Life cycle impact assessment (LCA) provides a better understanding of the energy, water, and material input and evaluates any production system’s output impacts. LCA has been carried out on various crops and products across the world. Some countries, however, have none or only a few studies. Here, we present the results of a literature review, following the PRISMA protocol, of what has been done in LCA to help stakeholders in these regions to understand the environmental impact at different stages of a product. The published literature was examined using the Google Scholar database to synthesize LCA research on agricultural activities, and 74 studies were analyzed. The evaluated papers are extensively studied in order to comprehend the various impact categories involved in LCA. The study reveals that tomatoes and wheat were the major crops considered in LCA. The major environmental impacts, namely, human toxicity potential and terrestrial ecotoxicity potential, were the major focus. Furthermore, the most used impact methods were CML, ISO, and IPCC. It was also found that studies were most often conducted in the European sector since most models and databases are suited for European agri-food products. The literature review did not focus on a specific region or a crop. Consequently, many studies appeared while searching using the keywords. Notwithstanding such limitations, this review provides a valuable reference point for those practicing LCA.

Fertilizers and pesticides have been widely used in agriculture production, causing polluted soil, water, and atmosphere. This study aims to quantify air emissions from pesticides and fertilizers applied for peanut production in Georgia during selected years (1991, 1999, 2004, 2013, and 2018). Specifically, the oral and dermal potential impacts from pesticide emissions and the global warming potential (GWP) impact from fertilizers to air were investigated. This study followed the ISO 14040 series standards for life cycle assessment (LCA) methodology to assess six active ingredients (AIs) (2,4-DB, Bentazon, Chlorothalonil, Ethalfluralin, Paraquat, and Pendimethalin) and one greenhouse gas (nitrous oxide N₂O). Their physical and chemical characteristics and the temporal scales greatly influenced the oral and dermal toxicity impacts. According to the low values obtained for Henry’s law (K_H) and vapor pressure (VP), 2,4-dichlorophenoxy butanoic (DB), Pendimethalin, and Chlorothalonil have a higher impact on the continental air scale. The effect factor (EF) from oral exposure was higher in 2,4-DB, Bentazon, and Pendimethalin than dermal exposure, according to the relatively low lethal dose (LD₅₀) for oral exposure, while the EF of Ethalfluralin and Chlorothalonil was the same for oral and dermal exposure according to their similar LD₅₀.

Life cycle assessment (LCA) is widely used to evaluate the environmental impacts of agricultural production systems with four phases. The first phase (Phase 1) is an important phase describing the goal and scope of the entire LCA. However, data on existing and potential goals and scope are scattered across studies and not available at a single location, making it hard to reuse and compare them. The objective of this study is to create a dataset of Phase 1 information (goals, products, and scopes) for agricultural LCA. The dataset was generated from a systematic review of 184 published agricultural LCA studies, including peer-reviewed journal articles and selected conference papers, published between 1999 and 2025, following PRISMA guidelines. Studies were identified through keyword searches on Google Scholar and screened for relevance and availability. Only studies that clearly reported Phase 1 information were included. Data was collected manually and organized using standard IDs. The dataset has 41 goals, 65 products, and 7 scopes; each was assigned an ID (Goal_ID, Product_ID, Scope_ID, and Stage_ID) to support consistency and traceability. The dataset supports comparisons across studies, assists users in selecting appropriate goals, products, and system boundaries, and can support the development of LCA tools, databases, and decision-support frameworks.

Agriculture faces increasing pressure to meet global food demands while minimizing environmental harm, yet many current practices remain unsustainable. This study develops the EAGLES framework (Environmental Impact of Agriculture using Life Cycle Assessment and Expert System) to address limitations in current sustainability assessment approaches. Life Cycle Assessment (LCA) evaluates environmental impacts but is limited by data availability and usability, especially for new users in agriculture. The objective of this study is to address this gap by developing the EAGLES framework, which organizes agricultural LCA data within an expert system (knowledge-based, rule-based) structure to guide the application of LCA phases. The knowledge base is developed from Phase 1 datasets reported in previous work and additional datasets developed as part of this study. The rule base uses if–then logic to check if the required data are available and to guide movement across the LCA phases. The framework is designed to support multiple scope types, impact categories, and assessment methods within a single structure. The framework was applied to rice production in Mississippi (2021) to assess marine eutrophication and acidification. The case study results show that the framework enables consistent progression across all LCA phases and produces impact results that can be interpreted using normalization and weighting. A second pathway was applied to assess acidification, demonstrating that the framework can handle multiple impact categories within the same system. By organizing data and linking inventory, impact assessment, and interpretation into a single process, the framework provides a structured and transparent approach for conducting agricultural LCA.

Life cycle inventory (LCI) data constitute Phase 2 of life cycle assessment (LCA) and serve as the basis for calculating environmental impacts. In agricultural LCA studies, LCI data are often reported using different scopes, stages, units, and calculation methods, making it difficult to reproduce results and compare studies. The objective of this study is to compile and standardize Phase 2 LCI data reported in agricultural LCA studies into a structured dataset. The dataset is based on 184 peer-reviewed agricultural LCA studies published between 1999 and 2025. Data were collected through a systematic review using Google Scholar, and studies were included if they applied LCA to crop production systems and reported inventory data such as inputs, outputs, emission factors, or calculation equations. Inventory data were manually extracted from each study, including inputs and outputs, emission factors, equations, and data sources. The dataset is provided as an Excel workbook containing linked sheets for study identifiers, inputs, outputs, emission factors, equations, and data sources. Rather than providing newly harmonized inventory values, the dataset organizes extracted and categorized information reported in the reviewed studies using standardized identifiers and categories. The dataset includes more than 2000 inputs, around 1000 outputs, about 200 emission factors, and over 600 data sources. It is intended for researchers, practitioners, and tool developers to support LCI development, cross-study comparison, and integration into databases, knowledge bases, and decision-support tools.