Can Farm Mechanization Enhance Small Farmers’ Income? A Lesson learnt of Lower Shivalik hills of Indian Himalayan Region


 Indian farming is fraught with small land holdings, and farm mechanization's economic viability has remained a debatable issue at the core of Indian agriculture's technology growth. The authors attempted to determine the socio-agro-economic impact of seed cum fertiliser drill and zero tillage through Difference In Difference(DID) method with ex-ante (before application) and ex-post (after application) approach. Results depicted labour costs were reduced by almost 80% and seed savings were reduced by 20%. The seed cum fertiliser drill and zero tillage adopters saved a sum of Rs. 3764.10 and Rs. 4047.54 from 1 ha of land, respectively. An effort was also made to quantify the additional economic benefit by using the Apparently Unrelated Regression (SUR) model to apply selected forms of machinery to different varieties. Seed cum fertiliser drill and zero tillage results have been found to increase yield by 13.39 quintals and 6.0 quintals per ha respectively and decrease the seed rate by 27.71 kg/ha and 24.20 kg /ha, respectively, for the HD 2967 wheat variety. The growth of the agricultural mechanisation sector is hindered by machine cost, the widespread existence of resource poor farmers, and inaccessibility of agricultural technology. In addition, few suggestions on critical aspects were made on the basis of the application of technology in different states to implement suitable policies for the additional financial advantage of farmers.

mechanization can be pro table for smallholder farmers. Seed cum fertilizer drill and zero tillage implements are two very handy machineries used e ciently in many Indian farms of small and medium-size, and the following study deals with the economic e ciency of these two implements. These are helped to improve fertilizer use e ciency, save time, water, labour, cost and escape terminal heat stress in wheat cultivation (Mittal, 2017). There is immense scope of farm mechanization and is the need of the hour. With the intensi cation of agriculture, there is a need for farm power availability from the present level (0.60 kW/ha) to about 2.0 kW/ha by 2020. Hence in this study, the authors have attempted to study the impact of seed cum fertilizer drill and zero tillage machine on the production, the productivity of improved varieties of wheat at lower Shivalik hills of Himalayan region. The authors have also attempted to project Uttarakhand's scenario in other states of India where these varieties of wheat are grown. This presents the scenario of out-scaling of seed drill and zero-till in wheat across India and its effect on farmers' income as farm gate prices, and cost of cultivation of that crop vary from state to state. So the article has tried to explore the necessity of up-scaling (vertical) and out-scaling (horizontal) of farm machinery, and the results were expected to generate policy implications for how the up-scaling and out-scaling can be done. Thus, there is an urgent need to enhance the level of farm mechanization in our country by redressing the states with a lower share of mechanization. How the machines perform and enhance the yield of smallholder farmers of rugged terrain and how the same can up-scaled and out-scaled to bene t several other smallholders of different states have served as the motivation behind this study.

Materials And Methods:
Locale of Study Lower Shivalik hills, instead of adequate natural resources for successful crop growth like fertile soil, 87 percent irrigation water, the productivity was found not to reach a competitive level for the lower Shivalik region of Uttarakhand for various crops as compared to other parts of the lower Shivalik Hills (i.e., Jammu region of J&K and Malwa region of Punjab) . The non-availability of improved planting materials (seed), poor access to modern technologies, and poor productivity lead to an abysmally low marketable surplus in the plains of Lower Shivalik hills Uttarakhand (Roy et al., 2018). Moreover, farm Mechanization stands at about 40-45% in UP and Punjab states, whereas little mechanization in states like Uttarakhand. So the study has been purposively conducted in the lower Shivalik hills of Uttarakhand. India's hilly state is Uttarakhand, situated in North Western Himalayas.

Sample size determination
The Cochran formula (1977) has been used to calculate an ideal sample size given a desired level of precision, desired con dence level and the estimated proportion of the attributes present in the population. The Cochran formula is: where, e is the desired level of precision (margin of error) p is the (estimated) proportion of the population which has attributes in question q is 1-p The z-value is found to be 1.96 In the present study, authors do not have much information on the subject to begin with, so going to assume that half of the farmers have adopted that particular farm machinery that give maximum variability. So p = 0.5. Now considering 95% con dence and at least +5 percent precision, authors assume more than 95% con dence level gives Z value of 1.96, per the normal table, so get ((1.96) 2 (0.5) (0.5))/ (0.04) 2 = 359. 23 Hence the sample size was approximately 360. Apart from these 20 government o cials (Krishi Vigyan Kendra Scientists and extension functionaries of the state department of agriculture) have been interviewed to suggest suitable policy for upscaling and out scaling of adoption of improved technologies by farmers in the particular region. Thus, a total sample of 380 respondents were selected for this study.
Statistical tools and software: Binary logistic regression was used to nd out the factor affecting farmers' decision to adoption of particular technologies (Seed cum fertilizer drill, Zero tillage). It is assumed that the binary response, Y, takes on the values of 0 and 1 with 0 representing non adoption of particular machinery and 1 representing adoption of particular machinery. The equation is as follows Where Pi is a probability of farmers decision, Pi = 0 indicates adoption and Pi = 1 indicates non adoption Y = probability of farmers decision β 0 = intercept β 1 -β 8 = regression coe cients of the dependent variables X 1 -X 19 = Independent variables In addition to these, Kendal tau has been used for nd out the degree of association with different independent variables. Kendall's tau is computed as τ=Nc−Nd/Nc+Nd whereN c and N d denoting the number of concordant pairs and the number of discordant pairs, respectively, in the sample. Ties add 0.5 to both the concordant and discordant counts.
Seeming Unrelated Regression (SUR) Model was employed to estimate the economic e cacy of a particular farm machinery with respect to varieties. The SUR method estimates the parameter of all equations simultaneously, so that the parameters of each single equation also take the information provided by the other equations into account. This results in greater e ciency in estimation by combining the information on different equations.
InΠi* = InAi* + μi1* Inp + μi2* Inr + μi3* Inw + bi1* InK + bi2* InT + bi3*lnD Where :Πi* = production function , P,r, w, k…… = quantity of inputs Alfares and Duffuaa's (2009) methodology was used to nd out the factors for upscaling of technologies, which is based on a linear rank-weight function whose slope (Sn) depends on the number of criteria (n). In the present study, an effort was given to determine aggregate criteria weights of each dimension or statement; the 20 judges ranked the statements within each dimension as well as each dimension. Thus, after obtaining aggregate weights, the important aspects of strategy development for up-scaling and out-scaling can be identi ed.
Where, n= number of criteria, r = rank assign to statement or criteria, Wrn= weight assign to criteria based on individual rank, W= aggregate weight of respondent.
Garett ranking technique has been employed to nd out the most signi cant factor which in uences the respondent and the outcomes of such ranking have been converted into score value with the help of the following formula: Percent position = 100 (R ij -0.5) N j Where R ij = Rank given for the i th variable by j th respondents ,N j = Number of variable ranked by jth respondent. Moreover, to calculate pro tability of technologies following calculation has been taken into consideration.

Results And Discussion
Extent of adoption of farm machineries Only 45 percent of farmers had adopted seed cum fertilizer drill, and the rest, 55 percent, did not adopt it. Among the adopter farmers, more than 65 percent of farmers used seed cum fertilizer drill in the range of 6.60 to10.69 acres of land, which fell in the group of medium and about 16 percent farmers in the category of low as well as and high category. In zero tillage, only 32.78 percent of farmers had adopted, and 67.22 percent still belonged to the non-adopter category. This dossier was matched with the outcome of Mottaleb et al, 2016.
Discussion explored the prerequisite condition for adopting farm machinery was large operational land. However, most of the farmers were small or marginal farmers. The land was also scattered over many areas were the reason of lower adoption. Financial limitations were another impeding factor that refrained them from adoption. Farmers were solely resourcing poor and were not able to purchase farm machineries. They were not able to recognise the use as well as the working mechanism of farm machinery. Another signi cant reason for non-adoption was the unavailability of machinery on a custom hiring basis as well as availability to auxiliary parts and maintenance thereof. Focus group discussion implied peoples' mindset and the potentiality to make farmers aware of the farm machineries and bene ts were the main reasons for non-adoption. However, once the crop germinated, other farmers wanted to know how they accomplished the results and were persuaded that it would work, although many waited until the harvesting was done for the nal decision (seeing and doing). Since farmers rely upon farming for a livelihood, they will change production practices after being convinced.

Determinants of adoption of Seed cum fertilizer drill and Zero tillage
The observed adoption choice of farm machineries was speculated to be the consequence of a tangled set of inter-technology favoured evaluations created by farmers. It was obligatory to scrutinize the elements persuading the adoption of farm machineries by evaluating a binary logic model with independent variables. This model represented the cumulative outcome of the explanatory variables impeding or encouraging the adoption of farm machinery. For Seed cum fertilizer drill, the Pseudo R 2 value showed that the model is a 91 percent best t ( Availability of information (0.00*), mass media exposure (0.02**), risk orientation (0.06***), innovativeness (0.09***) and farm asset (0.00*) were the signi cant factors of adoption. The odds ratio indicated that with a one-unit increase in available information, the adoption level could increase by 5.15 percent. Similarly, with a one-unit increase in mass media exposure, the adoption level had risen by 2.02 percent. With one unit increase of risk orientation, innovativeness, and farm asset, the adoption level increased by 0.76, 1.13, and 13.73 percent, respectively. A similar study was carried out by Ainembabazi et al, 2017, which reported that accessibility of information enhanced awareness level, which eventually increased the adoption of technologies. More mass media exposure enhanced ability to procure, analyse and elucidate information of using seed cum fertilizer drill. This discovery is following the studies of Feder et al. (1985). Farmers had more data sources that would increase the capabilities of decision-making to embrace seed cum fertilizer drill. Farmers with more risk-bearing capacity, sometimes, lead to higher adoption as compared to other fellow farmers. They could resist with success as well as failure, simultaneously leading to more adoption. Focus group discussion with the non-adopted farmers disclosed that before adoption, they thought more about the outcome. They thought of using seed cum fertilizer drill could not have any signi cant increase in yield. Similarly, the numbers of farm assets had signi cant involvement in this regard. It referred that the farmers who had higher nancial resources purchase more farm assets for use in their eld. So, it can be expressed that establishing a custom hiring center is mandatory, which would increase more adoption of machinery. As anticipated, operational landholding (OLH) has an upbeat and noteworthy collision on zero tillage technology adoption. With the increase of every added unit of an acre of land, the chance of adoption was increased by 1. Socio-Agro-Economic impact of farm machineries: Social impact mentioned the adoption of farm machineries that lead to any change in an individual, family, and community well-being like timesaving, employment generation, depletion in labour requirement, etc. Agronomic impact referred to change in parameters like coverage ( eld capacity), seed rate, germination percentage, crop establishment, plant population per ha, etc. Economic aspects dealt with BCR (bene t-cost ratio), Net Return, and RR (rate of return) from adopted technologies.
An attempt had been made to note down the in uence of seed cum fertilizer drill adoption on socio-agronomic issues. DID method was applied to evaluate the technical as well as social features with ex-ante (before application) and ex-post (after application) analytical approach. Table 3      Farm level e ciency of improved machineries for upscaling: This part is focused on devising an approach for out scaling of selected technologies for Lower Shivalik range of Uttarakhand as well as other regions on lower Shivalik hills. It alludes to the most suitable variety of wheat crop, for that particular region in economic parameters and economic e cacy of each machinery, related to each selected improved varieties in lower Shivalik hills. It aids farmers to step up agricultural production and income which results in economic growth, redistribution of resources at individual, local and regional level.
To estimate economic e ciency (in terms of yield and seed rate quantity) of seed cum fertilizer drill on selected wheat varieties, Seeming Unrelated Regression (SUR) model has been adopted. In the Table 6, RMSE score 11.48 shows model presents 11.48% absolute t of predicted results of yield estimation of HD-2967 by using seed drill than OLS (Ordinal least Square) model. It presents 27.63% and 26.17% absolute t predicted results for yield estimation for HD-3086 and HD-3059 than OLS model. In the similar way, model present 24.42%, 63.31% and 64.56% more e cient absolute predicted results for seed rate estimation in HD 2967, HD 3086 and HD 3059, respectively. Lesser RMSE values instructed for better t. Here RMSE value 11.48 indicated in Table 6 that Yield estimation of HD 2967 is the best t model. The data in Table 6 explains the e cacy of seed drill on yield and seed rate of different wheat varieties. It was observed that the use of seed drill enhances 13.39 q more yield per ha for the variety HD 2967. The varieties HD 3086 and HD 3059 have 12.39q and 10.34q more yield per ha respectively when sown through seed drill. Similarly, it was found that use of seed drill lessened seed rate by 27.71 kg/ha for HD-2967 which was followed by 3.96 kg/ha and 2.90 kg/ha for HD 3086 and HD 3059, respectively.  Table 7 explain the e cacy of zero tillage on yield and seed rate for different wheat varieties. It was observed that use of zero tillage enhance yield by 6.00q more per ha for the variety HD2967. The HD 3086 and HD 3059 have 5.08q and 10.08q more yield per hectare, respectively when sown by zero tillage. As such, it was found that of use of zero tillage adoption helps to, seed rate reduction 24.20 kg per ha in case 2967 which was followed by 4.49 kg and 1.79 kg per ha for HD 3086 and HD 3059. Thus, it saved the cost of seed which, in turn, increased farmers' net income. In view of the e cacy of above discussed machineries on wheat varieties, an attempt has been made to study the improved varieties of wheat grown all over India in the context of future prospects of scaling up of these varieties in those particular regions where the usage of machinery in cultivation of these crops can lead to enhanced production and productivity.
Based on the above results, an effort has been made to present the state-wise scenario in respect of economic bene ts where these varieties are grown and the selected mechanizations have been done. Fig 4 presents the scenarios of farm income for application of seed drill and zero till with reference to wheat varieties. Estimates based on the state-wise secondary data on cost of cultivation (Rs/q), price of seed (Rs/kg), farm harvest price (Rs/q) showed that the cost of cultivation (Rs/q) was the lowest in Punjab. It implied that farmers earned an additional bene t of at least more than Rs. 13000/-per ha and varied according to the cost of production. Similarly, for HD 3086 and for HD 3059, it was at least Rs. 10,000/ per ha each.If the farmers sold their product at MSP, they could earn additional income of Rs 24107.85/-, Rs22797.6/ and Rs.19026.74/-per ha from grain yield with respect to variety HD-2967, HD-3086 and HD-3059. But farmers reported that they were forced to sell their product at farm harvest price which was below the rate of MSP.
Considering this, estimation was made which afforded an additional income ranging Rs 20000-25000/-per ha for variety HD-2967, Rs. 16094.61-25622.52/-per ha for variety HD-3086 and Rs.13432.47-21384.4/ per ha for HD-3059 respectively. In case of Zero till, it implied farmers earned an additional bene t of at least Rs. 6000/-per ha which is varied according to the variety and cost of production. The farmers selling their product at MSP, could earn additional income of Rs 11040/-, Rs9347.20/ and Rs.18547.20/per ha from grain yield with respect to variety HD-2967, HD-3086 and HD-3059. In case for Farm Harvest Price, estimation was made which afforded an additional income ranging Rs 10000/--Rs. 21000/ per ha which varies variety wise.

Constraints analysis for strategy formulation for out scaling of farm machineries
Expert opinion has been taken to identify the constraints related to out scaling of farm machineries.
According to experts view point lack of custom hiring services (farm machinery) was the major Organisational constraint (average score of 65.8) followed by unavailability of proper government support (avg score 51.55), poor cooperation at grass root level organizations (avg score 52.85).Related discovery was conveyed by Loon et al, 2020 and Gowda, 2012, Kelsey 2011, Balachandran, 2004. The custom hiring service could also be fruitful solution for using machinery as the initial investment was comparatively high. Another fascinating apprehension spot lighted that custom hiring farmer that possession of the tractor could be a sign of aristocracy in this sort of circumstances, indeed little ranches purchased tractor which turns into obstruction in customized hiring services. Hence it is imperative to create additional awareness regarding custom hiring of machinery which can facilitate to reduce the xed costs of farm operations and lessen the burden of heavy capital investments.
Experts advised that farmers had to confront multidimensional problem for adoption of farm machinery and, as consequence, it had re ected to the level of up-scaling and out-scaling of farm machinery. As small and marginal farmers were predominant in the study area and they were no longer in a position to compete with the rich farmers. Thus, Rich farmers were bene tted from the different government subsidy schemes. Most farmers own sets of separate small and scattered plots. In some cases it used to be beyond the location of the village too, which made it impossible for them to use uniform farming techniques on their entire holding. Therefore, farmers were unable to use the equipment effectively. Henceforth, farm mechanization of scattered, parcels of land became too troublesome and ine cient, which, in turn, reduced agricultural production and owner's incentive for land improvement and accomplishment of high production.
Non-availability of machines was the predominant technological problems (rank rst) for out-scaling of farm machinery. Moreover, lack of skills, expert guidance, skilled personnel for handling machine and poor technicalities were also correlated with the technical problems of out-scaling of machinery. This nding lies with Kelsey, 2011, Balachandran, 2004. Availability of spare components was being imported. Similar nding was reported by Gowda, 2012. It is assumed that lot of attempts have to be taken up in this sector for mechanization of agriculture in this area for which govt. initiatives are assumed to be more important.
Dearth of manufacturers in the state led to buying of farm implements from other states. It required excessive capital investment for a small farm which made it uneconomical for small farmers. The excessive cost of farm machinery had continually been a serious limiting element in mechanization of agriculture. Farmers in this study area pay appreciably greater for machines than their counterparts in industrialized states like Punjab, Haryana, and U.P. Lack of genuine spare parts of machinery parts at a reasonable price and at a convenient distance had badly affected the operating of machines. Thus, lack of spare components for agricultural machinery and equipment used to be a primary trouble which notably affected all mechanization. Hence, awareness about the govt. credit facilities and accountability of implementing agencies may be taken into consideration while framing any govt. policy in this regard. More than 70 per cent farmers have been economically poor. Due to this nancial condition, in spite of their willingness to own farm implements, they were unable to purchase as these did not come in their order of priority of day to day requirements. Majority of the farmers having small farm holdings couldn't bear to save capital out of their own investment funds to purchase farm implements. If farmers had to take care of each tractor drawn and animal drawn implements, it might be uneconomical. On discussion with the experts it was disclosed that the farmers of that region facing unbelievable trouble in availing credit facilities for the purchase of implements.
They reported that huge formalities and a numerous visits were essential for availing credit facility. They additionally feared as to how many times they would be needed to reimburse the deposit obtained on account of suspected foul play in societies. They enquire interest free credit for buying implements and machinery. Moreover it was found that majority of farmers were having poor educational status and were unaware of such facilities. Some of them who were eager to take bene t of modern technology were excessively poor and could not mortgage their property to secure a bank loan. In addition, banking services had not been proper in rural areas. Indeed, even if it was accessible, farmers had not been well trained to take advantage of the banking facilities. They weren't habituated to deposit their cash in a bank or required a loan from a bank and refund it. Henceforth, it is needed to educate them, to expose them to banking and make them habitual of using bank. Thus lack of well organised workshops in the areas has made it hard to carryout mechanization programmes programs effectively.
Strategy for out-scaling of improved machineries (Expert Opinion): Following Alfares and Duffuaa method, the aggregate weight (W) has been calculated for each dimension (criteria) assuming 100% for rank-1 which is evident from the Table 8. Economic problems (aggregate wt. 1823.11) were the most serious problems having rst ranked for up-scaling and outscaling of machinery followed by technical issues (1646.23), organisational problem (1241.92) and situational factors (1014.51) with rank of 2 nd , 3 rd and 4 th , respectively.
Average size of operational holdings is shrinking resulting in higher proportion of marginal and small holdings hence making possession of agriculture equipment economic and unviable. Establishment of Farmer's Cooperatives and Farm Machinery Utilization Centres or customized hiring service for multi-farm use are crucial. Necessary steps for improvement of supply chain and value chain mechanism must be developed and communicated to the farmers. Financial incentives, sponsored loans, low interest rate, provision of training will motivate the farmers for using farm machinery. Besides, dissemination of information, technical guidance and alternatives farm income may be promoted collectively. But poor information dissemination refrained them from use and management of those expensive resources. Experts felt that this drawback may be resolved by introducing joint farming or farming on co-operative basis resulting in increase in farm holding size. Other organizations like KVK, NGO, SHGs, etc. may play an important role for promotion of machinery in agricultural sector. Therefore, the extension programmes of agricultural engineering ought to be strong. This was re ected in the perception of farmers and use of farm implement and machinery. Similarly manufacturers have not been accessible. This was because of poor extension intervention towards this path. Henceforth mechanisms and incentives should be put in place to encourage the procurement of machinery by smallholders and a favourable tax, liability, and/or excise regime should be enforced. Relevant economic instruments need to be established in this setting to placed small farmers into the nancial aid bene ciary circle. It is important to consider whether farmers in real need of access to loans are excluded because of their ineligibility under established criteria. They were determined to prepare for land consolidation by government agencies. Such consolidation might improve cooperative farming or mechanized farming. The education of most of the farmers was poor. The majority of farmers have very little or no exposure to improve machines for farm operation and were hesitant to even attempt handling motor/ electric operated equipment. A programme of farmers training in handling and managing farm equipment used to be felt an urgent need to make mechanization a success. Custom hiring is a successful strategy to promote mechanization and tackle numerous constraints for the overall improvement of the agricultural sector, such as labour shortage, climatic disasters, as well as timely bound activities. It was orated that farmers had been looking for hands-on training experience starting from tractor driving, hitching of implements, ploughing, harrowing, seed sowing, cultivating, spraying, dusting, harvesting, and their repair and maintenance. They also want a knowledge/training programme for restoring and renovating diesel engines and electric motors. Due to the lack of perfect technical knowledge they had been unable to utilize the machine properly even after hiring it. So it has been conveyed that training centers might be established in the study area either by government organizations, agriculture universities, NGO, Agriculture line departments, or KVK to take up this task. It may be referred to that a higher percentage of labour association in agriculture with a lower contribution to GDP creates agriculture even less satisfying is the cause of ranchers' destitution. With the estimation of reverse fashion in the populace and agricultural growth, it will undesirably effect on production. In such scenario agricultural mechanization is an answer to address the trouble of growing call for of food grains. However, farmers' incapacity to buy farm implements and commercial banks' reluctance to nance farm machinery is one of the major obstacles to the rise in the pace of mechanization which leads to an upward push in entering costs attributable to labour charges. The production of economical technology alongside state support for tiny farmers needs to be checked out and encouraged at the village level, often near the place where small and marginal farmers live. Custom Hiring Centres (CHCs) must be formed through Public-Private Partnership (PPP), non-pro t organizations, co-operative foundation, farmer groups, and charitable trusts. A few governments like Andhra Pradesh, Gujarat, Karnataka, Madhya Pradesh, Punjab, etc have been endorsing farm mechanization through CHCs and such endeavours should be ventured up. Governments must catalyze to inspire them and enable farmers to recognize new economic models, such as custom hiring. In this particular circumstance, cross-sectoral collaborations with the non-government segment, nancial institutions, and farmers' associations must be pursued to focus the numerous monetary blessings of customized hiring and the possible contribution in the direction of modernizing agricultural operations and improving rural livelihoods. Steps need to be taken to provide meaningful and accurate information to key stakeholders to promote and disseminate this activity for customized hiring. Besides, it is important to encourage proper communication along with the value chain including the dissemination of information on the overall performance of agricultural machinery, appropriate training modules developed, and regular training sessions organized to train people involved in machine operations and those involved in repair and maintenance services. Training may also add an instrument to make bigger consciousness among the various stakeholders.

Conclusion:
The study found availability of information (0.00*), mass media exposure (0.02**), risk orientation (0.06***), innovativeness (0.09***) and farm asset (0.00*) were the signi cant factors of adoption of seed drill whereas, operational land holding (0.01**), frequency of mass media use (0.01**) and innovativeness (0.00**) were signi cant factors for zero tillage adoption. Evaluation of seed drill and ZT technology exhibited positive impact on all aspects of agronomic ( eld capacity, seed rate, labour, germination, establishment, plant population and nutrients) as well as economics issues (BCR and Net Return).The e cacy of farm machinery showed that seed drill enhances yield at maximum level for the variety of HD2967 and saved seed rate by 27.71 kg/ha. Similarly zero tillage enhanced the maximum yield of HD 3059 by 10.08q/ha. Use of zero tillage reduced seed rate by 24.20 kg per ha in case of HD-2967 which was followed by 4.49 kg/ha and 1.79 kg/ha for HD 3086 and HD 3059. Thus, it reduced the cost of seed which, in turn, increased farmers' net income. The state-wise scenario showed that enhanced rate of income of the farmers could be obtained for use of farm machinery. Alfares and Duffuaa method referred economic problem (aggregate wt. 1823.11) was the most serious issue for up-scaling and outscaling of machinery. Majority of the farmers are resource-poor, Custom Hiring Centres (CHCs) should be established through Public Private Partnership (PPP), private entrepreneurs, co-operative basis, farmer's organizations and charitable trusts. Small and marginal farmers can also avail machinery from different state institutions which offer handsome subsidies on agricultural machinery procurement. Govt. guidelines towards designing of appropriate model of farm machineries should be made mandatory for access of small and marginal farmers. Further, for provision of credit facilities, Agriculture Machinery Banks can be a useful step support in direction. In addition, awareness and training programme will motivate the farmers for use of machineries which may contribute to the goal of doubling farmers' income by 2022-23. Increasing demand for farm machineries explores the opportunity for establishment of business models and entrepreneurial innovation. Besides, spill over effect of mechanization opens up the scope for development of animal husbandry, dairying, sheries sector too. So it can be concluded that adoption of seed cum fertilizer drill and zero tillage had positive socio-agro-economic impact on small holder farmers' livelihood and the sustainability of this impact can be ensured through support of CHC, Government and rural nancial institutions.