Efficiency Of Agricultural Sector Research Articles

THE TURKMENISTAN FEED PRODUCTION’S TECHNOLOGIES IMPROVEMENT ABOUT

The agricultural sector efficiency increasing as a whole puts forwards new requirements for scientific-and-technical achievements using. In the feed production system this is feed preparation, storage and distribution’s harvesting technologies in a single producing line improving. There are harvested more than 2 million tons of wheat straw annually in Turkmenistan. If the straw is properly prepared and with more valuable feed enriched, can be assumed that more than in 30% of feed to animal main ration of feeding it will be added. Therefore in front of machine builders’ face the task of modern highperformance sets of machines’ farm equipping. The forage harvesting equipment development should be carried out by forage harvesting operations reducing and combining, machines universalization’s justifying. An important factor in the food canning technology is the necessary equipment’s combination and selection for performance, bodywork and trench’s capacity, feed shelter and loading time keeping. On the straw processing and preparation’ numerous production-and-practical experiences in order its digestibility increasing basis, we a wheat straw enriching technology have developed. To implement proposed technology, these machines must be self-propelled and mounted. The silage harvesting technology (especially at corn green mass’ high humidity - up to 80% instead of the optimal 65-75%) having studied, we proposed with straw noncrushed addition in an amount of 8-10% of the green mass’s total weight with its layer-by-layer into the trenches introducing to carry out for silage quality improving. As a result of experimental studies, the given silage had a yellowish-green color, a pleasant smell, 4.2 acidity (pH) did not exceed.

Dynamic assessment of agro-industrial sector efficiency and productivity changes among G20 nations

In this study, the Group of 20 (G20; excluding EU economies) were selected as the research objects, and the dynamic network slacks-based model (SBM) was used to evaluate the impact of carbon dioxide (CO2) emissions and forested area on the efficiency and productivity of the industrial and agricultural sectors from 2011 to 2015. Empirical results showed that: (1) The efficiency of the industrial sector was superior to that of the agricultural sector among the G20 countries. Argentina, Australia, Indonesia, Saudi Arabia, South Africa, Turkey, the UK, and the US maintained the best industrial sector efficiency values, falling on the efficiency boundary, whereas Argentina, Brazil, Canada, France, Indonesia, South Korea, Russia, and the US had the best agricultural sector efficiency values. (2) Argentina, Indonesia, and the US had the best overall efficiency value of G20 countries. Saudi Arabia (0.0303), China (0.2721), and the UK (0.2809) had the lowest efficiency values. (3) Only France and Germany had higher than average total factor productivity, while Indonesia and Saudi Arabia had declining industrial and agricultural sector productivity. (4) The proportion of forested area (546.02%) was the most important variable to be improved due to the influence of desert topography, followed by the proportion of agricultural output values (60.86%) and the proportion of industrial output values (38.02%) in some countries.

Digital extension and the development of agricultural performance in Indonesia

The agricultural sector plays an essential role in providing foodstuffs for the population of every country. However, the lack of innovation in agricultural technology and the limited distribution channels for crop yields have caused farmers' welfare levels to be relatively low in various regions. Meanwhile, Smart Agriculture and 4.0 Technologies play a considerable role in increasing the agricultural sector's efficiency. Digitalization has had a significant influence on transforming traditional agricultural systems into data management-based approaches. The Desa Apps is an open access agricultural extension platform developed in Indonesia that facilitates farmers to interact with other farmers to share ideas, innovations, and solutions to face various farm and off-farm obstacles. This paper aims to describe the development platform and identify opportunities related to developing the Desa Apps platform. The results showed that Java and Sumatra islands have good potential for developing the Desa Apps platform. Besides, the registered members with the most significant reporting level are farmers, extension agents, and traders.

Integrated assessment of cleaning air policy in China: A case study for Beijing-Tianjin-Hebei region

Since 2018, the Blue Sky Protection Campaign (BSPC) have been implemented at unprecedented levels to combat air pollution in the Beijing-Tianjin-Hebei (JJJ) region. In this study, the GAINS IV Asia (Greenhouse Gas and Air Pollution Interactions and Synergies) model is used to assess the potential for air pollution abatement, air quality improvement and associated costs of the BSPC in the JJJ region. The key findings are: 1) The total energy consumption under BSPC will decrease by 3%, 2%, and 6% for Beijing, Tianjin, and Hebei, respectively, by 2020 compared with the baseline scenario and Hebei is projected to experience the greatest changes in energy consumption both in absolute terms and in proportion. 2) Hebei would have the largest air pollution abatement. Compared to 2015, emissions of NOx, PM2.5, SO2, and NH3 under 2020 will be decrease by 31.3% 44.8%, 40.3%, and 10.7%, respectively. Residential and industrial combustion play vital contributions for pollution abatement, accounting for 52.3% together of Hebei’s total. 3) Emissions of NOx, PM2.5, and SO2 of Beijing will decrease by 21.2%, 58.7%, and 56.1% by 2020, compared to 2015. Transportation and residential sectors have key contributions to reductions. 4) The population-weighted annual PM2.5 concentration would decrease to 41.4 μg/m³, 49.4 μg/m³, and 53.8 μg/m³ by 2020 in Beijing, Tianjin, and Hebei, respectively. Finally, we recommend that actions of increasing nitrogen use efficiency of agricultural sector, super low emission standard in industrial sector, and switching off coal power plants are most cost-effective in air quality improvement during 2020–2025.

Solving the problem of energy efficiency of remote agricultural farms

The research focuses on the viability of a mathematical model of energy efficiency of agricultural sector for the case of Russia. The article describes the methodology and results of research aimed at improving energy efficiency in the activities of remote farms of the agro-industrial complex. The emphasis is placed on the application of a scientific approach based on mathematical modeling of work on a limited resource. For this purpose, the most common solutions are SAN (Storage Area Network), while the programs that are common for enterprises of the network are located on cloud servers. The results of the research were applied in a joint project with the Catalan Polytechnic University (Polytechnic University of Catalonia).

ОПТИМИЗАЦИОННЫЕ МОДЕЛИ РАСПРЕДЕЛЕНИЯ ЗЕМЕЛЬНЫХ УГОДИЙ ПОД ЗЕРНОВЫЕ КУЛЬТУРЫ

In this study, the goal is theoretical and practical aspects of optimizing agricultural production management in the system of market economy based on economic and mathematical modeling. The relevance of the topic - in the theoretical and methodological provisions for improving agricultural sector, taking into account modern trends which is proposed by the authors. Optimization models of specialization in agriculture in conditions of irrigated agriculture in deterministic and stochastic formulations on the basis of their technological specifics in the practice of planning grain production of the SNP "Akzhar" of Saryagash district of Turkestan region have been built and implemented. The objective function is to maximize its total income. The specialization of cultivation of six grain crops on irrigated lands was investigated. The dependences of their productivity were revealed, taking into account moisture for irrigation and mineral fertilizers on the basis of multivariate regression models. The article presents economic and mathematical models for determining the optimal size of agricultural enterprises on irrigation, which make it possible to rationally use natural production resources and make informed management decisions. The results of the study are new methodologies for constructing an integrated system for optimizing the management of agricultural production activities, aimed at increasing the level of effective use of material and labor resources. The specified set of economic and mathematical models is aimed to help to the heads of farms and regions. The introduction of this approach through the implementation of optimization schemes allows to increase the amount of profit, increase economic efficiency of agricultural sector.

Exploring environmental efficiency of the European agricultural sector in the use of mineral fertilizers

This study analyzes the environmental efficiency of the agricultural sector regarding the use of mineral fertilizers in the period 2001–2012 for a group of European countries. Specifically, efficiency is assessed through a dynamic Data Envelopment Analysis methodology. This method aims to analyze temporal efficiency changes through the estimation of Malmquist indexes with increasing and decreasing temporal windows. Findings show that most countries register efficiency advances in the periods 2002–2003 and 2007–2008. Specific countries, such as Belgium-Luxembourg, Denmark, Netherlands, Sweden and United Kingdom, register persistently higher values of the estimated Malmquist indexes. This study contributes to the existing literature by assessing country-specific efficiency paths, as well as by identifying best-performing countries from which lessons can be learnt. A brief review of main measures taken by a selected group of benchmark countries is offered.

Increasing labor productivity as the major line of agricultural industry development

The improvement of the agricultural sector efficiency, a shift to innovative development approaches to increase the competitiveness of domestic agriculture in modern conditions is possible only if labor productivity increases. This task is more relevant today than ever, since the main factor of production – labor (labor resources) has a steady downward trend. The study has shown that in the agricultural sector of the region there is an increase of labor productivity both by value and volume. The application of deterministic factor analysis has revealed that in the dynamics both factors (number of employees and cost of production) had a positive impact on increasing labor productivity, but the increase in production volumes in the industry had a more noticeable effect (the value of the factor varied from 57.7 to 69.7 %). However due regard must be paid to the fact that agricultural production is subject to fluctuations and the decrease in the number of workers in the industry is sustainable. The positive impact and the main factor in the growth of annual labor productivity is an increase in the average hourly output of workers due to an increase in the yield and technical re-equipment, and this should be noted as a strategically important direction for the development of the industry. The normalization of employment also acts as a factor in further increasing labor productivity.

Formation of conceptual apparatus of agroindustrial complex stable development as a megacluster

The economy clustering makes it possible to form a comprehensive look at the state policy of regional development, increase performance, efficiency and competitiveness of business, expand opportunities for innovative development, optimize interaction between various subjects: state, business structures, research and educational establishments and other organizations. As world practice shows, the cluster claims to be one of the key components of the competitiveness of the most progressively developing countries. A list of the most important threats affecting the sustainable development of the agro-industrial complex as a megacluster is presented in the paper: a strong dependence of agricultural sector efficiency on the areas of processing and trade, a high dependence of the agro-industrial complex on the market price condition, a high dependence of domestic agro-industrial production on the external food markets, etc. Critical analysis of literature on stability issues was carried out. It is determined that the existing definitions characterize the production process and its efficiency not significantly. This made it possible to clarify the existing interpretations and characterize stability as the ability of a production or business system to function stably for a long time, despite internal and external threats. Integral components of sustainable development are determined in relation to AIC as a cluster organization: production and economic development, social and economic development, territorial development and maintaining stability of the ecosystem. Own definition of sustainable development of the agro-industrial complex as a megacluster unit has been developed. An extended classification of forms and types of stability of the cluster arrangement of the AIC is proposed. Such systematization gives an objective idea of the multiplicity of stability issues and defines the AIC as a sophisticated megacluster system.

Application of Fuzzy Technique for Order-Preference by Similarity to Ideal Solution (FTOPSIS) to Prioritize Water Resource Development Economic Scenarios in Pishin Catchment

Water is a basic demand of sustainable development in most regions of the world. The non-uniform temporal and spatial distribution of water resources will lead to water shortage in arid and semi-arid areas. Pishin catchment is one of the most important catchments in South-East Iran. The basin had been faced with consecutive droughts in recent years. On the other hand, water resources development projects anticipated and necessary in this catchment. Hence, the need for a study to prioritize different scenarios and their effects on the catchment should be considered to overcome these dry periods. The main objective of the present study is to predict water development projects in the study area. Due to the multiplicity of projects and high cost of them, the concurrent execution priority implementation of these projects is considered as an important factor. Fuzzy multiple attribute decision making is a suitable method for comparison, selection and prioritization of the different options taking into account different criteria. Hence, in this study, the effects of the water development projects are predicted using Water Evaluation and Planning System (WEAP) model. The projects according to the economic criteria are evaluated and prioritized with Fuzzy TOPSIS. Six water development projects and criteria including five economic indexes are considered. Based on the results, according to the investigated indicators, increasing irrigation efficiency in agricultural sector and reducing evaporation from the reservoir scenarios have top priority.

Technical efficiency of the Russian agriculture

Based on the data envelopment analysis methodology applied in the cross-country context with a metafrontier approach and window analysis, the article provides a technical efficiency estimate of the Russian agriculture. The group of countries included in the study comprises the CIS, BRIC, EU, and OECD members. The time interval is 1992-2007. The research has revealed low efficiency of the Russian agriculture among the CIS members and a relatively large technology gap with respect to advanced economies, but which tends to decline. The estimates also indicate growth of the Russian agricultural sector efficiency within the CIS beyond the time interval of the research.

Exploring the changes of energy-related carbon intensity in China: an extended Divisia index decomposition

To gain a better understanding of the changes in carbon intensity of China, this study firstly adopted logarithmic mean Divisia index decomposition analysis to decompose the carbon intensity into three driving factors, including emission coefficient effect, energy intensity effect and industrial structure effect. Then, the analysis was furtherly conducted to study the contributions of four economic sectors to the percent change in carbon intensity through each influencing factor by attribution analysis. The results illustrated that the carbon intensity dropped by 46.21 % from 1996 to 2012 mainly caused by the decrease in energy intensity, of which the industrial sector, transportation sector and commercial & service sector were the dominant contributors. The emission coefficient effect and industrial structure effect were equally important in terms of increasing carbon intensity, which principally due to the industrial sector and commercial & service sector. In addition, the energy efficiency of agricultural sector should be furtherly improved, and it is imperative to optimize the energy mix and industrial structure of the industrial sector and commercial & service sector. Therefore, more differentiated policies are urgently required to be implemented in different economic sectors to mitigate the China’s carbon intensity.

Ūkių apskaitos duomenų tinklo naudojimas vertinant optimalų ūkininko ūkio dydį mikroekonomikos požiūriu

Benchmarking of the economic subjects—viz. enterprises, organizations, regions—usually involves assessment of the efficiency. Suchlike analyses are not only important in the private sector, but also in the public one for public agencies are usually funded by public funds and thus need to be effective. Indeed, the private (business) subjects are sometimes also operating under the environment requiring appropriate regulation based on benchmarking. This is the case for the agricultural sector which receives voluminous public support as direct payments and rural development measures. On the other hand, the efficiency of agricultural sector impacts the prices of agricultural products as well as factor markets. Therefore, it is important to measure the efficiency of agricultural sector as an outcome of the effectiveness of the agricultural policy. The scale efficiency constitutes one of the components of the gross technical efficiency.
 The latter measure is related to the farm size and farm structure in general. Furthermore, the optimal farm size is a key issue for the agricultural policy and thus is often influenced by the legal regulations. This paper aims at identifying the optimal scale size for Lithuanian family farms. The paper discusses the neoclassical methodology for analysis of the scale efficiency.
 The results indicate that the optimal farm size depends on the farming type. Nevertheless, the current maximum limit of land area (i. e. 500 ha) has not been exceeded by any farming type.

Mobile Solution for Improving Operational Efficiency in Agricultural Sector

India is the second populous country in the world with more than 70% of the population living in rural area, 60% of India’s 1.1 billion populations living off agriculture which contributes to 17% of the Indian economy. The main resource for the agriculture is timely and adequate supply of water and electricity. Nearly 20% of the farmers in India are dependent on electric water pumps for irrigation. However many states have a huge gap in demand and supply of electrical energy. The highly unreliable power supply with frequent power cuts has lowered the operational efficiency of farmers. In this paper, we have discussed an intelligent mobile based solution that has helped farmers to increase the operational efficiency. The methodology of the paper is based on case study where mobile solutions have been deployed which has resulted in benefits to all the stakeholders making it a sustainable deployment.

Mobile Solution for Improving Operational Efficiency in Agricultural Sector

India is the second populous country in the world with more than 70% of the population living in rural area, 60% of India’s 1.1 billion populations living off agriculture which contributes to 17% of the Indian economy. The main resource for the agriculture is timely and adequate supply of water and electricity. Nearly 20% of the farmers in India are dependent on electric water pumps for irrigation. However many states have a huge gap in demand and supply of electrical energy. The highly unreliable power supply with frequent power cuts has lowered the operational efficiency of farmers. In this paper, we have discussed an intelligent mobile based solution that has helped farmers to increase the operational efficiency. The methodology of the paper is based on case study where mobile solutions have been deployed which has resulted in benefits to all the stakeholders making it a sustainable deployment.