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Predicting Soft Scale Insect Population Dynamics in Greenhouses

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9 diapositives · 214 Views · Jul 28, 2014

Applying mathematical models to predict soft scale insect population growth can aid in effective greenhouse management. Explore consumption types, growth rates, and impacts on plants. Utilize statistical models for data analysis and extrapolation to propose control measures.

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Predicting Soft Scale Insect Population Dynamics in Greenhouses
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  1. Research Proposal: Predation Pengse Po, Scott Maxson

  2. Introduction • The objective of this study is to apply a mathematical model to predict overall population of soft scale insects alive in the Durfee greenhouse. • Exponential Equation: • N(t)= N(0)+e^rt^ • Linear Equation: • lnN(t)= lnN(0)+rt

  3. Scale Insect Physiology When it comes to the scale insects gaining energy from plants there are three major types of consumption present. First is herbivory which takes place when an animal (an herbivore, in this case the scale insect) consumes plant tissues. Second is paratism which occurs when a parasite consumes relatively small amounts of tissue or nutrients from another individual, the host. In this case the scale insects are the parasites and the plants within house 2 are the hosts. Third, predation occurs when a predator kills and consumes all or most of another individual (Freeman S. 1220).

  4. Growth Rate and Survival The scale insects literally suck the life out of plants, thus killing them, and in the process they consume much of the material that makes up the plant. These insects generate their energy from the sucked out plant juices, and eventually, infested plants habitat (Steve 186).

  5. The Impact on Plant Another danger to the plants is that in humid areas a fungus can grow on the honeydew that is secreted by the insects. Because this fungus makes the plant leaves and stems appear sooty; its common name is “sooty mold” (Merchant 1914). Scale insect eggs are laid underneath the plant's waxy covering and hatch over a period of one to three weeks (University of Florida 2009).

  6. Exponential Equation: N(t)= N(0)+e^rt^ Linear Equation: lnN(t)= lnN(0)+rt

  7. Methods Our experiments will involve counting population size of soft scale insects with in house number 2 of the Durfee greenhouse. Table 1: Group 1,2,3,and 4 will use table 1 to collect sample size on day 1 and 2. This table will reflex the hand counted of soft scale insects in house number 2 at Durfee greenhouse. Table 2: Group 5,6,7, and 8 will use table 2 to collect sample size on day 3 and 4. This table will reflex the hand counted of soft scale insects in house number 2 at Durfee greenhouse.

  8. Statistical Model Team 9 (us) will use a program called “Stat R” to plot and create a visual model of the Arrhenius equation. This model will then be used to extrapolate the top-down hypothesis that needed to control the insect population.

  9. Discussion The results of this study will be used to provide an effective model of scale insect population within house 2 over time. This, in turn, can be used to predict what preventative and reactionary measures the greenhouse staff should take to keep the orchid population healthy. The top-down control hypothesis states that herbivores populations are limited by predation or disease (Freeman, S. 1224). This method is the most efficient to control soft scale insects without a risk of damaging the plants with chemicals.