M.Baskar, H.Gopal, M.Sheik Dawood and M.Subash Chandra Bose

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Scandaliaris, J., Dantur, C. and Roncedo, M. (1987). Effect of vinase on sugarcane yields and soil properties. Revista Industrial Agricola de Tucuman. 64: 1-44. Somashekar, R.K., Gowda, M.T.G., Shettigar, S.L.N. and Srinath,K.P. (1984) Effect of industrial effluents on crop plants. Indian J. Environ. Hith. 26: 36 - 146. Subash

Chandra Bose, M., Baskar, M., Gopal. H., Kayalvizhi,C., Sivanantham, M. and Ravindran, K. (2002) Utilisation of distillery effluent in coastal sandy soil to improve soil fertility and yield of sugarcane.World Congress on Soil Science, 14-21 August 2002, Bangkok,Thailand: 1980(1 -8)

Sweeney, D.W. and Graetzm, D.A. (1991). Application of distillery waste anaerobic digester effluent to St., Augustine graa. Agriculture, Ecosystems and Environment. 33: 341 -3 51. Thiyagarajan, T.M. (2001). Use of distillery effluents in agriculture: problems and perspectives. In: Proc. Nat. Sem. Use of Poor Qualitv Water and Sugar Industrial Effluents in Agriculture. Feb. 5th,2001. AC & RI, Trichy. pp.:1-19. Usher, J.F. and Wellington, I.P. (1979). The potential of distillery waste water on sugarcane and soil fertility. Proc. ABBCT, 1 : 143. Vierira,D.B. (1982). Methods of vinasse application in sugarcane. Sacchatum APC, Sao Paulo 5 : 21.26. (Received : December 2003; Revised : August 2005)

Madras Agric. J. 92 (4-6) : 354-358 April-June 2005 Research Notes

Relationship of selected traits of mango growers with adoption behaviour M.RAMASUBRAMANIAN AND M.MANOHARAN Tamil Nadu Agricultural University, Coimbatore - 641 003, Tamil Nadu.

Among the horticultural commodities mango ranks first with 42,894.93 tonnes in the form of fresh fruits, jam, jelly, squash, ketch-up and other processed products being exported worth of Rs.7,359.61 lakhs during 2002-2003. But the discouraging and disappointing scenario is the reduction in the quantity of fruits exported over-years including mango. The quantity of fruits and vegetables exported during 199192 was 4,93,611.39 tonnes which has reduced to 3,87,429.57 tonnes during 2002-2003. This reduction in productivity and export of fruits including mango is of great concern and Deeds to be addressed. The reasons that could be

attributed to this reduction may 6e many. One among that is lack of awareness and adoption of recommended technologies for mango cultivation. For achieving higher yields, farmers have to resort to scientific farming by adopting innovative and improved technologies. Rogers and Shoemaker (1971) defined adoption as the mental process through which an individual passes from first hearing about an innovation to final adoption. This adoption behaviour bound to be affected by varied characteristics of mango growers including personal, socio-economic and psychological

Relationship of selected traits of mango growers with adoption behaviour

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Table 1. Correlation and multiple regression co-efficients of characteristics of respondents with their adoption (n=120) Variable number

X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 x11 X12 X13 X14 X15 X16

Variables

Educational status Occupational status Fanning experience Farm size Information seeking behaviour Information giving behaviour Annual income Attitude towards mango cultivation Economic motivation Innovativeness Decision making pattern Market perception Market orientation Crop supervision behaviour Export orientation Perception towards value addition

R2 = 0.517

'r' value

Partial regression co-efficients

Standard error of regression

Computed ‘t’ value

0.2508** 0.1126ns 0.291** -0.0177™ -0.1275ns 0.1924** 0.0979ns -0.2437** 0.2042* 0.3479** 0.2351** 0.1834* -0.1647ns 0.2010* 0.1240™ -0.1466

0.697 0.341 0.517 1.082 -0.032 0.483 0.592 -0.367 -0.337 -1.592 -0.111 0.195 -0.724 0.989 0.249 0.214

0.101 0.221 -0.347 -1.008 -0.113 1.014 0.272 -0.246 -0.155 -0.155 0.022 0.469 -0.256 -0.213 0.069 0.061

3.462** 2.496* 3.592** 4.427** 1.039 6.163** 1.689 1.908 1.190 1.656 0.176 3.130** 2.457* 2.508* 0.661 0.586

F =6.900

** - Significant at one per cent level * - Significant at five per cent level

characteristics. Hence, it is imperative to examine the influence of these characters on the adoption behaviour of mango growers. In this context, the present study was taken up with the objective of studying the relationship and contribution of characteristics of mango growers with their adoption behaviour. The study was conducted in Srivilliputtur block of Virudhunagar district. Totally 120 mango growers were selected from six villages following the random sampling procedure. The dependent variable of adoption of improved mango cultivation practices was measured through a schedule exclusively

ns - Non-significant

constructed for the study and improved by using difficulty and discrimination index. The data were collected by means of personal interview with the help of structured interview schedule. Correlation, multiple regression and path analysis were performed to study the relationship and contribution of profile of mango growers (independent variables) with their adoption behaviour (dependent variable) respectively. From table 1, it could be seen that five variables viz., educational status (X1), farming experience (X3), information giving behaviour

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Table 2. Direct, indirect and substantial indirect effects of independent variables on adoption (n=120) Variable number X1 X2 X3 X4 X5 X6 X7 X8 X9 X10

X11 X12 X13 X14 X15 X16

Variables

Educational status Occupational status Fanning experience Farm size Information seeking behaviour Information giving behaviour Annual income Attitude towards mango cultivation Economic motivation Innovativeness Decision making pattern Market perception Market orientation Crop supervision behaviour Export orientation Perception towards value addition

Direct effect 0.4206 0.2211 -0.1468 -1.0084 -0.1132 1.0137 0.2719 -0.2457 -0.1844 0.1546 -0.0230 0.4689 -0.2559 -0.2130 0.0686 0.0614

(X6), innovativeness (X10) and decision making pattern (X11) had positive and significant association with adoption at one per cent level of probability. The variables viz., economic motivation (X9), market perception (X12) and crop supervision behaviour (X14) had also shown positive and significant association with adoption, but at five per cent level of probability. Attitude towards mango cultivation (X8) had shown a negative and significant association with adoption at one per cent of probability. The positive and significant relationship of education and farming experience with adoption is in accordance with the findings of Nirmaladevi (1997) and Murukanandan (1998). Simple correlation will explain only the type of association existing between the

Indirect effect -0.1698 -0.1085 0.4389 0.9907 -0.0143 -0.8213 -0.1740 0.0020 -0.0198 0.1933 0.2574 -0.2854 0.0911 0.0120 0.0554 -0.2080

Substantial indirect effect I

II

III

0.1625X6 0.0067X15 -0.0723X12 -0.7807X6 -0.0517X6 0.7849X4 0.1164X11 -0.0750X7 -0.0561X6 0.0206X2 -0.0020X6 0.3617X4 -0.0250X11 -0.0353X2 0.0260X9 0.0203X8

0.1341X8 0.0294X10 -0.0710X10 -0.7780X12 -0.0716X12 0.5611X12 0.0952X13 -0.0783X1 -0.0580X12 0.0233X16 -0.0022X13 0.2964X5 -0.0512X8 -0.0408X6 0.0102X16 0.0092X10

0.1168X9 0.0366X14 -0.0459X7 -0.6688X5 -0.0751X4 0.4630X5 0.0830X8 -0.0814X16 -0.0585X15 0.0316X3 -0.0095X7 0.2595X6 -0.0896X7 -0.0554X7 0.0095X12 0.0090X15

characteristics and extent of adoption. To find out relative contribution of each variable towards adoption multiple regression was carried out. The results are presented in table 1 Results indicated that co-efficients of determination (R2 values) was 0.517 which revealed that 51.7 per cent variation in adoption level was explained by the selected 16 variables. The ‘F’ value showed that the analysis was significant at one per cent level of probability. Therefore the prediction equation was fitted for adoption level of the respondents as given below. Y2 = 44.488 + 0.697** X1 + 0.341* X2 + 0.517** X3 + 1.082** X4 - 0.032 X5 + 0.483** X6 + 0.592 X7 - 0.367 X8 - 0.337 X9 - 1.592 X10 - 0.111 X11 + 0.195** X12 - 0.724* X13 + 0.989* X 14 + 0.249 X15 + 0.214 X16.

Relationship of selected traits of mango growers with adoption behaviour

Among the variables selected, the variables viz., educational status (X1), farming experience (X3), farm size (X4), information giving behaviour (X6) and market perception (X12) had shown a positive significant contribution for adoption at one per cent level of probability. The variable namely occupational status (X2) and crop supervision behaviour (X14) had shown a positive significant contribution for adoption at five per cent level of probability. Market orientation (X13) showed a negative and significant contribution for adoption at five per cent level of probability. The strength of contribution of these variables could be explained as, one unit increase ceteris paribus in educational status, occupational status, farming experience, information giving behaviour, market perception and crop supervision behaviour would bring an increase of 0.0697, 0.341, 0.517, 0.182, 0.482, 0.195 and 0.989 units in adoption behaviour of farmers respectively. One unit increase in market orientation decreased 0.724 units in adoption. Path analysis was attempted to separate the direct and indirect effects through other related variables apportioning the correlation co-efficients. The results of path analysis are presented in table 2. The results from table 2 explained that information giving behaviour, market perception and educational status had more direct effects on adoption behaviour. The variables of farm size, farming experience and decision making pattern had more indirect effect on adoption. Out of 48 substantial indirect effects studied 7 acted through information giving behaviour and showed a dominant role, 6 acted through market perception, 5 acted through annual income, 4 acted through attitude towards mango cultivation, 3 each acted through farm size, information seeking behaviour, innovativeness, export orientation and perception towards value addition, 2 each acted through occupational status, economic motivation, decision making pattern and market orientation and one each acted through educational

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status, farming experience and crop supervision behaviour. Conclusion and implications of the study In a nut shell, the following conclusions can be drawn. 1. The variables viz., educational status, farming experience, information giving behaviour, innovativeness, decision making pattern, economic motivation, market perception and crop supervision behaviour had shown positive and significant association with adoption. 2. The variables viz., educational status, farming experience, farm size, information giving behaviour, market perception, occupational status and crop supervision behaviour were the crucial and significantly contributing factors for the adoption behaviour of mango cultivators. Implications *

From the findings it could be inferred that more the educational level more will be adoption of recommended practices. Therefore the educational facilities could be strengthened in rural areas in order to increase the literacy level and to have improved farm status.

*

Economic motivation and innovativeness were found to be significant which implies that farmers are willing to take risk. If mango farmers are properly motivated they will have increased adoption level.

*

Information giving behaviour is another character which was found to be significant, which means that farmers are ready to share their ideas with their fellow farmers. So an information shop with all communication facilities in the village will be of very much helpful to the farming community.

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*

*

*

Market perception and market orientation are also found to be contributing to adoption of technologies. This indicated that if mango farmers are adequately the marketing personnel should devote more attention so that farmers could get remunerative prices for their produce. Government planning and policy making body should reorient their policies to encourage export of mango and it should assist in setting up of processing units and cold storage units. Contract farming system between farmers and exporters of fresh fruits should be encouraged and the extension efforts should be channelised in providing better expertise and education to the growers. ‘Fruit growers association’ may be encouraged based on

self help group concept so that the mango growers can reap mutual benefits. References Dahama, O.P. and O.P.Bhatnagar. (1985). Education and communication for development. Oxford and IBH Publishing Co. Pvt Ltd., Calcutta. Murukanandam, V. (1998). Knowledge level and extent of adoption of rainfed critical technologies on groundnut : A critical analysis. Unpub. M.Sc.(Ag.) Thesis, AC & RI, TNAU, Madurai. Nirmaladevi, M. (1997). Developing a strategy for guava production. Unpub. M.Sc.(Ag.) Thesis, AC & RI, TNAU, Madurai.

(Received : May 2003; Revised : December 2004)

Madras Agric. J. 92 (4-6) : 358-363 April-June 2005 Research Notes

Effect of Cow-five (Panchakavya) on brinjal pests Epilachna vigintioctopunctata Fab. and Leucinodes orbonalis Guen. E. BELINA, P. M. M. DAVID AND M. A. K. PILLAI Department of Entomology, Tamil Nadu Agricultural College and Research Institute, Killikulam, Vallanad 628252, Tamil Nadu. Everything has a tradition and agriculture is no exception. Traditional agricultural systems are finely tuned and adapted, both biologically and socially, to counter the biotic stresses. A journey into the traditional literature would reveal that man has used many age-old practices to manage insect pests and diseases of livestock, crops and human beings. Panchakavya, called here Cow-five in English, is an indigenous compound, i.e., a fermented filtrate prepared by mixing cow dung, cow urine, cow’s milk, cow’s curd and cow’s ghee (Nayagam, 2001; Vasuthevan, 2003). It is considered a growth

stimulant that increases the yield of crops (Natarajan, 2003; Somasundaram et al. 2003; Selvaraj, 2004). It is claimed to possess insecticidal principles as well (Natarajan, 2003). Hence a study was taken up to evaluate the efficacy of Cow-five against the spotted leaf beetle, Epilachna vigintioctopuctata Fab. and the shoot and fruit borer, Leucinodes orbonalis Guen. in brinjal. Cow-five preparation involved the following steps. Half-a-kg of ghee (Aavin) was first added to 5 kg of fresh cow dung and mixed well