Agricultural Mechanization Level Research Articles

Response Mechanism and Evolution Trend of Carbon Effect in the Farmland Ecosystem of the Middle and Lower Reaches of the Yangtze River

The farmland system in the global terrestrial ecosystem has dual attributes as both a carbon source and a carbon sink, playing a crucial role in controlling carbon emissions and mitigating global warming. Using carbon source and sink accounting of farmland ecosystems, we applied methods such as standard deviation ellipse, Tapio decoupling theory, and Markov chain to analyze the spatiotemporal changes, response mechanisms, and evolutionary trends of regional carbon effects. The results indicated that from 2011 to 2021, the farmland ecosystem in the middle and lower reaches of the Yangtze River consistently acted as a carbon sink. However, the net carbon sink showed slight fluctuations and significant spatial differences. The migration range of the net carbon sink center in the farmland ecosystem of the middle and lower reaches of the Yangtze River was relatively small, ranging from 115.52 to 115.77° E and 30.14 to 30.27° N. The decomposition of the Tapio decoupling index between the net carbon sink of the farmland ecosystem and agricultural output value showed the order of effects on their coupling relationship as follows: agricultural mechanization level > agricultural mechanization efficiency > agricultural output value > planting scale. The probability of maintaining the original state of net carbon sink in various cities in the middle and lower reaches of the Yangtze River (over 77%) was much higher than the probability of transfer, making it difficult to achieve a leapfrog growth in net carbon sink. The net carbon sink at the city scale exhibits the Matthew effect and spatial spillover effect. The above research results clarify the spatiotemporal changes in carbon effects in agricultural production at multiple levels, including city, province, and region. They also provide a theoretical basis for formulating differentiated regional emission reduction and sink enhancement strategies in the middle and lower reaches of the Yangtze River, promoting the rapid development of low-carbon agriculture in China.

Study on Influencing Factors of Grain Supply Chain Resilience Based on DEMATEL-ISM Method

The essential requirement for the resilience and safety of the food industry supply chain is to achieve independent, controllable, safe, efficient, and sustainable development. Currently, and for a significant period in the future, the food industry supply chain faces several risks, primarily due to increased uncertainties. These risks manifest as the need for optimization in the layout of the food industry, prominent structural shortages, and a lack of full autonomy and control in key links of the industry chain. Such risks can potentially evolve into critical factors that restrict the resilience and security of the food industry supply chain. To effectively address these risks, this paper identifies 12 influencing factors based on four key capabilities of the food supply chain: forecasting ability, response-ability, adaptation ability, and recovery ability. An evaluation index system for the resilience of the food supply chain is constructed, integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methodologies. Analysis of the interactions between these factors reveals that three factors, including supply chain visibility, are fundamental, seven factors, including the level of agricultural mechanization, are intermediate, and dynamic logistics and flexibility are direct factors. Based on these conclusions, this paper proposes several targeted recommendations to enhance the development of the food supply chain. These recommendations aim to improve the supply chain's resilience and ability to withstand potential risks.

Inequality of rural residents’ income in China since the targeted poverty alleviation strategy: New trends, causes, and policy implications

Poverty and income inequality are problems faced by many countries including China. Since the implementation of Targeted Poverty Alleviation (TPA), absolute poverty has been eradicated, meanwhile, Chinese rural residents' income and inequality have experienced unprecedented new dynamics, but still, very few studies have focused on them. Hence, we attempt to examine the new trends in Chinese farmers' income inequality and to understand its causes during this period. We observe that China's urban-rural income ratio has been shrinking and the urban-rural inequality has been decreasing from 2014 to 2021. The reduction in the Theil index indicates a decrease in the regional inequality of farmers' income as well, and the decline in inter-regional inequality among eight economic zones contributes about 80% to increased equality. These new trends are caused by the fact that, with the TPA, the incomes of rural residents especially that in destitute areas, grew faster than that of urban residents and farmers in prosperous areas. The higher share of non-agricultural industry and agricultural mechanization level have significant positive impact on regional equality of farmers' income, while urban-rural dual structure has significant negative inhibitory effects. The lowest farmers' income and the highest inequality in the Northwest, and the slowest growth in the Northeast deserve more attention in rural Revitalization. From these findings, we propose four policy implications that would be applied to improve Chinese farmers' income equality, govern relative poverty, and achieve common prosperity in the post-poverty era.

How does improving agricultural mechanization affect the green development of agriculture? Evidence from China

Over the past two decades, China has actively pursued a green, low-carbon economy in response to climate change. Amidst rapid economic development, China's green total factor productivity—a key metric reflecting the nation's green development—has notably risen. As a developing country with a population exceeding 1.4 billion, agriculture plays a key role in China. China has persistently strived to comprehensively promote the scale and scope of agricultural mechanization, recognizing it as a crucial gauge to enhance agricultural productivity, thereby facilitating agricultural modernization and ensuring food security. However, can elevating the agricultural mechanization level improve China's green development within the agricultural sector? Specifically, how does agricultural mechanization (AM) affect agricultural green total factor productivity (AGTFP)? To address these questions, we assess the effects of agricultural mechanization on agricultural green total factor productivity and examine its channels using panel data from 30 provinces in China spanning from 2000 to 2021. Additionally, we investigate the heterogeneous effects under different levels of economic development, agricultural economic development, environmental regulation intensity, and agricultural technology. The results indicate that: First, the development of agricultural mechanization promotes the agricultural green total factor productivity. Second, channel analysis indicates that agricultural mechanization can bolster agricultural green total factor productivity through three channels: enhancing agricultural management level, improving agricultural factor efficiency, and fostering diversification of agricultural industrial structure. Third, heterogeneous analysis suggests that agricultural mechanization exerts a more pronounced impact on agricultural green total factor productivity in provinces characterized by lower levels of economic development, more backward agricultural economic development, higher environmental regulation intensity, and more advanced agricultural technology. This article is anticipated to furnish empirical evidence from China for developing nations seeking to foster agricultural green sustainable development through the widespread adoption of agricultural mechanization, thereby contributing significantly to global efforts to mitigate climate change.

Rural Industrial Integration and New Urbanization in China: Coupling Coordination, Spatial–Temporal Differentiation, and Driving Factors

Understanding the coupling coordination status between rural industrial integration (RII) and new urbanization (NU) is critical for the Chinese government to optimize policies that promote the synergetic and sustainable development of RII and NU. Based on constructing evaluation index systems, this paper uses the entropy value method, coupling coordination degree model, exploratory spatial analysis method, gravity center model, and geographical detector model to reveal the characteristics of the spatial–temporal differentiation of the coupling coordination and its driving factors in China. The results show that: (1) The regional differences in the coupling coordination degree between RII and NU are obvious, and the coupling coordination degree of China’s three economic regions are all in an increasing trend, but the mean values in the central and western regions are always below the national average. (2) The coupling coordination degree has significant spatial agglomeration characteristics, but the regional differences are gradually decreasing. The whole country is still dominated by the low–low agglomeration, and the provinces with the high–high agglomeration are mainly located in the eastern region. (3) The gravity center of the coupling coordination degree has moved in both the east–west and north–south directions from 2011 to 2021, but the movement trend in the north–south direction is more obvious. (4) The economic development level, industrial structure, transportation conditions, government support capacity, financial support level, and agricultural mechanization level are important factors driving the spatial–temporal variation, and their interactions will enhance the differentiation. The results can provide a theoretical basis and decision-making reference for relevant government departments in China to promote the sustainable development of RII and NU.

Kahramanmaraş İlinde Tarımsal Mekanizasyon Düzeyinin İlçelere Göre Poisson Regresyon ile Belirlenmesi

In this study, agricultural mechanization level indicators of the districts of Kahramanmaraş between the years 2012-2021 were calculated. A model has been established for this. While the dependent variable in the model is the agricultural areas planted in the districts according to the years, the independent variables are the number of tractors in the districts according to the years and other determined tools, equipment and machines. Poisson regression test was used, there was 25.022 chi-square probability relationship between the planted agricultural areas in Kahramanmaraş districts between 2012 and 2021, with the number of tractors in the districts and other determined equipment by years. At the level of agricultural mechanization, it was determined that there was a 3.32 decrease in the average number of tractors per 1000 hectares of land in Kahramanmaraş districts between 2012 and 2021, and a decrease of 12.45 in the number of specific equipment per tractor over the years. Among this decrease, it was thought that reasons such as climate change, input costs and job change were among the main reasons for leaving agriculture. In the comparison made from 2012 to 2021, the number of tractors in all districts increased by 54.18%, while the number of tractor equipment was also observed. An increase of 46.11% was observed. In addition, as a result of the trend analysis value applied, it was concluded that the average absolute percentage errors in the districts were 4.10443, the average number of tractors per 1000 hectares by years, and the number of specific equipment per tractor in the districts according to the years was 1.96718, which is a good estimation.

Research on the influence factors of sustainable development of plateau characteristic agriculture based on DEMATEL and AISM combined model.

Under the background of the continuous progress of China's agricultural reform, the development of characteristic agriculture is an important field of agricultural development in the country and even the world. Yunnan has unique advantages in geography, location, climate, and human resources, and has unique conditions for the development of agriculture with plateau characteristic. However, the sustainable development of agriculture with plateau characteristic is affected and restricted by many factors. How to promote the sustainable development of agriculture with plateau characteristic is an important research topic, and it is also the main purpose of this study. Therefore, through literature analysis and investigation, this study studies the advantages and disadvantages, development status, main problems, countermeasures and suggestions, macro development direction, and theoretical research methods of characteristic agriculture in the Yunnan plateau. This paper analyzes the advantages and disadvantages of the Decision-making Trial and Evaluation Laboratory (DEMATEL) and the Adversarial Interpretation Structure Modeling Method (AISM) and proposes to combine the two models to make up for each other and improve the accuracy of model analysis. On this basis, a set of identification and evaluation systems of factors affecting the sustainable development of agriculture with plateau characteristic is established, which can comprehensively and accurately identify and evaluate various influencing factors, and provide a scientific basis for the sustainable development of agriculture with plateau characteristic. Finally, combined with the relevant statistical data of Yunnan Province from 2009 to 2020 and many results calculated by the model, the factors affecting the sustainable development of agriculture with plateau characteristic were comprehensively analyzed. The results show that transportation, environment, and insurance support factors are the root factors that affect the sustainable development of agriculture with plateau characteristic, while the regional economy, scientific and technological support, and the development of agricultural enterprises are of high importance. Financial support, the level of agricultural mechanization, the quality of labor, and other factors can not be ignored. Finally, according to the results of the analysis, the corresponding policy recommendations are put forward to provide a reference for the sustainable development of plateau characteristic agriculture in Yunnan Province.

A framework for quantification and integration of green development of cultivated land in China: From the perspective of adaptability‐vitality‐resistance

AbstractExploring the green development of cultivated land (GDCL) and solving the problem of “high consumption and high pollution” caused by the traditional model are of great significance for achieving sustainable use of cultivated land and green agricultural growth. However, the existing consensus on action lacks theoretical support and quantitative analysis. To this end, the objective of this study was to develop a new multidimensional framework considering as an integrated capacity to adaptability‐vitality‐resistance (A‐V‐R) assess GDCL according to the essential requirement of green development. The analytical framework and evaluation system proposed in this study are expected to provide empirical support for the green transition of cultivated land use in China or worldwide. This study determines spatiotemporal differentiation and influencing mechanism of GDCL in China from 2000 to 2020. The results demonstrated that the GDCL level of China was low and characterized by a W‐shaped fluctuation. The regional difference in GDCL is greater than that within the regions and the evolution of different types of regions showed significant path dependence and spatiotemporal inertia. The reason behind this phenomenon is that agricultural technology and socioeconomic development factors such as agricultural mechanization level, urban–rural income equity index and extensively influenced GDCL in different regions. The interaction among driving factors forms a complex multi‐resultant force to construct a comprehensive action mechanism at the GDCL level driven by demand, economy, technology, and ecology. Therefore, this study suggests coordinating the relationship between technological progress, technological diffusion, agricultural total factor productivity, and the GDCL path, in order to effectively reduce the internal and external contradictions of GDCL.

Impact of relaxing internal-migration restrictions on agricultural TFP of rural households: evidence from China

ABSTRACT In this paper, we study how a significant relaxation of internal migration restrictions affects the agricultural total factor productivity of rural households, taking advantage of the 2014 Hukou reform in China. This reform completely removed the migration restrictions for cities with an urban population of less than 0.5 million (towns and small cities) but left the migration restrictions in megacities unchanged. We find that the reform has significantly contributed to the off-farm transfer of rural labour and increased the agricultural TFP of rural households. Further mechanistic analysis shows that the reform increased the level of agricultural mechanization of rural households and facilitated the subcontracting of land by low productivity farmers.

Using and Molding of Agricultural Machinery Safety Management Evaluation based on Fuzzy Analytic Hierarchy Process

As the level of agricultural mechanization in China continues to improve, the issue of agricultural machinery safety management is becoming increasingly prominent. Strengthening the safety management of agricultural machinery is of great significance for safeguarding the safety of farmers' life and property and the healthy development of agricultural mechanization. This paper combines the hierarchical analysis method (AHP) and the fuzzy evaluation method, and establishes the evaluation index system of agricultural machinery safety management by selecting 18 indexes from five aspects: industry management, basic situation of drivers, management of agricultural machinery, insurance coverage of agricultural machinery, and operating environment. The fuzzy comprehensive evaluation method was used to establish the evaluation model of agricultural machinery safety management, and the evaluation method was applied to Liaoning Province. The results show that the safety management level of agricultural machinery in Liaoning Province is excellent.

Index and Sustainability Status of Agricultural Mechanization for Paddy Field in Indonesia

The use of agricultural machinery is one of the important factors in increasing agricultural production. A quantitative assessment of the agricultural mechanization index and its impact on agricultural production is needed in planning the development of agricultural mechanization nationally. This study aims to determine the value of the agricultural mechanization index which consists of the degree, level, and capacity of agricultural mechanization for tools and agricultural machinery for pre-harvest rice (2-wheel tractor, 4-wheel tractor, water pump, and rice transplanter). This research was conducted in several stages, namely collecting data, observing the working capacity of 3 units of machinery for each type of machinery, processing data and making agricultural mechanization index maps. Based on the results of the study, it was found that the average value of the degree of agricultural mechanization for 2-wheel tractors, 4-wheel tractors, water pumps and rice transplanters was 56.68%, 55.13%, 10.55 % and 13.94%. The average value of mechanization level in Indonesia is 0.45 hp/ha and the average value of mechanization capacity for rice pre-harvest activities in Indonesia is 1.28 kW hour/ha. In addition, based on the results of the classification of mechanization level, cropping index and rice productivity, it can be seen that the provinces of East Java, Central Java, West Java, Banten, DI Yogyakarta and Aceh are provinces that are recommended to increase the number of agricultural machinery, especially 2-wheel tractors, 4-wheel tractors. water pump and rice transplanter.

Rural digital credit and residential energy consumption: Evidence from the agricultural production perspective

Lack of capital hindered the development of agricultural production and the residential energy consumption transition in rural areas, but, with the continuous advancement of digital finance technologies, rural digital credit eased the liquidity constraint of agricultural production, which influenced residential energy consumption. However, few studies explored the relationship between rural digital credit and residential energy consumption. Hence, the instrumental variable (IV) method, the mediation effect model and the survey data that covered 295 effective samples were used to analyze the impact of rural digital credit on residential energy consumption from the agricultural production perspective in this study. The results indicated that rural digital credit resulted in a significant decline of the consumption of traditional energy products, but impacts of rural digital credit on electricity consumption and the new-style energy products consumption were not significant. Further, rural digital credit reduced traditional energy products consumption via boosting the level of agricultural mechanization and the adoption of precision fertilizer applying technique. This paper was conducive to not only developing the green credit markets in rural areas, but also enhancing the residential energy consumption transition and sustainable development.

The rebound effect of energy consumption and its determinants in China's agricultural production

With the facilitation of agricultural modernization, China's agricultural energy consumption continues to rise. This paper empirically tests the agricultural energy rebound effect and its influencing factors in China during 1999–2020. It is believed that the improvement of energy efficiency has not led to the expected energy-saving effect in agriculture due to the "Jevons paradox" of energy efficiency and energy consumption. The average energy efficiency of China's agricultural energy consumption was 0.446, and the average energy rebound effect was 68.9 %. The level of agricultural mechanization, the effective irrigated area of farmland and agricultural investment have a positive impact on the rebound effect of agricultural energy, and the direct effects are 0.062, 0.008 and 0.064, respectively, while agricultural labor force and energy price have a negative impact on the rebound effect of agricultural energy. In particular, technology spillover and scale spillover led by agricultural technology progress have strong negative space spillover effect. As it is argued, 1 % of agricultural technology progress can reduce 3.5 % of agricultural energy rebound effect in surrounding areas. In order to reduce the energy rebound effect, it is suggested to increase the subsidies to agricultural labors and rationally formulate regional differentiated energy regulation policies.

Can development of large scale agricultural business entities improve agricultural total factor productivity in China?: an empirical analysis

Large scale agricultural business entities (hereinafter referred to as “the large scale entities”) are newly sprouted in the process of China’s agricultural transformation from traditional production to modern mode, while the improvement of agricultural total factor productivity is an important driving force to realize agricultural transformation in China. Therefore, it is of great significance to explore whether the former has a promoting effect on the latter. First of all, the effective improvement of agricultural total factor productivity by the large scale entity development is analyzed from the two aspects of scale effect and technology utilization effect, and the effect mechanism is discussed in depth in this paper. Secondly, empirical test was carried out by using the panel data of prefecture-level cities from 2015 to 2020. The benchmark regression results show that the development of large scale entities can significantly improve agricultural total factor productivity. The mechanism test results indicate that the development of large scale entities improves the agricultural total factor productivity by raising the agricultural mechanization level. The results of heterogeneity analysis show that the difference between large scale entities would affect the benchmarking results. Therefore, it is believed through the study as discussed in this paper that devoting greater effort to support the development of large scale entities is an important measure to improve agricultural total factor productivity and promote China’s agricultural transformation, but it is necessary to act according to local conditions based on the difference of entity types in the process.

Achieving coordinated development of multi-functional urban agriculture in Xiamen, China

Urban agriculture's multi-functional coordinated development is an important approach for achieving sustainable development in urban areas. This study developed a comprehensive theoretical framework for evaluating, diagnosing, and optimizing multi-functional urban agriculture by integrating a TOPSIS evaluation model with the coordination degree model and the obstacle degree model. The framework was applied in Xiamen, China to identify the obstacles that impede its coordinated development. Subsequently, four optimized modes for the coordinated development of urban agriculture were proposed. Results showed that: (1) Urban agriculture in Xiamen exhibits the characteristics of "sound social function, moderate economic function, and poor ecological function". (2) The main obstacles affecting the coordination of urban agriculture's multi-function in Xiamen are the average grain crop output, level of agricultural mechanization, arable land carrying capacity, and amount of carbon sequestration. (3) Four optimized development modes for urban agriculture in Xiamen are identified. Through formulating customized strategies that align with the distinctive optimization development mode of each district can promote the sustainable development of urban agriculture in Xiamen. In conclusion, this framework provides a valuable tool for policymakers to explore effective strategies for promoting the multi-functional development of urban agriculture in China and can be expanded to other highly urbanized regions.

Analysis of the Level of Agricultural Mechanization in Eritrea Based on USDA Data Sources

Mechanical power is one of the main drivers of agricultural production systems and a key parameter in assessing the level of agricultural mechanization (LAM). The LAM has so far been evaluated based on the amount of mechanical power available per unit area. However, as African nations have gained autonomy over the past several years, it is difficult to directly monitor and compare each country's progress in the existing LAM assessment. Thus, determining LAM progress in Eritrea and comparing it to that of other African countries is the main point of departure, on which this study places a prior emphasis. For this purpose, data is filtered from the datasheet made available online by the USDA. On a comparative basis, Eritrea is ahead of the other 33 African countries with an average annual LAM progress of 0.0013 hp/ha/year. Eritrea ranks 12th in the SSA and 3rd in the EA, indicating relatively good and promising progress. Based on the data analyzed, around 10% of the countries’ rates of advancement in the level of agricultural mechanization are less than their rates of decline; as a result, the rate (AAP (LAM)) is showing a negative value. It is clear, however, that the AAP (LAM) of Eritrea is ten times slower than that of the country ranked first (Zimbabwe).

The impact of digital financial inclusion and urbanization on agricultural mechanization: Evidence from counties of China.

This paper expounds the theoretical logic among digital inclusive finance, urbanization, and agricultural mechanization level, puts forward the research hypothesis, and then selects the county unbalanced panel data of 1309 counties in China from 2014 to 2020 based on the two-way fixed model with standard error clustering to county level and mediating effect model for empirical data regression analysis. Through baseline regression analysis, mediation effect analysis, and heterogeneity analysis, the findings of this paper are as follows. First, digital financial inclusion has a significant positive effect on the growth of agricultural mechanization. Second, digital inclusive finance at the county level can also indirectly affect the growth of agricultural mechanization through urbanization. That is, agricultural mechanization has an intermediary effect between the financial agglomeration at the county level and the growth of farmers' income. Third, the impact of county-level digital financial inclusion on the growth of agricultural mechanization level is significantly heterogeneous, and the promoting effect is significant in areas with balanced grain production, national-level poor county or contiguous areas of dire poverty, and areas with a good foundation for digital financial inclusion. By analyzing digital inclusive finance, urbanization, and agricultural mechanization, this paper proposes targeted policy recommendations. First, the government can promote agricultural mechanization by developing digital financial inclusion. Second, the government should guide and accelerate the process of digital financial inclusion, promoting urbanization thereby amplifying the positive impact of digital financial inclusion on agricultural mechanization. Third, given the heterogeneity of the impact of digital financial inclusion on agricultural mechanization, local development should focus on developing different dimensions of digital financial inclusion according to specific conditions.

The current state of technological support for vegetable crops production in the Russian Federation

The main limiting factor in the development of the vegetable growing industry is the low technical level of vegetable cultivation. It should be noted that many works in domestic breeding, as well as in seed production of vegetable crops, are carried out manually. The decrease in the share of Russian varieties in the market of seed material of vegetable crops is largely due to the fact that the technological level and technical equipment of most originating institutions of Russian varieties are simply not comparable with the level of modern Western European breeding and seed production centers and companies that seek to increase the supply of seed material to the Russian market. One of the significant factors in increasing the efficiency of vegetable production is the use of highly efficient agricultural machinery and equipment. At the moment, there are no machines for performing the main operations of cultivating vegetable products in Russia, and the available agricultural machines for vegetable producers are on the verge of physical wear and tear and have long ago exhausted their depreciation resource. The existing foreign analogues presented on the Russian market do not fully meet the agrotechnical requirements imposed by Russian farmers on foreign-made machines. Based on the analysis of the technical support of the vegetable growing industry in the Russian Federation, the need for commodity producers in modern hightech complexes of machines for the production of vegetable crops is economically determined based on the total sown area of vegetable crops. The results of the statistical studies carried out made it possible to assess the current state of agricultural engineering for the production of the required number of machines for vegetable growing. The increase in sown (planting) areas and the expected increase in the production of the main types of crop products against the background of a decrease in the availability of agricultural machinery contributes to an increase in the load per unit of equipment and creates risks of a decrease in the level of agricultural mechanization. Currently, low volumes of domestic seed production are associated, among other things, with the low level of technical equipment of breeding and seed-growing organizations with specialized machines and equipment.

Assessing Rural Production Space Quality and Influencing Factors in Typical Grain-Producing Areas of Northeastern China

Rural production spaces are important sites for agricultural activities, and high-quality rural production space is of great significance for guaranteeing food security and revitalizing rural areas. This study used Songnen Plain, a typical grain-producing area in Northeast China, as the study area and analyzed the spatial and temporal patterns of rural production space quality and its influencing factors from 2005 to 2020 using the rural production space quality assessment model, spatial autocorrelation analysis, and Geodetector. The results showed that: (1) The rural production space quality in the Songnen Plain has undergone a general process of change with 2015 as the node, showing an overall increase followed by a small decrease in some counties. Input–output efficiency exhibited a pattern with a high center and low perimeter, and rural production space quality exhibited a high in the south and low in the north pattern for all the years. (2) The spatial distribution of rural production quality in the Songnen Plain is highly correlated, and H-H and L-L zones had obvious spatial clustering characteristics. There were slight variations in spatial correlations of quality in each year, but the overall spatial quality exhibited a stable pattern of high in the south and low in the north. (3) The purchasing power for means of production, the level of infrastructure, and the level of agricultural mechanization were the main factors affecting the rural production space quality in the Songnen Plain, and the influence of population contraction and urbanization was gradually increasing. The results of the study can provide support for the sustainable development of rural production space and rural revitalization in Northeast China.

Agricultural Mechanization Level and Projection Estimation of Soil Tillage Equipment’s, Drills -Fertilizer Distributors of TR22 Region

In this study, the change in agricultural mechanization level of Balıkesir and Çanakkale provinces (TR22 Region) for the last 10 years (2013-2022) was determined, and the projection estimation of soil tillage equipment, drills and fertilizer distributors was determined. The material of the study consisted of tillage equipment, drills-fertilizing machines, two-axle tractors, and total cultivated area data obtained from the Turkish Statistical Institute (TUIK). For Balıkesir and Çanakkale provinces, the level of agricultural mechanization tended to increase according to the measured parameters between the years 2013-2022, and increases were observed in the number of soil tillage equipment and drills-fertilizer distributors. According to the projection coefficient values, tractor power values are generally projected to increase between 2023-2032 in Balıkesir and Çanakkale provinces. While the number of tractors increased in both provinces, the tractor power per unit cultivated area (kW ha-1) and the number of tractors per 1000 hectares (tractor 1000 ha-1) increased over the years, while the cultivated area per unit tractor (ha tractor-1) also decreased in value. These findings show that there is an improvement in agricultural mechanization level in Balıkesir and Çanakkale provinces.