Search Results (76)

Background: There is a high demand for long-term postharvest storage of valuable perishables with high-quality preservation and minimal product loss due to decay and physiological disorders. Postharvest low-pressure storage (LPS) provides a viable option for many fruits. While recent studies have presented the details of technology, this pilot study presents the metabolomics changes due to the hypobaric storage of pomegranates as a model system. Methods: Nuclear magnetic resonance (NMR)-based metabolomics studies were performed on pomegranate fruit tissues, comparing fruit stored under LPS conditions versus the traditional storage system, with modified atmosphere packaging (MAP) as the control. The metabolomic changes in the exocarp, mesocarp, and arils were measured using ¹H NMR spectroscopy, and the results were analyzed using multivariate statistics. Results: Distinguishable differences were noted between the MAP and LPS conditions in fruit quality attributes and metabolite profiles. Sucrose levels in the aril, mesocarp, and exocarp samples were higher under LPS, while sucrose levels were reduced in MAP. In addition, alanine levels were more abundant in the mesocarp and exocarp samples, and ethanol concentration decreased in the exocarp samples, albeit less significantly. Conclusions: This pilot investigation shows the potential for using NMR as a valuable assessment tool for monitoring the performance of viable long-term storage conditions in horticultural commodities. Full article

The phenomenon of rising forward price volatility, both historical and implied, as maturity approaches is referred to as the Samuelson effect or maturity effect. Disregarding this effect leads to significant mispricing of early-exercise options, extendible options, or other path-dependent options. The primary objective of the research is to identify a practical way to incorporate the Samuelson effect into the evaluation of commodity derivatives. We choose to model the instantaneous variance employing the exponential decay parameterizations of the Samuelson effect. We develop efficient calibration techniques utilizing historical futures data and conduct an analysis of statistical errors to provide a benchmark for model performance. The study employs 15 years of data for WTI, Brent, and NG, producing excellent results, with the fitting error consistently inside the statistical error, except for the 2020 crisis period. We assess the stability of the fitted parameters via cross-validation techniques and examine the model’s out-of-sample efficacy. The approach is generalized to encompass seasonal commodities, such as natural gas and electricity. We illustrate the application of the calibrated model of instantaneous variance for the evaluation of commodity derivatives, including swaptions, as well as in the evaluation of power purchase agreements (PPAs). We demonstrate a compelling application of the Samuelson effect to a widely utilized auto-callable equity derivative known as the snowball. Full article

While traditional disposal of solid waste from the global wine industry causes significant environmental burden and hazards, a range of value-added by-products can be produced from the grape marc. This review focuses therefore on crucial sustainability-enhancing technologies for pomace dewatering and separation, which constitute a mandatory stage in obtaining storage-stable by-products and final value-added commodities. A number of dryers and separators were considered for pre-treatment of wet grape marc and analysed in terms of their design characteristics, functionality, feasibility, throughput and efficiency. A multi-criteria decision analysis was carried out to compare, rank and select the equipment which is most suitable for the purpose. It was found out that the rotary drum dryer and the drum screen separator with internal blade rotor are the best candidates to fulfil the technology requirements, while the flowsheet that includes an initial separation followed by drying of the resulting fractions is a rather attractive option. Valorising grape waste worldwide contributes substantially to achieving the United Nations Sustainable Development Goals for responsible consumption and production, mitigating climate change, caring for health and well-being, preserving land life and combating hunger. Full article

The accelerating energy transition, coupled with increasing market volatility and computational advances, has created an urgent need for sophisticated decision-making tools that can address the unique challenges of energy finance—a gap that reinforcement learning methodologies are uniquely positioned to fill. This paper provides a comprehensive review of the application of reinforcement learning (RL) in energy finance, with a particular focus on option value and risk management. Energy markets present unique challenges due to their complex price dynamics, seasonality patterns, regulatory constraints, and the physical nature of energy commodities. Traditional financial modeling approaches often struggle to capture these intricacies adequately. Reinforcement learning, with its ability to learn optimal decision policies through interaction with complex environments, has emerged as a promising alternative methodology. This review examines the theoretical foundations of RL in financial applications, surveys recent literature on RL implementations in energy markets, and critically analyzes the strengths and limitations of these approaches. We explore applications ranging from electricity price forecasting and optimal trading strategies to option valuation, including real options and products common in energy markets. The paper concludes by identifying current challenges and promising directions for future research in this rapidly evolving field. Full article

Volatile fatty acids (VFAs) are inevitable intermediates of biogas production during the anaerobic digestion of organic matter. The excessive accumulation of VFAs leads to a pH drop and the strong inhibition of methanogenesis. On the other hand, VFAs are useful commodities with different applications, and their fermentative production may compete with traditional production methods based on oil derivatives. The fermentation methods have commonalities with the biorefinery concept. The present review considers the methods of VFA fermentative production together with competitive simultaneous biogas and hydrogen production. Methods of the enhanced production of volatile fatty acids are presented, showing the option of integrated processes of product removal and energy production from the obtained biogas. On the basis of the present review, the following conclusion can be drawn. Volatile fatty acids (formic, acetic, propionic, and butyric ones) are useful commodities with various applications. That is why their targeted production with their desired production rate may shift the aims of the anaerobic digestion toward volatile fatty acids instead of biogas release. On the other hand, VFA production combined with biogas release can make the overall process self-consistent, with energy production sufficient to maintain the target processes using biogas for heating the digestor. The maintenance of optimum VFA concentrations can be accomplished by simultaneous VFA removal from the fermentation broth, thus integrating the product recovery with the maintenance of optimum operation conditions in the digester. The substrate preparation and the operating conditions (organic loading rate and hydraulic retention time) are of crucial importance for the successful fermentation process. Full article

Improvements in quality of life, new technologies and population growth have significantly increased energy consumption in Brazil and around the world. The Paris Agreement aims to limit global warming and promote sustainable development, making green hydrogen a fundamental option for industrial decarbonization. Green hydrogen, produced through the electrolysis of water using renewable energy, is gaining traction as a solution to reducing carbon emissions, with the global hydrogen market expected to grow substantially. This study applies the ${\rho }_{DCCA}$ method to evaluate the cross-correlation between the green hydrogen market and various financial assets, including the URTH ETF, Bitcoin, oil futures, and commodities, revealing some strong positive correlations. It highlights the interconnection of the green hydrogen market with developed financial markets and digital currencies. The cross-correlation between the green hydrogen market and the index representing global financial markets presented a value close to 0.7 for small and large time scales, indicating a strong cross-correlation. The green hydrogen market and Bitcoin also presented a cross-correlation value of 0.4. This study provides valuable information for investors and policymakers, especially those concerned with achieving sustainability goals and environmental-social governance compliance and seeking green assets to protect and diversify various traditional investments. Full article

The article mostly addresses the application of sustainable technologies in residential construction through life cycle cost analysis (LCC) using the net present value (NPV) calculation method. The authors rely on data obtained through their own research and information received from the market environment. The article outputs are in the form of conclusions based on a case study on a specific building (apartment building), elaborated in several versions with respect to the technologies used. In total, there are seven alternative versions divided into two groups, where a so-called reference technology representing a traditional (standard) technical solution is present in each group so that a relevant comparison can be made. The first group includes technologies related to heating and hot water, while the second group focuses on the application of recycled water (so-called grey water). The outputs obtained provide an interesting and fact-based view of sustainable technologies within the life cycle of a building drawing from currently available information sources. At the same time, the presented analysis has incorporated price predictions for key commodities, i.e., electricity, water, gas. The article’s specific conclusions indicate that the technologies utilizing renewable energy sources (RES) are typically less economically advantageous (in the absence of subsidy sources) compared to conventional (traditional) solutions, despite the significant savings in operating costs. The LCC indicator revealed a cost value per square meter of gross floor area (GFA) for a residential building ranging from EUR 43 to 68, contingent on the specific option under consideration. This cost value was determined over a 20-year follow-up period and a real discount rate of 4%. Full article

The goal of this paper is to derive closed-form approximation formulas for the spread option value and Greeks by using double integration and investigating the exercise boundary. We have found that the straight-line approximation suggested in previous research does not perform well for curved exercise boundaries. We propose a novel approach: to integrate in a sector and find a closed-form formula expressed in terms of the bivariate normal CDF. We call it the sector formula. Numerical tests show the good accuracy of our sector formula. We demonstrate applications of the formula to the market data of calendar spread options for three major commodities, WTI, Natural Gas, and Corn, listed on the CME site as of May, April, and June 2024. Full article

Due to the uncertainty of world economic development, market demands are stochastic and the supply quantities of suppliers in the supply chain are always flexible, so a mixed wholesale-option-contract (abbreviated as a mixed contract) is one of the good ways for commodity distributors to cope with flexible supply. For a contract farming supply chain composed of a distributor and two suppliers under random demand and yield, we propose the new mixed contracts with flexible supply for the players to make better procurement and inventory decisions. Therefore, with decentralized decision making with a wholesale price contract and centralized decision making as benchmarks for comparison, the advantages of mixed contracts were demonstrated in this paper. The expected profit function under each transaction mode was proved to be concave and the optimal orders or production quantities were obtained and compared. Theoretical derivation and numerical examples were carried out and the main conclusions are as follows. First, the distributor’s total order quantities are the largest under centralized decision making, then the second largest under mixed contracts, then the least under wholesale price contracts. Second, for the dealer under mixed contracts, within the feasible range, the smaller the option price (or option exercise price) is, the greater the dealer’s profit is. Third, with increasing initial order quantity, the gap between the dealer’s profits under different option prices (or option exercise prices) narrows, and eventually tends to the same point. For both the suppliers as a whole, a mixed contract is better than the wholesale price one. Fourth, when the prices of the option contract change within a reasonable range (they may not be too small or too large), the profits of both the dealer and suppliers under a mixed contract are not only higher than those under the wholesale price contract, but also higher than those under centralized decision making. Finally, policies and suggestions (such as full investigation, explicitly defining the process of contracts, establishing real-time supervision and information sharing mechanisms, and so on) were put forward to improve the accuracy of supply and demand forecasting, better implement mixed contracts under flexible supply, and strengthen reforms about agricultural supply side. Full article

The policy objectives of affordable housing programs in China are two-fold: on the one hand, they are designed to assist low- and moderate-income families and reduce inequality; on the other hand, they are intended to lower commodity housing prices. However, the effects of affordable housing land on housing prices, particularly the between-city variation and the mechanisms behind the market effects, have not been sufficiently examined, making it difficult to evaluate the housing policy and improve it accordingly. In this study, we address these gaps by using a prefecture-level panel dataset covering 2009–2020, obtained from national land and housing transaction information platforms. We use a threshold model to investigate the threshold effect of population size and a mediating model to uncover the channels through which the supply of affordable housing land affects housing prices. The results confirm that the affordable housing land supply can have a beneficial influence in terms of slowing down the increase in housing prices. The population size plays a significant role in explaining the between-city market effect variations. In cities with a population greater than 10.78 million, increasing the supply of affordable housing land would cause the housing prices to increase. Meanwhile, in cities with smaller populations, increasing the supply of affordable housing land could lower the housing prices. The underlying mechanisms of the market effects vary across cities with different population sizes. Although affordable housing land crowds out commodity housing land in all cities, housing demand diversion only exists in cities with a smaller population. At present, China is experimenting with city-specific housing policies; our findings imply that decision makers should explore additional policy options, besides building on incremental construction land, in order to make housing more affordable in supercities in China. Full article

In the supplier–retailer–consumer system, the retailer’s replenishment and pricing strategies impact the entire transaction process, forming a comprehensive trading market. Suppliers offer advance-cash-credit payments to retailers, while retailers provide customers with cash-credit payment options. In the current health-conscious consumer market, purchasing decisions are influenced not only by commodity prices but also by the freshness of products, particularly perishable goods. Growing awareness of climate change and the advent of carbon emission policies have raised concerns about the environmental costs of business transactions. This study focuses on perishable products whose demand is influenced by both price and freshness. It explores the adoption of various payment methods by suppliers and retailers, as well as the impact of carbon emission cap-and-trade policies or carbon tax policies on management and pricing strategies. Suitable inventory models are established to determine the optimal replenishment and pricing strategies for maximizing the current value of total profit. We illustrate that the current value of total profit demonstrates joint concavity concerning both the selling price and the replenishment time. Finally, we verify the proposed models using numerical examples and present the findings of sensitivity analyses. The findings of this study yield several valuable insights for inventory management of perishable goods. Full article

During the COVID-19 pandemic, there were significant restrictions on the transportation of food products in Indonesia. The research objective of this study was to investigate the extent to which these restrictions impacted changes in marketing margins at the provincial level in Indonesia. The approach taken was through the examination of trade and freight margin statistical data before the pandemic (2019) and after the pandemic (2020) across a number of different commodity markets: rice, shallots, red chilli pepper, beef, chicken meat and eggs, sugar, and cooking oil. The evidence indicates that the pandemic brought a rapid rise in Indonesian domestic prices as a result of purchasing panic at its start. But after the imposition of transportation restrictions, there were wide variations: some durable food options experienced increased marketing margins, whereas non-durables tended to experience decreased marketing margins in some regions, as fresh products such as red chillies and shallots were discarded as a result of declining consumer purchasing power. The conclusion for policymakers is that any future restrictions should take into account this likely difference in response, in order to minimise economic disruption by calibrating support along the supply chain. Full article

Natural gas is the most growing fossil fuel due to its environmental advantages. For the economical transportation of natural gas to distant markets, physical (i.e., liquefaction and compression) or chemical (i.e., direct and indirect) monetisation options must be considered to reduce volume and meet the demand of different markets. Planning natural gas supply chains is a complex problem in today’s turbulent markets, especially considering the uncertainties associated with final market demand and competition with emerging renewable and hydrogen energies. This review study evaluates the latest research on mathematical programming (i.e., MILP and MINLP) as a decision-making tool for designing and planning natural gas supply chains under different planning horizons. The first part of this study assesses the status of existing natural gas infrastructures by addressing readily available natural monetisation options, quantitative tools for selecting monetisation options, and single-state and multistate natural gas supply chain optimisation models. The second part investigates hydrogen as a potential energy carrier for integration with natural gas supply chains, carbon capture utilisation, and storage technologies. This integration is foreseen to decarbonise systems, diversify the product portfolio, and fill the gap between current supply chains and the future market need of cleaner energy commodities. Since natural gas markets are turbulent and hydrogen energy has the potential to replace fossil fuels in the future, addressing stochastic conditions and demand uncertainty is vital to hedge against risks through designing a responsive supply chain in the project’s early design stages. Hence, hydrogen supply chain optimisation studies and the latest works on hydrogen–natural gas supply chain optimisation were reviewed under deterministic and stochastic conditions. Only quantitative mathematical models for supply chain optimisation, including linear and nonlinear programming models, were considered in this study to evaluate the effectiveness of each proposed approach. Full article

This study analyses a series of live cattle spot and futures prices from the Boi Gordo Index (BGI) in Brazil. The objective is to develop a model that best portrays this commodity’s behaviour to estimate futures prices more accurately. The database created contains 2010 daily entries in which trade in futures contracts occurs, as well as BGI spot sales in the market, from 1 December 2006 to 30 April 2015. One of the most important reasons why this type of risk needs to be measured is to set loss limits. To identify patterns in price behaviour in order to improve future transaction results, investors must analyse fluctuations in asset values for longer periods. Bibliographic research reveals that no other study has conducted a comprehensive analysis of this commodity using this approach. Cattle ranching is big business in Brazil given that in 2021, this sector moved BRL 913.14 billion (USD 169.29 billion). In that year, agribusiness contributed 26.6% of Brazil’s total gross domestic product. Using the proposed risk modelling technique, economic agents can make the best decision about which options within these investors’ reach produce more effective risk management. The methodology is based on Holt–Winters exponential smoothing algorithm, autoregressive integrated moving-average (ARIMA), ARIMA with exogenous inputs, generalised autoregressive conditionally heteroskedastic and generalised autoregressive moving-average (GARMA) models. More specifically, five different methods are applied that allow a comparison of 12 different models as ways to portray and predict the BGI commodity behaviours. The results show that GARMA with order c(2,1) and without intercept is the best model. Investors equipped with such precise modelling insights stand at an advantageous position in the market, promoting informed investment decisions and optimising returns. Full article

Raw rubber production is the sole foundation for the rubber product industry, rendering raw rubber to manufacture essential commodities to mankind, such as tires, condoms, surgical gloves, and so forth. Raw rubber production involves various stakeholders; however, literature focusing on the social impacts of the supply chains of raw rubber production has hereto been absent. Social life cycle assessment, a popular tool to assess the social impacts of a product or process and was deployed herein to assess the social profiles of three Sri Lankan raw rubber supply chains (crepe rubber, concentrated latex, and ribbed smoked sheets) in a cradle-to-gate manner. The Social Hotspots Database v4 on Sima Pro v9.3 was used for the analysis. Results indicated that Governance, Labour rights & decent work had been affected due to Corruption and Freedom of association & collective bargaining issues, mainly in Belarus and China. Proposed improvement options to address these touchpoints were found to be effective. If the importation of K-fertilizer shifted into countries with lower risks, such as Canada, Israel, and Lithuania, overall social risks associated with Corruption and Freedom of association & collective bargaining could be reduced by ca. 36% and 25%, respectively. As a result, social risks in the impact described above categories, i.e., Governance and Labor rights & decent work, were reduced by ca. 35–41% and ca. 17–20%, respectively. Managers may pay thorough attention to the hotspots identified herein in the first place and try to avoid them as much as possible. They may consider importation from the aforesaid low-risk countries while weighing the trade-offs with economic and environmental aspects. Full article