Soybean Prices Research Articles

Profit Efficiency of Soybean Production in Federal Capital Territory, Nigeria

This study evaluated profit efficiency of soybeans production in Federal Capital Territory, Nigeria. Multi-stage sampling technique was adopted for this study. Data were collected through the use of well-structured questionnaire. The questionnaire was distributed to 188 sampled soybean farmers in the study area. The data were analyzed using descriptive statistics, gross margin analysis, financial analysis, Cobb-Douglas production functional model. and stochastic frontier profit model. The results of the analysis show that about 25% of the sampled farmers were within the age bracket of 31-40 years, while 56% fell within the age ranges of 41-50 years. The mean age of the sampled soybean farmers was estimated to be 44 years. The results further revealed that majority 82.4% of the sampled respondents were male farmers. About 44.1% of the sampled farmers had no formal education. Majority (78.7%) of the sampled soybeans farmers had a household size range from 1-5 persons, the average farming experience of the farmers in the study area was 7 years. About 80.9% of soybean farmers had farm size between 1-2 ha. The total variable cost on average was N 130,184.51 with an estimated average total revenue of N340,250.00. The gross margin obtained was N210,063.49. The operating ratio and rate of return on investments were 0.383 and 1.613 respectively, this result implies that soybean production is profitable in the study area. The profit efficiency level attained by soybean farmers was 52% leaving a gap of 48%. The statistically significant factors influencing profit efficiency were price of fertilizer (P<0.1), price of chemical (P<0.1), price of labour (P<0.01), unit price of soybean (P<0.01), and total revenue (P<0.01). The statistically significant factors influencing profit inefficiency were household size (P<0.1), educational level (P<0.1), cooperative association (P<0.01), farming experience (P<0.05), access to credit (P<0.05), and price information (P<0.05). The soybean farmers encountered the following problems in the cause of production: inconsistent government policy and outbreak of diseases, lack of hired labour, high cost of inputs, inadequate capital, lack of extension services and unavailability of improved seed varieties. Therefore, this study recommends that government should provide farm tractors and other farm implements to ease the drudgery in soybean production and reduce the cost of labour incur by farmers, market information should be made available for farmers, farmers should be encouraged to expand their scale of production by providing them with production inputs like fertilizer, chemical and credit facilities in order to have increased yield, government should also disseminate price information through extension agents, social media, and mass media (Radio, and Television news) to farmers in order to teach farmers how to apply fertilizer and chemical appropriately.

Text‐based soybean futures price forecasting: A two‐stage deep learning approach

AbstractThis paper investigates the soybean futures price prediction problem from a new perspective and proposes an effective prediction model named Two‐Stage Hybrid Long Short‐Term Memory (TSH‐LSTM) by using text data from social media. First, the unstructured text is transformed into structured data by sentiment analysis and text classification methods. The improved sentiment score is computed by combining the degree centrality of sentiment words based on the sentiment dictionary method, and the characteristics of price fluctuations in texts are learned through the text Recurrent Convolutional Neural Networks. Second, the significant relationship between social media features and soybean futures price is assessed through stepwise regression, and the results of such an assessment are used as a basis for the identification of significant factors as input variables of the prediction model. Finally, the TSH‐LSTM prediction model is designed, and the final prediction result is acquired through the combination of prediction results of each stage using the error reciprocal method. The empirical results indicate that the incorporation of the social media text feature helps improve forecasting performances. Specifically, the proposed TSH‐LSTM is more accurate than univariate LSTM, multivariate LSTM, and eXtreme Gradient Boosting.

Study of Tempe Demand in the City of Lhokseumawe

Soybean is kind food product made from soy materials. It is consumed as the substitution food and snack. Because of high nutrient content and good flavor, soybean becomes one of high demand food every year and it is able to adapt with the consumer preference development. Commonly, the increasing of the price, actually both of fish and beef cause the consumer give the preference to soybean. The research purposes to find out variables that influence the amount of demand and the concern of demand caused by the influence variable changing. The method of analyzing is double logarithm function while the co efficiency regression directly is elasticity co efficiency from each variable. The esult of research shows that the soybean product is still under market interest. The obvious variable that influences soybean demand is the education of housewife otherwise the variable both of soybean price and fish price have given the influence of demand obviously. The relationship between the soybean demand and housewife education is more awareness of soybean nutrientthat is kept consuming as both of substitution food and snack.

The impact of the cost of road transport on the price of Brazilian soybean: the case of Mato Grosso do Sul and the practice of collaborative logistics

Of vital importance to the economy of Mato Grosso do Sul, soybean held the second position in the overview of the products exported in 2020, however, the state is distant from the main export terminals and with high dependence on the road modal. In view of this, the present study sought to evaluate the impact of the average cost of transportation on the price of Mato Grosso do Sul state soybean and the adoption of the practice of collaborative logistics as an alternative to reduce transportation costs. In order to calculate the average cost of road transport, the criteria established in the National Policy of Minimum Costs of Road Cargo Transport (PNPM – TRC) were followed as a guide. Analyzes were made for the vehicle compositions with 7 axles and 9 axles, originating in the municipalities of Maracaju, Ponta Porã and São Gabriel do Oeste and as destinations the port of Santos, Paranaguá and São Francisco do Sul. The results indicate that the vehicle compositions with 9 axles presented the lowest cost per ton transported for all routes analyzed and that, in the comparison between the current scenario and the ideal scenario that considers the adoption of the practice of collaborative logistics with the aggregate of routes Santos (route 1a), Paranaguá (route 1b) and São Francisco do Sul (route 1d) the reduction in the total financial cost for 7-axle compositions was R$ 49,936,261.64, representing a reduction of 5.24% and for 9-axle compositions the reduction in the total financial cost between the current scenario and the ideal scenario of the same aggregate route was R$ 43,462,818.45, representing also a reduction of 5.24%.

PENGARUH PRODUKSI KEDELAI, HARGA KEDELAI IMPOR, DAN NILAI TUKAR TERHADAP IMPOR KEDELAI INDONESIA TAHUN 2011-2020

Indonesia is the 11th largest soybean consuming country in the world at 3 million tons after China, America, Argentina, and Brazil. The increasing demand for soybeans in the country is due to the increasing population and demand for soybeans. However, it is not balanced with soybean reserves that farmers are capable of producing, so imports are the way out. In addition to low soybean production, the price of imported soybeans and the exchange rate of the USD against the Rupiah also affected Indonesia's soybean imports. This study aims to determine the effect of soybean production, imported soybean prices, and exchange rates on soybean imports in 2011-2020. This type of research is a quantitative study with a sample of 40 quarterly data from 2011-2020. The research method used is multiple linear regression with the ordinary least square model. The results of this study show that soybean production, imported soybean prices, and exchange rates simultaneously have a significant effect on soybean imports. Partially soybean production and imported soybean prices each had a significant negative effect on soybean imports, while the exchange rate did not have a significant effect on Indonesia's soybean imports in 2011-2020.

The Impact of Price Support Policies and Public Emergencies on Agricultural Futures Markets — A Multifractal Cross-Correlations Analysis between China and the US

This paper investigates the presence and asymmetry of cross-correlations between agricultural futures markets in China and the US as well as the impact of price support policies and public emergencies (Sino–US trade conflict and COVID-19 pandemic) on the cross-correlations by the multifractal methods. The results show that the fluctuation characteristics and conduction directions of cross-correlations are asymmetric. The price fluctuations of soybean and corn futures in China are easier to be affected by the US soybean and corn futures. We find that the cross-correlations are multifractal under different price support policies and pubic emergencies. The price support policies with greater interventions on soybean and corn prices have aggravated the complexity of cross-correlations between the two futures markets in China and the US. The soybean and corn futures in China are hardly correlated to the US futures under the dual effect of the Sino–US trade conflict and the COVID-19 pandemic. The Sino–US trade conflict strengthens the complexity of cross-correlation for soybean futures and weakens it for corn futures, while the COVID-19 pandemic enhances the complexity of cross-correlations for soybean and corn futures. In addition, the fat-tailed probability distributions in different price support policy and public emergency periods have a dominant influence on the multifractality of cross-correlations.

Soybean price forecasting based on Lasso and regularized asymmetric ν-TSVR

Asymmetric ν-twin Support vector regression (Asy-ν-TSVR) is an effective regression model in price prediction. However, there is a matrix inverse operation when solving its dual problem. It is well known that it may be not reversible, therefore a regularized asymmetric ν-TSVR (RAsy-ν-TSVR) is proposed in this paper to avoid above problem. Numerical experiments on eight Benchmark datasets are conducted to demonstrate the validity of our proposed RAsy-ν-TSVR. Moreover, a statistical test is to further show the effectiveness. Before we apply it to Chinese soybean price forecasting, we firstly employ the Lasso to analyze the influence factors of soybean price, and select 21 important factors from the original 25 factors. And then RAsy-ν-TSVR is used to forecast the Chinese soybean price. It yields the lowest prediction error compared with other four models in both the training and testing phases. Meanwhile it produces lower prediction error after the feature selection than before. So the combined Lasso and RAsy-ν-TSVR model is effective for the Chinese soybean price.

The asymmetric impact of global economic policy uncertainty on international grain prices

Using monthly data from January 1998 to May 2021, this study investigates the asymmetric impact of global economic policy uncertainty (GEPU) on international grain prices by using nonlinear autoregressive distribution lag (NARDL). We find that there is a positive, asymmetric relationship between GEPU and international grain prices. Specifically, GEPU has a greater negative than positive impact on wheat and maize prices, and the positive impact on soybean price is more pronounced than the negative one. We have also observed that the asymmetric impact of GEPU on rice price is not significant in the long run. The findings have important implications to formulate targeted and differentiated international grain price regulatory policies.

Analisis Penawaran dan Permintaan Komoditas Kedelai (Glycine Max L.) di Provinsi Jawa Timur

The purpose of this study is to find out the factors that influence the supply and demand of soybeans and predict the supply and demand of soybeans in East Java in the next 10 years. The data used is Secondary data that has been collected by research institutions and published to data users. The results of the analysis on supply show that there are three factors that have a significant influence on soybean supply in East Java, namely land area, domestic soybean prices, and productivity. Meanwhile, other factors, namely the price of corn and the price of imported soybeans, do not affect the soybean supply in East Java. Of the four factors contained in the soybean demand model in East Java, there is one factor that has a significant influence on the demand for East Java soybeans, namely the population. Meanwhile, other factors are domestic soybean prices, imported soybean prices and income levels. The prediction of East Java soybean supply for the next 10 years will decrease every year until 2030 and the prediction of East Java soybean demand for the next 10 years will increase every year.Keywords: Trend Analysis, Supply and Demand, Soybean, Corn, Land Area

Changes of China’s soybean import market power and influencing factors

ABSTRACT Whether Chinese soybean importers can keenly grasp the changes of different source countries’ market power, will directly affects the safety and cost of soybean import. Based on the analysis of changes in China’s soybean import trade structure, this paper utilizes monthly data from January 2009 to December 2021, combines with the residual demand elasticity model, to compare and analyse the market power of the three major source countries. The results show that although the United States is no longer China’s largest soybean import country, its market power in China’s soybean import market has not been affected, while Argentina’s market power is gradually increasing. Although Brazil has grown into the first source of China’s soybean imports, it has only weak market influence. In addition, China, as the world’s largest buyer, doesn’t have market power. China’s soybean import price is mainly affected by futures prices, domestic soybean prices, international crude oil prices, Sino-US trade frictions and COVID-19 epidemic.

Responding to import surges: Price transmission from international to local soybean markets

Understanding the determinants of price transmission is critical for designing effective policies to cope with grain price fluctuations and protect vulnerable consumers and producers. This study investigates transmission patterns of soybean prices from international to local markets in different contexts of import dependency. Empirical results suggest that price transmission is more pronounced in the low-import dependency period than in the high-import dependency period. We find suggestive evidence that policy intervention and market power are important explanations for this price phenomenon.

TREND OF MARKET PRICE AND SEASONALITY OF SOYBEAN IN GUJARAT

The study was conducted to see the trend and relationship of market price and arrivals of soybean in Gujarat state. Total eight regulated markets were selected purposively on the basis of maximum arrival of soybean in the market. The secondary data on monthly prices and arrivals were collected from the website of www.agmarknet.gov.in of selected regulated markets for last ten years (2010 to 2019). The negative relationship was observed between arrivals and prices of soybean irrespective of the selected markets as expected and the pattern of arrival indices were found to be highest from March to May, whereas the peak of price indices was observed from the month of June to December. This may be due to the storage of soybean by the producers or farmers sale the produce to the local traders and they stored in post harvest season and released in the markets before commencement of new season to fetch better price. Therefore, it was suggested that farmers can sale their produce when prices are on peak in the market to get higher prices for their prosperity.

Comparative Transcriptome and Proteome Analysis Provides New Insights Into the Mechanism of Protein Synthesis in Kenaf (Hibiscus cannabinus L.) Leaves

Given the rising domestic demand and increasing global prices of corn and soybean, China is looking for alternatives for these imports to produce animal fodder. Kenaf (Hibiscus cannabinus L.) has great potential as a new forage source, due to abundant proteins, phenols and flavonoids in its leaves. However, few studies have evaluated the mechanism of protein synthesis in kenaf leaves. In the current work, compared with kenaf material “L332,” the percentage of crude protein content in leaves of material “Q303” increased by 6.13%; combined with transcriptome and proteome data, the kenaf samples were systematically studied to obtain mRNA-protein correlation. Then, the genes/proteins related to protein synthesis in the kenaf leaves were obtained. Moreover, this work detected mRNA expression of 20 differentially expressed genes (DEGs). Meanwhile, 20 differentially expressed proteins (DEPs) related to protein synthesis were performed parallel reaction monitoring. Fructose-1,6-bisphosphatase (FBP), nitrite reductase (NirA), prolyl tRNA synthase (PARS) and glycine dehydrogenase (GLDC) presented increased mRNA and protein levels within kenaf leaves with high protein content. Based on the obtained findings, FBP, NirA, PARS, and GLDC genes may exert a vital function in the protein synthesis of kenaf leaves. The results provide a new idea for further studying the potential genes affecting the quality trait of protein content in kenaf leaves and provide gene resources and a theoretical foundation for further cultivating high protein kenaf varieties.

Trend and Relationship of Market Arrivals and Prices of Major Oilseeds in Krishi Upaj Mandies in Chhattisgarh

Aim: To analysis the trend pattern and correlation of market arrivals and prices of major oilseeds in Krishi Upaj Mandies of Chhattisgarh.
 Study Design: The study was based on secondary data. The linear model for trend analysis and Karl Pearson’s correlation coefficient for relationship between arrivals and prices were used in the study.
 Place and Duration of Study: The study was conducted in four Krishi Upaj Mandies of Chhattisgarh. The monthly wise time series data from period of 2006-07 to 2020-21 were considered for study.
 Methodology: Four Krishi Upaj Mandies viz., Rajnandgaon, Bemetara, Pathalgaon and Ramanujganj were selected according to collectively maximum arrivals of major oilseeds in Chhattisgarh. 
 Results: The trend of arrivals of soybean in Rajnandgaon mandi was observed increasing trend over the year. Whereas, Bemetara mandi was shows negative decreasing trend. In case of groundnut positive but least trend were observed in arrivals of all selected mandies. In case of mustard least trend of arrivals was observed in Bemetara and Pathalgaon mandies. While significant increasing trend were noticed in Rajnandgaon and Ramanujganj mandies. The trends of prices of major oilseeds were found to be positively increasing in all selected mandies. The correlation coefficient of arrivals and prices of major oilseeds were positive and significant in all selected mandies except Bemetara and Rajnandgaon mandies. In Bemetara mandi approx no-correlation was found between arrivals and prices of soybean. Whereas Rajnandgaon mandi of mustard crop was seen positive but not significant of any level.
 Conclusion: The study concludes that the trends of arrivals of major oilseeds in various Mandies were estimated least over the years. The Majorities of Krishi Upaj Mandies were found to be positive and significant correlation between arrivals and prices. It was indicates that the variables of arrivals and prices were significantly associated with each other over the time.

FEED CONVERSION RATE, GROWTH PERFORMANCE AND BIOLOGICAL EFFECTS OF AZOLLA ON POULTRY AND LIVESTOCK: A SYSTEMATIC REVIEW

The rapid rise in soybean prices has necessitated a potential replacement protein source for animal feed. Azolla is a Salviniaceae duckweed with valuable properties that have captivated the public. Its abundance reduces feed costs, which account for the majority of overall production costs. The research on Azolla is extensive, but the efficiency as a potential feed for livestock and poultry is limited. Thus, there is an urgent need to study the efficacy of Azolla as feed materials. A systematic literature review was conducted to collect and analyze information on Azolla as feed materials. Following the Report Standards for Systematic Evidence Synthesis (ROSES) protocol, 13 studies (years 2000-2021) were extracted and reviewed from Scopus, Web of Science, and PubMed. Three aspects were primarily highlighted to review the efficacy of using Azolla as feed: (1) feed conversion rate, (2) growth performance, and (3) biological effects on poultry and livestock. This study revealed that the efficacy and proportion of Azolla in feed vary by animal type. The findings offer greater information on current research directions on this subject.

Work accidents in agriculture: a study of Brazilian soybean production

Soybean cultivation has great economic and social impacts, meaning it offers many job opportunities. Studying the number of accidents in this field is essential for a better understanding of the quality of work related to it. Therefore, the purpose of this article is to verify if, in the field of soybean cultivation, there are correlations between productivity, product price, and the number of accidents, between the years of 1999 and 2018, in Brazil. For that, Pearson’s method was applied, allowing for a bivariate analysis that can quantify a degree of strength between different variables. As a result, it was found that soybean production and price are linearly related to the number of work-related accidents in cultivation. Therefore, it is concluded that, if an increase in price or production occurs, it will lead to an increase in accidents, and the opposite will also happen.

Legal Protection for Soybean Farmers in Cooperation Based on the Muzara'ah Akad with the Murabahah System

Introduction: During the pandemic Covid-19, the global soybean market experienced a shock which resulted in the availability of imported soybeans in several countries decreasing and soybean prices increasing. This also has an impact on small and medium industries that cannot afford soybeans for their processed food raw materials, one of which is the production of “tempe”. Purposes of the Research: The purpose of this study is to explain the concept of cooperation to provide legal protection to soybean farmers based on a muzara'ah akad with a murabahah system. Methods of the Research: The research method used is normative legal research with a statute legal approach and a conceptual approach. Results of the Research: The result of this study include 2 (two) things, namely the concept of cooperation and the form of legal protection. The concept of cooperation consists of: The first scheme, cooperation between the government (Pemda) with soybean farmers and Islamic banks. The second scheme is the cooperation of Islamic banks with soybean farmers using a murabahah akad. The third scheme, namely cooperation between soybean farmers and cultivator using muzara’ah akad. In connection with the form of legal protection, it is divided into 2 (two) namely: first, external legal protection regulated in Law Number 19 of 2013 concerning Protection and Empowerment of Farmers, which was later changed to Law no. 11 of 2020 concerning Job Creation, and second, internal legal protection, namely 3 (three) concepts of cooperation as outlined in a written agreement as a form of guarantee of legal certainty for the parties, especially for soybean farmers.

Food security and power struggle in the Chinese ‘battle of the beans’

ABSTRACT The mid-2000s foreign headway over China’s soybean downstream complex, known as the battle of the beans, reinforced an uncritical nationalist discourse over food security based on a Sino-foreign dichotomy. This article demonstrates through an empirically rich analysis based on four crucial Chinese SOEs that such a discourse ignores diverging capitalist accumulation strategies as two SOEs (COFCO and Chinatex) took advantage of global soybean price fluctuations to grow in association with foreign agribusiness. Instead, I suggest that food security reflects dynamic state-capital relations in China evidenced by the political reaction of two state-owned competitors (Jiusan and Sinograin), endorsing its nationalist appeal.

Pengaruh Penggunaan Teknologi Terhadap Sikap Toleransi Petani Dalam Menghadapi Risiko Usahatani Jagung Di Kecamatan Bandar Baru Kabupaten Pidie Jaya

Corn is one of the food crops cultivated in Aceh Province, precisely in Bandar Baru District, Pidie Jaya Regency. Local corn farmers are soybean farmers who replace crop commodities for cultivation because the selling price of soybeans is lower than the price of corn. The existence of farming risk that occurs forces farmers to have a tolerance attitude towards risk so that the farming that is run will still exist even though the risk occurs. The purpose of this study was to find out what technology has been applied by corn farmers in Bandar Baru District and how the influence of technology use on farmers' tolerance in dealing with corn farming risks. The results of the study show that there have been many application technologies adopted by farmers in Bandar Baru District, 43% of them have reached the high category. The technology that has been applied by corn farmers in Bandar Baru District is the use of superior varieties, quality seeds, botanical pesticides, integrated pest control, tractors, weeding tools, corn shellers, pesticide sprayers, sanitation, rain-fed systems, and drying systems. Then corn farmers in Bandar Baru District who adopt high category application technology are more tolerant of corn farming risks.

Economic policy uncertainty and commodity market volatility: implications for economic recovery.

As a consequence of the COVID-19 pandemic outbreak, most commodities experienced significant price drops, which were expected to continue well into 2020. As a result, the Markov switching model is used to study the influence of policy uncertainty and the COVID-19 pandemic on commodity prices in the USA. Commodity markets are stimulated by economic policy uncertainty, according to results from a two-state Markov switching model. In both high and low regimes, economic policy uncertainty (EPU) influences the commodity market, according to the study’s findings. However, in the high regime, EPU has a greater influence on the energy and metal sectors. EPU has different influences on commodity markets in high- and low-volatility regimes, according to this study. There is a wide range of correlations between COVID-19 outcomes and EPU and how the prices of natural gas, oil, corn, silver, soybean, copper, gold, and steel respond to these tremors, in both high- and low-volatility tenure. Oil and natural gas, on the other hand, are unaffected by shifts in COVID-19 death rates under either regime. Results show that in both high- and low-volatility regimes, the demand and supply for most commodities are responsive to historical prices.