Energy budgeting and greenhouse gas emission under different cropping sequences in the North Western Plain Zone of Uttar Pradesh, India

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L. R. Meena¹ , Devendra Kumar² , S. A. Kochewad³ , Anjali⁴

¹Division of Cropping Systems and Resource Management, ICAR-Indian Institute of Farming Systems Research, Modipuram, Uttar Pradesh -250 110, India

²Division of Organic Agriculture Systems,ICAR-Indian Institute of Farming Systems Research, Modipuram, Uttar Pradesh -250 110, India

³School of Soil Stress Management (SSSM), ICAR- National Institute of Abiotic Stress Management, Malegam, Baramati, Pune, Maharashtra- 413 115, India

⁴Mahatma Gandhi Medical College and Hospital, Jaipur, Rajasthan- 302033, India

Corresponding Author Email: laxamn.meena@icar.gov.in

DOI : https://doi.org/10.51470/AGRI.2024.3.3.21

Abstract

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Introduction

Energy inputs are crucial for crop production and the increased use of fossil fuel energy resources has become important to both developed and developing countries. In India, energy use in agriculture has been increasing since the green revolution in the late sixties with increasing use of high-yielding varieties, synthetic fertilizers, agrochemicals, herbicides, machinery as well as diesel and electricity in farm operations leading to higher productivity. The era of low-priced energy is now ending and energy conservation has become more vital because rising cost of energy sources. Therefore, relation between crop production and energy use is very close. The energy inputs are inevitable features for fruitful crop growing in Indo-Gangetic Plains because high energy requires crops are be cultivated in the area such as sugarcane, rice, wheat, potato, and oilseed crops. The availability of power on the farm is required more and more for enhancing crop productivity and profitability. Energy is used in every form of input viz. labor, seed, fertilizer, irrigation, and insecticides for plant protection, machinery used for various operations, and farm machinery is directly linked with technological progress made in India. In the present years, a worldwide energy crisis prevailing due to fuel shortages and high prices of petroleum-based products. The energy crisis in a country like India had an adverse effect on economic growth. Among the field crops, legumes and oilseeds involves having less energy requirements than other crops. Looking at crops like rice, wheat, maize, and sugarcane require higher energy inputs, mainly for their higher demands of irrigation and fertilizers coupled with cultural operations [27].The production of crops in a diversified manner with advanced yield targets cannot be achieved without the use of high-energy inputs. The increase in crop productivity also needed an additional supply of mechanical power along with an adequate supply of chemical energy[8].Hence, increasing additional cropping intensity over existing requires a higher supply of energy for inputs like labor, seed, fertilizers, irrigation, and farm implements for tillage, harvest, and threshing [43]. The production factors have encouraged an increase in energy inputs to maximize yields and minimize labor-intensive operations [32]. Hence, there is an urgent need to sustain the productivity of various crops in India through the inclusion of remunerative crops that are highly energy efficient. This can be possible by adding customary energy input i.e. human labor with substantial investments in farm machinery, irrigation, equipment, fertilizers, soil, and water conservation practices, etc. These inputs and methods represent various energies that need to be evaluated to ascertain their effectiveness and to know how to conserve them[44].Energy computing is necessary for the efficient management of scarce resources for improved crop production in the Indian scenario because the faster decline in natural resources and climate change are the major concerns. It would be better to ascertain a high energy efficient output system with low energy input requirement and that would be an economically viable and livelihood for the farmers of Uttar Pradesh in India. The greenhouse gas emissions (GHGE) are major contributors to climate change. Therefore, there is a need to select suitable crop and cropping sequences; these are lessening the production of greenhouse gases. Scientific management of available resources in the most judicious manner ensures food security protects the environment from sequestering GHGs and mitigates emissions to some extent. In high-intensified cropping systems pulses, oilseed, green manure crop dhaincha, and fodder crops should add to build up underground carbon, higher aerial biomass production results in the reduction in of GHG emissions through the addition of organic carbon in the soil [40].The farmyard manure (FYM) and vermicompost (VC) were used to meet the nutrient demand of the crops and cropping sequences. This is concurrent with the finding that the integration of sustainable crop practices and cropping systems could reduce energy use and thereby GHG emissions [4].The net greenhouse gas emission from the different cropping sequences varied due to the use of, organic manures (Farmyard manure, biofertilizers, and vermicompost) and crop residues, chemical fertilizers, pesticides, mechanical farm tools, and implements, and biofuel/fossil fuel (diesel/ petrol) operated machines were used under different cropping sequences. Whereas, biomass/farmyard manure and vermicompost incorporated into the soil served as a sink for carbon sequestration and aided in mitigating GHG emissions. Sequestration of carbon(C) in agricultural soil can be promoted with the application of organic manure, crop residues, and balanced nutrients as reported by [26].

Material and Methods

The purpose of this study was to determine the amount of energy ingested i.e. the amount of inputs and outputs used in different cropping sequences to make an economic analysis at ICAR-Indian Institute of Farming Systems Research, Modipuram, Uttar Pradesh for a period of 4 consecutive years (2017-18 to 2020-21). The experiment site (29^o 43′ N latitude and 77^o 23′ E longitude at an elevation of 237 m above mean sea level) is classified as semi-arid sub-tropical with monsoonal climate and sandy loam soil classified as Typicusforthents. During the experimental period, the site received total annual rainfalls of 730.3mm, 976.7mm, 824.3mm, and 897.5mm in 37, 44, 42, and 44 rainy days, respectively. More than 80% of rainfall was received through the southwest monsoon. The mean annual minimum and maximum temperatures ranged between 18.1 ^oC and 30.7 ^oC (2017-18), 17.4 ^oC and 30.5 ^oC (2018-19), 17.0 ^oC and 29.9 ^oC (2019-20) and 16.9 ^oC and 30.2 ^oC (2020-21). While the humidity stands at 72.7%, 72.7%, 74.2%, and 75.2% in respective years (Fig.1). The mean over a period of 4 years of sunshine hours were 6.3 and pan evaporation (mm) was higher (1575.45mm) than normal annual rainfall. The total soil organic carbon (TSOC) was 0.89% (CHNS analyzer). Available N (176.6kg/ha) was estimated by alkaline permanganate (KMnO4) method. Similarly, available soil P (29.3 kg/ha) was analyzed by [13] method and available soil K (194.7 kg/ha) was estimated byNH4OAc method.

Energy inputs estimations were based on the human labour requirement, use of different types of machinery and quantity of materials, energy calculation was computed though using of different input and output energy equivalents.

Manual energy (Em) was determined through using of following formula [12].

                                               Em= 1.96Nm TmMJ

 Where, Nm= Number of labour spent on a farm activity, Tm= useful time spent by a labour on a farm activity. h.

The energy coefficients used in the calculations are presented in Table1. The total manual labour was recorded in each operation with working hours, which was converted in man – hour. All other factors affecting manual energy were neglected. Mechanical energy input was evaluated by quantifying the amount of diesel fuel consumed during the tillage, sowing, threshing, and winnowing as prescribed methodology. The total time spent was also recorded during irrigation. Hence, for every farm operation, the diesel fuel energy input was determined by:

Ef= 56.31DMJ

Where, 56.31=unit energy value of diesel, MJ^-1; D = amount of diesel consumed, L.

Energy value for various input and output use in the experiments is given Table1.The total energy input for a given cropping system was calculated by adding the energy requirement for human labour, insecticides, seeds, irrigation, farm yard manure (FYM), Vermicompost (VC), fertilizers, and diesel, used in the individual cropping sequence .The energy output was calculated by accumulating the main products and by products produced from the different crops in cropping sequences. Subtracting input energy from output energy derived the net returns of energy. The output: input ratio was worked out by dividing the total energy used for raising the crop in the unit area (Table2). The energy input and output were computed as Mega Joule (MJ) by using different formulae. The energy efficiency (EE) and specific energy (SE) were worked out as per [6].

  The methodologies for estimating GHG emitted from the activities, the data are based on the methodologies provided in the agriculture section of the IPCC 2006 and IPCC 1996 Revised Guidelines. Country-specific emission coefficient (Tier III) and IPCC default coefficient was applied to get the total emission from each crop and cropping sequences. The Indian Institute of Farming Systems, Research, Modipuram, Meerut, Uttar Pradesh using the IPCC guidelines designed emission of greenhouse gases (GHGs) was estimated from the various crops. The data were worked out based on the already available predicted value, fertilizer usage, machinery usage and chemical usage for different crops. The greenhouse gas emissions from different cropping sequences were converted into carbon dioxide equivalent for their comparison.

Emission = A × EF

 Where,

Emission =Annual emission in units of kg of CO₂ eq. per farm

A = Activity data (kg of N used, liters of fuel used etc.)

EF-Emission

Factor = IPCC default emission factors or Country-specific emission factors. 

 Results and Discussion

Energy input consumed in the cropping sequences: Details of the energy equivalent (conversion coefficient) of all inputs used in the different cropping sequences are shown in (Table 3). The relative amount of energy inputs in all cropping sequences involved 12.28% to 21.01 % for human labor (HL), 11.17% to 22.71% energy incurred in tractor/ diesel consumption, energy consumed in chemical fertilizers ranged between from13.86% to 21.74%, input energy in the form of pesticides used from 4.86% to 32.18%, energy inputs used in supplied of irrigations were diverse from 7.71% to 27.87% and it depends upon the water requirement of each crop and growing duration. Energy consumed for using farmyard manure (FYM) to grow crops was found at 8.68% to 26.08%, VC (Vermicompost) supplied in the crop production required energy value to the tune from 5.26% to 26.31% under various cropping sequences. The crucial energy input like seed was used in crop production and required the highest in sugarcane-ratoon-wheat sequence from 5.83% to 54.65% in sorghum-mustard- green gram when compared with other cropping sequences. Similarly[24] found that inputs energy differed with the cropping sequences due to varying energy coefficients, the highest was being in rice-wheat-dhaincha (R-W-D) system (39.52×10³MJ ha^-1) and well ahead by sugarcane-ratoon wheat (S-R-W) system (37.33×10³MJha^-1) and  the lowest in Napier+cowpea/berseem cropping sequence(29.05×10³MJha^-1). Energy consumption for irrigation (71.199MJha^-1), fertilizer (47.992MJha^-1), tractor/diesel (28.115MJha^-1) and seed (20.944MJha^-1) were the prime factors responsible for putting the crops and cropping sequences in the highest position in terms of total energy requirement for the production main and byproducts.

System-wise input energy requirement: Energy inputs consumed in different cropping sequences as reported in Table 4. The computation of  energy-linked inputs that were used for the crop production revealed that the total energy inputs were highest in the case of the sugarcane-ratoon-wheat(S-R-W) system because of this cropping pattern has the maximum demand of all inputs (47769MJha^-1 year^-1) when comparison was made with other cropping sequences and the next cropping sequence which needed  bulk energy inputs was rice-wheat-dhaincha(R-W-D) i.e. (39522 MJ ha^-1 year^-1). Despite this,  the least input energy was spent in maize-berseem- black gram (25785MJha^-1 year^-1).The reason for the declined in inputs use energy was a selection of crops like berseem, and black gram as compared to high demanding energy inputs crops like sugarcane, rice, wheat and maize. Among the energy inputs, irrigation, fertilizers, and tractor/diesel are having primary importance for output production. The total input energy was highest spent towards irrigations (35.43%), fertilizers (23.89%), tractor/ diesel (14.00%) and seed (10.42%), respectively. In fact, irrigation input energy is required highest for the crop production because some crops have been involved in sequences they have high demands of irrigation than others. The cost of energy input of different crops and cropping sequences can be reduced by the selection of apposite sequences. The total annual energy inputs for the cropping sequences ranged from about 47769 MJha^-1 yea^-1 sugarcane-ratoon- wheat (S-R-W) to 25785MJha^-1 year^-1in maize- berseem- black gram (M-B-BG). It is generally, pragmatic that short span crops like legumes and oilseeds have lowest demand for  energy inputs than other crops viz. sugarcane, rice, maize, wheat etc.[41] described that wheat required more energy than other crops.

Note:S-R-W(Sugarcane-ratoon-wheat);R-W-D(Rice-wheat-dhaincha);P+M-C-O (Pigeonpea + maize-chickpea-okra);M-B-BG(Maize- berseem-black gram);S-M-GG( Sorghum-mustard- green gram);N+C+B (Napier+ cowpea/berseem)    

Wheat equivalent yield: The pooled analysis data indicated that the annual wheat equivalent yield of sugarcane-ratoon-wheat (S-R-W) sequence was significantly higher than rest of the crop rotations (Table 5). Since the sugarcane have the higher yield potential and market value than other crops which were included in different cropping sequences. The divergent crops were grown among the different cropping sequences, so that the main and byproducts yields of all crops were converted into wheat equivalent yield (WEY t ha^-1) on the basis of prevailing market price of each commodity. Similar results were also reported by [2] [37] in cropping sequences. The wheat grain prices were comparable parameter with other farm produces and their market worth in order to take the wheat values equivalent to other crops produces at par because productivity and market values were different among themselves. The wheat equivalent yield (WEY t/ha) was highest with sugarcane-ratoon-wheat cropping sequence (125.58t ha^-1year^-1) followed by Pigeonpea-chickpea-okra (29.02 t ha^-1 year^-1) and minimum wheat equivalent yield (WEY) was estimated with Napier + cowpea+ berseem (2.47tha^-1 year^-1). This might be due to under this cropping sequence consisted mainly by fodder crops rather than valuable crops. The equivalent wheat yield is governed by quantity of produce and its prevailing price and combined effect of these two ultimately led to maximum equivalent yield. This finding corroborates the observations of [23].

Energy outputs of cropping sequences: The total output energy was highest in sugarcane-ratoon-wheat cropping sequence (597.70 GJ ha^-1 year^-1) followed by rice-wheat-dhaincha (463.44GJha^-1 year^-1), maize- berseem- black gram (369.71GJha^-1 year^-1) and Napier + berseem/cowpea (333.50 GJ/ha) as detailed in Fig.2. The lowest energy output was shared by sorghum – mustard- green gram (319.53GJha^-1 year^-1) and pigeonpea+ maize- chickpea- okra (280.09GJha^-1 year^-1). However, the main output energy from the different cropping sequences has paid more than their byproduct’s outcome energy. The perceptible output energy wasproduced where sugarcane, rice, wheat, maize, and mustard crops were composed with other crops in the cropping sequences. The total energy production from the different crops and cropping systems varied from 25.25% to 11.85%. However, maximum total energy output was contributed by the sugarcane-ratoon- wheat sequence (4 years) as compared to other cropping sequences. The main season of production of high energy output from this system was due to greater potential of sugarcane alone than remaining crops which were included in the various configurations.

   Energy input-output relationship: The total inputs and outputs energy of different cropping sequences were varied depending up on the crops involved and the practices used (Table 6). However, resource inputs energy was disbursed highest in sugarcane- ratoon- wheat (47.33-×10³MJha^-1 year^-1) as compared to rest of the systems. The minimum input energy was used in Napier+cowpea/ berseem (29.05-×10³MJha^-1 year^-1) sequence because demands of the chemical fertilizers, irrigation, tractor/ diesel and seed were smaller than other cropping sequences. Apart from these, there were no use of insecticides and pesticides in case of fodder crops leading to decline in input energy consumption. Besides, during Kharif season requirement of irrigation was meagre and nutrients requirement of Napier hybrid bajra was met through intercropping of legumes (cowpea and berseem) concurrently in Kharif and rabi seasons. Similarly, output energy was generated highly in sugarcane-ratoon- wheat cropping sequence and followed by maize- berseem- black gram( 369.71×10³MJha^-1 year^-1), rice-wheat- dhaincha (367.61×10³MJha^-1 year^-1) and Napier + cowpea/ berseem(333.50×10³MJha^-1 year^-1). The lowest output energy was given by Pigeonpea + maize- chickpea- ladyfinger (okra) crop sequence (280.09-×10³MJha^-1 year^-1). The net energy was highest in sugarcane-ratoon-wheat (549.37×10³MJha^-1 year^-1) and thereafter in maize- berseem- black gram   (334.67×10³MJha^-1 year^-1) and rice-wheat- dhaincha (328.09×10³MJha^-1 year^-1). The system net energy was minimum under pigeonpea+ maize- chickpea-okra (249.77×10³MJha^-1 year^-1). This might be due to these crops are highly exhausted towards required inputs and lesser responsive to output energy led to less net energy in the system. The output energy was declined to the tune of 61.39%, 62.31 and 78.92% with maize-berseem- black gram, rice-wheat- dhaincha and Napier + cowpea/ berseem cropping sequences over to sugarcane-ratoon – wheat. Similarly, system net energy returns was declined in the tune of 64.15 %, 67.44 %, 80.44%, 89.77% and 119.95% with maize-berseem- black gram, rice- wheat- dhaincha, Napier + cowpea/berseem, sorghums-mustard- green gram and Pigeonpea+ maize- chickpea- okra cropping sequences over sugarcane-ratoon-wheat system. Similar results were also reported by [1] [42]. The output- input ratio was highest in sugarcane-ratoon-wheat system (12.60) and closely followed by Napier + cowpea/ berseem( 11.48),  sorghums- mustard- green gram(10.68), maize- berseem- black gram( 10.55) and lowest output-input ration was  in pigeonpea + maize- chickpea- okra( 8.23) and rice-wheat- dhaincha( 8.30). The energy profitability was computed by system net energy returns and system input energy consumed. Numerically, maximum energy profitability was accounted with sugarcane-ratoon-wheat (11.60) followed by Napier+ cowpea/berseem (10.48) and sorghum-mustard- green gram (9.63). The least energy profitability was in pigeonpea+ maize-chickpea- ladyfinger (8.23). The sugarcane- ratoon- wheat and maize- berseem- black gram systems were more efficient (1657.50 and 1421.96) than other cropping sequences due to high output energy and longest crop duration resulting in maximum times land occupied by the combination of  crops and cropping sequences. Similar, results were earlier reported by [21] in various cropping sequences.

Assessment of greenhouse gas emission from different cropping sequences 

The result exposed that under different cropping sequences, the rice-wheat system had produced the highest GHGs (1304 kg CO₂-e from 1800 m² area) among cropping sequences. Another important cropping sequence was sugarcane-ratoon-wheat (641 kg CO₂-e from 3500 m²area) which was responsible for higher emission of GHGs (641 kg CO₂-e from 1800 m²area). However, lower CO₂-e emission was valued from 400m² area where perennial fodder component hybrid bajra Napier planted in cropping sequences (33kg CO₂-e) which contributed up to 1% of the total GHGs emission). This might be due to the minimum use of chemical fertilizers and other inputs in fodder-based cropping sequence and the demand of plant nutrients by Napier grass was fulfilled through intercropping of cowpea and berseem in respective seasons (Kharif and rabi) seasons (Table 7). Among the cropping sequences, the contribution of greenhouse emissions by individual crops varied from 1% (Napier+cowpea/berseem) to 44% (rice). However, three major crops, namely rice, wheat and sugarcane were extremely responsible for the increasing production of global warming gases (CH4, CO2, CO, NH3 and N2O) Out of the 13 crops, three crops were found to highly responsible for the greenhouse gases emitted in terms of quantity (75%) whilst remaining 9 crops had emitted only (25%) of the total greenhouse gases in this study(Fig 3). This might be because they have produced more carbon and higher carbon sequestration. They are legumes and pulses crops in the cropping sequences and other crops where cereals result in less carbon sequestration into the soil and higher demand for chemical inputs. From South Africa  reported that Production of cereal crops accounts for 68% of national total field crops’ GHG emissions followed by other field crops (14%), legumes and oilseeds (11%) and vegetables (7%). Cultivations of maize, wheat and sugarcane result in highest commodity emissions.

 Conclusion

 The outcome revealed that energy consumption for irrigation (71.199MJ ha^-1), fertilizer( 47.992MJ ha^-1), tractor/diesel (28.115MJ ha^-1),and seed (20.944MJ ha^-1) were the prime factors responsible for putting the crops and cropping sequences in the highest position in terms of total energy requirement for the main and byproducts of sugarcane-ratoon- wheat cropping sequence. The crucial input like seed used in sugarcane required 54.65% energy alone as compared to other energy inputs. However, the highest input energy was used in the sugarcane-ratoon-wheat cropping sequence (47.33×10³MJ ha^-1) followed by rice- wheat – dhaincha (39.52×10³MJ ha^-1). The total output energy (597.70 GJ ha^-1 year^-1) and net energy returns (463.44 GJ ha^-1 year^-1) were highest with this sequence. Similarly, energy output efficiency (1657.50), output-input ratio (12.60), and wheat equivalent yield (125.58t ha^-1) were highest under the same system. However, it would be better to ascertain a high energy efficient output system with low energy input requirement that could be an economically viable and livelihood for the farmers of the Upper Gangetic Plains of India. 

Acknowledgement 

Authors are thankful to Director, ICAR-Indian Institute of Farming Systems Research, Modipuram, Meerut, Uttar Pradesh for providing the necessary infrastructural facilities for accomplishment this project.

Conflicts of interest

The authors declare no conflict of interest. The funding agency had no role in designing of this study or interpretation of data or in the writing of the manuscript, or in taking the decision to publish the results.

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