be generated considered at the outset. The use of traps for the monitoring of insects is fraught with difficulties mainly caused by the variability of trap catch data. This vari- ability makes interpretation of the data dif- ficult and this in turn reduces the value of such traps as monitoring devices. It is important if traps are to be used for moni- toring that they are developed for the spe- cific purpose and conditions for which they are needed. In an ideal situation a trap would be developed and evaluated along the lines of the scheme in Fig. 2.12.
The most critical phase of the development occurs after the initial field test. If success- ful then full scale trials over a number of sites and seasons could take place. This could not be justified if the initial trial were not successful, but if results were partially successful the temptation always exists to expand the trial with the hope that more data will clarify the situation. A successful monitoring procedure will pro- vide consistent and reliable forecasts; if the data are variable then the value of the pro- cedure will be diminished.
Table 2.2. Incidence of pink bollworm on open and unopened bolls in plots treated with insecticides according to four different pheromone trap catch thresholds (T1–T4), a fixed schedule treatment (T5) and an untreated control (T6) (after Taneja and Jayaswal, 1981).
Treatment threshold Total Total
Number of moths/ number Percentage number Percentage
trap/night open bolls increase unopen bolls increase
1978–1979
T1 4 758.5 19.4 164.0 42.9
T2 8 769.7 25.8 168.7 45.9
T3 12 768.0 34.0 153.5 56.0
T4 16 765.0 47.3 175.7 66.9
T5 Fixed
schedule 778.5 48.9 169.5 72.8
T6 Control 724.2 84.9 172.5 91.0
F-test NS S NS S
1979–1980
T1 4 751.5 25.6 73.5 34.0
T2 8 770.2 32.7 72.5 43.6
T3 12 794.7 48.2 78.2 59.0
T4 16 811.5 47.8 84.0 56.4
T5 Fixed
schedule 812.5 44.2 90.2 49.9
T6 Control 821.5 72.4 92.5 78.6
F-test NS S NS S
spray application was made within 24–48 hours of the observed threshold. The fixed spray schedule was the application of insecticide at an interval of 13–14 days.
The incidence of pink bollworm during the experiment was recorded, in the squares, flowers, green bolls and opened and unopened bolls. Only the data from the opened and unopened bolls are discussed here.
Twenty plants were tagged in each plot and all the opened and unopened bolls from these plants were picked and the incidence of larvae recorded (Table 2.2).
The highest incidence of larvae in open and unopened bolls in each season occurred in the control plots where no insecticide was applied. In 1978–79 the percentage incidence in both opened and unopened bolls increased from treat- ment 1 to treatment 5, in the 1979–80 season the differences between treatments were less pronounced (Table 2.2). The first treatment recorded a significantly lower incidence of larvae in the opened and unopened bolls than other treat- ments in both years. Hence, the application of insecticides, when the number of moths averaged four or eight moths/trap/night, proved to be a better strategy than the fixed spray schedule. However, in this particular case, the spray pro- gramme based on a threshold of four moths/trap/night resulted in an increased number of insecticide applications. A study of the economics of this programme still indicated that even with a greater number of sprays than the fixed schedule the threshold programme produced a higher profit.
2.5.2 Temperature and physiological time Temperature has a major influence on insect development and, hence, can be used to predict emergence of a particular life stage. The use of age to define the development stage of insects or plants has been replaced by the idea of physiological time. Physiological time is a measure of the amount of heat required over time for an organism to complete development, or a stage of development (Campbell et al., 1974). Physiological time, which is the cumulative product of total time 3temper- ature above a developmental threshold (Southwood, 1978), is measured in day degrees and is considered to be a thermal constant (Andrewartha and Birch, 1954).
Hence, if it is assumed that development is a linear function of temperature (above a threshold) then the insect develops in pro- portion to the accumulated area under the temperature vs. time graph (Allen, 1976).
Before physiological time can be computed an estimate of the insect’s threshold tem- perature for development needs to be obtained and the form of the relationship between temperature and the insect’s development rate established.
The simplest estimate of the threshold for development is the point at which a
regression line crosses the x-axis (where the development rate = 0) in a develop- ment rate vs. temperature relationship (Fig.
2.13). The development rates are deter- mined for each individual as the reciprocal of the time to development (1/develop- ment time). They are normally obtained by measuring the development times for a number of individuals at constant tempera- tures in an environmentally controlled cabinet or growth chamber. Fluctuating temperatures may influence the time to complete insect development (Siddiqui et al., 1973; Foley, 1981; Sengonca et al., 1994) although Campbell et al. (1974) found no difference when constant and fluctuating temperatures were used, pro- vided that the fluctuations were not extreme, i.e. they did not extend below the threshold and the average temperature was not in the upper threshold region. The insect’s diet or host may also influence the development time, hence the host plants used in experiments should reflect those used by the insect in the field (Campbell et al., 1974; Williams and McDonald, 1982).
The use of the linear regression x-axis method for calculating a developmental threshold is sufficiently accurate for most applications; however, techniques for more
Fig. 2.13. A comparison of linear (––––) and sigmoid (– – – –) approximations of the relationship between rate of development (1/time) and temperature for (a) larvae and (b) pupae of Trichoplusia ni (after Stinner et al., 1974).
accurate threshold estimates are possible. If care is taken to obtain data at very low and high temperatures the relationship between development rate and temperature may be found to be sigmoidal (Fig. 2.13). The sig- moid relationship shown in Fig. 2.13 simu- lates the lower temperature relationship more accurately than the linear relation- ship (Stinner et al., 1974). The function used to produce the sigmoid relationship is as follows:
where:
RT = rate of development (1/time) at tem- perature T
C = maximum development rate 3 ek1+k2, i.e. the asymptote
Topt = temperature at which maximum development rate occurs
k1 = intercept (a constant) k2 = slope (a constant)
T′= T(temperature), for T< Topt T′= 2 ?Topt– T, for T> Topt
Stinners sigmoid model has been widely used (e.g. Whalon and Smilowitz, 1979;
Allsopp, 1981).
The daily temperature cycle needed in any day-degree calculation can be obtained from a daily temperature trace or it can be simulated using a sine wave approxima- tion. Using only daily maximum and mini- mum temperatures a sine wave can be generated that closely simulates a daily temperature cycle. A formula for calculat- ing half day, ‘day-degrees’ in situations where the temperature cycle is intercepted by a lower threshold temperature for devel- opment is provided by Allen (1976); a sim- ilar formula is also provided by Frazer and Gilbert (1976).
The accuracy with which a day-degree model predicts a biological event will depend on the accuracy of the developmen- tal threshold, the type of temperature mea- sure used and the precise time that the day-degree accumulation begins (Collier and Finch, 1985). Agronomists working
with annual crops commonly use sowing date as the time to start an accumulation (Pruess, 1983), i.e. a clearly defined starting time, with an obvious biological signifi- cance. However, entomologists using day- degree models find it more difficult to define a single discrete time/event that can be used to initiate an accumulation. Where insect growth stages are carefully monitored and where one growth stage is used to pre- dict the occurrence of a future stage (e.g. Jay and Cross, 1998), for example adult catches in traps used to predict egg hatch, then models may have a starting time that can be clearly defined, and are usually quite suc- cessful (Pruess, 1983; Garguillo et al., 1984). However, in situations where models are used to predict insect development after a period of dormancy or diapause, initiation times for an accumulation may not be easily defined. Often arbitrary dates are chosen (Baker et al., 1982; Collier and Finch, 1985).
The justification for this is usually that day- degree accumulation before that date is likely to be negligible. Use of such arbitrary starting times is likely to become a major source of error in any day-degree accumula- tion: an error that cannot be corrected by mathematically precise day-degree calcula- tions (Pruess, 1983). Where possible, start- ing dates for any day-degree calculation should be based on meaningful biological criteria.
Day-degrees can be most effectively used in combination with a monitoring technique to predict the onset of a particu- lar life stage of an insect, e.g. egg hatch.
This information can then be used to ensure timely application of a control measure. Most commonly it is used with insecticides (Minks and de Jong, 1975;
Glen and Brain, 1982; Potter and Timmons, 1983; Garguillo et al., 1984; Pitcairn et al., 1992); however, the principle applies to other control methods as well e.g. crop covers used to control Penphigus bursarius on lettuce (Collier et al., 1994), which is especially important when insects are only vulnerable to insecticides for very short periods of time, for example with boring insects.
R C
T = k k T