Life Cycle Sustainability Assessment of Agriproducts in Latin America: Overview Based on Latent Dirichlet Allocation

Abstract

This study explores the use of Life Cycle Assessments (LCAs), Total Sustainability Assessment, and Life Cycle Sustainability Assessment (LCSA) as tools to evaluate the environmental, social, and economic impacts in Agri-industry. It highlights the unique trajectory of LCA and LCSA implementation in Latin America, shaped by the region’s distinct environmental, social, and economic contexts, contrasted with global research trends. Evidence shows the importance of biodiversity, conservation, and deforestation mitigation in Latin American LCA applications, which differ from the urban-focused impacts seen in regions like Europe or North America. Furthermore, it emphasizes the significant role of LCSA in addressing socio-economic challenges unique to Latin America, such as inequality and labor conditions. The research reveals the benefits of LCA and LCSA methodologies in the agro-industrial sector, particularly in addressing social issues like land use rights and rural community welfare. Despite challenges such as limited access to high-quality data and the need for capacity building, the innovative application of these methodologies in Latin America offers valuable insights for the global community. Our work relies on Latent Dirichlet Allocation (LDA) to analyze the LCSA literature from 1990 to 2024, identifying evolving trends and research focal areas in sustainability. The analysis herein presented highlights the need for a multi-dimensional and holistic approach to sustainability research and practice. Our findings also emphasize the importance of developing comprehensive models and integrated methodologies to effectively address complex sustainability challenges. Environmental information remains crucial for policy processes, acknowledging uncertainties in estimations and the connection between land use change, agriculture, and emissions from the global food economy and bioenergy sectors. The research underscores the dynamic nature of LCSA and the importance of continually reassessing sustainability efforts to address pressing challenges.

1. Introduction

Life Cycle Assessments (LCAs), Total Sustainability Assessment (TSA), and Life Cycle Sustainability Assessment (LCSA) have traditionally served as analytical tools to evaluate the environmental, social, and economic impacts of products, processes, or services [1,2,3]. Outcomes of LCSA studies provide critical insights for businesses and consumers, pinpointing areas of operational efficiency. Results allow identifying opportunities for improvement and mitigating adverse effects across sustainability dimensions [4]. LCSA is a holistic examination of a product’s life cycle, covering all stages from the extraction of raw materials through to manufacturing, distribution, and ultimate disposal or recycling [3]. Furthermore, the methodology includes the entire life cycles of ancillary materials utilized in production. Social Life Cycle Assessment (S-LCA) [5] and Socio-Economic Assessments (SEA) introduce additional layers of impact analysis [6]. S-LCA and SEA offer valuable data for stakeholders committed to implementing responsible production and consumption practices. Comprehensive assessments are instruments which guide decision-making processes that align with sustainability objectives [7,8].

LCSA was originally developed for single products, but it has been increasingly applied to broader decision-making contexts. In the bigger scope for example, LCSA has been used for determining whether to construct specific energy production facilities, such as a power plant or a biorefinery [9,10]. The shift towards using LCSA in larger contexts is partially due to its effectiveness in assessing the environmental impacts of products [11]. This shift in perspective from “conventional” to “unconventional” products is characterized by two types of Life Cycle Assessments (LCAs). (I) The first type, Attributional Life Cycle Assessment (ALCA), focuses on detailing the environmentally relevant flows that a product or process emits and receives. ALCA provides a comprehensive view of the environmental impacts associated with a product’s life cycle. It encompasses raw material extraction, materials processing, manufacturing, distribution, use, repair and maintenance, and ultimately, disposal or recycling [12]. (II) Consequential life cycle assessment (CLCA) describes how relevant environmental flows will respond to decisions made and changes in the analyzed scenario [13,14]. In CLCA, the system boundaries are established to consider all activities that contribute to the environmental consequences of the change. CLCA is indifferent to whether the activities fall within or outside the cradle-to-grave system under investigation [15,16,17,18]. As a result, the process of system expansion (to avoid or deal with the allocation problem in multi-product systems) is an inherent part of the methodology. CLCA includes additional economic concepts like marginal production costs, elasticity of supply and demand, dynamic models (instead of the linear and static models of traditional LCA), etc. [9,19]. CLCA is more complex than traditional LCA, and the results obtained are highly sensitive to assumptions made [20]. The failure to identify inadequate implicit assumptions will lead to a deficient analysis.

In ALCA, average data are used to represent the typical environmental burden associated with producing a unit of the good or service within the system. On the other hand, consequential LCA uses marginal data, which reflect the environmental effects coming from a small change in the output of goods and/or services [12,14]. Focusing on marginal data by CLCA reduces the amount of data needed, as it only requires information about the indicators that change due to the intervention. ALCA, on the contrary, requires all relevant indicators to be known, regardless of whether they change or not [12,14,18]. The challenge in CLCA is thoroughly justifying that indicators will not be impacted and can be ignored.

Let us consider “AgroLatina Inc.”—a hypothetical agricultural company—requesting a Life Cycle Assessment (LCA) of their latest product: a batch of organic coffee. AgroLatina Inc. is interested in understanding the environmental footprint (E-LCA) of its coffee production and identifying opportunities for reducing emissions and other negative environmental impacts. Additionally, AgroLatina Inc. seeks insights into the social and socio-economic effects of their activities on workers and communities.

In the context of sustainable coffee production, companies like AgroLatina Inc. are keen on broadening the ethical evaluation to cover the entire life cycle [21,22]. The study must go from planting to consumption—or even adopt a “Cradle to Cradle” approach, where coffee waste is repurposed into new products [23]. The comprehensive analysis would include considerations of transportation, waste management, and other stages. Detailed specifications help analysts focus on acquiring data and information relevant to AgroLatina Inc.’s goals. This includes assessing emissions to air, water, and soil and identifying the spectrum of chemicals used during cultivation, recognizing that some may be more detrimental than others. Special attention will likely be given to greenhouse gas emissions like CO₂ and CH₄, as they have been considered for other crops like Maize [24], Wheat [25], or Quinoa [26]. Collaborative efforts with analysts are crucial to determine the necessary data for the study. Moreover, analysts must inform stakeholders about which life cycle stages are most labor-intensive and where social impacts may be most significant. This requires additional data to provide a complete overview of the product’s life cycle impacts [7]. The integration of such CLCA is pivotal for companies like “AgroLatina Inc.” to ensure that products are ethically produced and sustainably managed throughout their entire life cycle.

Environmental impacts are more straightforward to standardize and quantify compared to social and socio-economic impacts. [8,21,27]. Emissions, for example, can be readily measured, and the gathered quantitative data can be used over and over. However, Social Life Cycle Assessments (S-LCAs) are surely as important as environmental ones [8,10,22]. How can we proceed to conduct an S-LCA? How do we collect the data? How can we begin to assess and measure the social effects of a T-shirt? How do we define a socially responsible company or practice? How do we bring the results for every phase of the life cycle together? These questions must be answered.

One of the most significant challenges with S-LCA is maintaining consistency in standards across different studies. Variations will always exist, even if the criteria eventually become more aligned. S-LCAs often need to rely heavily on qualitative data, as quantitative data alone may not adequately address the issues at hand. When numerical data is useful, additional context is still required to interpret its meaning. For example, compliance with minimum wage laws does not necessarily equate to livable wages. Frequently, data must be collected on-site, as databases for specific social and socio-economic impacts are often missing. As one might expect, the current limitations of S-LCA are numerous.

TSA and LCSA are two related frameworks for evaluating the sustainability of systems, products, or services. TSA adopts an expansive approach, covering a wide range of sustainability indicators, including environmental, economic, social, and cultural dimensions. It is typically applied to organizations or business models to assess overall sustainability performance, often using qualitative measures and involving stakeholders. In contrast, LCSA is more focused, combining LCA with economic (Life Cycle Costing—LCC) and SLCA considerations. Therefore, LCSA is the tripartite nature of sustainability.

LCSA traces the impacts of a product or service from inception to end-of-life using quantitative data. While TSA provides a broad overview of sustainability, LCSA offers a detailed, data-driven analysis, making it a powerful tool for identifying specific areas for improvement and guiding strategic decisions in sustainability. Despite their methodological differences, both frameworks are crucial for pursuing sustainable development. Analyzing the implementation of the methodologies in South America reveals a growing commitment to sustainable development across the region. Initially, TSA and LCSA were introduced to address environmental concerns, particularly in response to the region’s rich biodiversity and the environmental pressures from industrialization and agricultural expansion. Countries like Brazil, Argentina, and Chile spearheaded the adoption of LCA, using it to assess the environmental impacts of key industries such as agriculture, forestry, and mining. Meanwhile, other countries in the region, such as Ecuador, Colombia, Peru, Paraguay, Uruguay, Venezuela, and Bolivia, are only beginning to implement the methodology in their local industries. Moreover, research and technological advancements in this area remain limited.

This manuscript explores the integration of social and economic dimensions into LCSA in South America, particularly in the agricultural and agro-industry sectors. The scope is to outline the growing importance of LCSA in addressing key socio-economic challenges, such as inequality and labor conditions, which are critical in developing countries. The following sections detail the methodology employed, focusing on the use of Latent Dirichlet Allocation (LDA) for topic modeling. This approach is applied to abstracts from indexed research articles collected from CrossRef and DOI databases to identify prominent themes in LCSA research published between 2020 and 2024. The results section presents an analysis of the key topics and their statistical relevance, followed by a discussion of how these findings reflect broader global trends and specific regional sustainability concerns. Finally, the aim is to emphasize the study’s implications for future research and policy development in promoting sustainable practices across South America’s agricultural sectors.

2. Materials and Methods

LDA is an unsupervised generative probabilistic model used for topic modeling within a corpus [28]. Topic modeling is an unsupervised method for classifying documents into natural groups or topics, like clustering in numeric data. It identifies groups of related items even when the specific topics are unknown [29,30]. A document can be a part of multiple topics; based on posterior probabilities estimation, it is possible to classify and infer contributions to a set of topics. Topic modeling helps automatically organize, understand, search, and summarize large electronic files by discovering hidden themes, classifying documents according to these themes, and using this classification to manage and search the documents. LDA, one of the most popular topic modeling algorithms, relies on Dirichlet distribution. It treats each document as a mixture of words and each topic as a collection of words. The aim of LDA is to identify the topics a document is associated with based on its words. LDA clusters words into different topics, and topics can be ranked by posterior probability scores (PPSs). The top words from each topic are selected to represent and describe the topic.

In this study, we conducted a comprehensive literature review to assess the scope of Life Cycle Sustainability Assessment (LCSA) in agriculture and Agri-products. The methodological framework was developed by installing and loading essential R V 4.2.1 packages, including “tm” for text mining, “topicmodels” for statistical modeling, and “slam” for matrix operations. We also used “rcrossref” and “metafor” for metadata and bibliometric analysis.

A systematic search was conducted using the cr_works function from the rcrossref package. The search queries were designed to capture a broad spectrum of literature related to LCSA, including environmental, social, and techno-economical aspects, as well as Life Cycle Assessment (LCA) in the agriculture and food sectors. Two specific queries were used:

(i)

Global Query: “Life Cycle sustainability Assessment + environmental + social + technoeconomical + Life Cycle Assessment + Agriculture + Agri-products + agricultural + Food”;

(ii)

Latin-America Query: “Life Cycle sustainability Assessment + environmental + social + technoeconomical + Life Cycle Assessment + Latin America + Agriculture + Argentina Bolivia + Brasil + Chile + Colombia + Costa Rica + Cuba + Ecuador + El Salvador + Guatemala Haití + Honduras + México + Nicaragua + Panamá + Paraguay + Perú + República Dominicana + Uruguay + Venezuela + Agri-products + agricultural + food”.

The search was filtered to include papers with ORCID identifiers, abstracts available, and published dates. This supported the inclusion of peer-reviewed and credible sources, enhancing the reliability of the data aiming to discover topics in a collection of documents, and then automatically classify them by a Bayesian network.

Abstracts of the retrieved papers were extracted and printed for preliminary analysis. To facilitate a deeper investigation into the thematic structures of the literature, the abstracts were compiled into a text corpus after removing any missing values. The corpus underwent a series of preprocessing steps using the tm package, which included converting the text to lowercase, removing punctuation, discarding common English stop-words, and eliminating extra whitespace. These preprocessing steps were crucial for standardizing the text data, ensuring consistency and accuracy in the subsequent thematic analysis. The processed corpus served as a basis for developing a topic model using the Latent Dirichlet Allocation (LDA) algorithm. The LDA model was implemented using the topicmodels package. The robustness of the LDA model was ensured by the following:

(i)

Selecting an appropriate number of topics (k): Various values of k were tested, and the model’s coherence score was used to determine the optimal number of topics.

(ii)

Cross-validation: The model was validated using a subset of the data to ensure its generalizability.

(iii)

Parameter tuning: Hyperparameters such as alpha and beta were fine-tuned to improve model performance.

To facilitate a deeper investigation into the thematic structures of the literature, abstracts from the papers were compiled into a text corpus after removing any missing values. This corpus underwent preprocessing using the tm package, which included converting the text to lowercase, removing punctuation, discarding common English stop words, and eliminating extra whitespace. This preprocessing was essential for standardizing the text data, ensuring consistency and accuracy in the subsequent thematic analysis. The processed corpus provided the foundation for developing a topic model to uncover latent thematic patterns within the extensive literature on LCSA in the agricultural sector, both globally and in Latin America, following the steps remarked in Figure 1.

3. Results

3.1. LCA and LCSA Approaches in Latin America

The application of Life Cycle Assessment (LCA) and Life Cycle Sustainability Assessment (LCSA) methodologies in Latin America has shown a unique trajectory shaped by the region’s specific environmental, social, and economic contexts. Compared to the rest of the world, Latin America’s approach to these methodologies highlights both shared global trends and distinct regional adaptations. However, the future pathway of the application of LCA and LCSA approaches in Latin America remains unclear.

In Latin America, the initial application of LCA was largely driven by the region’s rich biodiversity and the need to balance economic development with environmental conservation, which was applied later in the 2000s. Countries like Brazil, Colombia, and Argentina have utilized LCA to evaluate the environmental impacts of key industries such as agriculture, forestry, and mining [12,31,32,33,34]. For instance, Brazil’s extensive use of LCA in the sugarcane industry to produce bioethanol reflects a strong commitment to reducing greenhouse gas emissions and promoting renewable energy. This mirrors global trends where LCA is used to optimize resource use and mitigate environmental impacts. However, the focus on preserving biodiversity and addressing deforestation gives Latin American LCA studies a unique emphasis compared to regions like Europe or North America, where industrial impacts on urban environments are more prevalent.

In the energy sector, Latin America has leveraged LCA to evaluate the impacts of various energy production methods, including hydropower and biofuels [35,36,37]. Brazil’s leadership in bioethanol production from sugarcane is a prime example of how LCA has been used to optimize the environmental performance of renewable energy sources [38,39,40,41,42]. Other countries worldwide use LCA to support energy transitions; the emphasis in Latin America on biofuels to reduce dependency on fossil fuels and improve energy security is particularly pronounced [31,34,42,43,44]. In contrast, regions like Europe focus heavily on wind and solar energy, reflecting their geographical and climatic needs.

The integration of LCSA in Latin America has been particularly significant in addressing the socio-economic challenges unique to the region, such as inequality, accessibility, well-being, and labor conditions. Meanwhile, LCSA methodologies worldwide aim to provide a holistic view of sustainability, and Latin American applications often place greater emphasis on one dimension: social [45]. For example, the refining industry in Colombia and the recycling industry in Peru have adopted LCSA to improve labor conditions, ensure fair wages, and support community development [46,47,48]. This contrasts with regions like Europe, where LCSA applications might prioritize economic sustainability and consumer impacts more heavily.

In the context of this work, Latin America’s agro-industrial sector has been a major beneficiary of LCA and LCSA methodologies. LCA has been used extensively to assess the sustainability of beef and dairy production in countries such as Argentina, Colombia, and Paraguay [49,50,51,52]. In other cases, such as Brazil, the methodology is used for the analysis of seed-derived products and the sustainable development of crops [26,38,53,54,55]. However, in all cases, the aim has mainly focused on reducing deforestation, social issues, and greenhouse gas emissions. The application of LCSA in these sectors also addresses social issues such as land use rights and the well-being of rural communities. This approach is somewhat different from practices in the United States or Australia, where LCA in agriculture might concentrate more on technological innovations and efficiency improvements.

Despite these advancements, the application of LCA and LCSA in Latin America faces several challenges, including limited access to high-quality data and the need for capacity-building among practitioners. The delay and the implementation and development of the methodology can be clearly seen in Figure 2, which shows that South America began exploring the field approximately 10 years later. Regions like Europe and North America benefit from more established databases and stronger institutional support for sustainability assessments. Nonetheless, Latin America’s innovative use of these methodologies to address local sustainability issues provides valuable insights and opportunities for the global community. However, it is a matter of time before the region levels the balance, especially for countries with economic power in the region, such as Brazil, Chile, and Argentina.

3.2. Latent Dirichlet Allocation (LDA) Results

The LDA results reveal a range of topics, each focusing on different aspects of LCSA, the global trends from 2020 to 2024 are presented in

Table 1. Words clusters generated by the LDA model under global query.

Topic 1: Environmental Impact and Production Processes	Topic 2: Agricultural and Animal Production Impacts	Topic 3: Environmental Footprint of Products	Topic 4: Energy Systems and Emissions	Topic 5: LCA Studies and Methodological Challenges	Topic 6: LCA Approaches and Tools	Topic 7: Technology, GHG Emissions and Climate	Topic 8: Building Materials and Infrastructure	Topic 9: Global Environmental Scenarios	Topic 10: Waste Management and Recycling	Topic 11: Sustainability Indicators and Frameworks
environmental	production	Products	energy	lca	approach	life	building	impact	waste	sustainability
process	impacts	water	emissions	studies	different	performance	environmental	potential	environmental	social
production	environmental	Food	electricity	research	results	cycle	life	environmental	scenario	assessment
impacts	system	Environmental	system	data	based	cost	construction	categories	life	life
processes	use	producto	gas	literature	can	economic	carbon	global	management	indicators
results	agricultural	Consumption	systems	life	model	results	materials	study	study	framework
technology	systems	Impact	ghg	review	method	analysis	cycle	warming	scenarios	slca
assessment	impact	Supply	cycle	cycle	assessment	concrete	design	life	recycling	sustainable
considered	land	Footprint	fuel	study	analysis	costs	buildings	human	cycle	development
raw	using	Impacts	renewable	future	developed	study	lca	cycle	circular	slca
material	organic	Chain	consumption	analysis	used	infrastructure	potential	depletion	assessment	economic
manufacturing	soil	Results	technologies	several	proposed	significant	emissions	gwp	impacts	results
extraction	conventional	Use	greenhouse	paper	however	higher	impacts	using	plastic	value
industrial	feed	Milk	climate	challenges	tool	using	using	eutrophication	packaging	sector
resources	agriculture	Primary	emission	methodological	lca	stages	stage	assess	materials	assess

and can be interpreted as follows.

• Topic 1 centers on environmental impacts and production processes, particularly resource extraction and industrial manufacturing (PPS = 0.1373).
• Topic 2 focuses on the environmental impacts of agricultural and animal production, including land use, soil health, and the consumption of organic and conventional feed (PPS = 0.0313).
• Topic 3 addresses the environmental footprint of products, especially food and primary agricultural goods like milk and rice, along the supply chain (PPS = 0.0798).
• Topic 4 is concerned with energy systems, focusing on electricity generation, gas, renewable technologies, and their greenhouse gas (GHG) emissions and climate impact related to agrisystems (PPS = 0.0424).
• Topic 5 provides a review and overview of life cycle assessment (LCA) studies, including literature reviews, data analysis, and methodological challenges (PPS = 0.0323).
• Topic 6 discusses various LCA approaches, including model-based and tool-assisted analyses, as well as the development of new methods (PPS = 0.0775).
• Topic 7 examines the impact of technology systems on GHG emissions and global warming scenarios within agrisystems (PPS = 0.0805).
• Topic 8 focuses on the life cycle performance and economic analysis of building materials and infrastructure, such as concrete construction and design for agriculture and food production (PPS = 0.0719).
• Topic 9 explores the potential environmental impact of global scenarios, including climate change and human-induced eutrophication (PPS = 0.0240).
• Topic 10 covers waste management, emphasizing recycling and the life cycle of packaging materials, particularly plastics (PPS = 0.0518).
• Topic 11 discusses sustainability indicators and frameworks, with an emphasis on the Social Life Cycle Assessment (SLCA) and the economic value of sustainable development (PSS = 0.0194).

The frequent occurrence of keywords like “environmental” and “cycles” across multiple clusters highlights their broad applicability and fundamental importance within the field of LCSA. The repetition of the aforementioned keywords underscores the interconnected nature of the topics, suggesting that a holistic approach is crucial for addressing sustainability issues. The presence of these core concepts across various clusters indicates the complexity and multi-dimensionality of LCSA, where different aspects are interrelated and cannot be studied in isolation. This emphasizes the need for comprehensive and integrated research methodologies to effectively analyze and address environmental impacts and sustainability challenges.

Figure 3 highlights the differences in topic prevalence between global and Latin America. Topic 2 shows a significant increase from 0.03128 to 0.13318, indicating a growing interest in the environmental impacts of agricultural and animal production. Topic 2 includes land and soil use and the consumption of organic and conventional feed in Latin America. Topic 3 has decreased from 0.07982 to 0.03811, representing a reduced emphasis on the environmental footprint of food and primary agricultural products, such as milk and rice, along the supply chain in Latin America. Topic 9 has risen from 0.02403 to 0.10890, indicative of increased concern about the potential environmental impacts of global scenarios, including climate warming and human-induced eutrophication. Topic 10 has increased from 0.01938 to 0.06874, indicating an interest in waste management, particularly recycling and the life cycle of packaging materials. Finally, Topic 11 remains relatively stable, with a slight decrease from 0.04561 to 0.04534. The changes in topic probabilities highlight the contextual differences and the gap between Latin American and global research efforts and budgets dedicated to these topics (see Figure 2).

The bar graph presented in Figure 4 represents the composition of different topics (T1 to T11) in four different papers that were taken as an example for the analysis in this work. The used works represent an example of the application of LCSA and LCA in Latin America. They will be referenced as Paper 1, Paper 2, Paper 3, and Paper 4 for the analysis.

In comparing the four papers based on the LDA results, distinct differences in topic focus were observed. Topic 9, which addresses the potential environmental impact of global scenarios, showed the most significant variation in increasing this topic’s prevalence in Latin America. Paper 1 emphasized this topic the most (PPS = 0.3976), while Paper 2 gave it the least attention (PPS = 0.0556). This indicates a major difference in focus, with Paper 1 dedicating nearly 40% of its content to this topic, compared to just over 5% in Paper 2. In contrast, Topic 11, covering sustainability indicators and frameworks, was most prominent in Paper 2 (PPS = 0.2702) and least in Paper 1 (PPS = 0.0643). This suggests that Paper 2 prioritizes sustainability frameworks, while Paper 1 places less emphasis on them.

Topic 1 significantly contributes to Paper 3, suggesting a strong focus on the environmental impacts and production processes, particularly concerning resource extraction and industrial manufacturing related to agriproducts. The notable contribution of Topic 7 in Paper 3 indicates that the paper likely addresses the impact of technology systems on greenhouse gas emissions and global warming scenarios in agri-systems. In Paper 4, Topic 1, Topic 7, and Topic 8 contribute notably, similar to Paper 3, but with different proportions. This suggests that while Paper 4 focuses on these areas, the emphasis differs from Paper 3. Additionally, Topic 6 is more prominent in Paper 4 than in the other papers, indicating a significant focus on various approaches to Life Cycle Assessment, including model-based and tool-assisted analyses and the development of new methods. These findings highlight the diverse focus areas across the papers, underscoring the broad spectrum of research within the field of LCSA. The marked differences in topic emphasis also suggest varying research interests and approaches among the authors of the considered works. Further research could delve into the implications of these differences and their impact on the field of LCSA.

4. Discussion

The implementation of LCA and LCSA methodologies in Latin America has shown a distinctive trajectory. It has been influenced by the region’s unique environmental, social, and economic contexts [3,35].

The rich biodiversity of Latin America and the need to balance economic growth with environmental preservation have been key drivers in the early adoption of LCA [60,61]. Nations such as Brazil, Colombia, and Argentina have applied LCA to assess the environmental repercussions of the activities from crucial sectors like agriculture, forestry, food, and mining [12,18,62,63]. The emphasis on biodiversity conservation and deforestation mitigation gives Latin American LCA studies a unique focus, in contrast to regions like Europe or North America, where the impact of industries on urban environments is more dominant. The incorporation of LCSA in Latin America has been crucial in addressing the region’s unique socio-economic challenges, i.e., inequality and labor conditions [7,21,64]. Applications in Latin America often emphasize social impacts, contrasting with regions like Europe, where LCSA tends to prioritize economic sustainability and consumer impacts more heavily. The agro-industrial sector in Latin America has greatly benefited from LCA and LCSA methodologies [26,35,60,65], particularly in addressing social issues such as land use rights and the welfare of rural communities. This approach differs from practices in the United States or Australia, where LCA in agriculture might focus more on technological innovations and efficiency improvements [66,67,68,69].

The application of LCA and LCSA in Latin America faces several challenges, including limited access to high-quality data and the need for capacity building among practitioners [70,71]. Nevertheless, the region’s innovative use of these methodologies to address local sustainability issues provides valuable insights and opportunities for the global community. With time and strategic political decisions, the region will achieve equilibrium, especially for economically powerful countries in the region, such as Brazil, Chile, and Argentina [72,73,74,75,76,77].

The Latent Dirichlet Allocation (LDA) analysis of the literature from 1990 to 2024 has revealed a diverse range of topics within the domain of LCSA, each providing insights into the evolving trends and research focal areas [73]. The thematic distribution reflects a multifaceted exploration of environmental, social, and techno-economic dimensions in agriculture and food production. It underscores the interplay between sustainability and technological advancements [73,75,78,79]. The observed variations in topic probabilities between global and Latin American contexts show the influence of regional priorities, research efforts, and resource allocation on the LCSA literature. The differences can be attributed to the unique environmental challenges, socio-economic conditions, and policy frameworks that shape the research agenda in Latin America compared to the global stage. The frequent appearance of keywords such as “environmental” and “cycles” across multiple clusters in the LDA results suggests that these concepts are transversal to the theoretical framework of Life Cycle Sustainability Assessment (LCSA). The keyword appearance indicates that LCSA research requires a multi-dimensional approach, integrating various aspects of environmental science, sustainability, and life cycle analysis. Theoretically, this shows the need for comprehensive models that link different sustainability factors, helping us understand complex environmental systems better. Practically, the repeated use of key terms highlights the need for integrated methods like fuzzy logic in sustainability assessments. For practitioners, this means considering all environmental impacts and life cycle stages, not just isolated parts. This approach can lead to better decision-making in industries such as manufacturing, agriculture, and energy production. It also helps policymakers create effective regulations and standards by addressing the full scope of environmental sustainability, leading to stronger and more impactful practices.

The trends in LCSA topics between Latin America and the global context reveal important shifts in sustainability research priorities. In Latin America, the rise in Topic 2, which addresses the environmental impacts of agricultural and animal production, reflects the region’s focus on its strong agricultural sector and its environmental effects. The decrease in Topic 3, which covers the environmental footprint of products along the supply chain, might indicate a shift in research focus or saturation in this area. The increase in Topic 9, dealing with global environmental scenarios, shows a growing concern about climate change. The rise in Topic 10, on waste management and recycling, highlights increasing concerns about waste and packaging impacts. The stability of Topic 11 indicates its steady importance in LCSA analyses both regionally and globally. These trends show that LCSA research is evolving and highlight the need to continually reassess our sustainability efforts. Monitoring these trends and understanding their causes will help ensure that sustainability practices remain effective and relevant. While this study offers valuable insights into the scope of Life Cycle Sustainability Assessment (LCSA) in agriculture and Agri-products, it has several potential limitations. One major challenge is the reliability of data, especially in regions with limited data availability. In many developing areas, including parts of Latin America, environmental, social, and economic data may be sparse or inconsistent, leading to uncertainties in the results and limiting the applicability of the findings. Additionally, the diversity of agricultural practices and socio-economic conditions across regions adds complexities. Availability and variability in data quality can affect the accuracy of the LCA and LCSA models, making it hard to draw broad conclusions. To address these issues, efforts are needed to improve data collection and standardization in these regions.

To provide a balanced view, it is important to note where further research is needed. Future studies should focus on improving methods to handle data gaps and uncertainties. This could include using advanced statistical techniques or the integration of qualitative data to complement quantitative assessments.

5. Conclusions

The use of LCA and LCSA in Latin America has made promising progress, reflecting the region’s commitment to sustainable development and contributing valuable insights to global sustainability discussions. However, a notable weakness is the limited focus on innovation and technology development, which slows the region’s progress compared to Europe and North America. This paper offers important insights into the current state and future directions of LCSA research. Using LDA to analyze global trends, the study identifies key topics and highlights how sustainability issues are interconnected. Core concepts like “environmental” and “cycles” frequently appear across different topics, showing the need for a broad and holistic approach.

The study reveals that the implementation of LCA and LCSA in Latin America has developed uniquely compared to global trends. The region’s focus on preserving biodiversity and mitigating deforestation contrasts with the urban-focused environmental concerns of Europe and North America. Latin American LCSA studies place significant emphasis on addressing socio-economic challenges, such as inequality and labor conditions, reflecting the region’s unique social context. This highlights the necessity for tailored sustainability methodologies that align with local environmental, social, and economic priorities. Growing Focus on Agricultural and Environmental Impacts: The use of LDA identified key topics within the LCSA literature, showing a notable increase in research focused on the environmental impacts of agricultural and animal production in Latin America. This includes concerns about land and soil use, organic and conventional feed consumption, and global environmental scenarios such as climate change and eutrophication. The study also emphasizes a rising interest in waste management, particularly recycling and the life cycle of packaging materials. These findings suggest a shift in research priorities towards more sustainable practices and a holistic understanding of the environmental and social dimensions of agriproducts in the region.