Estimation of energy flow and environmental impacts of quinoa cultivation through life cycle assessment methodology

Dehkordi, Amin Lotfalian; Forootan, Marziye

doi:10.1007/s11356-020-08576-9

Cited by 12 publications

(14 citation statements)

References 34 publications

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“…The energy equivalents of inputs and outputs show the energy content of them. Energy content embodied in the crops is calculated based on the literature review 33–35 and ASAE standards stated by Kitani 36 . Energy equivalents of inputs and outputs are given in Appendix .…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, there is a range of energy input and output relationships for the same crop depending on the region. Thus, on a national scale it was decided to use available values in conducted studies in Iran 34,35,37–39 . For example, chemical fertilizers are widely used in agricultural crops and require high rates of direct energy for their production, mainly in the nitrogen fertilizer industry.…”

Section: Methodsmentioning

confidence: 99%

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Potential for optimization of energy consumption and costs in saffron production in central Iran through data envelopment analysis and multi‐objective genetic algorithm

Saeidi

Dehkordi

Nabavi‐Pelesaraei

2022

Env Prog and Sustain Energy

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Technical management of agricultural units plays an important role in increasing the yield, energy efficiency, and decreasing the production costs. Based on that, the present study aimed to evaluate and optimize the technical and economic efficiency in Saffron farms in the 2019-20 cropping season in Iran. Required data were collected from 70 Saffron farms through interviews and questionnaires and were analyzed and compared using two optimization methods including data envelopment analysis (DEA), and multi-objective genetic algorithm (MOGA). Based on the results related to the energy section, the total energy input was obtained as 43,578 MJ ha À1 before any optimization, while it was determined as 36,033 and 36,910 MJ ha À1 after optimization using DEA, and MOGA, respectively. Also DEA and MOGA methods improved the energy ratio index (ER) (0.002) by 50, and 159%, respectively. Results related to the economic section showed that the total production costs were mitigated from 1260 $ ha À1 to 863.5 and 1069 $ ha À1 after optimization by DEA, and MOGA, respectively. After optimization of revenue (using MOGA method), and total costs (using MOGA, and DEA), the benefit cost ratio index was improved from 1.43 to 2.09 (using DEA), and 3.3 (using MOGA). Consequently, MOGA optimization method showed better results compared to DEA in both energy and economic sections.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Potential for optimization of energy consumption and costs in saffron production in central Iran through data envelopment analysis and multi‐objective genetic algorithm

Saeidi

Dehkordi

Nabavi‐Pelesaraei

2022

Env Prog and Sustain Energy

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“…For sustainable cultivation of quinoa crop, proper management of chemical fertilizers and farm machinery are the key factors [97]. Additional characteristics include modifying land use and mechanization of agricultural practices [92].…”

Section: Mechanizationmentioning

confidence: 99%

Trends and Limits for Quinoa Production and Promotion in Pakistan

Afzal

Basra

Rehman

et al. 2022

Plants

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Quinoa is known as a super food due to its extraordinary nutritional qualities and has the potential to ensure future global food and nutritional security. As a model plant with halophytic behavior, quinoa has potential to meet the challenges of climate change and salinization due to its capabilities for survival in harsh climatic conditions. The quinoa crop has received worldwide attention due to its adoption and production expanded in countries out of the native Andean region. Quinoa was introduced to Pakistan in 2009 and it is still a new crop in Pakistan. The first quinoa variety was registered in 2019, then afterward, its cultivation started on a larger scale. Weed pressure, terminal heat stress, stem lodging, bold grain size, and an unstructured market are the major challenges in the production and promotion of the crop. The potential of superior features of quinoa has not been fully explored and utilized. Hence, there is a need to acquire more diverse quinoa germplasm and to establish a strong breeding program to develop new lines with higher productivity and improved crop features for the Pakistan market. Mechanized production, processing practices, and a structured market are needed for further scaling of quinoa production in Pakistan. To achieve these objectives, there is a dire need to create an enabling environment for quinoa production and promotion through the involvement of policymakers, research institutions, farmers associations, and the private sector.

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“…Similarly, in her research on buckwheat, Kuczuk [113] demonstrated substantially higher energy inputs for an organic system (7838 to 8104 MJ ha −1 ) than for the conventional system (12,302 to 12,462 MJ ha −1 ). According to Lotfalian and Forootan [114], energy inputs for quinoa production were 25,514 MJ ha −1 . In research by Sławi ński and Bujaczek [115], the energy inputs for rye cultivation varied from 9935 to 16,120 MJ ha −1 .…”

Section: Input-output Analysis Of Energy Use In Buckwheat Productionmentioning

confidence: 99%

“…According to Lotfalian and Forootan [114], the energy consumed in nitrogen fertilisers for the production of quinoa was 6449 MJ ha −1 or 25.27% of the total energy inputs. In Bielski's research [69], mineral fertilisation accounted for 37.7 to 64.6% of the total energy inputs for the production of winter triticale, depending on the production system.…”

Section: Input-output Analysis Of Energy Use In Buckwheat Productionmentioning

confidence: 99%

Investigation of Energy and Economic Balance and GHG Emissions in the Production of Different Cultivars of Buckwheat (Fagopyrum esculentum Moench): A Case Study in Northeastern Poland

2022

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Every type of agricultural production is a burden for the natural environment. The paper’s objective is to assess the energy use efficiency, GHG emissions, and provide an economic analysis of buckwheat production for Central Europe (Poland). The analysis and comparison involved two production systems: low-input and high-input ones. The experiment involved three varieties of buckwheat, Panda, Volma, and Mancan. The yields for analysis were obtained from the field experiment which was set up in 3k-p fractional design was applied in two replications in which at the same time five factors were tested (A—variety, B—mineral fertilisation, C—sowing rate, D—weed control, E—growth regulator). A quartile was used as a statistical tool to select production systems. A high-input buckwheat production regime required, on average, 74.00% more energy than a low-input system. The total mean energy input for three varieties ranged from 7532.7 to 13,106.9 MJ ha−1 for low- and high-input systems, respectively. The results show that the energy use efficiency, specific energy, and net energy gain for the low-input system were on average 1.51, 9.6 MJ kg−1, and 3878.8 MJ ha−1, respectively, for the investigated varieties. For the high-input system, it was 1.35, 10.9 MJ kg−1, 4529.9 MJ ha−1, respectively. The total CO2 equivalent emissions during buckwheat production were higher for the high-input system than for the low-input system by more than 40%. The economic analysis demonstrated that the high-input system had better economic efficiency (without EU payment), 1.01 on average, than the low-input system, 1.07 on average. The international literature does not offer research on energy analysis for the production of common buckwheat and GHG emissions. The findings of this study demonstrate how the production systems affect energy and economic efficiency as well as GHG emissions. The authors suggest further research in Europe and globally, particularly on the energy use efficiency and GHG emissions in the production of common buckwheat, to verify the present results and improve production technologies (reduce inputs and costs).

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Estimation of energy flow and environmental impacts of quinoa cultivation through life cycle assessment methodology

Cited by 12 publications

References 34 publications

Potential for optimization of energy consumption and costs in saffron production in central Iran through data envelopment analysis and multi‐objective genetic algorithm

Potential for optimization of energy consumption and costs in saffron production in central Iran through data envelopment analysis and multi‐objective genetic algorithm

Trends and Limits for Quinoa Production and Promotion in Pakistan

Investigation of Energy and Economic Balance and GHG Emissions in the Production of Different Cultivars of Buckwheat (Fagopyrum esculentum Moench): A Case Study in Northeastern Poland

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