Study on the Influencing Factors of Farmers’ Adoption of Conservation Tillage Technology in Black Soil Region in China: A Logistic-ISM Model Approach

Xue

2022

IJERPH

Along with the increasing prominence of environmental risks such as soil surface source pollution and declining quality grade of arable land, the issues of how to address irrational fertilizer application and enhance the safety of agricultural products have attracted widespread attention. In this context, clarifying the main factors affecting farmers’ use of soil testing and formulated fertilization technology (STFFT) can further improve the technology adoption rate and fertilizer utilization efficiency, promote standardized agricultural production and maintain the health and stability of soil ecology in black soil areas. This is of great significance to the construction of green agriculture, national dietary health and national food security. This study builds an “external environmental stimuli-perceived characteristics-adoption behavior” theoretical framework to investigate the decision-making and the dynamic influence mechanisms of farmers’ adoption behavior of STFFT. Based on farmer survey data, the logistic-ISM model has been applied. The main findings are as follows. First, five types of influencing factors, namely individual characteristics, family characteristics, business characteristics, cognitive characteristics and external environmental characteristics, had significant “push” effects on farmers’ STFFT adoption behavior. Among them, planting scale and technical training are the key factors influencing farmers’ adoption of scientific fertilizer application technology. Second, both farmers’ perceived ease of use and perceived usefulness play a significant role in farmers’ decision-making process, and the easier farmers perceive STFFT to be to master and the greater the benefits it brings, the more pronounced the tendency to adopt the technology, all other influencing conditions being equal. Third, the main influencing factors of farmers’ STFFT adoption behavior are intrinsically related and divided into four categories based on the magnitude of influence: deep-rooted, medium indirect, shallow indirect and superficial direct. In order to reduce further degradation of black soil caused by farmers’ irrational production habits and to improve resource utilization efficiency, this study recommends the government to further regulate the land transfer market, strengthen the propagation of soil-conservation-type technologies in black soil areas, expand the breadth of agricultural technology training and enhance farmers’ understanding and trust in STFFT. Thus, the maintenance of soil ecosystem in black soil areas, effective guarantee of food security and sustainable development of agriculture can be achieved.

Section: Methodsmentioning

confidence: 99%

What Influences Farmers’ Adoption of Soil Testing and Formulated Fertilization Technology in Black Soil Areas? An Empirical Analysis Based on Logistic-ISM Model

Xue

2022

IJERPH

“…Northeast China is one of the four largest black soil areas in the world and has included the protection of black soil in legislation that is dedicated to the protection of black soil, construction of agricultural infrastructure, improvement of black land quality, restoration and improvement of the black land, and prohibition of poaching and indiscriminate excavation [62]. Heilongjiang and Jilin provinces in northeast China have issued several policy initiatives related to black soil conservation and black soil protection master plans in response to national and global soil conservation programs [62,63].…”

Section: Impact Of Wind-driven Organic Carbon Loss From Farmland On C...mentioning

confidence: 99%

Estimates of Dust Emissions and Organic Carbon Losses Induced by Wind Erosion in Farmland Worldwide from 2017 to 2021

Zhao

et al. 2023

Agriculture

Wind erosion can cause high dust emissions from agricultural land and can lead to a significant loss of carbon and nutrients from the soil. The carbon balance of farmland soil is an integral part of the carbon cycle, especially under the current drive to develop carbon-neutral practices. However, the amount of global carbon lost due to the wind erosion of farmland is unknown. In this study, global farmland dust emissions were estimated from a dust emission inventory (0.1° × 0.1°, daily) built using the improved Community Multiscale Air Quality Modeling System–FENGSHA (CMAQ-FENGSHA), and global farmland organic carbon losses were estimated by combining this with global soil organic carbon concentration data. The average global annual dust emissions from agricultural land from 2017 to 2021 were 1.75 × 109 g/s. Global dust emissions from agricultural land are concentrated in the UK, Ukraine, and Russia in Europe; in southern Canada and the central US in North America; in the area around Buenos Aires, the capital of Argentina, in South America; and in northeast China in Asia. The global average annual organic carbon loss from agricultural land was 2970 Gg for 2017–2021. The spatial distribution of emissions is roughly consistent with that of dust emissions, which are mainly concentrated in the world’s four major black soil regions. These estimates of dust and organic carbon losses from agricultural land are essential references that can inform the global responses to the carbon cycle, dust emissions, and black soil conservation.

“…Government subsidies and policy regulation serve as the two main incentives adopted by governments. Subsidy policies provide incentives for farmers to shift to planting segments that require new technologies more 39,40 , while institutional constraints discourage farmer adoption behaviour 15 . The government also motivates farmers through agricultural technology training [41][42] , advocacy and guidance, and monitoring and control 43 .…”

Section: Introductionmentioning

confidence: 99%

Study on the Influence Mechanism of Adoption of Smart Agriculture Technology Behavior

Chen

2023

Preprint

Smart agricultural (SA) technology has become an inevitable trend in the modernisation of China's agriculture and a realistic demand for the transformation and upgrading of traditional agriculture. Based on microscopic research data, a structural equation model (SEM) is constructed using deconstructive planning behaviour theory (DPBT) as the analytical framework to empirically analyse the factors and degrees of influence on cotton farmers' adoption of SA technologies. In-depth interviews were then combined to further reveal the mechanisms influencing cotton farmers' adoption of SA technology. The results show that: (1) the risk of the technology itself has a dampening effect on willingness, but cotton farmers value the positive role played by perceived usefulness more. (2) superior influences such as trial field demonstrations and government publicity have a greater impact on willingness to adopt SA technologies than the group effect of peer influence. (3) factors such as self-efficacy and information channels have an impact on willingness and behaviour to adopt. (4) Willingness influences technology adoption behaviour through mediating effects. (5) Policy and technology satisfaction have a positive moderating role in the occurrence of willingness and adoption behaviour.