Energy use and greenhouse gas emissions in organic and conventional grain crop production: Accounting for nutrient inflows

Hoffman, Eric; Cavigelli, Michel A.; Camargo, Gustavo; Ryan, Matthew R.; Ackroyd, Victoria J.; Richard, Tom L.; Mirsky, Steven B.

doi:10.1016/j.agsy.2018.01.021

Cited by 44 publications

(24 citation statements)

References 29 publications

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“…A significant share (15.5%) of reviewed papers declare having no co-products, usually those that define an areabased FU or those that define the timeframe as being post harvesting of a previous crop until the harvest of the following crop. Under the latter approach, the burdens and benefits associated with non-harvested legume cover crops, for example, are fully attributed to crop harvested after the legume cultivation (Prechsl et al 2017;Hoffman et al 2018), or attributed to multiple following crops harvested after the legume cultivation (Peter et al 2017). However, if the legume cover crop is harvested and leaves the farm boundaries, the N benefit promoted by the legume crop is fully attributed to the following crop, whilst the leaching is fully attributed to the legume crop (Fig.…”

Section: N Carryover Carbon Sequestration and Allocation Methodsmentioning

confidence: 99%

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Representing crop rotations in life cycle assessment: a review of legume LCA studies

Costa

Chadwick

Saget

et al. 2020

Int J Life Cycle Assess

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Purpose There is an imperative to accurately assess the environmental sustainability of crop system interventions in the context of food security and climate change. Previous studies have indicated that the incorporation of legumes into cereal rotations could reduce overall environmental burdens from cropping systems. However, most life cycle assessment (LCA) studies focus on individual crops and miss environmental consequences of inter-annual crop sequence and nutrient cycling effects. This review investigates state-of-the-art representation of inter-crop rotation effects within legume LCA studies. Methods A literature review was undertaken, starting with a search for all peer-reviewed articles with combinations of ‘LCA’, ‘legumes’ and ‘rotations’ or synonyms thereof. In total, 3180 articles were obtained. Articles were screened for compliance with all of the following requirements: (i) reporting results based on LCA or life cycle inventory methodology; (ii) inclusion of (a) legume(s); (iii) the legume(s) is/are analysed within the context of a wider cropping system (i.e. rotation or intercropping). Seventy articles satisfying these requirements were analysed. Results and discussion We identified three broad approaches to legume LCA. Most studies involved simple attributional LCA disregarding important interactions across years and crops in rotations. N-fertilizer reduction through legume residue N carryover is either disregarded or the benefit is attributed to the following crop in such studies, whilst N leaching burdens from residues are usually attributed to the legume crop. Some studies applied robust allocation approaches and/or complex functional units to enable analysis of entire rotation sequences, accounting for nutrient cycling and break crop effects. Finally, a few studies applied consequential LCA to identify downstream substitution effects, though these studies did not simultaneously account for agronomic effects of rotational sequence changes. Conclusions We recommend that LCA studies for legume cropping systems should (i) evaluate entire rotations; (ii) represent nitrogen and ideally carbon cycling; (iii) for attributional studies, define at least two functional units, where one should encompass the multifunctional outputs of an entire rotation and the other should enable product footprints to be calculated; (iv) for CLCA studies, account for both agronomic changes in rotations and markets effects; (v) include impact categories that reflect hotspots for agricultural production.

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Section: N Carryover Carbon Sequestration and Allocation Methodsmentioning

confidence: 99%

“…The remaining 39 articles (56%) analysed at least two types of FU, with numerous authors proposing that one FU is insufficient to assess multi-product crop rotations (Carranza-Gallego et al 2018;Hoffman et al 2018;Reinsch et al 2018). Almost 20% of articles (13) analysed three or more types of FU.…”

Section: Definition Of Goal and Functional Unitmentioning

confidence: 99%

Representing crop rotations in life cycle assessment: a review of legume LCA studies

Costa

Chadwick

Saget

et al. 2020

Int J Life Cycle Assess

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“…For instance, even though the Beltsville site had a common history of no-till management prior to 1996, microbial communities today are easily differentiated by farming system. Differences in management have effects that extend beyond microbial taxa to include nematodes [37], as well as soil organic matter and phosphorous concentrations, greenhouse gas emissions, and total energetic costs of the farming system [24, 38, 39].…”

Section: Discussionmentioning

confidence: 99%

Soil microbial communities in diverse agroecosystems exposed to glyphosate

Kepler

Schmidt

Yarwood

et al. 2018

Preprint

Self Cite

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24In spite of glyphosate's wide use in agriculture, questions remain about effects of the herbicide 25 on soil microbial communities. Conflicting scientific literature reports divergent results; from no 26 observable effect of glyphosate to the enrichment of common agricultural pathogens such as 27Fusarium. We conducted a comprehensive field-based study to compare treatments that did 28 and did not receive foliar application of glyphosate spray. The study included two field sites, 29Maryland and Mississippi; two crops, soybean and corn; four site years, 2013 and 2014; and a 30 variety of organic and conventional farming systems. Using amplicon sequencing, the 31 prokaryotic (16S rRNA) and fungal (ITS) communities were described along with chemical and 32 physical properties of the soil. Sections of corn and soy roots were plated to screen for the 33 presence of plant pathogens. Geography, farming system, and seasonal progression were 34 significant factors determining composition of fungal and bacterial communities. Plots treated 35 with or without glyphosate did not differ in overall microbial community composition after 36 controlling for these factors. No differential effect of glyphosate treatment was found in the 37 relative abundance of organisms such as Fusarium spp. or putative growth-promoting bacteria 38

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“…Process-based modelling can extend the results from a short-term field experiment to predict the long-term effect of management practices and climate variability on grain yield and soil GHG emissions, especially for SOC change, which is tended to be ignored when estimating GHG emissions of different management in the short term [8][9][10][11]. The limitation of this method is that the model needs to be calibrated and validated against the experimental data before its application in other regions.…”

Section: Limitations and Suggestionsmentioning

confidence: 99%

“…Increasing SOC stocks of agricultural soils (top 1 m of soil) by 0.4% can offset about 30% of global greenhouse gas emissions [7]. However, SOC change is tended to be ignored when estimating GHG emissions of different management in the short term [8][9][10][11]. In addition to the soil CO 2 and N 2 O emissions, CO 2 emissions from agricultural inputs (e.g., fuel combustion, production, transportation, and application of fertilizers, pesticides, etc.)…”

Section: Introductionmentioning

confidence: 99%

Optimizing Nitrogen and Residue Management to Reduce GHG Emissions while Maintaining Crop Yield: A Case Study in a Mono-Cropping System of Northeast China

Luo

Wang

et al. 2019

Sustainability

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Reducing the use of nitrogen fertilizers and returning straw to field are being promoted in northeast China (NEC). In this paper, the agricultural production system model (APSIM) was applied to assess the long-term variations of crop yield and soil GHG emissions in a maize mono-cropping system of NEC, and the simulation results were combined with lifecycle assessment to estimate annual GHG emissions (GHG L ) and GHG emission intensity (GHG I , GHG emissions per unit yield) of different agricultural practices. Under current farmers' practice, emissions due to machinery input (including production, transportation, repair, and maintenance) and soil organic carbon (SOC) decline accounted for 15% of GHG L , while emissions from nitrogen fertilizer input (production and transportation) and direct N 2 O emissions from soil accounted for the majority (~60% of GHG L ). Current farmers' practice in terms of N application and residue management are nearly optimal for crop production but not for climate change mitigation. Reducing N input by 13% and increasing straw retention by 20% can maintain crop yield and SOC, and also reduce GHG L and GHG I by 13% and 11%, respectively. However, it is not feasible to incorporate the straw used as household fuel into soil, which could incur substantial fossil CO 2 emissions of 3.98 Mg CO 2 -eq ha −1 resulting from the substitution of coal for straw. APSIM was successful in simulating crop yield, N 2 O emissions, and SOC change in NEC, and our results highlight opportunities to further optimize management strategies (especially for the nitrogen and straw management) to reduce GHG emissions while maintaining crop yield.

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Energy use and greenhouse gas emissions in organic and conventional grain crop production: Accounting for nutrient inflows

Cited by 44 publications

References 29 publications

Representing crop rotations in life cycle assessment: a review of legume LCA studies

Representing crop rotations in life cycle assessment: a review of legume LCA studies

Soil microbial communities in diverse agroecosystems exposed to glyphosate

Optimizing Nitrogen and Residue Management to Reduce GHG Emissions while Maintaining Crop Yield: A Case Study in a Mono-Cropping System of Northeast China

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