Search Results (39)

The Black–Scholes model is a fundamental concept in modern financial theory. It is designed to estimate the theoretical value of derivatives, particularly option prices, by considering time and risk factors. In the context of agricultural insurance, this model can be applied to premium determination due to the similar characteristics shared with the option pricing mechanism. The primary challenge in its implementation is determining a fair premium by considering the potential financial losses due to crop failure. Therefore, this study aimed to analyze the determination of rainfall index-based agricultural insurance premiums using the standard and fractional Black–Scholes models. The results showed that a solution to the fractional model could be obtained through the Daftardar-Gejji Laplace method. The premium was subsequently calculated using the Black–Scholes model applied throughout the growing season and paid at the beginning of the season. Meanwhile, the fractional Black–Scholes model incorporated the fractional order parameter to provide greater flexibility in the premium payment mechanism. The novelty of this study was in the application of the fractional Black–Scholes model for agricultural insurance premium determination, with due consideration for the long-term effects to ensure more dynamism and flexibility. The results could serve as a reference for governments, agricultural departments, and insurance companies in designing agricultural insurance programs to mitigate risks caused by rainfall fluctuations. Full article

This study assesses the impact of two regulated deficit irrigation (RDI) and one sustained deficit irrigation (SDI) strategies on the fruit quality characteristics of pomegranate (Punica granatum L.) compared to a fully irrigated control in a Mediterranean climate. Field trials were conducted over two growing seasons at the Cajamar Experimental Center in Paiporta, Valencia, Spain. The SDI strategy, which achieved considerable water savings of approximately 50%, led to a reduction in yield (both total and marketable), as well as a decrease in the size and unit weight of the fruits. However, it also produced arils with higher dry matter content and aril juice with higher soluble solids content, all without altering the maturity index. Notably, the SDI approach resulted in increased non-marketable production due to a higher incidence of cracking, particularly during the exceptionally hot and dry summer of 2023. Although the maturity index remained unchanged across the irrigation strategies, the SDI yielded a greater percentage of pink-red rind on marketable fruits compared to the other strategies. This is important because ‘Mollar de Elche’ pomegranates are typically harvested based on their external colour. Thus, the SDI strategy could allow for earlier harvesting, potentially enhancing the commercial value, as earlier harvests often command higher prices, which may partially offset some of the reduction in marketable yield. Conversely, both RDI strategies achieved a slight water saving without compromising marketable yield or the quality characteristics of the fruit. Full article

Background: The global rise in obesity has been significantly influenced by shifts in dietary habits that have been exacerbated by external factors such as the COVID-19 pandemic. This study aims to analyze the trends in Romanian dietary habits from 2015 to 2023, focusing on the impact of the COVID-19 pandemic and the role of socio-economic factors, seasonality, and cultural practices. Methods: For dietary habits, we used nationally representative data from the Romanian Household Budget Survey provided by the Romanian National Institute of Statistics. The survey includes 30,000 households annually. From the same provider, we downloaded data about potential drivers of food consumption, such as income, the consumer price index, and the unemployment rate. The analysis mixes descriptive statistics and panel data analysis. Among the main drivers, the econometric models include seasonality and regional factors, ensuring a comprehensive understanding of the changes in dietary behavior. Results: During the COVID-19 pandemic, daily calorie consumption increased to over 3000 calories per person, representing a 20% increase compared to the pre-pandemic period. Post-pandemic, food consumption remains elevated, averaging 2500–2600 calories per person daily. The pandemic also led to a shift in dietary composition, with significant changes. Thus, we mark an increase in fat (p < 0.001) and carbohydrate intake (p < 0.01) and a decrease in protein intake (p < 0.001). Beyond the presence of health disruptors, we confirm the significant impact of income (p < 0.001) and seasonality (p < 0.001). Other factors like unemployment, the consumer price index, and hidden regional factors have a minor role. Conclusions: The COVID-19 pandemic has had a lasting impact on Romanian dietary habits, reinforcing unhealthy eating patterns that were already prevalent. The sustained increase in calorie consumption, particularly of nutrient-poor, energy-dense foods, poses a significant public health challenge. The study also highlights significant seasonal variations, with a marked increase in food intake during the last quarter of the year, driven by cultural and religious traditions. These findings underscore the need for targeted public health interventions and policies that address economic factors and cultural and regional influences to promote healthier dietary behaviors in Romania. Full article

Sweet cherry (Prunus avium L.) is a valuable fruit crop for fresh consumption. Due to its early availability in season, it achieves relatively high prices on the market. Self-fertile cultivar Lapins is one of the world’s leading sweet cherry varieties. Intensive cherry production seeks for new technologies such as using more adaptable rootstocks and microbiological products that could help plants adopt more sustainable growth in different soils/climates. The aim of this work is to determine the substrate properties, vegetative growth, leaf chlorophyll and mineral content of maiden trees grafted on three different rootstocks due to the application of growth-promoting rhizobacteria. A pot experiment was carried out on one-year-old maiden trees of cv. Lapins grafted on SL 64, MaxMa 14 and Gisela 5 and grown in 12 L plant pots filled with commercial substrate. Plant growth-promoting rhizobacteria Azospirillum brasilense was added by watering the plants with 1.12 g L⁻¹ per pot once a month (T₁) or every two months (T₂) from March to September with seven treatments in T₁ and four treatments in T₂. At the same time, control (C) plants were watered with rainwater. Plant height, trunk circumference and leaf chlorophyll content index (CCI) were measured. In addition, shoot growth and internode number were measured in three development stages (BBCH 34, 39 and 91). The substrate and leaf samples were collected and analyzed in the laboratory in accordance with established procedures. Data were processed by ANOVA and the Tukey test. Results have showed that rootstock affected substrate electrical conductivity (EC); nitrate (NO₃⁻), phosphorous (P₂O₅), calcium (Ca) and magnesium (Mg) content, including mineral nitrogen (N) content; tree height, circumference, shoot length and internode number; the leaf chlorophyll content index (CCI); and leaf potassium (K), Ca and Mg content. Furthermore, treatment significantly affected the CCI, average internode length, ammonia (NH₄⁺) and Ca content in the substrate and leaf N, Ca and Mg content. Rhizobacteria A. brasilense can be used as an additional biofertilizer in sustainable agricultural practices for obtaining healthier sweet cherry maiden trees, but microbial biotechnology rules must be respected. Full article

Due to the vulnerability of pepper (Capsicum spp.) and the virulence of tomato spotted wilt virus (TSWV), seasonal shortages and surges of prices are a challenge and thus threaten household income. Traditional bioassays for detecting TSWV, such as observation for symptoms and reverse transcription-PCR, are time-consuming, labor-intensive, and sometimes lack precision, highlighting the need for a faster and more reliable approach to plant disease assessment. Here, two imaging techniques—Red–Green–Blue (RGB) and hyperspectral imaging (using NDVI and wavelength intensities)—were compared with a bioassay method to study the incidence and severity of TSWV in different pepper accessions. The bioassay results gave TSWV an incidence from 0 to 100% among the accessions, while severity ranged from 0 to 5.68% based on RGB analysis. The normalized difference vegetative index (NDVI) scored from 0.21 to 0.23 for healthy spots on the leaf but from 0.14 to 0.19 for disease spots, depending on the severity of the damage. The peak reflectance of the disease spots on the leaves was identified in the visible light spectrum (430–470 nm) when spectral bands were studied in the broad spectrum (400.93–1004.5 nm). For the selected wavelength in the visible light spectrum, a high reflectance intensity of 340 to 430 was identified for disease areas, but between 270 and 290 for healthy leaves. RGB and hyperspectral imaging techniques can be recommended for precise and accurate detection and quantification of TSWV infection. Full article

By the end of the decade, the world population is expected to increase by nearly one billion people, posing challenges to meeting global food demand. In this scenario, soybean production is projected to increase by 18% within this decade. Despite being the largest soybean producer, responsible for over 40% of soybeans produced worldwide, drought events often impair Brazilian production. The goals of the present research were to quantify soybean yield losses related to drought in Brazil from 1973 to 2023 at national, state, and municipal levels and to assess the spatial distribution of losses across the production areas. The hypothesis investigated is that year-to-year variations in soybean yield are closely related to water availability, considering that crop management practices are constant from year to year, while increments in soybean yield across time (more than five years) relate tightly to better crop management practices and breeding improvements. Thus, quantifying year-to-year yield losses might demonstrate the effects of water availability on soybean yield. Yield data from the 1976/1977 to 2022/2023 crop seasons from the 26 states and the Federal District came from the National Supply Company, while the Brazilian Institute of Geography and Statistics supplied yield data for the 1973/1974 to 2020/2021 crop seasons from 1998 municipalities with more than 14 crop seasons. Soybean drought yield losses were calculated for each cropping season individually at the municipal, state, and national levels, based on the deviation in the observed yield to the corresponding maximum yield in the five-year window, considering that crop management practices and genetics represent a regular increment in soybean yield, which means that production practices improved over time and deviations from year to year are mainly related to drought occurrence. Annual soybean yield loss (expressed in tons, USD, and percentage), frequency of yield loss, and severity of yield loss were calculated at national, state, and municipal levels for each cropping season. The Standardized Precipitation Index (SPI), acquired from the Brazilian Weather Forecast and Climate Studies Center at the National Space Research Institute, was used as a qualitative indicator to corroborate the assessed soybean yield losses related to drought. The results demonstrate yield losses in more than 50% of crop seasons at the national level, with a similar frequency across the five decades, albeit with lower severities in the last 30 years. The Central–West region was more stable than the South region, with yield losses of up to 74%. In five decades, yield losses related to drought events stand at 11.65%, corresponding to 280 million tons or USD 152 billion (considering the average soybean price in 2022 at the Chicago Board of Trade). At the municipal level, analogous behavior was observed across time and space. The outcomes from the present research might subsidize public and corporative policies related to agricultural zoning, farm loan programs, crop insurance contracts, and food security, contributing to higher agricultural, environmental, economic, and social sustainability. Full article

Indigenous foods are used to prepare delicious delicacies (Imefino) in South Africa, and are consumed for their medicinal, food security, and nutritional value. Many of them are rich in macro- and micronutrients and contribute to improving the households’ income. However, the commercialization of many indigenous foods remains problematic with poor market penetration. This study investigates the commercialization status and determinants of indigenous floral food (IFF) commercialization using descriptive statistics, and the double- and triple-hurdle analysis. A semi-structured questionnaire was used to collect cross-sectional data from 240 rural households in Amathole District Municipality in the Eastern Cape Province, South Africa. The result shows that most (60%) of the rural households rely solely on agriculture and agricultural-related activities as their source of employment. Ironically, among the rural household heads who are solely engaged in agriculture, most (83%) do not sell IFFs despite being involved solely in agriculture. More so, there is poor commercialization of IFF with the evidence of a low-commercialization index and low-income generation from IFF. However, IFF consumed for medicinal value has a higher commercialization index. Indigenous foods show potential for commercialization if well harnessed. The results also show that if the rural householder is a male and adds value to indigenous floral foods, he is more likely to make a decision that entails him being involved in the commercialization of indigenous floral foods. The result further proves that the influence of households’ willingness to pay for the improved seed of IFFs will not necessarily affect the intensity of IFF commercialization. Household size is among the determinants of IFF commercialization. Commercialization indicators reveal that rural household heads are committing to IFF commercialization. Based on the study’s overall findings, factors such as seasonality, price, demand fluctuation, and other identified challenges in this study affect IFF commercialization. Programs addressing value addition and the domestication of indigenous floral foods, application of marketing philosophy, and marketing mix, among others, are recommended. Full article

Indonesia suffers significant economic losses from floods, and state budget allocations are often inadequate. Flood bonds provide an alternative funding source, but the pricing framework is complex due to simultaneous flood and financial risk considerations. Therefore, this study aims to model flood bond prices as an alternative flood funding in Indonesia. The model is formulated using the risk-neutral-pricing measure with the stochastic assumption of the force of interest. The claim trigger is represented as maximum rainfall, which is modeled as a continuous-stochastic process with a discrete-time index. Given the varying patterns of rainy and dry seasons, we assume both durations are dynamic. Then, we provide the approximate model solution for the government to estimate bond prices quickly. This estimation shows that the bond’s trigger point is proportional to the bond prices. Additionally, bond prices are proportional to the dry season duration and inversely proportional to the rainy season duration. We also show that using a stochastic force of interest yields significant differences from a constant one except for the constant as data average. This study can help the Indonesian government price flood bonds and provide more tools for related meteorological and climatological institutions to calculate the probability of future maximum rainfall. Full article

Over-budgeting due to inflation is a common phenomenon in the construction industry of both developed and developing countries. Inflation, with time changes, leaves an adverse effect on the project budget. Hence, this study aims to focus on the construction price index (CPI) behavior and inspect its correlation with inflation in Thailand’s construction industry as there has not been much work performed. The prediction of CPI was made from 2024 to 2028, relying on the data set from 2000 to 2023. The relationship between inflation and CPI categories helps in prediction by considering inflation as the independent variable and CPI (All Commodities, Lumber and Wood Products, Cement, and Iron Products) as the dependent variable that was incorporated in EViews to perform automated ARIMA forecasting. The correlation results show that out of four CPI, only Iron Products showed a significant relationship with inflation. For All Commodities, Lumber, and Wood Products, the predicted values were fluctuating, while for Cement and Iron Products, a clear seasonal pattern was observed. This prediction gives a direction to construction industry practitioners to make necessary adjustments to their budget estimation before signing the contract to overcome cost overrun obstruction. Full article

Over the last few decades, short food supply chains and local food markets, where farmers either sell their products directly to consumers or use a limited number of intermediaries, have developed worldwide in rural and urban areas. They complement conventional, often globalized, long food chains where small farmers have little bargaining power, and consumers cannot link the food they buy to a known agricultural producer or geographical area where the food is produced. The advantage of direct sales is that producers can obtain a higher price while consumers have easier access to fresh and seasonal food products. The main aim of the paper is to identify and characterize the spatial concentration of local food systems in Poland and their importance in sustainable development and food policy for healthy eating. As part of this study, an analysis of the statistical data of the Central Statistical Office for 2021 was carried out. Data obtained from the Chief Veterinary Inspectorate as of mid-2021 were analyzed to discuss the topic in detail. Descriptive methods and comparative analyses were used to understand regional differences. Absolute and proportional values were used for the research to enable better comparisons between regions, using the traditional method used in spatial structure studies, i.e., the distribution index (number of entities per 1000 inhabitants). The analysis identified spatial differences and possible implications for food policy and regional development. In addition, data on the number of marketplaces in Polish regions in 2022 were used. The study results indicated that short supply chains in the Polish food system contribute to increasing the availability of healthy local products, which may improve consumer health. However, despite these benefits, the results revealed challenges such as the limited production scale of local suppliers and the need to adapt to changing market conditions. Full article

According to numerous chamber and free-air CO₂ enrichment (FACE) studies with artificially raised CO₂ concentration and/or temperature, it appears that increasing atmospheric CO₂ concentrations ([CO₂]) stimulates crop yield. However, there is still controversy about the extent of the yield stimulation by elevating [CO₂] and concern regarding the potential adverse effects when temperature rises concomitantly. Here, we tested the effects of natural elevated [CO₂] (ca. 120 ppm above the ambient level in 100 years ago) and warming (ca. 1.7–3.2 °C above the ambient level 100 years ago) on rice growth and yield over three crop seasons via a past reference investigation and current experiment (PRICE) study. In 2020–2022, the rice cultivar Tamanishiki (Oryza sativa, ssp. japonica) was grown in Wagner’s pots (1/2000 a) at the experiment fields of Chonnam National University (35°10′ N, 126°53′ E), Gwangju, Korea, according to the pot trial methodology of the reference experiment conducted in 1920–1922. Elevated [CO₂] and temperature over the last 100 years significantly stimulated plant height (13.4% on average), tiller number (11.5%), and shoot biomass (10.8%). In addition, elevated [CO₂] and warming resulted in a marked acceleration of flowering phenology (6.8% or 5.1 days), potentially leading to adverse effects on tiller number and grain yield. While the harvest index exhibited a dramatic reduction (12.2%), grain yield remained unchanged with elevated [CO₂] and warming over the last century. The response of these crop parameters to elevated [CO₂] and warming was highly sensitive to sunshine duration during the period from transplanting to heading. Despite the pot-based observations, considering a piecewise response pattern of C₃ crop productivity to [CO₂] of <500 ppm, our observations demonstrate realistic responses of rice crops to elevated [CO₂] (+120 ppm) and moderate warming (+1.7–3.2 °C) in the absence of adaptation measures (e.g., cultivars and agronomic management practices). Hence, our results suggest that the PRICE platform may provide a promising way to better understand and forecast the net impact of climate change on major crops that have historical and experimental archived data, like rice, wheat, and soybean. Full article

Aligned with Sustainable Development Goal 12 and Sub-Indicator 12.3.1.a, this study rigorously examines food loss dynamics in the longan value chain—encompassing the stages from production to wholesale. Longan, a key commodity in Thailand’s national food loss index calculation, undergoes a comprehensive evaluation following FAO guidelines. This study aims to quantify quantity loss in fresh longan fruit, which pinpoints critical loss stages for targeted policy recommendations. Additionally, it seeks to establish a robust methodology for data collection and calculation, providing a model for evaluating food losses in tropical fruits. Results disclose varying loss percentages across supply chains: quantitative loss 14.07% and qualitative loss 11.02% for domestic consumption, quantitative loss 13.50% and qualitative loss 14.82% for export-bound fresh longans on-season, and quantitative loss 9.85% and qualitative loss 6.52% for export-bound fresh longans off-season. Critical loss stages are identified—particularly over-ripe longan harvesting due to labor shortages and price volatility. Further factors contributing to food losses encompass insufficient pre-harvest handling practices, which result in subsequent post-harvest losses, deficiencies in SO₂ fumigation and storage processes, as well as transportation-related issues. This study’s contribution lies in its comprehensive guidance, emphasizing field survey measurements and aligning with the FAO guidelines, making it a vital tool for quantifying and addressing food loss, especially in the tropical fruit sector. Full article

With the continuous advancement of machine learning and the increasing availability of internet-based information, there is a belief that these approaches and datasets enhance the accuracy of price prediction. However, this study aims to investigate the validity of this claim. The study examines the effectiveness of a large dataset and sophisticated methodologies in forecasting foreign exchange rates (FX) and commodity prices. Specifically, we employ sentiment analysis to construct a robust sentiment index and explore whether combining sentiment analysis with machine learning surpasses the performance of a large dataset when predicting FX and commodity prices. Additionally, we apply machine learning methodologies such as random forest (RF), eXtreme gradient boosting (XGB), and long short-term memory (LSTM), alongside the classical statistical model autoregressive integrated moving average (ARIMA), to forecast these prices and compare the models’ performance. Based on the results, we propose novel methodologies that integrate wavelet transformation with classical ARIMA and machine learning techniques (seasonal-decomposition-ARIMA-LSTM, wavelet-ARIMA-LSTM, wavelet-ARIMA-RF, wavelet-ARIMA-XGB). We apply this analysis procedure to the commodity gold futures prices and the euro foreign exchange rates against the US dollar. Full article

The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affected by fluctuating spot LNG prices. This study aimed to use machine learning (ML) to predict the Japan Korea Marker (JKM), a spot LNG price index, to reduce price fluctuation risks for LNG importers such as the Korean Gas Corporation (KOGAS). Hence, price prediction models were developed based on long short-term memory (LSTM), artificial neural network (ANN), and support vector machine (SVM) algorithms, which were used for time series data prediction. Eighty-seven variables were collected for JKM prediction, of which eight were selected for modeling. Four scenarios (scenarios A, B, C, and D) were devised and tested to analyze the effect of each variable on the performance of the models. Among the eight variables, JKM, national balancing point (NBP), and Brent price indexes demonstrated the largest effects on the performance of the ML models. In contrast, the variable of LNG import volume in China had the least effect. The LSTM model showed a mean absolute error (MAE) of 0.195, making it the best-performing algorithm. However, the LSTM model demonstrated a decreased in performance of at least 57% during the COVID-19 period, which raises concerns regarding the reliability of the test results obtained during that time. The study compared the ML models’ prediction performances with those of the traditional statistical model, autoregressive integrated moving averages (ARIMA), to verify their effectiveness. The comparison results showed that the LSTM model’s performance deviated by an MAE of 15–22%, which can be attributed to the constraints of the small dataset size and conceptual structural differences between the ML and ARIMA models. However, if a sufficiently large dataset can be secured for training, the ML model is expected to perform better than the ARIMA. Additionally, separate tests were conducted to predict the trends of JKM fluctuations and comprehensively validate the practicality of the ML models. Based on the test results, LSTM model, identified as the optimal ML algorithm, achieved a performance of 53% during the regular period and 57% d during the abnormal period (i.e., COVID-19). Subject matter experts agreed that the performance of the ML models could be improved through additional studies, ultimately reducing the risk of price fluctuations when purchasing spot LNG. Full article

Double direct seeding of cotton (with wheat or rapeseed) is a new method for cotton-growing regions in the Yangtze River Basin to adapt to the development of mechanization. It would help to reduce manual labor, optimize the amount of nitrogen fertilizer to be used, reduce the physical and chemical production costs, and improve the benefits of cotton fields. We selected five counties from the major cotton-producing areas of Hubei Province for three consecutive seasons, from winter 2020 to spring 2022. The experimental sites used no tillage with straw returning to the field, double direct seeding, late sowing at high density, and one-time fertilization to study the effects of different nitrogen fertilizer rates on the yield characteristics of cotton, wheat, and rape and calculate the economic benefits of the two cultivation modes under different nitrogen fertilizer input levels through parameters such as land-use efficiency, production efficiency, and profitability. In both cotton–wheat and cotton–rapeseed cropping systems, the number of bolls per plant in cotton was the lowest in the N165 (90 cotton + 75 wheat/rape kg ha⁻¹) treatment. The cotton yield was the highest at N247.5 (135 cotton + 112.5 wheat/rape kg ha⁻¹) in the cotton after the wheat system and N412.5 (225 cotton + 187.5 wheat/rape kg ha⁻¹) in the cotton after the rape system. The yield of wheat and rape increased with the increase in the levels of nitrogen fertilizer, with the N165 treatment showing the lowest values. With an increase in nitrogen fertilizer, the harvest index of wheat first maximized and then started decreasing. The harvest index in wheat was the highest at N247.5 (135 cotton + 112.5 wheat/rape kg ha⁻¹) and N330 (180 cotton + 150 wheat/rape kg ha⁻¹), whereas, in rape, it increased with nitrogen fertilizer application, with the highest value at N495 (270 cotton + 225 wheat/rape kg ha⁻¹). Economically, the expenses and income of both cotton–wheat and cotton–rape systems increased as nitrogen fertilizer increased. The net profit and benefit ratio first increased and then decreased with increasing nitrogen fertilizer, with N247.5 (135 cotton + 112.5 wheat/rape kg ha⁻¹) scoring the maximum values for both of these parameters. The land-use efficiency and production efficiency increased with the increase in nitrogen fertilizer, and the production efficiency of the N165 (90 cotton + 75 wheat/rape) treatment was significantly lower than that of the other four treatments. The profitability increased first and then decreased with the increase in nitrogen fertilizer, with the N247.5 (135 cotton + 112.5 wheat/rape) treatment showing the highest profit. The production cycle of cotton–rape was slightly shorter than that of cotton–wheat, and the system productivity was also lower. The expenses and land-use and production efficiency of the rapeseed system were lower than those of wheat, while the gross income, net profit, and productivity of the cotton–rape system were higher than those of cotton–wheat. The application of nitrogen fertilizer in the cotton–wheat double-cropping system under straw return can achieve the maximum net profit, production ratio, and yield at the low nitrogen level of N247.5, (135 cotton + 112.5 wheat/rape kg ha⁻¹). Due to the price advantage of rape, the net profit, production ratio, and income of the cotton–rape production system are higher than those of the cotton–wheat production system. Full article