economic analysis of cotton-insect control in the sudan gezira

CROP PROTECTION (1986) 5 (5), 348-354

Economic analysis of cotton-insect control in the Sudan Gezira

GERALD A. CARLSON AND AHMED MOHAMED

Department of Economics and Business, North Carolina State University, Raleigh, North Carolina 2 76958110, USA

ABSTRACT. Changes in net returns from modifications in insecticide use are evaluated by estimation of three component models: a yield function, a cotton-quality relationship and an alternative pesticide use equation. Data from 41-99 production regions and 3 crop years are used to evaluate a shift from conventional insecticides to ground-applied aldicarb for late-season insect control. Analysis of multiple effects of insecticides reveals that net returns from aldicarb use in the short term are about 220%. This change in pesticide use has improved yields and increased cotton quality.

Introduction

Cotton insect control in the Gezira area of Sudan has been experiencing difficulties (Eveleens, 1983). The number of insecticide applications increased steadily over the last two decades until over nine sprays per season were applied in 1978/79; thus the proportion of production costs used for crop protection increased until it stabilized at about 25% in 1979/80 (Elobeid, 1982). Cotton yields and the area planted declined during the 1970s (Reynolds et al., 1983). Subse- quently, insecticide treatments were reduced in the last five seasons, and yields and cotton area have expanded rapidly in the past three seasons, with the area planted expanding by about 15% and yields increasing from about 2 * 5 kantars/feddan* in 1979-81 to 4 - 8 in 1982-84 (see Table 1) (Mohamed, 1984).

Various explanations are given for the production changes taking place in recent years. Sudan Gezira Board (SGB) officials have cited fortuitous weather conditions that have kept whitefly (Bemisia tabaci) populations low. Reynolds et al. (1983) have pointed to the importance of change in cotton-tenant incentives brought about by the switch to individual tenant accounts beginning in the 1981/82 season. The use of herbicides and fertilizer has also increased in the same period (Reynolds et al., 1983). The other major change has been the switch to aldicarb (Temik@ ) insecticide applied mid-season to prevent the build-up of poten- tially damaging populations of mid- to late-season cotton insects, primarily the whitefly. Aldicarb (2-methyl-2-(methylthio)propionaldehyde O-methyl- carbamoyloxine) is a relatively expensive systemic

l One kantar is 141.5kg and one feddan is O-417ha.

insecticide with a long efficacy period and which is ground-applied during September to October in the furrow at 6.75 kg a.i./feddan as 15% granules. Irriga- tion follows the aldicarb application. The use of aldicarb has increased from 842 feddans in 1979/80 to 141794 feddans in the Gezira in the 1983/84 season (Table 1).

The relative efficacy of aldicarb has been assessed by the Agricultural Research Corporation (ARC) in the Sudan on small-scale plots and in some commercial fields since 1966/67 (Anonymous, 1983a). Yield comparisons between cotton treated or not treated with aldicarb over the 1979/80-l 982183 period showed yield gains that ranged from 4% to 124% (Anonymous, 1983a). In one season (1981182) costs of insect control were compared between four aldicarbtreated areas and two conventionally treated cotton areas: the latter required approximately 4.5 more applications and cost 7 * 4% more. Other benefits that have been claimed for aldicarb are the increase in cotton fibre quality, reduced trash and reduced stickiness (caused by honeydew secreted by whiteflies) on the cotton lint. The economic effect of whitefly control on cotton quality has not been studied, and the direct yield effect of different whitefly levels has not been quantified. There is also very little information on the quantitative reduction in the number of whiteflies that can be associated with aldicarb treatment.

Use of aldicarb involves a large investment and because there is considerable uncertainty about the magnitude and types of benefits from its use, this study presents detailed estimates for costs and returns of its

0261-2194/86/05/0348-07 $03.00 0 1986 Butterworth & Co (Publishers) Ltd

GERALD A. CARLSON AND AHMED MOHAMED 349

TABLE 1. General statistics for Sudan Gezira cotton production*

Total area in cotton (feddans) Yield (kantarslfeddan) Average price (LSikantar) Gross revenuelfeddan (LS) Area treated with aldicarb (feddans) Area treated with aldicarb (%)

Acala (70) Baracat (W)

Average cost of other sprays (LSlfeddanlseason) Average number of other sprays (no./season) Other insecticide cost application (LSlfeddan) per Aldicarb cost application (LSlfeddan) per Offtcial exchange rate (LSIUS dollar) Whitefly (no.1400 leaves)? Jassids (no./400 leaves)? American bollworm (no./400 plants)?

1981/82 1982183 1983184

43 1346 477494 494759 3.886 4.662 4.981

87.89 84.89 101.15 341.54 395.75 503.83

20951 48000 141794 4.86 10.05 28.66 0.0 17.86 74.81 5.29 7.64 6.90

56.47 60.63 92.95 7.10 5.35 5.70 7.90 11.33 16.31

23.30 53.38 65.97 0.80 0.90 1.29

1380 1023 723 25 55 79

8.3 2.4 2.6

* Source: Compiled from Sudan Gezira Board records. t Sum of averages of 4 months for all 41 blocks for which insect data VKR available

use over the past three seasons. Detailed records on pest counts for three pest species, namely whitefly, American bollworm (H&this arm&era) and jassid (Empoasca Zybica), and on cotton yields, cotton quality as measured by grades, other insecticide costs, past yield histories and aldicarb use were compiled from SGB records for each of the 99 cotton-growing blocks within the Gezira. Models relating cotton yield, cotton quality, cotton receipts per feddan, whitefly counts and other insecticide costs were developed and, from these models, estimates were made of price and yield changes resulting from aldicarb use. Estimates were also obtained for the effect of aldicarb use on whitefly counts and expenditures for other cotton insecticides. Combined estimates for Acala and Barakat cotton varieties on the net returns from treating with aldicarb have been obtained.

Methods of analysis and data collection

Aldicarb is effective against whitefly (Balla, 1980; Anonymous, 1983b; Reynolds et al., 1983), but it is less clear what the whitefly pest densities are in the Gezira, and how they are affecting cotton yield and quality. Aldicarb has been used principally in the Southern part of the Gezira, and on the Acala cotton variety in the last two seasons (see Table 1).

The models of aldicarb use were designed to assess possible economic effects in four areas: yield, cotton quality as measured by grade changes, changes in other cotton-insecticide expenditures, and changes in off- farm benefits as affected by ginning costs, environmental quality and safety and cotton-price changes. The general model of net return per feddan of cotton (NR) for each block in the Gezira was specified as:

NR=P(T, WF, 0,) Y(T, WF, 0,) - TC-OIC(T, OJ-o4 (1)

where P( T, WF, 0,) is the price per kantar, Y( T, WF, 0,) is the yield of cotton in kantars per feddan, TC is

the aldicarb cost per feddan, OIC( T, 0,) is the other insecticide cost per feddan and 0, are other production costs (water, fertilizer, labour) considered to be unaffected by aldicarb use. T is the measure of aldicarb use which for block data will be in terms of percentage of the cotton area in a block treated with aldicarb in a given season. WF is the whitefly level for the season which is measured as the average adults per 100 leaves summed over 4 months. Oi, O2 and 0, represent sets of other variables to be explained later, such as cotton variety, year, other insecticide cost (OIC), other insects, and average yield in the block over the past 8 years. A block is an administrative unit of the Gezira which typically has 3000-5000 feddans of cotton. Equation 1 represents how individual tenant farmers receive changes in income from aldicarb use, and how its value might be evaluated by the SGB, other Sudanese officials and lending agencies.

The primary data collection was on averages for each of the individual blocks of the Gezira for the three seasons 198 1/82-l 983/84. Some data from randomly selected tenant farms were collected, but insecticide- use data were incomplete and only the block level analysis was continued. Some of the summary figures are shown in Table 1. Data on expenditures for other cotton insecticides by block were not available for 198 l/82. Some of the following analyses are based on 2 years, but most have 3 years’ data. Analysis of all 99 blocks combined was carried out, but aldicarb has been used over these years on only 41 blocks for which complete insect counts for the three species were available. The 41-block sample represents 9970, 48% and 62% of aldicarb use in the 3 years.

In the results reported below, separate estimates are made of several components of net returns in equation (1) above. The three main components are quality estimates related to P(‘), yield estimates related to Y( ‘) and other insecticide costs, OIC( ‘). The yield and quality models can be represented as:

Yield, Y( ‘) = 6Y/d WF -F + SY/dT (2)

350 Economic analysis of cotton-insect control

Quality, P( ‘) = W/6 WF - F (3)

where all variables are as defined as above, and 6Y/ 6 WF is read as the change in yield of cotton from a small change in whitefly numbers. The total yield effect from aldicarb treatment is considered to be the product of the effect of whitefly on yield (6 Y/d WF) and the reduction in whitefly from applications of aldicarb (6 WF/6 T), plus a possible effect of aldicarb on other unmeasured, insects and direct effects on plant growth. Direct effects of aldicarb on plant growth have been found in experiments verifying additional uptake of nutrients and plant growth by cotton plants treated with aldicarb (Ragab, 1981). Three separate models are estimated below to give estimates of these three components. The effect of aldicarb on cotton quality is the product of the effect of a small change in whitefly on cotton quality (U/d WF) and the same effect of aldicarb on whitefly population. There is not expected to be any direct effect on cotton grades of aldicarb use except through its effect on whitefly population level.

The estimates of the components of equations (l), (2) and (3) were obtained by ordinary least-square pro- cedures applied separately to the average yields, quality and cost of other insecticide-dependent variables in additive, linear form (unless otherwise indicated). Dummy variables for crop season and cotton variety are added as shifters of the intercept term to account for unexplained effects that change with year and variety. Statistical significance of effects were measured by Student’s ‘t’ statistics. Overall ability to explain the dependent variables as measured by R2 (70 of total variation ‘explained’ by variables in the model) is also given, but the size of the ‘t’ statistics indicates the chance that correct inferences on individual variables are being made.

Statistical results of on-farm aldicarb effects

Yield effects of whitefly

The first regression model estimated the effect of whitefly numbers on cotton yield (model A in

Table 2). The other variables in the model reflect other factors that might affect yield. These include yield history, and shifters related to the years (1982/83 and 1983184) and to the cotton variety, Barakat. The year parameter estimates indicate if there was a change in yield from the (arbitrarily) chosen base of 1981/82 season yield on Acala cotton. Values under each parameter give the ‘t’ statistic for that parameter. A value greater than l-97 shows that the parameter is different from zero with 95% certainty. For example, in model A of Table 2, the crop years 1982/83, 1983/ 84, Barakat cotton, whitefly and yield history are statistically significant in affecting average cotton yield. The yield history variable is the 8-year average yield for each block prior to the time of this analysis (1973/74-1980/81) to reflect fixed factors such as soil fertility, weather factors and management differences by blocks.

Model A shows that whiteflies are associated with lower yields. In particular, each additional 100 whiteflies per season, reduces yield by O-035 kantars per feddan. Other models were estimated which included bollworm and jassid pest-count variables, but the results were not different from those reported here except that higher bollworm levels were associated with lower yields. One model with an interaction between whitefly and variety showed more damage per whitefly on Barakat than on Acala.

Effect of aldicarb on whitefly numbers

The second component of the yield effect of aldicarb use (Model B of Table 2) estimates the change in whitefly with changes in the proportion of the cotton area treated with aldicarb. This is the direct chemical efficacy or a linear dosage-response curve. The statistical significance of aldicarb is 99%. Each 1% increase in aldicarb is associated with a reduction of the season whitefly count of 10 - 762. Notice also that there is an indication from Model B that whitefly levels are lower on Barakat cotton. The intercept term is 1284 for Acala and if the variety is Barakat the intercept is 520 (1284- 764) whiteflies per 400 leaves. As the co- efflcients for years 1982/83 and 1983/84 are statistically

TABLE 2. Yield, quality and whitefly control regression parameter estimates*

Log revenue+ Yield per feddan Season whitefly numbers per kantar

Independent variables (4 P) (Cl

Intercept 4.15 (8,55) 1284 (3.78) 4.34 (2.20) 1982183 0.44 (2.19) -543 (3 79) 0.01 (2.76) 1983184 0.73 (3 * 24) -558 (3.55) 0.223 (53.4) Barakat - 1.65 (7.71) - 764 (5.00) Whitefly

0.233 (60.6) -0*00035 (3.16) - -0.00717t (3.15)

Yield history 0.451 (5.39) 216 (3.54) -O.OlfH (3.01) Aldicarb (%) - - IO.762 (6.20) - R= 0.68 0.48 0.99 Sample size (N) 123 123 123 Dependent mean 4.92 1042 4.491

* Values are least-squares regression estimates; valnes in parentheses are ‘f’ statistics; values greater than I .97 are significant at the 95% confidence level with 188 degrees of freedom.

t Whitefly numbers, revenue per kantar and yield history are expressed as logarithms.


significant, there is an indication that these years had lower whitefly levels compared with 1981182 when account is taken of other factors in the model. Blocks with higher yields in the past also have higher whitefly levels. All of this is consistent with observations and discussion with the SGB entomologists interviewed. The relatively low R2 value indicates that there are other unknown factors which affect whitefly levels.

Together, the effects of aldicarb treatment on whitefly count and whitefly count on yield give the effect of whitefly control on yield (6Y/6 WF - 6 NV?/ 6 T). The figures are - 0 - 035 X - 10 * 762 = 0 * 38. This does not include the effect of aldicarb on other pests or direct growth enhancement which is estimated in a later section.

Effect of whitefly control on cotton quality

Model C of Table 2 shows the effect of whitefly on average revenue per kantar. Average revenue per kantar in each block was computed by taking a weighted average of all amounts harvested in each quality grade, where the weights were the prices paid by the Sudanese government to the farmers for each grade in each year. Grades in this case reflect classification of the cotton as to libre length, cleanliness and other factors as it reaches the gin. The model which best fit the data was a logarithm transformation of the continuous variables. In this case whitefly level was statistically significant in reducing revenue per kantar. The value ( - 0 * 007 17) is quite small and when it is transformed and multiplied by the effect of aldicarb on whitefly control ( - 10 * 76), it gives only a 0.65.LS (Sudanese pounds) increase in price per kantar. As Table 1 indicates, the average price for this data set was 93 LS per kantar, so the effect of aldicarb treatment on cotton quality as graded at present at the farm gate is only 0 - 6%. With an average yield of 4.92 kantars per feddan, this represents an increase in income of 3 * 2 LS per feddan from aldicarb treatment due to quality gain.

Direct effect of aldicarb on cotton production

The estimates of the direct or total yield effects of aldicarb use on cotton are shown i% Table 3. Model D gives the estimated value of O-0068 kantars per feddan from each 1% of a block treated with aldicarb. Complete treatment of all cotton in a block would increase yield by 0 -68 kantars per feddan, which is an average figure for both Acala and Barakat cotton. The yield effect is statistically significant at higher than 95%.

The implied effects of aldicarb on plant growth and on control of other pests (jassids, bollworms and other pests) is approximately 0 - 30 kantars per feddan (0-0068x 100-O-38). The total yield gain is 0 - 68 kantars so 0 - 38 or 56% of this is from whitefly control. This is an average figure over 3 years over both varieties of cotton.

Several other estimates of the total yield gain from aldicarb treatment were made because the timing of irrigation before and after aldicarb application, and the timing of aldicarb application relative to cotton plant growth, are critical for effective whitefly control. Co- ordination of ground applications is difficult over wide areas. To test whether aldicarb application was more effective in later years, the same yield model was estimated for only the last two crop seasons using the same 41 blocks for direct comparison. Model E in Table 3 gives the yield gain in the last 2 years from aldicarb. The overall yield gain of 0 - 77 kantars is slightly higher compared with 0 * 68 for the 3-year period, but the difference (O-09 kantars) is not statistically significant.

Another yield model was estimated to control for the yield-enhancing effects of the non-aldicarb (other) insecticides. (Two blocks were deleted because of lack of other insecticide cost data.) A yield effect from aldicarb of 1.02 kantars was obtained when the cost of other insecticides is included in model F. This is approximately a 32% additional yield effect compared with model E. The expenditure for other insecticides is not statistically significant in increasing yield in this

TABLE 3. Cotton yield regression results*

Independent variables

Intercept 1982183 1983/84

Barakat Temik (%) Other insecticides Yield history R2 Sample size (N) Dependent mean

Yield per feddant CD)

3.69 (7.89) 0.65 (3.27) 0.84 (3.88)

- 1.32 (6.29) 0*0068 (2.83)

- 0.36 (4.23) 0.67

123 4.92

-

Yield per feddan* (E)

3.02 (5.63) -

0.23 (1.19) -0.97 (3.77)

0.0077 (2.85) -

0.63 (6.12) 0.75

82 5.34

Yield per feddang F)

2.59 (4.68) -

0.18 (0.90) - 1.01 (4.06)

0.0102 (3.47) 0.0028 (1.01) 0.70 (6.97) 0.79

78 5.31

Yield per feddanl 63

1.789 (4.92) -

-0.178 (1.07) -0.672 (3.64)

0.0109 (4.84) 0.0045 (1.78) 0.821 (10.35) 0.643

198 4.807

* Parameter estimates are by least squares; values in parentheses are ‘t’ statistics with significance of 95% with all sample sizes for f values greater than 1.97. All models are in linear form of the raw data.

t Estimates are for 41 blocks for three seasons, 1981/82-1983184. * Estimates are for 41 blocks in 1982183 and 1983/84. § Estimates are for 39 blocks in 1982/83 and 1983184 1 Estimate is for 99 blocks in 1982/83 and 1983/84.


model. This may be a statistical artefact because of negative correlation between aldicarb use and level of non-aldicarb use, or because there are a limited number of blocks.

Model G estimated final yield using data from all blocks for which costs of other insecticide treatments were available (99 blocks for the last two seasons). The overall yield effects are quite consistent with model F with a yield gain from aldicarb use of l-09 kantars. All variables have the expected signs, and the aldicarb variable is significant at 99% and the other insecticide expenditure variable at 90% certainty.

Overall, the yield gain with aldicarb treatment is slightly higher in recent years. The gain is higher when the effect of use of other chemicals is included, and when a wider geographical area is considered. The percentage gain from aldicarb use is approximately 14% in Model D, 14% in Model E, 19% in Model F and 22% in Model G. Of all of these models, Models F and G can most easily be defended on statistical and biological grounds. These results will be used in the overall evaluation below.

Other insecticide cost savings

The final component of the net return equation (1) is the change in costs of other chemicals when aldicarb is used. Other insecticides are used early in the season because they are thought to be more effective against jassids. The level of other insecticide expenditures will vary from year to year, depending upon pest levels, variety and use of aldicarb. The data set is all blocks for which data on other insecticide costs are available (the same as for Model G). Other insecticide costs (OIC) estimated in the same manner as the yield equations are given by:

OIC=46-58+25*86 (Barakat)+41-66 (1983/84)- (10.58) (5.77) (11.25)

0 * 395 (% aldicarb), (6.81)

R*=0.55; N= 198

where values in parentheses are the ‘t’ statistics. This model indicates that 100% aldicarb treatment will lower other insecticide cost by 39.5LS per feddan. This represents 3 * 50 applications at the 1982/83 cost of 11*33LS per application, and 2 * 42 applications at the 1983/84 cost of 16.31 LS. The statistical significance of all the variables in the model is 99% or higher. This model also shows that for the last 2 years, other insecticide costs. were higher on Barakat cotton than Acala (+ 25 * 86 LS) and higher in 1983184 than in 1982/83 (4 1.66 LS). The latter figure primarily reflects the increasing dollar cost of each insecticide application because of devaluation of the Sudanese currency.

The implication of use of aldicarb in terms of reduced other insecticide costs is that each feddan treated with aldicarb lowers other insecticide costs by 39 - 5 LS per feddan.

Off-farm benefits due to aldicarb

Treatment with aldicarb lowers honeydew levels on cotton fibres and thus can improve ginning efficiency and the prices which export buyers are willing to pay for cotton. In addition, because aldicarb is replacing about three conventional aerial insecticide applications, there is the possibility of less environmental damage due to pesticide drift.

The relative benefits of aldicarb compared with substitute compounds, as far as reduced off-site damages to animals, fish and human health are concerned, are difficult to assess in economic terms. A USAID team of safety and entomological specialists in Sudan during the 1983184 season when aldicarb was applied indicated that only minor incidents of fish and livestock damage occurred. Farmers have been warned of the potential danger to livestock during the time when aldicarb is active in cotton plants and other fodder within the cotton fields. Several farmers within the Gezira allowed livestock to feed on aldicarb-treated fields during early January 1984 (10 weeks after aldicarb was applied); none reported ill effects to their livestock. Unfortunately, the USAID team did not sample cotton blocks and surrounding areas, so that a direct comparison of off-site damage in aldicarbtreated and conventional insecticide areas could not be made.

The effects of reduced honeydew on cotton gin efficiency were assessed by interviews of cotton classifiers and gin managers at the Maringa gin in the Gezira. They indicated that there were two ways in which higher costs were incurred when honeydew levels were higher: they had to pay gin workers bonuses (about 20% of base salaries) to replace blades in the gins more frequently, and they experienced reduced gin output per day when ginning cotton from blocks with high honeydew content and high humidity conditions. They reported that these conditions were more severe late in the season. One other change taking place, partly as a result of the difficulties with honeydew, is the more rapid replacement of the roller- type gins with the faster saw gins.

The effects of honeydew on national export prices of cotton were investigated by compiling all available information on prices received over years. The Cotton Public Corporation in Sudan compiles information on average sales prices received by year, cotton type and cotton grades. They cannot identify cotton by blocks, but only by major growing regions. The available information on cotton prices by regions for the past 6 years does not indicate a consistent price discount for level of honeydew. The market prices paid by region reflect many factors besides the level of honeydew. However, when asked to estimate honeydew effects, a Cotton Public Corporation official estimated that the price premium due to whitefly control could be about 10%. This 10% premium figure is only a guess of the actual willingness of cotton brokers to pay for absence of honeydew. More analysis of the prices paid for


TABLE 4. Overall net benefits from aldicarb use

Yield change Yield change’ Yield changet (kantarslfeddan) (“lo) (LSlfeddan)

1. Whitefly control 0.38 7.7 2. Other yield changes 0.30 6.1

3. Total yield change 0.68 138 4. Total yield changes with other insecticide 1.02 19.2 94.90 5. Grade change 3.20 6. Other insecticide savings 39.50

7. Total aldicarb benefits 137.60 8. Aldicarb costs -62.81

Net returns per feddan 74.19 Percentage rate of return 137.60/62.81=219

* t

Based on the 3.year yield of 4.92 kantardfeddan average for items 1, 2, 3 and 2-year yield of 5.31 for item 4. Based on 1982/83-1983/84 weighted average prices of cotton (93.OLS/kantar), costs of(l3.84LSlfeddan) and aldicarb costs of(62.81 LSifeddan).

various cotton lots from particular cotton blocks with the associated whitefly counts is needed to verify the export price premium.

Summary of aldicarb net benefits

This analysis was intended to provide a more accurate estimate of net benefits from aldicarb use in cotton in the Sudan Gezira, as previous comparisons indicated that increases in cotton yields were highly variable (4-124%). No effort had been made in earlier studies to hold constant other variables affecting yields, such as soil productivity, pest level, variety and use of other insecticides over wide areas. Little seemed to be known about the actual practice of reducing other insecticides in areas treated with aldicarb by SGB decision makers. The assumption was that as many as four conventional applications could be saved as aldicarb activity in the cotton plant lasted for 6-8 weeks. This work also developed models which would help to indicate whether the yield gains could be associated with reduced whitefly numbers or with other cotton-crop effects such as control of other insect species and direct cotton-plant growth enhancement.

A simple profit model with three separate aldicarb effects (yield, quality or cotton price, and other insecticide savings) was specified. Each component of the model with three sub-components of the yield model were estimated. The data for the analysis was compiled from SGB records for all Gezira blocks for the last three cotton seasons (1981/82-1983/84).

A general summary of the data used is in Table 1, and Tables 2 and 3 show seven of the eight statistical models estimated. Statistical tests show with a high degree of confidence (95-99%) that whiteflies reduce cotton yield, that aldicarb reduces whitefly populations, that average cotton quality is slightly increased by aldicarb use, that aldicarb produces cotton yield gains beyond those due to whitefly control, and that aldicarb use decreases use of other insecticides in the Sudan Gezira.

The major findings of the analysis are shown in Table 4. If the effects of use of other insecticides are ignored, the models show a 0 - 68 kantar per feddan (k/f)

yield gain (i.e. about 13.8%), similar to the average results of previous studies (Reynolds et al., 1983). The components of the yield gain show that about 60% of the yield gain (0 - 38 klfeddan) is from measurable whitefly reductions and the other 40% (0 - 30 k/feddan) from direct cotton-plant growth enhancement and control of other pests. When the statistical model is expanded to include the effects of other insecticides and restricted to the last 2 years, the yield gain is estimated to be 19.2% or 94.90LSlfeddan.

The quality-enhancement effects of aldicarb were statistically significant, but small in magnitude. This measurement of quality change includes only changes in cotton grades related to fibre length and cleanliness. The value of this gain was estimated as 3 -20 LS/ feddan. The use of aldicarb provides savings in the use of other insecticides of about 39 *SOLS/feddan (i.e. about 2 * 85 aerial insecticide applications).

The net return from use of aldicarb over the past two seasons was 74 * 79 LSlfeddan. At a cost of 62.81 LS per feddan for aldicarb, this represents a rate of return of 219%. There is a high degree of certainty that the yield, quality and insecticide-savings gain is in the 130-145 LS range. Sudan cotton marketing specialists believe that cotton prices are reduced about 10% by whitefly honeydew secretions. More data analyses are needed to verify these cotton price effects.

Aldicarb use in the Sudan as currently practised is determined by decisions well in advance of knowing precise whitefly levels in particular cotton fields or blocks. There is always the chance that whiteflies and other insects will develop resistance to aldicarb. There should be continued investigation of a wide range of chemical and non-chemical approaches to pest management such as resistant cotton variet.ies, use of economic thresholds and pesticide rotations (Eveleens, 1983; Reynolds et al., 1983). The above analysis indicates that data from wide areas can be assessed to evaluate the short-term profitability of pesticide use.

References

ANONYMOUS (1983a). Review of Performance; Residue and Environ- mental Effect of Temik Aldicarb Pesticide Applicable to Use for


Whitejb, Bemisia tabaci Control on Cotton in Sudan. Research Triangle Park, North Carolina: Union Carbide.

ANONYMOUS (1983b). Temik@ Aldicarb Pesticide: A Scientific Assessment. Research Triangle Park, North Carolina: Union Carbide Agricultural Products Co., Inc.

BALLA, A. W. (1980). Recommendation of Temik 15G, Bidrin 103, Bidrin 103+Endosuljan 50, Bidrin 24+Endosulfan 50, Roger 50, and Rogor SO+DDT. Wad Medani, Sudan: Agricultural Research Corporation.

ELOBEID, H. A. (1982). The Gezira Current Statistics, Season 1980/81-1981/82. Barakat, Sudan: Sudan Gezira Board, Economic and Social Research Unit.

EVELEENS, K. G. (1983). Cotton-insect control in the Sudan Gezira: analysis of a crisis. Crop Protection 2, 273-287.

MOHAMED, A. (1984). Economic Analysis of Cotton Insect Control in

Sudanese Cotton. MS thesis, Department of Economics and Business, North Carolina State University, Raleigh, North Carolina.

RAGAB, S. M. (1981). Cotton growth and nutrient uptake following Temik aldicarb application. Journal of Agricultural Science 97, 731-737.

REYNOLDS, H. T., CARLSON, G. A., DANAUSKAS, J. X. AND GRIMES, D. G. (1983). Evaluation of PM Development on Cotton in the Sudan Gezira with Particular Reference to the Useoj Temik. Berkeley, California: Consortium for International Crop Protection.

Accepted 1 March 1986

economic analysis of cotton-insect control in the sudan gezira

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