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Energy demand forecast for mechanized agriculture in rural India
ARTICLE IN PRESS Energy Policy 36 (2008) 2628– 2636
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Energy Policy journal homepage: www.elsevier.com/locate/enpol
Energy demand forecast for mechanized agriculture in rural India Debendra C. Baruah a,, Ganesh C. Bora b,1 a b
Department of Energy, Tezpur University, Tezpur 784028, Assam, India Precision Agricultural Technology Program, Oklahoma State University, Okmulgee, OK 74447, USA
a r t i c l e in f o
a b s t r a c t
Article history: Received 14 January 2008 Accepted 26 March 2008 Available online 7 May 2008
Though India has done well in agricultural development, the state of Assam in the northeastern region needs special attention for agricultural development to address several socio-economic issues and is a typical example of economically backward rural India. Agricultural development aiming at higher production would require mechanization and supply of sufficient energy is a prerequisite for mechanized agriculture. Rice is the major crop of Assam and the mechanization is at a nascent stage. The energy demand and supply scenarios with reference to some prospective mechanization strategies for rice crop are investigated in this study. Four strategic scenarios of mechanization including a baseline scenario incorporating some proven technologies are designed to assess the energy demands. The result of the analysis indicated that the demand for diesel would increase by more than 200% with an associated decrease in manpower by more than 80% and also 100% reduction of bullock power. The ‘‘availability index’’, which is the ratio of available human workers to its critical demand, indicated insufficiency of required human workers in almost all agro-climatic zones of Assam justifying the need for mechanization. Economic analysis considering the prevailing rate of input commodities also favors agricultural mechanization in Assam. & 2008 Elsevier Ltd. All rights reserved.
Keywords: Energy Mechanization Availability index
1. Introduction Energy has an influencing role in the development of key sectors of economic importance such as industry, transport and agriculture. This has motivated many researchers to focus their research on energy management. Energy has been a key input of agriculture since the age of subsistence agriculture. It is an established fact worldwide that agricultural production is positively correlated with energy input (Singh, 1999). This has also been reflected in Indian agriculture. The green revolution accelerated the growth of farm mechanization vis-a`-vis energy input and resulting productivity in India. But the scenario is not uniform throughout the country. There has been a great variation in the level of mechanization vis-a`-vis the level of energy input amongst the regions. The state of Assam, located in the northeastern part of India, has remained rural, agriculture being the main occupation in the rural areas. This is one of the economically backward states of India (Anonymous, 2005). On the basis of agro-climatic parameters, the state is divided into six agro-climatic zones. Nearly Corresponding author. Tel.: +91 3712 267007; mobile: +91 9435508563; fax: +91 3712 267005. E-mail addresses: [email protected] (D.C. Baruah), [email protected] (G.C. Bora). 1 Tel.: +1 918 293 4788; fax: +1 918 293 4658.
0301-4215/$ - see front matter & 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2008.03.030
76% of the state’s population depends on agriculture and allied occupations for their livelihood and about 74% of the total labor force of the state is engaged in agriculture (Bhattacharyya et al., 2001). In spite of having abundant favorable natural resources for crop production, the productivity level in the state is low. It is reported that the productivity of rice, which is a major crop of the state, is about 29% lower than the national average and 72% lower than that of the most developed state in the country, Punjab (Bhattacharyya et al., 2001; Mustafa, 2002). This lower level of productivity is due to lower level of inputs (Singh, 1999) and also due to lack of mechanization. Rice cultivation is one of the major economic activities, and improving the productivity of rice crop and rational use of inputs may lead to a boost in the economy of the state. This will require a suitable mechanization program. With rice primarily being a wetland crop, not many machines had been used earlier (Bora and Hansen, 2007). However, an in-depth analysis—aiming to boost rice crop production through prospective mechanization—is a prerequisite for any such attempt of mechanization. Properly planned mechanization could enhance crop productivity with economic uses of precious energy resources. There have been some specific studies showing the impact of mechanization on rice productivity (Arora et al., 2006; Chauhan et al., 2006; Baruah and Dutta, 2007). Arora et al. (2006) reported adverse effects of inadequate land preparation, inadequate irrigation and delayed transplanting on rice productivity while
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analyzing the results of a study of rice production in Punjab (India). According to their study, rice yield was declined up to 0.5 ton/ha due to delayed transplanting. The lack of mechanization is one of the causes of such delays in transplanting rice seedlings. Similar reductions were also reported due to inadequate land preparation and irrigation. In another study concerning energy management in rice cultivation in West Bengal state of India, Chauhan et al. (2006) reported that better use of power tillers and introduction of improved machinery could improve the efficiency of energy use and thereby improve the energy productivity of rice production system. Baruah and Dutta (2007) while investigating the energy use in relation to yield of rice in Assam (India) obtained similar results. Their study investigated 576 rice farms belonging to both non-mechanized and mechanized categories in Assam (India). The rice yield of mechanized farms was more than that of the non-mechanized farm. A positive correlation of the commercial energy input and rice yield was also reported by the study (commercial energy requirements increase due to increased level of mechanization). Mechanization brings technological changes and due to the technological changes, the resource demand would also change in comparison to the non-mechanization scenario. For example, introduction of power-driven machinery in place of manual and animal-powered implements would increase the demand of resources like machinery and diesel. Cost of operation is another important deciding factor for selection of mechanization options. There are several technological (machine type, nature and frequency of maintenance requirements, etc.) and economical parameters (rate of interest on investment, insurance, taxes, etc.) that influence the operational cost of machinery. Several standard norms are available for estimating the cost of farm operations. In India, the guidelines provided by the Bureau of Indian Standards (BIS) for estimation of cost of farm operations are practiced and, therefore, these guidelines are used for assessment of operational costs. The cost analysis can indicate the relative economic merits of mechanization options. In addition to cost estimation, forecasting of resource demands is also essential for strategic planning of farm mechanization. Forecasting is helpful for planning as well as for policy assessment. In a multi-sector economy, where there prevails competition for precious energy resources amongst different sectors like industry, transport, services and agriculture, rational forecast of energy demand helps to plan and thus supports unimpeded growth of a sector. Agriculture in Assam critically needs development. Mechanization is one of the essential inputs of agricultural development. In view of the above, the present study is undertaken with the following objectives: i. To assess the demand of energy resources for mechanized rice cultivation in the state of Assam in India. ii. To investigate the cost of farm operations with regard to some selected mechanization options. iii. To test the adequacy of locally available human resources to support higher rice production without causing timeliness penalty in different agro-climatic zones of the state.
2. Materials and methods The present study investigates the demand of energy resources in crop production under some specific levels of mechanization. The methodology for (i) selection of study area and type of crops, (ii) selection of mechanization strategies, (iii) assessment of energy demand and (iv) examining the adequacy of locally available human resources to support higher productivity are
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discussed. Further, comprehensive cost analyses of the selected mechanization scenarios are also done. These are discussed below. 2.1. Selection of study area and type of crops The state of Assam, which is considered for the study, is a backward region of the country—both economically and agriculturally. The state is in northeast corner of India and is divided into six agro-climatic zones. The availability of human resources and cultivable areas of six representative villages of each of the agroclimatic zones are considered for the study. Rice (Oryza sativa) is a major crop of the state and a mostly rice-based cropping system is followed. Therefore, the technology selection of the present investigation is based on rice grown in the state of Assam. 2.2. Selection of mechanization scenarios The crop production process can be conveniently divided into some distinct unit operations. Generally, the unit operations remain the same for all crops, with slight variation for some specific crops. The earlier investigations (Anonymous, 2001; Baruah et al., 2004; Singh et al., 1988) reported that the unit operations, such as land preparation, sowing or transplanting, irrigation, harvesting and threshing, are critical considering their higher share of energy demand. These operations are also critical because of the urgency to complete these operations in time in order to avoid timeliness penalty (Bector and Singh, 1999). Major technological variations with regard to the existing scenarios of rice cultivation in Assam are not observed amongst the different sub-regions of the state (Anonymous, 2001). However, there are too many modern options for performing these unit operations. Based on some recent studies (Anonymous, 2001; Baruah et al., 2004), some specific type of technology options are considered for the present study. Three sets of mechanization options comprising the improved technologies are considered as three strategic scenarios, viz., S1, S2 and S3. Another baseline scenario (S0) comprising the muscle power-operated traditional technologies is also considered to estimate the changes in demand as the mechanization progresses. The details of the technologies used in the strategic scenarios are presented in Table 1. 2.3. Machinery selection Power tillers and tractors are two common mechanical power sources in Indian agriculture. The shift from muscle power to mechanical power would result in an increased demand for power tillers (S1) and tractors (S2 and S3). The introduction of IC enginedriven self-propelled transplanters (Fig. 1) and self-propelled reaper harvesters (Fig. 2) was reported to be successful in Assam (Baruah, 2006a, b). Both these technologies are incorporated in S2. Scenario S3 incorporates a tractor-drawn reaper harvester and a tractor-drawn power thresher. The tractor-driven rice thresher is successfully tested in Assam for rice threshing (Fig. 3). The tractor is also used for transporting harvested crop from the fields to the storage place or to the nearby market (Fig. 4) and, therefore, used as an option for transportation (S2 and S3). 2.4. Assessment of energy demand The four resources, viz., human, animal, diesel and machinery, required to perform the selected farm operations are estimated from the work capacity of the specific technology. The details of the energy estimation for the unit operations are discussed below.
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Table 1 The list of technologies considered for four different mechanization strategies Operation
Scenario S0
Scenario S1
Scenario S2
Scenario S3
Primary tillage
Animal-drawn indigenous plough Animal-drawn indigenous plough Manual transplanting
Animal-drawn mould board plough Power tiller-drawn rotavator
Tractor-drawn disk harrow
Tractor-drawn disk harrow
Tractor-drawn cultivator
Tractor-drawn rotavator
Manual transplanting, transportation of seedling by power tiller trolley
Self-propelled rice transplanter, transportation of seedling by tractor trolley
Self-propelled rice transplanter, transportation of seedling by tractor trolley
Self-propelled reaper harvester and transporting by tractor trolley IC engine operated power thresher
Tractor-drawn reaper harvester and transporting by tractor trolley Tractor-operated power thresher
Puddling Transplanting
Irrigation Harvesting and handling Threshing
IC engine-driven centrifugal pump for all the scenarios Manual harvesting by sickle Manual harvesting by sickle and manual transporting and transporting by power tiller trolley Threshing by bullock treading Threshing by power tiller treading
Fig. 1. Operation of a self-propelled transplanter.
Fig. 3. A power thresher for rice crop.
Fig. 2. A self-propelled reaper harvester in the field.
Fig. 4. A tractor used in the transportation of harvested crop.
Time required to complete the required functions in a unit area (ha) is determined form the average work capacity of the respective machineries. The selected machineries were earlier tested to investigate their performances and such performance test data are considered for estimating their work capacity. The demand of human-hour, animal pair-hour, IC engine-hour, power tiller-hour and tractor-hour are estimated from the number of units required (as per performance test data) to complete the work of 1 ha of crop land and their respective engagement time in hours. The potential yield of most of the rice varieties in Assam
has been reported as 6 ton/ha (Anonymous, 1998). However, in the present study a yield of 5 ton/ha is considered for estimating the resource demand for threshing and handling. Rice crop requires standing water during most of its growing period. The water needs are met from rain and irrigation. The irrigation requirement varies based on rainfall pattern and soil conditions. In the present study three times irrigations (during the entire growing period of the crop with 15 cm depth of water application each time) are uniformly considered for all the strategies.
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The demand for diesel is estimated using the following relationship: D ¼ P sfc t lf
(1)
where D is the quantity of diesel required to perform an operation in unit area, liter; P is the size of the power source, kW; sfc is the specific fuel consumption, l/kWh; t is the duration of engagement in unit area, h; and lf is the load factor of the particular operation. It is assumed that a 26.11 kW tractor, 7.46 kW power tiller and 3.73 kW engine would perform the required unit operations. These sizes are considered based on the prevailing sizes used in Indian agriculture. For self-propelled transplanters and reaper harvesters, a 2.61 kW engine is considered. Three levels of loading conditions, viz., light (lf ¼ 0.4), medium (lf ¼ 0.6) and heavy (lf ¼ 0.8), are separately considered based on the nature of unit operations (Anonymous, 1996).
2.5. Examining the adequacy of locally available human resources Available adult workers and cultivable areas of six different villages under six agro-climatic zones of Assam are used to estimate the available human resources with the following considerations:
It is assumed that the crop will be grown following
recommended package and practices (Anonymous, 1998) and the targeted yield is 5 ton/ha. Out of the total adult population in the selected villages, 50% of males and 33% of females are available for farm work within the village. The villages are considered representative of the respective agro-climatic zones. With regard to timeliness of transplanting and harvesting operations, three critical durations, viz., 15, 20 and 30 days are used for three timeliness levels, viz., highly critical, moderately critical and liberally critical, respectively. The available human resources in a village for different timeliness levels are determined using the following relationship: AH ¼ cd tp
(2)
where AH is the human resource available for a farm operation, human-days; cd is the critical duration, days, and tp is the estimated adult population available for farm work.
The demands for human resources (human-days/ha) for completing transplanting and harvesting operations are estimated from the rate of work, as discussed in the previous section. This is then expressed for the whole village using the values of cultivable area of the village. To test the adequacy of the available human resources in a village to perform critical farm operations, an index is defined as follows: AI ¼
AH DH
(3)
where AI is the availability index and DH is the human resource required to perform a critical farm operation, which is estimated based on baseline strategy, human-days. Adequacy condition is fulfilled if AI is greater than unity. The required data of farm worker population and cultivated area of six villages of Assam are taken from a published report concerning rice production in Assam (Anonymous, 2001).
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2.6. Assessment of operational cost Costs of farm operations are estimated using the procedure given by the BIS (ISI, 1979). The fixed and variable cost components are separately estimated for each of the individual machinery operations. The fixed cost components of machinery operations are (i) depreciation, (ii) interest on investment, (iii) insurance and taxes and (iv) investment on shelter for machinery. The variable cost components considered for the analysis are (i) fuel and (ii) repair and maintenance. The costs on labor for machinery operation as well as for manual operations are separately considered based on the prevailing rate of labor charge and added to the total cost of operation. Similarly, the cost of operation of animal-powered implements is separately estimated based on the prevailing rate of hiring charges. The prevailing market prices of the machineries are considered as the purchase price required for estimating the fixed costs. The values include those for (a) useful life of the machineries, (b) annual uses, (c) salvage values, (d) rate of interest on investment on machineries, (e) insurance and tax rates, and (f) cost on shelter for machineries. The annual rate of repair and maintenance costs increases with the age of the machinery. In the present study, a realistic assumption is made to assess this cost component in the first year of use as per the guidelines of BIS standards (ISI, 1979). The price of diesel (at $0.82 per liter) is used to determine the cost for diesel required for machinery operation. The rates are considered as per the market values of March 2008. The major parameters considered for economic analysis are presented in Table 2.
3. Results and discussions The results of the present investigation are discussed below. 3.1. Requirement of resources for different levels of mechanization Requirements of six types of resources for five farm operations with four levels of mechanization are presented in Table 3. The level S0 is a non-mechanized scenario where farm operations except irrigation are performed by muscle power. Land preparation and threshing are two operations performed by animals. A pair of bullocks pull a plough and a human worker handles the plough and guides the animals to perform the land preparation operation. Threshing is performed by the bullock treading guided by the human worker. Thus, humans and animals are the two major energy sources required for animal-operated unit operations. Diesel is required for irrigation. Irrigation is uniformly considered for all levels of mechanization. Human intervention is required in all the operations, whereas bullocks are required in land preparation and threshing. Considering 1 ha of cropland under the S0 level, transplanting requires the highest amount of human days (31.50) followed by harvesting and handling (29.38), land preparation (27.67), threshing (18.75) and irrigation (5.63). Partial introduction of power tillers in land preparation (S1) would reduce the requirements of both humans and bullocks as compared to S0. However, the use of power tillers for 11.11 h/ha for land preparation would cause an additional demand for 18.31 l of diesel. Similarly, use of power tillers for threshing (25 h/ha) and transportation of seedlings (2 h/ha) as well as transportation of harvested crop (7 h/ha) would create additional demand for diesel. The use of tractors for land preparation (5.86 h/ha), transportation of seedlings (1 h/ha) and transportation of harvest (3 h/ha)
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Table 2 Values of some economic parameters considered for cost estimation of farm operations in rice cultivation Sl. no.
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Machineries
Specification
IC engine IC engine-driven centrifugal pump IC engine-driven power thresher Power tiller Power tiller-drawn rotavator Power tiller trolley Tractor Tractor-drawn cultivator Tractor-drawn disk harrow Tractor-drawn rotavator Tractor trolley Tractor-operated power thresher Self-propelled reaper harvester Self-propelled rice transplanter Residual value of the machineries Cost on interest on investment Cost of insurance and taxes Cost of shelter and housing of the machineries
Purchase price
Annual use
Useful life
Annual repair and maintenance cost
$
Hour
Year
% of purchase price
10,000 10,000 2500 8000 2400 3600 10,000 4000 3000 2400 3600 2500 2500 3000
10 10 8 10 8 12 10 10 10 8 12 8 8 6
3.8 3.8 10 3.8 7 2 3.2 6 6 7 2.5 10 4.9 6
3.73 kW 384.62 Matching with IC engine 102.56 Matching with IC engine 512.82 7.46 kW 3076.92 Matching with power tiller 641.03 Matching with power tiller 307.69 26.11 kW 8974.36 Matching with tractor 512.82 Matching with tractor 897.44 Matching with tractor 1794.87 Matching with tractor 897.44 Matching with tractor 1538.46 2.61 kW 2564.10 2.61 kW 3589.74 5% of the purchase price 11.5% of average purchase price 2% of average purchase price 1.5% of average purchase price
Table 3 Resources required for some critical farm operations of rice cultivation with four levels of mechanization Operations
Human-day/ha
Bullock pair-day/ha
Engine-h/ha
S0 Land preparation Transplanting Irrigation Harvesting and handling Threshing
27.67 31.50 5.63 29.38 18.75
23.92 0.00 0.00 0.00 6.25
0.00 0.00 45.00 0.00 0.00
S1 Land preparation Transplanting Irrigation Harvesting and handling Threshing
9.92 31.50 5.63 27.13 17.19
4.78 0.00 0.00 0.00 0.00
S2 Land preparation Transplanting Irrigation Harvesting and handling Threshing by small thresher
4.48 1.26 5.63 3.77 3.33
S3 Land preparation Transplanting Irrigation Harvesting and handling Threshing by large thresher
4.41 1.26 5.63 3.23 1.00
Power tiller-h/ha
Tractor-h/ha
Diesel, l/ha
0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00
0.00 0.00 45.90 0.00 0.00
0.00 0.00 45.00 0.00 0.00
11.11 2.00 0.00 7.00 25.00
0.00 0.00 0.00 0.00 0.00
18.31 1.65 45.90 5.77 20.50
0.00 0.00 0.00 0.00 0.00
0.00 9.09 45.00 7.14 26.67
0.00 0.00 0.00 0.00 0.00
5.86 1.00 0.00 3.00 0.00
32.15 9.23 45.90 15.03 36.27
0.00 0.00 0.00 0.00 0.00
0.00 9.09 45.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00
5.30 1.00 0.00 5.86 8.00
29.10 9.23 45.90 23.91 43.90
Note: S0: manual harvesting, manual transplanting, bullock treading; S1: manual harvesting, manual transplanting, power tiller used in land preparation and transportation; S2: self-propelled (SP) reaper harvesting, SP transplanting, small thresher, tractor used in land preparation and transportation; S3: tractor drawn reaper harvesting, SP transplanting, large thresher, tractor used in land preparation, harvesting, threshing and transportation.
along with the use of self-propelled transplanters (9.09 h/ha), selfpropelled harvesters (7.14 h/ha) and power threshers (26.67 h/ha) in the mechanization scenario S2 would further increase the demand of diesel, reducing the demand of human workers and completely replacing the bullock. In the mechanization scenario S3, a tractor-drawn rotavator is introduced for land preparation, instead of the conventional disk harrow–cultivator combination, reducing the time of tractor engagement as well as diesel requirements. However, the use of tractor-drawn reaper harvesters and tractor-driven power threshers is expected to increase the diesel requirements marginally over S2, even though the time of engagement for these two
operations in S3 is lower than in S2. The higher capacity of these machineries might have resulted in higher diesel requirements.
3.2. Changes of resource requirements with changing levels of mechanization The sum total of the resources required for all the farm operations considered in this study are presented in Fig. 5 and the percentage changes with respect to S0 are presented in Table 4. As the level of mechanization progresses from S0 to S3, the demand for human workers decreases by about 19% in S1, 84% in S2 and 86%
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Human-day/ha
Bullock pair-day/ha
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Diesel, l/ha
160 140
Resources, units/ha
120 100 80 60 40 20 0 S0
S1
S2
S3
Mechanization scenarios Fig. 5. Estimated resource requirement at different mechanization scenarios.
Table 4 Percentage changes of three types of resource requirements with reference to nonmechanized scenario S0
Table 5 Projected demand for the state in different mechanization scenarios S0
Human-day Bullock pair-day Diesel, l
S1
S2
S3
19.10 84.17 +100.28
83.64 100.00 +201.27
86.25 100.00 +230.54
in S3 (Table 4). Similarly, decreases in the requirements of bullock by about 84% in S1 and 100% in S2 as well as in S3 are noticed. Such a decrease in the demand for muscle power is associated with an increase in the requirements of diesel by about 100% in S1, 201% in S2 and 231% in S3 compared to the non-mechanized scenario S0.
S1
S2
Human-day Bullock pair-day Engine-hour Power tiller-hour Tractor-hour Diesel, l
Winter rice area: 1,743,320 ha (in million units) 197 159 32 53 8 0 78 78 153 0 79 0 0 0 17 80 161 242
Human-day Bullock pair-day Engine-hour Power tiller-hour Tractor-hour Diesel, l
Summer rice area: 174,970 ha 20 16 5 1 8 8 0 8 0 0 8 16
3 0 15 0 2 24
S3
27 0 94 0 35 265
3 0 9 0 4 27
3.3. Projected demand of energy resources for the state Based on the total area under two major rice crops, the resource demands for the state of Assam are estimated and presented in Table 5. The resource requirements for the nonmechanized baseline scenario are estimated as 217 million human-days and 58 million bullock pair-days for the two major crops. In addition, 88 million liters of diesel would also be required to provide three times irrigation during entire growing oeriod of the crop. The projected demand for a mixed type of technologies (S2) to grow rice crops is estimated as 35 million man-days and 266 million liters of diesel. The diesel would be required to run 188 million machinery hours including 19 million hours of tractor operation. The increasing demand for diesel in the agricultural sector is already becoming a prime issue in India. The country, depending on export for more than 70% of petroleum requirements, has initiated new and alternative searches for energy. Renewable energy from biomass resources is one of the priority areas for the Government of India. The possibilities to produce farm-level renewable energy to support the selected technologies may be explored in the agriculture of Assam. The thermal conversion of crop residue to produce producer gas may supplement conventional fossil fuel for stationary operations like threshing and
irrigation. However, for operations like land preparation, transplanting and harvesting, which need mobile power sources production of farm-level biodiesel, may be planned without affecting the prospect of food production. However, the extent of techno-economic feasibility needs to be studied before practical implementation.
3.4. Availability index The availability indices of farm workers during two most critical farm operations covering six agro-climatic zones of Assam are presented in Table 6. These two operations are highly sensitive to timeliness penalty and, therefore, these are considered for the present study. The indices are estimated based on the nonmechanized baseline scenario and the results are the projections of six representative villages. In the Upper Brahmaputra Valley Zone and North Bank Plain Zone, the scarcity of farm workers is predicted up to the LC level of timeliness (i.e., 30 days) as the values of AI are less than unity at all levels for both the operations. Thus, transplanting and harvesting operations could not be completed with the available manpower in these two zones even if a 30-day time period each is
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Table 6 Availability indices of farm worker in different agro-climatic zones of Assam Zone
Timeliness level
Availability index Transplanting
Harvesting
Upper Brahmaputra Valley Zone
HC MC LC
0.46 0.61 0.92
0.49 0.66 0.99
Central Brahmaputra Valley Zone
HC MC LC
0.54 0.72 1.07
0.58 0.77 1.15
North Bank Plain Zone
HC MC LC
0.43 0.57 0.86
0.46 0.61 0.92
Hill Zone
HC MC LC
0.99 1.31 1.97
1.06 1.41 2.11
Lower Brahmaputra Valley Zone
HC MC LC
0.64 0.86 1.29
0.69 0.92 1.38
Barak Valley Zone
HC MC LC
1.25 1.66 2.49
1.34 1.78 2.67
For all zones together
HC MC LC
0.57 0.77 1.15
0.62 0.82 1.23
HC: highly critical, MC: moderately critical; LC: liberally critical.
allowed for completion of these operations. Similar conditions are also expected to occur in the Central and Lower Brahmaputra Valley Zones up to 20 days’ durations each (HC and MC) of completion time for transplanting and harvesting. However, Hill Zone and Barak Valley Zone would have adequate manpower to perform these operations even if the operations become highly critical and need to be completed within 15 days. While the indices are calculated for the state taking all zones together, inadequacy of available human workers is noticed up to moderately critical levels of timeliness for both transplanting and harvesting operations. The required human workers for the critical farm operations are estimated based on a non-mechanized scenario. As discussed earlier, the demand would reduce if the operations were mechanized. Timely completion of these operations is essential to ensure higher production and also to prevent losses (Arora et al., 2006; Bector and Singh, 1999). Thus, the results of this study favor mechanization of these operations.
3.5. Cost analysis The costs of operations for land preparation, irrigation, transplanting, harvesting (including handling) and threshing have been separately estimated considering the costs of (i) hired charges of farm workers, (ii) hired charges of working animals, (iii) machinery ownership cost, (iv) machinery maintenance cost and (v) cost of diesel for machinery operations. The details of the estimated costs are presented in Table 7. The total operational costs ($/ha) are found as 491, 435, 375 and 403 for S0, S1, S2 and S3, respectively. Compared to the non-mechanization scenario (i.e., S0), the reduction of operational costs for S1, S2 and S3 is found as 11%, 24% and 18%, respectively.
In the non-mechanization S0 scenario, the major portion of the operational cost (more than 90% of the total cost) is spent on engagement of human workers and animal power. Similarly, the partial mechanization scenario (S1) also pays about 59% of the total operational cost for engagement of humans and animals. On the other hand, the shares of human and animal power costs in mechanized scenarios are less (13% for S2 and 10% for S3), as major cost contributions come from diesel and machinery in these mechanized scenarios. Thus, the operational cost of mechanized farming is dominated by diesel and machinery prices, whereas non-mechanized farming is dominated by prices of muscle power. The operation-wise costs are also estimated. The machinery operation costs are estimated using two components, viz., (i) sum total of ownership (fixed cost) and maintenance cost and (ii) diesel cost. The ownership and maintenance costs of machineries are found as $8.71, $100.68, $213.97 and $238.48 of the four scenarios S0, S1, S2 and S3, respectively. The quantities of diesel requirements for each operation under all the selected mechanization scenarios are determined and discussed earlier. Estimated costs on diesel are found as $37.74, $75.59, $113.71 and $124.76 for S0, S1, S2 and S3, respectively. While investigating the operation-wise cost, it was found that land preparation with animal ploughs (S0) is the costliest while disk harrow–cultivators (S2) is the cheapest with values of $193.64/ha and $63.34/ha, respectively, amongst the four different options. Longer duration of engagement associated with higher charges for muscle power (human and animal power) is the cause for higher cost of land preparation in S0. The type of machinery also affects the cost of operation. This is reflected from cost comparison between S2 and S3. A tractor-drawn rotavator is considered in S3, whereas the S2 scenario considers cultivators for land preparation. The higher cost of land preparation in S3 is due to higher ownership cost (i.e., higher purchase price) and repair maintenance cost (i.e., presence of high-speed rotary components) of tractor-drawn rotavators. Similarly, the higher cost of threshing operation is attributed to the larger-capacity tractor-drawn power thresher used in S3. The quality of work achieved by different options are not analyzed in the present study, which could justify the higher cost of tractor-drawn rotavators and tractor-operated power threshers. As mentioned earlier, some fixed charges as per the prevailing rates are considered in the present study for estimation of the operational costs. These charges may get modified through the influences of three broad areas. First, the Government’s economic policy conducive to promote farm mechanization could reduce the interest rates, taxes, etc., which in turn influence machinery ownership cost. Second, technological advancement could (i) reduce the requirements of repair–maintenance, (ii) cut down the purchase price through simplified manufacturing and (iii) reduce the diesel cost through improvement of fuel efficiency. Third, increasing the annual operational use through the provision of custom hiring, etc. would also cut down the fixed cost per hour. Moreover, regulation for promoting manufacturing and marketing of standard and quality farm machinery through the provision of financial incentives could also ensure reduction of operational cost. This is essential because the farm machinery manufacturing industry is growing in India at an accelerated pace and India has several recognized testing and certifying institutes. Overall, with the prevailing rates of labor, diesel and machinery, mechanization of rice cultivation in Assam is cheaper than non-mechanized farming. Thus, both shortage of farm workers and its higher costs favor farm mechanization in Assam. However, considering the backwardness of the region, some specific issues need to addressed. The Government has already some forms of subsidy for farm mechanization. Instead of a blanket subsidy,
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Table 7 Details of cost of farm operations of four scenarios Operation
S0 Land preparation Transplanting Irrigation Harvesting Threshing Total S1 Land preparation Transplanting Irrigation Harvesting and handling Threshing Total S2 Land preparation Transplanting Irrigation Harvesting Threshing Total S3 Land preparation Transplanting Irrigation Harvesting Threshing Total
Cost ($/ha) of Manual worker
Animal power
Total human and animal
70.96
122.69
193.64
80.77 0.00 80.77 14.42 0.00 14.42 75.32 0.00 75.32 48.08 32.05 80.13 289.55 (59) 154.74 (32) 444.28 (91)
Self-propelled machinery operation
Power tiller operation
Tractor operation
Total machinery operational and ownership
0
0
0
0.00
0 8.71 0 0 8.71 (2)
0 0 0 0 0.00 (0)
0 0 0 0 0.00 (0)
0.00 8.71 0.00 0.00 8.71 (2)
Diesel
0
Total cost
193.64 (40)
0 37.74 0 0 37.74 (8)
80.77 60.88 75.32 80.13 490.74
(17) (12) (15) (16) (100)
25.42
24.50
49.92
0
38.34
0
38.34
15.02
103.29 (24)
80.77 14.42 69.55
0.00 0.00 0.00
80.77 14.42 69.55
0 8.71 0
3.43 0.00 11.99
0 0
3.43 8.71 11.99
1.35 37.66 4.73
85.55 (20) 60.80 (14) 86.27 (20)
0 8.71 (2)
38.21 91.97 (21)
0 0.00 (0)
44.08 234.25 (54)
0.00 24.50 (6)
44.08 258.74 (59)
11.49
0.00
11.49
3.23 14.42 9.66 8.55 47.36 (13)
0.00 0.00 0.00 0.00 0.00 (0)
3.23 14.42 9.66 8.55 47.36 (13)
11.32
0
11.32
3.23 14.42 8.29 2.56 39.82 (10)
0 0 0 0 0.00 (0)
3.23 14.42 8.29 2.56 39.82 (10)
0 67.84 8.71 37.33 59.86 173.75 (46)
0.00 67.17 8.71 0.00 0.00 75.88 (19)
38.21 100.68 (23)
0
25.47
0 0 0 0.00 (0)
3.69 71.53 0 8.71 11.07 48.40 0 59.86 40.23 (11) 213.97 (57)
0
35.23
0 0 0 0 0.00 (0)
25.47
35.23
3.69 70.86 0 8.71 49.26 49.26 74.42 74.42 162.60 (40) 238.48 (59)
16.82 99.11 (23) 75.59 (17) 435.01 (100)
26.38
63.34 (17)
7.58 82.34 37.66 60.80 12.33 70.40 29.76 98.17 113.71 (30) 375.04
23.88
(22) (16) (19) (26) (100)
70.42 (17)
7.57 81.67 (20) 37.66 60.80 (15) 19.62 77.17 (19) 36.02 113.01 (28) 124.76 (31) 403.06 (100)
Figures in parenthesis indicates percentage of respective total.
technological and economical performances should be considered while deciding such subsidy programs. Another characteristic feature of the state is the lack of machinery manufacturing facility. Higher prices are paid by farm machinery customers of Assam for the transported machinery manufactured elsewhere. For relatively heavier and bulky machinery the cost differences could be substantial. Therefore, provision of local manufacturing could reduce the burden on the farmers of Assam. Finally, a mechanization strategy aiming to promote agricultural development in Assam should take into consideration the forecasted energy demand and plan accordingly.
4. Conclusions
Mechanization would reduce the demand of humans and
animals with associated increases in the demand of diesel and machinery in rice cultivation in Assam. As the level of mechanization progresses, the demand for human workers decreases up to 86% in comparison to a non-mechanized scenario. A decrease in the requirements of bullocks up to 100% is forecasted. Such a decrease in the demand for muscle power is associated with an increase in the requirements of diesel by up to 231% compared to the non-mechanized scenario. Human resources are inadequate in most of the regions to complete transplanting and harvesting operations in time. This
indicates the needs of transplanter and harvester machineries for these operations. Considering the area under rice crop, the resource requirements for the non-mechanized baseline scenario are estimated as 217 million human-days and 58 million bullock pair-days. In addition, the 88 million liters of diesel would also be required to provide three times irrigation during entire growing period of the crop. The projected mechanized demands to grow rice crops with a specific set of tested machineries are estimated as 35 million man-days and 266 million liters of diesel, 188 million machinery hours including 19 million hours of tractor operation. The operational costs ($/ha) for the three strategic mechanization scenarios are 435, 375 and 403, which are lesser than the cost of non-mechanized scenarios (491) by 11%, 24% and 18%, respectively. In the non-mechanization scenario, more than 90% of the total cost is spent on muscle power, whereas about 59% of the total operational cost is spent for muscle power in the partial mechanized scenario. Machinery ownership and machinery operation including diesel are the major costs for the two mechanization scenarios (87% and 90% of the total operational cost) considered in the present study. Major cost contributions come from diesel and machinery in both the mechanization options. Technological advancement of machinery manufacturing, policy incentives to encourage
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manufacturing of quality machinery and some social changes of farm machinery operation (to increase annual use) would reduce the operational cost. Forecasted energy demand along with results of cost analysis would be a guiding tool for strategic mechanization and hence agricultural development in Assam.
Acknowledgement The authors are thankful to the Head of the Department, Agricultural Engineering, Assam Agricultural University, Jorhat, Assam, India, for providing some mechanization information for the study. References Anonymous, 1996. Energy Digest: Report of All India Co-ordinated Research Project on Energy Requirements in Agricultural Sectors. Department of Farm Power and Machinery, Punjab Agricultural University, Ludhiana, India. Anonymous, 1998. Package of Practices for Kharif Crops of Assam. A joint publication of the Department of Agriculture, Government of Assam and Assam Agricultural University, Jorhat. Anonymous, 2001. Energy Use Scenario and Future Demand for Crop Production in Assam. Final Report of All India Co-ordinated Research Project on Energy Requirements in Agricultural Sectors. Department of Agricultural Engineering, Assam Agricultural University, India. Anonymous, 2005. India’s Best & Worst States. India Today August 15, 30–49.
Arora, V.K., Gajri, P.R., Uppal, H.S., 2006. Puddling, irrigation, and transplantingtime effects on productivity of rice–wheat system on a sandy loam soil of Punjab, India. Soil & Tillage Research 85, 212–220. Baruah, D.C., 2006a. Technical Bulletin on Mechanization of Paddy Harvesting in Assam. Department of Agricultural Engineering, Assam Agricultural University, India. Baruah, D.C., 2006b. Technical Bulletin on Mechanization Paddy Transplanting in Assam. Department of Agricultural Engineering, Assam Agricultural University, India. Baruah, D.C., Dutta, P.K., 2007. An investigation into the energy use in relation to yield of rice (Oryza sativa) in Assam (India). Agriculture, Ecosystem and Environment 120, 185–191. Baruah, D.C., Das, P.K., Dutta, P.K., 2004. Present status and future demand for energy for bullock-operated rice farms in Assam (India). Applied Energy 79, 145–157. Bector, V., Singh, S., 1999. Timeliness loss factor for different operations and major crops in Punjab. Journal of the Institute of Engineers of India 79, 32–35. Bhattacharyya, H.C., Borkakoti, K., Saikia, R.S., 2001. Agricultural profile in Assam. In: Thakur, AC. (Ed.), Agriculture in Assam. Assam Agricultural University, Jorhat, pp. 1–17. Bora, G.C., Hansen, G.K., 2007. Low cost mechanical aid for rice harvesting. Journal of Applied Sciences 7 (23), 3815–3818. Chauhan, N.S., Mohapatra, P.K.J., Pandey, K.P., 2006. Improving energy productivity in paddy production through benchmarking—an application of data envelopment analysis. Energy Conversion and Management 47, 1063–1085. ISI, 1979. Indian Standard Guide for Estimating Cost of Farm Machinery Operation. Bureau of Indian Standards, New Delhi. Mustafa, K., 2002. Land ownership patterns and yields in two Punjab. DAWN, 11 November 2002, Monday, Ramazan, 5, 1423. Singh, G., 1999. Relationship between mechanization and productivity in various parts of India. A paper presented during the XXXIV Annual Convention, Indian Society of Agricultural Engineers, CCSHAU, Hisar, December 16–18, 1999. Singh, S., Mittal, J.P., Singh, M.P., Bakhshi, R., 1988. Energy-use patterns under various farming systems in Punjab. Applied Energy 30, 261–268.
Contents lists available at ScienceDirect
Energy Policy journal homepage: www.elsevier.com/locate/enpol
Energy demand forecast for mechanized agriculture in rural India Debendra C. Baruah a,, Ganesh C. Bora b,1 a b
Department of Energy, Tezpur University, Tezpur 784028, Assam, India Precision Agricultural Technology Program, Oklahoma State University, Okmulgee, OK 74447, USA
a r t i c l e in f o
a b s t r a c t
Article history: Received 14 January 2008 Accepted 26 March 2008 Available online 7 May 2008
Though India has done well in agricultural development, the state of Assam in the northeastern region needs special attention for agricultural development to address several socio-economic issues and is a typical example of economically backward rural India. Agricultural development aiming at higher production would require mechanization and supply of sufficient energy is a prerequisite for mechanized agriculture. Rice is the major crop of Assam and the mechanization is at a nascent stage. The energy demand and supply scenarios with reference to some prospective mechanization strategies for rice crop are investigated in this study. Four strategic scenarios of mechanization including a baseline scenario incorporating some proven technologies are designed to assess the energy demands. The result of the analysis indicated that the demand for diesel would increase by more than 200% with an associated decrease in manpower by more than 80% and also 100% reduction of bullock power. The ‘‘availability index’’, which is the ratio of available human workers to its critical demand, indicated insufficiency of required human workers in almost all agro-climatic zones of Assam justifying the need for mechanization. Economic analysis considering the prevailing rate of input commodities also favors agricultural mechanization in Assam. & 2008 Elsevier Ltd. All rights reserved.
Keywords: Energy Mechanization Availability index
1. Introduction Energy has an influencing role in the development of key sectors of economic importance such as industry, transport and agriculture. This has motivated many researchers to focus their research on energy management. Energy has been a key input of agriculture since the age of subsistence agriculture. It is an established fact worldwide that agricultural production is positively correlated with energy input (Singh, 1999). This has also been reflected in Indian agriculture. The green revolution accelerated the growth of farm mechanization vis-a`-vis energy input and resulting productivity in India. But the scenario is not uniform throughout the country. There has been a great variation in the level of mechanization vis-a`-vis the level of energy input amongst the regions. The state of Assam, located in the northeastern part of India, has remained rural, agriculture being the main occupation in the rural areas. This is one of the economically backward states of India (Anonymous, 2005). On the basis of agro-climatic parameters, the state is divided into six agro-climatic zones. Nearly Corresponding author. Tel.: +91 3712 267007; mobile: +91 9435508563; fax: +91 3712 267005. E-mail addresses: [email protected] (D.C. Baruah), [email protected] (G.C. Bora). 1 Tel.: +1 918 293 4788; fax: +1 918 293 4658.
0301-4215/$ - see front matter & 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2008.03.030
76% of the state’s population depends on agriculture and allied occupations for their livelihood and about 74% of the total labor force of the state is engaged in agriculture (Bhattacharyya et al., 2001). In spite of having abundant favorable natural resources for crop production, the productivity level in the state is low. It is reported that the productivity of rice, which is a major crop of the state, is about 29% lower than the national average and 72% lower than that of the most developed state in the country, Punjab (Bhattacharyya et al., 2001; Mustafa, 2002). This lower level of productivity is due to lower level of inputs (Singh, 1999) and also due to lack of mechanization. Rice cultivation is one of the major economic activities, and improving the productivity of rice crop and rational use of inputs may lead to a boost in the economy of the state. This will require a suitable mechanization program. With rice primarily being a wetland crop, not many machines had been used earlier (Bora and Hansen, 2007). However, an in-depth analysis—aiming to boost rice crop production through prospective mechanization—is a prerequisite for any such attempt of mechanization. Properly planned mechanization could enhance crop productivity with economic uses of precious energy resources. There have been some specific studies showing the impact of mechanization on rice productivity (Arora et al., 2006; Chauhan et al., 2006; Baruah and Dutta, 2007). Arora et al. (2006) reported adverse effects of inadequate land preparation, inadequate irrigation and delayed transplanting on rice productivity while
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analyzing the results of a study of rice production in Punjab (India). According to their study, rice yield was declined up to 0.5 ton/ha due to delayed transplanting. The lack of mechanization is one of the causes of such delays in transplanting rice seedlings. Similar reductions were also reported due to inadequate land preparation and irrigation. In another study concerning energy management in rice cultivation in West Bengal state of India, Chauhan et al. (2006) reported that better use of power tillers and introduction of improved machinery could improve the efficiency of energy use and thereby improve the energy productivity of rice production system. Baruah and Dutta (2007) while investigating the energy use in relation to yield of rice in Assam (India) obtained similar results. Their study investigated 576 rice farms belonging to both non-mechanized and mechanized categories in Assam (India). The rice yield of mechanized farms was more than that of the non-mechanized farm. A positive correlation of the commercial energy input and rice yield was also reported by the study (commercial energy requirements increase due to increased level of mechanization). Mechanization brings technological changes and due to the technological changes, the resource demand would also change in comparison to the non-mechanization scenario. For example, introduction of power-driven machinery in place of manual and animal-powered implements would increase the demand of resources like machinery and diesel. Cost of operation is another important deciding factor for selection of mechanization options. There are several technological (machine type, nature and frequency of maintenance requirements, etc.) and economical parameters (rate of interest on investment, insurance, taxes, etc.) that influence the operational cost of machinery. Several standard norms are available for estimating the cost of farm operations. In India, the guidelines provided by the Bureau of Indian Standards (BIS) for estimation of cost of farm operations are practiced and, therefore, these guidelines are used for assessment of operational costs. The cost analysis can indicate the relative economic merits of mechanization options. In addition to cost estimation, forecasting of resource demands is also essential for strategic planning of farm mechanization. Forecasting is helpful for planning as well as for policy assessment. In a multi-sector economy, where there prevails competition for precious energy resources amongst different sectors like industry, transport, services and agriculture, rational forecast of energy demand helps to plan and thus supports unimpeded growth of a sector. Agriculture in Assam critically needs development. Mechanization is one of the essential inputs of agricultural development. In view of the above, the present study is undertaken with the following objectives: i. To assess the demand of energy resources for mechanized rice cultivation in the state of Assam in India. ii. To investigate the cost of farm operations with regard to some selected mechanization options. iii. To test the adequacy of locally available human resources to support higher rice production without causing timeliness penalty in different agro-climatic zones of the state.
2. Materials and methods The present study investigates the demand of energy resources in crop production under some specific levels of mechanization. The methodology for (i) selection of study area and type of crops, (ii) selection of mechanization strategies, (iii) assessment of energy demand and (iv) examining the adequacy of locally available human resources to support higher productivity are
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discussed. Further, comprehensive cost analyses of the selected mechanization scenarios are also done. These are discussed below. 2.1. Selection of study area and type of crops The state of Assam, which is considered for the study, is a backward region of the country—both economically and agriculturally. The state is in northeast corner of India and is divided into six agro-climatic zones. The availability of human resources and cultivable areas of six representative villages of each of the agroclimatic zones are considered for the study. Rice (Oryza sativa) is a major crop of the state and a mostly rice-based cropping system is followed. Therefore, the technology selection of the present investigation is based on rice grown in the state of Assam. 2.2. Selection of mechanization scenarios The crop production process can be conveniently divided into some distinct unit operations. Generally, the unit operations remain the same for all crops, with slight variation for some specific crops. The earlier investigations (Anonymous, 2001; Baruah et al., 2004; Singh et al., 1988) reported that the unit operations, such as land preparation, sowing or transplanting, irrigation, harvesting and threshing, are critical considering their higher share of energy demand. These operations are also critical because of the urgency to complete these operations in time in order to avoid timeliness penalty (Bector and Singh, 1999). Major technological variations with regard to the existing scenarios of rice cultivation in Assam are not observed amongst the different sub-regions of the state (Anonymous, 2001). However, there are too many modern options for performing these unit operations. Based on some recent studies (Anonymous, 2001; Baruah et al., 2004), some specific type of technology options are considered for the present study. Three sets of mechanization options comprising the improved technologies are considered as three strategic scenarios, viz., S1, S2 and S3. Another baseline scenario (S0) comprising the muscle power-operated traditional technologies is also considered to estimate the changes in demand as the mechanization progresses. The details of the technologies used in the strategic scenarios are presented in Table 1. 2.3. Machinery selection Power tillers and tractors are two common mechanical power sources in Indian agriculture. The shift from muscle power to mechanical power would result in an increased demand for power tillers (S1) and tractors (S2 and S3). The introduction of IC enginedriven self-propelled transplanters (Fig. 1) and self-propelled reaper harvesters (Fig. 2) was reported to be successful in Assam (Baruah, 2006a, b). Both these technologies are incorporated in S2. Scenario S3 incorporates a tractor-drawn reaper harvester and a tractor-drawn power thresher. The tractor-driven rice thresher is successfully tested in Assam for rice threshing (Fig. 3). The tractor is also used for transporting harvested crop from the fields to the storage place or to the nearby market (Fig. 4) and, therefore, used as an option for transportation (S2 and S3). 2.4. Assessment of energy demand The four resources, viz., human, animal, diesel and machinery, required to perform the selected farm operations are estimated from the work capacity of the specific technology. The details of the energy estimation for the unit operations are discussed below.
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Table 1 The list of technologies considered for four different mechanization strategies Operation
Scenario S0
Scenario S1
Scenario S2
Scenario S3
Primary tillage
Animal-drawn indigenous plough Animal-drawn indigenous plough Manual transplanting
Animal-drawn mould board plough Power tiller-drawn rotavator
Tractor-drawn disk harrow
Tractor-drawn disk harrow
Tractor-drawn cultivator
Tractor-drawn rotavator
Manual transplanting, transportation of seedling by power tiller trolley
Self-propelled rice transplanter, transportation of seedling by tractor trolley
Self-propelled rice transplanter, transportation of seedling by tractor trolley
Self-propelled reaper harvester and transporting by tractor trolley IC engine operated power thresher
Tractor-drawn reaper harvester and transporting by tractor trolley Tractor-operated power thresher
Puddling Transplanting
Irrigation Harvesting and handling Threshing
IC engine-driven centrifugal pump for all the scenarios Manual harvesting by sickle Manual harvesting by sickle and manual transporting and transporting by power tiller trolley Threshing by bullock treading Threshing by power tiller treading
Fig. 1. Operation of a self-propelled transplanter.
Fig. 3. A power thresher for rice crop.
Fig. 2. A self-propelled reaper harvester in the field.
Fig. 4. A tractor used in the transportation of harvested crop.
Time required to complete the required functions in a unit area (ha) is determined form the average work capacity of the respective machineries. The selected machineries were earlier tested to investigate their performances and such performance test data are considered for estimating their work capacity. The demand of human-hour, animal pair-hour, IC engine-hour, power tiller-hour and tractor-hour are estimated from the number of units required (as per performance test data) to complete the work of 1 ha of crop land and their respective engagement time in hours. The potential yield of most of the rice varieties in Assam
has been reported as 6 ton/ha (Anonymous, 1998). However, in the present study a yield of 5 ton/ha is considered for estimating the resource demand for threshing and handling. Rice crop requires standing water during most of its growing period. The water needs are met from rain and irrigation. The irrigation requirement varies based on rainfall pattern and soil conditions. In the present study three times irrigations (during the entire growing period of the crop with 15 cm depth of water application each time) are uniformly considered for all the strategies.
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The demand for diesel is estimated using the following relationship: D ¼ P sfc t lf
(1)
where D is the quantity of diesel required to perform an operation in unit area, liter; P is the size of the power source, kW; sfc is the specific fuel consumption, l/kWh; t is the duration of engagement in unit area, h; and lf is the load factor of the particular operation. It is assumed that a 26.11 kW tractor, 7.46 kW power tiller and 3.73 kW engine would perform the required unit operations. These sizes are considered based on the prevailing sizes used in Indian agriculture. For self-propelled transplanters and reaper harvesters, a 2.61 kW engine is considered. Three levels of loading conditions, viz., light (lf ¼ 0.4), medium (lf ¼ 0.6) and heavy (lf ¼ 0.8), are separately considered based on the nature of unit operations (Anonymous, 1996).
2.5. Examining the adequacy of locally available human resources Available adult workers and cultivable areas of six different villages under six agro-climatic zones of Assam are used to estimate the available human resources with the following considerations:
It is assumed that the crop will be grown following
recommended package and practices (Anonymous, 1998) and the targeted yield is 5 ton/ha. Out of the total adult population in the selected villages, 50% of males and 33% of females are available for farm work within the village. The villages are considered representative of the respective agro-climatic zones. With regard to timeliness of transplanting and harvesting operations, three critical durations, viz., 15, 20 and 30 days are used for three timeliness levels, viz., highly critical, moderately critical and liberally critical, respectively. The available human resources in a village for different timeliness levels are determined using the following relationship: AH ¼ cd tp
(2)
where AH is the human resource available for a farm operation, human-days; cd is the critical duration, days, and tp is the estimated adult population available for farm work.
The demands for human resources (human-days/ha) for completing transplanting and harvesting operations are estimated from the rate of work, as discussed in the previous section. This is then expressed for the whole village using the values of cultivable area of the village. To test the adequacy of the available human resources in a village to perform critical farm operations, an index is defined as follows: AI ¼
AH DH
(3)
where AI is the availability index and DH is the human resource required to perform a critical farm operation, which is estimated based on baseline strategy, human-days. Adequacy condition is fulfilled if AI is greater than unity. The required data of farm worker population and cultivated area of six villages of Assam are taken from a published report concerning rice production in Assam (Anonymous, 2001).
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2.6. Assessment of operational cost Costs of farm operations are estimated using the procedure given by the BIS (ISI, 1979). The fixed and variable cost components are separately estimated for each of the individual machinery operations. The fixed cost components of machinery operations are (i) depreciation, (ii) interest on investment, (iii) insurance and taxes and (iv) investment on shelter for machinery. The variable cost components considered for the analysis are (i) fuel and (ii) repair and maintenance. The costs on labor for machinery operation as well as for manual operations are separately considered based on the prevailing rate of labor charge and added to the total cost of operation. Similarly, the cost of operation of animal-powered implements is separately estimated based on the prevailing rate of hiring charges. The prevailing market prices of the machineries are considered as the purchase price required for estimating the fixed costs. The values include those for (a) useful life of the machineries, (b) annual uses, (c) salvage values, (d) rate of interest on investment on machineries, (e) insurance and tax rates, and (f) cost on shelter for machineries. The annual rate of repair and maintenance costs increases with the age of the machinery. In the present study, a realistic assumption is made to assess this cost component in the first year of use as per the guidelines of BIS standards (ISI, 1979). The price of diesel (at $0.82 per liter) is used to determine the cost for diesel required for machinery operation. The rates are considered as per the market values of March 2008. The major parameters considered for economic analysis are presented in Table 2.
3. Results and discussions The results of the present investigation are discussed below. 3.1. Requirement of resources for different levels of mechanization Requirements of six types of resources for five farm operations with four levels of mechanization are presented in Table 3. The level S0 is a non-mechanized scenario where farm operations except irrigation are performed by muscle power. Land preparation and threshing are two operations performed by animals. A pair of bullocks pull a plough and a human worker handles the plough and guides the animals to perform the land preparation operation. Threshing is performed by the bullock treading guided by the human worker. Thus, humans and animals are the two major energy sources required for animal-operated unit operations. Diesel is required for irrigation. Irrigation is uniformly considered for all levels of mechanization. Human intervention is required in all the operations, whereas bullocks are required in land preparation and threshing. Considering 1 ha of cropland under the S0 level, transplanting requires the highest amount of human days (31.50) followed by harvesting and handling (29.38), land preparation (27.67), threshing (18.75) and irrigation (5.63). Partial introduction of power tillers in land preparation (S1) would reduce the requirements of both humans and bullocks as compared to S0. However, the use of power tillers for 11.11 h/ha for land preparation would cause an additional demand for 18.31 l of diesel. Similarly, use of power tillers for threshing (25 h/ha) and transportation of seedlings (2 h/ha) as well as transportation of harvested crop (7 h/ha) would create additional demand for diesel. The use of tractors for land preparation (5.86 h/ha), transportation of seedlings (1 h/ha) and transportation of harvest (3 h/ha)
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Table 2 Values of some economic parameters considered for cost estimation of farm operations in rice cultivation Sl. no.
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Machineries
Specification
IC engine IC engine-driven centrifugal pump IC engine-driven power thresher Power tiller Power tiller-drawn rotavator Power tiller trolley Tractor Tractor-drawn cultivator Tractor-drawn disk harrow Tractor-drawn rotavator Tractor trolley Tractor-operated power thresher Self-propelled reaper harvester Self-propelled rice transplanter Residual value of the machineries Cost on interest on investment Cost of insurance and taxes Cost of shelter and housing of the machineries
Purchase price
Annual use
Useful life
Annual repair and maintenance cost
$
Hour
Year
% of purchase price
10,000 10,000 2500 8000 2400 3600 10,000 4000 3000 2400 3600 2500 2500 3000
10 10 8 10 8 12 10 10 10 8 12 8 8 6
3.8 3.8 10 3.8 7 2 3.2 6 6 7 2.5 10 4.9 6
3.73 kW 384.62 Matching with IC engine 102.56 Matching with IC engine 512.82 7.46 kW 3076.92 Matching with power tiller 641.03 Matching with power tiller 307.69 26.11 kW 8974.36 Matching with tractor 512.82 Matching with tractor 897.44 Matching with tractor 1794.87 Matching with tractor 897.44 Matching with tractor 1538.46 2.61 kW 2564.10 2.61 kW 3589.74 5% of the purchase price 11.5% of average purchase price 2% of average purchase price 1.5% of average purchase price
Table 3 Resources required for some critical farm operations of rice cultivation with four levels of mechanization Operations
Human-day/ha
Bullock pair-day/ha
Engine-h/ha
S0 Land preparation Transplanting Irrigation Harvesting and handling Threshing
27.67 31.50 5.63 29.38 18.75
23.92 0.00 0.00 0.00 6.25
0.00 0.00 45.00 0.00 0.00
S1 Land preparation Transplanting Irrigation Harvesting and handling Threshing
9.92 31.50 5.63 27.13 17.19
4.78 0.00 0.00 0.00 0.00
S2 Land preparation Transplanting Irrigation Harvesting and handling Threshing by small thresher
4.48 1.26 5.63 3.77 3.33
S3 Land preparation Transplanting Irrigation Harvesting and handling Threshing by large thresher
4.41 1.26 5.63 3.23 1.00
Power tiller-h/ha
Tractor-h/ha
Diesel, l/ha
0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00
0.00 0.00 45.90 0.00 0.00
0.00 0.00 45.00 0.00 0.00
11.11 2.00 0.00 7.00 25.00
0.00 0.00 0.00 0.00 0.00
18.31 1.65 45.90 5.77 20.50
0.00 0.00 0.00 0.00 0.00
0.00 9.09 45.00 7.14 26.67
0.00 0.00 0.00 0.00 0.00
5.86 1.00 0.00 3.00 0.00
32.15 9.23 45.90 15.03 36.27
0.00 0.00 0.00 0.00 0.00
0.00 9.09 45.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00
5.30 1.00 0.00 5.86 8.00
29.10 9.23 45.90 23.91 43.90
Note: S0: manual harvesting, manual transplanting, bullock treading; S1: manual harvesting, manual transplanting, power tiller used in land preparation and transportation; S2: self-propelled (SP) reaper harvesting, SP transplanting, small thresher, tractor used in land preparation and transportation; S3: tractor drawn reaper harvesting, SP transplanting, large thresher, tractor used in land preparation, harvesting, threshing and transportation.
along with the use of self-propelled transplanters (9.09 h/ha), selfpropelled harvesters (7.14 h/ha) and power threshers (26.67 h/ha) in the mechanization scenario S2 would further increase the demand of diesel, reducing the demand of human workers and completely replacing the bullock. In the mechanization scenario S3, a tractor-drawn rotavator is introduced for land preparation, instead of the conventional disk harrow–cultivator combination, reducing the time of tractor engagement as well as diesel requirements. However, the use of tractor-drawn reaper harvesters and tractor-driven power threshers is expected to increase the diesel requirements marginally over S2, even though the time of engagement for these two
operations in S3 is lower than in S2. The higher capacity of these machineries might have resulted in higher diesel requirements.
3.2. Changes of resource requirements with changing levels of mechanization The sum total of the resources required for all the farm operations considered in this study are presented in Fig. 5 and the percentage changes with respect to S0 are presented in Table 4. As the level of mechanization progresses from S0 to S3, the demand for human workers decreases by about 19% in S1, 84% in S2 and 86%
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Human-day/ha
Bullock pair-day/ha
2633
Diesel, l/ha
160 140
Resources, units/ha
120 100 80 60 40 20 0 S0
S1
S2
S3
Mechanization scenarios Fig. 5. Estimated resource requirement at different mechanization scenarios.
Table 4 Percentage changes of three types of resource requirements with reference to nonmechanized scenario S0
Table 5 Projected demand for the state in different mechanization scenarios S0
Human-day Bullock pair-day Diesel, l
S1
S2
S3
19.10 84.17 +100.28
83.64 100.00 +201.27
86.25 100.00 +230.54
in S3 (Table 4). Similarly, decreases in the requirements of bullock by about 84% in S1 and 100% in S2 as well as in S3 are noticed. Such a decrease in the demand for muscle power is associated with an increase in the requirements of diesel by about 100% in S1, 201% in S2 and 231% in S3 compared to the non-mechanized scenario S0.
S1
S2
Human-day Bullock pair-day Engine-hour Power tiller-hour Tractor-hour Diesel, l
Winter rice area: 1,743,320 ha (in million units) 197 159 32 53 8 0 78 78 153 0 79 0 0 0 17 80 161 242
Human-day Bullock pair-day Engine-hour Power tiller-hour Tractor-hour Diesel, l
Summer rice area: 174,970 ha 20 16 5 1 8 8 0 8 0 0 8 16
3 0 15 0 2 24
S3
27 0 94 0 35 265
3 0 9 0 4 27
3.3. Projected demand of energy resources for the state Based on the total area under two major rice crops, the resource demands for the state of Assam are estimated and presented in Table 5. The resource requirements for the nonmechanized baseline scenario are estimated as 217 million human-days and 58 million bullock pair-days for the two major crops. In addition, 88 million liters of diesel would also be required to provide three times irrigation during entire growing oeriod of the crop. The projected demand for a mixed type of technologies (S2) to grow rice crops is estimated as 35 million man-days and 266 million liters of diesel. The diesel would be required to run 188 million machinery hours including 19 million hours of tractor operation. The increasing demand for diesel in the agricultural sector is already becoming a prime issue in India. The country, depending on export for more than 70% of petroleum requirements, has initiated new and alternative searches for energy. Renewable energy from biomass resources is one of the priority areas for the Government of India. The possibilities to produce farm-level renewable energy to support the selected technologies may be explored in the agriculture of Assam. The thermal conversion of crop residue to produce producer gas may supplement conventional fossil fuel for stationary operations like threshing and
irrigation. However, for operations like land preparation, transplanting and harvesting, which need mobile power sources production of farm-level biodiesel, may be planned without affecting the prospect of food production. However, the extent of techno-economic feasibility needs to be studied before practical implementation.
3.4. Availability index The availability indices of farm workers during two most critical farm operations covering six agro-climatic zones of Assam are presented in Table 6. These two operations are highly sensitive to timeliness penalty and, therefore, these are considered for the present study. The indices are estimated based on the nonmechanized baseline scenario and the results are the projections of six representative villages. In the Upper Brahmaputra Valley Zone and North Bank Plain Zone, the scarcity of farm workers is predicted up to the LC level of timeliness (i.e., 30 days) as the values of AI are less than unity at all levels for both the operations. Thus, transplanting and harvesting operations could not be completed with the available manpower in these two zones even if a 30-day time period each is
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Table 6 Availability indices of farm worker in different agro-climatic zones of Assam Zone
Timeliness level
Availability index Transplanting
Harvesting
Upper Brahmaputra Valley Zone
HC MC LC
0.46 0.61 0.92
0.49 0.66 0.99
Central Brahmaputra Valley Zone
HC MC LC
0.54 0.72 1.07
0.58 0.77 1.15
North Bank Plain Zone
HC MC LC
0.43 0.57 0.86
0.46 0.61 0.92
Hill Zone
HC MC LC
0.99 1.31 1.97
1.06 1.41 2.11
Lower Brahmaputra Valley Zone
HC MC LC
0.64 0.86 1.29
0.69 0.92 1.38
Barak Valley Zone
HC MC LC
1.25 1.66 2.49
1.34 1.78 2.67
For all zones together
HC MC LC
0.57 0.77 1.15
0.62 0.82 1.23
HC: highly critical, MC: moderately critical; LC: liberally critical.
allowed for completion of these operations. Similar conditions are also expected to occur in the Central and Lower Brahmaputra Valley Zones up to 20 days’ durations each (HC and MC) of completion time for transplanting and harvesting. However, Hill Zone and Barak Valley Zone would have adequate manpower to perform these operations even if the operations become highly critical and need to be completed within 15 days. While the indices are calculated for the state taking all zones together, inadequacy of available human workers is noticed up to moderately critical levels of timeliness for both transplanting and harvesting operations. The required human workers for the critical farm operations are estimated based on a non-mechanized scenario. As discussed earlier, the demand would reduce if the operations were mechanized. Timely completion of these operations is essential to ensure higher production and also to prevent losses (Arora et al., 2006; Bector and Singh, 1999). Thus, the results of this study favor mechanization of these operations.
3.5. Cost analysis The costs of operations for land preparation, irrigation, transplanting, harvesting (including handling) and threshing have been separately estimated considering the costs of (i) hired charges of farm workers, (ii) hired charges of working animals, (iii) machinery ownership cost, (iv) machinery maintenance cost and (v) cost of diesel for machinery operations. The details of the estimated costs are presented in Table 7. The total operational costs ($/ha) are found as 491, 435, 375 and 403 for S0, S1, S2 and S3, respectively. Compared to the non-mechanization scenario (i.e., S0), the reduction of operational costs for S1, S2 and S3 is found as 11%, 24% and 18%, respectively.
In the non-mechanization S0 scenario, the major portion of the operational cost (more than 90% of the total cost) is spent on engagement of human workers and animal power. Similarly, the partial mechanization scenario (S1) also pays about 59% of the total operational cost for engagement of humans and animals. On the other hand, the shares of human and animal power costs in mechanized scenarios are less (13% for S2 and 10% for S3), as major cost contributions come from diesel and machinery in these mechanized scenarios. Thus, the operational cost of mechanized farming is dominated by diesel and machinery prices, whereas non-mechanized farming is dominated by prices of muscle power. The operation-wise costs are also estimated. The machinery operation costs are estimated using two components, viz., (i) sum total of ownership (fixed cost) and maintenance cost and (ii) diesel cost. The ownership and maintenance costs of machineries are found as $8.71, $100.68, $213.97 and $238.48 of the four scenarios S0, S1, S2 and S3, respectively. The quantities of diesel requirements for each operation under all the selected mechanization scenarios are determined and discussed earlier. Estimated costs on diesel are found as $37.74, $75.59, $113.71 and $124.76 for S0, S1, S2 and S3, respectively. While investigating the operation-wise cost, it was found that land preparation with animal ploughs (S0) is the costliest while disk harrow–cultivators (S2) is the cheapest with values of $193.64/ha and $63.34/ha, respectively, amongst the four different options. Longer duration of engagement associated with higher charges for muscle power (human and animal power) is the cause for higher cost of land preparation in S0. The type of machinery also affects the cost of operation. This is reflected from cost comparison between S2 and S3. A tractor-drawn rotavator is considered in S3, whereas the S2 scenario considers cultivators for land preparation. The higher cost of land preparation in S3 is due to higher ownership cost (i.e., higher purchase price) and repair maintenance cost (i.e., presence of high-speed rotary components) of tractor-drawn rotavators. Similarly, the higher cost of threshing operation is attributed to the larger-capacity tractor-drawn power thresher used in S3. The quality of work achieved by different options are not analyzed in the present study, which could justify the higher cost of tractor-drawn rotavators and tractor-operated power threshers. As mentioned earlier, some fixed charges as per the prevailing rates are considered in the present study for estimation of the operational costs. These charges may get modified through the influences of three broad areas. First, the Government’s economic policy conducive to promote farm mechanization could reduce the interest rates, taxes, etc., which in turn influence machinery ownership cost. Second, technological advancement could (i) reduce the requirements of repair–maintenance, (ii) cut down the purchase price through simplified manufacturing and (iii) reduce the diesel cost through improvement of fuel efficiency. Third, increasing the annual operational use through the provision of custom hiring, etc. would also cut down the fixed cost per hour. Moreover, regulation for promoting manufacturing and marketing of standard and quality farm machinery through the provision of financial incentives could also ensure reduction of operational cost. This is essential because the farm machinery manufacturing industry is growing in India at an accelerated pace and India has several recognized testing and certifying institutes. Overall, with the prevailing rates of labor, diesel and machinery, mechanization of rice cultivation in Assam is cheaper than non-mechanized farming. Thus, both shortage of farm workers and its higher costs favor farm mechanization in Assam. However, considering the backwardness of the region, some specific issues need to addressed. The Government has already some forms of subsidy for farm mechanization. Instead of a blanket subsidy,
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Table 7 Details of cost of farm operations of four scenarios Operation
S0 Land preparation Transplanting Irrigation Harvesting Threshing Total S1 Land preparation Transplanting Irrigation Harvesting and handling Threshing Total S2 Land preparation Transplanting Irrigation Harvesting Threshing Total S3 Land preparation Transplanting Irrigation Harvesting Threshing Total
Cost ($/ha) of Manual worker
Animal power
Total human and animal
70.96
122.69
193.64
80.77 0.00 80.77 14.42 0.00 14.42 75.32 0.00 75.32 48.08 32.05 80.13 289.55 (59) 154.74 (32) 444.28 (91)
Self-propelled machinery operation
Power tiller operation
Tractor operation
Total machinery operational and ownership
0
0
0
0.00
0 8.71 0 0 8.71 (2)
0 0 0 0 0.00 (0)
0 0 0 0 0.00 (0)
0.00 8.71 0.00 0.00 8.71 (2)
Diesel
0
Total cost
193.64 (40)
0 37.74 0 0 37.74 (8)
80.77 60.88 75.32 80.13 490.74
(17) (12) (15) (16) (100)
25.42
24.50
49.92
0
38.34
0
38.34
15.02
103.29 (24)
80.77 14.42 69.55
0.00 0.00 0.00
80.77 14.42 69.55
0 8.71 0
3.43 0.00 11.99
0 0
3.43 8.71 11.99
1.35 37.66 4.73
85.55 (20) 60.80 (14) 86.27 (20)
0 8.71 (2)
38.21 91.97 (21)
0 0.00 (0)
44.08 234.25 (54)
0.00 24.50 (6)
44.08 258.74 (59)
11.49
0.00
11.49
3.23 14.42 9.66 8.55 47.36 (13)
0.00 0.00 0.00 0.00 0.00 (0)
3.23 14.42 9.66 8.55 47.36 (13)
11.32
0
11.32
3.23 14.42 8.29 2.56 39.82 (10)
0 0 0 0 0.00 (0)
3.23 14.42 8.29 2.56 39.82 (10)
0 67.84 8.71 37.33 59.86 173.75 (46)
0.00 67.17 8.71 0.00 0.00 75.88 (19)
38.21 100.68 (23)
0
25.47
0 0 0 0.00 (0)
3.69 71.53 0 8.71 11.07 48.40 0 59.86 40.23 (11) 213.97 (57)
0
35.23
0 0 0 0 0.00 (0)
25.47
35.23
3.69 70.86 0 8.71 49.26 49.26 74.42 74.42 162.60 (40) 238.48 (59)
16.82 99.11 (23) 75.59 (17) 435.01 (100)
26.38
63.34 (17)
7.58 82.34 37.66 60.80 12.33 70.40 29.76 98.17 113.71 (30) 375.04
23.88
(22) (16) (19) (26) (100)
70.42 (17)
7.57 81.67 (20) 37.66 60.80 (15) 19.62 77.17 (19) 36.02 113.01 (28) 124.76 (31) 403.06 (100)
Figures in parenthesis indicates percentage of respective total.
technological and economical performances should be considered while deciding such subsidy programs. Another characteristic feature of the state is the lack of machinery manufacturing facility. Higher prices are paid by farm machinery customers of Assam for the transported machinery manufactured elsewhere. For relatively heavier and bulky machinery the cost differences could be substantial. Therefore, provision of local manufacturing could reduce the burden on the farmers of Assam. Finally, a mechanization strategy aiming to promote agricultural development in Assam should take into consideration the forecasted energy demand and plan accordingly.
4. Conclusions
Mechanization would reduce the demand of humans and
animals with associated increases in the demand of diesel and machinery in rice cultivation in Assam. As the level of mechanization progresses, the demand for human workers decreases up to 86% in comparison to a non-mechanized scenario. A decrease in the requirements of bullocks up to 100% is forecasted. Such a decrease in the demand for muscle power is associated with an increase in the requirements of diesel by up to 231% compared to the non-mechanized scenario. Human resources are inadequate in most of the regions to complete transplanting and harvesting operations in time. This
indicates the needs of transplanter and harvester machineries for these operations. Considering the area under rice crop, the resource requirements for the non-mechanized baseline scenario are estimated as 217 million human-days and 58 million bullock pair-days. In addition, the 88 million liters of diesel would also be required to provide three times irrigation during entire growing period of the crop. The projected mechanized demands to grow rice crops with a specific set of tested machineries are estimated as 35 million man-days and 266 million liters of diesel, 188 million machinery hours including 19 million hours of tractor operation. The operational costs ($/ha) for the three strategic mechanization scenarios are 435, 375 and 403, which are lesser than the cost of non-mechanized scenarios (491) by 11%, 24% and 18%, respectively. In the non-mechanization scenario, more than 90% of the total cost is spent on muscle power, whereas about 59% of the total operational cost is spent for muscle power in the partial mechanized scenario. Machinery ownership and machinery operation including diesel are the major costs for the two mechanization scenarios (87% and 90% of the total operational cost) considered in the present study. Major cost contributions come from diesel and machinery in both the mechanization options. Technological advancement of machinery manufacturing, policy incentives to encourage
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manufacturing of quality machinery and some social changes of farm machinery operation (to increase annual use) would reduce the operational cost. Forecasted energy demand along with results of cost analysis would be a guiding tool for strategic mechanization and hence agricultural development in Assam.
Acknowledgement The authors are thankful to the Head of the Department, Agricultural Engineering, Assam Agricultural University, Jorhat, Assam, India, for providing some mechanization information for the study. References Anonymous, 1996. Energy Digest: Report of All India Co-ordinated Research Project on Energy Requirements in Agricultural Sectors. Department of Farm Power and Machinery, Punjab Agricultural University, Ludhiana, India. Anonymous, 1998. Package of Practices for Kharif Crops of Assam. A joint publication of the Department of Agriculture, Government of Assam and Assam Agricultural University, Jorhat. Anonymous, 2001. Energy Use Scenario and Future Demand for Crop Production in Assam. Final Report of All India Co-ordinated Research Project on Energy Requirements in Agricultural Sectors. Department of Agricultural Engineering, Assam Agricultural University, India. Anonymous, 2005. India’s Best & Worst States. India Today August 15, 30–49.
Arora, V.K., Gajri, P.R., Uppal, H.S., 2006. Puddling, irrigation, and transplantingtime effects on productivity of rice–wheat system on a sandy loam soil of Punjab, India. Soil & Tillage Research 85, 212–220. Baruah, D.C., 2006a. Technical Bulletin on Mechanization of Paddy Harvesting in Assam. Department of Agricultural Engineering, Assam Agricultural University, India. Baruah, D.C., 2006b. Technical Bulletin on Mechanization Paddy Transplanting in Assam. Department of Agricultural Engineering, Assam Agricultural University, India. Baruah, D.C., Dutta, P.K., 2007. An investigation into the energy use in relation to yield of rice (Oryza sativa) in Assam (India). Agriculture, Ecosystem and Environment 120, 185–191. Baruah, D.C., Das, P.K., Dutta, P.K., 2004. Present status and future demand for energy for bullock-operated rice farms in Assam (India). Applied Energy 79, 145–157. Bector, V., Singh, S., 1999. Timeliness loss factor for different operations and major crops in Punjab. Journal of the Institute of Engineers of India 79, 32–35. Bhattacharyya, H.C., Borkakoti, K., Saikia, R.S., 2001. Agricultural profile in Assam. In: Thakur, AC. (Ed.), Agriculture in Assam. Assam Agricultural University, Jorhat, pp. 1–17. Bora, G.C., Hansen, G.K., 2007. Low cost mechanical aid for rice harvesting. Journal of Applied Sciences 7 (23), 3815–3818. Chauhan, N.S., Mohapatra, P.K.J., Pandey, K.P., 2006. Improving energy productivity in paddy production through benchmarking—an application of data envelopment analysis. Energy Conversion and Management 47, 1063–1085. ISI, 1979. Indian Standard Guide for Estimating Cost of Farm Machinery Operation. Bureau of Indian Standards, New Delhi. Mustafa, K., 2002. Land ownership patterns and yields in two Punjab. DAWN, 11 November 2002, Monday, Ramazan, 5, 1423. Singh, G., 1999. Relationship between mechanization and productivity in various parts of India. A paper presented during the XXXIV Annual Convention, Indian Society of Agricultural Engineers, CCSHAU, Hisar, December 16–18, 1999. Singh, S., Mittal, J.P., Singh, M.P., Bakhshi, R., 1988. Energy-use patterns under various farming systems in Punjab. Applied Energy 30, 261–268.