Farmland Quality Research Articles

Soil Nutrient Estimation and Mapping in Farmland Based on UAV Imaging Spectrometry.

Soil nutrient is one of the most important properties for improving farmland quality and product. Imaging spectrometry has the potential for rapid acquisition and real-time monitoring of soil characteristics. This study aims to explore the preprocessing and modeling methods of hyperspectral images obtained from an unmanned aerial vehicle (UAV) platform for estimating the soil organic matter (SOM) and soil total nitrogen (STN) in farmland. The results showed that: (1) Multiplicative Scattering Correction (MSC) performed better in reducing image scattering noise than Standard Normal Variate (SNV) transformation or spectral derivatives, and it yielded a result with higher correlation and lower signal-to-noise ratio; (2) The proposed feature selection method combining Successive Projections Algorithm (SPA) and Competitive Adaptive Reweighted Sampling algorithm (CARS), could provide selective preference for hyperspectral bands. Exploiting this method, 24 and 22 feature bands were selected for SOM and STN estimation, respectively; (3) The particle swarm optimization (PSO) algorithm was employed to obtain optimized input weights and bias values of the extreme learning machine (ELM) model for more accurate prediction of SOM and STN. The improved PSO-ELM model based on the selected preference bands achieved higher prediction accuracy (R2 of 0.73 and RPD of 1.91 for SOM, R2 of 0.63, and RPD of 1.53 for STN) than support vector machine (SVM), partial least squares regression (PLSR), and the ELM model. This study provides an important guideline for monitoring soil nutrient for precision agriculture with imaging spectrometry.

Study on the Farmland Evaluation Index System through the Construction of Mathematical Models and Big Data

Basic farmland is the essence of cultivated land. To completely solve China’s food security problems and achieve stable growth of agricultural production in China, it is one of the most effective ways to build high-standard basic farmland. Therefore, this paper evaluates the high standard basic farmland. This paper evaluates the natural quality of basic farmland through the construction of mathematical models. The total cultivated land area in the hilly area of Faku County is 153061.02 hm2, while the natural quality score of cultivated land in the hilly area of Faku County is between 51 and 86. Among the equal-valued intervals, the maximum cultivated land area between ≥60-70 is 129110.25 hm2, accounting for 84.35% of the total cultivated land in the hilly area of the county, followed by the area between ≥70-80, which is 9069.44 hm2. The total area of cultivated land in the hilly area of the county is 5.92%, followed by the interval of ≥ 80 points, <60 interval, the area is 8095.61 hm2, and the ratio of 6787.72 hm2 accounts for 5.29% and 4.43% of the total cultivated land in the hilly area of the county. In general, the natural quality of cultivated land in the hilly area of Faku County is moderate.

Factors influencing farmers’ adoption of eco-friendly fertilization technology in grain production: An integrated spatial–econometric analysis in China

Encouraging more farmers to adopt eco-friendly fertilization technology is essential for achieving sustainable grain production. To systematically explore the factors influencing farmers' adoption of such technology, based on a logistic regression model and three mutually complementary spatial analysis models, our study proposes a spatial-econometric analytical framework. Using data from household surveys, farmland quality investigations, remote-sensing images, and a digital elevation model, we test our study framework in 30 neighboring villages in Taojiang County, China. The results indicate that major socioeconomic influential factors include the age and education level of the household head, farm size, and degree of farmland fragmentation; geographic influential factors involve landform characteristics, drainage capacity, irrigation capacity, and topsoil thickness. In addition, the type of technology promoter and the farmer's perceived usefulness of the technology play important roles affecting farmers' technology adoption willingness. To increase the probability of technology adoption, more energy should be spent on relatively younger and better-educated farmers and farmers who occupy a larger cultivation area. Non-adopter-dominated areas should also be targeted during the technology promotion process. Further, local policymakers should consider strong measures that encourage adopters to become active technology promoters.

Solar power promotion plans, energy market liberalization, and farmland prices – Empirical evidence from Taiwan

Since solar panels are typically built on the roofs of residential housing or large factories, most of the existing studies focus on the relationship between solar panels and residential housing prices. Research on the effects of solar panel policies and farmland prices is rare. This paper provides the first empirical evaluation of solar power promotion plans on farmland prices before and after the liberalization of the energy market using the unique case of Taiwan. Using administrative data on farmland market transactions, we estimate the difference-in-differences model to identify the causal effect of solar power promotion plans on farmland prices. The solar power promotion plan lowers farmland prices by 15.8% and 36.6% before and after the liberalization of the energy market. Moreover, these effects vary based on farmland quality. The negative effect of the solar power promotion plan on farmland prices is more pronounced for low-quality farmland during the post-energy market liberalization period.

Does the stability of farmland rental contract & conservation tillage adoption improve family welfare? Empirical insights from Zhangye, China

China’s farmland rental markets have brought new strategies to improve farmland quality by adopting conservation tillage (CT) and improving family welfare. In the existing literature, little attention is given to this phenomenon. Hence, the current research is attempted to explore the family welfare outcome of transferees adopting CT compared with traditional tillage (TT). Data from 652 households have been collected from Zhangye, China, to meet the study objective by employing the endogenous switching regression model (ESR). The results showed that farmland rental contract positively and significantly influences transferees’ decision to adopt CT and improve family welfare. The findings further endorsed inverted U-shaped relationships with the optimal turning point of 6.5 and 8 years of the contract period. More importantly, considering the sample selection and endogenous issues of the transferee’s decision to adopt CT, the findings further showed that if the transferee adopting CT switch to adopt TT, the welfare level of the family will be decline by 0.1985. And if the transferee adopting TT switch to adopt CT, then it is likely that the welfare level of the family will be rise by 0.1785. The empirical findings of the current study provide guidelines for policy makers to stabilize farmland rental contracts and encourage farmers to opt CT application for the family's overall welfare.

Appropriate Management Scale of Farmland and Regional Differences under Different Objectives in Shaanxi Province, China

Agricultural development is facing two problems: insufficient grain production and low profit of farmers. There is a contradiction between the government’s goal of increasing production and the farmer’s goal of increasing profit. Exploring the appropriate management scale of farmland under different objectives is of great significance to alleviate the conflict of interests between the government and farmers. In this study the Cobb-Douglas production function model was used to measure the appropriate management scale of farmland under different objectives in Shaanxi Province and analyze the regional differences. Under the two objectives, the appropriate management scale of the Loess Plateau was the largest in the three regions, followed by Qinba Mountains and Guanzhong Plain. Farmland area and quality were the main influencing factors for the appropriate management scale of farmland under the goal of maximizing the farmland yield, while the nonagricultural employment rate and farmland transfer rate were the main influencing factors under the goal of maximizing farmers’ profits. It is easy for Shaanxi Province to increase farmers’ profits, but more land needed to be transferred to increase farmland yield. These results suggest that in order to balance the goal of increasing yield and profit, the transfer of rural surplus labor should be promoted, and the nonagricultural employment rate should be improved. In Loess Plateau, restoring the ecological environment and enhancing the farmland quality. In Guanzhong Plain, avoiding urban land encroachment on farmland. In Qinba Mountains, developing farming techniques and moderately increasing the intensity of farmland exploit.

Heavy metals in soil-vegetable system around E-waste site and the health risk assessment.

Investigating the farmland quality around electronic waste (E-waste) dismantling site and taking positive measures to ensure local food safety are urgent. Eleven types of vegetables (n=184) and their corresponding soils were collected from vegetable fields in a city with famous historical e-waste activities in China. Nemerow integrated pollution indices analysis revealed that local vegetable fields suffered from heavy metal pollution to a certain extent, especially with regards to Cd, Cu, and Zn. The human health risk models provided by USEPA have been used to evaluate the non-carcinogenic and carcinogenic risks associated with the consumption of vegetables by local residents. Results indicated that both adults and children were suffering potential health risks. And the consumption of lettuce and sweet potato caused the greatest health risk, whereas cabbage and cowpea were relatively safe. The bioaccumulation factors (BAF) of heavy metals in various vegetables were calculated, and different vegetables showed huge variance in metal accumulation. Considering both contamination status and health risk assessment, cabbage and cowpea were selected as low accumulators of heavy metals. This study reveals the need for adjusting plantation structure and applying amendments to current protocols to alleviate the adverse effects caused by soil pollution.

A Rapid Method for Monitoring Landscape Structure and Ecological Value in European Farmlands: the LISA approach

Farmland biodiversity has dramatically declined in European agricultural landscapes over the past century. The key driver of this decline is the intensification of farming practices. In response, various policies have been developed to protect and promote farmland biodiversity, including so-called greening measures under the Common Agricultural Policy(CAP). However, there is currently very little systematically collected data on the ecological quality of European farmland. Therefore, we developed a survey method to provide repeatable and comparable data. This method comprises the mapping of land use and ecological quality of parcels in sample plots of 500 m x 500 m, vegetation transects on up to four predefined parcels in each sample plot and a photo documentation of the transects and the whole plot. Using this LISA method (Landscape Infrastructure and Sustainable Agriculture), we investigated about 25plots in each of 35 regions in 2014 and 13 regions in 2016, altogether in 10 EU countries. The methodology provides a time- and cost-efficient possibility to collect standardised data on the ecological quality of farmland habitats. We show that biodiversity in arable fields is at an extremely low level. The survey methodology proved to be applicable in all parts of Europe and thus being applied widely it could deliver a representative view on the ecological situation of all agricultural landscapes in Europe.

Application of Three Deep Machine-Learning Algorithms in a Construction Assessment Model of Farmland Quality at the County Scale: Case Study of Xiangzhou, Hubei Province, China

Constructing a scientific and quantitative quality-assessment model for farmland is important for understanding farmland quality, and can provide a theoretical basis and technical support for formulating rational and effective management policies and realizing the sustainable use of farmland resources. To more accurately reflect the systematic, complex, and differential characteristics of farmland quality, this study aimed to explore an intelligent farmland quality-assessment method that avoids the subjectivity of determining indicator weights while improving assessment accuracy. Taking Xiangzhou in Hubei Province, China, as the study area, 14 indicators were selected from four dimensions—terrain, soil conditions, socioeconomics, and ecological environment—to build a comprehensive assessment index system for farmland quality applicable to the region. A total of 1590 representative samples in Xiangzhou were selected, of which 1110 were used as training samples, 320 as test samples, and 160 as validation samples. Three models of entropy weight (EW), backpropagation neural network (BPNN), and random forest (RF) were selected for training, and the assessment results of farmland quality were output through simulations to compare their assessment accuracy and analyze the distribution pattern of farmland quality grades in Xiangzhou in 2018. The results showed the following: (1) The RF model for farmland quality assessment required fewer parameters, and could simulate the complex relationships between indicators more accurately and analyze each indicator’s contribution to farmland quality scientifically. (2) In terms of the average quality index of farmland, RF &gt; BPNN &gt; EW. The spatial patterns of the quality index from RF and BPNN were similar, and both were significantly different from EW. (3) In terms of the assessment results and precision characterization indicators, the assessment results of RF were more in line with realities of natural and socioeconomic development, with higher applicability and reliability. (4) Compared to BPNN and EW, RF had a higher data mining ability and training accuracy, and its assessment result was the best. The coefficient of determination (R2) was 0.8145, the mean absolute error (MAE) was 0.009, and the mean squared error (MSE) was 0.012. (5) The overall quality of farmland in Xiangzhou was higher, with a larger area of second- and third-grade farmland, accounting for 54.63%, and the grade basically conformed to the trend of positive distribution, showing an obvious pattern of geographical distribution, with overall high performance in the north-central part and low in the south. The distribution of farmland quality grades also varied widely among regions. This showed that RF was more suitable for the quality assessment of farmland with complex nonlinear characteristics. This study enriches and improves the index system and methodological research of farmland quality assessment at the county scale, and provides a basis for achieving a threefold production pattern of farmland quantity, quality, and ecology in Xiangzhou, while also serving as a reference for similar regions and countries.

Spatial Distribution of Soil Nutrients in Farmland in a Hilly Region of the Pearl River Delta in China Based on Geostatistics and the Inverse Distance Weighting Method

Soil nutrients are essential factors that reflect farmland quality. Nitrogen, phosphorus, and potassium are essential elements for plants, while silicon is considered a “quasi-essential” element. This study investigated the spatial distribution of plant nutrients in soil in a hilly region of the Pearl River Delta in China. A total of 201 soil samples were collected from farmland topsoil (0–20 cm) for the analysis of total nitrogen (TN), available phosphorus (AP), available potassium (AK), and available silicon (ASi). The coefficients of variation ranged from 47.88% to 76.91%. The NSRs of TN, AP, AK, and ASi were 0.15, 0. 07, 0.12, and 0.13, respectively. The NSRs varied from 0.02 to 0.20. All variables exhibited weak spatial dependence (R2 &lt; 0.5), except for TN (R2 = 0.701). After comparing the prediction accuracy of the different methods, we used the inverse distance weighting method to analyze the spatial distribution of plant nutrients in soil. The uniform spatial distribution of AK, TN overall showed a trend of increasing from northeast to southwest, and the overall spatial distribution of AP and ASi showed that the northeast was higher than the southwest. This study provides support for the delimitation of basic farmland protection areas, the formulation of land use spatial planning, and the formulation of accurate farmland protection policies.

Spatial Structure Characteristics of Slope Farmland Quality in Plateau Mountain Area: A Case Study of Yunnan Province, China

As an important part of farmland, the slope farmland is widely distributed in the central and western plateau mountain region in China. It is necessary to scientifically evaluate the slope farmland quality (SFQ) and analyze the spatial structure characteristics of SFQ to ensure reasonable utilization and partition protection of slope farmland resources. This paper takes the typical plateau mountain region—Yunnan Province in China—as an example and systematically identifies the leading factors of SFQ. The sloping integrated fertility index (SIFI) is adopted to reflect the SFQ. The evaluation system is built to quantitatively evaluate the SFQ and the spatial structure characteristics of SFQ were analyzed by a geostatistical model, autocorrelation analysis and spatial cold–hot spot analysis. The results show that the SFQ indexes in Yunnan Province are between 0.36 and 0.81, with a mean of 0.59. The SFQ grade is based on sixth-class, fifth-class, seventh-class and fourth-class land. The SFQ indexes present a normal spatial distribution, and the Gaussian model fits well with the semi-variance function of the spatial distribution of SFQ indexes. Furthermore, the spatial distribution of SFQ indexes is moderately autocorrelated. The structural factors play a major role in the spatial heterogeneity of SFQ indexes, but the influence of random factors should not be ignored. The spatial distribution of SFQ grades has a significant spatial aggregation characteristic, and the types of local indicators of spatial association (LISA) are based on high–high (HH) aggregation and low–low (LL) aggregation. The cold spot and hot spot distributions of SFQ grades display the significant spatial difference. The hot spot area is mainly distributed in Central Yunnan and the Southern Fringe, while the cold spot area mainly distributes in the Northeastern Yunnan, Northwestern Yunnan and Southwestern Yunnan. This study could provide a scientific basis for SFQ management and ecological environment protection in the plateau mountain region.

Coordinating the food-energy-water nexus in grain production in the context of rural livelihood transitions and farmland resource constraints

Understanding the interconnections and tradeoffs between food, energy, and water (FEW) in grain production, which are essential for agricultural sustainability, remains an elusive yet important task. We propose a four-step analysis method for exploring potential approaches to coordinating the FEW nexus in grain production based on a conceptual framework that incorporates the impact of rural livelihood transitions and farmland resource constraints. We apply this method to a small-scale watershed in Hunan Province, China using data from land-use maps, farm household surveys, farmland quality surveys, and cropping-pattern surveys. Transitions of rural livelihoods have led farmlands to become increasingly large in scale. The combined impacts of this concentration of large-scale farms and the government subsidy policy, which favors double cropping, undermines the FEW nexus. Our findings suggest two operational approaches for coordinating the FEW nexus in rice production. One is to develop adaptive agricultural policies that support farmers whose aggregate performance on rice production is superior or more balanced. The other is to optimize cropping patterns based on the suitability of farmland for grain planting.

The impact of land transfer and farmers’ knowledge of farmland protection policy on pro-environmental agricultural practices: The case of straw return to fields in Ningxia, China

Farmers’ pro-environmental agricultural practices (PAPs) are important measures to limit agricultural pollution and improve farmland quality. Given the positive externality of PAPs, the Chinese government has proposed a series of farmland protection policies to encourage farmers to implement PAPs. However, land transfer, an increasingly common phenomenon, may affect the effectiveness of policies. This study aims to explore how farmers’ PAPs have been affected by land transfer and farmers’ knowledge of farmland protection policy (KFPP). A systematic theoretical framework for this relation is developed. The probit model is applied to empirically investigate the relationship between land transfer, KFPP and the PAP of straw return to fields based on data collected from 400 farmers in Ningxia Province in China. The findings reveal that farmers’ KFPP has a positive effect on PAPs. Rented-in land has a positive effect on PAPs, while rented-out land has a negative effect, which is significantly reduced with the adjustment effect of KFPP on land transfer. Our analysis provides policy implications for the successful implementation of PAPs. The positive effect of rented-in land and the negative effect of land fragmentation on PAPs suggest the importance of policies promoting land consolidation by incorporating plot-connecting interventions in the land rental market. The positive and significant effect of KFPP on PAPs suggests further enhancing farmers’ knowledge of farmland protection policy, for example, by improving information channels and extension services.

Detecting and Assessing Nondominant Farmland Area with Long-Term MODIS Time Series Images

While most land use and land cover (LULC) studies have focused on modeling, change detection and driving forces at the class or categorical level, few have focused on the subclass level, especially regarding the quality change within a class such as farmland. The concept of nondominant farmland area (NAF) is proposed in this study to assess within class variability and quantify farmland areas where poor environmental conditions, unsuitable natural factors, natural disasters or unsustainable management practices lead to poor crop growth and thus low yield. A 17-year (2000–2016) time series of the Normalized Difference Vegetation Index (NDVI) was used to develop a NAF extraction model with abnormal features in the NDVI curves and subsequently applied to Heilongjiang province in China. The NAF model was analyzed and assessed from three aspects: agricultural disasters, soil types and medium- and low-yield fields, to determine dominant factors of the NAF patterns. The results suggested that: (1) the NAF model was able to extract a variety of NAF types with an overall accuracy of ~80%. The NAF area accumulated more than 8 years in 17 years is 6.20 thousand km2 in Heilongjiang Province, accounting for 3.75% of the total cultivated land area; (2) the NAF had significant spatial clustering characteristics and temporal variability. 53.24% of the NAF accumulated more than 8 years in 17 years is mainly concentrated in the west of Heilongjiang Province. The inter-annual NAF variability was related with meteorological variations, topography and soil properties; and (3) the spatial and temporal NAF patterns seem to reflect a cumulative impact of meteorological disasters, poor farmland quality, and soil degradation on crop growth. The determinant factors of the observed NAF patterns differed across regions, and must be interpreted in the local context of topography, soil properties and meteorological environment. Spatial and temporal NAF variability could provide useful, diagnostic information for precision farmland management.

How to minimize the impacts of urban expansion on farmland loss: developing a few large or many small cities?

In China, large cities are often held to blame for the drastic loss of high-quality farmland. However, others propose that the development of large cities should be prioritized for their scale economy in saving farmland. A policy debate remains regarding which urbanization mode—developing a few large or many small cities—can minimize the impacts of urban expansion on farmland loss. The present study aims to clarify the controversy by quantifying the quantity and quality of urbanization-encroached farmland (UEF) in different sizes of cities. We proposed two indexes to quantify the UEF among different sizes of cities during 2000–2010: “the UEF area per urban population growth” and “the average potential yield of UEF”. Furthermore, we proposed a spatial prioritization matrix to facilitate place-based policy design for UEF management. The super large cities (SLC) consumed the least UEF area per urban population growth and also the lowest average potential yield of UEF. However, there were large variations within city categories in both the quality and quantity dimensions. Farmland loss to urban expansion is determined by a city’s biophysical and socio-political conditions. Our analyses show that urban growth of SLC consumed smaller quantity of farmland when accommodating a certain amount of urban population. Containing the development of large cities in the name of food security is ineffective, which will cause double failures in farmland preservation and urban development. As the impacts of urban expansion on farmland loss are highly place-variant and urban sustainability is more than just food security, place-based policies following the landscape sustainability perspective are needed to address urban encroachment of farmland.

Study on the abandonment of sloping farmland in Fengjie County, Three Gorges Reservoir Area, a mountainous area in China

The farmland abandonment phenomenon in mountainous areas is a recent change in relationships between man and land that emerged in China's land-use transition. Revealing spatial distribution characteristics and influence factors of sloping farmland (SF) and abandoned farmland (AF) in mountainous areas is conducive to rational allocation and optimization on local land resources. This paper investigated regional distribution features of SF and AF in the hinterland of the Three Gorges Reservoir Area (TGRA) using high-resolution remote sensing images, ArcGIS spatial analysis, and statistical methods. The results found that the spatial distribution of SF and AF has an approximate characteristic under different topography, location, or accessibility backgrounds. However, within different spatial coupling relationships between SF and AF, influencing mechanisms of farmland abandonment are significantly different. The diversity of geographical locations reflecting natural and social contexts is an essential reason for this differentiation. Moreover, dominant influencing factors of farmland abandonment in the study area are natural factors such as slope and farmland quality. Socioeconomic factors, including distance to road, peasant income, and labor force proportion, guide the distribution and trend of farmland abandonment to varying degrees. Finally, four modes of farmland abandonment in TGRA have proposed and suggested that the corresponding plans for SF consolidation should be proposed based on fine classification, which is of great significance for farmland utilization and rural revitalization in underdeveloped mountainous areas.

Assessment of semi-natural habitats and landscape features on Irish farmland: New insights to inform EU Common Agricultural Policy implementation.

Concerns over the loss of biodiversity and ecosystem services in farmland have prompted the development of agri-environment policy measures aimed at reducing farming pressure and maintaining semi-natural habitats in farmed landscapes. However, further knowledge is needed to guarantee successful agri-environment measures implementation. The current study assessed the quantity and the quality of semi-natural habitats in farms across a gradient of farming intensities in two contrasting regions in Ireland. Policy protection seemed fundamental for semi-natural habitats preservation. Habitats not protected by agricultural policy relied on extensive farming and are in danger of disappearing if they are intensified or abandoned. Due to the lack of policy incentives for habitat quality, no correlations were found between farming intensity and share of semi-natural habitats with habitat quality. Therefore, extensive farming and retention of habitats alone may not reverse the decline of farmland quality and biodiverisity and, thus, measures incentivising the environmental quality may be more successful.

Soil quality should be accurate evaluated at the beginning of lifecycle after land consolidation for eco-sustainable development on the Loess Plateau

Evaluating farmland soil quality and zoning the obstacle factors regions were essential to enhance the productiveness of cultivated land and adopt sustainable management practices after land reclamation. The land consolidation project was initiated to reclaim gullies of the Loess Plateau and return them to farmland. However, soil quality and eco-sustainable improvement strategies of the reclaimed farmland were still unknown. The primary objective of this research was to assess soil quality, select a suitable evaluation method and provide precise amendment recommendations for this regions, selecting the reclaimed farmland of Yan’an city as a case. Indictor values of SOM, CEC, nitrogen, phosphorus, avail -Mn and -Zn on reclaimed farmland were considered at low level and soil quality was generally poor. A minimum data set evaluation method selecting by the Norm values is recommended for delineating poor quality farmland, with the threshold values of soil quality at 0.92. The main limiting factors for reclaimed farmland were identified as SOM, CEC, nitrogen, NaHCO3-P, and enzyme activities. SOM and nitrogen content, CEC and clay percentage, and NaHCO3-P concentration were the main limiting factors of soil quality on the all Yan’an regions, northern and southern areas, respectively, indicating the soil texture should be improved in the arid areas while the phosphate fertilizer should be accurately applied in the semi-arid regions. Those approaches will identify areas needing more intense management and improve utilization of applied amendments. We emphasize the spatial distribution of limiting factors was uneven on the Loess Plateau regions and the particular attention should be paid on specialized soil quality evaluation of targeted regions for precise amendment and utilization. The results of this study are important at the practices for avoiding the traditional unsustainable and inaccurately fertilization strategy.

Effect of Fertilizer Reduction and Biochar Application on Soil Nitrogen Loss in Purple Upland

This study seeks to clarify the effect of biochar application on nitrogen loss patterns and flux in purple arid sloping land, so as to provide a scientific basis for improving the quality of farmland and reducing the risk of agricultural non-point source pollution in purple arid sloping land. The effects of four treatments on surface runoff and soil nitrogen loss patterns and fluxes in purple arid sloping land were studied by field experiments, including no fertilization (control), conventional fertilization, optimized fertilization, and biochar (fertilizer reduction and biochar application). The results showed that:① Of the fertilization treatments, the total runoff of conventional treatment was the highest at 16133 L·a-1, and the total runoff of biochar treatment was the lowest at 11893 L·a-1. In each fertilization treatment, soil midstream was the main mode of runoff, accounting for 61.80%-68.60% of the total loss. Compared with the control (no fertilization treatment), the sediment loss in other fertilization treatments was decreased, with conventional treatment showing the most significant effect. ② Ammonium nitrogen is mainly lost by surface runoff, accounting for 86.51%-96.58% of the total loss flux. Biochar treatment had the highest loss flux at 0.69 kg·(hm2·a)-1, and the control treatment had the lowest at 0.17 kg·(hm2·a)-1. ③ The concentration of granular nitrogen in the production flow of each fertilization treatment was higher than that of the control treatment, and the loss flux of granular nitrogen in the conventional fertilization treatment was the highest at 2.87 kg·(hm2·a)-1. ④ There was a significant positive correlation between total nitrogen concentration and nitrate nitrogen concentration in the soil midstream and surface runoff of each fertilization treatment (P<0.01). Nitrate nitrogen is the main form of total nitrogen loss, and both take soil midstream as the main way of loss. The total nitrogen loss through soil flow accounted for 72.86%-89.13%, and that of conventional fertilization was the highest at 35.58 kg·(hm2·a)-1, whereas that of biochar treatment was the lowest at 21.49 kg·(hm2·a)-1. Reducing the amount of fertilizer and applying biochar can significantly reduce the runoff and nitrogen flux, and effectively prevent and control the risk of agricultural non-point source pollution.

Influences of the Transaction Intention of Farmland Transfer under Information Asymmetry: An Empirical Study of 1100 Questionnaires from China

The original intention of the tripartite rural land entitlement system was to activate farmland management rights and improve the efficiency of land element allocation. However, information asymmetry is prevalent in a market with imperfect competition. We analyzed the key factors affecting farmland transfer transactions with the structural equation model using survey data from farmers in five major grain-producing counties in Henan province, China. The purpose of our study was to investigate how these factors contribute to the avoidance of a “lemon market” emerging in farmland transfer and can promote the market regulation of farmland transfer operations. This study was conducted under the framework of asymmetric theory analysis with the purpose of discussing the fundamental forces driving farmland transfer transactions. The results show that (1) the economic characteristics of farmers play an important role in the formation of farmland transfer transactions, and their impacts on the willingness to transfer farmland in and out were 0.69 and 0.97, respectively; and (2) among the observable variables, the satisfaction degree of agricultural technology training and the proportion of non-agricultural income had a strong ability to explain the choice of farmland transfer behavior, and the factors that strongly impacted farmland transfer out behavior were physical condition and farmland quality. Thus, we recommend establishing a detailed land transfer pricing system based on the background quality of farmland and increasing the agricultural science and technology education, focusing on dredging information transmission channels to fulfill the new requirements of the three-right separation system on the government’s supervision of farmland transfer to promote effective links between small-scale peasant economies and modern agriculture.