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Applying DEA optimization approach for energy auditing in wheat cultivation under rice-wheat and cotton-wheat cropping systems in north-western India

机译:在印度西南稻米和棉质 - 小麦种植系统下采用DEA优化方法对小麦栽培中的小麦种植

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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 similar to 45%, while irrigation, electricity and diesel fuel consumption each shared similar to 15% towards total input energy (E-I). Wheat cultivation was energy efficient with EI 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 (similar to 65% of total DMUs) with TE 1.00 were inefficient. Therefore, by the adoption of recommendations of the study, 3819 +/- 641 MJ ha(-1) (similar to 12% of E-I) energy saving is possible from different inputs in wheat cultivation. (C) 2019 Elsevier Ltd. All rights reserved.
机译:小麦(Triticum aestivum L.)是印度西北部稻米和棉质 - 小麦种植系统中的高能量密集型冬季作物。在这项研究中,通过面对面的调查,从8个小麦生产者收集的数据(每种小麦和棉 - 小麦种植系统中的40个)收集的数据估算了小麦培养的能量投入输出关系。通过米小麦,通过灌水水输入通过灌溉水的能量显着(p <0.05),在小麦下,小麦(4093 +/- 133 mJ(-1)),与米小麦相比(3576 +/- 124 MJ(-1));虽然来自其他来源的能量输入在种植系统中是非显着的。用于裁剪系统的数据显示,化肥包含与45%相似,而灌溉,电和柴油燃料消耗,每个灌溉,电力和柴油燃料消耗每次共用至总输入能量(E-I)的15%。小麦栽培与EI为25.6 +/- 0.5 GJ(-1)和191.7 +/- 3.6 GJ(-1)的总输出能量(EO)产生的净能源增益(NEG)为166.1 +/- 3.5 GJ HA(-1)。数据包络分析(DEA)阐明了28个决策单位(DMU),作为1.00的技术评分(TE)的能量效率,而TE <1.00的52 DMUS(占总DMU的65%)效率低下。因此,通过采用该研究的建议,3819 +/- 641 MJ(-1)(类似于E-i的12%)节能来自小麦栽培中的不同投入。 (c)2019 Elsevier Ltd.保留所有权利。

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