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利用数据包络分析(DEA)方法提高向日葵生产的能源生产力。

Improving energy productivity of sunflower production using data envelopment analysis (DEA) approach.

机构信息

Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran.

出版信息

J Sci Food Agric. 2011 Aug 15;91(10):1885-92. doi: 10.1002/jsfa.4403. Epub 2011 Apr 7.

Abstract

BACKGROUND

Efficient use of energy in agriculture is one of the conditions for sustainable agricultural production. This study applies the data envelopment analysis (DEA) approach to the data of 95 randomly selected farms to investigate the technical and scale efficiencies of farmers with respect to energy use for sunflower production in Golestan province, Iran. The study also helps to identify the wasteful usage and the optimum level of energy from different inputs.

RESULTS

According to the results of DEA models, about 36% of farmers were found to be technically efficient and the mean efficiency of sunflower producers was found to be 0.87 and 0.96 under the constant and variable returns to scale assumptions respectively. The optimum energy requirement was calculated as 8448.3 MJ ha⁻¹; accordingly, a potential reduction of 10.8% (1020.3 MJ ha⁻¹) in total energy input could be achieved by raising the performance of farmers to the highest level.

CONCLUSION

Applying a better machinery management technique and conservation tillage methods, application of fertilisers by performance monitoring and utilisation of alternative sources of energy such as compost and chopped residues may be the pathways for improving energy productivity and reducing the environmental footprint.

摘要

背景

农业中能源的高效利用是可持续农业生产的条件之一。本研究应用数据包络分析(DEA)方法对 95 个随机选择的农场的数据进行分析,以调查伊朗戈勒斯坦省向日葵生产中农民在能源使用方面的技术和规模效率。该研究还有助于确定能源投入的浪费使用和最佳水平。

结果

根据 DEA 模型的结果,约 36%的农民被认为是技术上有效的,在不变和可变规模报酬假设下,向日葵生产者的平均效率分别为 0.87 和 0.96。最优能源需求计算为 8448.3 MJ ha⁻¹;因此,通过将农民的绩效提高到最高水平,总能源投入可减少 10.8%(1020.3 MJ ha⁻¹)。

结论

应用更好的机械管理技术和保护性耕作方法,通过性能监测应用肥料,以及利用堆肥和切碎残渣等替代能源,可能是提高能源生产力和减少环境足迹的途径。

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