Production Price Research Articles

Agricultural Marketing Infrastructure In Coochbehar District Of West Bengal: An Empirical Study

The income of the farmers may highly depend on production and market price of the product but agricultural marketing infrastructure also plays a major role in the profitability of the farmers. Development of agriculture marketing infrastructure can safeguard the farmers from price volatility by enhancing the storage capacity. In this article an attempt is made to analyse the current status and bottlenecks of the agricultural marketing infrastructure of the Cooch Behar District. For the purpose of the study, a survey was conducted and information was collected from 582 respondents from Coochbehar using simple random sampling technique. The study indicates that majority of the farmers of the District do not have cold storage access. Along with it, majority of the farmers are facing problems regarding black marketing of the bonds of cold storages. To tackle these issues, the Government should promote investment in agricultural marketing infrastructure and also take strict action against all those who are involved in black marketing of the bonds.

Agricultural products price prediction based on improved RBF neural network model

ABSTRACT The agricultural products price has been affecting people’s livelihood issues and economic and social security and stability. The cyclical fluctuation of the price of agricultural products often indirectly affects the inner psychological demand of agricultural consumers. If the prices of production and processing industries, which rely on cheap raw materials as basic raw materials, are subject to frequent and abnormal fluctuations, it is likely to cause further widespread concerns about people’s lives, and ultimately lead to a vicious cycle of falling commodity prices. In recent years, as a result of lack of timely authoritative information all the time, the market price of agricultural products appeared a lot of varieties before short-term rise and fall repeatedly phenomenon. This paper attempts to take the quantity of garlic produced and sold by pork in China as the key object of analysis and research, and analyzes the level of market price index and the main factors influencing the price of pork sales and edible garlic demand in China in recent ten years. In information economics, financial market theory, statistical methods and other relevant mathematical model as the main guidance, combined with China’s agricultural prices during the period of policy, select the RBF neural network theory and the analysis methods for technical improvements, in a variety of market factors affecting economic operation under the mixed operation China period in our country agricultural prices technology wave prediction rule, broken Based on the traditional artificial statistics and forecasting model method of agricultural product price, the short-term forecasting model of Chinese agricultural product market price theory based on information technology innovation method was established.

Can Hydrogen Production Be Economically Viable on the Existing Gas-Fired Power Plant Location? New Empirical Evidence

The paper provides an economic model for the assessment of hydrogen production at the site of an existing thermal power plant, which is then integrated into the existing gas grid. The model uses projections of electricity prices, natural gas prices, and CO2 prices, as well as estimates of the cost of building a power-to-gas system for a 25-year period. The objective of this research is to calculate the yellow hydrogen production price for each lifetime year of the Power-to-gas system to evaluate yellow hydrogen competitiveness compared to the fossil alternatives. We test if an incentive scheme is needed to make this technology economically viable. The research also provides several sensitivity scenarios of electricity, natural gas, and CO2 price changes. Our research results clearly prove that yellow hydrogen is not yet competitive with fossil alternatives and needs incentive mechanisms for the time being. At given natural gas and CO2 prices, the incentive for hydrogen production needs to be 52.90 EUR/MWh in 2025 and 36.18 EUR/MWh in 2050. However, the role of hydrogen in the green transition could be very important as it provides ancillary services and balances energy sources in the power system.

Structural sources of oil market volatility and correlation dynamics

This paper explores the structural driving sources of oil market volatility and correlation dynamics using our derived volatility impulse response and correlation decomposition functions. A focal point of this paper is to conduct hypothesis tests for the observed diverging dynamics of oil market volatilities (a steady decline in oil production volatility and a concurrent increase in oil price volatility). In order to circumvent the restriction of uncorrelated disturbances in traditional structural models with stochastic volatility, we specify a time-varying level-volatility transmission matrix that allows for time-varying correlations between level and volatility innovations. Our model generalization hence captures transmissions of unexpected changes in oil levels to oil volatilities, and proves more adequate than traditional models for estimating oil market dynamics. Our results reveal several new useful insights for policy-makers, firms and investors. First, we find that a decrease in oil price persistence is at the origin of the diverging pattern of oil volatilities. Second, decreased variability of flow supply shocks is responsible for about 32% of the reduction in oil production volatility, while increased variability of demand-side shocks explains almost 60% of the increase in oil price volatility. Lastly, we find a near-zero correlation between oil production and oil price since the mid-1980s – a result that supports the theoretical prediction that oil production is inelastic to oil price changes.

Direct Extraction of Platinum Nanoparticles from Fuel Cells with Ionic Liquids: Part 1. Implementation and Optimization of the Process Parameters

The cost of proton-exchange membrane fuel cells (PEMFCs) comes mainly from platinum nanoparticles, which are used as a catalyst; it represents 40% of the stack price for large-scale production. It is thus crucial to reduce their cost to produce cheaper devices, which could compete with fossil energy on the industrial market. One way to reach this goal would be to recover the Pt catalyst from the membrane electrode assembly (MEA) for further recycling. For now, current end-of-life (EoL) technologies are mainly based on hydrometallurgical and pyro-hydrometallurgical processes for recovering platinum, which are identified to be energy-demanding and generate high amounts of toxic liquids and gaseous effluents. To meet sustainability and circular economy criteria in the recycling of noble metals, our approach was based on the use of ionic liquids (ILs) to both extract and stabilize platinum in the form of metallic nanoparticles (Pt NPs), thus avoiding the use of strong acids and the emissions of hydrofluoric acid (HF), which make the waste management of conventional processes complicated. Thirteen different ILs were selected to investigate how their structural composition as well as their physicochemical properties may affect the extent of Pt extraction, and their ability to stabilize detached nanoparticles. This screening study showed that ionic liquids could interact with all of the elements of the active layer and allowed us to delineate the key parameters that ILs should possess to achieve the best extraction performance: hydrophilicity, hydrogen bonding ability, and the coordinating ability of the anions. The best result was obtained with trihexyltetradecylphosphonium chloride (P66614Cl, commercial Cyphos IL 101; 120 °C and 6 h), which not only led to an extraction extent up to >90% of the Pt present initially on the catalytic layer but also allowed in a single step to detach the Pt NPs from the carbon support. The metallic Pt NPs suspended in P66614Cl were found stable with diameters of around 2–3 nm, as evidenced by transmission electron microscopy (TEM) and high-resolution transmission electron microscopy (HRTEM) analyses. Compared to conventional processes, this safer and convenient route to recover Pt catalysts from MEAs directly in their metallic form by simple immersion of the electrode in the appropriate IL opens up new perspectives in terms of rare earth metal recycling from material composites.

Analisis Faktor-Faktor Yang Mempengaruhi Pendapatan Pembudidaya Ikan Air Tawar Di Kabupaten Lima Puluh Kota

<em>The fisheries sector is one sector that has great potential in improving the economy. To increase the income of fish cultivators, farmers need to manage their business results better before they were marketed or sold. The welfare level of fish farmers was still low, this is not because the selling price of fish is low, nor is it because of the large number of imported fish, but rather due to the government's lack of attention to the fishery sector, especially freshwater fisheries. This study used a descriptive method, which was conducted in the Lima Puluh Kota Regency. The selection of the research area was carried out in purposive method. Determination of the research sample using the snowball sampling method. Collecting data using interview method using questionnaires to obtain primary data and documentation method to obtain secondary data. The data analysis method used descriptive qualitative analysis and quantitative analysis using a triangulation technique approach that tested the validity of the data using methods, sources, and theories. The results showed that the factors that significantly influenced the income of fish farmers in Nagari Andaleh, Luak District, Lima Puluh Kota Regency were the number of harvests (X1), land area (X2), production costs (X5), and the selling price of production (X6). While the factors that do not affect the income of rice farmers are farmer education (X3), farmer age (X4) and other occupations (X7).</em>

Molecular cloning, characterization and expression analysis of putative resistance gene analogs from betelvine (Piper betle L.) against anthracnose disease

Betelvine (Piper betle L.) is a cash crop whose cultivation generates healthy earnings, significantly impacting the livelihood security of India and other Asian countries. However, betelvine plant encounters various fungal diseases, out of which anthracnose disease is a serious concern in India caused by Colletotrichum capsici. It causes crop loss up to 60% subsequently decreasing the overall production and market price. Several chemicals and fungicides are used against anthracnose disease. However, all of these are not fully effective in eradicating the disease as well as have an adverse effect on the environment. The development of resistant clones would be an alternative and effective approach. In this study, degenerate primers were used for cloning and characterization of NBS-LRR type resistant gene from betelvine against anthracnose disease. A strong amino acid identity ranging from 90.38 to 97.75% and the presence of internal conserved motifs, provided evidence that the identified resistance gene analogs (RGAs) belong to the non-TIR NBS-LRR class of R genes. The multiple sequence alignment and phylogenetic relationship study identified three non-TIR NBS-LRR class of RGAs from betelvine. Further, the gene expression pattern of identified RGAs were studied against resistant and susceptible lines of betelvine. A differential gene expression pattern after C. capsici inoculation was observed using qRT-PCR. The identification of betelvine RGAs specific to C. capsici would have enough significance for the in depth characterization of potential C. capsici resistance gene and the development of resistant lines.

THE VALUE OF REAL AND VIRTUAL WATER IN THE PRODUCTION OF CONCRET IN THE METROPOLITAN REGION OF BELÉM-PABelém-PA, AMAZONIA, BRAZIL

Water is present in civil construction in real and virtual forms. Real water is used in the extraction of raw materials, for manufacturing building materials and during the daily activities of buildings. Virtual water, on the other hand, is incorporated into the product. Assuming growth in concrete production and water scarcity concerns, this research proposed analysing the amounts, importance and economic values of real and virtual water as intrinsic parts of concrete. By considering the amount of water in raw materials and the corresponding unit costs, the percentages of increase in the value of one cubic metre of concrete correspond to less than 1.14% for real water and 39.9% for virtual water. These price differences, although they exist, are currently not added to the final production price of concrete. Therefore, it is necessary to consider the amount of this natural resource as an inherent part of concrete, so that the value of water can effectively be perceived and approximated by the construction sector today and in the future.

Forecasting value of production of palay and retail price of rice in the Philippines using ARIMA modelling

As rice (milled palay) is an integral part of a Filipino meal, it is important to have an accurate estimation of its governing economic factors such as value of production and retail price. This study utilized Autoregressive Integrated Moving Average (ARIMA) Modelling and Box-Jenkins Method to forecast the value of production of palay and the retail price of the three varieties of its end-product, rice (regular-milled, well-milled, and special), for 2023 to 2027 using historical data from 2000 to 2022, and from 2012 to 2021, respectively. Results suggested that ARIMA (4, 1, 1) can be used to predict the value of production of palay, and ARIMA (1, 1, 1) to predict the retail prices of the three rice varieties. The value of production of palay was forecasted to continuously increase for the next 5 years, retaining its annual seasonal behavior. The retail price of all the three rice varieties were also forecasted to continuously increase, with the special variety of rice expected to surpass its 2018 maximum value by 2027. This study will be of significance in ensuring adequacy and stability of supply in the country for this major agricultural crop.

A novel life cycle assessment and life cycle costing framework for carbon fibre-reinforced composite materials in the aviation industry

PurposeCarbon fibre-reinforced composite materials offer superior mechanical properties and lower weight than conventional metal products. However, relatively, little is known about the environmental impacts and economic costs associated with composite products displacing conventional metal products. The purpose of this study is to develop an integrated life cycle assessment and life cycle costing framework for composite materials in the aviation industry.MethodsAn integrated life cycle assessment (LCA) and life cycle costing (LCC) framework has been developed. The displacement of a conventional aluminium door for an aircraft by a composite door is presented as an example of the use of this framework. A graphical visualisation tool is proposed to model the integrated environmental and economic performances of this displacement. LCA and LCC models for composite applications are developed accordingly. The environmental hotspots are identified, and the sensitivity of the environmental impact results to the different composite waste treatment routes is performed. Subsequently, the research suggests a learning curve to analyse the unit price for competitive mass production. Sensitivity analysis and Monte Carlo simulation have been applied to demonstrate the cost result changes caused by data uncertainty.ResultsEnergy consumption was the hotspot, and the choice of composite waste treatment routes had a negligible effect on the LCA outcomes. Concerning the costs, the most significant cost contribution for the unit door production was labour. The future door production cost was decreased by about 29% based on the learning curve theory. The uncertainties associated with the variables could lead to variations in the production cost of up to about 16%. The comparison between the two doors shows that the composite door had higher potential environmental impacts and cost compared to the conventional aluminium door during the production stage. However, the composite door would have better environmental and financial performance if a weight reduction of 47% was achieved in future designs.ConclusionsThe proposed framework and relevant analysis models were applied through a case study in the aerospace industry, creating a site-specific database for the community to support material selection and product development. The graphical tool was proved to be useful in representing a graphical visualisation comparison based on the integration of the LCA and LCC results of potential modifications to the composite door against the reference door, providing understandable information to the decision-makers.

NaNO3 assisted gelatin-derived multi-level porous carbon aerogel loaded Fe single-atom for high efficient oxygen reduction reaction

In thrall to the low productivity and expensive price of the precious metal catalysts (PMC), it is imminent to develop high-efficient non-noble metal single-atom catalysts (SACs) to replace PMC. However, thermally induced aggregation into nanoparticles and micropores-dominated structures are commonly encountered issues in loading SACs on carbonaceous supports, leading to low exposure ratio of active sites and inadequate mass transference. Herein, we fabricated a series of gelatin-derived carbon-aerogels (GDCAx) to prevent the aggregation of Fe atom and form the hierarchically porous nanonetwork, and thus the Fe SACs (Fe-N-GDCAx) with abundant and hierarchical pores are obtained after pyrolysis. The Fe-N-GDCAx has plentiful accessible Fe-Nx active sites and mass transfer pathways, benefiting to ORR procedure. The optimal sample Fe-N-GDCA0.8 without other gas assisted during annealing (only in argon atmosphere) exhibits exceedingly excellent half-wave potential (E1/2) of 0.93 V (vs. RHE) in 0.1 M KOH. Aqueous zinc-air battery assembled with Fe-N-GDCA0.8 presents ultrahigh specific capacitance of 803.4 mAh gZn−1 (close to 824 mAh gZn−1 theoretical value) and long-term stability. Meanwhile, quasi-solid zinc-air battery has high peak density and specific capacitance of 82.6 mW cm−2 and 713.2 mAh gZn−1 respectively.

Fondillón Wine Adulteration by Addition of Other Monastrell Wines

Authenticity and traceability are two issues of great importance to quality and food safety in the food industry. For wine producers and authorities, it is essential to know how to detect adulterations because wine is one of the alcoholic beverages most prone to adulteration, as indicated by the European Commission. Fondillón is one of the most important naturally sweet Spanish wines and is certainly the core of the Alicante PDO. Fondillón is a wine that is prone to be adulteration due to its limited production and high price. The aim of this study was to identify potential markers of Fondillón adulteration by mixing it with other Monastrell wines. The experimental results showed that Fondillón is characterized by high concentrations of acetic acid, furfural, benzaldehyde, vitispirane, and TDN and low concentrations of citric, tartaric, and malic acids; a low total phenolic content; and low values of antioxidant activity.

An Empirical Analysis of Supply Response of Food Grains to Changes in Price: Evidence from India

The issue of food production is very important as it affects growth, food security and poverty. Stable food grain price is also important to have a stable food grain market. This article attempts to study the impact of food price fluctuations on food production based on the annual data from 1962 to 2019 by using Non-linear Auto Regressive Distributed Lag model. The results show that changes in food grain price affects grain production and it is statistically significant. Furthermore, the result of asymmetric cointegration test shows that there is a long-run asymmetric relationship that exists between food production and food grain price. JEL Codes: Q11, C01, C32

An update on SARS-CoV-2 immunization and future directions.

Millions of people have died as a result of SARS-CoV-2, which was first discovered in China and has since spread globally. Patients with SARS-CoV-2 infection may show a range of symptoms, including fever, coughing, and shortness of breath, or they may show no symptoms at all. To treat COVID-19 symptoms and avoid serious infections, many medications and vaccinations have been employed. However, to entirely eradicate COVID-19 from the world, next-generation vaccine research is required because of the devastating consequences it is having for humanity and every nation's economy. Scientists are working hard to eradicate this dangerous virus across the world. SARS-CoV-2 has also undergone significant mutation, leading to distinct viral types such as the alpha, beta, gamma, delta, and omicron variants. This has sparked discussion about the effectiveness of current vaccines for the newly formed variants. A proper comparison of these vaccinations is required to compare their efficacy as the number of people immunized against SARS-CoV-2 globally increases. Population-level statistics evaluating the capacity of these vaccines to reduce infection are therefore being developed. In this paper, we analyze the many vaccines on the market in terms of their production process, price, dosage needed, and efficacy. This article also discusses the challenges of achieving herd immunity, the likelihood of reinfection, and the importance of convalescent plasma therapy in reducing infection.

Prediction of KLCI Index Through Economic LASSO Regression Model and Model Averaging

The Financial Times Stock Exchange (FTSE) Bursa Malaysia KLCI Index is a key component in the development of Malaysia's economic growth and the complexity in terms of identifying the factors that have a substantial impact on the Malaysian stock market has always been a contentious issue. In this study, the macroeconomic factors of exchange rate, interest rate, gold price, consumer price index, money supply M1, M2, and M3, industrial production, and oil price were discussed by using economic LASSO regression and Bayesian Model Averaging (BMA) with monthly average and monthly end time-series data spanning from January 2015 to June 2021, with a total of 78 observations by using the R Studio. The findings demonstrate that month-end data is better suited for stock market prediction than month-average data and that the BMA model is more suitable than the LASSO model, as seen by lower Mean Square Error of Prediction, MSE(P) and Residual Mean Square Error of Prediction, RMSE(P) values. The exchange rate, gold price, and money supply have a negative association with the dependent variables, while the consumer price index has a positive relationship associated with the dependent variables. The consumer price index is the most significant contributing factor, whereas gold price is the least significant. The result depicted that the KLCI index has no significant relationship with the variables interest rate, money supply M2, M1, industrial production index, and oil price. In conclusion, investors could specifically focus on the positive contributor and put lesser attention on improving their portfolio return.

Hydrothermal liquefaction of wood wastes in a concentrating solar plant: A techno-economic analysis

This paper reports the simulation and techno-economic analysis of a hydrothermal liquefaction (HTL) solar plant for bio-oil production from forestry residues. The HTL solar plant is designed to process 1 ton of biomass daily. The heat required by the HTL process is provided by a parabolic trough solar collector field and a natural gas boiler to allow continuous operation. The annual simulation of the thermal performance of the plant is carried out using the TRNSYS software. The considered location is Temixco, México, and a Typical Meteorological year is used to characterize the site's climate. The bio-oil yield is calculated by a kinetic model that considers the biomass's composition and the slurry's temperature. An economic model is implemented that includes the costs involved and helps determine the bio-oils minimum selling price for the system's financial viability. The obtained yields of biogas, bio-oil, biochar, and organic aqueous phase are 13.3, 29.4, 13.6, and 42.9 wt%, respectively. The minimum fuel sale price (MFSP) for the annual production obtained is estimated between $1.27 and USD 1.55/kg. Eliminating transportation costs, the value of MFSP was assessed in a range of $0.89 to USD 1.09/kg. The results show that integrating concentrated solar thermal technology for processing lignocellulosic waste from the sawmill industry may be an attractive, viable, and sustainable option for producing biofuels, with potential application in countries with high availability of forest biomass, such as Mexico.

ZnO UV sensor photoresponse enhancement by coating method optimization

Modern high-performance photodetector research is driven by the need to simultaneously improve multiple parameters, but also fit the decreasing size of electronics and maintain low production price. Here, we demonstrated how our synthesized ZnO tetrapod (ZnO-T) nanostructure was deposited on electrodes with variating gap by four coating methods including drop casting, microdrop casting, spray coating and slot-die coating with the same thickness. Optimizing the inter-electrode gap and coating method the record IUV/IDark ratio per unit area value of 8.73 × 106 was obtained. The fastest rise time 0.78 s and fastest decay time 0.94 s were obtained by slot-die coated sensors. High photoresponse of ZnO-Ts, the inter-electrode gap size influences formation of ZnO-T microstructure during coating process and morphology influence on photoresponse was explained. We demonstrate that even with the same optimized ZnO-T nanostructures photoresponse can be improved by 2 orders of magnitude. Our work shows the importance of coating morphology and inter-electrode gap optimization.

The shale revolution, geopolitical risk, and oil price volatility

The U.S. shale revolution, using new technologies to extract crude oil, has led to new dynamics in the supply side of the global oil market. We ask whether the shale revolution has dampened the role of geopolitical risk in oil price volatility. We extend a reduced form Structural Break Threshold Vector Autoregressive (SBT-VAR) model to a structural SBT-VAR model and identify the structural innovations by allowing conditional heteroskedasticity. Compared with the conventional reduced form VAR and TVAR models, an SBT-VAR with a constant threshold and a break in April 2014 are supported by the data. We then analyse the conditional (co)variance impulse response concerning two distinct shock scenarios, one with only a geopolitical risk shock, and the other with a simultaneous shale production shock and a geopolitical risk shock. The volatility responses are due to the identified contemporaneous relationships amongst geopolitical risk, shale production and oil prices, and are conditional on volatilities at the points in time. With the extra unit shale production shock, we find that the volatility response of oil prices to a geopolitical risk shock is higher, but the response is less correlated with the geopolitical risk factor.

Agricultural production and market prices in Mexico

Objective: to establish that the price of the main products of the Mexican agricultural sector are cointegrated with the production of the main producing States of the five regions of the Mexican agricultural sector.
 Design/methodology/approach: thirty cointegration tests were carried out to determine if prices influence the production of the main producing States of the regions of the agricultural sector of Mexico of the main products of Mexico, which are grain corn, grain sorghum and bean.
 Results: in the northwest region, the price does not influence the production of the main producing States of grain corn, grain sorghum and beans; In the northeast, central-western and central regions, the price influences the production of the main producing States of grain maize, grain sorghum and beans; and, in the south-southeast region, in most of the States, the price does not affect the production of the main producing States of grain corn, grain sorghum and beans.
 Limitations on study/implications: Not all States and their main products were analyzed because it was not the objective of the investigation.
 Findings/conclusions: the price influences the production, but it does not influence in the same way the production of the five regions of Mexico and neither of the main producing States of grain corn, grain sorghum and beans.

The economic impact of floods on the plantation sector: a study of selected districts in Kerala

The people of Kerala have suffered the worst natural calamity in the form of heavy flood in 2018 and this continued for a week. The flood and the landslide had created a havoc in the agricultural sector of Kerala. The worst affected sector in the vagary of nature was the plantation sector. The industry lost around Rs. 3.382 crore due to heavy floods (CDS). The floods and the landslide had a major impact on the major planation crops including rubber, tea, coffee and cardamom. Among the different districts, Wayanad was the worst affected district along with Kottayam and Pathanamthitta. In the given context, this study is an attempt to analyse the economic impact of floods in the plantation sector in Kerala. The study found that the farmers are facing the worst financial crisis due to low price and high cost of production. The major problems faced by farmers are the inadequacy of assistance, reduction in yield and lack of pure water, delay in getting support, repayment of the loan and so on.