The desirability of a shift towards an insect farming industry
in the Netherlands based on the environmental effects
An interdisciplinary project
University of Amsterdam Course: Interdisciplinair project
Tutor: Mw. dr. M.F. Hamers Expert Supervisor: Dhr. dr. K.F. Rijsdijk
date: 10-05-2015
Fieke Vlaar - 10467165 Jaleesa Schaap - 10474463 Tim de Kruiff - 10444009 Muriël Hol - 10161740
Table of contents
0.Abstract__________________________________________________________ p.2 1.Introduction_________________________________________________ p.2 2.Method ____________________________________________________ p.4 2.1 Finding common ground _____________________________________ p.4 2.2 Integrating techniques_______________________________________ p.5 3.Theoretical Framework______________________________________________ p.6 3.1 Ecology __________________________________________________ p.6 3.2 Earth sciences_____________________________________________ p.6 3.3 Economics________________________________________________ p.6
3.3.1. The prevention cost method __________________________ p.7 3.4 Artificial intelligence_________________________________________ p.7 4.Parameter analysis ________________________________________________ p.8 4.1.Feed and water ____________________________________________ p.8 4.1.1 Composition of the feed ______________________________ p.8 4.1.2 Feed conversion ratio ________________________________ p.8 4.1.3 Water consumption __________________________________ p.10 4.1.4 Costs of feed_______________________________________ p.10 4.2. Farm temperature__________________________________________ p.11 4.2.1 Optimal farm temperature for insect or pig production _______ p.11 4.2.2 Environmental effect of the temperature regulation __________p.12 4.3. Greenhouse gas production___________________________________p.13 4.3.1 Pig and insect CO2 and CH4 production___________________ p.13
4.3.2 Environmental effect of the greenhouse gas production ______ p.14 4.3.3 Costs of the greenhouse gas production__________________ p.15 4.4. Manure production __________________________________________p.16 4.4.1 Amount and composition of manure______________________p.16 4.4.2 Effects of this manure on the environment_________________ p.17
4.4.3 The monetary cost of manure pollution___________________ p.18 5.Large scale insect production _________________________________________ p.20 5.1 The simulation of insect production systems ______________________ p.20 5.1 Fuzzy Logic__________________________________________ p.21 5.2 Fuzzy logic for insect production systems ___________________p.23 5.2 Automation of insect productions_______________________________ p.24 6. Discussion _______________________________________________________ p.25 7. Conclusion_______________________________________________________ p.26 8. References________________________________________________________p.27
0.Abstract
The increasing demand for protein causes a higher rate of livestock production. The conventional livestock production system damages the environment and depletes natural resources. Insects are a potential alternative protein source and many studies conclude that insects have a significantly lower impact on the environment and natural resources. An interdisciplinary research is executed in order to see if the environment of the Netherlands would benefit from a shift towards an insect industry. Farm temperature, livestock feed, manure production, greenhouse gas production and water usage are compared between the insect industry and the national pig industry and their environmental impacts are valued by their external effects. Finally the automation and simulation of production is studied to see how a future of mass rearing can be approached.
1. Introduction
The world’s population has been growing exponentially over the last decades and global wealth has been increasing. This has caused a rapid increase in the demand for animal protein (Boland et al., 2013). With the current growth rate, livestock production will be twice as high in 2050 as it was in 1999 (Steinfield et al., 2006).
The livestock industry is responsible for 18 percent of all global greenhouse gas emissions. Furthermore, the livestock industry accounts for 8 percent of global freshwater usage and thereby contributes significantly to freshwater shortage. Moreover, livestock industry causes water pollution by leaking hormones, pesticides, fertilizers and antibiotics into freshwater
ecosystems (Steinfield et al., 2006). To produce the protein demanded by the market roughly 70 percent of all arable land is used for agriculture in order to feed livestock (FAO, 2006).
Boland et al. (2013) address the challenge of the high protein demand and discuss a wide variety of potential alternative protein sources, although they do not consider an important potential protein source: insects.
The eating of insects is called entomophagy and this could be an alternate protein source with a high potential. The potential of eating insects is illustrated in a study by Van Huis (2013) in which he compared the ratio of inputs and outputs of animal protein versus insect protein. In this interdisciplinary research report, the focus will be on a comparison between pigs and insects. Pigs are the most consumed animals in the Netherlands: 49% of the total meat consumption in 2012 consisted of pork (Productschap vee & vlees, 2013). Furthermore, the Dutch pig
production sector is strongly developed and studied by the University of Wageningen. This simplifies the data collection needed for this report.
Pork and insects contain a similar amount of protein, as is illustrated in figure 1.1. Therefore, this report assumes that is possible to substitute pork with insects as a protein source.
Figure 1.1 Visual display of energy, protein, fat and mineral content of meat pigs in comparison with Tenebriomolitor larvae (mealworms). Source: Boeckx, Peeters and Van Der Borght (2012).
Although social acceptance seems to be the biggest barrier for the shift towards insects protein consumption (FOA, 2013), we do not include this aspect in our research. According to a survey of Lensevelt and Steenbekkers (2014) to find the consumer acceptance of entomophagy in the Netherlands, the most important driver is the availability of the product. Once people have easy access and thus the ability to try the product, we assume that acceptance will be more than likely follow.
There are some important steps to take before entomophagy should be promoted in the Netherlands. The environmental desirability of a shift toward an insect protein based diet is a very complex problem and can not be assessed within a single discipline. This indicates that interdisciplinarity is needed (Repko, 2012). Expert knowledge from different disciplines needs to be integrated for we need knowledge about the inputs and the outputs of the production, the effects they have on the national environment and their external costs. In extension we will search for a possibility to simulate and automate this insect production to enable the insect production to be equal to the conventional pig industry and in order to simulate the production parameters.
Therefore our research question is: What are the environmental effects of a shift from the conventional pig industry towards an insect industry in the Netherlands when productions are equal?
2. Method
This interdisciplinary report will be based on literature. It was tried to receive information from insect and pig farms in the Netherlands. However, they were not willing to share critical information for this research, such as the input and output fluxes of the farm with regard to for example the feed, manure and energy.
It is considered an interdisciplinary project for the disciplines as ecology, earth science, economy and artificial intelligence are all contributing information from their research field on similar factors in order to answer the research question.
In order to answer our research question, this report is divided in several sections. Each section describes the environmental effects of a certain parameter needed for the rearing of insects and pigs. These parameters are as followed: feed and water, farm temperature, greenhouse gas production and finally manure production.
The choice for these parameters is arbitrary and is based on what we considered the most impactful elements of production after a screening of literature and the available data. 2.1 Finding common ground
Concerning (mini) livestock production, all four disciplines have one similarity: they all use the rearing parameters for the analysis of the production. The parameters feed, temperature, manure, water and greenhouse gas emissions are set by the ecology of the (mini) livestock, determine the earth scientific effects, have an economical value and are the components of the intelligent simulation of the system. The parameters of the farm form hereby our common ground. This is visualised in figure 2.1.
2.2 Integrating techniques
Prior to this interdisciplinary report, all involved disciplines have done research with regard to the theories and concepts used in this paper. This was executed in order to identify possible similarities and differences in the used theories and concepts between the disciplines. The overlapping technique of interdisciplinary integration, which is used by all the four disciplines, is the rearranging sub-systems to bring out interrelationships technique (Newell, 2000). This is because ecology sets the boundaries for the other disciplines to work with. Ecological and earth scientific knowledge are integrated by the joint dependent variables technique (Newell, 2000). Ecology and earth science have a causal relationship concerning the production parameters. The farming of (mini) livestock products in the Netherlands has an impact on the national environment which will be studied by the earth sciences. These environmental impacts depend on the ecology of the livestock.
To be able to compare the environmental impact of (mini) livestock production, based on ecology and earth sciences, we need a unifying value that we chosen to be monetary.
Therefore, we will integrate economical expertise with the joint dependent variables technique as well (Nowell, 2000). When all values of the current national insect and pig industry are found we will extend these values to a comparable scale in order to judge whether a shift is desirable or not. To support this we need to evaluate the possibility of a large scale insect production. Artificial intelligence is integrated with the other disciplines by redefining terms, a technique that is used when disciplines focus on two different subjects (Newell, 2000). We extended the research subject, insect production, to the simulation and automation of the mass rearing production systems that will be needed to enable a shift toward a national insect production. Artificial intelligence will search a model for simulating and automating insect farms. This enables the integration of artificial intelligence and builds an arching bridge between the disciplines.
The method and disciplines are shown in the concept map in figure 2.2.
3.Theoretical framework
3.1 Ecology
A theory that is commonly used in the ecology as well as in earth sciences is the resilience theory. Holling introduced the ecological resilience to understand the nonlinear dynamics observed in ecosystems (Gunderson, 2000). Walker et al. (2004) defined this resilience theory as the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same structure, function, identity and feedbacks.
Looking at resilience in ecosystems, resilience is an important aspect of ecosystems and is related to the self-organizing behaviour of ecosystems over time. In this case, self-organizing refers to the interaction between structure and processes that lead to system development, not taking into account the initial conditions (Gunderson, 2000).
All use of resources as well as the contamination due to pig and insect farms can have an impact on the resilience of systems.
Pig and insect farms both need different environmental conditions, both due to the difference in resistance of both type of animals as well as due to the different conditions both type of animals prefer. If the conditions do not fall between the thresholds, the tipping point will be passed and as described by Holling in Gunderson (2000), a regime shift will take place to a new (less preferable) state.
3.2 Earth sciences
The earth science discipline will use the theory of global warming and the in chapter 3.1 described resilience to investigate the impacts of multiple factors, such as stable temperature and content of manure of the pigs and insects, on the environment. In earth science, the
resilience theory is used to describe the earth scientific variables that control the disturbances of an ecosystem. The earth scientific variables are for example excessive addition of nitrogen (N) and phosphorus (P) to land and water bodies. One of the assumptions that is used with this theory is that more than one stable state exists in nature (Gunderson, 2000).
The anthropogenic global warming theory indicates that the increasing amount of greenhouse gases, influences the temperature on earth (IPCCa, 2013). One of the assumptions with this theory is that the variation in solar activity does not have more influence on the global warming than the increasing amount of greenhouse gases (Van Geel et al., 1999; Benestad & Schmidt, 2009).
3.3 Economics
Quantifying environmental effects in monetary value is a difficult task. In order to do so, an understanding of the theory of externalities is needed. Externalities is a central concept when expressing environmental damages in monetary terms and are changes in the welfare of people or the society as a consequence of the actions of others without there being a transaction to compensate either party for change (Davidson,1996). These effects therefore always fall outside of the market, as no transaction takes place. This has as a result that there is no price known and the value of these effects has to be determined with another method. Several methods are available to quantify external effects but this study will use the prevention cost method. This method will be explained later. There are several reasons for this choice. First of
all, due to the complex nature of the externalities involved in our subject, some others methods are very hard to apply. For instance, a lack of data hinders the implementation of the market price method (Davidson,1996). Second, earlier studies, such as Davidson (1996), conducted on the externalities of Dutch agriculture have mostly been using the prevention cost method. The methods of these studies have served as an example for us on how to do the evaluation of external effects and therefore using the same methodology seemed a logical step.
3.3.1 The prevention cost method
The prevention cost method is based on the assumption that the societal environmental preferences are given by the environmental policy goals set by the government. Society determines how much environmental damage they deem acceptable and then sets goals accordingly. It is therefore assumed that reaching these goals results in the optimal situation, where the external costs or benefits can still exist but are very small in comparison to the total (Davidson,1996). In order to reach these policy goals companies have to make costs, named prevention costs. The minimum value of costs needed to reach the policy goals is then named the price of the external effects (Blom & Schroten, 2009).
3.4 Artificial Intelligence
Leon-Velarde and Quiroz (2001) made a framework for modelling cattle production systems. Their focus is on the most important cause-effects within the system by making schematic representations. The relationships between the different components or parameters are mathematically defined. Although for insect rearing systems this is not the case, these production systems are mainly based on trial and error (Erens et al., 2012), the schematic representation of the parameters and components could still be useful for the production simulation.
One of the conclusions of the study from FAO by van Huis et al. (2013) is that the price of insect products need to be lowered by reducing production cost by increasing innovation and
automation. Moreover Cohen (2001) argues that publications about insect rearing lack
references to the rearing conditions and technologies. Therefore we searched for studies similar to Leon-Velarde and Quiroz (2001) that apply to insect productions.
The only study we could find about the modelling of insect production systems is from the FOA and IAEA by Caceres, Rendon and Jessup (2012). They made a generic Excel spreadsheet that describes which parameters are most important for the design and operation of insect mass-rearing facilities. This paper is made for the provision of information about this model, including in great detail the production parameters, physical and biological factors, how to select the optimal location and political factors that need to be considered.
Thus we can infer from Leon-Velarde and Quiroz (2001) how to represent the production parameters and we can infer from Caceres, Rendon and Jessup (2012) which parameters to include. There is still no information available about the mathematical relations between these parameters, thus we do need to search for a theoretical framework about how this could be provided.
Passino (2015) did a study on intelligent control. He studies control frameworks that control a system with human heuristic knowledge rather than mathematical models. One of these control methods is Fuzzy Logic. Fuzzy logic is a method for controlling and simulating systems that can
cope with uncertainties and rules based on vague expert knowledge. In this paper we will study if this control method can be applied for the automation and simulation of insect farms.
4. Parameter analysis
4.1 Feed and water
4.1.1 Composition of the feed
Pig feed contains a combination of wheat, barley, corn and soya. Of these, corn has the highest energy value and contains 630 grams (g) per kilograms (kg) starch. Wheat and barley fill up the largest part of the portion. Barley is an important component for young pigs and wheat
especially for older pigs. Every pig farm determines its own compilation, depending on the age of the pigs and the type of farm (Havens Diervoerders, 2015). Table 4.1 contains the mineral content of pig feed for meat pigs.
Table 4.1 Mineral content pig feed. Data for 2012 and 2013. Source: van Bruggen and Faqiri (2014).
For insects, the type of feed and so their diet, has an influence on the growth rate and body composition. Even the nutritional quality of the insects is influenced by this diet.
One sustainable type of diet is a diet based on composted organic by-products (Broekhoven et al., 2015). However, it depends on the type of species whether insects can use waste as feed. As an example, the edible larvae of black soldier flies can even use manure as feed. Although this has as a result that the growth is not optimal, as the development time is prolonged.
According to Oonincx (2015) the larvae developed on all of the manures tested. The magnotory locus, the grasshopper, requires fresh grass as part of their diet, and thus waste is not suitable as feed. The house cricket can develop on a variety of substrates, but cannot live on only waste products such as manure. They can however live on industrial byproducts, such as cooking remains. These byproducts can be considered as waste (Oonincx, 2015). It is thus very hard to conclude what the contents are of the insect feed as they vary extremely.
4.1.2 Feed Conversion Ratio
To compare the ratio of inputs and outputs of pigs protein versus insect protein, the Feed Conversion Ratio (FCR) is used: how many kilograms of feed is converted in how many kilograms of edible food for human consumption. Table 4.2 shows the values of his Feed Conversion Ratio for conventional meat and crickets. The values clearly show the potential of insects as a protein source, as stated before in the introduction.
FCR’s vary widely because they depend on the class of animal and the production practices used. Van Huis (2013) made a very rough calculation from average figures using long term
statistics for the United States. This calculation indicated that the FCR for pork is 5 (Smil, 2002 as cited in Broekhoeven et al., 2015). His estimates are given in the table 4.2.
Table 4.2 Efficiencies of production of conventional meat and crickets. Source: van Huis (2013).
Cricket Poultry Pork Beef
Feed conversion ratio(Kg feed : Kg liveweight)
1.7 2.5 5 10
Edible portion % 80 55 55 40
Feed ratio (Kg feed: Kg edible weight)
2.1 4.5 9.1 25
However, according to Agrovision (2003), cited in Jongbloed and Kemme (2005), the FCR of pigs in the Netherlands is 2.67. The same FCR is also given in Hoste (2011). This report will therefore use this value for our calculations. Pigs are mostly bought at an age of 10 weeks with a weight of 25 kg and are being grown till 114 kg. This means that the mean growth is 762 gram per day (Agrovision, 2003 as cited in Jongbloed & Kemme, 2005) with a growth period of 115 days. The total amount of feed needed to grow a pig, calculated as growth times the feed conversion ratio is 235 kg for 2002, which gives the FCR value of 2.67 (van Huis, 2012). The growth period depends on the type of feed and can vary a few days, as can the exact amount of feed. Based on these numbers, an amount of P and N excretion can be calculated. There are multiple types of pig feed. The age of the pig is the leading factor of which type of feed is used. Pig feed contains heavy metals, among which copper. Starting feed contains the highest amount of copper, but this type of feed has only been fed for a short time to not exceed the European directive for the maximum copper emission (Jongbloed & Kemme, 2005). It is not clear when farmers change from starting feed to growing feed, which makes it difficult to
estimate the amount of emission of meat pigs. The most important factors which define the N- and P-emission are the amount of these elements in the feed and the FCR. The FCR value of Agrovision (2003), cited in Jongbloed and Kemme (2005), gives an emission of 11.6 kg/year N and 1.98 kg/year P as seen in table 4.3.
Table 4.3 N- and P-secretion (kg/year) for meat pigs with a FCR of 2.67. Source: Agrovision (2003), as cited in Jongbloed and Kemme (2005)
Insects are poikilotherms and therefore do not use metabolic energy to maintain a constant body temperature. This energy can be invested in growth, which results in a higher feed conversion efficiency (Nakagaki & DeFoliart, 1991 as cited in Broekhoven et al., 2015). This means that it is likely that crickets for example convert feed more efficiently to body mass than conventional livestock like pigs. According to Van Huis (2013) there are few studies on feed conversion for edible insects. The edible house cricket can have a FCR of 1.7 for fresh weight, as can be seen in table 3 (van Huis, 2012). In figure 4.3 the overview of FCR ratio for pigs and insects are given.
4.1.3 Water consumption
Pigs with a weight between 20 and 110 kg have a water consumption of 1.60 m3 per year (4.4 liter per day), while pigs with a weight more than 110 kg have a water consumption of 4.55 m3 per year (12.5 liter per day) (D’hooghe, Wustenberghs & Lauwers, 2007). A rough calculation, based on a water consumption of 1.60m3 per year, taking into account the growth period of 115 days, gives an outcome of 5.8 liter per kg produced pig.
Insects use food as the main source for their water. Depending on the species, development stage and type of site, water absorbed from the environment is needed.
In an interview with Damien Huysman, cited in van der Noot(2014), is revealed that for 1 kg of insects only 2 litres of water. In figure 4.1 an overview of the water consumption (L) per produced kg insect and pig is given.
4.1.4 Cost of Feed
The cost of feed is an important variable in the cost of pig production and is therefore well documented in the data available over the sector. This paper uses the data provided by Hoste in 2011. Hoste states in his report over the production costs of pigs in 2009 that from the total production cost per kg slaughter weight approximately 78 eurocents are from cost of feed. These numbers can fluctuate on the basis of the global food prices. The Netherlands has one of the most beneficial feed conversion ratios in the pig industry when compared to other countries. This has as a result that a rise in global feed prices has less impact on total production costs in the Netherlands when compared to other countries (Hoste, 2011).
The same mechanism that gives the Dutch pig industry a competitive edge also gives the insects an advantage. As stated before, insect grow with a more efficient feed conversion ratio (van Huis, 2013). A second interesting opportunity that would result in lower feed costs for insects is the possibility to breed insects on organic side streams of the current livestock
industry. Several species such as the black soldier fly and the yellow mealworm are able to very efficiently convert organic waste in live weight. This would greatly reduce the organic pollution from our conventional livestock industry and lower the feed costs. However, this way of growing insects is currently not allowed by law (Veldkamp et al., 2002).
Figure 4.4 The overview of the FCR ratio in kg feed per kg live weight for pigs and insects are given according to the values of Agrovision (2003) for insects and for pigs. Also, an overview of the water consumption in L per produced kg is given for insects and pigs.
4.2. Farm temperature
4.2.1 Optimal farm temperature for insect or pig production
Comparing with other farm animals, pigs are very sensitive to environmental temperature. This is because pigs are not able to actively perspire, and even warmth loss due to breathing is limited. In addition, fast growing pigs like meat pigs produce more warmth than their relatives in the wild and the cooling capabilities in the stable are limited. This combination makes it hard for pigs to lose warmth if temperatures are high. Increasing temperatures, for example from 18 to 26 °C, increases their breathing frequency, decreases their feed intake and finally increases their body temperature. Decrease in feed intake influences the growing capacity directly, and thus has a negative effect on the production (World of Warmth, 2005).
The optimal stable temperature depends on the weight of the meat pig. A pig with a weight of 20 kg has an optimal environmental temperature of 24 °C, while this decreases to 21 °C when the pig weighs more than 80 kg (Cnockaert, n.d.). This can be seen in table 4.4.
Table 4.5 Optimal environmental temperature for meat pigs (20 to 100 kg). Source: Cnockaert (n.d.)
Concerning insects, the efficiency in converting food to biomass is temperature sensitive. At a temperature of 30°C, the efficiency of converting food into biomass (ECI) is optimal for the house cricket (Van Itterbeeck, 2008).
The rate of diffusion of gases increases with temperature. As insects breathe through diffusion, this is an important factor that determines why insects are larger in warm climates. This can be an important factor why insects are not eaten in moderate climates: they are too small in size and too little in number (Mela, 1999 as cited in Van Itterbeeck, 2008). Now, tropical climate can be simulated in greenhouses or in a warmth chamber.
4.2.2 Environmental effect of the temperature regulation
In order to raise the temperature in a pig or insect farm, energy is needed. Most conventional pig farms use fossil fuel for obtaining energy. To make a correct comparison with insect farms, based on the environmental effect of the temperature regulation, fossil fuel is considered to be the energy source for both type of farms. When a higher temperature is required, more fossil fuel needs to be burned. The product of burning fossil fuel is carbon dioxide (CO2), which is one
of the greenhouse gases (Walker, 2003). Due to the CO2 emissions into the atmosphere, the
total amount of greenhouse gases increases. The greenhouse gases change the amount of outgoing longwave radiation from the earth by absorbing it, causing a temperature rise. This temperature rise is also referred to as global warming (IPCC, 2013b). So far, the overall temperature of both land and ocean surface combined has increased approximately 0.85°C between 1880 and 2012 (IPCC, 2013a).
As stated before, to obtain a higher temperature in a pig or insect farm, more fossil fuel needs to be burned. The average temperature of a pig farm is between 21 and 24°C, depending on the age and weight of the pigs. The average temperature of an insect farm is 30°C. Therefore, farming insects in the Netherlands will have a higher negative impact on the environment
4.3. Greenhouse gas production
4.3.1 Pig and insect CO2 and CH4 production
The (mini)livestock sector can be associated with environmental pollution, as this sector is one of the large contributors of greenhouse gas emissions. In table 4.4 the CO2 production is
reported for five insect species and pigs. The production is expressed per kilogram of live body mass per day (24 hours), per kg of mass gain and average daily gain. It can be seen that insects have a higher emission of CO2 per kg of body mass per day than pigs.
Table 4.6 CO2 production (average +- standard deviation). BM=Body Mass. Source: Oonincx et al., 2010
Of these insects, the Pachnoda marginata (sun beetles), tenebrio molitor (mealworms), Blaptica dubia (cockroaches), Acheta domesticus (crickets) and Locusta migratoria (locust) are some of the most used species produced as pet food and fish bait and are all edible for human (FAO, n.d.).
Table 4.5 reports the methane (CH4) production per kilogram of body mass per day for these
five insect species, pigs and beef cattle. It can be seen that pigs have a larger emission CH4
than insects.
This table reports the CO2 equivalent as well. As seen, it is presumed that pigs have a higher
CO2 equivalent than insects. The range of the CO2 eq. for pigs is large, 2.03-27.96. Only when
the production of pigs is in the lowest range, the CO2 eq. is lower compared to insects.
Table 4.7 CH4 and CO2 eq (average +- standard deviation) per kg of body mass per day. BM=Body Mass. Source: Oonincx et al., 2010
Figure 4.8 The minimum and maximum values of CO2 equivalence and CH4 for five edible insect species and pigs. Source: Oonincx et al., 2010
4.3.2 Environmental effect of the greenhouse gas production
CH4 is classified as a greenhouse gas. According to the IPCC (2013c), the total amount of CH4
in the atmosphere is lower compared to the amount of CO2 (1.8 ppm CH4 compared to 391 ppm
CO2). However, CH4 molecules absorb the longwave radiation transmitted by the earth more
strongly than CO2. Due to this, CH4 is responsible for a greater impact on global warming than
CO2 over a period of 100 years. This impact will approximately be 25 times stronger for CH4
than CO2 (USEPA, 2015).
As stated in paragraph 4.3.1, pigs presumably have a higher CO2 equivalent than edible
insects. The impact of pigs on the environment with regard to global warming, will therefore be higher compared to the impact of insects.
The greenhouse gas (GHG) emissions of mealworms (Tenebrio molitor) and other livestock have been compared in a study conducted by Oonincx & de Boer in 2012. The results can be seen in figure 4.6. Mealworms fall relatively in the middle of the spectrum when looking at GHG emissions for insects, with high N2O production but a very low CH4 and medium CO2 production
(Oonincx et al., 2010). It is therefore assumed that using mealworms as a comparison unit for insects in general to pigs is justified. It can then be observed that mealworms seem to have a lower global warming potential but a similar or even higher energy use. This higher energy use is mainly due to the higher temperature needed to produce insects.
Figure 4.9 Global warming potential (kg CO2-eq) and energy use (MJ) needed for producing 1 kg of mealworm protein, compared to other protein sources (Oonincx & de Boer, 2012)
4.3.3 Costs of the greenhouse gas production and temperature regulation
The European and Dutch policy regarding GHG emissions is that these must have dropped 20% in 2020 when compared to 1990. In order to comply to this goal, a significant reduction in GHG emissions must be made. As the table below shows, the last decade has seen a steady decline of emissions, especially with CH4 and NO2.
Table 4.10 National emissions of greenhouse gasses. CBS(2015).
In order to have a 20% decrease in CO2, these emissions need to be lowered by 37760 million
kg. The CH4 and N2O emissions have already a surplus of 284.81 and 21.1 million kg when taking into account the necessary 20% decrease. When taking into account the conversion rate
to CO2 as described in the IPCC report from 1996 (on a hundred years horizon these are 21 for
CH4 and 310 for N2O), the needed decrease in CO2 emissions comes to 25238 million kg. In
the Netherlands, 8.4% of the GHG emissions comes from livestock farming (Van der maas et al,2011). This study assumes that the livestock farming sector has to decrease their GHG emissions to their current share, so 8.4% of 25238 million kg of CO2 equivalent. This accounts
to 2120 million kg CO2 equivalent. It is very difficult to further specify this to a specific sector,
although figure 4.6 shows that beef cattle has a significantly higher output per unit (Oonincx & de Boer, 2012).
The cost per unit of GHG are heavily debated, but this study will use the costs as estimated in the study executed by Eyre et al. in 1997. These are as follows: For CO2, a range of 65 to 157
euro per ton is established. For N2O, a range of 5960 to 24208 euro per ton is used and for CH4 a range of 333 to 493 euro per ton.
The total external effects of GHG emissions by the livestock industry expressed in euro is therefore then a result of a simple calculation and comes to a range of 137-332 million euro. 4.5. Manure production
4.5.1 Amount and composition of manure
According to table 4.8 from the CBS, meat-pigs produce 1100 kg per animal per year thin manure. This gives 3.01 kg manure per day per animal and when the average weight of the pig is set on 70 kg, pigs produce 43 grams manure per kg pig per day.
Pig manure contains minerals, of which 12.0 kg/animal per year N, 4.2 kg/animal per year P and 7.5 Potassium oxide (van Bruggen and Faqiri, 2013). The almost all metals present in animal manures are derived from the feed. According to Nicholson et al. (1999) pig manure typically contains c.500 mg Zinc per kg dry matter and c.360 mg Copper per kg dry manure, reflecting metal concentrations in the feed. Concentrations of other metals (Ni, Pb, Cd, As and Cr) were usually less than 5 mg per kg dry matter (Nicholson et al., 1999).
Table 4.11 Manure production and mineral excretion of pigs. source: van Bruggen and Faqiri, 2013
The manure of insect is named frass. According to Spang (2013) 2.0070 grams of frass were recovered from 555.8043 grams of mealworms per 25 days. This shows a frass production of 3.61 grams per kg mealworms per 25 days. Mealworms usually live around 2 months
(Wiegersma, 2015) . A rough calculation based on the information given by Spang (2013) makes that mealworms produces 8.664 grams frass per kg mealworms per lifetime, and 0.144 gram per kg mealworms per day. Figure 1 gives an overview of the manure produced by pigs and insects.
Figure 4.12 Manure production in grams per day per kg live weight insects and pigs. Source: CBS To give an indication of the amount of N and P in the frass, grasshopper species are used. The species include among others the T. Varicornis, O. Abruptus and D. Venusta. The percentage of N and P of the grasshopper manure is approximately 2% and 0.45% respectively (Das, Ganguly and Haldar, 2010). The percentage of N and P of the pig manure is approximately 1.1% and 0.4% respectively when observing table 4.8. Subsequently, pig manure contains a lower
percentage of N and P. However, it is assumed that meat pigs produce more manure compared to insects and therefore the total amount of excreted N and P will be higher for pigs.
4.5.2 Effects of this manure on the environment
As described in paragraph 4.5.1, pig manure contains a variety of heavy metals as trace elements. One of these heavy metals is copper (Cu). It is therefore assumed that copper is a component of pig manure for this research.Copper is one of the essential micronutrients that organisms need for growth and development as it is used for a variety of metabolic processes. The micronutrient can be found in the earth’s crust abundantly. Copper can only be taken up by organisms in soluble form. However, because it is quite abundant and easily soluble, copper is rarely a limited nutrient. When the concentration of copper passes a certain limit though, it can become toxic for organisms. The effects of toxicity have a huge influence especially on the microorganisms in the soil and on the plants (Flemming & Trevors, 1989). Microorganisms are responsible for processes such as mineralization. Mineralization includes the decomposition of soil organic matter into carbon dioxide and nutrients, which are being released back into the environment (Martens, 1995). These nutrients are then available for plants again, which need them for growth and development. When the amount of copper in soils exceeds a certain
threshold, for example 500 mg copper per kg soil for agricultural land, the activity of microorganisms is being reduced resulting in a lower amount of nutrients that are being
released into the soil (Arthur et al., 2012). This will have an effect on the growth of plants as the amount of available nutrients is decreasing, which might result in a lower yield. However, this does depend on the amount of manure that is produced and how the manure is distributed on the land. When the manure is divided over agricultural land, and the threshold is exceeded, land degradation might occur. However, because the exact amount of copper is not known, an indication of the extent of land degradation cannot be given.
Other heavy metals that might be included in the pig manure are nickel, lead, cadmium, arsenic, chromium and mercury (Nicholson et al., 1999). All these heavy metals have, like copper, a toxicity threshold above which the soil might be unsafe. These are for nickel: 10 mg per kg soil, lead: 50 mg per kg soil, cadmium: 0.4 mg per kg soil, arsenic: 15 mg per kg soil, chromium: 50 mg per kg soil and mercury: 0.2 mg per kg soil (Bouma et al., 2002).
It is important to remove heavy metals from land quickly, as they accumulate in the land and as they are the main group of inorganic contamination (Singh et al., 2011). However, the total amount of these heavy metals are not known so an indication of the extent of land degradation cannot be given.
As described in the section ‘amount and composition of manure’ (paragraph 4.5.1), N and P are some of the elements contained by pig and insect manure. Both elements are essential for plant and animal growth and are therefore constituents of artificial fertilizer (Richardson et al., 2009). However, when nitrogen is excessively applied to land, soil acidification can occur and the cation exchange capacity of the soil decreases as a result. This inhibits the fertility of the land and land degradation occurs. Subsequently, an increasing amount of nitrogen can positively influence the leaching of nitrate (NO3-), because of the mobilization of nitrogen. When the NO3
-comes into contact with water bodies, eutrophication can be the result. The same applies to the leaching of P, as both elements are required for growth by animals and plants. Eutrophication can only occur though when P and N are added in excessive amounts, which the ecosystem cannot neutralize. So the ecosystem of the waterbodies cannot absorb the disturbances caused by the addition of N and P (Barak et al., 1997; Gunderson & Holling, 2002).
As pigs produce a higher amount of manure compared to insects, it is expected that pigs has a higher negative impact on the environment in terms of land degradation and eutrophication than insects, even though the concentration of N and P is higher in insect manure. Furthermore, no literature indicated the presence of heavy metals in insect manure. Subsequently, it is assumed that insects have a lower impact on the environment in terms of land degradation caused by heavy metals than pigs.
4.5.3 The monetary cost of manure pollution
The first of our parameters to be evaluated is the damage effected by the use of excessive manure. The Netherlands still has a surplus of phosphorus and nitrate inputs by the agricultural sector. This has as a result that our drinking water supply becomes contaminated with resulting costs and that eutrophication processes take place (Davidson,1996). The tables below show the surplus of phosphorus and nitrate in the last decades. This surplus has significantly lowered, but still poses a problem.
Figure 4.13 Mineral balance in the Netherlands. CBS(2010).
The policy goal is not to exceed the 50 mg/l of nitrate in surface water and 25 mg/l in the
drinking water (EU,2006)(Davidson,1996). The policy goals of phosphate are more complex, but are also significantly exceeded(CBS,2009). Pig and insect farms are usually very space
intensive farms. They produce a large number of animals on a very small area. This has as a result that they can apply the produced manure only very limited on their land without overusing. This is expressed in the table below. It shows the manure production and the so called disposal space, which is the amount of allowed manure to be used on their agricultural land (van der Maas et al., 2011).
Figure 4.14 Manure production and mineral excretion in the Netherlands. Source: CBS(2015).
In order to comply with the environmental policy goals, the strictest norm has to be used. This is in this context the phosphate regulation. To comply, a total of 9800 million tons of manure has to be processed. According to the data provided by the sector itself, the costs of processing a ton of manure falls in a price range between 8 and 22 euro per ton of manure. This relatively large price range comes from differences in region and season(KWIN,2014). Processing 9.8 million tons to this price range comes to a total cost range of 78-215 million euro to fully comply to the environmental policy goals as a pig industry. This is then the total value of the external effects of manure production when using the prevention cost method. With 14,5 million pigs in the
Netherlands slaughtered a year with an average slaughter weight of 93 kilos, this leads to an average cost of manure processing of between 6 and 16 cent per kg of produced pig. Within this margin are the costs described by the sector itself. According to a rapport of the Wageningen University, the manure disposal cost account to 8 cent per kg of slaughter weight (Hoste,2009). When comparing this to insect production, an important difference can be observed. Insect faeces are dry and therefore far easier and cheaper processed. This is around a factor 4 cheaper (Davidson,1996). However, clear data of manure produced is as of yet not to our disposal, making a calculation very difficult.
5. The possibilities for insect production on equal scale
5.1 A model for the approach of simulating the insect production
There is a lack of available information about the breeding standards of insects (Erens, van Es, Haverkort, Kapsomenou & Luijben, 2012). Thus when insect breeding is up scaled it is unknown what the optimal scale of production is, or what the system parameters will be. Moreover for the production of insects an ecosystem needs to be created were light, temperature, humidity, disease control, feed and density are accurately controlled (Erens et al., 2012).
To be able to predict the optimal production scale with the adjusted parameters and to simulate a system that can facilitate large scale insect production, an intelligent simulation model is needed.
The current techniques for insect breeding production are mainly based on empirical trial and error (Erens et al., 2012). Therefore we need a simulation model that can cope with
uncertainties.
Fuzzy Control is a theoretical framework describing how to implement human knowledge about how to control a system that is not mathematical defined and needs “vague” expert knowledge. This is often when a system dynamics is nonlinear or uncertain (Passino & Yurkovich, 1998). We found that this model is best suited for the simulated of insect productions.
We will study the design of a fuzzy controller to be able to illustrate how fuzzy control can be used for simulating and parameter tuning. Each component of the design of a fuzzy controller will be briefly explained followed by a example of how this could be applied in a insect
production system. 5.1.1 Fuzzy Control
Classical logic operates and structures with sharp boundaries. For example you only belong to the set of “old men” if you are a male person older than 60. In fuzzy logic an entity can have partial membership to a set. For example a man of the age 58 has the membership value of 0.24 to the set of old men. Figure 5.1 is a good visual representation of Bai & Wang (2006) of the difference between classical and fuzzy sets. Low, medium and high are the linguistic values.
Figure 5.1 Representations of classical and fuzzy sets from Bai & Wang, 2006.
An example of a linguistic variable is “age” with for example the values “old, not so old, middle aged, quite young, young” (Zadeh, 1975). Each value represents a suitable numerical value on a scale. For example the scale “age” goes from 0 to 100 with the value “old” starting at 70. Figure 5.2 is a good example of an age scale with the linguistic values.
The membership function determines the grade of membership of the entity to a fuzzy set. What the best membership function is depends on the application and is a difficult task.
Figure 5.3 of Jantzen (1998) shows some of the many membership functions.
Figure 5.3 Examples of membership functions. Read from top to bottom, left to right: (a) s-function, (b) ℼ- function, (c) z-function, (d-f) triangular versions, (g-i) trapezoidal versions, (j) flat ℼ- function, (k) rectangle, (l) singleton.
When a certain entity belongs to multiple sets there are multiple ways to choose which output is the best. Based on Bai & Wang (2006) it is considered best to use the Center Of Gravity method (COG). The COG method chooses the membership by weighted average, this is visualised in figure 5.4.
Figure 5.4 the Center Of Gravity method in Bai & Wang 2006
A final major component are the control rules. The control rules are based on the expert knowledge about insect farming. The rules say how to control the plant and match the input values to the output values(Bai & Wang, 2006).
We do not have the expertise to say which membership function is the best for the production system of an insect farm, but there are certain guidelines. Hill, Horstkotte & Teichrow (in Jantzen, 1998) recommend to start with triangular sets with an overlap of at least 50%. The output membership is recommended bij Jantzen (1998) to be singletons.
The input membership function is illustrated in figure 5.4 created in the fuzzytech demo on fuzzytech.com.
Figure 5.5: Membership function created in the fuzzytech demo (fuzzytech.com)
We will provide an example of how a fuzzy logic model for insect breeding could look like: Control rule: IF specie is MEALWORM AND age is YOUNG AND
density is HIGH THEN feed should be VERY_HIGH
Linguistic values: {Very_Low, Low, Medium, High, Very_high} { Young, Average, Old} Membership function:
Input = Age, Density: Triangular, overlap 50%.
Output= Feed: Singletons.
Defuzzification method: Centre of Gravity
Thus even though expert knowledge is needed for the design of this simulation model, there is no need for mathematical models. Moreover, with the literature that we have found it can be concluded that their is a good potential for fuzzy logic control in the insect farming industry. Naturally it is important that there is available software for the implementation of this model. FuzzyTECH as cited on fuzzytech.com is “the world leading family of software development tools for fuzzy logic and neural-fuzzy solutions”. There is a variety of software available depending on the application. A licence is needed for all applications.
As well Matlab fuzzy Logic Toolbox is available at http://nl.mathworks.com/products/fuzzy-logic/ and requires a licence. This toolbox runs in Simulink and is made for the analyzing, design and simulation of systems based on fuzzy logic.
Insect productions need to be automated in order to be able to produce large amount of protein and to lower the production costs (van Huis et al., 2013). A system can be automated when the process is controllable. The objectives for controlling a system are controllability and
observability (Loehle, 2006). Controllability is high when a system can be easily influenced. a system is observable if the causal relations between inputs and outputs can be inferenced. Insects have a very low threshold for reacting on parameter controlling such as light and temperature (Erens et al., 2012), and therefore their controllability is high.
Insect rearing systems do not have a high observability, for example a change in light and temperature can cause the same reaction (Erens et al., 2012). This should be taken into account when a control system is designed. Moreover it pleads for a control model that can cope with uncertainties, like fuzzy logic.
Dorf & Bisschop explain the 3 steps of the design of a control system:
1. Establishment of the goals, the variables that need to be controlled and the specifications
2. System definition and modeling
3. Control system design, simulation and analysis
Caceres, Rendon and Jessup (2012) made a generic Excel spreadsheet for the FOA and IAEA that describes which parameters are most important for the design and operation of insect mass-rearing facilities. These kind of insect rearing expert knowledge is needed for step 1 of the design.
Step 2 is about which equipment and sensors are used. There is view available information on this for us to find, buth the insect production company Protix Biosystems (www.Protix.com) announces on their website that they have large mass rearing production systems and they produce 3 tons of insects per week. An overview of their system is available on their website. The third step is to choose a controller and to test the system to see if it is working correctly. The controller we recommend is, as said before, a fuzzy logic controller.
The future steps of the control design is to firstly simulate a fuzzy controller with the software we have found using fuzzy logic and the insect production parameters. When all parameters are tuned and fuzzy logic has proved to be a good controller, hardware needs to be selected by studying current existing plants like Protix.
6. Discussion
In order to answer our research question, we must look at the aggregated results of this study. However, due to a lack of data on mainly the insect production parameters, we could not fully describe the details of the environmental effects. Furthermore, there was not enough
information available on a single insect species which could be used for all the chosen parameters. Consequently, we could not make a comparison between pigs and single insect species.
This report therefore uses several insect species to answer our subquestions.
Moreover, much of the data found in literature was inconsequent. For example, the components of pig manure would differ between articles as well as the amount of feed needed to obtain one kg of pig protein. To overcome this problem, either the most reliable source or an average of the found quantities was used.
However, this study does create an overall picture which shows the differences between insects and pigs in orders of magnitude. This enables us to address our research question with a relatively concise answer.
When the environmental impact of the insects’ and pigs’ manure is discussed, no absolute indication can be given of the total land degradation or eutrophication. This would only be possible when extensive research is conducted in situ in order to know the buffering capacity or natural state of the specific area. Therefore, only a rough comparison is given between the impact of pigs and insects on the amount of land degradation and eutrophication.
Because greenhouse gas emissions of the stable temperature and greenhouse gas production of the organisms themselves was considered separately, no precise indication can be given which species has an higher impact on the environment with regard to global warming potential. This study already discussed the reasons for choosing our method of quantifying the
environmental effects. However, the assumptions of our chosen methods are in need of clarification as well. First of all, the used method assumes that the set policy goals are an accurate representation of societal preferences. However, it can be argued that due to for instance a lack of information about a subject within a society could lead to not optimal policy goals. Second, the policy goals are set to be reached by a specific year. For example, the greenhouse gas emissions policy goals is set to be reached in 2020. These goals are set in the future in order to enable companies to prepare and comply with the policy goals. This could imply that the societal goals in the current year are on a lower level. However, this report assumes that there will be no major technological advances that reduce prevention costs in the near future. The external cost will therefore be similar(Davidson, 1996).
Furthermore It should be taken in account that the fuzzy control model is only a theoretical commencement and does not suggest that the actual implementation will be successful. This possible implementation depends greatly on the available hardware.
An overview of the comparable findings of the research can be observed in table 7.1. When we look at temperature and greenhouse gases, the greenhouse gas emissions per produced unit seem to favour insects. This is mainly due to their very low CH4 production. However, their
needed temperature and associated energy use and CO2 emissions are relatively comparable
to pig farming. This parameter is also the most impactful, with the livestock industry contribution to greenhouse gas emissions costing between 137 and 332 million Euros.
A second important parameter is the manure production. This seems to favour insects. This is due to several reasons. First of all, insects produce dry manure, incurring to a factor 4 times less costs. Furthermore, insects produce less manure than pigs. Due to this the total amount of excreted N and P is higher for pigs, even though insect frass contains a higher percentage of both.
Moreover, there are some possibilities to breed insects on organic side streams. This would significantly decrease the negative external manure effects and even create a potential positive external effect of insect breeding
The manure is the factor whit the second most impact in our research. The external costs of processing the manure of pigs come to a range of 78-215 million Euros. With at least a factor 4 less costs incurred by the insect farms, this is our first very clear difference.
Table 7.1: An overview of the comparable findings of the research
Parameter Pigs Insects (Species)
Feed
Feed ratio (Kg feed: Kg edible weight)
Composition
2.67
High value agricultural products
2.1 (Cricket)
Species dependent but potentially waste material Farm Temperature Optimal in ℃ 21-24 30 Respiratory gasses CO2 eq min CO2 eq max 2.03 27.69 0.05 4.00 Water consumption
water/kg produced livestock 5.8 2
Manure
Fuzzy Control has good potential for simulating and automating the insect production, despite the uncertainties within this industry. The production parameters can be used as both inputs and outputs of the control system.
For further research we recommend cooperation between insect rearing experts, hardware experts and artificial intelligence experts to design finish the design. Also the FOA and IAEA should be contacted to ask for information about their insect mass rearing spreadsheet. Moreover interviews with Protex Biosystems about their rearing system could be of major interest.
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