International Research Journal of Applied and Basic Sciences © 2012 Available online at www.irjabs.com ISSN 2251-838X / Vol, 3 (S): 2829-2833 Science Explorer Publications

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Factors Influencing on Attitude of Vine Owner of Iran toward Integrated Pest Management (IPM)

Gholamreza Dinpanah, Marjan Naji

1. Agricultural Extension & Education Department, Islamic Azad University, Sari Branch, Sari, Iran 2. Address: Marzdaran Blvd., Sadeghieh Sq.,Postal code 1464743864, Tehran, Iran

Corresponding Author email: Dinpanah@iausari.ac.ir

ABSTRACT: The present survey studies the factors influence on attitude of Vine owner of Iran toward integrated pest management. The study is of descriptive-correlative type. Statistical population includes 6500 vine owners of Iran that 285 numbers of were selected sample in randomize. To determine validity of questionnaires, the ideas of agricultural development professors, researchers, and experts were applied, and their reliability was over 0.83 through Cronbach Alpha coefficient. The results showed that 7.2%, 17.5% and 75.3%of vine owners had attitude of low, moderate, high toward IPM respectively. The results of multi variable regression revealed that variable of the effect of education-extension activities explained 49.8% of attitude changes toward IPM. Key words: Vine Owner, Attitude, Integrated Pest Management (IPM)

INTRODUCTION

Pesticides have Longley been integral parts of modern agriculture; however, the results of recent research show that the residue of such pesticides in agricultural products can endanger consumers’ health. Based on WHO report, about 200000 individuals die every due to pesticide consumption. This is one of modern societies’ concerns and the reason that developing countries intend to replace other ways of eliminating pests and produce healthy products (Tofiqi, 2010). Integrated pest management (IPM) involves choosing appropriate tactics from a range of pest control techniques including biological, cultural and chemical methods to suit individual cropping systems, pest complexes and local environments (Tang et al, 2010) IPM is an ecological strategy mainly based on natural control factors such as natural enemies. It looks for those controlling tactics that cause the least possible disorder in production factors. IPM uses pesticides only after continuous tracing of pests and natural control factors acknowledge the necessity for pesticides (Talebei Chaychi and Khoramshahi, 1997). IPM seems to be a solution to achieve durable agricultural production with the least damage to environment. In fact, there is no particular definition for IPM, but it generally refers to a variety of strategies to manage insects and keep them under damage threshold. It also contains usage of controlling functions ranging from agricultural to chemical activities (Bakhshi and Rejaul, 2005). The main IPM factor is controlling pests and diseases level and the least usage of pesticides (only in case of need). IPM indeed reduces expenses related to pesticides and saves time through hiring skillful work force that control pests and diseases (Bekman, 2006). IPM can reduce environmental concerns and probable damages to wheat quality in related warehouses. However, managers of many wheat warehouses in the U.S apply chemicals-based methods. To determine economical reasonability of this option, the whole expenses (including execution and failure in controlling insects) were investigated and the results showed that high rate of health, reduced sampling charges, and wheat storage for shorter period may make IPM method economical in wheat warehoused (Adam et al, 2010). Two surveys were done in EU with the focus on 4 areas. Experts were requested to identify pruning time in their own areas, find the present measures to save products, and suggest advanced measures to fight with main pests. Weed and diseases, and evaluate ambient, economic, and social influence of creative IPM means. The results showed that deviation among areas was mainly due to differences in evaluating economic or social effect of

Intl. Res. J. Appl. Basic. Sci. Vol., 3 (S), 2829-2833, 2012

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some means. Applied surveys and farmers’ motivation to promote usage of modern IPM methods are essential in stable development in Europe (Vasileidis et al, 2011). Consumer’s awareness of pesticides and fertilizers contamination, and ecosystem concerns and danger has led to a wide range of requests to produce healthy and organic agricultural products. It is now very common among consumers to have coreless fruits (because of high rate of valuable anti oxidants). Such a survey done in Portugal evaluated the effect of applying fertilizers and applying IPM among farmers, and revealed that strawberries having been produced by IPM have higher anti oxidant activities than the one with fertilizers (Fernandes et al, 2012). In 2 areas in Brazil, five experiments were done on soya aiming at evaluation of prohibiting usage of insecticides (PUI) and in comparison with IPM and Biological Controlling (BC) strategies. The results of such experiments showed that PUI on soya doesn’t lead to higher productivity in farms and this measure only needs high rate of pesticides which may under rate the stability of soya. Therefore, applying IPM is till the best way to control and manage pests in soya farms (Bueno et al, 2011). A discussion of IPM revealed that the cotton industry in Australia is well positioned to support and further develop IPM in cotton, especially given its policy to develop Best Management Practice (BMP). However, differences in interpretive knowledge by the stakeholders appeared to be inhibiting the development of mirid IPM. This common problem in multi-disciplined groups may account for the reluctance of pest managers to adjust their mirid threshold in respect to sampling method (Whitehouse, 2011)

MATERIALS AND METHODS Here, descriptive-correlative method is used, because it defines variables and also determines the rate and the type of relation between dependent and independent variables. The statistical population of this research includes 6500 vine owners in Iran. The sampling method is simple and random through Cochran formula (n=285). To determine the validity of questionnaires, a few copies were given to professors and experts in Agricultural Organization, and the preliminary testing was done to find the reliability of research instruments and the variance for sampling. In this test, the stated questionnaires were handed out among 25 vine owners who were similar to the statistical sample in view of climate, geography, culture and society. After gaining data, alpha Cronbach coefficient was found for all variables with 0.83 Scale.

Table 1.reliability coefficient of variables Variables Number of question Cronbach α

Social participation 8 0.83 attitude toward IPM 5 0.79 Ecological characteristics 8 0.81 innovation characteristics 15 0.89 extension-communication characteristics 11 0.83

RESULTS AND DISCUSSIONS

Attitude toward IPM Attitude toward IPM was measured by 5 questions with Likert 5-choice range. The said range is scored as follows: Strongly disagree -1, Disagree -2, Neither agree nor disagree -3, Agree -4, Strongly agree -5. Therefore, maximum and minimum score of Attitude toward IPM was 25 and 5 respectively. Table 2 shows the responders’ attitudinal situation toward IPM. According to the table, 7.2%, 17.5% and 75.3% of responders have had bad, middle and good attitude towards IPM. The average amount of attitude toward IPM is 18.6 and standard deviation is 4.2.

Table 2. Attitudinal situation toward IPM Attitudinal situation Frequency % Frequency % Cumulative frequency

Very bad(5-8) 13 4.6 4.6 Bad (9-12) 7 2.6 7.1 Middle (13-16) 49 17.5 24.6 Good (17-20) 156 55.7 80.4 Excellent (21-25) 55 19.6 100 Total 280 100 �

M = 18.6 SD= 4.2

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Studying the relationship between personal, social, economic, extension-knowledge, communicative and innovative characteristics of vine owners and attitude toward IPM

Table 3 shows the amount, intensity and direction of relation and a meaningful level between the personal, social, economic, extension-knowledge, communicative and innovative characteristics of vine owners and attitude toward IPM. As the table indicates, there is a negative and meaningful relation between age and the agriculture background, vine production expense with the attitude toward IPM in 0.01% confidence level. As well, there is a positive and meaningful relation between level of education, vine product yield, educational-extension activities effect, vine owners technical knowledge, social participation, relative advantage, adaptability, testability, visibility, and complexity of IPM innovations with the attitude toward IPM are in the level of 0.01 and there is a positive and meaningful relation between Social impressiveness and attitude toward IPM in the level of 0.05.

Table 3. The relationship between research variables and attitude toward IPM Variables r p

Age -0.170** 0.005 Experience of farming -0.191** 0.001 Education level 0.346** 0.000 Agricultural area land 0.019 0.760 Vine farmed area 0.112 0.065 Vine production expense -0.491** 0.000 Vine product yield 0.414** 0.000 Educational-extension activities effect 0.697** 0.000 Vine owners technical knowledge 0.226** 0.000 Social impressiveness 0.142* 0.018 Social participation 0.495** 0.000 Relative advantage 0435** 0.000 Adaptability 0.542** 0.000 Trial ability 0.419** 0.000 Visibility 0.325** 0.000 Complexity 0.676** 0.000 Using information resources 0.481** 0.000

**p<0.01 *p<0.05

The influence of personal, social, economic, extension-knowledge, communicative and innovative characteristics of vine owners on attitude toward IPM

We use the step by step regression in order to anticipate the influence of the personal, social, economic,

extension-knowledge, communicative and innovative characteristics on attitude toward IPM. This analysis has got nine steps as following:

First step: In the first step of regression analysis, the variable of educational-extension activities effect was placed in the equation. The amount of multiple correlation (R) and determination coefficients (R

2) was equal to

0.706 and 0.498 respectively. It means that 49.8% of changes in attitude toward IPM are explained by this variable. Second step: In the second step of regression analysis, the variable of the experience of farming entered

to the equation. This variable increased the amount of multiple correlation (R) and determination (R2) coefficients to

0.744 and 0.554 respectively. It means that 5.6% of changes in attitude toward IPM are explained by this variable. The third step: In the third step of regression analysis, the variable of trial ability entered to the equation.

This variable increased the amount of multiple correlation (R) and determination (R2) coefficients to 0.766 and

0.587 respectively. It means that 3.3% of changes in attitude toward IPM are explained by this variable. The fourth step: In the fourth step of regression analysis, the variable of complexity entered to the

equation. This variable increased the amount of multiple correlation (R) and determination (R2) coefficients to 0.807

and 0.651 respectively. It means that 6.4% of changes in attitude toward IPM are explained by this variable. The fifth step: In the fifth step of regression analysis, the variable of visibility entered to the equation. This

variable increased the amount of multiple correlation (R) and determination (R2) coefficients to 0.826 and 0.682

respectively. It means that 3.2% of changes in attitude toward IPM are explained by this variable. The sixth step: In the sixth step of regression analysis, the variable of adaptability entered to the equation.

This variable increased the amount of multiple correlation (R) and determination (R2) coefficients to 0.838 and

0.702 respectively. It means that 1.9% of changes in attitude toward IPM are explained by this variable.

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The seventh step: In the seventh step of regression analysis, the variable of vine product yield was placed in the equation. This variable increased the amount of multiple correlation (R) and determination (R

2) coefficients to

0.844 and 0.712 respectively. It means that 1% of changes in attitude toward IPM are explained by this variable. The eighth step: In the eighth step of regression analysis, the variable of vine farmed area entered to the

equation. This variable increased the amount of multiple correlation (R) and determination (R2) coefficients to

0.847 and 0.718 respectively. It means that 0.6% of changes in attitude toward IPM are explained by this variable. The ninth step: In the ninth step of regression analysis, the variable of relative advantage entered to the

equation. This variable increased the amount of multiple correlation (R) and determination (R2) coefficients to

0.851 and 0.724 respectively. It means that 0.6% of changes in attitude toward IPM are explained by this variable. Totally, the nine mentioned variables define 72.4% of changes in attitude toward IPM.

Table 6. the coefficients of determination of the influential variables on the attitude toward IPM

step Variable

R R

2

1 Educational-extension activities effect 0.706 0.498 2 Experience of farming 0.744 0.554 3 Trial ability 0.766 0.587 4 Complexity 0.807 0.651 5 Visibility 0.826 0.682 6 Adaptability 0.838 0.702 7 Vine product yield 0.844 0.712 8 Vine farmed area 0.847 0.718 9 Relative advantage 0.851 0.724

Table 7. the step-by-step regression in order to define the influence of the vines ’ characteristics on the attitude toward IPM Variable B Beta t Sig

constant 3.61 � 4.17 0.000 Educational-extension activities effect(x1) 0.186 0.598 7.59 0.000 Experience of farming(x2) -0.087 -0.147 3.70 0.000 Trial ability(x3) 1.36 0.612 9.24 0.000 Complexity(x4) 0.399 0.340 5.49 0.000 Visibility(x5) 0.454 0.200 4.61 0.000 Adaptability(x6) 0.267 0.180 3.34 0.001 Vine product yield(x7) 0.266 0.183 3.80 0.000 Vine farmed area(x8) 0.211 0.0107 2.48 0.014 Relative advantage(x9) 0.137 0.110 2.18 0.030

F=65.03 Sig=0.000

R=0.851 R2=0.724

Y=3.61+0.186X1-0.087X2+1.36X3+0.399X4+0.545X5+0.267X6 +0.266X7 + 0.211X8+0.137X9

CONCLUSION Among the mentioned characteristics personal, age and experience of farming has got a negative and meaningful relationship with attitude toward IPM, or the younger and less experienced farmers have got better attitude toward IPM. The amount of these correlations regarding age and experience of farming is 0.17 and 0.19 respectively which are in the average and low level. There is a positive and meaningful relationship between the education level and attitude toward IPM or more literate farmers have got better attitude toward IPM which this correlation is at the moderate level (0.35). Among the economical characteristics, vine production expense have got negative and meaningful relation with attitude toward IPM, or the farmers with the less cost have got better attitude toward IPM which these correlations are in the moderate levels. Also between vines product yield have got positive and meaningful relation with attitude toward IPM, or more production farmers have got better attitude toward IPM which this correlation is at the moderate level (0.41).

Among the social characteristics, social impressiveness and social participation have got positive and meaningful relation with attitude toward IPM, or the farmers with more social permeability and participation have got better attitude toward IPM The amount of these correlations regarding social impressiveness and social participation is 0.14 and 0.5 respectively which are in the average and low and high level respectively.

Among the extension-knowledge characteristics, vine owners technical knowledge and effect of extension activities have got positive and meaningful relation with attitude toward IPM, or the farmers that have technical

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knowledge and participated in extension coerces have got better attitude toward IPM. The amount of these correlations regarding technical knowledge and effect of extension activities is 0.23 and 0.69 respectively which are in the average and low and high level respectively.

Among the communicative and innovative characteristics, the usage amount of informative resources, relative advantage, adaptability, testability, visibility, and complexity of IPM innovations have got positive and meaningful relation with attitude toward IPM, or the farmers that use informative resources and have innovator have got better attitude toward IPM. The amount of these correlations regarding informative resources, relative advantage, adaptability, testability, visibility, and complexity is 0.48, 0.43, 0.54, 0.42, 0.32 and 0.68 respectively which are high level.

The results of step by step regression depicts that the variables of educational-extension activities effect, experience of farming, trial ability, complexity, visibility, adaptability, vine product yield, vine farmed area and relative advantage entered the regression equation which finally defines 72.4% of changes in attitude toward IPM. It should be mentioned that about 50% of changes in attitude about IPM are explained by the variable of educational-extension activities effect.

Recommendations 1- It is recommended to employ younger and more literate farmers and start with more yields. 2- It is recommended to use the informative resources and develop the training-extension programs in order

to modify the attitude toward IPM. 3- It is recommended to improve farmer's participation and social permeability in order to increase the

attitude toward IPM. 4- It is recommended to improve innovation characteristic of IPM and increase farmers' knowledge technical.

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