Search Results (55)

Despite geographical proximity and broadly similar agro -climatic conditions, China and Vietnam show sharply divergent coffee export performance, with Vietnam ranking as the world’s second largest exporter, while China’s exports remain modest. This study compares the determinants of their bilateral coffee exports over 2001 to 2022, using a gravity model estimated by Poisson pseudo maximum likelihood with partner and year fixed effects, a specification that retains zero trade flows and absorbs global price and demand shocks. Once these common shocks and fixed bilateral factors are controlled, trading-partner demand characteristics such as GDP, population, and urbanization are not robust determinants of exports for either country. The most consistent determinant is domestic production, which is positively associated with exports for both nations and helps explain their divergent export scale. Domestic consumption cannot be separated cleanly from production, so it is not interpreted as crowding out exports. On the policy dimension, Vietnam’s WTO accession shows a positive association with exports while China’s Belt and Road participation shows none, but these are institutionally different forms of integration and are read as associations, rather than causal effects. The findings carry implications for sustainable development, linking producer competitiveness to livelihoods under Goal 1, growth and decent work under Goal 8, and the balance between domestic and export use of production under Goal 12. Full article

Indonesian coffee MSMEs face increasing pressure to meet certification standards and adopt digital technologies to remain competitive in export markets. Despite strong agro-ecological advantages and rising global demand, upgrading efforts remain fragmented and lack clear prioritization. This study develops and empirically evaluates a decision-focused upgrading framework by integrating Porter’s Diamond, Global Value Chain (GVC) upgrading, and Analytic Hierarchy Process (AHP). Using Dampit coffee MSMEs as a case study, the results identify competitiveness gaps linked to functional upgrading needs. AHP prioritization highlights Operational Excellence as the most critical strategy, emphasizing process improvement and reliability. The framework offers practical guidance for MSMEs and policymakers to support structured and sustainable upgrading toward global market integration. Full article

Coffee export price volatility is a relevant problem for producing countries because it affects commercial planning, contract negotiation, producers’ income stability, and the financial sustainability of the agro-export value chain. In economies that are highly dependent on primary commodities, abrupt fluctuations in international prices increase uncertainty and reduce the ability of economic agents to anticipate market behavior. In this context, the objective of this study was to forecast the behavior of the Peruvian coffee export price during 2025 by comparing econometric and time-series models. The research adopted a quantitative approach with a non-experimental, retrospective, and longitudinal design, using a monthly series for the 2010–2024 period. Seven specifications were estimated: linear model, quadratic model, Holt–Winters exponential smoothing, causal model, lagged model, ARIMA, and GARCH. The results showed that the GARCH (1,1) model achieved the best statistical performance, with the lowest Akaike Information Criterion, a Durbin–Watson statistic close to 2, an R² higher than that of the alternative models, and no residual autocorrelation. Likewise, the significance of the ARCH and GARCH components confirmed the existence of volatility clustering in the series. The projections for 2025 show a fluctuating trajectory, although with a tendency to stabilize around values close to 10 from March onward. It is concluded that the GARCH (1,1) model is the most appropriate specification for forecasting the Peruvian coffee export price, as it provides a useful tool for export planning, risk management, and decision-making in a context of high uncertainty in the coffee market. Full article

Despite Morocco’s emergence as the world’s fourth-largest berry exporter, no comprehensive review has evaluated the polyphenol composition, antioxidant properties, and health benefits of raspberries (Rubus idaeus), blackberries (Rubus fruticosus), and blueberries (Vaccinium corymbosum) specifically within the Moroccan cultivation context. This narrative review synthesized evidence from phytochemical analyses, in vitro and in vivo studies, randomized controlled trials (RCTs), meta-analyses, and epidemiological data sourced from PubMed, Scopus, and Web of Science. Blackberries exhibited the highest total polyphenol content (149 μmol GAE/L) and antioxidant capacity, driven primarily by anthocyanin concentration and diversity. Antioxidant mechanisms included free radical scavenging, transition metal chelation, and upregulation of endogenous antioxidant enzymes. Pooled RCT data demonstrated that regular consumption (150–300 g/day) significantly reduced systolic blood pressure (−2.72 mmHg), LDL cholesterol (−0.21 mmol/L), and fasting glucose (−2.70 mg/dL). Additional benefits included neuroprotection via blood-brain barrier crossing and brain-derived neurotrophic factor (BDNF) elevation, prebiotic modulation of Bifidobacterium, Lactobacillus, and Akkermansia populations, and anti-cancer activity via nuclear factor-kappa B (NF-κB) and mitogen-activated protein kinase (MAPK) inhibition. Processing significantly affected bioactive retention: freezing preserved phenolic compounds effectively, while conventional drying reduced anthocyanin content by up to 49%. These findings support the integration of Moroccan-cultivated berries—particularly from the Gharb, Loukkos, and Souss-Massa regions—into evidence-based dietary and functional food strategies. Priority research gaps include bioavailability assessment, dose-response characterization, and cultivar-specific phytochemical profiling under Moroccan agro-climatic conditions. Full article

The increasing concern over heavy metal contamination in export crops has intensified research on the application of computer vision systems (CVS) and advanced sensing technologies within multi-level agricultural monitoring frameworks spanning soil contamination assessment, crop spectral diagnostics, and in situ elemental sensing. This study conducts a systematic literature review following Kitchenham’s methodology, from which 68 studies were finally included after screening and eligibility assessment. The review focuses on the use of hyperspectral imaging (HSI) and XRF-IoT sensors (X-ray fluorescence units enhanced with IoT connectivity) for detecting heavy metals in export crops, considering publications from the last seven years indexed in Web of Science Core Collection, Scopus, IEEE Xplore, EBSCOhost, and Springer Nature Link. The findings indicate that research is concentrated in highly digitalized countries, which limits its global applicability; moreover, a substantial proportion of studies is published in Q1 journals, although the methodologies are not always fully objective. Likewise, the most developed research lines are oriented toward image-based diagnostics and crop analysis. These results reveal a gap between technological advances in computer vision and their integration into agricultural decision-making aimed at improving the quality of export crops. It is recommended to foster research with greater geographical diversity, grounded in solid theoretical frameworks and an ethical perspective. Full article

The present study examined the impact of agricultural exports on economic growth in Lambayeque, Peru, during the period 2010–2023. An ordinary least squares (OLS) econometric model was employed to analyze the relationship between gross value added (GVA) and key macroeconomic variables, including agricultural exports, private investment, real wages, terms of trade, and the real multilateral exchange rate. The findings indicate that the model possesses considerable explanatory power (R² = 0.973) and that agricultural exports exert a positive and significant influence on regional GVA. In addition, private investment and real wages demonstrate positive elasticities, while terms of trade exhibit a negative relationship with regional economic growth. This highlights Lambayeque’s vulnerability to external price shocks. The study thus underscores the pivotal role of the Olmos Project, which has been instrumental in transforming arid land into fruitful agricultural zones through the implementation of an irrigation system encompassing over 22,000 hectares. This initiative has not only augmented agricultural exports, accounting for an impressive 90% of Lambayeque’s supply, but also contributed significantly to regional economic development by supporting employment generation and poverty reduction. Nevertheless, the presence of negative terms of trade indicates that the regional economy exhibits structural vulnerability in the face of external shocks. Notwithstanding the intrinsic limitations of regional, trade, and macroeconomic statistics, an understanding of the correlation between agro-exports and economic growth in a paradigmatic region of northern Peru provides substantial evidence for formulating policies to enhance the competitiveness and sustainability of the agro-export model. Full article

The early detection of internal damage caused by Elasmopalpus lignosellus in fresh asparagus constitutes a challenge for the agro-export industry due to the limited sensitivity of traditional visual inspection. This study evaluated the potential of VIS–NIR hyperspectral imaging (390–1036 nm) combined with machine-learning models to discriminate between infested (PB) and sound (SB) asparagus spears. A balanced dataset of 900 samples was acquired, and preprocessing was performed using Savitzky–Golay and SNV. Four classifiers (SVM, MLP, Elastic Net, and XGBoost) were compared. The optimized SVM model achieved the best results (CV Accuracy = 0.9889; AUC = 0.9997). The spectrum was reduced to 60 bands while LOBO and RFE were used to maintain high performance. In external validation (n = 3000), the model achieved an accuracy of 97.9% and an AUC of 0.9976. The results demonstrate the viability of implementing non-destructive systems based on VIS–NIR to improve the quality control of asparagus destined for export. Full article

High-quality agricultural products from the Lambayeque region have contributed to the growth of Peru’s agro-export sector and increased international trade. However, the need for agricultural exports to be more resilient and sustainable is demonstrated by the fact that markets are still concentrated, logistical costs are high, and global demand is constantly shifting. The purpose of this study is to use a gravity-based trade model and market intelligence techniques to analyse the agricultural exports from the Lambayeque region between 2015 and 2024. Using official data from the World Bank, AZATRADE, CEPII, and MINCETUR, we employed a quantitative explanatory approach. The results show that the concentration of businesses has significantly decreased while the value of exports has increased steadily. The Herfindahl–Hirschman Index increased from 6209 in 2015 to 1349 in 2024, and export destinations have become slightly more diverse. Exports are negatively impacted by geographic distance, but free trade agreements greatly benefit them. There is a lot of export potential in markets like Finland, Indonesia, Austria, Bolivia, and Vietnam. However, Israel and Hong Kong appear to be full. Overall, the findings indicate that Lambayeque’s export performance has improved, but it still runs the risk of becoming overly focused on a single sector. Long-term sustainability of the region’s agricultural exports depends on enhancing logistical infrastructure, bolstering market intelligence, and promoting regional diversity. Full article

This study analyzes the determinants of organizational performance and efficiency in Ecuadorian banana-exporting firms, considering human capital management as a strategic axis of competitiveness. Based on a cross-sectional quantitative design, a structured questionnaire was administered to 513 employees from companies registered in the El Oro Chamber of Commerce. The survey evaluated indicators of human capital, organizational climate, leadership, and competencies. To reduce dimensionality and uncover latent patterns, a Principal Component Analysis (PCA) was performed, followed by unsupervised clustering algorithms (K-means and Ward’s method). The results identified three principal components: (i) specific human capital and job support, (ii) general human capital and inter-area coordination, and (iii) applied competencies and current performance, jointly explaining more than 54% of the total variance. The segmentation revealed two major efficiency profiles: one of high specific deployment, characterized by greater training, tenure, and managerial support; and another of low deployment, dependent on individual effort. The evidence confirms that organizational efficiency is grounded in the articulation between idiosyncratic learning, managerial accompaniment, and structured processes. The study extends the application of the Resource-Based View (VRIO framework) to the agro-export context and proposes a replicable multivariate analytics model for diagnosing and strengthening human capital management in labor-intensive sectors. Full article

This article presents the results of a comprehensive study aimed at developing automated diagnostic methods for identifying spring wheat phytopathologies using hyperspectral imaging (HSI). The research aimed to create an effective plant disease detection system, including at the early stages, which is critically important for ensuring food security in regions where wheat plays a key role in the agro-industrial sector. The study analyses the spectral characteristics of major wheat diseases, including powdery mildew, fusarium head blight, septoria glume blotch, root rots, various types of leaf spots, brown rust, and loose smut. Healthy plants differ from diseased ones in that they show a mostly uniform tone without distinct spots or patches on hyperspectral images, and their spectra have a consistent shape without sharp fluctuations. In contrast, disease spectra, differ sharply from those of healthy areas and can take diverse forms. Wheat diseases with a light coating (powdery mildew, fusarium head blight) exhibit high reflectance; chlorosis in the early stages of diseases (rust, leaf spot, septoria leaf blotch) exhibits curves with medium reflectance, and diseases with dark colouration (loose smut, root rot) have low reflectance values. These differences in reflectance among fungal diseases are caused by pigments produced by the pathogens, which either strongly absorb light or reflect most of it. The presence or absence of pigment production is determined by adaptive mechanisms. Based on these patterns in the spectral characteristics and optical properties of the diseases, a classification model was developed with 94% overall accuracy. Random Forest proved to be the most effective method for the automated detection of wheat phytopathogens using hyperspectral data. The practical significance of this research lies in the potential integration of the developed phytopathology detection approach into precision agriculture systems and the use of UAV platforms, enabling rapid large-scale crop monitoring for the timely detection. The study’s results confirm the promising potential of combining hyperspectral technologies and machine learning methods for monitoring the phytosanitary condition of crops. Our findings contribute to the advancement of digital agriculture and are particularly valuable for the agro-industrial sector of Central Asia, where adopting precision farming technologies is a strategic priority given the climatic risks and export-oriented nature of grain production. Full article

At the European level, potato cultivation is highly polarized. In Western Europe (Germany, France, the Netherlands, Belgium, Denmark), yields are high, agricultural technology is advanced, and production systems ensure stability and competitiveness. In contrast, in Eastern and Southern Europe (including Romania, Poland, Italy, and Spain), yields are considerably lower due to the use of outdated agricultural practices, a low degree of mechanization, and increased exposure to adverse climatic factors. In Romania, potato cultivation is marked by significant territorial disparities and structural imbalances, influenced by land fragmentation, agro-pedoclimatic variability, and the lack of capital necessary for investments in modern technologies and irrigation systems. This study analyzes these regional disparities in relation to the country’s real agricultural potential and quantifies the economic impact of its failure to realize it. The methodology applied is based on descriptive statistical analysis of data at the county and regional level for the period 2003–2024, including minimum, maximum, average, and standard deviations of yields. These were integrated into a production function that correlates cultivated areas with average prices, highlighting major intra-regional differences and significant economic consequences at the national level. The results indicate a double crisis: a drastic reduction in the areas cultivated with potatoes (from 196,000 ha in 2017 to 76,000 ha in 2024) and consistently low yields (12,000–18,000 kg/ha), which led to the collapse of total production (from 3.1 million tons in 2017 to under 1 million tons in 2024). As a result, Romania registers a productivity three to four times lower than the reference Western European countries. Moreover, Romania has moved from being a net exporter to a net importer of potatoes, with the food self-sufficiency indicator decreasing from 100.3% in 2017 to 48.1% in 2023. Although domestic production could theoretically cover consumption needs, structural problems regarding yields, the sharp reduction in cultivated areas, and distribution deficiencies have seriously affected the balance of the domestic market. While per capita consumption has remained relatively constant, the decline in production has led, after 2021, to an increasing dependence on imports. These trends highlight the need for urgent structural reforms, technological modernization, and targeted agricultural policies to increase productivity and restore food security in the Romanian potato crop system. Full article

Africa has always been among the top geopolitical priorities for the EU due to the continent’s close geographical proximity and long-standing economic ties. The agro-food trade between the EU27 and Africa is extremely important for both subjects and not only in terms of food security, as it is also a useful tool to secure a long-term partnership between the two continents, making them true and reliable allies ready to give support to each other, especially in the current unstable global situation. The analyzed data were taken from the official publications of the Eurostat (ESTAT). The time frame under analysis is 23 time periods—from 2002 to 2024 inclusive. Such methods and tools of scientific research as textual and tabular methods, empirical, statistical and comparative analyses, as well as the logical method, comprising deductive and inductive reasoning, time series analysis, modelling and forecasting, methods of time series data decomposition, etc. were used while conducting the research presented in the given article. The results for the time series analysis, modelling and forecasting assume the projections for the next four time periods for the EU27 to Africa agro-exports to be around their last observed value, slightly fluctuating or increasing with a delicateslope. The EU27 from Africa agro imports for the next four time periods are projected to increase, with a rather sharp slope. The research and its results can be of great help for public administrators, decision makers, academic community representatives, statisticians, and data analysts. Full article

Digitalisation in logistics has evolved in the search for continuous improvement and optimised processes. This study aims to determine the effectiveness of digitalisation implemented by companies to improve the automated logistics of cross-border trade in the agricultural sector. The research methodology was generated through a bibliometric analysis, exploring the evolution of the state of the art through the Scopus, WOS and Dimensions databases, in order to select relevant empirical studies on digitalisation and automated logistics, using quality criteria and applying the PRISMA flow chart. The results highlighted that since 2017, there have been signs of increased interest from researchers, with authors such as Zoubek, Kumar and Ghobakhloo standing out. This review revealed how digitalisation contributes to the optimisation of costs and time in the logistics chain. Designing public policies allows for a better integration of technologies such as IoT and AI. Three important blocks were identified that have contributed to the effectiveness of digitalisation in automated logistics: the impact of digitalisation on logistics efficiency and the supply chain, technological integration and automation in cross-border logistics, and governance, policies and social considerations in logistics digitalisation. The conclusions reached were that digitalisation has been a fundamental element in improving logistics and making it autonomous within cross-border trade, allowing technology to become integrated and reducing obstacles in the supply chain through digital technologies such as artificial intelligence (AI). Full article

This study investigates sustainable competitiveness in the wine industry using Romania and Portugal as comparative case studies within the conceptual frameworks of Industry 5.0 and the Triple Bottom Line (TBL). While sustainability, robotics, and performance indicators are explored directionally, the core empirical contribution focuses on evaluating key wine industry metrics and their impact on export value. Using data from the International Organisation of Vine and Wine (OIV) and the World Trade Map, we perform a one-way ANOVA to examine differences between the two countries across five variables: vineyard area, wine production volume, grape production, consumption, and export value. The results reveal statistically significant differences in all indicators except vineyard area, with Portugal significantly outperforming Romania in production, consumption, and exports (p < 0.001). To assess the drivers of export performance, we construct a Structural Equation Model (SEM) using SmartPLS. The model confirms that wine production volume and domestic consumption are the strongest positive predictors of export value (loading factors 1.003 and 0.909, respectively), while vineyard area has minimal influence. The model exhibits strong fit indices (e.g., SRMR = 0.009; NFI = 0.971), supporting the robustness of the results. The findings suggest that internal market strength and production efficiency, rather than land size, are critical for export competitiveness. Romania can enhance its performance by aligning production strategies with TBL principles and selectively adopting Industry 5.0 technologies in viticulture. Full article

This article analyses the impacts of the Russia–Ukraine conflict and the COVID-19 pandemic on the supply chain and logistics related to the management of agro-food production based on a comprehensive review of the scientific literature. The challenges and lessons posed by market dependence in a scenario of globalization through monopolies and oligopolies in the production and export of agro-food are assessed, highlighting the vulnerability and uncertainty faced when an international conflict occurs. The review examines the format of globalization versus glocalization, analyzing their respective advantages and disadvantages in supply chains and management in the context of two major crises such as the COVID-19 pandemic and the armed conflict between Ukraine and Russia. Likewise, the resilience of agro-food and agro-industrial systems that were negatively affected by food insecurity and food price inflation in parts of Europe, Africa, and other regions of the planet is analyzed. By identifying opportunities arising from these challenges, the research offers insights into fostering a more robust agro-food supply chain that is more adaptable to global crises based on the geographic location and regional development of agribusinesses capable of responding to demand in the event of a global crisis such as a pandemic or armed conflict. Full article