Search Results (47)

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

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

Water scarcity and soil salinization pose significant challenges to sustainable agricultural development in arid and semi-arid regions globally. This study applies Positive Mathematical Programming (PMP) to analyze agricultural water resource management in the Hetao Irrigation District (HID), China. The research constructs a comprehensive multi-stress-factor integrated PMP model to evaluate the compound impacts of water resource constraints, pricing policies, and environmental stress on agricultural production systems. The model incorporates crop-specific salinity tolerance thresholds and simulates farmer decision-making behaviors under various scenarios including water supply reduction (0–100%), water pricing increases (0.2–1.0 CNY/m³), and soil salinity stress (0–10 dS/m). The results reveal that the agricultural system exhibits significant vulnerability characteristics with critical thresholds concentrated in the 60–70% water resource utilization interval. Water pricing policies show limited effectiveness in low-price ranges, with wheat demonstrating the highest price sensitivity (−23.8% elasticity). Crop salinity tolerance analysis indicates that wheat–sunflower rotation systems maintain an 85% planting proportion even under extreme salinity conditions (10 dS/m), significantly outperforming individual crops. The study proposes a hierarchical water resource quota allocation system based on vulnerability thresholds and recommends promoting salt-tolerant rotation systems to enhance agricultural resilience. These findings provide scientific evidence for sustainable water resource management and agricultural adaptation strategies in water-stressed regions, contributing to both theoretical advancement of the PMP methodology and practical policy formulation for irrigation districts facing similar challenges. Full article

Nowadays, food traceability represents an important issue in the current context of trade agreements, which influence global food prices. Many consumers prefer to pay a higher price for a traditional cultivation regime of a certain food product that comes from a certain region, appreciating the taste of the respective foodstuff. The potato is now the world’s fourth most important food crop in terms of human consumption, after wheat, maize, and rice. In this context, 100 potato samples from the Romanian market were collected. While 68 samples came from Romania, the rest of the 32 were from abroad (Hungary, France, Greece, Italy, Germany, Egypt, and Poland). The countries selected for potato sample analysis are among the main exporters of potatoes to the Romanian market. The samples were investigated by their multi-elemental and isotopic (²H, ¹⁸O and ¹³C) fingerprints, using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Isotope Ratio Mass Spectrometry (IRMS). Then, to distinguish the geographical origin, the experimental results were statistically processed using linear discriminant analysis (LDA). The best markers that emphasize Romanian potatoes were identified to be δ¹³C_bulk, δ²H_water, and Sr. Full article

Globally, crop productive systems exhibit climatic adaptation, resulting in increased overall yields over the past century. Nevertheless, inter-annual fluctuations in production can lead to food price volatility, raising concerns about food security. Within this framework, short-term crop yield predictions informed by climate observations may significantly contribute to sustainable agricultural development. In this study, we discuss the criteria for historical monitoring and forecasting of the productive system response to climatic fluctuations, both ordinary and extreme. Here, forecasting is intended as an assessment of the conditional probability distribution of crop yield, given the observed value of a key climatic index in an appropriately chosen month of the year. Wheat production in the Teramo province (central Italy) is adopted as a case study to illustrate the approach. To characterize climatic conditions, this study utilizes the Standardized Precipitation Evapotranspiration Index (SPEI) as a key indicator impacting wheat yield. Validation has been carried out by means of Monte Carlo simulations, confirming the effectiveness of the method. The main findings of this study show that the model describing the yield–SPEI relationship has time-varying parameters and that the study of their variation trend allows for an estimate of their current values. These results are of interest from a methodological point of view, as these methods can be adapted to various crop products across different geographical regions, offering a tool to anticipate production figures. This offers effective tools for informed decision-making in support of both agricultural and economic sustainability, with the additional benefit of helping to mitigate price volatility. 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 current rising food prices, influenced by importation costs, the global food crisis, as well as pre- and post-harvest losses, have contributed majorly to malnutrition and food insecurity. Therefore, utilizing technologies that harness our indigenous agro-products as composite flours to develop functional foods will address these issues. In this study, dry raw samples of perishable and healthy yellow potato, yellow maize and pigeon pea were obtained from the agricultural development program, Edo State, Nigeria, and authenticated and processed into gluten-free fermented composite flours. The flours were profiled physicochemically and nutritionally, providing valuable insight into their multiple benefits. An experimental design software (Design Expert 13.0.) was applied to achieve optimum blended flours regarding the ratio of sweet potato–pigeon pea–maize, and mix 5 (67.70:20.00:12.31) displayed more outstanding attributes than other blends for the production of biscuits, bread and cakes using creaming and mixing methods. Various standard tests for flours and products were appropriately carried out to evaluate the proximate, techno-functional, mineral, antioxidant, anti-nutrient, sensory and color values. Individual antioxidant parameters were improved across all products compared to wheat-based products (control) under the same production conditions, showing a statistical significance at p < 0.05. A similar trend was observed in the proximate, anti-nutritional and mineral contents, while all products had a desirable color outlook. A sensory evaluation revealed the general acceptability, while an in vivo animal experimental model revealed that all animals fed with the various product samples gained weight with improved general body organs and no evidence of disease. This research underscores the potential of harnessing agri-value chain approaches in developing functional foods and promoting food security. Full article

The asymmetric effects of global and national factors on agricultural production negatively affect the sustainability of agriculture in Turkey. This study seeks to explore those impacts on wheat prices by focusing on key input prices such as diesel, fertilizers, and substitute barley prices and wheat production. Unlike studies that use crude oil prices as agricultural input parameters, this study aims to address the lack of behavioural variables in time series studies by considering diesel and fertilizer prices. The Vector Autoregressive (VAR) model analysis examines the effect of barley prices as a substitute for wheat, while the Granger causality analysis is conducted to assess the causal relationships between variables. Additionally, unlike previous studies that primarily focus on causality between variables or the effects of lagged values, this study investigates the dual effects of explanatory variables. Furthermore, impulse response functions are utilized to analyse the dynamic interactions among the variables and to identify symmetric and asymmetric relationships. Granger causality analysis indicates that wheat production in Türkiye is influenced by wheat prices; however, production does not impact prices. Wheat prices are not market-driven, and price interventions aim to ensure agricultural sustainability. The absence of causality between the wheat production amount and its price emerged bilaterally as barley price/wheat production/barley price. An analysis of wheat price responses to shocks in fertilizer and diesel prices reveals an asymmetric pattern. Wheat prices reacted more strongly to negative shocks, while their response to positive shocks was more moderate. These findings indicate the existence of asymmetric relationships between wheat prices and these two agricultural inputs, underscoring the asymmetric nature of price transmission in agricultural markets. They also highlight the policy requirements associated with ensuring food price stability and sustainable agricultural practices as well as a crucial lesson: policymakers in developing countries should prioritize structural reforms over interventionist policies that distort market signals. 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

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

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

This study aims to analyze the drivers behind price changes in agricultural products in Türkiye from 2002 to 2021, considering the impacts of three crises of different causes which are the global food crisis, the Russia–Türkiye aircraft crisis, and the COVID-19 pandemic. The potential factors are categorized into four subgroups: governmental effects, agricultural inputs, macroeconomic indicators, and climatic conditions. The selected agricultural goods for price change measurement include wheat and maize representing subsistence goods, and olive oil and cotton as marketing goods. The autoregressive distributed lag (ARDL) model is applied to observe both the short- and long-term impacts of the variables on price developments. The results suggest that government effectiveness, regulatory quality, nitrogen use, water price, money supply, exchange rate, and GDP under the related categories are the most effective factors in price changes. Among the variables under the category of climatic conditions, significant values are obtained only in the analysis of the temperature impact on olive oil. The analysis also reveals the variable impact of crises on the prices of the chosen products, depending on the goods involved. The maize and wheat analyses yield particularly noteworthy results. In the long run, nitrogen use demonstrates a substantial positive impact, registering at 29% for wheat and 19.47% for maize, respectively. Conversely, GDP exhibits a significant negative impact, with 26.15% and 20.08%. Short-term observations reveal that a unit increase in the governmental effect leads to a reduction in inflation for these products by 17.01% and 21.42%. However, changes in regulatory quality result in an increase in inflation by 25.45% and 20.77% for these products, respectively. Full article