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Scientific research methodology applied to aquaponics

· Aqu@teach

The following case studies illustrate some of the different kinds of methodologies that can be used for research relating to aquaponics. The first case study is an example of social science research conducted using a questionnaire. A questionnaire is a tool for collecting and recording information about a particular issue of interest in a standardized manner. The information from questionnaires tends to fall into two broad categories – facts and opinions; very often they include questions about both. The questions may be unstructured or structured or, as in the case study below, a combination of both. Unstructured questions ask respondents to provide a response in their own words, while structured questions ask respondents to select an answer from a given set of choices. Structured questionnaires are usually associated with quantitative research, i.e. research that is concerned with numbers (how many? how often? how satisfied?). The responses to individual questions in a structured questionnaire may be aggregated and used for statistical analysis (Nayak & Singh 2015).

Case Study 1
Love, D.C. et al. 2014. An international survey of aquaponics practitioners. PLoS ONE 9(7), e102662.
AimTo track aquaponics in the United States and provide information that can better inform policy, research, and education efforts regarding aquaponics as it matures and possibly evolves into a mainstream form of agriculture
ObjectiveTo document and analyse the production methods, experiences, motivations, and demographics of aquaponics practitioners, both in the United States and internationally
Methodology
  1. Literature review to determine whether suitable survey tools exist to collect information on production practices and attitudes of individuals engaged in aquaponics
  2. Development of a questionnaire informed by previously described methods for internet surveys and surveys about agricultural practice
  3. Pre-test of the draft questionnaire for comprehension of contents with 10 people who were either experts in or practitioners of aquaponics, and were representative of the groups targeted in the survey (i.e. commercial farmers, educators, hobbyists, and non-profit organizations)
  4. Online survey using the snowball sampling method in order to reach as many people as possible. Eighteen organizations distributed the questionnaire to their members or subscribers using their own preferred means of communication (e-mail, listservs, online newsletters, direct email, and social media). The incentive offered for participation in the survey was the chance to win one of four $75 gift cards
  5. Of the 1084 respondents, 809 met the inclusion criteria (18 years of age or over, able to read English, and had operated and maintained an aquaponic system in the previous 12 months), and their responses constitute the sample
  6. Data from the survey software (Qualtrics) were exported and analysed in Excel or SPSS, and figures were produced using Prism. T-tests were conducted to compare respondent demographics by sex, with significance set at an alpha of 0.05. Error was reported as standard deviation
Limitations of theThe use of the snowball sampling approach and social media to identify potential
researchparticipants means that it is not possible to calculate the survey response rate, andthere is limited generalisability to aquaponics practitioners beyond those who responded to the study. The fact that the majority of respondents were from the US (80%) suggests that the results may be skewed because the survey originated in the US and was not offered in languages other than English

Questionnaires are one of the most affordable ways of gathering quantitative data. Online surveys in particular can have a very low cost and a generous reach, and the results can be analysed quickly and easily to highlight trends in the data. However, there are a number of drawbacks to using questionnaires. While every researcher hopes for conscientious responses, there is no way of knowing whether the respondent has really thought the question through before answering. At times, answers will be chosen before fully reading the question or the potential answers, and sometimes respondents will skip through questions, or split-second choices may be made. All of these will affect the validity of the data collected. While questionnaires may reveal patterns and trends in the data, they do not permit an understanding of their causes.

The second case study is an example of social science research using a comparative case study approach and semi-structured interviews to generate qualitative data.

Case study 2
Laidlaw, J. & McGee, L. 2016. Towards urban food sovereignty: the trials and tribulations of community- based aquaponics enterprises in Milwaukee and Melbourne. Local Environment 21 (5), 573–590.
AimTo understand the socio-economic and cultural context that is essential for building food sovereign communities and cities, in particular the potentially catalytic role of urban aquaponics social enterprises in fostering a broader civic disposition and receptiveness towards food sovereignty
ObjectiveTo explore stakeholder experiences of building community-based urban aquaponics enterprises in order to understand the internal and external factors that impact on their success or failure
MethodologyComparative case study approach involving:
  1. Unstructured qualitative interviews with key project stakeholders at two community-based urban aquaponics enterprises and an online survey of a broader cohort of stakeholders. The sample size is 23 (7 key project stakeholders and 15 other stakeholders)
  2. Analysis of project documentation and observations compiled through a series of site visits
  3. Discourse analysis of the interview transcripts
Limitations of the researchThe small sample size (stakeholders associated with two aquaponics enterprises) means that there is limited generalisability of the findings. The methods used for the discourse analysis are not stated

Comparative case studies such as this involve the analysis and synthesis of the similarities, differences and patterns across two or more cases that share a common focus or goal. Given the focus on generating a good understanding of the cases and case context, methods such as fieldwork visits, observation, interviews and document analysis often dominate among the various data collection methods employed. Comparative case studies may incorporate both qualitative and quantitative data, and while they may be time consuming, they can generate rich detail about the context and features of two or more instances of specific phenomena.

The field of aquaponics is quite new, with the first scientific paper specifically using the term appearing in an impact journal in 20044. Many advancements had been made before that, namely by James Rakocy and his group (University of the Virgin Islands) but their publications are more demonstrative and less experimental. According to the Web of Science, more than 60 peer-reviewed papers have been published on aquaponics since 2004, but many articles concentrate more on promoting the potential of aquaponics than on completing scientific trials per se. Part of the problem stems from having enough replicates and establishing proper control groups. It is usually quite difficult and time consuming to set up an aquaponic system, with its filter, bacteria, fish, and plants, let alone setting up several units or replicas per treatment. In feed trials in aquaculture, for example, it is common to have at least 3 replicas per treatment, each experimental unit usually being one tank, not the individual fish. That would mean, for example, were we to compare the effects of adding garlic extract to feed, we would need three tanks of fish to which we add garlic feed and three more tanks to which we add control feed. To do something similar using aquaponics is more complex. For example, if we want to compare the effect of water pH on fish welfare and lettuce growth, we would need six separate aquaponic units, three of which were at a specific pH and another three at another pH level, and all six units would need to have fish and lettuce in the same stocking densities. Thus, the cost of each experiment is higher than for feed trials, and the list of things that could possibly go wrong is also much higher. For this reason, when looking at the literature, we normally see very few or no replicates, or two replicates per treatment at the most.

4 Tokuyama, T., Mine, A., Kamiyama, K., Yabe, R., Satoh, K., Matsumoto, H., Takahashi, R.& Itonaga, K. 2004. Nitrosomonas communis strain YNSRA, an ammonia-oxidizing bacterium, isolated from the reed rhizoplane in an aquaponics plant. Journal of Bioscience and Bioengineering 98 (4), 309-312.

The third case study is an example of an experimental research methodology. The purpose of experimental research design is to enable the researcher to credibly establish a cause-and-effect relationship. An experiment is a test under controlled conditions that is carried out in order to support, refute, or validate a hypothesis. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular variable is manipulated. Experiments vary greatly in goal and scale, but they always rely on a repeatable procedure and logical analysis of the results. The research methodology is therefore explained in great detail in order to enable other researchers to repeat the experiment and thereby validate, or falsify, its results.

Case study 3
Goddek, S. & Vermeulen, T. 2018. Comparison of Lactuca sativa growth performance in conventional and RAS-based hydroponic systems. Aquaculture International 2018, 1–10.
AimTo verify the findings of Delaide et al. (2016)5 – that lettuce growth performance in complemented aquaponics solution outperforms hydroponics
ObjectiveTo compare the growth performance of lettuce in a conventional hydroponic system with that in a RAS-based system
MethodologyTwo NFT systems, each one consisting of sixteen 7.7 metre long gullies and a recirculation container holding 250 litres, were planted with 38 lettuces per gully, resulting in a planting density of 12 lettuce heads per square metre. The hydroponic treatment tank was continuously filled with rain water and the RAS treatment tank with 30% RAS water and 70% rain water. Analysis of the micro and macronutrient concentrations in the water was carried out once every two weeks using HPLC equipment according to the ISO 17025 norm. 20 lettuce shoots were randomly selected, harvested and weighed individually seven weeks after planting. Prior to sending the milled lettuce shoots for lead analysis, the lettuce heads of each system were cut into small pieces and dried (for 24 h at 103 °C) in order to determine their dry weight. The leaf nutrient content analysis was performed with an ICP-OES by Groen Agro Control according to their certified analysis protocol. Analysis of statistical significance and ANOVA were conducted in R. A nonparametric two-sample Kolmogorov–Smirnov test was used to test whether Na concentration probability distributions differ between the hydroponic and RAS systems. Genstat software was used to conduct a principal component analysis with respect to the nutrient composition of the lettuces

Copyright © Partners of the Aqu@teach Project. Aqu@teach is an Erasmus+ Strategic Partnership in Higher Education (2017-2020) led by the University of Greenwich, in collaboration with the Zurich University of Applied Sciences (Switzerland), the Technical University of Madrid (Spain), the University of Ljubljana and the Biotechnical Centre Naklo (Slovenia).

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