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Volume 7, Issue 5, October Issue - 2019, Pages:462-467


Authors: Aakash, Lalita Bhayal, N. S. Thakur, Sudheer Kumar Kirar, S. K. Choudhary
Abstract: A field experiment was conducted at research farm of IFSR Project, College of Agriculture, Indore, (M.P.) during Kharif 2018-19 in order to develop energy efficient sustainable maize production system. Maize production system had two factors which, laid out in factorial randomized block design and replicated thrice. Among the studied two factors, first factor was variety which consist two levels i.e. V1 (JM 216) and V2 (JM 218) and the second factor was N scheduling which consist six levels namely N1 to N6 which contained various proportion of N including foliar spray and scheduled at different stages. The results indicated that, nitrogen fertilizer share (62%) maximum of total input energy of production system. Among the levels, maize variety JM 218 and N scheduling N5 (33.3% N at sowing + 33.3% N at knee high stage + 1% N foliar spray at 40 DAS + 32.3% N at tasseling stage) were found promising since it recorded maximum value of output energy (115238 and 116306 MJ ha-1), net energy (103417 and 104468 MJ ha-1), energy efficiency (9.04 and 9.83), energy productivity (0.52 and 0.52 kg MJ-1), energy profitability (8.75 and 8.83) and energy intensity in economic terms (3.21 and 3.21 MJ Rs-1) respectively. It could be concluded that the maize variety JM 218 and N5, N scheduling would be more profitable compared to others combinations for developing an energy efficient sustainable production system.
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Full Text: 1 Introduction Maize (Zea mays L.) the “Queen of Cereals” is the third most important cereal crop after rice and wheat in the world.  Farmers involved in maize cultivation in Indian, is not less than 15 Million and its cultivation generates more than 650 million person-days employment at farming and its related business ecosystem levels (Anonymous, 2018). It is cultivated over 9.86 million ha area with annual production of 26.26 million tonnes and an average productivity of 2664 kg ha-1 in India in 2016-17 (Anonymous, 2017). Under the changing global climatic conditions and increasingly growing energy demands makes necessitate that development of a production system which utilizes less energy and produces more energy as output. Some varieties give good response to certain climatic conditions and effective management practices adds in exploring their fully genetic potential to produce more output. Many workers reported that the inputs such as fuel, electricity, machinery, seed, fertilizer and chemical take significant share of the energy supplies to the production system in modern agriculture among them the foremost important is careful management of nitrogen because on the one hand, in many cases its alone share more than 50% of total input energy used in a system and the other, it is the most imperative element for proper growth and development of plants. But if it is over-applied in many cases causes pollution of rivers, lakes and contributes to the emission of greenhouse gases. So over application is wasting of energy, money and needlessly worsening environmental problems (Pannell, 2016). In order to makes an energy efficient sustainable production system so it is important to assess the magnitude of varieties response, to nitrogen scheduling which demand less and produces more energy. 2 Materials and Methods The experiment was conducted at field of Integrated Farming System Research Project, College of Agriculture, Indore, (M. P.) during Kharif 2018-19. The topography of field was uniform with gentle slope. The experimental site was situated in Malwa Plateau agro-climatic zone in the Western Madhya Pradesh at an altitude of 555.5 m above mean sea level (MSL). It is located at latitude 22.43o N and longitude of 75.66o E. This region enjoys sub tropical semi arid type climate with an average annual rainfall of 964 mm, most of which is received during mid June to middle of September. The mean minimum and maximum temperature ranges from 7 oC to 23 oC and 23 oC to 43 oC, in winter and summer season, respectively. The monsoon activities during study year had commenced in 22nd Standard Meteorology Week (SMW) and continued till 38th and during crop growing period (05th July to 28th October 2018) 756.7 mm rain was received in 38 rainy days. The soil of the experimental field was clay in texture, having pH 7.60, EC 0.26 dSm-1, organic carbon 0.40 % with available N 188 kg ha-1, P 15.8 kg ha-1 and K 526 kg ha-1. The experiment consisted of two factors which made twelve treatment combinations laid out in factorial randomized block design and replicated thrice. The first factor was variety which consist two levels i.e. V1 (JM 216) and V2 (JM 218) and the second factor was N scheduling which consist six levels namely N1 - 33.3% N at sowing (S) + 33.3% N at knee high stage (KN) + 33.3% N at tasseling stage (T), N­2 - 50% N at S + 25% N at KN + 25% N at T, N­3 - 25% N at S + 50% N at KN + 25% N at T, N4 - 25% N at S + 25% N at KN + 25% N at T + 25% N at silking stage (Si), N5 - 33.3% N at S + 33.3% N at KN + 1% N foliar spray (FS) at 40 DAS + 32.3% N at T and N6 - 25% N at S + 25% N at KN + 1% N FS at 40 DAS + 25% N at T + 24% N at Si. Fertilizer was applied @ 120: 50: 30 N:P2O5:K2O kg ha-1 and other agronomical operations were followed as per recommendation. The amount of input and output was calculated per hectare and then these input data were multiplied with conversion factor of its energy equivalent (Table 1). The energy indices were determined by using standard equation (Devi et al., 2018). Energy efficiency=Total energy output (MJ ha-1)Total energy input (MJ ha-1) Energy profitability=Net energy (MJ ha-1)Total energy input (MJ ha-1) Specific energy (MJ kg-1)=Total energy input (MJ ha-1)Maize grain yield (kg ha-1) Energy productivity (kg MJ-1)=Maize grain yield (kg ha-1)Total energy input (MJ ha-1) Net energy ration (MJ ha-1)=Total energy output-Total energy input Energy intensity in economic terms (MJ Rs-1) =Total energy output (MJ ha-1)Cost of cultivation (Rs ha-1) The data on energetics was compiled and statically analyzed as per the method given in “A Handbook of Agricultural Statistics” by Chandel (2016) using computer programmed. Appropriate standard error (S.E.) and critical difference (C.D.) at 5 % levels were worked out for interpretation of result. 3 Results and Discussion 3.1 Share of input energy under common practices The common practices adopted under all the treatments showed in Table 2 revealed that the total input energy used in the production of maize i.e. 11805.7 MJ ha-1, out of this nitrogen fertilizer share maximum (62%) input energy followed by insecticides (10%) and diesel fuel (9%) (Figure 1). Fertilizer management of maize is very essential since it utilized almost 70% of total input energy used in production. Similar results emerge out to studies earlier carried out by Hosseinpanahi & Kafi (2012) and Lal et al. (2015) who reported that nitrogen fertilizer allocated the largest part of energy consumption among chemicals in crop production. The lowest input energy was used in herbicide (0.18%) followed by seed (1%). 3.2 Analysis of input output energy use in maize production  The input energy is the sum of all energy equivalent coefficients of different inputs which were used in the process of production. The data highlighted in Table 3 suggested that both varieties incurred equal input energy (11820 MJ ha-1) and with respect to factor; N scheduling, N6 (25% N at sowing + 25% N at knee high stage + 1% N foliar spray at 40 DAS + 25% N at tasseling   stage + 24% N at silking stage) needed maximum input energy (11850 MJ ha-1) followed by N5 (33.3% N at sowing + 33.3% N at knee high stage + 1% N foliar spray at 40 DAS + 32.3% N at tasseling stage). The higher input energy consumption of N6 was due to the additional labour required for nitrogen application (Table 2). Variation in input energy among treatments was mainly due to the maximum energy consumption was associated with fertilizer application practice (Batabyal el al., 2016). It was observed from the Table 3 that significantly higher value of output energy (115238 MJ ha-1), net energy grain (103417 MJ ha-1) and energy efficiency (9.75) were recorded under JM 218 than those of JM 216. The reason behind the more value of JM 218, may be the differences in varietal genetic potential which make them strong to adopt better in climatic conditions and helps in fully exploring their own characters. Singh et al. (2018) also observed varietal variation in wheat cultivars and stated that among cultivars, K 9107 being comparable to HUW 234 led to significantly higher energy output, net energy return and energy use efficiency than K 0307, HUW 468 and Birsa Gehu 3. For energy parameters namely output energy, net energy grain and energy efficiency (Figure- 2), N5 received significant maximum values for all three above parameters 116306 MJ ha-1, 104468 MJ ha-1, 9.83 respectively, that was not significantly differ from N4 (25% N at sowing + 25% N at knee high stage + 25% N at tasseling stage + 25% N at silking stage) and N6 (25% N at sowing + 25% N at knee high stage + 1% N foliar spray at 40 DAS + 25% N at tasseling stage + 24% N at silking stage) but gave significantly enhanced value over rest of the treatments. These increased values were due to the higher productive effect of treatment. These findings are in close conformity with that reported by Lorzadeh et al. (2011). The statistical analysis of the data pertaining to energy productivity, energy profitability and energy intensity in economic terms revealed that the JM 218 recorded significantly more energy productivity (0.52 kg MJ-1), energy profitability (8.75) and energy intensity in economic terms (3.21 MJ Rs-1), which was 7.98%, 8.84% and 7.85% extra respectively when compared to JM 216, whereas for the parameter specific energy both varieties were found statistically at par. These findings are in close agreement with those of earlier reported by Kumar et al., (2017) and Singh et al. (2018). In case of the factor, N scheduling, N5 (33.3% N at sowing + 33.3% N at knee high stage + 1% N foliar spray at 40 DAS + 32.3% N at tasseling stage) achieved significant superiority in their effects over N2 and N3 with respect to energy productivity and energy intensity in economic terms and also found significant to N1, N2 and N3 for energy profitability but was found statistically similar to rest of the treatments. For specific energy, N3 registered significantly more value (2.11 MJ kg-1) as compared to N5 and N6 but it was statistically identical to remaining treatments. Conclusion The energetic indices (input-output energy parameters) of maize production system were reported superior by JM 218 under factor variety and N5 under factor N scheduling. N6 utilized maximum amount of input energy. It could be concluded that the maize variety JM 218 and N5, N scheduling would be more profitable compared to others combinations for developing an energy efficient sustainable production system. Acknowledgement Authors are thankful to the RVSKVV, Gwalior and IFSR project, CoA, Indore for providing all types of necessary facilities for conducting the experiment. Conflict of Interest: Nil
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