MATERIALS AND METHODS

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1 CHAPTER-III MATERIALS AND METHODS Science is a body of knowledge which consists mainly of systematic observation, classification and interpretation of data. Careful and accurate classification of facts and their observations and discovery of scientific laws by creative imagination and self- criticism are the ways to arrive at final conclusions. These conclusions should closely resemble the functioning of real world situation and provide clues to understand the principles underlying functioning of human behavior. It is; therefore, essential to follow the scientific procedure, especially in an empirical study, to ensure the validity and acceptability of the results/findings. This is only possible if one follows a sound methodological procedure to conduct the study. This chapter has been devoted to discuss the methodology followed to select the sample households and different statistical tools employed to accomplish the objectives of study. Selection of study area Out of 12 districts of the state of Himachal Pradesh, two districts namely Kullu and Shimla were purposively selected for the study (Fig. 3.1 and Fig 3.2). The selection of the districts was influenced by two factors. First, in these districts the cultivation of high value crops namely apple and off- seasonal vegetable is being practiced since the late sixties and early seventies. Second, these two districts together account for more than three-fourths of the total area under fruits and more than two-thirds of the total fruit production.

2 Fig. 3.1 Map of study area Kullu, District Kullu (Himachal Pradesh) Fig. 3.2 Map of study area Theog, District Shimla (Himachal Pradesh)

3 Sampling design: Two blocks namely, Kullu block in Kullu district and Theog block in Shimla district were purposively selected for the study. Thereafter, a list of panchayats falling in each of the two selected blocks was prepared. At the first stage of the sampling, one panchayat from each of the two blocks was randomly selected. The selected panchayats were Jallugran from Kullu block and Matiyana from Theog block. In the next stage of sample selection, the list of the villages falling in each of the two panchayats was prepared. Thereafter, 50 per cent of the villages were selected randomly in each of the panchayats. The list of the selected blocks, panchayats and villages is given in Table 3.1. Himachal Pradesh District Kullu District Shimla Kullu Block Theog Block Jallugran panchayat Matiyana panchayat No. of Villages =11 No of Villages = Households Households Fig. 3.3 Sampling plan

4 Table 3.1 List of the selected Blocks, Panchayats and Villages Blocks Panchayat Village No. of villages Kullu Jallugran Rumus, Preyee, Kapri, Diyanthala, 11 Jallugran, Tungadhar, Hesirashoran, Nakadhar, Sharani, Tapruwai, Seruthana Theog Matiyana Kalinda, Taleen, Kalag, Bharmali, Kouthu, Kalzar, Pajeli, Sungra, Kajiwal, Mulyana, Mul matiyana, Katog, Sonarghati, Teer, 20 Nanni, Sunthi, Katehr, Rauni, Kui, Dharaman Selection of sample households: In each of the two panchayats, hundred households were allocated among the selected villages through a proportional allocation method. Further for the collection of the village level data, one key informant was selected from the each of the sample village in both the panchayats. Thus, the total sample consists of 200 households, 100 from each panchayat, and 31 key informants, 11 from Jallugran and 20 from Matiyana. The complete sampling plan has been given in Fig 3.3. Stratification of sample households: For the construction of strata, cumulative square root frequency method was used (Singh and Mangat, 1995). The detailed procedure is given in Table 3.2. The households were divided into two strata: a+ b+ + m First Strata: = = X (Say ) 2 X lies in between Class interval in class E. Second Strata: The remaining households fall in the second strata

5 Table 3.2 method Class No. Stratification of households using cumulative cube root frequency Class Interval (Bigha) Frequency (n) n Cumulative square root Frequency Strata A 1 to 5 a a a Ist Strata B 6 to 10 b b a+ b C 11 to 15 c c a+ b+ c D d d a+ b+ c+ d E e e a+ b+ c+ d+ e F f f a+..+ f IInd Strata G g g a+..+ g H h h a+..+ h I i i a+..+ i J j j a+..+ j K k k a+..+ k L l l a+..+ l M m m a+..+ m The classification of sample households into different categories viz. small and large, as obtained from the above table, and their number in respective category and the basis for classification is presented in the Table 3.3. Table 3.3 Farm size (ha.) category of sample households Category Land holding Block and Sample size (ha.) Kullu Theog Total Small Up to Large > Total The small farmers were those who had land upto 2.08 ha and the large farmers having land more than 2.08 ha. Data collection The study is based both on primary and secondary data. The primary data were collected from the sample households using a pre-tested schedule through a personal interview method for the agricultural year The data were

6 collected on the following aspects : family size, educational status of the family, land holding size, land utilization pattern, cropping pattern, farm inputs and prices; pesticide exposure; farmers and family characteristics and other variables affecting health; symptoms due to prolonged exposure to pesticides; medicinal history and expenditures incurred in treating the illness of farmers particularly impacts caused by use of pesticide; farmers awareness of the change in health condition due to greater or prolonged use of pesticide; farm outputs and prices; and income from the farm etc. In addition the height and weight of the person in a household who was doing spray for most of the time and for the last many years was also recorded to construct Body Mass Index (BMI). The secondary data were collected from the Statistical outline of Himachal Pradesh, on demographic features of the study area. Methods of analysis: The following different methods were used to analyze the data: Tabular analysis: Tabular method was employed to present the results of the study. Cost and returns analysis: The cost and returns have been worked out following farm management cost concepts like Cost A 1, cost A 2, cost C 1, Cost C 2 and Cost D. The definitions of these concepts have been explained below. Cost A 1 : 1. Value of human labour 2. Value of Bullock labour 3. Value of seed 4. Value of manure

7 5. Value of fertilizer 6. Value of chemicals 7. Machinery 8. Depreciation of farm equipment, calculated as 10 per cent of total value of farm equipment, annually 9. Irrigation charges 10. Land revenue 11. Interest on working capital for half of the growth period of the crop. Cost A 2 : A 1 + Rent paid for leased-in land. Cost B 1 : Cost A 1 + imputed interest on owned fixed capital (excluding land). Cost B 2 : Cost A2 + imputed rental value of owned land (less land revenue) + imputed interest on owned fixed capital (excluding land). Cost C 1 : Cost C 2 : Cost D: Cost B 1 + imputed value of family labour. Cost B 2 + imputed value of family labour. C per cent of cost C 2 (management charges). The net returns from different crops were estimated over different costs. The calculations have been made on per hectare basis. The details of procedure followed to compute the returns are explained below. The net returns of the crop were calculated by using following method. NR = GR Costs Where, NR = Net return over cost GR = Y M P M + Y B P B Where, GR = Gross returns per hectare of the crop

8 Y M = Yield level of the main product of the crop P M = Price per quintal of the main product of the crop Y B = Yield level of the by-product of the crop P B = Price level of the by-product of the crop P B = Price per quintal of the by-product of the crop and different costs over which net returns have been worked out and it include Cost A 1, Cost A 2, Cost B 1, Cost B 2,Cost C 1 and Cost C 2 and Cost D. The profitability of fruit crops like apple, which is a perennial crop, has been computed by following the most commonly used approach i.e. by analyzing the cross sectional data on the value of inputs and outputs for different age groups of apple plantations. Standard project worth measures like net present value (NPV), benefit cost ratio (BCR) and internal rate of return (IRR) have been computed to work out the financial viability of apple plantation (Gittinger, 1976). n Bt t t 1 (1 i) Benefit cost ratio = ; n Ct t (1 i t 1 )

9 n Bt Ct t t 1 (1 i) Net present value = ; n Ct t (1 i t 1 ) n Bt Ct t t 1 (1 i) Internal rate of return = = 0; n Ct t (1 i t 1 ) Where B t = returns in each year; C t = costs in each year; i = the discount rate; t = 1, 2, -----, n and n= number of years Functional analysis: The logit regression was used to quantify the probability of different factors affecting human health in terms of body mass index being not normal. The following form of the model was used:

10 Log 1 p p b 0 n j 1 b j x j u Where p = is the probability of the body mass index being not normal; xj denotes the independent variables like the age of the respondents, education, number of years since spraying, number of sprays, Integrated Pest Management, use of protective equipments and having clinic access. Collection and preparation of soil samples: The soil samples were separately collected from the cultivated area of each of the 200 sample households. Since apple was the most important crop in Kullu and vegetables in Theog, the soil samples were collected from apple orchards in Kullu and vegetable fields in Theog. The representative soil samples were collected from 0-15 cm depth and tested under laboratory conditions. The samples were analyzed for soil P H (Jackson, 1967), Organic carbon (Walkley and Black, 1934), available P (Olsen et al., 1954), available K (Mervin and Peech, 1951) and micro nutrient cations (Cu, Fe, Mn and Zn by Lindsay and Norvell, 1978). The following formula was used to classify the soils into different status: Overall Status of soil= (l*1+m*2+h*3)/100 The values used to classify the soils into low, medium and high through soil nutrient index are given below. Low < 1.67, Medium 1.67 to2.33 and high >2.33 (Muhr et al. 1963).

11 The status of the availability of micro nutrients was considered sufficient if the availability was more than the following critical limits in mg per kilogram. If availability was less than these limits, the status was considered as deficient (Nayyar,and Chhibba, 1995). Zinc = 0.60 Copper = 0.20 Iron = 4.50 Manganese = 1.00 Valuation of environmental cost Environmental cost has been defined to include the cost of the effect on human health and soil degradation. The effect on human health is estimated to include the number of days lost, the loss in the work efficiency for those who experienced some health problems but did not take medicines, the yearly medical expenditure of the person who handled the pesticides and the value of kit. For computing monetary value of the degradation of soil health, the soil status was compared with the recommended doses in the packages of practices of horticulture and vegetable crops. If the status of a particular nutrient in the soil was high, then recommended dose, given in the package of practices, was reduced by 25 per cent. In case of medium status, the recommend was the same as given in the package of practices. If the status of a particular nutrient was low, 25 per cent was added to the recommended dose. These doses were now considered as optimum doses for a

12 particular nutrient. Thereafter, actual dose used by the farmer was compared with the recommended dose. The difference for different nutrients from their recommended doses could either be excess or deficit. The excess or deficit amount then was converted into monetary value by multiplying the price of a particular nutrient with the excess or deficit amount. The total environmental cost then was apportioned among different crops in proportion to the area under these crops. As mentioned above, all the soil samples in Theog were collected from the area under vegetable crops. Therefore, the environmental cost in Theog was apportioned only among vegetable crops.