Using the available indicators of potential biodiversity damage for Life Cycle Assessment on soybean crop according to Brazilian ecoregions

Lucas, Kássio Ricardo Garcia; Antón, Assumpció; Ventura, Maurício Ursi; Andrade, Edilene Pereira; Ralisch, Ricardo

doi:10.1016/j.ecolind.2021.107809

Cited by 13 publications

(6 citation statements)

References 9 publications

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“…Lucas et al [ 33 ] carried out LCA on soybean based on the potential biodiversity damage index ( BD ) in a different ecoregion ( j ) of Brazil and assessed the biodiversity damage of 804 terrestrial ecoregions in five different land use ( i ) types (managed forest, plantation, pasture, arable land, and city). The potential biodiversity damage is calculated by multiplying Characterization Factors ( CFs ) [ 34 ] and the total crop area ( A i,j , m 2 ) as follows:

…”

Section: Environmental Impact Assessment (Eia) Index System Of Agricu...mentioning

confidence: 99%

Life Cycle Assessment on Agricultural Production: A Mini Review on Methodology, Application, and Challenges

Fan

Liu

Xie

et al. 2022

IJERPH

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Agricultural Life Cycle Assessment (LCA) is an effective tool for the quantitative evaluation and analysis of agricultural materials production and operation activities in various stages of the agricultural system. Based on the concept of life cycle, it comprehensively summarizes the impact of agriculture on the environment, which is an effective tool to promote the sustainability and green development of agriculture. In recent years, agricultural LCA has been widely used in the agroecosystem for resource and environmental impacts analysis. However, some challenges still exist in agricultural LCA, i.e., the environmental impact assessment index system needs to be improved; its application in different production mode is limited; and combination research with other models needs more attention. This paper discusses the above-mentioned challenges and recommends research priorities for both scientific development and improvements in practical implementation. In summary, further research is needed to construct a regional heterogeneity database and develop innovated methodologies to develop more meaningful functional units for agricultural products to complement LCA by other models. These efforts will make agricultural LCA more robust and effective in environmental impacts assessment to support decision making from individual farm to regional or (inter)national for the sustainable future of agriculture.

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…”

Section: Environmental Impact Assessment (Eia) Index System Of Agricu...mentioning

confidence: 99%

Life Cycle Assessment on Agricultural Production: A Mini Review on Methodology, Application, and Challenges

Fan

Liu

Xie

et al. 2022

IJERPH

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“…For example, livestock grazing results in the removal of biomass, trampling, and replacement of wild animals by livestock (Alkemade et al, 2013). The production of soybean in Brazil has resulted in biodiversity damage to mammals, birds, amphibians, reptiles and plants (Garcia Lucas et al, 2021). Nitrogen addition to N‐limited grasslands improves productivity but decreases biodiversity that can last for decades despite decreases in soil nitrate after cessation of nitrogen addition (Isbell et al, 2013).…”

Section: Circular Agriculturementioning

confidence: 99%

Sustainable development in circular agriculture: An illustrative bee↺legume↺poultry example

Rauw

Gomez‐Raya

Star

et al. 2022

Sustainable Development

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Circular economic principals of production are based on material flows through the system with minimum external inputs, recycling of resources, generating minimum waste, emissions, or pollution. Agriculture presents a major opportunity for the utilization of wastes, by-products and co-products in the development of a circular economy via the design of circular agricultural production systems and the creation of new sustainable value chains. The present work outlines an illustrative example of a

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“…The research emphasized the importance of considering climate change scenarios in predicting the potential climate suitability of food crop GIs. Lucas Kássio R. Garcia et al evaluated biodiversity damage indicators for soybean crops in different ecoregions in Brazil, assessing the potential impacts of soybean production on biodiversity loss [38]. The research proposed adjustments to biodiversity indicators for the life cycle assessment of soybean production in different Brazilian ecoregions.…”

Section: Introductionmentioning

confidence: 99%

Classification of soybeans from different habitats based on metabolomic–transcriptomic integration

Wang,

Zheng,

Wang

et al. 2024

Appl Biol Chem

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Soybeans are a significant agricultural product in China, with certain geographical locations often yielding higher quality, and thus more expensive, soybean crops. In this study, metabolomics and transcriptomics analyses were conducted on soybean samples from nine regions in Heilongjiang and Liaoning Provinces using untargeted liquid chromatography–mass spectrometry (LC–MS) and Illumina sequencing technologies. The primary objective was to devise an effective and unbiased method for determining the geographical origin of each soybean variety to mitigate potential fraudulent practices. Through multidimensional and unidimensional analyses, successful identification of differentially expressed metabolites (DEMs) and differentially expressed genes (DEGs) was achieved, yielding statistically significant outcomes. Integration of the metabolomics and transcriptomics datasets facilitated the construction of a correlation network model capable of distinguishing soybeans originating from different geographical locations, leading to the identification of significant biomarkers exemplifying noteworthy distinctions. To validate the feasibility of this method in practical applications, partial least squares discriminant analysis was employed to differentiate soybean samples from the nine regions. The results convincingly showcased the applicability and reliability of this approach in accurately pinpointing the geographical origin of soybeans. Distinguishing itself from prior research in soybean traceability, this study incorporates an integrated analysis of metabolomics and transcriptomics data, thereby unveiling biomarkers that offer a more precise differentiation of soybean traits across distinct regions, thereby bridging a critical research gap within the soybean traceability domain. This innovative dual-data integration analysis methodology is poised to enhance the accuracy of soybean traceability tools and lay a new foundation for future agricultural product identification research.

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Using the available indicators of potential biodiversity damage for Life Cycle Assessment on soybean crop according to Brazilian ecoregions

Cited by 13 publications

References 9 publications

Life Cycle Assessment on Agricultural Production: A Mini Review on Methodology, Application, and Challenges

Life Cycle Assessment on Agricultural Production: A Mini Review on Methodology, Application, and Challenges

Sustainable development in circular agriculture: An illustrative bee↺legume↺poultry example

Classification of soybeans from different habitats based on metabolomic–transcriptomic integration

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