Search Results (38)

Understanding the forces that shape farmland rental prices in major agricultural regions such as the U.S. Corn Belt is essential for evaluating the economic and environmental resilience of agricultural regions. This study develops an integrated framework that combines spatial modelling with uncertainty-aware spatial analysis to examine how macroeconomic conditions influence rental dynamics across the core Corn Belt. Using geographically weighted regression, the analysis captures spatial variation in the sensitivity of rental prices to oil prices, interest rates, and economic activity, revealing substantial geographic heterogeneity in macroeconomic exposure. The results reveal pronounced spatial heterogeneity in rental price responses, with geographically weighted models consistently outperforming global linear specifications. Despite strong spatial variation in rental sensitivities, neither prediction uncertainty nor maize yield volatility displays a clear regional pattern, indicating that production stability and model reliability are highly localised. By linking spatially varying rent sensitivities with indicators of economic pressure and production instability, this study provides new insights into agricultural sustainability risk. The findings highlight the importance of place-based policy and region-specific risk management under increasing macroeconomic volatility. Full article

Due to global increases in poultry meat and egg production, consumers request sustainable agricultural practices, requiring alternative solutions for future feeding. Global egg production increased by over 41% between 2000 and 2020, from 51 to 87 million tonnes, at an average increasing rate of 3%. Similarly, the production of poultry meat reached 145 million tonnes in 2023 and continues to increase, which amplifies the pressure on sustainable alternative feed solutions. Commercial poultry diets are typically based on a cereal (corn or wheat) as an energy source and a quality protein source, especially soybean meal (SBM), to provide essential amino acids. Soybean production is associated with deforesting and land use in several countries, sensitiveness to supply chains and price volatility. As a response to these challenges over the last decade, research and commercial innovation have intensively focused on alternative and novel feed resources that can be integrated into both broiler and layer diets. Some future candidate ingredients are insect meal, algae, agro-industrial by-products such as distiller’s dried grains with solubles (DDGS), brewery spent grains (BSG) and fermented feedstuffs (oilseed cakes/meals). Literature data showed that moderate inclusion of these alternative ingredients can be partly integrated in poultry diets, without compromising egg or meat quality. In some cases, studies showed improvements of productive performances and specific quality traits (yolk color, fatty acids and antioxidant compounds), offering potential to valorize waste streams, improve local circularity and provide functional ingredients for animals and humans. However, challenges still remain, especially in terms of nutrient variability, digestibility limitations, higher processing costs and still-evolving regulations which constrain mainstream adoption of some of these potential future alternatives. Full article

In this paper, we investigate the relationship between spot and futures contracts in the context of spot prices being higher than futures (backwardation). We focus on the persistence in stickiness during backwardation periods by covering major agricultural commodities (corn, oats, soybeans, soybean oil, wheat, and hard red wheat). The period of investigation, January 2000–August 2022, comprises many subperiods, including the pre-2008 global financial crisis, the global financial crisis, the single event of 2014, and the post-2014 stability and growth in world trade. We find the presence of price backwardation and its stickiness for corn and wheat, with the most significant determinants being convenience yield and interest risk. Full article

Crude oil and grain, as two pivotal global commodities, exhibit significant price co-movement that profoundly affects national economic stability and food security. From the perspective of systems theory, the energy and grain markets do not exist in isolation but rather form a highly coupled complex system, characterized by nonlinear feedback, cross-market risk contagion, and cascading effects. This study systematically investigates the transmission mechanisms from international crude oil prices to the domestic prices of Chinese four major grains, employing the DY spillover index, Vector Error Correction Model (VECM), and a mediation effect framework. The empirical findings reveal three key insights. First, rising international crude oil prices significantly strengthen the pass-through of global grain prices to domestic markets, while simultaneously weakening the effectiveness of domestic price stabilization policies. Second, higher crude oil prices amplify international-to-domestic price spillovers by increasing maritime freight costs, a key channel in global grain trade logistics. Third, elevated oil prices stimulate demand for renewable biofuels, including biodiesel and ethanol, thereby boosting international demand for corn and soybeans and intensifying the transmission of price fluctuations in these commodities to the domestic market. These findings reveal the key pathways through which shocks in the energy market affect food security and highlight the necessity of studying the “energy–food” coupling mechanism within a systems framework, enabling a more comprehensive understanding of cross-market risk transmission. Full article

Globalisation, population growth, climate change, and energy-policy shifts have deepened interdependence between agri-food and energy systems, amplifying price volatility. This study examines the determinants of global wheat and corn price dynamics over 2000–2023, emphasising energy markets (oil and biofuels), agronomic and climatic factors, population pressure, and cross-market interdependencies. Using multiple linear regression with backward selection on annual global data from official sources (FAO, USDA, EIA and market series), we quantify the relative contributions of these drivers. The models explain most of the variation in world prices (R² = 0.89 for wheat; 0.92 for corn). Oil prices are a dominant covariate: a 1 USD/barrel increase in Brent is associated with a 1.33 USD/t rise in the wheat price, while a 1 USD/t increase in the corn price raises the wheat price by 0.54 USD/t. Lower biodiesel output per million people is linked to higher wheat prices (+0.67 USD/t), underscoring the role of biofuel supply conditions. We also document an asymmetric yield effect—higher yields correlate positively with wheat prices but negatively with corn—consistent with crop-specific market mechanisms. Although temperature and precipitation were excluded from the regressions due to collinearity, their strong correlations with yields and biofuel activity signal continuing climate risk. The contribution of this study lies in integrating energy, climate, and agricultural market factors within a single empirical framework, offering evidence of their joint role in shaping staple grain prices. These findings add to the literature on food–energy linkages and provide insights for sustainability policies, particularly the design of integrated energy–agriculture strategies and risk-management instruments to enhance resilience in global food systems. Full article

Agricultural markets are increasingly exposed to global risks as climate change intensifies and macro-financial volatility becomes more prevalent. This study examines the dynamic interconnection between major agricultural commodities—soybeans, corn, wheat, rough rice, and sugar—and key uncertainty indicators, including climate policy uncertainty, global economic policy uncertainty, geopolitical risk, financial market volatility, oil price volatility, and the U.S. Dollar Index. Using a Time-Varying Parameter Vector Autoregressive (TVP-VAR) model with monthly data, we assess both internal spillovers within the commodity system and external spillovers from macro-level uncertainties. On average, the external shock from the VIX to corn reaches 12.4%, and the spillover from RGEPU to wheat exceeds 10%, while internal links like corn to wheat remain below 8%. The results show that external uncertainty consistently dominates the connectedness structure, particularly during periods of geopolitical or financial stress, while internal interactions remain relatively subdued. Unexpectedly, recent global disruptions such as the COVID-19 pandemic and the Russia–Ukraine conflict do not exhibit strong or persistent effects on the connectedness patterns, likely due to model smoothing, stockpiling policies, and supply chain adaptations. These findings highlight the importance of strengthening international macro-financial and climate policy coordination to mitigate the propagation of external shocks. By distinguishing between internal and external connectedness under climate stress, this study contributes new insights into how systemic risks affect agri-food systems and offers a methodological framework for future risk monitoring. Full article

According to the FAO, wheat, corn, and rice are staple crops that support global food security, providing 50% of the world’s dietary energy. The ability to predict accurately these key food crop agricultural commodity prices is important in stabilizing markets, supporting policymaking, and informing stakeholders’ decisions. To this aim, machine learning (ML), ensemble learning (EL), deep learning (DL), and time series methods (TS) have been increasingly used for forecasting due to the rapid development of computational power and data availability. This study presents a systematic literature review (SLR) of peer-reviewed original research articles focused on forecasting the prices of wheat, corn, and rice using machine learning (ML), deep learning (DL), ensemble learning (EL), and time series techniques. The results of the study help uncover suitable forecasting methods, such as hybrid deep learning models that consistently outperform traditional methods, and they identify important limitations in model interpretability and the use of region-specific datasets, highlighting the need for explainable and generalizable forecasting solutions. This systematic review adheres to the PRISMA 2020 reporting guidelines. Full article

The outbreak of war in Ukraine has severely disrupted global food and agricultural markets and affected commodity prices. The grain agreement, also known as the Black Sea Initiative, was concluded on 22 July 2022 by Ukraine, Russia, Turkey, and the United Nations, to alleviate the global food crisis caused by the conflict. This study aims to ascertain whether the agreement has resulted in the stabilization of cereal markets, examining the evolution of prices of wheat and corn, which are of significant importance in Ukrainian exports, throughout the duration of the agreement, including its signing, implementation, and expiration. The analysis, based on the GARCH model and using daily quotations of corn and wheat futures contracts of the European futures exchange Euronext from December 2021 to May 2024, indicates that prices were characterized by exceptionally high volatility in the period preceding the signing of the agreement, and at the time of its expiration. The uncertainty regarding cereal trade conditions has triggered shocks, with a long-lasting impact on price volatility. Full article

Corn and soybeans are commodities and ingredients of global interest, whose prices fluctuate based on global demands. In this sense, this study aimed to assess ora-pro-nóbis (Pereskia aculeata) leaf meal (OLM) as an alternative to be included in the diets of Nile tilapia (Oreochromis niloticus). The optimal inclusion level of OLM in tilapia diets is investigated herein, aiming to improve their growth performance and health. Five diet variations containing OLM (0%, 5%, 10%, 15%, and 20%) were tested. Feed conversion and protein efficiency rates in the 5% and 10% OLM groups were statistically similar to the control group (p ≤ 0.05) and lower in the 15% and 20% OLM groups. Fish fed 5% and 10% OLM diets showed better feed efficiency, while higher OLM levels (15% and 20%) led to reduced carcass protein and ether extract levels. Increasing OLM levels enhanced intestinal villi height and area, associated with improved nutrient absorption and decreased liver fat degeneration, suggesting dietary adaptation and healthier liver conditions. Thus, OLM can be included up to 10% in tilapia diets, improving their growth performance, feed efficiency, and intestinal absorptive capacity without adversely affecting other parameters. Full article

The war in Ukraine and the related disruptions in its supply chains shook global markets for agricultural and energy commodities, causing their prices to increase to unprecedented levels. At the same time, this situation highlighted the fact that Ukraine is an important global producer and exporter of certain agricultural products. The complete opening of the EU market to duty-free imports from Ukraine showed that Ukrainian products constitute competition for both EU and Polish food producers. This, in turn, caused further disruptions in the food supply chains within the EU. The aim of this article is to assess the competitive position of Polish and Ukrainian food producers in the EU market and the prospects for the evolution of their competitive advantages. The analysis was carried out using selected quantitative indicators of competitive position, namely Balassa’s Revealed Comparative Advantage Index (RCA) and the Trade Coverage Index (TC). The calculations were made using statistical data from the World Bank WITS-Comtrade database. The research covered the period from 2018 to 2023, inclusive. The research shows that between 2018 and 2023, the share of products in Polish exports to the EU, in which both countries compete, increased to 37.5%; that is, both countries had comparative advantages in these products on this market. The current competition includes, among others, poultry meat, bakery products, wafers and cookies, chocolate, corn, fruit juices, frozen fruit, water and other non-alcoholic drinks, and wheat. At the same time, more than half of Polish exports consisted of products that may become the subject of such competition in the future (currently, only Poland has comparative advantages in the export of these products). These may include, among others, cigarettes, animal feed, fresh or chilled beef, other food products, smoked fish, canned meat, fish fillets, pork, canned fish, and liquid milk and cream. Therefore, Polish food producers face big challenges; the process of the post-war reconstruction of Ukraine and its potential integration with the single European market will strengthen the competitive position of Ukrainian food producers in the EU market. The current competitive strategy of Polish producers, based on cost and price advantages, may turn out to be ineffective under these conditions. Therefore, they must look for new sources of competitive advantage that will distinguish Polish products from the cheaper Ukrainian ones. Therefore, a strategy of competing on quality may prove effective. Full article

The global food market’s escalating volatility has led to a complex network of uncertainty and risk transmission across different grain markets. This study utilizes the Time-Varying Parameter Vector Autoregression (TVP-VAR)-Connectedness approach to analyze the price transmission and volatility dynamics of key grains, including wheat, maize, rice, barley, peanut, soybean, and soybean meal, and their dynamic spillover directions, intensity, and network. By integrating the TVP-VAR-Connectedness model, this research captures the time-varying variability and interconnected nature of global grain price movements. The main findings reveal significant spillover effects, particularly in corn prices, with prices of soybean dominating other grains while prices of peanut and corn experience higher external spillover effects from other grains. The conclusions drawn underscore the imperative for policymakers to consider a holistic perspective of all types of grains when addressing global food security, with this study providing valuable insights for risk management in the grain sector at both global level and country level. Full article

The global market for potato and corn chips is rapidly expanding due to the modern fast-paced lifestyle. However, the high fat content, especially saturated fats in these deep-fried snacks, poses significant health risks such as hypertension, coronary heart disease, and diabetes. In this study, fatty acid profiles of commercially available corn and potato chips are analyzed and their impacts on consumer preferences in Turkey is examined. The findings reveal notable differences in the nutritional content between potato and corn chips, with potato chips generally having higher fat and protein content. The survey results indicate that consumer preferences are significantly influenced by age, education level, and occupation. The factor analysis identified three main components affecting purchasing decisions: nutritional value and additives, hygiene and brand quality, and price and affordability. Considering these insights, manufacturers should be encouraged to reformulate their products to meet the increasing demand for healthier options, emphasize food safety standards, and balance product quality with affordability to appeal to a broader range of consumers. Full article

Drought, as a widespread natural calamity, leads to the most severe agricultural losses among all such disasters. Alterations in the yield of major global agricultural products are pivotal factors influencing food prices, food security, and land use decisions. China’s rapidly expanding demand for sustenance will persist over the forthcoming decades, emphasizing the critical need for an accurate assessment of drought’s impact on food production. Consequently, we conducted a comprehensive evaluation of the drought risk in China and its repercussions on agricultural output. Additionally, we delved into the underlying factors driving changes in yield for three primary grain crops (wheat, corn, and rice), which hold particular relevance for shaping effective strategies to mitigate future drought challenges. The findings divulge that both the number of drought months (DM) and the drought magnitude index (DMI) have displayed an upward trajectory over 60 years with a correlation coefficient of 0.96. The overall severity of meteorological drought has escalated across China, and it is particularly evident in regions such as the southwest and central parts of the Huang-Huai-Hai region, the northwestern middle region, and the Xinjiang region. Conversely, there has been some relief from drought conditions in southern China and the Yangtze River Delta. Shifts in the total grain output (TGO) during this period were compared: it underwent three stages, namely “fluctuating growth” (1961–1999), then a “sharp decline” (2000–2003), followed by “stable growth” (2004–2018). Similarly, changes in the grain planting area (GPA) experienced two stages, “continuous reduction” (1961–2003) succeeded by “stable growth” (2004–2018), while maintaining an upward trend for grain yield per unit area (GY) throughout. Furthermore, it was revealed that the drought grade serves as a significant constraint on continuous expansion within China’s grain output—where the drought damage rate’s influence on the TGO outweighs that from the GY. Our research outcomes play an instrumental role in deepening our comprehension regarding how drought impacts agricultural production within China while furnishing the scientific groundwork to devise efficacious policies addressing these challenges. Full article

As an important cereal crop, maize is a versatile and multi-purpose crop, primarily used as a feed globally, but also is important as a food crop, and has other uses such as oil and industrial raw materials. Quality detection is an indispensable part of functional and usage classification, avoiding significant waste as well as increasing the added value of the product. The research on algorithms for real-time, accurate, and non-destructive identification and localization of corn kernels based on quality classification and equipped with non-destructive algorithms suitable for embedding in intelligent agricultural machinery systems is a key step in improving the effective utilization rate of maize kernels. The difference in maize kernel quality leads to significant differences in price and economic benefits. This algorithm reduced unnecessary waste caused by the low efficiency and accuracy of manual and mechanical detection. Image datasets of four kinds of maize kernel quality were established and each image contains a total of about 20 kernels of different quality randomly distributed. Based on the self-built dataset, the YOLOv7-tiny, as the backbone network, was used to design a maize kernel detection and recognition model named “YOLOv7-MEF”. Firstly, the backbone feature layer of the algorithm was replaced by MobileNetV3 as the feature extraction backbone network. Secondly, ESE-Net was used to enhance feature extraction and obtain better generalization performance. Finally, the loss function was optimized and replaced with the Focal-EOIU loss function. The experiment showed that the improved algorithm achieved an accuracy of 98.94%, a recall of 96.42%, and a Frame Per Second (FPS) of 76.92 with a model size of 9.1 M. This algorithm greatly reduced the size of the model while ensuring high detection accuracy and has good real-time performance. It was suitable for deploying embedded track detection systems in agricultural machinery equipment, providing a powerful theoretical research method for efficient detection of corn kernel quality. Full article

We develop a binary tree pricing model with underlying asset price dynamics following Itô–McKean skew Brownian motion. Our work was motivated by the Corns–Satchell, continuous-time, option pricing model. However, the Corns–Satchell market model is incomplete, while our discrete-time market model is defined in the natural world, extended to the risk-neutral world under the no-arbitrage condition where derivatives are priced under uniquely determined risk-neutral probabilities, and is complete. The skewness introduced in the natural world is preserved in the risk-neutral world. Furthermore, we show that the model preserves skewness under the continuous-time limit. We provide empirical applications of our model to the valuation of European put and call options on exchange-traded funds tracking the S&P Global 1200 index. Full article