http://www.hsrc.ac.za/uploads/pageContent/9523/NATIONAL%20SURVEY%20AGRICULTURAL%20R&D%202010112.pdf        [ Links ]

HLATSHWAYO, S.I., NGIDI, M., OJO, T., MODI, A.T., MABHAUDHI, T. & SLOTOW, R.A., 2021. Typology of the Level of Market Participation among Smallholder Farmers in South Africa: Limpopo and Mpumalanga Provinces. Sustainability., 13: 7699. https://doi.org/10.3390/su13147699        [ Links ]

HOFSTEE, E., 2006. Constructing a good dissertation: a practical guide to finishing a masters, MBA or PhD on schedule. Sandton, South Africa: Exactica.         [ Links ]

KARAAN, M. & VINK, N., 2014. Agriculture and rural development policies in the post-apartheid era. In H. Bhorat, A. Hirsch, R. Kanbur & M. Mncube (eds.), The oxford companion to the economics of South Africa, Oxford University Press, Cape Town, 400-410.         [ Links ]

LEEDY, P.D. & ORMROD, J.E., 2018. Practical research planning and design. 12th ed. New York: Pearson.         [ Links ]

LIEBENBERG, L., PARDEY, P.G. & KAHN, M., 2011. South African agricultural R&D investments: Sources, structure, and trends, 1910-2007. Agrekon., 50(2): 1-26.         [ Links ]

LIEBENBERG, F., 2013. South African agricultural production, productivity and research performance in the 20th century. PhD Thesis. University of Pretoria.         [ Links ]

LIPTON, M., 1977. South Africa: Two agricultures? In Farm labour in South Africa, 72-85 Cape Town. David Philip.         [ Links ]

PARDEY, P.G., ANDRADE, R.S., HURLEY, T.M., RAO, X. & LIEBENBERG, F.G., 2016. Returns to food and agricultural R&D investments in Sub-Saharan Africa, 1975-2014. Food Policy., 65: 1-8.         [ Links ]

PIENAAR, L. & VON FINTEL, D., 2014. Hunger in the former apartheid homelands: Determinants of convergence one century after the 1913 Land Act. Agrekon., 53(4): 38-67.         [ Links ]

QUEIRÓS, A., FARIA, D. & ALMEID, F., 2017. Strengths and limitations of qualitative and quantitative research methods. Eur. J. Educ. Studies., 3(9): 369-387.         [ Links ]

REPUBLIC OF SOUTH AFRICA., 2020. Regulations and Guidelines - Coronavirus COVID-19.[Viewed January 2021]. Available from https://www.gov.za/coronavirus/guidelines        [ Links ]

REY-MORENO, C., BLIGNAUT, R., TUCKER, W.D. & MAY, J., 2016. An in-depth study of the ICT ecosystem in a South African rural community: unveiling expenditure and communication patterns. Inf. Technol. Dev., 22(sup1): 101-120.         [ Links ]

SIHLOBO, W., 2023. A country of two agricultures: the disparities, the challenges, the solutions. Bryanston: Tracey McDonald Publishers.         [ Links ]

STATISTICS SOUTH AFRICA [StatsSA]., 2016. Community Survey 2016: Agricultural households. Report 03-01-05. Pretoria.         [ Links ]

STATISTICS SOUTH AFRICA [StatsSA]., 2019. General Household Survey. Statistical release P0318. Pretoria.         [ Links ]

STATISTICS SOUTH AFRICA [StatsSA]., 2020. COVID-19 Pandemic in South Africa - Demography Volume, Report 00-80-05. Pretoria.         [ Links ]

STEPHENS, E.C., MARTIN, G., VAN WIJK, M., TIMSINA, J. & SNOW, V., 2020. Editorial: Impacts of COVID-19 on agricultural and food systems worldwide and on progress to the sustainable development goals. Agric. Syst., 183: 102873.         [ Links ]

SOUTH AFRICAN CORONAVIRUS., 2021. Update on Covid-19 (24th March 2021).         [ Links ]

TUROK, I. & VISAGIE, J., 2020. The Covid-19 crisis has amplified spatial inequalities. Econ3x3 paper. Available from https://www.econ3x3.org/article/covid-19-crisis-has-amplified-spatial-inequalities        [ Links ]

VINK, N., 2001. Small farmer research in South Africa: A survey. The 2001 F.R. Tomlinson Memorial Lecture. Agrekon., 40(2): 130-186.         [ Links ]

VINK, N., 2012. Agricultural economics: an exoteric or esoteric science?. Agrekon., 51(2): 1-21.         [ Links ]

ZANTSI, S., PIENAAR, L.P. & GREYLING, J.C., 2021. A typology of emerging farmers in three rural provinces of South Africa: what are the implications for the land redistribution policy? Int. J. Soc. Econ., 48(5): 724-747.         [ Links ]

 

 

Correspondence:
S. Zantsi
Email: siphezantsi@yahoo.com

 

 

APPENDIX

 


Table 5 - Click to enlarge

 

 


Table 6 - Click to enlarge

 

 


Table 7 - Click to enlarge

 

 


Table 8 - Click to enlarge

 

 


Table 9 - Click to enlarge

 

 


Table 10 - Click to enlarge

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License