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Scientific parameters

A scientific parameter is a definable or measurable characteristic or a value, selected from a set of data. A variable is any factor, trait, or condition that can exist in differing amounts or types. In experimental science, there are usually three types of variables: 1) independent, 2) dependent, and 3) controlled. The independent variable is the one that the experimenter changes in order to measure or observe a response or an effect. The dependent variable is the measured response to the changes made to the independent variable. The controlled variables are the variables which are kept constant in an experiment.

Let us illustrate these variables with an imaginary experiment using an aquaponic system. We are interested in how the total mass of fish affects ammonia production in the fish tank connected to the hydroponic unit. The ammonia concentration will be measured in g/L in the fish tank as well as in the hydroponic unit. The feed amount and rate will remain constant, whereas the total mass of fish will vary with the addition of fish into the fish tank. In this imaginary experiment, the total mass of fish is the independent variable (this is what we are changing), and the ammonia concentration is the dependent variable (this is what we are interested in – it is what we are measuring as a response to varying the mass of fish). Variables, such as the amount of feed, feeding rate, the time intervals between feeding and varying the total mass of fish, water temperature in the fish tank and in the hydroponic unit, surface area of the biofilter, the number of plants in the hydroponic unit, etc., all have to be kept constant in order to measure just the effect of varying the total mass of fish on ammonia production, and they are therefore the controlled variables.

It is important to note that scientific experiments (or measurements of the same parameter in monitoring) are done in multiples, usually triplicates, in order to validate empirical data or the observed results. Three replications are usually enough to rule out any potential outliers (if the other two measurements agree). An average (in statistics called the arithmetic mean) of such measurements is then taken in order to improve the precision of the result. The standard deviation (SD) of the three replicates should also be calculated in order to report on variability among the data. A low standard deviation is preferable. Do not forget to include units in your measurements. The equations for calculating the arithmetic mean and the standard deviation are shown below:

image-20210212143736065

Where: $\bar{x}$ = arithmetic mean

$𝑥1, 𝑥2, 𝑥3, 𝑥n$ = individual values in the data set 𝑛 = the number of data points in the set (the number of ‘x’ values)

image-20210212143704949

Where:

𝑆𝐷 = standard deviation

Σ = summation symbol

𝑥 = each individual value in the data set

𝑥 = the arithmetic mean

𝑛 = the number of data points in the set (the number of ‘x’ values)

Why monitor?

The need for monitoring in aquaponics arises from two points of view: legislation and management. The holistic nature of aquaponics means that it falls into several different legislative categories with regards to policy at the EU level. The Common Fisheries Policy (CFP) and the Common Agricultural Policy (CAP), as well as policies on food safety, animal health and welfare, plant health, and environmental legislation, among others, may all apply, depending on the operational characteristics of the system. The legislation and regulations which need to be observed during aquaponic production include, but are not limited to:

  • Water Framework Directive (2000/60/EC) (WFD) – Among other things, the WFD lays down the rules for monitoring, sampling, and analysing effluent discharge into watercourses. It also requires member states to set up monitoring regimes within their country, which often includes inspections at discharge sites to analyse effluent

  • Nitrates Directive (91/676/EEC) specifies the parameter limits of effluents that can be discharged

  • Food safety regulations, which will be covered in greater detail in Chapter 10 of this textbook

  • Animal Welfare and Fish Health regulations, such as Directive 91/496/EEC, which lays down the principles governing the organisation of veterinary checks on animals entering the EU from third countries

In most countries help will be available from government agencies to keep aquaponic farmers in line with the law, and they should therefore seek comprehensive information from the competent authorities in regards to their particular situation (Joly 2018).

Regular monitoring of parameters is an indispensable part of the management, operation, and maintenance of the aquaponic system. Monitoring the water quality, and the health of the fish and the plants, will indicate how well the system is performing and has significant cost benefits. Keeping good records of your measurements can help greatly in observing trends and diagnosing future problems. It is important to record all of your readings. Parameters such as ammonia, nitrite, dissolved oxygen, and pH can give an indication of whether the system is underperforming.

Identifying the parameter that is problematic (i.e. outside of the desired range) helps the operator to fix the problem quickly and restore the functioning of the aquaponic system back to optimum levels, which will result in the highest yield of fish and plants.

Different monitoring approaches

The monitoring approaches for testing the quality of aquaponic water range from very simple and cheap to complex and involving expensive analytical equipment. The simplest and cheapest approach is to use test strips, which you submerge in the water. These contain a reagent which changes colour when it comes into contact with the water. The intensity of this reaction can be compared to the colour chart provided with the kit, which will then give a relatively accurate measure of what is being tested for. These kits are often cheap and simple to use, although as they are a consumable material, stocks will need to be constantly replenished. These, however, can usually only be used for a limited range. For example, some test strips for pH only work within a pH range from 5 to 8. If the pH in the aquaponic system falls outside of this range (below 5 or above 8), then the test strips may give false results.

The next level in terms of complexity and cost are tests using chemical reagents and a colour chart. Here the sample is put into a small test tube and drops of reagents are added according to the instructions. A reaction occurs and the colour of the solution in the test tube is compared to the colour chart that comes with the kit. The price of these tests varies. A more precise and advanced version of these tests measures the colour with spectrophotometers.

Spectrometry is a method of quantitative analysis that utilises the absorbance of light. Usually a water sample is centrifuged to remove suspended solids and a reagent specific to the desired test is added. This is then placed inside a spectrophotometer for analysis. The reading given by the spectrophotometer can then be related to known standard curves for that particular chemical parameter to give a concentration. Some manufacturers also provide test kits for a quicker analysis, without the need to use calibration curves, and these are available for a wide range of water quality parameters.

The most advanced and expensive approach to monitoring involves using probes and electronic meters. These exist in single parameter configurations, or in multiprobe single meter configurations. The probes are connected to a digital electronic meter and submerged in the water. Continuous online monitors can also be installed inside the fish tank, with a probe constantly in contact with the water. They cost more in comparison with tests described previously, however, they are the most accurate instruments for monitoring, and have the largest measuring range (Klinger-Bowen et al. 2011).

The chosen monitoring approach is usually associated with the size of the aquaponic system and the level of productivity. Professional commercial systems usually employ continuous online monitors for dissolved oxygen (DO), water level and electric supply. On the other hand, hobby backyard systems often rely on the simplest and cheapest approaches, such as test strips, or even just visual inspections of water turbidity, oxygenation in biofilter, plant and fish health.

Classification of monitoring parameters

The parameters that need to be monitored in an aquaponic system are the water quality, the health of the fish, and the health of the plants, and can be classified into the following types: 1) chemical, 2) physical, and 3) biological. Chemical parameters have to do with the quality of the water and include pH, DO, ammonia, nitrite, nitrate, phosphorus content, and water hardness. Physical parameters include water and air temperature, relative humidity, and UV light intensity. Biological parameters provide direct insight to system performance, and include everything from the mass and health of the fish and the plants, nutrient deficiencies in the plants, algae contamination, and other microbiological parameters. Each organism in an aquaponics unit – the fish, the plants, and the bacteria in the biofilter – has a specific tolerance range for each physico-chemical parameter (Table 1). The tolerance ranges are relatively similar for all three organisms, but there is a need for compromise and therefore some organisms might not be functioning at their optimum level (Somerville et al. 2014a).

Table 1: Optimal ranges of physio-chemical parameters for fish (warm- and cold-water), plants and nitrifying bacteria

Organism typeTemperature (oC)pHAmmonia (mg/L)Nitrite (mg/L)Nitrate (mg/L)DO(mg/L)Warm water fish22-326-8.5<3<1<3004-6Cold water fish10-186-8.5<1<0.2<3006-8Plants16-305.5-6.5<30<1-> 3Bacteria14-346-8.5<3<1-4-8

The goal is to maintain a healthy ecosystem with physico-chemical as well as other parameters that satisfy the requirements for growing fish, vegetables, and bacteria simultaneously. There are occasions when the water quality will need to be actively manipulated in order to meet these criteria and keep the system functioning properly.

Frequency of monitoring

Frequency of monitoring varies depending on the parameter being monitored. As a general rule, start-up systems (at initial stocking of plants and animals) should be tested daily so that adjustments can be made quickly when needed. For example, feeding levels can be reduced, aeration can be increased, or water can be diluted in response to high ammonia levels. Once nutrient cycles are balanced (after a minimum of 4 weeks without significant fluctuations in parameters), weekly monitoring is usually sufficient to maintain good water quality. However, if a problem is suspected (change in the appearance or behaviour of the fish, deficiency indicators in plants), then more frequent monitoring of the water quality should be resumed. Therefore, daily monitoring of the health of the fish and plants is essential in order to discover potential problems early. It is also very important to keep a good record of monitoring parameters, e.g. appearance and behaviour of the fish (normal/out of the ordinary), appearance of the plants (normal/unhealthy look), and water chemistry parameters (pH, DO, ammonia, nitrites, nitrates). This way, the cause of a potential problem can be identified more easily and, in case the problem arises again, the amendment that previously worked well can be quickly implemented (Sallenave 2016; Somerville et al. 2014a). An example of a data log book is shown in Figure 1.

image-20210212144002731

Figure 1: An example of monitoring data log table. SS in the table stands for ‘sample site’

Copyright © Partners of the [email protected] Project. [email protected] 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).

Please see the table of contents for more topics.


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