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Combined application of Artificial Neural Networks and life cycle assessment in lentil farming in Iran

Information Processing in Agriculture 2017年第1期4卷 18-32页

作者： behzad elhami Majid Khanali Asadollah Akram Department of Agricultural Machinery Engineering Faculty of Agricultural Engineering and TechnologyCollege of Agriculture and Natural ResourcesUniversity of TehranKarajIran

In this study,an Artificial Neural Network(ANN)was applied to model yield and environmental emissions from lentil cultivation in Esfahan province of *** was gathered from lentil farmers using face to face questionnaire method during 2014–2015 cropping *** cycle assessment(LCA)was applied to investigate the environmental impact categories associated with lentil *** on the results,total energy input,energy output to input ratio and energy productivity were determined to be 32,970.10 MJ ha1,0.902 and 0.06 kg MJ1,*** greatest amount of energy consumption was attributed to chemical fertilizer(42.76%).Environmental analysis indicated that the acidification potential was higher than other environmental impact categories in lentil production *** results showed that the production of agricultural machinery was the main hotspot in abiotic depletion,eutrophication,global warming,human toxicity,fresh water aquatic ecotoxicity,marine aquatic ecotoxicity and terrestrial ecotoxicity impact categories,while direct emissions associated with lentil cultivation was the main hotspot in acidification potential and photochemical oxidation *** addition,diesel fuel was the main hotspot only in ozone layer *** ANN model with 9-10-6-11 structure was identified as the most appropriate network for predicting yield and related environmental impact categories of lentil ***,the results of sensitivity analysis revealed that farmyard manure had the greatest effect on the most of the environmental impacts,while machinery was the most affecting parameter on the yield of the crop.

关键词： Artificial Neural Network Energy balance Environmental impacts Lentil production Sensitivity analysis

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Optimization of energy consumption and environmental impacts of chickpea production using data envelopment analysis(DEA)and multi objective genetic algorithm(MOGA)approaches

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Information Processing in Agriculture 2016年第3期3卷 190-205页

作者： behzad elhami Asadollah Akram Majid Khanali Department of Agricultural Machinery Engineering Faculty of Agricultural Engineering and TechnologyUniversity of TehranKarajIran

Energy consumption in agricultural products and its environmental damages has increased in recent *** cycle assessment(LCA)has been introduced as a suitable tool for evaluation environmental impacts related to a product over its life *** this study,optimization of energy consumption and environmental impacts of chickpea production was conducted using data envelopment analysis(DEA)and multi objective genetic algorithm(MOGA)*** were collected from 110 chickpea production enterprises using a face to face questionnaire in the cropping season of *** results of optimization revealed that,when applying MOGA,optimum energy requirement for chickpea production was significantly lower compared to application of DEA technique;so that,total energy requirement in optimum situation was found to be 31511.72 and 27570.61 MJ ha^-1 by using DEA and MOGA techniques,respectively;showing a reduction by 5.11%and 17%relative to current situation of energy *** of environmental impacts by application of MOGA resulted in reduction of acidification potential(ACP),eutrophication potential(EUP),global warming potential(GWP),human toxicity potential(HTP)and terrestrial ecotoxicity potential(TEP)by 29%,23%,10%,6%and 36%,*** capable of reducing the energy consumption from machinery,farmyard manure(FYM)diesel fuel and nitrogen fertilizer(the mostly contributed inputs to the environmental emissions)by 59%,28.5%,24.58%and 11.24%,***,the MOGA technique showed a superior performance relative to DEA approach for optimizing energy inputs and reducing environmental impacts of chickpea production system.

关键词： Data envelopment analysis Energy Life cycle assessment Multi objective genetic algorithm

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Improvement of energy efficiency and environmental impacts of rainbow trout in Iran

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Artificial Intelligence in Agriculture 2019年第2期2卷 13-27页

作者： behzad elhami Saeid Shahvarooghi Farahani Afshin Marzban Department of Agricultural Machinery and Mechanization Engineering Agriculture Science and Natural Resources University of KhuzestanMollasaniIran

Combination of Life Cycle Assessment(LCA)and other management tools can help production units to improve economic productivity and environmental *** this study,a combination of LCA and Data Envelopment Analysis(DEA)was applied in order to improve the energy efficiency and reduce the environmental burdens of rainbow trout farm in Ardal and Lordegan regions located in Chaharmahal and Bakhtiari Province of *** required data were collected from 60 rainbow trout farms in Ardal region and 38 rainbow trout farms in Lordegan region through face-to-face questionnaire *** Ardal region,total energy inputs,rainbow trout yield and Energy Ratio(ER)were estimated as 60,483.50 MJ ton−1,281.78 ton ha−1 and 0.40,respectively,while for Lordegan region,these estimates were obtained as 77,183.63 MJ ha−1,210.50 kg ha−1 and 0.33,*** results of LCA revealed that rainbow trout production in Ardal region had lower environmental burdens than Lordegan region in all impact ***,Environmental Emissions Final Score(EEFS)in Ardal and Lordegan regions were 1638.88 and 3484.31 ppt ton−1,*** normalized results also showed that Marine Aquatic Ecotoxicity(MAE)had the highest value among all impact categories in both *** DEA results showed that in Ardal and Lordegan regions about 29.28%and 9.59%of the total energy can be saved without reducing the yield,*** highest potential for saving energy was related to feed in both Ardal(24.74%)and Lordegan(9.12%)*** results of LCA coupled with DEA also revealed that there is a higher potential for reduction of environmental impacts in Ardal region compare to Lordegan ***,the EEFS value in Ardal and Lordegan regionswere reduced by 27.34%and 8.85%,***,rainbow trout production in Ardal region had higher energy efficiency,lower environmental burdens and also higher potential to improve energy consumption and reduce the environmental impacts c

关键词： Life cycle assessment Energy ratio Data envelopment analysis Rainbow trout

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