A central tenet of the rearing program at NCSU is that insect rearing systems are artificial ecological niches of the insects we rear. This means that every aspect of the insect’s needs must be met by our rearing system. This responsibility of rearing personnel applies whether we know each requirement or not. For example, each insect (and each insect population in our colonies) requires a certain range of oxygen to meet their metabolic needs. We may not know how much oxygen this requires (the range of oxygen concentrations), but when we provide holes in the lid of the rearing container or a screen that permits gas exchange, we hope that the openings are adequate to meet the oxygen demands.

Therefore, we can think of the oxygen requirements as part of our insects’ ecological niche, and if our insects perform adequately under the conditions of our rearing containers, we assume that everything is OK “oxygen-wise.” We make the same kinds of assumptions about carbon dioxide concentrations and air flow and the same about water vapour. Sometimes we get ourselves in trouble when we try to restrict water loss from he diet or the insects by making the openings so limited that we wind up starving our insects of adequate oxygen (a phenomenon known as hypoxia or even anoxia); and/or we make create a situation of excess carbon dioxide, which can threaten our insects’ well-being.

In all the rearing courses that I teach, I try to convey to students that the rearing system with all its components that meet the insect’s ecological niche parameters is a complex set of interactions between various (ALL) components, and a helpful way of viewing all this is with a 3-D model or diagram such as what is seen here:

In this diagram that simulates or suggests three-dimensional space, I have tried to show about 20 of the many, many parameters in a niche. The diagram is intended to illustrate that there are interconnections and interactions that involve all the biotic (biological) and abiotic (physical/chemical) factors that play roles in our insects’ well-being. This model of N-dimensional hyperspace is derived from the work of the famous ecologist G. Evelyn Hutchison. I have used this model in my recent book, Design, Operation, and Control of Insect Rearing Systems 2021, CRC Press, Boca Raton, FL).

For this discussion, let us take-up a simplification of this diagram with 3 factors, heat, CO₂, and O₂. Here is the simplified diagram:

In this 3-D, three-factor diagram, I am trying to show that the waxworm from my colony (of Galleria mellonella) is greatly influenced by the heat (temperature) conditions in their rearing container; but also, the concentration of CO₂ and O₂ are interacting factors that influence the metabolism and aggregation behavior of the waxworms, as well as food consumption, digestion rates, development rates, etc.

These interactions are illustrated in the images taken from my waxworm colony where I used a thermal imaging camera to capture the heat (thermal) gradient produced by the waxworms in this container.

In the study of the colony described here, I have also included (besides the thermal profile) the CO₂ and O₂ gradient that results from the waxworms’ behavior and metabolism. The example, taken from waxworm cultivation in my research program, is typical of the kinds of multi-dimensional dynamics that apply to ALL insect rearing systems. My whole point in this and related discussions is to get students of insect rearing to recognise the complexities of their rearing systems components. It is further intended to awaken students’ appreciation for knowing the nature of (the science of) these many factors and their interactions.

This approach is not simple or easy; but it is very powerful in establishing and maintaining healthy, productive colonies!

In yesterday’s post, I discussed the matrix concept in insect diets. I used an example of a visual treatment of a diet matrix using an image of a stained wheat germ-based diet viewed and photographed under about 20 x magnification in a video microscopy system. The basic image looked like this:

In the above images, the lower image shows a 1 x 3 cm section of diet with hornworms consuming the diet. The neonates (newly-hatched 1st instar larvae) depend upon finding all the nutrients they require within a small area of the diet where all lipids, protein, carbohydrates, minerals, and vitamins must be present in adequate amounts to support healthy growth. The upper image shows the granular nature of the diet whose particles (which are suspended in an agar or carrageenan framework) have an organization that can be thought of as conforming to a network, matrix relationship. This relationship (the granulometery) contributes to the potential for structural integrity, resulting in diet consistency and texture. There is also a great deal of potential chemical interaction such as lipid-binding by lipoproteins, carbohydrate-protein interactions, enzymatic and oxidative reactions, diffusion of solutes or nano-particles that are involved in the diet’s taste/texture qualities (palatability), the availability of nutrients within the reach of the insect’s mouthparts; then upon ingestion, the particles and solutes must be available for digestion and absorption. Finally, the arrangement of the particles and other diet components must lend itself to the diet’r retention of palatability, nutritional value, and bioavailability in a framework that we call stability. All the physicochemical characteristics and interactions constitute the diet’s MATRIX.

In these images, there is an implicit matrix organization that dictates or commands the nature of the diets in question. To better understand this matrix/organization feature, we can examine the following diagram:

In the above diagram (partly explained in the image caption), the various levels of organization are shown from macro- to nano levels. The inset on the right-central part of the diagram is a fluorescent micrograph of the diet that was stained with the lipid stain, Nile Red, which shows the lipids in a 20 micron particle of wheat germ. Other fragments in this insect (against the black background) are brightly-coloured carbohydrates, which stain blueish with Nile Red. The upper central portion is a diagram of a large lipoprotein molecule of about 25 nm x 5 nm, and on the left central portion a sterol molecule is depicted as a less than 1 nm structure. The lipoprotein molecule contains hydrophobic pockets (the greenish structures on the left and right ends of the molecular structure). It is the hydrophobic pockets in lipoproteins that bind with and carry lipids (= lipophorins). Throughout this diagram, it is evident that there are micro-relationships on the physicochemical level of organization, and these relationships lead to degrees of stability, nutrient bioavailability, and taste (palatability). An important part of this relationship is in the interactions between particles and liquid interfaces, and we will further explore these in relationships that we study with granulometry.

At the centre of insect rearing systems are diets, usually artificial diets. These diets are composed of multiple components such as base nutrients and functional components. Base nutrients are usually complex nutrient “packages” such as wheat germ, soy flour, chicken eggs, corn meal, meat products, yeast products, rice flour, wheat bran, oat bran, and dozens of other foods that contain proteins, carbohydrates, lipids, minerals, vitamins, and various biochemical components such as flavonoids, phenolics, etc. Many of the base nutrients common to insect diets are nearly complete nutrient packages that are supplemented by other components to complete the nutritional and phagostimulatory (feeding stimulation) of the artificial diet. If a component such as wheat germ is found to have a deficiency in carbohydrate or lipid, for example, sucrose or starch and linseed oil or cholesterol may be added to complete the nutritional or phagostimulatory needs of the insects. Salt (mineral) and vitamin mixtures are also often added to complete the nutritional package.

Other artificial diet components that help give the diet consistency and stability are added to meet our target insect’s specific feeding characteristics. For example, many insects that feed on plant tissues do well with gelled diets, so we use gelling agents such as agar, carrageenan, or other substances that bind water and diet components in such a way that the consistency of plant leaves, stems, roots, or fruits is mimicked enough that the insect accepts the diet as a suitable plant-part substitute. We also add materials that reduce microbial spoilage or oxidative deterioration (anti-microbial agents and antioxidants) to stabilize the diet. While the topic of nutritional and functional components of diets deserves much more attention, for the present discussion, let us say that the diets that are designed to provide complete nutrition, palatability, bioavailability, and stability are the diets that we deem “successful” (See Cohen 2004 and 2015 for further discussion of the nature of successful diets).

However, one of the facts of life that became apparent to me decades ago is that many diets that people had tried to develop failed to support complete development of successive generations of target insects. Even though ALL the seemingly necessary components were present, often, our diets failed!

I came to realize that “the whole is greater than the sum of its parts,” in diet development research. I found that I could take a good diet as as living or frozen prey of a predator, break down the components, and then reassemble them and I would NOT have a diet that worked as well as the original food. I found further that it was not just a question of the food being alive that related to the food’s success. It was something in the organization of the food’s components that conferred (in part anyway) success of the diet. The organization is another way of discussing the matrix nature of the diet and its constituent components. I offer an image of a diet that shows how components function at various levels of organization (gross macro-, macro-, micro-, and nano-levels of organization.)

I will further discuss this diagram and its MATRIX nature in further discussions on these pages. I also point out that in my classes, I try to provide an intense and. detailed documentation and process of inquiry into the matrix nature of diets that work=successful diets.

A problem that I have found in the insect rearing community is that we rearing specialists tend to view our domain as a strictly applied discipline. I try to counter this trend in my rearing courses. The problem is that as rearing specialists, we have a very narrow purpose in our job description: producing the target insect. The complexities of this job are so great that it’s easy to see why a busy rearing scientist would not find time to scan the literature looking for research findings that MAY be applicable to our target insect.

What I try to do in my courses is to make constant efforts to expand my own base of understanding and knowledge, and I further try to provide a base of information on the issues that give the students an appreciation for how seemingly disparate information may be of great value in understanding their insects in a rearing context.

One example of this is the recent discussions that I have posted on oxygen and carbon dioxide in our rearing systems. My experience of working with wax worms (larval Galleria mellonella) called my attention to the issue about whether or not the larvae were able to get sufficient O2 (and to void the CO2) that was produced by these crowded larvae (see Figure 1). Early in my waxworm rearing experiences, I learned that the larvae tend to aggregate and display high levels of activity, sometimes just pulsing back and forth in their silk tunnels. I saw this phenomenon in many different containers that I tested to optimise the rearing cages for my rearing system. From my observations, I became convinced that the larvae spend a great deal of their time and their silk-making resources in a quest for gas exchange.

This very applied question led me to investigate the gas exchange issues with G. mellonella larvae, and one of my current research topics is the determination of respiratory dynamics with various diets (low vs. high fat/ low vs. high carbohydrate diet mixtures). These studies have further led me to measure the O2 and CO2 in rearing containers where the waxworms crowd themselves in tight aggregations with high density populations. Naturally, the discovery that the waxworms were chronically under low O2 and high CO2 conditions led me to ask the questions about O2 and CO2 dynamics of other reared insects, especially the gregarious ones that we keep at high densities. This line of thinking led me to search the literature for various publications on the effects of O2 and CO2 stress (low oxygen and high carbon dioxide conditions). It was during this line of inquiry that I found the paper that I have been discussing from VandenBrooks et al. 2018 where the authors demonstrated the effects of hypoxia manifesting itself with enrichment of tracheoles and mitochondria. This very basic science discovery may have far-reaching implications for insect rearing where the practical (applied) issue of quality control of our insects can be directly related to availability of O2 and dispensing of CO2.

More about these relationships in further posts, but let me re-emphasize the importance of being flexible minded about what is “mere basic science” vs. what has very practical implications in our rearing systems.

In a recent post, I discussed the components of rearing systems that comprise the ecological niche setting. In that post, I provided a table from my book on rearing systems, and this table included 22 parameters which are present in the insects’ natural ecological niche and which must be provided in the artificial niche. For example, the table includes what I have called the “starter insects’ genetic characteristics” as well as food, waste product accommodations, gas exchange, moisture exchange, light relations, and so on.

In my experience with scores of rearing systems, small and large scale, many of these “niche components” are often neglected or underestimated by rearing personnel. Because most of us who require insects for research or other purposes are concerned only with the practical matter of having the insects available for our purposes, we do not bother to scrutinise the various features of how well our rearing system satisfies the fulfilment of the niche requirements. This is to say, we do not examine the character of the light relations (optimal photo-period, optimal intensity, and optimal light qualities or wavelengths). Likewise, we do not pay much (or any) attention to the microbial profile of our insects; and with few exceptions, we take at face value the microbial relations that are taking place in our insects. If we produce successive generations of Drosophila, for example, to meet our genetics investigations, we do not ask about the microbial profile of the insects’ guts or their environmental microbial associations. If the flies reproduce in their rearing containers, we do not ask if the gas exchange is optimal or if there is a stress imposed on our flies by excessive buildup of CO2 or by O2 deficits. Despite the fact that some researchers such as the VandenBrooks team have shown that O2 deficits can lead to dramatic changes in the respiratory system’s ultrastructure (increased tracheal branching and diameters as well as increased mitochondria associated with hypoxic conditions).

We rearing specialists and users of reared insects too often make the mistake of taking at face value the health and well-being (FITNESS) of our insects. Another way of regarding this fitness is as the QUALITY of our insects, and this is directly associated with the physiological concept of HOMEOSTASIS.

The above image (Figure 1) shows pre-pupal larvae being reared on a wheat germ diet derived from the Yamamoto 1969 tobacco hornworm diet. In this figure, a few of the “moving parts” of the rearing system are depicted, the insect, the diet, frass, and slits in lidding for gas exchange. There is also an indication that microbes are ever-present in rearing systems, within the insects, in the frass, and other parts of the rearing system. Still more features are present in this rearing sub-system, including the environmental conditions such as temperature, humidity, light qualities (including photo-phases, light intensity, and light quality). Sounds and odors also help comprise the insects’ environment as are container configuration and population density (number of individuals per unit of container volume). Many examples of the potential complexity and intricacy are prominent features of rearing systems that are helpful to understand; take microbes, for example.

Various microbial interactions are possible in the rearing system.

In Figure 2, the greenish background is a colony of fungi that grew on an insect diet where the moisture content was too high. In the upper foreground, the black and white image shows the partially-dissected gut of a lacewing adult with the gut contents shown to include yeast which are part of the rearing diet of the lacewings and which also reside in the insect’s specialised, diverticulum-based gut where the yeast thrive as symbionts with the host adult. The lower left picture shows whitefly larvae with their characteristic mycetomes (paired reddish structures), and the image on the lower right shows microbial inhabitants of the gut of termites. Besides these relationships of insects with symbionts (which are mutualists with the insects) and contaminants, there are also possible relationships with pathogenic microbes. ALL of these relationships must be understood to help keep our insects thriving (unstressed and displaying homeostasis) in the colonies that we house in our rearing systems. More on this in the next post. Please note the table (taken from Cohen 2021: Design, Operation, and Control of Insect Rearing Systems, CRC Press). I will comment further on this table in the next post.

Figure 6.1. Simplified Niche Parameters Expressed in an N-Dimensional Hypervolume. Figure 6.1 depicts the idea that there are many facets of niches, represented as intersecting or overlapping vectors. The intersections represent the concept that niche parameters are interactive.

Table 6.1. Niche parameters in rearing systems.

I have become comfortable with the JMP (from SAS) tools for using design of experiments (DOE). I share here some compelling statements from the JMP website:

ttps://www.jmp.com/en_ph/statistics-knowledge-portal/what-is-design-of-experiments.html

“What is design of experiments?

“Design of experiments (DOE) is a systematic, efficient method that enables scientists and engineers to study the relationship between multiple input variables (aka factors) and key output variables (aka responses). It is a structured approach for collecting data and making discoveries.

“When to use DOE?

• To determine whether a factor, or a collection of factors, has an effect on the response.
• To determine whether factors interact in their effect on the response.
• To model the behavior of the response as a function of the factors.
• To Optimize the response.

“Ronald Fisher first introduced four enduring principles of DOE in 1926: the factorial principle, randomisation, replication and blocking. Generating and analysing these designs relied primarily on hand calculation in the past; until recently practitioners started using computer-generated designs for a more effective and efficient DOE.”

The quotation from the stated website (from JMP) gives the basis of the arguments that I am asserting about why DOE is such a valuable tool for insect rearing personnel. First, the idea of studying the relationships between multiple factors should appeal to every rearing specialist. When we put our insects into a rearing system and provide them with artificial diets, we should wonder how the diet components affect the insect and how they affect one-another. For example, how does the pH of the diet relate to solubility of a protein supplement such as casein? Furthermore, how does the pH affect solubility of salt mixtures such as Wesson salts? A little inquiry about casein (which should more properly be called “caseins” because there are several milk proteins that are indicated by the term “casein”) shows that this protein is very hard to dissolve at near neutral pH levels. Therefore, unless we make special efforts to dissolve casein (such as pre-dissolution in basic solutions), this important protein is likely to form pockets within the diet where it is non-homogeneously distributed. The casein-rich vs. casein-poor pockets contribute to the problem of non-uniformity, which leads to serious differences in growth and development rates of larvae that are otherwise similar in age and genetic composition. The same type of non-homogeneity applies to dissolution and distribution of salt mixtures. I have shown (Cohen 2015) that Wesson salts are virtually non-soluble unless they are dissolved in a low pH solution. That helps explain some of the positive effects of using diets that are on the acidic side, rather than neutral. Further analysis helps us understand that the texture of the diet, in terms of firmness or gel strength, is enhanced by the presence of salt mixtures where Wesson and Beck salts have an enhancing effect on the gel strength of agar, carrageenan, or other hydrocolloid gels (Cohen unpublished data).

In Figure 1, I have tried to suggest some of the complicated interactions that are present in an insect diet. The lesson here is that using DOE-based investigations, we can begin to dissect the components of our rearing systems to help us understand the ways that rearing factors affect the nature and success of our rearing systems. The whole thrust of this approach is to turn the “black boxes” that describe our rearing systems into more transparent and logical processes.

More about this in future postings!

Currently, in all my classes, I use design of experiments (DOE) to help us better understand the factors that are most important in insect rearing systems. I originally became aware of the applications of DOE through a criticism of my statements about using one factor at a time for diet development in my book on insect diets (Cohen 2004). The criticism came from Dr. Steve Lapointe et al. (Lapointe, S. L., T. J. Evens, and R. P. Niedz. 2008. Insect diets as mixtures: Optimization for a polyphagous weevil. Journal of Insect Physiology. 54: 1157-1167.) I was initially dismayed at the criticism of my conventional (and outdated) thinking that we could only use one variable (one factor) at a time in a good scientific experiment. Once I got over the ego-deflation of having a blatantly narrow statement in my book, I set-out to learn how multiple factor experiments could be far more telling about the nature of our diets and other rearing system components.

As a start in my new-found application of DOE, I included this more sophisticated approach in the 2nd edition of my Insect Diets: Science and Technology, but I still had a steep learning curve. After years of effort to learn how to use the JMP approaches to DOE, I have reached a point where I routinely use various DOE tools (response surface designs, full-factorial designs, mixture designs, and Taguchi designs–all of which have their own specific applications). I have included extensive tutorials on using JMP’s system of DOE-based programs in my newest book, Design, Operation, and Control of Insect Rearing Systems (2021, CRC Press).

I want to make a special point about using JMP’s DOE: I am a physiologist, NOT A STATISTICIAN. Despite my trying to learn how to apply DOE, once I learned how powerful it could be in helping me understand the science behind insect rearing system dynamics, it was still a steep learning curve for me. I realize that most of my fellow rearing professionals are NOT statisticians either, and that is why I believe the JMP system’s DOE is so helpful. It allows people like me to ease their way into the very powerful statistical programs that can be so helpful in understanding what is going on in our rearing systems. The following mini-case study helps illustrate this point:

In Figure 1, I present a test that I did with painted lady butterflies (Vanessa cardui). In this test, I was asking the questions about the efficacy of sweet potato flour, rice bran extract, citric acid, and three types of protein (casein, soy, and dairy whey). The table in Figure 1 shows that I used two levels of sweet potato flour, two of rice bran extract, and two of citric acid while I provided casein, soy, or whey proteins. This full-factorial design required that I make up and evaluate 24 different diets (all of which had the same proportions of the other diet components not shown here). In the last two columns (on the right), the responses of total biomass per rearing unit and mean weight of individuals are presented. Feeding these data into the JMP system resulted in a complete statistical analysis of the experiment, including this convenient summary of the outcomes:

In Figure 2, the summary of the experiment is shown in terms of the total biomass that was derived from insects on the 24 different diets. This graphic representation helps us see clearly that the higher amount of sweet potato flour (10 g) gave superior results to the 5 g versions. The rice bran extract did not contribute substantially in either the 3 g or the 6 g versions. The higher level of citric acid (2 g) gave FAR better results than the lower (1 g). And the three proteins were not very different from one-another, with a possible trend towards the whey protein. What is not shown here (for reasons of simplicity) is that another graphic table in the JMP results shows which factors had interactions with other factors (positive or negative interactions). And this is one of the most exciting parts of using design of experiments with multi-factor components. It is, in my estimation, the interactions that really help explain how our rearing systems work.

By using a DOE approach we can better explore what factors are of significance in our rearing systems, the direction of their influence (positive or negative), and the factors which interact in ways that would not be intuitively predictable. Therefore, my teaching approach is to examine our rearing systems through the DOE approach! More about this will be presented in subsequent blogs and web pages.