Search Results (582)

In this study, we investigate the return propagation mechanism, hedging effectiveness, and portfolio performance across several common agricultural commodities, crude oil, and S&P 500 index, ranging from July 2000 to June 2024 by using a time-varying parameter vector autoregression (TVP-VAR) connectedness approach and three common multiple assets portfolio optimization strategies. The empirical results show that, the total connectedness peaked during the 2008 global financial crisis, followed by the European debt crisis and the COVID-19 pandemic, while it remained relatively lower at the onset of the Russia-Ukraine conflict. In the transmission mechanism, commodities and S&P 500 index exhibit distinct and dynamic characteristics as transmitters or receivers. Portfolio analysis reveals that, with exception of the COVID-19 pandemic, all three dynamic portfolios outperform the S&P 500 benchmark across major global crises. Additionally, the minimum correlation and minimum connectedness strategies are superior than transitional minimum variance method in most scenarios. Our findings have implications for policymakers in preventing systemic risk, for investors in managing portfolio risk, and for farmers and agribusiness enterprises in enhancing economic benefits. Full article

Global policy narratives on livestock development increasingly emphasize environmental concerns, often overlooking the social dimensions of the sector. In the case of dairy, the world’s most valuable agricultural commodity, its role in social and economic development remains poorly quantified. Our study contributes to a more balanced vision of the UN SDGs thanks to the inclusion of a socio-economic dimension. Here we present a novel empirical approach to assess the socio-economic impacts of dairy development using a new global dataset and non-parametric modelling techniques (local polynomial regressions), with yield as a proxy for sectoral performance. We find that as dairy systems intensify, the number of farm households engaged in production declines, yet household incomes rise. On-farm labour productivity also increases, accompanied by a reduction in employment but higher wages. In dairy processing, employment initially grows, peaks, and then contracts, again with rising wages. The most substantial impact is observed among consumers: an increased milk supply leads to lower prices and improved affordability, expanding the access to dairy products. Additionally, dairy development is associated with greater agricultural value added, an expanding tax base, and the increased formalization of the economy. These findings suggest that dairy development, beyond its environmental footprint, plays a significant and largely positive role in social transformation, yet is having to adapt sustainably while tackling labour force relocation, and that dairy development’s social impacts mimic the general agricultural sector. These results might be of interest for the assessment of policies regarding dairy development. Full article

Driven by the rapid expansion of e-commerce in China, there is a growing demand for high-efficiency, sustainability-oriented logistics solutions in rural regions, particularly for the time-sensitive distribution of perishable agricultural commodities. Traditional logistics systems face considerable challenges in these geographically complex regions due to limited infrastructure and extended travel distances. To address these issues, this study proposes an intelligent cooperative delivery system that integrates automated drones with conventional trucks, aiming to enhance both operational efficiency and environmental sustainability. A mixed-integer linear programming (MILP) model is developed to account for the diverse terrain characteristics of rural China, including forest, lake, and mountain regions. To optimize distribution strategies, the model incorporates an improved Fuzzy C-Means (FCM) algorithm combined with a hybrid genetic simulated annealing algorithm. The performance of three transportation modes, namely truck-only, drone-only, and truck–drone integrated delivery, was evaluated and compared. Sustainability-related externalities, such as carbon emission costs and delivery delay penalties, are quantitatively integrated into the total transportation cost objective function. Simulation results indicate that the cooperative delivery model is especially effective in lake regions, significantly reducing overall costs while improving environmental performance and service quality. This research offers practical insights into the development of sustainable intelligent transportation systems tailored to the unique challenges of rural logistics. Full article

Globalization and the spread of technological innovations have made world markets and economies increasingly unified and conditioned by international trade, not only for sales markets but above all for the supply of raw materials necessary for the functioning of the production complex of each country. Alongside oil and gold, the main commodities traded include industrial metals, such as aluminum and copper, mineral products such as gas, electrical and electronic components, agricultural products, and precious metals. The conflict between Russia and Ukraine tested the unification of markets, given that these are countries with notable raw materials and are strongly dedicated to exports. This suggests that commodity prices were able to influence the stock markets, especially in the countries most closely linked to the two belligerents in terms of import-export. Given the importance of industrial metals in this period of energy transition, the aim of our study is to analyze whether Industrial Metals volatility affects G7 stock markets. To this end, the BEKK-GARCH model is used. The sample period spans from 3 January 2018 to 17 September 2024. The results show that lagged shocks and volatility significantly and positively influence the current conditional volatility of commodity and stock returns during all periods. In fact, past shocks inversely influence the current volatility of stock indices in periods when external events disrupt financial markets. The results show a non-linear and positive impact of commodity volatility on the implied volatility of the stock markets. The findings suggest that the war significantly affected stock prices and exacerbated volatility, so investors should diversify their portfolios to maximize returns and reduce risk differently in times of crisis, and a lack of diversification of raw materials is a risky factor for investors. Full article

The major objective was to investigate the protective capabilities of endophytic bacterial strains isolated from a number of medicinal plant species towards Aspergillus spp. secured from the internal tissues of fungi-infected peanuts. Among 32 fungal isolates surveyed for mycotoxin production in various culture media (PDA, RBCA, YES, CA), 10 isolates qualitatively producing AFB₁, besides 10 OTA-producers, were assayed by HPLC for quantitative toxin production. Aspergillus spp. isolate Be 13 produced an extraordinary quantity of 1859.18 μg mL⁻¹ AFB₁, against the lowest toxin level of 280.40 μg mL⁻¹ produced by the fungus isolate IS 4. The estimated amounts of OTA were considerably lower and fell in the range 0.88–6.00 μg mL⁻¹; isolate Sa 1 was superior, while isolate Be 7 seemed inferior. Based on ITS gene sequencing, the highly toxigenic Aspergillus spp. isolates Be 13 and Sa 1 matched the description of A. novoparasiticus and A. ochraceus, respectively, ochraceus, respectively, which are present in GenBank with identity exceeding 99%. According to 16S rRNA gene sequencing, these antagonists labeled Ar6, Ma27 and So34 showed the typical characteristics of Pseudomonas aeruginosa, Bacillus subtilis and Bacillus velezensis, respectively, with similarity percentages of 99–100. The plant growth-promoting activity measurements of the identified endophytes indicated the production of 16.96–80.00 μg/100 mL culture medium of IAA. Phosphate-solubilizing capacity varied among endophytes from 2.50 to 21.38 μg/100 mL. The polysaccharide production pool of bacterial strains ranged between 2.74 and 6.57 mg mL⁻¹. P. aeruginosa Ar6 and B. velezensis successfully produced HCN, but B. subtilis failed. The in vitro mycotoxin biodegradation potential of tested bacterial endophytes indicated the superiority of B. velezensis in degrading both mycotoxins (AFB₁-OTA) with average percentage of 88.7; B. subtilis ranked thereafter (85.6%). The 30-day old peanut (cv. Giza 6) seedlings grown in gnotobiotic system severely injured due to infection with AFB₁/OTA-producing fungi, an effect expressed in significant reductions in shoot and root growth traits. Simultaneous treatment with the endophytic antagonists greatly diminished the harmful impact of the pathogens; B. velezensis was the pioneer, not P. aeruginosa Ar6. In conclusion, these findings proved that several endophytic bacterial species have the potential as alternative tools to chemical fungicides for protecting agricultural commodities against mycotoxin-producing fungi. 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

Digital agriculture has rapidly developed in the last decade in many countries where the share of agricultural production is a significant part of the total volume of gross production. Digital agroecosystems are developed using a variety of IT solutions, software and hardware tools, wired and wireless data transmission technologies, open source code, Open API, etc. A special place in agroecosystems is occupied by electronic payment technologies and blockchain technologies, which allow farmers and other agricultural enterprises to conduct commodity and monetary transactions with suppliers, creditors, and buyers of products. Such ecosystems contribute to the sustainable development of agriculture, agricultural engineering, and management of production and financial operations in the agricultural industry and related industries, as well as in other sectors of the economy of a number of countries. The introduction of crypto solutions in the agricultural sector is designed to create integrated platforms aimed at helping farmers manage supply lines or gain access to financial services. At the same time, there are risks of illegal use of computing power for cryptocurrency mining—cryptojacking. This article offers a thorough risk assessment of cryptojacking attacks on endpoint systems, focusing on identifying critical vulnerabilities within IT infrastructures and outlining practical preventive measures. The analysis examines key attack vectors—including compromised websites, infected applications, and supply chain infiltration—and explores how unauthorized cryptocurrency mining degrades system performance and endangers data security. The research methodology combines an evaluation of current cybersecurity trends, a review of specialized literature, and a controlled experiment simulating cryptojacking attacks. The findings highlight the importance of multi-layered protection mechanisms and ongoing system monitoring to detect malicious activities at an early stage. Full article

This study investigates the impact of dynamically adjusting the potassium-to-calcium ratio (molar ratio) in nutrient solutions used on cherry tomatoes at different growth stages (seedling, flowering and fruit setting, and maturity) to enhance fruit appearance, nutritional quality, and mineral content. By focusing on the ‘Saopolo’ variety, 17 treatments were implemented, each involving a specific potassium-to-calcium ratio in the nutrient solutions applied during the seedling, flowering and fruit setting, and fruiting stages. The aim was to optimize the nutrient solution formula and enhance fruit quality. Fruit quality parameters were assessed at the initial maturity stage across various treatments, encompassing commodity quality (fruit stalk length, fruit shape index, and fruit hardness), taste quality (total soluble sugar, titratable acid content, and sugar-acid ratio), nutritional quality (vitamin C (Vc), soluble protein, and lycopene content), antioxidant quality (total phenol and flavonoid content), as well as comprehensive quality (soluble solids content). Principal component analysis was conducted on these parameters. Additionally, mineral element levels in fruits were analyzed at different developmental stages (white ripe, color transition, and mature stages). When tomato plants were treated with nutrient solutions containing varying potassium-to-calcium ratios at different growth stages, observations revealed distinct outcomes in the first fruit cluster. T15 (seedling stage (A): 0.5 times standard nutrient solution; flowering and fruit-setting stage (B): potassium-to-calcium = 1.6:1; fruiting stage (C): potassium-to-calcium = 2.1:1) exhibited the highest fruit firmness (1.54 kg·cm⁻²), while T14 (A; B (K:Ca = 1.6:1); C (K:Ca = 2.0:1)) elevated levels of total soluble sugars (6.59%), titratable acidity (0.74%), soluble proteins (2.79 mg·g⁻¹), and total phenolics (2.56 mg·g⁻¹). T13 (A; B (K:Ca = 1.6:1); C (K:Ca = 1.9:1)) demonstrated superior soluble solids (5.9%), lycopene (32.09 µg·g⁻¹), and flavonoid contents (0.77 mg·g⁻¹), whereas T12 (A; B (K:Ca = 1.6:1); C (K:Ca = 1.8:1)) showcased the highest sugar–acid ratio (12.63) and soluble solids content (5.9%). Notably, T8 (A; B (K:Ca = 1.5: 1); C (K:Ca = 1.9:1)) exhibited the highest Vc content (10.03 mg·100 g⁻¹). Mineral element analysis indicated that an increased potassium-to-calcium ratio in the nutrient solution during various growth stages enhanced phosphorus and potassium uptake by the fruits but hindered the absorption of nitrogen, calcium, magnesium, and iron. In summary, employing half the standard nutrient solution dosage during the seedling stage, utilizing a potassium-to-calcium ratio of 1.6:1 in the nutrient solution at the flowering and fruit setting stage, and applying nutrient solution T13 with a potassium-to-calcium ratio of 1.9:1 during the fruit-bearing phase, optimally coordinates fruit nutrient accrual and enhances flavor quality. These findings support the use of stage-specific nutrient modulation to improve cherry tomato quality in controlled-environment agriculture. Full article

Cocoa (Theobroma cacao) is one of the world’s most traded commodities. Cocoa grown in agroforestry systems is considered a climate-smart agricultural practice, in part due to the role of shade trees as carbon reservoirs and carbon sinks. In Brazil, most production is concentrated in Bahia state, where traditional cocoa agroforests—locally known as cabrucas—are well known to harbor significant above- and below-ground carbon stocks, although their ability to act as carbon sinks is less well established. By analyzing previously published data on the dynamics of tree assemblages within a 1.7 ha area on a cabruca farm, we estimated an annual carbon increment of 3.46 Mg C ha⁻¹, a value comparable to other shade cocoa plantations elsewhere but more than three times the previous estimate for a cabruca. We discuss the importance of these findings and highlight the potential role of traditional cocoa shade plantations as climate-friendly crops, thus contributing to climate mitigation. It is also essential to highlight the importance of the carbon sequestration and storage services provided by tropical agroforestry systems. Full article

The relationships between mycotoxins content in food commodities or feedstuffs and the foodborne diseases is well known. So far, the available data mainly include chemical methods of mycotoxins decontamination for agricultural commodities or raw materials, including mycotoxin binders. Therefore, the possible use of some natural and cost-effective supplements such as herbs, fungi, microorganisms, or plants with powerful and safe protection against mycotoxin-induced health ailments is the main subject of this review paper. Various antagonistic microorganisms or yeast with fungicidal properties, as well as some herbs or plants that suppress fungal development and the subsequent production of target mycotoxins and/or have protective effect against mycotoxins, are deeply studied in the literature, and practical suggestions are given in this regard. The protection by degradation, biotransformation, or binding of mycotoxins by using natural additives such as herbs or plants to feedstuffs or foods has also been thoroughly investigated and analyzed as a possible approach for ameliorating the target adverse effects of mycotoxins. Possible beneficial dietary changes have also been studied to potentially alleviate mycotoxin toxicity. Practical advice are provided for possible application of the same natural supplements in real-life practice for combating mycotoxin-induced health ailments. Natural feed supplements and bioactive compounds appeared to be safe emerging approaches to preventing health ailments caused by mycotoxins. However, the available data mainly address some in vitro studies, and more in vivo experiments are necessary for introducing such approaches in the real-life practice or industry. Generally, target herbal supplements, antioxidants, or polyenzyme complements could be used as powerful protectors in addition to natural mycotoxin binders. Bioactive agents and enzymatic degradation are reported to be very successful in regard to PAT and OTA, whereas antagonistic microorganisms/fungi/yeasts have a successful application against AFs and PAT-producing fungi. Full article

The prediction of agricultural commodity futures returns is crucial for understanding global economic trends, alleviating inflationary pressures, and optimizing investment portfolios. However, current research that uses full-sample decomposition to predict agricultural futures returns suffers from data leakage, and the resulting forecast bias leads to overly optimistic outcomes. Additionally, previous studies have lacked a comprehensive consideration of key economic variables that influence agricultural prices. To address these issues, this study proposes the “Rolling VMD-LASSO-Mixed Ensemble” forecasting framework and compares its performance with “Rolling VMD” against univariate models, “Rolling VMD-LASSO” against “Rolling VMD”, and “Rolling VMD-LASSO-Mixed Ensemble” against “Rolling VMD-LASSO”. Empirical results show that, on average, “Rolling VMD” improved MSE, MAE, Theil U, ARV, and DA by 3.05%, 1.09%, 1.52%, 2.96%, and 11.11%, respectively, compared to univariate models. “Rolling VMD-LASSO” improved these five indicators by 2.11%, 1.15%, 1.09%, 2.13%, and 1.00% over “Rolling VMD”. The decision tree-based “Rolling VMD-LASSO-Mixed Ensemble” outperformed “Rolling VMD-LASSO” by 1.98%, 0.96%, 1.28%, 2.55%, and 4.18% in the five metrics. Furthermore, the daily average return, maximum drawdown, Sharpe ratio, Sortino ratio, and Calmar ratio based on prediction results also show that “Rolling VMD” outperforms univariate forecasting, “Rolling VMD-LASSO” outperforms “Rolling VMD”, and “Rolling VMD-LASSO-Mixed Ensemble” outperforms “Rolling VMD-LASSO”. This study provides a more accurate and robust forecasting framework for the global agricultural futures market, offering significant practical value for investor risk management and policymakers in stabilizing prices. Full article

Soybean is one of the main agricultural commodities, and its productivity is limited by several diseases, such as anthracnose, which is caused by a complex of fungal species, with Colletotrichum truncatum being the most prevalent. Management is mainly carried out through chemical seed treatment. However, a reduction in the sensitivity of C. truncatum to fungicides was observed. Therefore, it is extremely important to search for products that are effective in controlling the disease. The objectives of this study were to evaluate the efficacy of commercial formulations of copper, potassium, manganese, and zinc phosphites in the treatment of soybean seeds infected by C. truncatum, as well as their direct fungitoxicity and ability to induce soybean defense mechanisms. For this purpose, seeds inoculated with C. truncatum were subjected to phosphites and a fungicide (carbendazim + thiram). The seeds were exposed to germination, health, and vigor tests. Fungal toxicity and the ability of phosphites to induce defense through the activities of catalase, peroxidase, and superoxide dismutase enzymes, as well as the levels of lignin and total soluble phenols, were also evaluated. Mn and Zn phosphites showed direct toxicity to C. truncatum and were as effective as the fungicide (carbendazim + thiram) in treating soybean seeds infected by the fungus. Mn phosphite induced the production of catalase (CAT), peroxidase (POX) and lignin, while Zn phosphite increased the production of CAT and POX. These results demonstrate the efficacy of Mn and Zn phosphites in controlling C. truncatum in infected soybean seeds, their direct toxic action, and their ability to induce resistance. Full article

Fresh produce, such as peaches and apples, are agricultural commodities, making them susceptible to contamination by foodborne pathogens such as Listeria monocytogenes and Salmonella enterica. Traditional methods, such as chlorine washes, have limitations related to antimicrobial efficacy, prompting interest in alternative techniques, such as power ultrasound. This study evaluated the use of power ultrasound, alone and combined with organic acids (citric, lactic, and malic), to reduce pathogen populations on whole apples and peaches. Pathogen cocktails of L. monocytogenes and S. enterica were spot-inoculated on fruit surfaces at an initial population level of 8–9 log CFU/fruit. The fruits were then submerged in water or citric, malic, or lactic acid at concentrations of 1%, 2%, or 5% alone or with power ultrasound treatment at 40 kHz for 2, 5, or 10 min. Results revealed that treatment conditions on apples exhibited significantly greater pathogen reduction than on peaches, likely due to the smoother surface topology on apples compared to the rougher, trichome-covered peach surfaces. Between the two pathogens, L. monocytogenes exhibited significantly greater resistance to treatments, resulting in maximum reductions of approximately 4 log CFU/fruit. In contrast, treatments were more effective against S. enterica, as lactic acid alone reduced S. enterica populations by >6 log CFU/fruit. Malic acid was the second-most effective organic acid against S. enterica, leading to >4 log CFU/fruit reduction. Synergistic antimicrobial effects were observed when organic acids were used in combination with power ultrasound. For instance, an additional reduction of 2–3 log CFU/fruit was achieved for S. enterica compared to the use of organic acid treatments alone. These findings support the use of organic acid and power ultrasound in hurdle as an effective strategy to mitigate foodborne pathogen risks on whole fruits such as apples and peaches. Further research would be helpful to optimize and validate such hurdle treatments for inactivating a broader spectrum of microbial pathogens on diverse produce surfaces. Full article

The fresh produce supply chain sector is a vital pillar of any society and an indispensable part of the national economic structure. As a significant segment of the agricultural market, accurately forecasting vegetable prices holds significant importance. Vegetable market pricing is subject to a myriad of complex influences, resulting in nonlinear patterns that conventional time series methodologies often struggle to decode. Future planning for commodity pricing is achievable by forecasting the future price anticipated by the current circumstances. This paper presents a price forecasting methodology for tomatoes which uses price and production data taken from 2008 to 2021 and analyzed by means of advanced deep learning-based Long Short-Term Memory (LSTM) networks. A comparative analysis of three models based on Root Mean Square Error (RMSE) identifies LSTM as the most accurate model, achieving the lowest RMSE (0.2818), while SARIMA performs relatively well. The proposed deep learning-based method significantly improved the results versus other conventional machine learning and statistical time series analysis methods. Full article

Carbohydrate-based biodegradable films offer an eco-friendly alternative to conventional petroleum-derived packaging for agricultural commodities. Derived from renewable polysaccharides such as starch, cellulose, chitosan, pectin, alginate, pullulan, and xanthan gum, these films exhibit favorable biodegradability, film-forming ability, and compatibility with food systems. This review presents a comprehensive analysis of recent developments in the preparation, functionalization, and application of these polysaccharide-based films for agricultural packaging. Emphasis is placed on emerging fabrication techniques, including electrospinning, extrusion, and layer-by-layer assembly, which have significantly enhanced the mechanical, barrier, and antimicrobial properties of these materials. Furthermore, the incorporation of active compounds such as antioxidants and antimicrobials has improved the performance and shelf-life of packaged goods. Despite notable advancements, key limitations such as moisture sensitivity, poor mechanical durability, and high production costs persist. Strategies including polymer blending, nanofiller incorporation, and surface modification are explored as potential solutions. The applicability of these films in packaging fruits, vegetables, dairy, grains, and meat products is also discussed. By assessing current progress and future prospects, this review underscores the importance of carbohydrate-based films in promoting sustainable agricultural packaging systems, reducing environmental impact through the advancement of circular bioeconomy principles and sustainable development. Full article