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Synergistic effect of temperature of acetone extraction of Piper guineense on maize weevil (Stitophylus zea mays) by mixture experimental design.

Introduction

Synthetic insecticides; aldrin, chlordane, endrin and DDT are some of the potent insecticides, small-scale, large-scale farmers and industrialists (Jackai and Oyediran, 1991). Synthetic insecticides are toxic to man and his environment. (WHO, 1994).Toxicity arises because insecticidal residuals are consumed along with the treated grains, damage to the ecosystem because they are not biodegradable (FAO, 1994), increase pest genetic resistance through mutation (Champ and Dyke, 1976). They are costly to produce and procure needs special skill through proper education for safe and effective application. The high cost of medical treatment on affected persons and bioremediation of soils contaminated is enormous, such expenses could be directed into more useful projects.

Soft maize highly cherished of the varieties among the rural populace where this work was done, it is eaten green, dried, roasted and boiled. It is used for starched product manufacturing due to its high starch content. It is strictly protected for fear of extinction especially from the attack of maize weevil in storage.

Before the advent of insecticides, soft maize was preserved with spices from plants, (Sigamony, et al., 1997),. In addition to their use as food and cosmetics, spices have been used as mosquito repellant and antifungal household fumigants. They are generally regarded as safe and more environmentally-friendly than synthetic counterparts and a little chance of causing resistant pests. The application of aromatic suitable pytochemicals, the synthetic counterparts will be eliminated. Even though the method was effective, the method was not scientific. Dev & Koul, (1997) and Adgeh, (1987), have found onions, pepper (Capcicum annum), Neem (Azdirachta indica) and African black pepper (Piper guineense).

Piper guineense is a plant among the candidates with enormous potential for use as a bioinsecticide, it is a member of the Piperraceae family (Dodson, et al., 2000), grows and fruits in abundance in Essien Udim Local Government Area, Akwa Ibom State, Nigeria. It is used in small quantities for flavour in foods and medicinal purposes, the excess post harvest is usually wasted since new stock come to meet the previous season' stock. Adgeh, 1989, Gbenwonyo et. al., 1993 Su and Hovart, 1981) suggests that amide olifinic, or alkyl isobutylamines compounds (piperine, tricostacine, peepulidin, piplartin and trichonine are responsible for the insecticidal effect of the plant product.

At the rural level, pulverized seed of Piper guineense is extracted with cold solvents like ethanol, methylated spirit and acetone; the extracts are diluted with hot water and used in dressing the maize before storage.

This work was done to investigate the insecticidal potency of cold and hot acetone extracts of Piper guineense on soft maize using the mixture experimental design of the response surface methodology (RSM), to optimize formulation of potent bioinsecticide. This work would point at the proper utilization of the wasted plant in Nigeria and save resources and the environment from chemical degradation.

Materials and methods

Piper guineense fruit was obtained from Ikot Ata Enin, Essien Udim Local Government Area, young male and female weevils were obtained from Akwa Ibom State Agricultural Development Programme (AKADEP) Office, Ikot Ekpene, technical grade acetone was obtained from MacEma Scientific shop, Ikot Ekpene, all in Nigeria.

Preparation of plant product extracts

P. guineense was soaked and bruised between the palms to remove the berries, the seeds were separated from the fruit and dried, blended with Super-Master food blender (No.1, Japan) to pass through 300[micro]m sieve. The granulated plant product was divided into 3 groups. Each group was extracted with acetone under reflux for 4 hours at three temperatures (30[degrees]C, 50[degrees]C, 60[degrees]C) and named P1, P2 and P3 respectively, with reflux system (Model No. 1220, Germany). The extracts were stored in different 100ml capacity bottles for use.

Potency test

Young weevils were introduced into 14 Petri dishes (totaling 72 in triplicates) containing 100 grains of disinfected (soft) local maize and stored in a laboratory microclimate environment with average temperature of about 29 C and relative humidity of about 70%. The Petri dishes were inoculated according to the experimental design in o Table 1.

Preparation of the plant product blends

The blends of the plant products were obtained according the formulation plan in Table 2, ten (10) blends in all were obtained from the arrangement--pure, binary and tertiary blends.

Ten (10) weevil eggs were introduced into the Petri dishes which contained the local maize grains measured volumes of the extracts w e re introduced into each of the plates according to the experimental plan in Table 2. The plates were covered with porous material, each run of the experiments was done in triplicate and set aside in the laboratory. After 46 days, the theoretical life-cycle of the weevil, the Petri dishes were opened, number of dead insects (Y1) and percentage of completely damaged grains (Y2) were recorded. Failure of a probed insect to move indicated death, while grains that had lost the plumule were considered totally damaged.

Data were subjected to analysis of variance (ANOVA), multiple regression analysis and RSM, optimization analysis.

Data collected were subjected to analysis of variance (ANOVA), multiple regression analysis and RSM plots.

Theory of the experimental design

Simplex-centroid design (Scheffe, 1963) was used for the experiment, it was augmented with axial check blends duplicated and overall centroid replicated 3 times. Layout of the three blends of the design is shown in Table 1.

From Table 1 the constraints on the levels of the primary components in the designs are related with equations 1a, b and c of the plant products in the blends of the insecticides.

0% (0ml) [less than or equal to] [X.sub.1])P1 [less than or equal to] 1%(ml) ... (1a) 0% (0ml) [less than or equal to] [X.sub.2])P2 [less than or equal to] 1%(ml) ... (b) 0% (0ml) [less than or equal to] [X.sub.3])P3 [less than or equal to] 1%(ml) ... (c)

That is

P1([X.sub.1]) + P2([X.sub.2]) + P3([X.sub.3]) = 1 or 100% ... (d)

of the mixture.

It was assumed that a mathematical function in equation 2 existed for each response variable, [Y.sub.k] in terms of the 3 components variables

[Y.sub.i] = [b.sub.1][X.sub.1] + [b.sub.2][X.sub.2] + [b.sub.3][X.sub.3] + [b.sub.1][X.sup.2.sub.1] + ... ... [X.sub.n]

Where Y is a dependent variable, [b.sub.i], [b.sub.ii] and [b.sub.ij] are linear, quadratic and interactive effects of the independent variables respectively. A 3-dimentional surface and contour plots were drawn to illustrate interactive effects of the factors on the dependent variables, ANOVA determined significant effect of the components all at a significant levels of 0.05. Design-Expert 7.1.1 Software package (State-ease Corp., Minneapolis, Minn; USA) was used to generate designs to fit response surface model to the experimental data and drawn response surface plots. The result of the analysis of variance (F-test) for the dependent variable and their correspondence coefficient of determination ([R.sup.2]) was obtained by fitting experimental data to second-order response model. 2

Simplex centroid is chosen for this work since it uses all possible blends of the 3 components for {3,3} design. Table 1 shows 14 different runs, the design points are blending coordinates such that effect of all combinations of factor levels are tested with the sum of each mixture runs equal 1 or 100% while the components levels are proportions and not real quantities.

Results and discussion

From Table 3, model for number of dead insects is significant (p<0.05), the coefficient of estimates of the three extracts are positive indicating synergism increasing in value with temperature, the linear effect overall was also significant (p<<0.05). Cross-product effect was significant (p<0.05) with a significant lack of fit (0.9249), [R.sup.2] of 0.6870 shows a weak linear relationship. Figure 2 shows the same trend.

[FIGURE 2 OMITTED]

Model for percentage grain damage was significant (p<0.05), linear, cross-product, effect were significant p<0.05), the coefficient of estimates for pure blends were positive while the cross products effect showed negative values of antagonism, the [R.sup.] of 0.7646 was significant for good estimation. Figure 3 confirms this trend.

[FIGURE 3 OMITTED]

The study shows that individual blends of the plant extracts were capable of inhibiting the growth and multiplication of maize weevils. The influence of temperature was obvious and suggests that the real insecticidal component would be extracted with acetone at higher temperature, hence the greater number of dead insects at the experimental run. The reduction in the coefficient of determination and cross product effect tended to be negative at the damage to grain, this may be due to the diluting effct of the two extracts.

The multiple response optimization to evaluate the overall desirability for the 2 responses is displayed in Figure 3. The analysis revealed that 0.00ml, 0.41ml and 0.51ml of P1, P2, P3 respectively producing 102.05 of dead insects and 28.68% of damaged grains at a desirability level of 100%.

The models show the relationship between the parameters and the variables, these do not suggest a final set of models for formulation of the bioinsecticides but a pointer to how it can be obtained. More work should be done on the isolation and characterization of the most active component of the plant materials.

Conclusion

The experiment showed that the potency of the plant extracts was proportional to the temperature of extraction solvent. This combination showed higher potency than single blend but all single blends showed synergism on the protection of maize. Generally, analysis of data revealed that 0.00ml, 0.41ml and 0.51ml of A, B, C respectively produced 102.05 of dead insects and 28.68% of damaged grains at a desirability level of 100% with the highest potency obtained from the highest temperature extract in single and combine blend. More work should be done on the use of blends of other plant products and solvents, their extraction methods and blending.

References

Anderson, M.J. and J.P. Whitcomb, 2004. RSM simplified: optimizing processes methods for design of experiments. Productivity press, New York.

Bondari, K., 1999. Interactions in entomology: multiple comparisons and statistical interactions in entomological experimentation. Journal of Entomological Science, 34: 57-71.

Box, G.E.P. and N.R. Draper, 1987. Empirical Model building and response surface. John Wiley & Sons, New York,

Cornelll, J.A., 1999. Experiments, mixtures, designs, models and the analysis of mixture data, 2 edition, John nd Wiley & Sons, New York.

Expert Design (2006) Response surface simplified .......

FAO/WHO (1977). Pesticide residues I food: FAO plant production and protection Paper 10 Sup.

Jacobson, M.D.K., M.M. Reed, D.S. Crystal, Monreno and E.L. Sodastorm, 1978. Chemistry and biological activity of insect feeding deterents. Entomologia Exp. Appl., 24: 248-257.

Jimenez, A., F. Romojaro, J.M. Gomez, M.R. Lianos and F. Sevilla, 2003. Antioxidant systems and their relationship with the response of pepper fruits to storage at 20 C. Agric. Food Chem., 51(21): 6293-9. o

Ojimelukwe, P.C., 2002. Potentials of Xylopia aethopica for short term protection of cowpea (var. IT-81D-975) seeds in Nigeria. Nigerian Agric. Journal, 31: 39-48.

Olatunde, A.F., 1989. Maize utilization and nutrition: In Food crop production, utilization and nutrition. (eds. B.N. Mbah, and D.O. Nnanyelugo) Department of Home Sciences and Nutrition of Nigeria, Nsukka. pp: 96-110.

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Scheffe, H., 1963. Simplex lattice design for experiment with mixture. Journal of Royal Statistical Society, Series B, 28: 235-263.

Schmitterer, H. and K.R.S. Ascher, 1987. Natural pesticides from the neem trees A indica, A. Juss. and other tropical plants. Proc. 2nd Int. Neem Conf; Rauischholzhausen, 25-28 May 1983. GT2, Eschborn; 587.

Corresponding Auhtor: P.G. Udofia, Department of Food Science and Technology, Akwa Ibom State Polytechnic, P. O. Box 1121, Ikot Ekpene, Akwa Ibom State, Nigeria E-mail: paddofff@yahoo.com

(1) P.G. Udofia, (1) P.J. Udoudoh, (2) A.A.Okon and (3) M.L. Ekanem

(1) Department of Food Science and Technology, Akwa Ibom State Polytechnic, Ikot Ekpene, Nigeria (2) Department of food Science and Technology, University of Uyo, Akwa Ibom State, Nigeria (3) Department of Agriculture and Nutrition, College of Agriculture,Obio Akpa, Abak, Akwa Ibom State, Nigeria.

P.G. Udofia, P.J. Udoudoh, A.A. Okon and M.L. Ekanem: Synergistic Effect of Temperature of Acetone Extraction of Piper Guineense on Maize Weevil (Stitophylus zea mays) by Mixture Experimental Design: Adv. in Nat. Appl. Sci., 2(2): 43-48, 2008
Table 1: Specification of primary components

 Codes and real values of primary components

 Units Lower (real) Upper (real)

P1 (X1) ml 0 1
P2 (X2) ml 0 1
P3 (X3) ml 0 1

P1 = P. guineense extracted at 30 [degrees]C, P2 at 50 [degrees]C,
P3 at 70 [degrees]C

Table 2: Experimental layout and results from a mixture design

Std Run P1 P2 P3 No. of % grain
 dead damage
 insects

5 1 0.50 0.00 0.50 71 39
3 2 0.00 0.00 1.00 88 49
9 3 0.17 0.67 0.17 77 38
12 4 0.00 1.00 0.00 63 84
6 5 0.00 0.50 0.50 96 32
14 6 0.50 0.50 0.00 68 72
13 7 0.00 0.00 1.00 59 80
10 8 0.17 0.17 0.67 95 31
8 9 0.67 0.17 0.17 62 79
4 10 0.50 0.50 0.00 60 75
1 11 1.00 0.00 0.00 52 89
2 12 0.00 1.00 0.00 75 53
7 13 0.33 0.33 0.33 87 45
11 14 1.00 0.00 0.00 54 90

Experimental setup

Table 3: ANOVA, regression analysis and coefficients of the parameters

 [F.sub.(0.05)] [P.sub.(0.05)] Coef. Estimate

 Dead insects

Models 7.32 0.070

VariablesLinear

P1 56.15

P2 65.05

P3 77.00

Linear mixture 7.32 0.0070

Cross product

P1P3 10.26 0.0094 124.04

P2P3

Parameters

Lack of fit 0.27 0.9249

Mean 71.21

[R.sup.2] 0.6870

Adj. [R.sup.2] 0.5931

 [F.sub.(0.05)] [P.sub.(0.05)] Coef. Estimate

 % of damaged grains

Models 7.31 0.0066

VariablesLinear

P1 90.62

P2 65.10

P3 63.37

Linear mixture 6.90 0.021

Cross product

P1P3 8.33 0.0180 133.56

P2P3 6.91 0.0274 146.70

Parameters

Lack of fit 0.44 0.8023

Mean 61.14

[R.sup.2] 0.7646

Adj. [R.sup.2] 61.14
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Title Annotation:Original Article
Author:Udofia, P.G.; Udoudoh, P.J.; Okon, A.A.; Ekanem, M.L.
Publication:Advances in Natural and Applied Sciences
Article Type:Report
Date:May 1, 2008
Words:2465
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