Tag: Statistical Process Control in insect rearing

Updated Class in Insect Rearing Systems Fundamentals

Figure 1: From the Case Study I Developing Predator Diets and the Concept: “KNOW YOUR INSECT.” Using discovery/inquiry to develop and improve rearing systems.

Figure 2 : From Case Study II Using Experimental Designs to Explore Relationships in Insect Rearing Systems.

  • October 28, 2025: Introduction: Case study—developing predator diets; why we rear insects (several case studies); sustainability & quality of reared insects; reduction of error and variability in rearing systems
  • October 30, 2025: Interactions and importance of rearing system components: using statistically based design of optimization experiments
  • November 4, 2025: Nutrition and dietetics in rearing systems
  • November 6, 2025: Approaches to quality control and process control (QC & PC)
  • November 11, 2025: No Class: Veterans’ Day Holiday
  • November 13, 2025: The nature and importance of stresses in rearing systems
  • November 18, 2025: The science and technology of equipment in rearing systems
  • November 20, 2025; Genetics and epigenetics in rearing systems
  • November 25, 2025; Microbial relations and invasive organisms in rearing systems

All classes start at 10:00 am Eastern Time through 1:00 pm Eastern Time. In each class meeting we will have two group discussion of 10-15 minutes to allow questions and contributions from and by participants. The registration fee is $450 for the 24 hours of instruction.

This class is substantially revised and offers up-to-date information about all major aspects or components of insect rearing systems. The content is rich in explanations and guidance to developing standard operating procedures with a scientific basis. The importance of stress is emphasised and quality and process control are key components. The scope of the class is suitable for novices in insect rearing through intermediate levels of background. There is also ample opportunity for participants to individualise their learning experience to meet their current needs and interests.

Please Note: We have greatly increased the interactive opportunities in this course to encourage participants to explore with Professor Cohen special interests from each person’s rearing interests.

To inquire further about the course, contact Professor Allen Carson Cohen at accohen@ncsu.edu

For registration information, please contact

https://reporter.ncsu.edu/link/courseview?courseID=MCE-OPD-C-OLFIRSF&deptName=MCE.

Ms. Darthea Powden

Program Assistant

NC State Continuing and Lifelong Education

Office of Professional Development

Campus Box 7401

Raleigh, NC  27695

dpowden@ncsu.edu

919-515-9092 (office)

919-515-7614 (fax)

OR, you may contact

Jamie Merritt

Program Coordinator,

NC State Continuing and Lifelong Education

Office of Professional Development

NC State University

Campus Box 7401

Raleigh, NC 27695

Direct line: 919-515-4796

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Anticipating and Treating Problems in Rearing Systems by Using Statistical Process Control: Getting Started

Insect rearing is a process.  The desired outcomes in rearing are to have insects that are healthy, representative of their species, readily available, useful for various programs (research, crop protection, conservation, as food for other organisms, etc.)  Being a process, insect rearing can be made more useful by application of process control, specifically statistical process control (SPC).  This concept was realized by a few pioneering authorities in insect mass rearing (including Boller et al. 1981 and Calkins et al. 1994: it should be noted that D. Chambers , T. Ashley, and E. F. Boller were suggesting the application of statistical quality control and SPC back in the 1970s, and a few facilities had adopted their suggestions.)

R. T. Staten and A. C. Cohen checking for problems in USDA, APHIS colony of big-eyed bugs in mass-rearing facility for predators

R. T. Staten and A. C. Cohen checking for problems in USDA, APHIS colony of big-eyed bugs in mass-rearing facility for predators

 

Green lacewing larva eating Cohen diet, feeding through a Parafilm membrane

Green lacewing larva eating Cohen diet, feeding through a Parafilm membrane

 

Getting Started in SPC:

A good first move in developing a process control system is to determine WHAT we are trying to control or what the problems may be = the causes of error or variability that have crept into our system.  A nearly universal tool or model of decision-making about which processes contribute the most to the benefit or the harm of our system is the Pareto analysis.  So, for example, when we were trying to mass rear predators such as big-eyed bugs (upper left figure with R. T. Staten and A. C. Cohen in the Phoenix USDA, APHIS lab in 1995 or the lacewing rearing as in the upper right image), we would try to reduce mortality in our system.  With careful observation by the rearing specialists, we decided that in one rearing unit (one rack) in our system we had the following causes of mortality or loss:

 

Pareto Plot of Mortality in Predators

In this case, we found that 22 deaths could be attributed to mold in the diet, 16 deaths from diet drying out, and cannibalism, poor stretching of the Parafilm membrane preventing the proper feeding seen in the upper right diagram, problems with molting, and escapes accounting for other loses.  In 8 containers, the causes of failure were not determined, possibly unseen pathogens or genetic defects.

The point here is that once we had collected data on the most likely causes of loss and the relative frequency of these causes, we could launch an effort to correct the problems, and clearly dealing with contaminants would be the most fruitful in improving our rearing outcomes (since nearly half the loses came from contamination.  This data-driven conclusion was based on the Pareto analysis, which is a simple tool that helps to shape decision-making about rearing system improvements.

This simple example tells us these things (take home messages): 1) collecting data is where to start, 2) using the expertise that is available is helpful in deciding what data to collect and how to interpret (e.g. how do we know how to recognize mold or desiccated insects?), 3) analysis of the data with graphic techniques can be very useful.

In a soon to be posted blog, we will cover some approaches taken to improve the problem with straggling in the Forest Service gypsy moth colony at Hamden, CT back in the late 1980’s (see ODell 1992 below).  It’s an excellent example of problem-solving approaches.

 

Boller, E. F., B. I. Katsoyannos, U. Remund, and D. L. Chambers.  1981.  Measuring, monitoring, and improving the quality of mass-reared Mediterranean fruit flies, Ceratitis capitata Wied. 1.  The RAPID quality control system for early warning.  Z. angew. Entomol.  92: 67-83.

Calkins, C. O., K. Bloem, S. Bloem, and D. L. Chambers.  1994.  Advances in measuring quality and assuring good field performance in mass reared fruit flies.  Pp. 85-96.  In C. O. Calkins, w. Klassen, P. Liedo [eds.], Fruit flies and the sterile insect technique.  CRC Press.  Boca Raton, Florida.  U.S.A.

ODell, T. M.  1992.  Straggling in gypsy moth production strains: a problem analysis for developing research priorities, pp. 325-350.  In T. A. Anderson and N. C. Leppla [eds.], Advances in insect rearing for research and pest management.  Westview, Boulder, CO.

 

 

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