AN EMPERICAL STUDY ON FARMER ACCEPTANCE OF SURYA RAITHA SCHEM BY GOVERNMENT OF KARNATAKA Dr.Hemanth Kumar.S 1 and Dr.Umakanth.S 2 1 Associate Professor CMS-Business School Jain University, Bangalore India 2 Associate Professor & HOD Management - CMS - Jain University Bangalore India Abstract Government of Karnataka has planned to harness Solar Energy for the benefit of the Farmer. The state government announced the launch of the ambitious suryaraitha programme. The programme will ensure solar panels are placed to generate electricity for running irrigation pump sets, and will also enable farmers to sell excess power generated to the government. In this paper an effort is made to find how suryaraitha scheme is helpful for farmers, and how effectively farmers and government can utilize this natural power. In this paper a structured questionnaire was used to collect primary data from a sample size of 210 respondents, various statistical tool such as frequency table, KMO and Bartlett s test, Communalities Test, reliability statistics, Anova, Correlation and Chi-squae. There are many advantage of this scheme from this scheme farmers can earn money. This paper has made an effort to analyze the pros and cons of suryaraitha scheme and understand farmers preferences on solar v/s electric pumps and suggest the various methods of create awareness amongst the farmer about this scheme. Keywords: - Income,Agriculture,Electricity,Farmers,Naturalpower,subsidies, Hypothesis. I. INTRODUCTION Agriculture plays a vital role in India s economy. Over 58 per cent of the rural households depend on agriculture as their principal means of livelihood. As per the 2nd advised estimates by the Central Statistics Office (CSO), the share of agriculture and allied sectors (including agriculture, livestock, forestry and fishery) is estimated to be 17.3 per cent of the Gross Value Added (GVA) during 2016-17 at 2011-12 prices. The agriculture sector in India is expected to generate better momentum in the next few years due to increased investments in agricultural infrastructure such as irrigation facilities, warehousing and cold storage. Furthermore, the growing use of genetically modified crops will likely improve the yield for Indian farmers (The Economic Survey 2016 17, Agricultural and Processed Food Products Export Development Authority (APEDA), Department of Commerce and Industry, Union Budget 2017 18, Press Information Bureau.)For the first time in India, Government of Karnataka is has planned to harness Solar Energy for the benefit of the Farmer. This scheme will ensure solar panels are placed to generate electricity for running irrigation pumpsets, and will also enable farmers to sell excess power generated to the government. The Karnataka Government s revolutionary Solar Policy, 2014-2021 under this scheme via which farmers can generate additional income from their lands, take part in the move towards green energy and also have no fear of electricity cuts. The state provides free power to the agriculture sector. As a result, the subsidy agriculture consumption has shown an increasing trend year on year. The revised solar policy 2014-21 promises solar power adoption in the industrial, commercial and residential segments for rooftop PV System. On the same line the benefit shall be extended to the farmers who are otherwise, denied of the benefits of government schemes. Solar powered irrigation system can be suitable alternative for farmers in present state energy crisis. Solar energy is generated through the year, and since farmers do not need power all 365 days, they can transmit excess power generated to the power grid. DOI:10.22623/IJAPSA.2018.4014.GOG6J Page 4
II. KARNATAKA S SMART, NEW SOLAR PUMP POLICY FOR IRRIGATION The Energy-Irrigation Nexus Solar energy, considered to be ideal for home lighting uses, has suddenly become attractive for pumping irrigation water in Karnataka. India already has some 20,000 solar irrigation pumps (SIPs) on fields; and farmers everywhere seem happy with their performance and potential (Kishore et al 2014a; Tiwary 2012). However, providing farmers the reliable energy for pumping is as much of a challenge as the availability of water. This makes SIPs important and their numbers are expected to grow at faster and exponential rates in the coming years. 2.1 Surya Raitha Karnataka s new solar pump promotion policy offers guaranteed buy-back of surplus solar power from SIP owners at an attractive feed-in Tariff, as is the case of rooftop solar generators in Germany, Japan, Italy and California. Rooftop solar generation for evacuation to the grid is rapidly emerging, and is strongly advocated in India too (Gambhir et al 2012). Surya Raitha will target several goals such as cash income for growing solar energy as a remunerative cash crop, conserve environment to a built-in incentive to conserve groundwater, enhance the quality of irrigation by giving, uninterrupted, daytime power supply, reduce the carbon footprint of groundwater irrigation by reducing the electricity and diesel using pumping water, improve finances of the power sector by providing subsidies. 2.2 Proposed Model Natural power Productivity Regulation Installation Surya Raitha Loan Figure 2. Authors Model III. RESEARCH METHODOLOGY 3.1 Statement of the problem: The state government announced the launch of the ambitious suryaraithaprogramme. In this paper an effort is made to find how suryaraitha scheme is helpful for farmers, how effectively farmers and government can utilize this natural power and to find impact and create awareness on Government of Karnataka s innovative initiative Surya Raitha scheme which addresses theissueofshortageinwaterandpowerforfarmingacross the state andaidesinincreasingtheirincomelevel and also to findwhatare the challengesanddifficulties farmers arefacingtoadoptthis scheme? 3.2 SCOPE OF THE STUDY In this study we analyze the pros and cons of SURYARAITH Ascheme and suggest the various methods to create awareness amongst the farmer about this scheme. This paper attempts to gather farmer spreferences on solar v/select ricpumps and implementation of SURYARAITH Ascheme within a geographical area. @IJAPSA-2018, All rights Reserved Page 5
3.3 OBJECTIVES OF THE STUDY a. To study the farmers requirements for power and other utilities for effective agricultural activities b. To analyze the impact of the suryaraitha scheme across the various demographic variables c. To analyze the various dimensions of surayathiascheme and its acceptance among the farmers 3.4 HYPOTHESES ANOVA Age and Dimensions of Suryaraitha Scheme H0: There is no significant difference between ages of respondents across the various dimensions of suryaitha scheme. H1: There is significant difference between ages of respondents across the various dimensions of suryaitha scheme. Income and Dimension H0: There is no significant difference between incomes of respondents across the various dimensions of suryaraitha scheme. H1: There is significant difference between incomes of respondents across the various dimensions of suryaraitha scheme. Land and Dimension H0: There is no significant difference between acres of land owned by the respondents across acceptance of various dimensions of suryaraitha scheme. H1: There is a significant difference between acres of land owned by the respondents across acceptance of various dimension of suryaraitha scheme. CHI-SQUARE TEST Hypothesis for natural power v/s loan for agriculture H0: There is no significant relationship between agriculture loan and the generation of natural power. H1: There is significant relationship between agriculture loan and the generation of natural power. Hypothesis for productivity v/s loan for agriculture H0: There is no significant relationship between agriculture loan and the generation of natural power. H1: There is significance relationship between agriculture loan and the generation of productivity. Hypothesis for regulation v/s loan for agriculture H0: There is no significance relationship between agriculture loan and the rules and regulation from government on suryaraitha scheme. H1: There is significance relationship between agriculture loan and the rules and regulation from government on suryaraitha scheme. Hypothesis for installation v/s loan for agriculture H0: There is no significance relationship between agriculture loan and the installation of suryaraitha scheme H1: There is a significance relationship between agriculture loan and the installation of suryaraitha scheme. 3.5 SAMPLING Here the sampling population is specific to agricultural farmers who had agricultural land of minimum 1 acre. Scientific sampling Technique was used to collect data for the research. As it understands the formers acceptance of the scheme it forms to be exploratory study. 3.6 DATA COLLECTION Primary data has been collected using a structured and focused questionnaire; which covered various dimensions of the research questions. While, secondary data has been collected from books, internet, literature and other relevant documents. Magazines, Journals, and Web resources, online libraries and websites are other sources. @IJAPSA-2018, All rights Reserved Page 6
3.7 DATA ANALYSIS &SOFTWARE USED. Hypothesis are made using the data and data analysis is being done using the statistical methods such as KMO measure of sampling adequacy and Bartlett s Test of Sphericity has been conducted to identify the Communalities of the item used in the variable. ANOVA analysis, which is performed to study Table 1. Age of the respondent Valid Age Frequency Percent 20-30 68 32.4 31-40 90 42.9 41-50 39 18.6 >51 13 6.2 Inference:- out of the analyzed respondents the single largest category is from the age group of 30-40 years. According to survey results which we made out of 210 respondents 68 people are from 20-30 years, 90 respondents are from 31-40 years, 39 people are rom 41-50 years and 13 people are from more than 50 years of age. Hence in tumkur district kumbarahalli, the majority of the farmers are from the age group of 30-40 years. Table 2. Is Agriculture your main occupation Valid Frequency Yes 207 98.6 No 03 1.4 Percent Inference: After conducting the survey in tumkur district kumbarahalli out of 210 respondents, 207 respondents are working in agriculture sector, so in this area agriculture is the main occupation. Table 3. What is the income level of the Family Valid Income Frequency Percent 0 50,000 21 10 50,001 1,50,000 185 88.1 1,50,001 2,00,000 04 1.9 Inference: According to survey on income level of agriculture, out of 210 people, 185 respondents have the income lies between 50,000 1,50,000, 21 respondents income lies between 0-50,000 and 4 respondents income lies between 1,50,001 2,00,000. Table 4. What is the main source of income in your Family Valid Occupation Frequency Percent Agriculture 199 94.76 Business 5 2.4 Employment 4 1.9 Labour 2 1.0 Inference: Survey result describes that out of 210 respondents, 199 respondents convey their main source of income for their family is through agriculture and 5 respondents convey from business followed by 4 respondents from employment and only 2 says their earning through labour source. Table 5. Past how many years you have been in this agricultural sector Valid Years Frequency Percent 10-20 63 30 21-30 99 47.14 31-40 34 16.19 > 40 years 14 6.67 @IJAPSA-2018, All rights Reserved Page 7
Inference: In the Kumbarahalli 99 respondents out of 210 who have been surveyed has more than 21-30 years of experience in agriculture sector followed by 63 respondents between 10-20 years and 34 respondents between 31-40 years of experience in agriculture and only 14 respondents have more than 40 years of experience in agriculture Table 6. How much agricultural land do you own Valid Acres of land Frequency Percent 1-5 7 3.33 6-10 187 89.05 11-15 14 6.67 > 15 2 0.95 Inference The survey data reveals that 187 respondents convey that they have 6-10 acres of agricultural land followed by 14 respondents between 11-15 acres and 7 respondents between 1-5 acres of land and only 2 respondents more than 15 acres of agricultural land. Table 7. In the last 3 months how many hour did you get electricity for agriculture Valid Hour Frequency Percent 1-3 198 94.28 4-6 7 3.33 7-9 5 2.39 Inference: The data reveals that 198 respondents has conveyed that government providing only 1-3 hours of electricity for their agriculture but this is not sufficient for their agriculture so they requesting government minimum of 6-8 hours of electricity for agriculture, and few farmer in that are getting more than 7-9 hours of electricity because of nerantharajothi project. Table 8. Do you think that power shortage is influencing your agricultural activities? Strongly disagree 9 4.28 Disagree 20 9.53 Valid Neutral 52 24.77 Agree 84 40 Strongly agree 45 21.42 Inference: According to farmers of kumbarahalli 84 farmers agree that power shortage is influence their agriculture activities, 52 farmers are replied may be may not be power shortage influence their agriculture and 45 people replied that its strongly agree and rest of the farmers replied that it strongly agreed and rest of the farmers conveyed that power shortage is not influencing their agriculture activities. Table 9. Do you think suryaraitha scheme introduced will help in power generation adequately. Valid Frequency Percent Frequency Strongly disagree 10 4.8 Disagree 17 8.09 Neutral 66 31.42 Agree 72 34.28 Strongly agree 45 21.42 Percent Inference: Most of the farmers of the kumbarahalli have conveyed that suryvraitha scheme helps to generate power adequately and also helps to reduce dependency on general electricity, and only few farmers of same village replied that suryaraitha scheme will not help to generate power. @IJAPSA-2018, All rights Reserved Page 8
Table 10. Do you think suryaraitha scheme will eliminate the dependence on transformer Frequency Percent Strongly disagree 10 4.76 Disagree 37 17.61 Valid Neutral 45 21.43 Agree 70 33.34 Strongly agree 48 22.86 Inference: Transformers are very much in agriculture activities because bore well motors and other equipment s need transformers so farmers replayed that suryaraitha scheme will eliminates the dependency on transformers and few farmers did not agree that suryaraitha scheme will eliminate transformers. Tbale 11.Do you think suryaraitha scheme helps in increasing your income? Frequency Percent Strongly disagree 4 1.90 Disagree 23 10.95 Valid Neutral 59 28.09 Agree 77 36.67 Strongly agree 47 22.39 Inference: In this survey most of the farmers replied that suryaraitha scheme helps to increase their income Communalities for Survey Initial Extraction 1. Do you think power shortage is influencing you agricultural activities? 1.000 0.535 2. Do you think power supplied by the power board is sufficient to for your agriculture 1.000 0.349 3. Do you think suryaraitha scheme introduced will help you in power generation adequately 1.000 0.681 4. Do you think suryaraitha has scheme will help to reduce the dependence on general electricity 1.000 0.678 5. Do you think surharaitha scheme will eliminate the dependence on transformers 1.000 0.577 6. Do you think solar technology offers a opportunity to stabilize their energy cost 1.000 0.651 7. Do you think solar pumps helps in energy savings 1.000 0.788 8. Do you think solar pumps can also be run during night time 1.000 0.969 9.Do you think suryaraitha scheme helps to increase your income 1.000 0.960 10.Do you think solar power is better substitution for other forms of energy 1.000 0.614 11. Do you think this scheme helps to increase the yield of your agriculture 1.000 0.671 12.Do you think this scheme provides safety for farmers from agriculture 1.000 0.974 13.Do you think solar pumps are more convenient to operate than diesel generators 1.000 0.956 14. Do you think through this scheme farmers can save their time 1.000 0.919 15. Do you think solar pumps are highly reliable and durable 1.000 0.565 level because of the available of adequate natural resource and also they can sell back to government @IJAPSA-2018, All rights Reserved Page 9
16. Do you think installing the solar pumps in the field will increases the value of land 1.000 0.593 17. Do you think photovoltaic panel are often a cheaper option than new electric lines for providing power to remote location 1.000 0.962 18.Do you think there is a high rule and regulations for government schemes 1.000 0.989 19. Do you think there is delay in providing subsidy amount 1.000 0.493 20. Do you think this scheme is non-polluting and eco friendly scheme 1.000 0.985 21. Do you think initial investment of this scheme is high 1.000 0.936 22. Do you think brand image of this scheme increases the brand image of the government 1.000 0.928 23.Do you think solar panels are highly durable 1.000 0.974 24.Do you think it required the less maintains cost 1.000 0.667 25.Do you think solar panels are easy to install and operate 1.000 0.971 26. Do you think the installation can be freely mobile from one place to another place 1.000 0.946 27. Do you think there is a resale value for solar equipment s 1.000 0.918 IV. STATISTICAL TECHNIQUES Table 12 KMO Measure of Sampling Adequacy and Bartlett s Test of Sphericity for Company Survey. Kaiser Meyer Olkin Measure of Sampling Adequacy 0.757 Approx. Chi Square 4216.396 Bartlett s Test of Sphericity Df 351 Sig..000 Normally, 0<KMO<1, If KMO>0.5 the sample is adequate Here, KMO=0.75 which indicates that the sample is adequate and we may proceed with in factor Bartlett s Test of Sphericity Taking 95% level of significance, a=0.05, the p- value (sig.) of.000<0.05, therefore the factor analysis is valid. As p<a, therefore reject the null hypothesis is H0 and accept the alternative hypothesis. (H1) That there may be statistically significant interrelationship between variable. The Kaiser-Meyer Olkin (KMO) and Bartlett s test measure of sampling adequacy was used to examine the appropriateness of factor analysis. The approximate of chi-square is 4216.396 with 351 degrees of freedom, which is significant at 0.05 level of significant. The KMO statistic of 0.757 is also large (greater than 0.50). Hence factor analysis is considered as an appropriate technique for further analysis of the data. Table 13 showing reliability of statistics Cronbach s Alpha No. of items.728 27 Cronbach s alpha is tested to establish the consistency of the instrument which is used to collect the data or their reliability analysis was conducted by computing the Cronbach s alpha (a) for each moderating variables. Most of the constructs are more than. 7 which shows that the instrument is very much consistent. The respondents have provided consistent response to the items of the concerned @IJAPSA-2018, All rights Reserved Page 10
constructs. The Cronbch s alpha for independent variables used to measure the Surya Raitha scheme was 0.728 indicating that the measures have acceptable internal consistency. CHI-SQUARETEST Hypothesis for natural power v/s loan for agriculture Ho: There is no significance relationship between agriculture loan and the generation of natural power H1:There is significance relationship between agriculture loan and the generation of natural power Particulars Value Df Asymp Sig (2-sided) Pearson chi-square 20.199 15.024 Likelihood Ratio 16.289 15.363 Linear-by-Linear association.362 1.547 N of valid cases 210 a. 23 Cells (71.9%) have expected countless than 5. The mimimum expected counts is.13 Result: Since the pearson Chi-square calculated value (20.199, p=0.024) is less than the table value (0.05) so we reject null hypothesis and the alternative hypothesis is accepted i.e there is significant relationship between agricultural loan and the natural power. Hypothesis for productivity v/s loan or agriculture H0: There is no significant relationship between agriculture loan and the generation of productivity H1: There is significant relationship between agriculture loan and the generation of productivity Chi-Square Tests Particulars Value Df Asymp Sig (2-sided) Pearson chi-square 27.594 20.019 Likelihood Ratio 25.925 20.168 Linear-by-Linear association 2.025 1.155 N of valid cases 210 a. 28 cells (66.7%) have expected countless than 5. The minimum expected count is.13 Result: Since the pearson chi-square calculated value (27.594, p=0.019) is less than the table value (0.05) we reject the null hypothesis and accept the alternative hypothesis i.e there is a significant relationship between agricultural loan and the productivity. Hypothesis for regulations v/s Loan for agriculture H0: There is no significance relationship between agriculture loan and the rules and regulation from government on suryaraitha scheme. H1: There is significant relationship between agriculture loan and the rules and regulation from government on suryaraitha scheme. Chi-Square Tests Particulars Value Df Asymp Sig (2-sided) Pearson chi-square 22.321 19.069 Likelihood Ratio 25.118 19.157 Linear-by-Linear association.593 1.441 N of valid cases 210 a.29 cells (72.5%) have expected count less than 5. The minimum expected count is.13. Result: Since the pearson chi-square calculated value (22.321, p=0.069) is less than the table value (0.05) were reject the null hypothesis and the alternative hypothesis i.e there is a significance relationship between agricultural loan and the regulations. Hypothesis for installation v/s loan for agriculture H0: There is no significant relationship between agriculture loan and the installation of suryaraitha scheme @IJAPSA-2018, All rights Reserved Page 11
H1: There is a significant relationship between agriculture loan and the installation of suryaraitha scheme Chi-Square Tests Particulars Value Df Asymp Sig (2-sided) Pearson chi-square 17.712 14.020 Likelihood Ratio 12.816 14.541 Linear-by-Linear association.113 1.736 N of valid cases 210 a. 20 cells (66.7%) have expected countless than 5. The minimum expected count is.13 Result: Since the pearson chi-square calculated value (17.712, p0.020) is less than the table value (0.05), we reject the null hypothesis and accept the alternative hypothesis i.e there is a significance relationship between agricultural loan and the installation. ANOVA Age and dimensions of suryaraitha scheme H0: There is no significant difference between age of respondents across the various dimensions of suryaraitha scheme H1: There is significant difference between age of respondent across the various dimensions of suryaraitha scheme Table 14- One way ANOVA of age on dimension Particulars Sum of Df Mean F Sig. squares square Between groups 54.406 3 18.135 2.394.070 Natural power Within 1560.718 206 7.576 groups Total 1615.124 209 Between 55.087 3 18.362 1.142.033 Productivity groups Within 3313.770 206 16.086 groups Total 3368.857 209 Between 21.456 3 7.152.419.040 Regulations groups Within 3520.372 206 17.089 groups Total 3541.829 209 Between 36.885 3 12.295 1.604.190 Installation groups Within 1579.096 206 7.666 groups Total 1615.981 209 *Significant at 5% level The One way ANOVA result shows that there is an overall significance for productivity F(1.142), p=0.033, Regulation F(0.491), p=0.040, whose value of p is below 0.05 (p<0.05) at the level of significance. Hence null hypothesis is rejected and alternative hypothesis is accepted. Now we can intent to see that productivity, regulation, has a significance difference across age. Where as for natural power and installation there is no significance difference. Income on dimension H0: There is no significant difference between income of respondent across the various dimensions of suryaraitha scheme. @IJAPSA-2018, All rights Reserved Page 12
H1: There is significant difference between income of respondent across the various dimensions of suryaraitha scheme. Table 15 one way Anova of Income and Dimension of suryaraitha scheme Particulars Sum of df Mean F Sig. squares square Between groups 4.682 2 2.341.301.040 Natural power Within groups 1610.442 207 7.708 Total 1615.124 209 Between groups 1.929 2.964.059.042 Productivity Within groups 3366.929 207 16.265 Total 3368.857 209 Between groups 22.036 2 11.018.648.024 Regulations Within groups 3519.793 207 17.004 Total 3541.829 209 Installation Between groups 13.392 2 6.696.865.423 Within groups 1602.589 207 7.742 Total 1615.981 209 *Significant at 5% level The one way ANOVA result that there is an overall significant for natural power (F0.301), p=0.040, productivity F(0.059), p=0.042, Regulation F(0.648), p=0.024) whose value of p is below 0.05 (p<0.05) at the level of significance. Hence null hypothesis is rejected and alternative hypothesis is accepted. Now we can intent to see that natural power, productivity, regulation has a significant difference across income. Whereas for installation there is no significance difference. Land on dimension H0: There is no significant difference between acres of land owned by the respondents across acceptance of various dimension of suryaraitha scheme. H1: There is a significant difference between acres of land owned by the respondents across acceptance of various dimension of suryaraitha scheme. Particulars Sum of squares df Mean square F Sig. Between groups 53.334 3 17.778 2.345.044 Natural power Within groups 1561.790 206 7.582 Total 1615.124 209 Between groups 303.459 3 101.153 6.789.000 Productivity Within groups 3065.398 206 14.881 Total 3368.857 209 Between groups 50.182 3 16.727.987.400 Regulations Within groups 3491.829 206 16.950 Total 3541.829 209 Between groups 20.606 3 6.869.887.449 Installation Within groups 1595.375 206 7.745 Total 1615.981 209 *Significant at 5% level The one way ANOVA result that there is an overall significant for Natural power (F (20345), p=0.044, productivity F(6.798), p=0.000, whose value of p is below 0.05 (p<0.05) at the level of significant. Hence null hypothesis is rejected and alternative hypothesis is accepted. Now we can intent to see that natural power, productivity has significance difference across land. Where as for installation and regulation there is no significance. Correlation between various dimensions of surayaraitha scheme @IJAPSA-2018, All rights Reserved Page 13
Particulars Natural power Productivity Regulations Installation Loan Pearson 1.449*.416* 1 423** Natural correlation power Sig (2-0.477 0.821 0.527 tailed) N 210 210 210 210 210 Pearson correlation 449* 1 431** 449* 432* Productivity Sig (2 0.477 0.653 0.477 0.451 tailed) N 210 210 210 210 210 Pearson 416** 431** 1 416** 422* Regulations correlation Sig (2-0.821 0.653 0.821 0.644 tailed) N 210 210 210 210 210 Pearson 413** 404** 298** 1 486** Installation correlation Sig (2-0.008 0 0 0.008 tailed) N 210 210 210 210 210 Pearson correlation 423** 0.456 0.397 436** 1 Loan Sig (2-0.576 0.745 0.665 0.731 tailed) N 210 210 210 210 210 Inference: a. Pearson correlation value for natural power is 0.423** and p value is 0.576 which shows there is a significant impact of natural power on loan. Here natural power is consider as independent variable and loan is considered as dependent variable. Assume that for null hypothesis there is no correlation between natural power and loan, like wise for alternative hypothesis consider there is correlation between natural power and loan confined that the natural power and loan are correlate to each other. b. Pearson correlative value for productivity is 0.432** and p value is 0.451 which shows there is a significant impact of productivity on loan. Here productivity is considered as independent variable and loan is considered as dependent variable. Assume that for null hyhpothesis is there is no correlation between productivity and loan, like wise for alternative hypothesis considered there is correlation between productivity and loan. It is confined that the productivity and loan are correlated to each other. c. Pearson correlation value for regulation is 0.422** and p value is 0.644 which shows there is a significant impact of regulation on loan. Here regulations is considered as independent variable and loan is considered as dependent variable. Assume that for null hypothesis is there is no correlation between regulation and loan, like wise for alternative hypothesis is consider there is correlation between regulation and loan, like wise for alternative hypothesis considered there is correlation between regulation and loan. It is confined that the regulations and loans are correlated to each other. d. Pearson correlation value for installation 0.486** and p value is 0.008 which shows there is a significant impact of installation on loan. Here regulation is considered as independent variable and loan is considered dependent variable. Assume that for null hypothesis there is no correlation between @IJAPSA-2018, All rights Reserved Page 14
installation and loan, like wise for alternative hypothesis considered there is correlation between installation and loan. It is confined that the installation and loan are correlated to each other. Findings of the study a. According to data obtained through the survey majority of the respondent in that particular village is between the age group of 31-40 and their main occupation is agriculture out of 210 sample more than 195 people s main occupation is agriculture and rest other are from labour, business etc. and the monthly income of their family is around 50,000-1,50,000 and few farmer s income is less than 50,000, these farmer are growing mainly rabi crop they will sowing in summer and harvest farmers like to grow kharif crops which is sowing in winter and harvest in summer, these farmer shaving have positive come of only 1-3 months and few of the farmers having more than 3-9 months of positive come from agriculture. Majority of the farmers are depending on bore well to grow crops and few farmers are depending on rain. The major factors affecting their yield are monsoon, insects, and animals. In a village from last 3 months farmers are getting 3 hours of electricity for their agriculture purpose and majority of the respondents ( out of 210 sample more than 180 farmers) taken loan for agriculture. b. Natural power:- country like India still facing problem in generation of electricity. Because of gambling in monsoon farmers are depending on borewell for their agriculture to overcome from this government taken much initiative but still there is problem. According to survey majority of the farmers conveys that power shortage is influencing their agriculture activities and the power supply from the power board is still not sufficient for the agriculture, most of the farmer agree that suryaraitha scheme helps in generation of natural electricity adequately and this scheme helps to reduce dependency on general electricity nowaday s to stabilize their energy cost, and because of this scheme government can save the energy cost and also government can manage the power shortage problem effectively, the main advantage of this solar power is it can also run during night time. c. Productivity and yield increase: Farmers agree that because of suryaraitha scheme they can increase the income level of their family and also they can increase the yield in agriculture and solar power is better substitution for other forms of energy like oil engines, biomass etc. As above said this scheme increases the yield of the agriculture and their income. General electricity is not safe for human life and because of this general electricity there is lot of death incident happen but this solar energy provides safety for farmers, and these solar pumps are more convenient to operate and manage than oil engines, this scheme also helps in time savings because once it is charged it will operate in any time and according to research solar panel are highly reliable and durable, because of this solar panels the value of the land will also increase and this will helpful farmers. These photovoltaic panel also cheaper and more reliable when compared to electric line and also these solar panels eliminates the transformers in remote location. d. Rules and regulations: Majority of the farmers agree that there is high rules and regulation for government subsidies hence these scheme are not properly reaching to the farmers and other main disadvantage is there is delay in providing subsidy amount to farmers so farmers are requesting government should give the subsidy amount and it should reach the farmers and this scheme is nonpolluting and eco friendly, government is providing 90 percent of subsidy to farmers but still farmers are not accepting this scheme because the initial investment is high so that farmers are not ready to accept this scheme. Because of this scheme the brand image of the government will increase. e. farmers are agreeing that solar panels are highly durable and reliable when compared to the general electricity and also it required less maintenance cost because it operates through natural light and heat and these solar panel are easy to install and operate as compared to diesel or oil engine it can be freely mobile from one place to another place and because of high demand for solar products there is a high resale value for solar equipments. @IJAPSA-2018, All rights Reserved Page 15
Statistical analysis In this study we have used KMO test Kaiser Meyer Olkin is used to measure of sampling adequacy, which varies between 0 and 1. The values closer to 1 are better and the value of 0.6 is the suggested minimum. Normally, 0<KMO<1 if KMO>0.5 the sample is adequate. Hence, KMO =0.757 which indicates that the sample is adequate and we may proceed with the factor analysis, and further there is reliability test was under taken in order to facilitate their liability of the data and the standard is set to 70% and our data comes upto 0.728 indicating that the measure have acceptable internal consistency. We identify the test demographic significant difference across on various dimensions, in that now we can intent to see that natural power, productivity, regulation has significant difference across on various dimension in that now we can intent to see that natural power, productivity, regulation has significant difference across age through ANOVA. From chi-square test we identify the impact analysis, whether any of the dimension has impact on purchasing power we suryaraitha scheme we conclude that on the dimension of natural power, productivity, rules and regulations and installation. Since the Pearson Chi-square calculated value (20.199, p=0.024) is less than the table (0.05) so we reject null hypothesis, and the alternative hypothesis i.e there is a significant relationship between agricultural loan and the natural power, productivity and installation. Since Pearson Chi-Square calculated value (22.321, p=0.069) is greater than the table value (0.05) we accept the null hypothesis and the alternative hypothesis i.e there is no significance relationship between agricultural loan and the regulation. Suggestion 1. Every year monsoon is gambling, delaying and insufficient to agriculture so farmers are depending on bore wells. Wells and channels but for such kind of water resources electricity is very much essential. 2. Because of many problems government cant table provide sufficient electricity to agriculture, so for this reasons government should encourage effectively for natural power (solar electricity) for such kind of scheme government should encourage effectively. 3. Department of agriculture, KPTCL and information and publication should provide proper knowledge about how to apply, what are all the documents need, what is the initial cost required, how much space is required, how to operate etc. all this information should guide to farmers. 4. Government should increase the subsidy amount and government should reduce the initial cost and government should provide subsidy amount quickly to farmers. 5. Respective departments should provide demo to farmers in each villages to improve this scheme, and also they should provide knowledge about how to sell excess power and earn money from this scheme. 6. Government should install this plant for drinking water facility and government schools to show advantages of this scheme. Instead of giving subsidy amount to farmer s government should take the initial investment cost and approve the power plant this will reduce the burden on farmers and increase the effectiveness of this scheme. V. CONCLUSION According to data obtain from the research farmers are facing many problem in agriculture sector like permanent irrigation, electricity, monsoon, insects, animals etc. Farmers are facing electricity problem, the power supply from the power board is insufficient for the agriculture hence both central and state government introducing many scheme like Krishi Bhagya, Krisanvikas, gram sansadadarsh grama yojana, soil health card, suryaraitha scheme to improve agricultural, but still many @IJAPSA-2018, All rights Reserved Page 16
of the farmer not aware about these project and scheme and also farmer conveyed that bore wells and monsoon are the major source of water for the agriculture. Gambling in monsoon, shortage of electricity will decrease the yield. Government of Karnataka introduced suryaraitha scheme to overcome from the shortage of electricity but because of high rules and regulation, delay in providing subsidy amount and high initial investment cost which is because of these protocols farmers are not ready to adopt these valuable scheme and government also failed to promote effectively from this scheme farmer can also increase their income and also increase the yield in agriculture. But still majority of the farmers not aware about suryaraitha scheme. From this scheme the value of the land also increases and this scheme will increase the brand value of the government. Farmers are agreeing that from this scheme they can save time and also there is safety from the external threats and it reduces the dependency on natural electricity, it can also eliminate the dependency on transformers. These solar motor and panel are more convenient to operate when compare to electric motor and oil engines, and also it required less maintenance cost, highly durable and reliable. Still in few remote locations general electricity is not available because of installation of electric lines and also transformers but in surayaraitha scheme both farmers and government can stabilize their energy cost and they can save energy, and one of the best advantage of this scheme is non-oil engines ad also there is high demand and resale value for solar panels. In this scheme one of the major advantage is government will purchase the excess of power from the farmers at seven to eight rupees per unit. BIBLIOGRAPHY [1] B.Eker, T. (2005). Solar powered water pumping system. Trakia Journal of Science, 3(11). [2] Gambhir, V. T. (2012, Nov). Solar Rooftop PV in India: Need to Prioritise Institute Generation or Self-consumption with a Net-Metering approach http;//www.prayaspune.org/peg/. Pravas Policy Discussion Paper, 20. [3] Kumar, D. H., & V, D. S. (2017). An Empirical Study on Farmer s Awareness And Mplementation of Agricultural Automated Products With Special Reference To Gipzonics. International Journal and Applied and Pure Science and Agriculture, 3(8), 7-15. [4] Misha, B. S. (2015). Utilization of solar energy for driving a water pumping system. International Research Journal of engineering and technolgy, 02(03). [5] S.S.Chandel, M. a. (2015). Review of solar photo voltaic water pumping system technology for irrigation and community drinking wateer supplies. 49(C), 1084-1099. [6] Shah, T. (1993). Groundwater Markets and Irrigation Development:. Political Economy and Practical Policy Climatic Change and Groundwater: Political Economy and Practical Policy Climatic Change and Groundwater, 3(4), 22-24. [7] Siddharth, D. ( 2015, April). Development of solar powered water pumping system. International Journal for Innovative research in Science & Technology, 1(12). [8] Singh, B. R. (2016, Jan 29). Future scope of Solar Energy in India. school of Management. [9] Tewari, N. P. (2012). Solar Irrigation pumps. Colombo: IWMI. [10] Tiwary. (2012). Solar Irrigation Pumps: Farmers Experience and State Policy in Rajasthan. Economic & Political Weekly, 55-62. [11] Treephak, J. (2015). An Economic Valuation of Solar water pumping system with engine pumping system for riceultivation kasem. 54, 8S1. [12] Vashishtha, S. F. (2015). Development of solar energy for driving a water pumping system. International Journal of Innovation Research in Science and technology, 1(12). @IJAPSA-2018, All rights Reserved Page 17