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Analysis of agricultural emissions and economic growth in Europe in search of ecological balance

  • Vanya Georgieva EMAIL logo
Published/Copyright: October 22, 2024
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Open Agriculture
From the journal Open Agriculture Volume 9 Issue 1

Abstract

This study analyses the relationship between economic growth, measured by gross value added in agriculture, and greenhouse gas emissions from the sector in 30 European countries during the period 2012–2021. The aim is to assess whether the increase in agricultural production leads to a corresponding increase in harmful emissions. Regression analysis is applied to establish linear statistical dependencies between variables, cluster analysis to group countries, and analysis of trends in the dynamics of indicators. The results show significant differences between countries, with no universal relationship between economic growth and emissions. A “decoupling” between growth and emissions is observed in some countries, demonstrating the potential for “green growth.” Regional and structural differences, as well as the level of technological development, stand out as key factors determining the relationship between economic growth and emissions, highlighting the need for an individualised approach in formulating policies for the sustainable development of the agricultural sector.

Keywords: greenhouse gases; agriculture; economic growth; Europe

1 Introduction

Agriculture is a vital sector for European economies, providing not only food but also income and employment in rural areas. Despite its significance, the sector faces a serious challenge – the need to reduce its carbon footprint without compromising its productivity. This dilemma is at the centre of contemporary debates on sustainable development and climate change.

Greenhouse gas emissions from agriculture, primarily methane and carbon dioxide, remain high, making their reduction a priority for sustainable development [1]. Intensive agricultural practices and the expansion of livestock farming increase greenhouse gas emissions and environmental pressure [2,3]. In the context of a growing world population and increased food needs, the introduction of environmentally friendly practices is becoming increasingly necessary to ensure food security and reduce negative impacts on the climate [4,5].

Multiple factors contribute to emissions from agriculture, including demographic changes, technological advancements, and changes in dietary habits [6]. Changes in land use, especially the expansion of arable land, also play a significant role [7,8,9,10]. Biomass burning represents another significant source of emissions [11,12].

The agricultural sector faces the challenge of reducing its emission intensity while maintaining its contribution to economic growth and employment. The European Union’s (EU) Common Agricultural Policy (CAP) aims for sustainable development of the sector while reducing its environmental impact [13]. Despite efforts, emissions remain significant, highlighting the need for additional measures and refinement of existing policies [14]. Studies show that EU strategies do not always achieve their emission reduction goals [15], and investments in research and development and employment in the sector may even increase emissions [16].

Innovative technologies and environmentally friendly practices are key to reducing emissions. Lapinskienė et al. [17] demonstrate that innovations and energy taxes can significantly reduce greenhouse gas emissions. Neagu and Teodoru [18] emphasise the need for country-specific policies tailored to their economic and energy structures. Sustainable agricultural policies and renewable energy consumption can significantly contribute to emission reduction [19].

In this context, the present study offers a detailed analysis of the relationship between gross value added (GVA) in the agricultural sector and greenhouse gas emissions for 30 European countries over the period 2012–2021. This analysis allows not only for the identification of general trends but also for the examination of individual characteristics of each country, taking into account factors such as innovation, investment and policy initiatives.

Unlike previous studies, which often limit themselves to general trends, this study integrates economic and environmental indicators into a single framework. This approach provides a deeper understanding of the current state and offers new perspectives for political and practical application. The period 2012–2021 is chosen in light of significant changes in EU policies regarding climate and agriculture, including reforms in the CAP and the adoption of the European Green Deal.

The main aim of the study is to determine whether an increase in agricultural production inevitably leads to increased emissions or whether there are models that successfully combine economic growth with a reduction in environmental footprint. The results of the study have the potential to inform the development of more effective and targeted policies that can support European countries in achieving a balance between economic development and emission reduction in the agricultural sector.

2 Theoretical framework

Greenhouse gas emissions and their relationship with economic growth are an important topic in contemporary research, especially in the context of efforts to achieve sustainable development [20,21,22,23,24,25]. In the EU, which aims to achieve carbon neutrality by 2050, understanding this relationship is of utmost importance for shaping effective policies.

One of the main areas of research is how economic growth affects greenhouse gas emissions. The classical economic model suggests that economic growth leads to increased use of resources and consequently to an increase in greenhouse gas emissions. However, research within the EU shows that this relationship is not always linear. For example, Murawska and Goryńska-Goldmann [26] find that in the EU, economic growth does not always lead to a proportional increase in emissions. This study shows that in countries where the agricultural sector plays a key role in the economy, greenhouse gas emissions can remain high despite economic improvements.

The relationship between economic growth and greenhouse gas emissions is often analysed through the Environmental Kuznets Curve theory. According to this theory, in the early stages of economic development, emissions increase along with income, but after reaching a certain level of income, a decrease in emissions begins to be observed. Jovanović et al. [27] prove the validity of this theory in the context of European developing and developed economies, highlighting the significant differences between them. In developed economies, a certain level of sustainable development has been achieved where emissions begin to decrease, while in developing countries this process is still in its early stages.

Although economic growth is often associated with increasing greenhouse gas emissions, there are cases where this model is not confirmed. The study by Zafeiriou et al. [28] finds that in some European countries, the relationship between agricultural income and greenhouse gas emissions is non-linear. This suggests that economic growth can be achieved without significantly increasing emissions if appropriate policies and technologies are applied.

Other studies support the idea of significant differences between European countries regarding the relationship between economic growth and emissions. For example, the study by Lapinskienė et al. [17] finds that some European countries, such as the Baltic states, show a positive correlation between energy consumption and GHG emissions, while other factors such as innovation and energy taxes have an inverse effect on emissions. Research shows that economic complexity and the structure of energy consumption also play a key role in determining greenhouse gas emissions in the EU. For example, according to Neagu and Teodoru [18], countries with lower economic complexity are more at risk of increased greenhouse gas emissions as economic complexity grows, especially when the energy balance leans towards non-renewable sources. This is particularly true for countries with less developed industries and a high dependence on carbon-intensive energy sources. According to Liu et al. [29], increasing agriculture and renewable energy reduces carbon dioxide emissions, while non-renewable energy increases emissions.

In their study, Cheng et al. [30] analyse the relationship between the concentration of agricultural production and the efficiency of carbon emission used in the agricultural sector. They find that this relationship follows the so-called Kuznets curve – initially, as agglomeration (concentration of production) increases, so does carbon efficiency. However, after reaching a certain level, further enlargement of the scale of economic units leads to a decrease in efficiency from the perspective of greenhouse gas emissions.

The EU is a world leader in policies to reduce carbon footprint and achieve climate neutrality. Some EU countries stand out with particularly successful strategies and practices that can serve as examples for other countries. For instance, Germany and Denmark are leaders in implementing innovative technologies and renewable energy sources in agriculture. Research shows that these countries have managed to significantly reduce their greenhouse gas emissions thanks to the widespread use of biogas plants and other technologies for utilising livestock waste [31]. These technologies not only reduce methane emissions but also generate clean energy that can replace conventional energy sources. Sweden has also made significant progress in reducing emissions from agriculture by implementing integrated farming systems that combine crop and livestock production. These systems allow for more efficient use of resources and reduction of greenhouse gas emissions, while improving soil health and biodiversity [32].

Integrated agroecological practices are another effective tool for reducing emissions in agriculture. These practices include the use of cover crops, crop rotation, and pasture management, which help to retain carbon in the soil and reduce the need for synthetic fertilisers and pesticides [33]. Research shows that these methods can lead to significant reductions in carbon dioxide and methane emissions. Some countries, such as France and the Netherlands, are applying innovative approaches like precision agriculture and digital technologies for emissions monitoring. These technologies allow for more efficient resource management and better control over emissions, leading to more sustainable production [34].

Although many European countries have made significant progress in reducing greenhouse gas emissions, there are still opportunities to improve existing policies and practices. One of the main challenges remains the integration of more sustainable practices in the smaller and less developed economies of the EU. Research shows that additional funding and support for farmers in these countries is necessary to enable them to implement new technologies and methods [35].

Another important area for improvement is the broader application of circular economy principles in agriculture, which can lead to waste reduction and resource utilisation. This includes using agricultural waste for biogas production or other forms of renewable energy [36].

A study of the relationship between emissions and economic growth in China from 1999 to 2013 identifies three stages: decoupling (1999–2004), coupling (2005–2009), and decoupling again (2010–2013) [37]. According to Farhani and Ozturk [38], the relationship between greenhouse emissions and economic growth is linear. Ozturk and Acaravci [39] and Balsalobre-Lorente et al. [40] define it as N-shaped, while according to Lantz and Feng [41], there is no significant correlation between the two factors.

Based on this literature review, the following research questions are formulated in this paper:

  1. What is the relationship between economic growth in agriculture, measured by its GVA, and the levels of greenhouse gas emissions in different European countries?

  2. What are the main factors that explain the lack of a universal linear dependency between these two variables in most of the analysed countries?

  3. What are the possible policies and measures to stimulate “green” economic growth in agriculture, so that the increase in production and incomes does not lead to a proportional increase in harmful emissions?

  4. Which European countries demonstrate the best results in terms of balancing economic growth in the agricultural sector and limiting the associated greenhouse gas emissions?

3 Methods

The present study focuses on analysing the relationship between two key variables in the agricultural sector: the GVA from agriculture (in million euros) and greenhouse gas emissions from agriculture (in million tonnes). The choice of these indicators is based on the theory of ecological modernisation, which suggests that economic growth and environmental sustainability can be compatible goals.

Gross value added (GVA) in agriculture is a fundamental economic indicator that measures the value added by this sector to the economy. The choice of GVA as an indicator is justified due to its role in reflecting agriculture’s contribution to economic development. It is directly linked to the sector’s efficiency and productivity and can indicate levels of innovation and investment, as well as improvement in the standard of living in countries where the agricultural sector plays a significant role.

Greenhouse gas emissions in agriculture are also a key indicator, important for assessing the environmental sustainability of agricultural practices. The inclusion of this indicator is based on its significance in revealing the relationship between economic development and environmental sustainability. It allows for the measurement of emission intensity, which reflects the efficiency of agricultural technologies and policies. Moreover, greenhouse gas emissions are directly influenced by regulations and policies aimed at reducing carbon emissions in agriculture.

Theoretically, the relationship between GVA and emissions can reveal the degree of environmental efficiency of agricultural production in different countries. The analysis of this relationship allows for an examination of how European countries balance economic growth in the agricultural sector by limiting their environmental impact.

To provide a better understanding of the distribution and characteristics of the main variables included in the analysis, Table 1 presents descriptive statistics for GVA and greenhouse gas emissions in agriculture for the period 2012–2021.

Table 1

Descriptive statistics of main variables (2012–2021)

Variable Mean Standard deviation Minimum Maximum
Greenhouse gas emissions (million tonnes CO2 eq.) 15.97 19.89 1.16 63.23
Gross value added (million euros) 4738.64 6697.77 151.10 35499.22

Source: Own calculations based on Eurostat data.

The study employs a quantitative approach, including cluster analysis, regression analysis, and trend analysis. Hierarchical cluster analysis is applied to 30 European countries, based on levels of greenhouse gas emissions and GVA from agriculture. Ward’s method and Euclidean distance are used, leading to the identification of four main clusters grouping countries with similar characteristics.

For each country, a linear regression model is developed, where greenhouse gas emissions are the dependent variable and GVA from agriculture is the independent variable.

The linear regression has the following formal construction:

y i t = α + β x i t + ϵ ,

where y it represents greenhouse gas emissions from agriculture for country i in year t, x it is the GVA from agriculture for country i in year t, α is a constant (intercept), β is the regression coefficient, which shows the degree of change in emissions with a change in GVA, and ϵ is the stochastic term (error).

Parameters such as coefficient of determination (R 2), regression coefficients, their significance, and p-values are estimated. Additionally, a trend analysis is conducted, examining the dynamics of variables separately by country for a 10-year period from 2012 to 2021.

The data for the study cover 30 European countries for a period of 10 years (2012–2021) and are extracted from the European Statistical Office (Eurostat) database. The criterion for selecting countries is the availability of comparable data for both main variables for a minimum of 10 years. The remaining European countries are not present in the sample due to the lack of a complete data series for one or both key indicators during the period under review.

The methodology has several limitations. Linear regression models do not account for potential non-linear relationships between the analysed variables. Furthermore, other country-specific factors such as climate, land use patterns, agricultural policies, and prices are not included. Cluster analysis, while useful for grouping countries, does not account for the unique characteristics of individual states. The trend analysis does not include regional variations within countries, which may mask important local differences.

For future research, the application of non-linear regression models and the inclusion of additional predictor variables characterising the national peculiarities of each country are suggested. It would also be useful to develop separate cluster models by region to better account for specificities. The trend analysis could be enriched through regional disaggregation of data within individual countries, which would allow for a more detailed understanding of local dynamics in the agricultural sector and associated emissions.

4 Results

4.1 Analysis of trends and growth rate of emissions and GVA by country for the period

Over the examined 10-year period, there is a trend of increase in the GVA from agriculture in most European countries. Leading in terms of growth rate are Ireland, Latvia, Czechia, Portugal and Romania.

At the same time, many countries report a decrease or limited growth in greenhouse gas emissions. The strongest decline in emissions is observed in Malta, Iceland, and Luxembourg. Another group of countries, where emissions are reducing, includes Belgium, Denmark, Germany, France, the Netherlands, Austria and Switzerland. In these countries, there is a decreasing trend in emissions alongside an increase in GVA.

However, there are also countries, where agricultural emissions are increasing together with the GVA. This applies most notably to Bulgaria, Estonia, Latvia, Lithuania, Slovenia, Finland and Sweden. In these countries, the link between economic growth and the rise of harmful emissions is still intact. But overall the data show that in most European countries there is already development of the economy without a respective increase in pollution.

In most European countries there is a trend of some increase in both the emissions and the economic activity in the sector. But there are exceptions as well, as in the Scandinavian countries, where the GVA from agriculture does not grow steadily.

4.2 Cluster analysis

The aim of the cluster analysis is to divide the European countries into groups according to their levels of GVA in agricultural production and associated greenhouse gas emissions.

By applying the K-means algorithm, four clusters were formed.

Cluster 1 from the conducted cluster analysis includes two European countries – Italy and Spain. Both are large economies with a well-developed agricultural sector, which has high productivity and competitiveness. Italy is the country with the highest GVA from agriculture among the 30 European countries analysed – around €32 billion. It is among the leading producers and exporters of various agricultural goods in Europe such as vegetables, fruits, olives and olive oil, wine. Spain also has a considerable GVA of around €26 billion and a strongly developed agricultural sector, specialised in products such as fruits and vegetables, oilseeds, and meat.

At the same time however, due to the large scale of their agricultural sectors, the two countries also generate high levels of greenhouse gases – around 29 million tonnes for Italy and 28 million tonnes for Spain (Figure 1). So despite their positive economic contribution, the agriculture of these countries also has a significant ecological footprint.

Figure 1 Dynamics of GVA and greenhouse gas emissions in cluster 1 (2012–2021). Source: Own calculations based on Eurostat data.
Figure 1

Dynamics of GVA and greenhouse gas emissions in cluster 1 (2012–2021). Source: Own calculations based on Eurostat data.

The second cluster includes France and Germany, which are among the largest economies in Europe with a highly developed agricultural sector. France is the second country after Italy in terms of GVA from agriculture – over €30 billion. The agricultural sector has high efficiency and productivity, with France being a world leader in the production of crops such as wheat, grain maize, and sugar beet. The situation is similar in Germany as well, whose agricultural sector generates over €19 billion in GVA. The country specialises in dairy and meat products, cereals, and industrial crops. Both countries are leading producers and exporters of a wide range of agricultural products in the region. However, due to the large scale of their agricultural sectors, both countries generate very high levels of greenhouse gas emissions (Figure 2). The main source is livestock farming activities, soil cultivation, use of fertilisers, etc. In recent years, both countries have undertaken measures to reduce emissions from agriculture. This includes support for organic farming, introduction of more sustainable practices, infrastructure improvements, etc. Nevertheless, their contribution to total EU greenhouse gas emissions remains substantial.

Figure 2 Dynamics of GVA and greenhouse gas emissions in cluster 2 (2012–2021). Source: Own calculations based on Eurostat data.
Figure 2

Dynamics of GVA and greenhouse gas emissions in cluster 2 (2012–2021). Source: Own calculations based on Eurostat data.

The third cluster includes a mix of large Western European economies such as the Netherlands, Switzerland, Denmark, Belgium, Portugal, Ireland and Austria and Central and Eastern European countries such as Poland, Hungary, Czechia, Romania, and Greece. Most of these 12 countries have a significant contribution of agriculture to their gross domestic product. For example, the Netherlands, despite its small territory, generates over €10 billion annually from the agricultural sector, thanks to its high intensity and productivity. Poland also has large and diverse agricultural production worth over €9 billion. The contribution of the remaining countries ranges between €3 and €8 billion.

At the same time, most of these 12 countries also maintain moderate levels of greenhouse gas emissions from agriculture – between 6 and 12 million tonnes annually (Figure 3). Thus, they achieve a good balance between economic growth and environmental sustainability in the agricultural sector. An exception is Ireland, where agriculture (mainly livestock) leads to 23 million tonnes of annual emissions. Additional nature-friendly measures are needed there.

Figure 3 Dynamics of GVA and greenhouse gas emissions in cluster 3 (2012–2021). Source: Own calculations based on Eurostat data.
Figure 3

Dynamics of GVA and greenhouse gas emissions in cluster 3 (2012–2021). Source: Own calculations based on Eurostat data.

Norway, Bulgaria, Sweden, Finland, Lithuania, Croatia, Slovakia, Slovenia, Latvia, Cyprus, Estonia, Iceland, Luxembourg and Malta form the fourth cluster. These are mainly smaller countries in Europe, located in the Northern, Eastern, and Central parts of the continent. Their economies are characterised by a relatively low contribution to the total value added from agriculture in the EU – between €57 million and €1.9 billion annually (Figure 4).

Figure 4 Dynamics of GVA and greenhouse gas emissions in cluster 4 (2012–2021). Source: Own calculations based on Eurostat data.
Figure 4

Dynamics of GVA and greenhouse gas emissions in cluster 4 (2012–2021). Source: Own calculations based on Eurostat data.

At the same time, they demonstrate low levels of greenhouse gas emissions – from just 0.09 million tonnes in Malta to 5.02 million tonnes in Finland. This is a significant difference compared to larger economies such as France, Germany, and Italy.

Most of the countries in this cluster are part of the EU, but there are also exceptions such as Norway and Iceland. They are characterised by relatively small and open economies, which are highly dependent on foreign trade and investment. Their focus is more on sectors such as services, industry, and tourism, rather than agriculture. From a political point of view, these countries enjoy stable political systems and good governance with a high degree of transparency. This allows them to develop competitive advantages in other areas and overall high levels of economic development.

Bulgaria is one of the countries with the highest GVA from agriculture within this cluster (€1.81 billion), along with Norway and Sweden. At the same time, however, the levels of greenhouse gas emissions are also relatively high (4.97 million tonnes). So from the point of view of sustainable development and ecological footprint, Bulgaria does not perform very well compared to other countries.

4.3 Regression analysis

The regression analysis of the 30 studied European countries showed mixed results. The dependent variable is the greenhouse gas emission from agriculture in million tonnes, and the independent variable is the GVA from agriculture also in million tonnes.

Statistically significant linear regression models linking these two variables were obtained for only 9 out of the total 30 studied countries. These are Czechia, Greece, Spain, Cyprus, Luxembourg, Hungary, Poland, Iceland and Switzerland. For these countries, there is a statistically significant linear relationship between the levels of greenhouse gas emissions from agriculture and the GVA generated by it (Table 2).

Table 2

Regression analysis of the relationship between emissions and GVA from agriculture by country: Statistically significant models

Country R R 2 Significance F Coefficients P-value
Czechia 0.8459 0.7155 0.0020 Intercept 5.4872 0.0000
Gross value added from agriculture Million euro 0.0014 0.0020
Creece 0.7366 0.5425 0.0241 Intercept 11.3973 0.0000
Gross value added from agriculture Million euro −0.0006 0.0151
Spain 0.7002 0.4903 0.0241 Intercept 26.1598 0.0000
Gross value added from agriculture Million euro 0.0001 0.0241
Cyprus 0.8661 0.7501 0.0012 Intercept 0.2686 0.0011
Gross value added from agriculture Million euro 0.0008 0.0012
Luxemburg 0.7196 0.5178 0.0190 Intercept 1.0790 0.0000
Gross value added from agriculture Million euro −0.0036 0.0190
Hungary 0.9308 0.8664 0.0001 Intercept 2.4488 0.0015
Gross value added from agriculture Million euro 0.0011 0.0001
Poland 0.7371 0.5433 0.0150 Intercept 19.1634 0.0007
Gross value added from agriculture Million euro 0.0012 0.0150
Iceland 0.7187 0.5166 0.0192 Intercept 2.5745 0.0000
Gross value added from agriculture Million euro −0.0057 0.0192
Switzerland 0.8504 0.7231 0.0018 Intercept 9.9898 0.0000
Gross value added from agriculture Million euro −0.0012 0.0018

Source: Own calculations based on Eurostat data.

For the remaining 21 European countries, however, the regression models were statistically insignificant. This means that for them, there is no evidence of a linear relationship between the two studied variables at the level of significance used. Possible explanations for the lack of relationship in these countries may be differences in the structure and practices of agriculture in individual countries.

Overall, however, the results show that the relationship between the GVA from agriculture and the greenhouse gas emissions it generates is rather weak and country-specific, rather than a universal pattern for European countries.

The regression analysis of the countries from the first cluster showed a statistically significant model for Spain and a statistically insignificant one for Italy. For Spain, a relatively strong positive linear relationship between the two variables is observed, expressed by a multiple correlation coefficient (multiple R) of 0.7. The coefficient of determination (R square) of 0.49 means that the model explains about 49% of the variation in emissions. For Italy, however, this relationship is much weaker – the correlation coefficient is only 0.26 and the R square is 0.07. So the factors explaining the emissions are mainly outside the model for Italy.

The regression analysis of the countries in the second cluster, including France and Germany, shows that there are no statistically significant linear regression models describing the relationship between greenhouse gas emission levels from agriculture and the GVA generated by it in these countries. Despite the significant contribution of the agricultural sector to the economies of France (€27 billion) and Germany (€17 billion), as well as substantial levels of greenhouse gas emissions (76 and 59 million tonnes annually, respectively), there is a lack of statistically significant evidence for the presence of a linear relationship between these two variables. These results suggest that the relationship between agricultural production, measured by its GVA, and greenhouse gas emissions in agriculture in France and Germany is either non-linear or influenced by a number of other factors not analysed in this particular study.

The regression analysis of the countries in the third cluster reveals several important trends. Statistically significant linear regression models linking greenhouse gas emissions from agriculture with the generated GVA are established in only 5 of the 12 countries studied: Greece, Hungary, Poland, the Czech Republic, and Switzerland. A positive linear relationship is observed in Hungary and Poland, meaning that as the GVA from agriculture increases, so do greenhouse gas emissions. This relationship is strongest in Poland (R² = 0.5433), followed by Hungary (R² = 0.8664) and Greece (R² = 0.5425). For the Czech Republic, a positive linear regression is also established with the highest coefficient of determination among the analysed countries (R² = 0.7155), suggesting that the model explains over 71% of the variation. In Switzerland, however, the regression coefficient is negative, meaning that as agricultural production and GVA increase, greenhouse gas emissions decrease. For the remaining seven countries in this cluster – the Netherlands, Denmark, Belgium, Portugal, Austria, Ireland, and Romania, no statistically significant regression dependencies are found between the variables studied.

The regression analysis of the countries in the fourth cluster reveals some important patterns. Out of the 14 countries studied, statistically significant linear regression models describing the relationship between greenhouse gas emissions from agriculture and the generated GVA are established for only three countries: Cyprus, Iceland and Luxembourg. In the case of Cyprus, a positive linear correlation is established between the two variables, with the coefficient of determination (R² = 0.7501), showing that 75% of the variation in greenhouse gas emissions can be explained by the change in GVA from agriculture. Unlike Cyprus, Iceland and Luxembourg show a statistically significant negative linear relationship, meaning that as the GVA from the agricultural sector increases, greenhouse gas emissions decrease. For the remaining 11 countries in this cluster, including Norway, Sweden, Finland, Bulgaria, Croatia, and Malta, the regression analysis does not establish statistically significant relationships between the levels of the two variables studied at a significance level of p ≤ 0.05.

5 Discussion

The results of this study provide valuable information on the interaction between the economic productivity of the agricultural sector and greenhouse gas emissions in various European countries. The analytical methods used – cluster, regression, and trend analysis – reveal a complex picture of economic activity and environmental sustainability, highlighting existing differences between countries.

The analysis of trends in greenhouse gas emissions and GVA from agriculture in European countries for the period 2012–2021 shows that most countries are experiencing growth in GVA. This underscores the continuing economic importance of the agricultural sector, with particularly impressive growth in Ireland, Latvia, the Czech Republic, Portugal, and Romania. This growth can be explained by factors such as increased productivity, technological innovations, and effective agricultural policies.

At the same time, trends in greenhouse gas emissions are more diverse. In several Western European countries, such as Belgium, Denmark, Germany, France, the Netherlands, Austria and Switzerland, emissions are decreasing alongside GVA growth. This demonstrates the possibility of achieving “decoupling” – economic growth without increasing pollution, likely due to more sustainable agricultural practices and strict environmental regulations.

In contrast, in Eastern and Northern European countries such as Bulgaria, Estonia, Latvia, Lithuania, Slovenia, Finland, and Sweden, emissions continue to rise in parallel with economic growth. This highlights the need for targeted policies and investments to promote more sustainable agriculture in these countries.

The cluster analysis reveals additional differences in the economic and environmental efficiency of the agricultural sector in Europe. In the first cluster, including Italy and Spain, despite high productivity and significant economic contribution from agriculture, greenhouse gas emission levels remain substantial. This underscores the dilemma facing large agrarian economies that must balance economic growth and sustainability. In the third cluster, including countries such as the Netherlands, Belgium, and Switzerland, a more successful combination of economic growth with lower emission levels is observed. This suggests that these countries are implementing effective sustainable agriculture policies and can serve as a model for other countries striving for more environmentally conscious development. The fourth cluster, consisting mainly of smaller and less developed agricultural economies, demonstrates relatively low emission levels. However, some of these countries, such as Bulgaria, have yet to reduce their environmental footprint in line with their economic growth, posing challenges to their sustainable development.

Regression analysis shows that the relationship between economic activity and greenhouse gas emissions is specific to each country and depends on regional and structural characteristics of agriculture. The lack of significant correlations in many countries suggests that emission levels are determined by complex factors, including climatic conditions, technologies used, and cultural practices. Moreover, some countries demonstrate significant deviations from general trends, which may be due to specific national policies or structural changes in the agricultural sector. Such countries may be subject to additional research to establish the factors contributing to their unique development patterns.

The observed differences between countries underscore the importance of individualised approaches to sustainable development that take into account the specific conditions and challenges in each country. While some countries have already made progress in decoupling economic growth from the environmental footprint, others are still seeking effective solutions to achieve a balance between economic productivity and environmental sustainability.

The present study emphasises the need for continued efforts to monitor and optimise agricultural practices to reduce greenhouse gas emissions. The question of how to stimulate “green” economic growth in agriculture, so that increasing production and income does not lead to a proportional increase in harmful emissions, remains central. Some key opportunities, in this regard, analysed and discussed in various studies include:

  • Introduction of tax incentives and subsidies to promote organic farming and practices such as crop rotation, composting, and use of biofertilisers [42,43,44,45].

  • State investments in scientific research and technology transfer for sustainable and low-carbon agriculture [46,47].

  • Training farmers in methods for efficient resource use and reduction of waste from agricultural activities [48,49,50].

  • Restructuring the livestock sector towards less emission-intensive subsectors [51,52,53].

  • Strengthening environmental criteria in granting direct subsidies to farmers from the EU’s CAP [54,55].

  • Tax incentives for farmers’ investments in energy-efficient technologies and renewable sources [56,57].

  • Raising public awareness about sustainable foods through eco-labelling and campaigns [58,59].

6 Conclusion

The present study provides an in-depth analysis of the interaction between economic productivity in the agricultural sector and greenhouse gas emissions across European countries. The results show that despite the overall growth in GVA in the agricultural sector, trends in greenhouse gas emissions vary significantly between countries, reflecting the specific regional and structural characteristics of each state.

Cluster analysis reveals significant differences in the efficiency of the agricultural sector in terms of economic growth and environmental sustainability. While some Western European countries, for example, Belgium, Denmark, and Germany, are experiencing successful “decoupling” – economic growth without a corresponding increase in harmful emissions – in Eastern and Northern European countries, such as Bulgaria and Latvia, this balance has not yet been achieved. This underscores the need for targeted policies and investments aimed at promoting sustainable agriculture and minimising the environmental footprint.

Regression analysis shows that the relationship between economic activity and greenhouse gas emissions is not universal and depends on various factors, including climatic conditions, technologies used, and cultural practices. In some countries, such as Spain and Poland, there is a positive correlation between GVA growth and increased emissions, indicating the need for additional efforts to integrate sustainable practices.

The study emphasises the importance of individualised approaches to sustainable development in the agricultural sector. To achieve sustainable development that combines economic growth with reduced environmental harm, a combination of policies and implementation of measures is necessary. These include tax incentives, subsidies for organic farming, investments in scientific research and technology, as well as training farmers in sustainable practices.

  1. Funding information: This research is supported by Agricultural University, Bulgaria, Plovdiv, under project 17-12 Support of the publication activity of the university lecturers in Agricultural university.

  2. Author contribution: The author confirms the sole responsibility for the conception of the study, presented results and manuscript preparation.

  3. Conflict of interest: The author states no conflict of interest.

  4. Data availability statement: All data are available in the Eurostat database, https://ec.europa.eu/eurostat/data/database, accessed on 14 January 2024. Other data sources included in the investigation are cited in the text.

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Received: 2024-01-17
Revised: 2024-09-18
Accepted: 2024-10-02
Published Online: 2024-10-22

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  2. Supplementation of P-solubilizing purple nonsulfur bacteria, Rhodopseudomonas palustris improved soil fertility, P nutrient, growth, and yield of Cucumis melo L.
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  42. An implementation of an extended theory of planned behavior to investigate consumer behavior on hygiene sanitation-certified livestock food products
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  46. Fostering cocoa industry resilience: A collaborative approach to managing farm gate price fluctuations in West Sulawesi, Indonesia
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  48. Near-infrared technology in agriculture: Rapid, simultaneous, and non-destructive determination of inner quality parameters on intact coffee beans
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  50. Weather index-based agricultural insurance for flower farmers: Willingness to pay, sales, and profitability perspectives
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  53. Determination of C-factor for conventional cultivation and soil conservation technique used in hop gardens
  54. Empowering farmers: Unveiling the economic impacts of contract farming on red chilli farmers’ income in Magelang District, Indonesia
  55. Evaluating salt tolerance in fodder crops: A field experiment in the dry land
  56. Labor productivity of lowland rice (Oryza sativa L.) farmers in Central Java Province, Indonesia
  57. Cropping systems and production assessment in southern Myanmar: Informing strategic interventions
  58. The effect of biostimulants and red mud on the growth and yield of shallots in post-unlicensed gold mining soil
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  63. Supply chain efficiency of red chilies in the production center of Sleman Indonesia based on performance measurement system
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  69. Spacing strategies for enhancing drought resilience and yield in maize agriculture
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  71. Investigating Spodoptera spp. diversity, percentage of attack, and control strategies in the West Java, Indonesia, corn cultivation
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  73. Evaluating agricultural yield and economic implications of varied irrigation depths on maize yield in semi-arid environments, at Birfarm, Upper Blue Nile, Ethiopia
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  75. Pomegranate peel ethanolic extract: A promising natural antioxidant, antimicrobial agent, and novel approach to mitigate rancidity in used edible oils
  76. Transformative learning and engagement with organic farming: Lessons learned from Indonesia
  77. Tourism in rural areas as a broader concept: Some insights from the Portuguese reality
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  82. Hibiscus sabdariffa L. petal biomass: A green source of nanoparticles of multifarious potential
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  88. Optimizing inorganic blended fertilizer application for the maximum grain yield and profitability of bread wheat and food barley in Dawuro Zone, Southwest Ethiopia
  89. The acceptance of social media as a channel of communication and livestock information for sheep farmers
  90. Adaptation of rice farmers to aging in Thailand
  91. Combined use of improved maize hybrids and nitrogen application increases grain yield of maize, under natural Striga hermonthica infestation
  92. From aquatic to terrestrial: An examination of plant diversity and ecological shifts
  93. Statistical modelling of a tractor tractive performance during ploughing operation on a tropical Alfisol
  94. Participation in artisanal diamond mining and food security: A case study of Kasai Oriental in DR Congo
  95. Assessment and multi-scenario simulation of ecosystem service values in Southwest China’s mountainous and hilly region
  96. Analysis of agricultural emissions and economic growth in Europe in search of ecological balance
  97. Bacillus thuringiensis strains with high insecticidal activity against insect larvae of the orders Coleoptera and Lepidoptera
  98. Technical efficiency of sugarcane farming in East Java, Indonesia: A bootstrap data envelopment analysis
  99. Comparison between mycobiota diversity and fungi and mycotoxin contamination of maize and wheat
  100. Evaluation of cultivation technology package and corn variety based on agronomy characters and leaf green indices
  101. Exploring the association between the consumption of beverages, fast foods, sweets, fats, and oils and the risk of gastric and pancreatic cancers: Findings from case–control study
  102. Phytochemical composition and insecticidal activity of Acokanthera oblongifolia (Hochst.) Benth & Hook.f. ex B.D.Jacks. extract on life span and biological aspects of Spodoptera littoralis (Biosd.)
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  107. Agronomic and economic benefits of rice–sweetpotato rotation in lowland rice cropping systems in Uganda
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  110. Evaluation of Abrams curve in agricultural sector using the NARDL approach
  111. Challenges and opportunities for young farmers in the implementation of the Rural Development Program 2014–2020 of the Republic of Croatia
  112. Yield stability of ten common bean (Phaseolus vulgaris L.) genotypes at different sowing dates in Lubumbashi, South-East of DR Congo
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  114. Phytochemical analysis of Bienertia sinuspersici extract and its antioxidant and antimicrobial activities
  115. Evaluation of relative drought tolerance of grapevines by leaf fluorescence parameters
  116. Yield assessment of new streak-resistant topcross maize hybrids in Benin
  117. Improvement of cocoa powder properties through ultrasonic- and microwave-assisted alkalization
  118. Potential of ecoenzymes made from nutmeg (Myristica fragrans) leaf and pulp waste as bioinsecticides for Periplaneta americana
  119. Analysis of farm performance to realize the sustainability of organic cabbage vegetable farming in Getasan Semarang, Indonesia
  120. Revealing the influences of organic amendment-derived dissolved organic matter on growth and nutrient accumulation in lettuce seedlings (Lactuca sativa L.)
  121. Identification of viruses infecting sweetpotato (Ipomoea batatas Lam.) in Benin
  122. Assessing the soil physical and chemical properties of long-term pomelo orchard based on tree growth
  123. Investigating access and use of digital tools for agriculture among rural farmers: A case study of Nkomazi Municipality, South Africa
  124. Does sex influence the impact of dietary vitD3 and UVB light on performance parameters and welfare indicators of broilers?
  125. Design of intelligent sprayer control for an autonomous farming drone using a multiclass support vector machine
  126. Deciphering salt-responsive NB-ARC genes in rice transcriptomic data: A bioinformatics approach with gene expression validation
  127. Review Articles
  128. Impact of nematode infestation in livestock production and the role of natural feed additives – A review
  129. Role of dietary fats in reproductive, health, and nutritional benefits in farm animals: A review
  130. Climate change and adaptive strategies on viticulture (Vitis spp.)
  131. The false tiger of almond, Monosteira unicostata (Hemiptera: Tingidae): Biology, ecology, and control methods
  132. A systematic review on potential analogy of phytobiomass and soil carbon evaluation methods: Ethiopia insights
  133. A review of storage temperature and relative humidity effects on shelf life and quality of mango (Mangifera indica L.) fruit and implications for nutrition insecurity in Ethiopia
  134. Green extraction of nutmeg (Myristica fragrans) phytochemicals: Prospective strategies and roadblocks
  135. Potential influence of nitrogen fertilizer rates on yield and yield components of carrot (Dacus carota L.) in Ethiopia: Systematic review
  136. Corn silk: A promising source of antimicrobial compounds for health and wellness
  137. State and contours of research on roselle (Hibiscus sabdariffa L.) in Africa
  138. The potential of phosphorus-solubilizing purple nonsulfur bacteria in agriculture: Present and future perspectives
  139. Minor millets: Processing techniques and their nutritional and health benefits
  140. Meta-analysis of reproductive performance of improved dairy cattle under Ethiopian environmental conditions
  141. Review on enhancing the efficiency of fertilizer utilization: Strategies for optimal nutrient management
  142. The nutritional, phytochemical composition, and utilisation of different parts of maize: A comparative analysis
  143. Motivations for farmers’ participation in agri-environmental scheme in the EU, literature review
  144. Evolution of climate-smart agriculture research: A science mapping exploration and network analysis
  145. Short Communications
  146. Music enrichment improves the behavior and leukocyte profile of dairy cattle
  147. Effect of pruning height and organic fertilization on the morphological and productive characteristics of Moringa oleifera Lam. in the Peruvian dry tropics
  148. Corrigendum
  149. Corrigendum to “Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance”
  150. Corrigendum to “Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types”
  151. Special issue: Smart Agriculture System for Sustainable Development: Methods and Practices
  152. Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy
  153. FruitVision: A deep learning based automatic fruit grading system
  154. Energy harvesting and ANFIS modeling of a PVDF/GO-ZNO piezoelectric nanogenerator on a UAV
  155. Effects of stress hormones on digestibility and performance in cattle: A review
  156. Special Issue of The 4th International Conference on Food Science and Engineering (ICFSE) 2022 - Part II
  157. Assessment of omega-3 and omega-6 fatty acid profiles and ratio of omega-6/omega-3 of white eggs produced by laying hens fed diets enriched with omega-3 rich vegetable oil
  158. Special Issue on FCEM - International Web Conference on Food Choice & Eating Motivation - Part II
  159. Special Issue on FCEM – International Web Conference on Food Choice & Eating Motivation: Message from the editor
  160. Fruit and vegetable consumption: Study involving Portuguese and French consumers
  161. Knowledge about consumption of milk: Study involving consumers from two European Countries – France and Portugal
https://doi.org/10.1515/opag-2022-0373
Keywords for this article
greenhouse gases; agriculture; economic growth; Europe
Creative Commons
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Articles in the same Issue

  1. Regular Articles
  2. Supplementation of P-solubilizing purple nonsulfur bacteria, Rhodopseudomonas palustris improved soil fertility, P nutrient, growth, and yield of Cucumis melo L.
  3. Yield gap variation in rice cultivation in Indonesia
  4. Effects of co-inoculation of indole-3-acetic acid- and ammonia-producing bacteria on plant growth and nutrition, soil elements, and the relationships of soil microbiomes with soil physicochemical parameters
  5. Impact of mulching and planting time on spring-wheat (Triticum aestivum) growth: A combined field experiment and empirical modeling approach
  6. Morphological diversity, correlation studies, and multiple-traits selection for yield and yield components of local cowpea varieties
  7. Participatory on-farm evaluation of new orange-fleshed sweetpotato varieties in Southern Ethiopia
  8. Yield performance and stability analysis of three cultivars of Gayo Arabica coffee across six different environments
  9. Biology of Spodoptera frugiperda (Lepidoptera: Noctuidae) on different types of plants feeds: Potency as a pest on various agricultural plants
  10. Antidiabetic activity of methanolic extract of Hibiscus sabdariffa Linn. fruit in alloxan-induced Swiss albino diabetic mice
  11. Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance
  12. Nicotinamide as a biostimulant improves soybean growth and yield
  13. Farmer’s willingness to accept the sustainable zoning-based organic farming development plan: A lesson from Sleman District, Indonesia
  14. Uncovering hidden determinants of millennial farmers’ intentions in running conservation agriculture: An application of the Norm Activation Model
  15. Mediating role of leadership and group capital between human capital component and sustainability of horticultural agribusiness institutions in Indonesia
  16. Biochar technology to increase cassava crop productivity: A study of sustainable agriculture on degraded land
  17. Effect of struvite on the growth of green beans on Mars and Moon regolith simulants
  18. UrbanAgriKG: A knowledge graph on urban agriculture and its embeddings
  19. Provision of loans and credit by cocoa buyers under non-price competition: Cocoa beans market in Ghana
  20. Effectiveness of micro-dosing of lime on selected chemical properties of soil in Banja District, North West, Ethiopia
  21. Effect of weather, nitrogen fertilizer, and biostimulators on the root size and yield components of Hordeum vulgare
  22. Effects of selected biostimulants on qualitative and quantitative parameters of nine cultivars of the genus Capsicum spp.
  23. Growth, yield, and secondary metabolite responses of three shallot cultivars at different watering intervals
  24. Design of drainage channel for effective use of land on fully mechanized sugarcane plantations: A case study at Bone Sugarcane Plantation
  25. Technical feasibility and economic benefit of combined shallot seedlings techniques in Indonesia
  26. Control of Meloidogyne javanica in banana by endophytic bacteria
  27. Comparison of important quality components of red-flesh kiwifruit (Actinidia chinensis) in different locations
  28. Efficiency of rice farming in flood-prone areas of East Java, Indonesia
  29. Comparative analysis of alpine agritourism in Trentino, Tyrol, and South Tyrol: Regional variations and prospects
  30. Detection of Fusarium spp. infection in potato (Solanum tuberosum L.) during postharvest storage through visible–near-infrared and shortwave–near-infrared reflectance spectroscopy
  31. Forage yield, seed, and forage qualitative traits evaluation by determining the optimal forage harvesting stage in dual-purpose cultivation in safflower varieties (Carthamus tinctorius L.)
  32. The influence of tourism on the development of urban space: Comparison in Hanoi, Danang, and Ho Chi Minh City
  33. Optimum intra-row spacing and clove size for the economical production of garlic (Allium sativum L.) in Northwestern Highlands of Ethiopia
  34. The role of organic rice farm income on farmer household welfare: Evidence from Yogyakarta, Indonesia
  35. Exploring innovative food in a developing country: Edible insects as a sustainable option
  36. Genotype by environment interaction and performance stability of common bean (Phaseolus vulgaris L.) cultivars grown in Dawuro zone, Southwestern Ethiopia
  37. Factors influencing green, environmentally-friendly consumer behaviour
  38. Factors affecting coffee farmers’ access to financial institutions: The case of Bandung Regency, Indonesia
  39. Morphological and yield trait-based evaluation and selection of chili (Capsicum annuum L.) genotypes suitable for both summer and winter seasons
  40. Sustainability analysis and decision-making strategy for swamp buffalo (Bubalus bubalis carabauesis) conservation in Jambi Province, Indonesia
  41. Understanding factors affecting rice purchasing decisions in Indonesia: Does rice brand matter?
  42. An implementation of an extended theory of planned behavior to investigate consumer behavior on hygiene sanitation-certified livestock food products
  43. Information technology adoption in Indonesia’s small-scale dairy farms
  44. Draft genome of a biological control agent against Bipolaris sorokiniana, the causal phytopathogen of spot blotch in wheat (Triticum turgidum L. subsp. durum): Bacillus inaquosorum TSO22
  45. Assessment of the recurrent mutagenesis efficacy of sesame crosses followed by isolation and evaluation of promising genetic resources for use in future breeding programs
  46. Fostering cocoa industry resilience: A collaborative approach to managing farm gate price fluctuations in West Sulawesi, Indonesia
  47. Field investigation of component failures for selected farm machinery used in small rice farming operations
  48. Near-infrared technology in agriculture: Rapid, simultaneous, and non-destructive determination of inner quality parameters on intact coffee beans
  49. The synergistic application of sucrose and various LED light exposures to enhance the in vitro growth of Stevia rebaudiana (Bertoni)
  50. Weather index-based agricultural insurance for flower farmers: Willingness to pay, sales, and profitability perspectives
  51. Meta-analysis of dietary Bacillus spp. on serum biochemical and antioxidant status and egg quality of laying hens
  52. Biochemical characterization of trypsin from Indonesian skipjack tuna (Katsuwonus pelamis) viscera
  53. Determination of C-factor for conventional cultivation and soil conservation technique used in hop gardens
  54. Empowering farmers: Unveiling the economic impacts of contract farming on red chilli farmers’ income in Magelang District, Indonesia
  55. Evaluating salt tolerance in fodder crops: A field experiment in the dry land
  56. Labor productivity of lowland rice (Oryza sativa L.) farmers in Central Java Province, Indonesia
  57. Cropping systems and production assessment in southern Myanmar: Informing strategic interventions
  58. The effect of biostimulants and red mud on the growth and yield of shallots in post-unlicensed gold mining soil
  59. Effects of dietary Adansonia digitata L. (baobab) seed meal on growth performance and carcass characteristics of broiler chickens: A systematic review and meta-analysis
  60. Analysis and structural characterization of the vid-pisco market
  61. Pseudomonas fluorescens SP007s enhances defense responses against the soybean bacterial pustule caused by Xanthomonas axonopodis pv. glycines
  62. A brief investigation on the prospective of co-composted biochar as a fertilizer for Zucchini plants cultivated in arid sandy soil
  63. Supply chain efficiency of red chilies in the production center of Sleman Indonesia based on performance measurement system
  64. Investment development path for developed economies: Is agriculture different?
  65. Power relations among actors in laying hen business in Indonesia: A MACTOR analysis
  66. High-throughput digital imaging and detection of morpho-physiological traits in tomato plants under drought
  67. Converting compression ignition engine to dual-fuel (diesel + CNG) engine and experimentally investigating its performance and emissions
  68. Structuration, risk management, and institutional dynamics in resolving palm oil conflicts
  69. Spacing strategies for enhancing drought resilience and yield in maize agriculture
  70. Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types
  71. Investigating Spodoptera spp. diversity, percentage of attack, and control strategies in the West Java, Indonesia, corn cultivation
  72. Yield stability of biofertilizer treatments to soybean in the rainy season based on the GGE biplot
  73. Evaluating agricultural yield and economic implications of varied irrigation depths on maize yield in semi-arid environments, at Birfarm, Upper Blue Nile, Ethiopia
  74. Chemometrics for mapping the spatial nitrate distribution on the leaf lamina of fenugreek grown under varying nitrogenous fertilizer doses
  75. Pomegranate peel ethanolic extract: A promising natural antioxidant, antimicrobial agent, and novel approach to mitigate rancidity in used edible oils
  76. Transformative learning and engagement with organic farming: Lessons learned from Indonesia
  77. Tourism in rural areas as a broader concept: Some insights from the Portuguese reality
  78. Assessment enhancing drought tolerance in henna (Lawsonia inermis L.) ecotypes through sodium nitroprusside foliar application
  79. Edible insects: A survey about perceptions regarding possible beneficial health effects and safety concerns among adult citizens from Portugal and Romania
  80. Phenological stages analysis in peach trees using electronic nose
  81. Harvest date and salicylic acid impact on peanut (Arachis hypogaea L.) properties under different humidity conditions
  82. Hibiscus sabdariffa L. petal biomass: A green source of nanoparticles of multifarious potential
  83. Use of different vegetation indices for the evaluation of the kinetics of the cherry tomato (Solanum lycopersicum var. cerasiforme) growth based on multispectral images by UAV
  84. First evidence of microplastic pollution in mangrove sediments and its ingestion by coral reef fish: Case study in Biawak Island, Indonesia
  85. Physical and textural properties and sensory acceptability of wheat bread partially incorporated with unripe non-commercial banana cultivars
  86. Cereibacter sphaeroides ST16 and ST26 were used to solubilize insoluble P forms to improve P uptake, growth, and yield of rice in acidic and extreme saline soil
  87. Avocado peel by-product in cattle diets and supplementation with oregano oil and effects on production, carcass, and meat quality
  88. Optimizing inorganic blended fertilizer application for the maximum grain yield and profitability of bread wheat and food barley in Dawuro Zone, Southwest Ethiopia
  89. The acceptance of social media as a channel of communication and livestock information for sheep farmers
  90. Adaptation of rice farmers to aging in Thailand
  91. Combined use of improved maize hybrids and nitrogen application increases grain yield of maize, under natural Striga hermonthica infestation
  92. From aquatic to terrestrial: An examination of plant diversity and ecological shifts
  93. Statistical modelling of a tractor tractive performance during ploughing operation on a tropical Alfisol
  94. Participation in artisanal diamond mining and food security: A case study of Kasai Oriental in DR Congo
  95. Assessment and multi-scenario simulation of ecosystem service values in Southwest China’s mountainous and hilly region
  96. Analysis of agricultural emissions and economic growth in Europe in search of ecological balance
  97. Bacillus thuringiensis strains with high insecticidal activity against insect larvae of the orders Coleoptera and Lepidoptera
  98. Technical efficiency of sugarcane farming in East Java, Indonesia: A bootstrap data envelopment analysis
  99. Comparison between mycobiota diversity and fungi and mycotoxin contamination of maize and wheat
  100. Evaluation of cultivation technology package and corn variety based on agronomy characters and leaf green indices
  101. Exploring the association between the consumption of beverages, fast foods, sweets, fats, and oils and the risk of gastric and pancreatic cancers: Findings from case–control study
  102. Phytochemical composition and insecticidal activity of Acokanthera oblongifolia (Hochst.) Benth & Hook.f. ex B.D.Jacks. extract on life span and biological aspects of Spodoptera littoralis (Biosd.)
  103. Land use management solutions in response to climate change: Case study in the central coastal areas of Vietnam
  104. Evaluation of coffee pulp as a feed ingredient for ruminants: A meta-analysis
  105. Interannual variations of normalized difference vegetation index and potential evapotranspiration and their relationship in the Baghdad area
  106. Harnessing synthetic microbial communities with nitrogen-fixing activity to promote rice growth
  107. Agronomic and economic benefits of rice–sweetpotato rotation in lowland rice cropping systems in Uganda
  108. Response of potato tuber as an effect of the N-fertilizer and paclobutrazol application in medium altitude
  109. Bridging the gap: The role of geographic proximity in enhancing seed sustainability in Bandung District
  110. Evaluation of Abrams curve in agricultural sector using the NARDL approach
  111. Challenges and opportunities for young farmers in the implementation of the Rural Development Program 2014–2020 of the Republic of Croatia
  112. Yield stability of ten common bean (Phaseolus vulgaris L.) genotypes at different sowing dates in Lubumbashi, South-East of DR Congo
  113. Effects of encapsulation and combining probiotics with different nitrate forms on methane emission and in vitro rumen fermentation characteristics
  114. Phytochemical analysis of Bienertia sinuspersici extract and its antioxidant and antimicrobial activities
  115. Evaluation of relative drought tolerance of grapevines by leaf fluorescence parameters
  116. Yield assessment of new streak-resistant topcross maize hybrids in Benin
  117. Improvement of cocoa powder properties through ultrasonic- and microwave-assisted alkalization
  118. Potential of ecoenzymes made from nutmeg (Myristica fragrans) leaf and pulp waste as bioinsecticides for Periplaneta americana
  119. Analysis of farm performance to realize the sustainability of organic cabbage vegetable farming in Getasan Semarang, Indonesia
  120. Revealing the influences of organic amendment-derived dissolved organic matter on growth and nutrient accumulation in lettuce seedlings (Lactuca sativa L.)
  121. Identification of viruses infecting sweetpotato (Ipomoea batatas Lam.) in Benin
  122. Assessing the soil physical and chemical properties of long-term pomelo orchard based on tree growth
  123. Investigating access and use of digital tools for agriculture among rural farmers: A case study of Nkomazi Municipality, South Africa
  124. Does sex influence the impact of dietary vitD3 and UVB light on performance parameters and welfare indicators of broilers?
  125. Design of intelligent sprayer control for an autonomous farming drone using a multiclass support vector machine
  126. Deciphering salt-responsive NB-ARC genes in rice transcriptomic data: A bioinformatics approach with gene expression validation
  127. Review Articles
  128. Impact of nematode infestation in livestock production and the role of natural feed additives – A review
  129. Role of dietary fats in reproductive, health, and nutritional benefits in farm animals: A review
  130. Climate change and adaptive strategies on viticulture (Vitis spp.)
  131. The false tiger of almond, Monosteira unicostata (Hemiptera: Tingidae): Biology, ecology, and control methods
  132. A systematic review on potential analogy of phytobiomass and soil carbon evaluation methods: Ethiopia insights
  133. A review of storage temperature and relative humidity effects on shelf life and quality of mango (Mangifera indica L.) fruit and implications for nutrition insecurity in Ethiopia
  134. Green extraction of nutmeg (Myristica fragrans) phytochemicals: Prospective strategies and roadblocks
  135. Potential influence of nitrogen fertilizer rates on yield and yield components of carrot (Dacus carota L.) in Ethiopia: Systematic review
  136. Corn silk: A promising source of antimicrobial compounds for health and wellness
  137. State and contours of research on roselle (Hibiscus sabdariffa L.) in Africa
  138. The potential of phosphorus-solubilizing purple nonsulfur bacteria in agriculture: Present and future perspectives
  139. Minor millets: Processing techniques and their nutritional and health benefits
  140. Meta-analysis of reproductive performance of improved dairy cattle under Ethiopian environmental conditions
  141. Review on enhancing the efficiency of fertilizer utilization: Strategies for optimal nutrient management
  142. The nutritional, phytochemical composition, and utilisation of different parts of maize: A comparative analysis
  143. Motivations for farmers’ participation in agri-environmental scheme in the EU, literature review
  144. Evolution of climate-smart agriculture research: A science mapping exploration and network analysis
  145. Short Communications
  146. Music enrichment improves the behavior and leukocyte profile of dairy cattle
  147. Effect of pruning height and organic fertilization on the morphological and productive characteristics of Moringa oleifera Lam. in the Peruvian dry tropics
  148. Corrigendum
  149. Corrigendum to “Bioinformatics investigation of the effect of volatile and non-volatile compounds of rhizobacteria in inhibiting late embryogenesis abundant protein that induces drought tolerance”
  150. Corrigendum to “Composition and quality of winter annual agrestal and ruderal herbages of two different land-use types”
  151. Special issue: Smart Agriculture System for Sustainable Development: Methods and Practices
  152. Construction of a sustainable model to predict the moisture content of porang powder (Amorphophallus oncophyllus) based on pointed-scan visible near-infrared spectroscopy
  153. FruitVision: A deep learning based automatic fruit grading system
  154. Energy harvesting and ANFIS modeling of a PVDF/GO-ZNO piezoelectric nanogenerator on a UAV
  155. Effects of stress hormones on digestibility and performance in cattle: A review
  156. Special Issue of The 4th International Conference on Food Science and Engineering (ICFSE) 2022 - Part II
  157. Assessment of omega-3 and omega-6 fatty acid profiles and ratio of omega-6/omega-3 of white eggs produced by laying hens fed diets enriched with omega-3 rich vegetable oil
  158. Special Issue on FCEM - International Web Conference on Food Choice & Eating Motivation - Part II
  159. Special Issue on FCEM – International Web Conference on Food Choice & Eating Motivation: Message from the editor
  160. Fruit and vegetable consumption: Study involving Portuguese and French consumers
  161. Knowledge about consumption of milk: Study involving consumers from two European Countries – France and Portugal
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