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Wheat (Triticum aestivum L.) is a winter cereal crop with higher energy footprints. We therefore aimed to budget energy use, establish input-output relationships, and to perform data envelopment analysis (DEA) based optimization in wheat established with innovative super seeder technology. Data-set of 45 decision-making units (DMUs) collected during face-to-face interviews were changed to energy units for enhancing their energy efficiency. These results revealed that total energy input (E I) of 22.6 GJ ha−1 and output energy of 125.3 GJ ha−1 yielded energy productivity of 0.231 kg MJ−1. The net energy gain (102.7 GJ ha−1) accomplished with an energy ratio of 5.6 indicates that super seeder technology was energy-efficient. Direct and indirect energy share ∼53.2 and 46.8%, whilst renewable and non-renewable energy comprised ∼24.8 and 75.2% of E I , respectively. Fertilizer-N emerged as the major energy input (∼44.7% of E I), followed by irrigation water (∼17.4%) and electricity (15.1%). The DEA based benchmarking elucidated 23 DMUs (∼51.1% of total studied) as efficient, whilst others inefficient. An average technical efficiency of 0.89 illustrates ∼11% E I saving possibilities by the adoption of best management practices. These results underpin the overwhelming significance of efficient fertilizer-N, irrigation water and electricity for reduced energy footprints in north-western India. [Display omitted] • Energy use efficiency of wheat established with super seeder technology was studied. • Net energy gain of 102.7 ± 1.7 GJ ha−1 was achieved with energy ratio (ER) of 5.6. • Fertilizer-N has highest energy input, comprised ∼44.7% of total energy input. • Data envelopment analysis (DEA) elucidated ∼51.1% wheat farms as energy efficient. • About 11% (2046.7 MJ ha−1) energy could be saved following recommendations of DEA. [ABSTRACT FROM AUTHOR]

Wheat (Triticum aestivum L.) is highly energy intensive winter crop grown in rice-wheat and cotton-wheat cropping systems in north-western India. In this study, energy input-output relationships for wheat cultivation were estimated from data collected from 80 wheat producers (40 each in rice-wheat and cotton-wheat cropping system) by face-to-face survey. Energy input through irrigation water was significantly (p < 0.05) higher by 517 MJ ha-1 (14.5%) in wheat under cotton-wheat (4093 ± 133 MJ ha-1), compared with rice-wheat (3576 ± 124 MJ ha-1); while energy input difference from other sources was non-significant among cropping systems. Data pooled for cropping systems revealed that chemical fertilizers comprised ∼45%, while irrigation, electricity and diesel fuel consumption each shared ∼15% towards total input energy (E I). Wheat cultivation was energy efficient with E I of 25.6 ± 0.5 GJ ha-1 and total output energy (E O) of 191.7 ± 3.6 GJ ha-1 produced net energy gain (NEG) of 166.1 ± 3.5 GJ ha-1. Data Envelopment Analysis (DEA) elucidated 28 decision making units (DMUs) as energy efficient with technical score (TE) of 1.00, while 52 DMUs (∼65% of total DMUs) with TE < 1.00 were inefficient. Therefore, by the adoption of recommendations of the study, 3819 ± 641 MJ ha-1 (∼12% of E I) energy saving is possible from different inputs in wheat cultivation. • Energy input was 26 GJ ha-1 and energy output was 192 GJ ha-1 in wheat cultivation. • Net energy gain of 166 GJ ha-1 shows that wheat cultivation is energy efficient. • Data envelopment analysis was used to optimize input energy in wheat cultivation. • Technical efficiency of 52 wheat farms (65% of total) was <1.00 • 12% (3819 MJ ha-1) of total input energy could be saved under optimized conditions. [ABSTRACT FROM AUTHOR]

Rice (Oryza sativa L.) is an important energy intensive cereal crop in India. In the present study, energy input and output were audited to optimize energy use in rice cultivation using data collected from 40 farmers during face-to-face interview. Average total energy input (E I) of 52.4 ± 1.3 GJ ha−1 produced total energy output (E O) of 259 ± 4.7 GJ ha−1, with energy productivity (E P) of 0.16 kg MJ−1. Results revealed that rice cultivation was energy efficient with energy ratio (E R) of 5.0 ± 0.12 and net energy gain (NEG) of 206 ± 4.5 GJ ha−1. In rice, irrigation water (∼40%) and chemical fertilizers (24.7%) had highest contribution towards E I. A non-parametric production function of DEA (Data Envelopment Analysis) applied to optimize energy use in rice, elucidated 20 decision making units (DMUs) as efficient, whilst 50% as inefficient. The average technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of rice farms were 0.94, 0.97 and 0.97, respectively. Our results revealed that between 9.4 and 2170 MJ ha−1 energy (0.2 and 46.9% of total saving) could be saved, if inefficient DMUs adopt the management practices of efficient DMUs. An average energy saving of 579 ± 166 MJ ha−1 by efficient DMUs accounts for ∼8.8% of the E I. • Energy input was 52.4 GJ ha−1 and energy output was 259 GJ ha−1 in rice cultivation. • Irrigation and fertilizers had highest contribution (64.7%) in total energy input. • Data envelopment analysis was used to optimize input energy use in rice cultivation. • Saving of 8.8% of total energy input is possible with current yield level. [ABSTRACT FROM AUTHOR]

Abstract This study aims at to make a heuristic analysis of energy efficiency performance of Indian paper industry in a non-parametric production theoretic approach. Using the data for 2004–05 to 2013–14, radial and non-radial variants of DEA were employed to estimate energy saving potential and identify the relative position of paper industry across the states. Preliminary analysis in terms of energy intensity scores showed declining trends of energy intensity over the period of analysis for most of the states except states like Assam, Chhattisgarh, Kerala and Punjab where it does not decline much. Assuming a variable returns to scale (VRS) technology under the conditions of inherent heterogeneity and market imperfection, the slack-based measure (SBM) reported a much higher energy saving potential than reported by other measures in the study. Further by taking scale efficiency into account, the study documented the higher contribution of pure energy inefficiency in explaining the total energy inefficiency within the paper industry relative to scale inefficiency. Finally, the study recommends the propagation of energy efficiency program through a market-based and regulatory mechanism along with consolidation and technological advancement of individual units, in order to tap vast energy saving potential and thereby ensure the growth and environmental sustainability. Highlights • The paper examined the energy efficiency performance of Indian paper industry. • Both radial (BCC) and the non-radial (SBM) measures of energy efficiency, were applied. • BCC measure reported an energy saving potential of 16%. • SBM measure reported an energy saving potential of 24%, higher than BCC measure. • Scale efficiency implied the relatively higher contribution of pure energy inefficiency. [ABSTRACT FROM AUTHOR]

Abstract: In this paper DEA (Data envelopment analysis), a non-parametric approach to frontier analysis, is applied to evaluate the relative performance of 29 EDDs (Electricity Distribution Divisions) of an Indian hilly state, namely Uttarakhand. Input oriented DEA is applied to evaluate the relative overall efficiency, technical efficiency and scale efficiency of EDDs. The results indicate that numerous divisions have scope for improvement in overall efficiency. Most of the utilities are inefficient due to their scale inefficiency rather than technical inefficiency. Further Slack analysis is carried out to formulate improvement directions for relatively inefficient divisions. Particular areas are identified, which are to be improved for overall efficiency enhancement through sensitivity analysis. Different alternatives for reorganization of the EDDs are explored in order to obtain most favorable and balanced scale. The result is envisaged to be instrumental to policy makers and managers to increase the operational efficiency of the EDDs leading to higher profitability of the state electricity board. [ABSTRACT FROM AUTHOR]

Rice residue management (RRM) impacts ecosystems' sustainability due to change in energy use, C footprints (CFs) and net ecosystem C budget (NECB). The energy input-output and CFs were audited to optimize energy use and C equivalent emissions (CE) in wheat following RRM with Happy Seeder using data collected from 53 farmers during face-to-face interview. Average total energy input (E I) of 23.5 GJ ha−1 produced output energy of 204.8 ± 2.9 GJ ha−1, with energy productivity (E P) of 0.24 kg MJ−1. The net energy gain (NEG) of 181.3 ± 3.0 GJ ha−1 was achieved with energy use efficiency (E R) of 8.81 ± 0.19. Chemical fertilizers were the major hotspots of energy (∼48.4% of E I) and CFs (∼59.2% of CE) in wheat cultivation. Data Envelopment Analysis (DEA) elucidated 23 decision making units (∼43% of total) as energy efficient, whilst 30 as inefficient with average technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) were 0.94, 0.97 and 0.94, respectively. DEA helped energy saving of 1462.8 MJ ha−1 (∼6.2%), mitigation of 107.8 kg CO 2 e ha−1 (∼7.6%) with significantly higher NECB of 716.4 kg C ha−1 (∼19.1%) due to change in soil organic C (ΔSOC) pool by 34.8 kg C ha−1 at efficient Happy Seeder sown wheat farms. [Display omitted] • Energy, C footprints (CFs) and NECB of Happy Seeder sown wheat was studied. • Wheat cultivation was energy efficient with net energy gain (NEG). • Chemical fertilizers were major hotspots of energy (∼48.4%) and CFs (∼59.2%). • DEA optimized energy and CFs were reduced by ∼6.2 and 7.6%, respectively. • Efficient wheat farms had ∼19.1% higher NECB, than the inefficient farms. [ABSTRACT FROM AUTHOR]