Agricultural Structure Research Articles

Rental and sale prices of agricultural lands under spatial competition

Much of the land economics literature has largely ignored the spatial nature of competition and related differences between farmland rental and sales markets when assessing return rates from farming, the capitalization of agricultural, environmental and energy policy into land values, and climate change impacts. We propose a model for price formation in both markets under a spatial competition framework. We demonstrate that price formation differs, particularly under policy-induced output price shocks.We suggest that using the rent-price ratio as an approximation for expectations in the net returns of farming, based on the net present value model, may produce biased results. In consequence, studies relying on land prices need to control for local land competition, farming structure, and policies.

Concentración económica en la región pampeana, un análisis según zonas productivas (1988-2018)

The most complete tool to analyze the development of the social economic structure of Argentine agriculture is the National Agricultural Census. The data provided by the surveys of 1988 and 2002 allowed us to measure the process of economic concentration and elimination of small producers during the 1990s, decade during which a model and a dynamic was implemented in agribusiness that is projected into the 21st century. This article analyzes the recent information from the 2018 Census, with the aim of studying the magnitude of the concentration process in the different productive areas of the Pampas region. Those sub-zones are constructed based on the predominance of different activities in the production data collected by the censuses, and the evolution of the farms present in them is evaluated, classified according to size, with the idea of testing the Association between the setback of small farms and the type of activity they undertake. It is observed that throughout the 21st century the previous tendencies of greater concentration in the agricultural departments with respect to the cattle-raising areas have moderated, configuring a more homogeneous picture in terms of the decline of small production.

A Study on the Construction Mechanism and High-quality Development Path of Jiaxing Agricultural Science and Technology Park

Agricultural science and technology park has deduced a brand-new economic development model in the era of science and technology agriculture, created a new economic form of science and technology agriculture industry, and will become the mainstream of agricultural development in the 21st century. Promoting the construction mechanism of agricultural science and technology parks is to show and demonstrate the achievements of advanced agricultural technology and management mode, and to use its demonstration effect to exert the radiation influence effect from point to area, so as to further promote the structural reform of agricultural supply side and promote the high-quality development of regional agricultural economy. Therefore, this paper intends to fully understand the present situation of Jiaxing Agricultural Science and Technology Park by exploring its construction mechanism, so as to provide effective reference for planning the high-quality development path of Jiaxing Agricultural Science and Technology Park, and combine the current market agriculture situation to build the agricultural science and technology park with high standards and high quality, so as to scientifically guide farmers to adjust agricultural structure according to market orientation, innovate agricultural service system, and change agricultural organization mode, thus improving the degree of marketization, industrialization, informationization, standardization and extroversion of agriculture.

Agricultural carbon emissions in China: measurement, spatiotemporal evolution, and influencing factors analysis

IntroductionThe agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets.MethodsAgricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model.ResultsThe analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts.ConclusionThe findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions.

New insights on the role of the farm household-farm operation interface in family farm persistence and a call for future research

Rural social scientists have long sought to understand what the structure of agriculture will look like in the future, who is going to do the work, and under what conditions with a focus on family owned and operated farms. Central to the theorization of farm families' ability to continue farming in the midst of on-going changes are the deep inter-connections between the farm household and the farm operation and farm families’ ability to adjust how resources are used within the farm household and operation spheres. Yet in this paper we argue that the interface between the household and operation has largely been treated as a black box and when it has been considered, it has largely been from the vantage point of the farm operation at the expense of the farm household. We substantiate our argument by drawing on insights from our individual research and collective discussions during a three-day workshop around three themes (i.e. gender, life course and farm business cycle, formal and informal support systems). As an invitation for others to join us in opening a new line of research, we propose a research agenda and discuss considerations around research designs, data, funding, and collaborations to tackle this research agenda.

Interweaving Ecology and Culture in Bibhutibhushan Bondopadhyay’s Of the Forest

This paper investigates the intricate relationship between ecology and culture as depicted in Bibhutibhushan Bandyopadhyay's novel Of the Forest (Aranyak). It looks at how common situations and human social orders are profoundly interconnected, with social character and conventional structure of tribal and rustic communities formed by the forest. The novel depicts the forest not simply as a scenery but as an imperative, living substance that impacts the social, spiritual, and economic lives of the individuals occupying it. This consider uncovers how social structure, such as customs, legends, and jobs like chasing and horticulture, are closely connected to the rhythms of the forest. Through an ecocritical focal point, this paper investigates how the novel highlights the indigenous communities’ ecological information and maintainable structure. These communities don't see the forest just as a asset, but as a sacrosanct space necessarily to their social and spiritual personalities. Their customs, folklores, agricultural structure, and livelihoods—whether chasing, gathering, or farming are molded by the common rhythms of the forest. The novel portrays their relationship with land isn't fair financial, but profoundly social, fortifying a holistic approach where nature and culture are indivisible. The paper moreover digs into how Bandyopadhyay employs the novel to regret the loss of both environmental and cultural differences. As the forest destroyed, the conventional ways of life tied to it, driving to the fragmentation of the communities and havoc of cultural habits established in environmental settings. This demolition is depicted as a catastrophe of both the natural world and the human soul. The novel also studies the capitalist ethos that prioritizes economic advancement at the cost of ecological sustainability, addressing the menacing effect of modernization on both nature and innate culture. The article concludes by examining how Bandyopadhyay’s forest imagery transcends simple environmental imagery and transforms it into a symbol of cultural and environmental tolerance. The forest gets to be a location of social resistance to advancement of modernity, encapsulating a space where innate knowledge and practices proceed to offer an alternative to the destructive impact of modernization. The paper calls for a deeper understanding of the relationship between people and their environment, and calls for a return to a better relationship with nature.

Contract Farming & Cost of Funding: Evidence from Madurase Solar Salt Small Businesses

This study aimed to estimate the indirect expenses borne by tenant farmers due to credits they receive in community salt farming operations managed through contract farming systems in Pamekasan Regency. Credits constitute a crucial aspect of tenant farmers’ rights within the community salt farming contract farming framework. This study employed a comparative analysis of the cost of funds based on the adopted contract farming models, specifically the two-way and three-way contract farming structures. Moreover, it investigated the correlation between the cultivated salt field’s size and the magnitude of the cost of funds endured by tenant farmers. The results of the analysis reveal that the average costs of funds borne by tenant farmers are notably high, ranging from 5.24% to 6.71% per month. Surprisingly, these figures exceed the loan interest rates offered by two formal financial institutions: BRI and Bank JATIM. Another significant finding is the positive correlation between the size of cultivated salt fields and the magnitude of the cost of funds borne by tenant farmers. Lastly, there is a clear positive relationship between the credit amount received and the corresponding cost of funds endured by tenant farmers. The substantial costs of funds shouldered by tenant farmers involved in the community salt farming, operated through contract farming systems in Pamekasan Regency, signify inefficiencies within the contract farming structure. It is expected that the government can aid these tenant farmers by disbursing subsidized credits through collaborations with relevant ministries and local formal financial institutions.

Animal health as a function of farmer personality and attitude: using the HEXACO model of personality structure to predict farm-level seropositivity for Fasciola hepatica and Ostertagia ostertagi in dairy cows.

Infections with Fasciola hepatica and Ostertagia ostertagi impinge upon dairy cow health and welfare and represent a major economic factor in livestock industry. Control measures largely rely on the use of anthelminthic drugs. However, reports of anthelmintic resistance necessitate sustainable approaches. Farmer characteristics such as attitude and personality are crucial for the implementation of control strategies and on-farm practices. In the present study, the HEXACO (Honesty-Humility, Emotionality, eXtraversion, Agreeableness, Conscientiousness, Openness to experience) model of personality structure, which conceptualizes human personality, was used to evaluate the relationship of farmer aspects with on-farm bulk tank milk seropositivity for F. hepatica and O. ostertagi. Moreover, information on farm structure, housing, management, and farmers' attitude was collected in a face-to-face interview. Farm-level seropositivity for F. hepatica and O. ostertagi was predicted via elastic net regression. Out of 193 farms housing 8,774 cows in the German Federal State of Bavaria, 47 farms (24.4%) were seropositive for F. hepatica, 77 farms (39.9%) for O. ostertagi, and 42 farms (21.8%) for both endoparasites. The model for F. hepatica seropositivity selected the covariates pasture access, O. ostertagi seropositivity, higher farmer conscientiousness, and organic farming as relevant predictors. Seropositivity for O. ostertagi was predicted by F. hepatica seropositivity, pasture access, organic farming, and farmers being neutral regarding their satisfaction with animal health on their farm. Higher values for the HEXACO factors extraversion and emotionality were inversely associated with O. ostertagi seropositivity. The present work emphasizes the importance of farmer traits in regard to animal health and parasite occurrence. For the effective acceptance and implementation of sustainable control strategies for livestock helminth infections, it is crucial to consider these aspects to holistically address the challenges of managing parasitic diseases. Moreover, tailored communication strategies can be developed incorporating the understanding of individual stockman characteristics and subsequently ensuring encouragement of stakeholders.

Drifting vessel statistics and emergency towing cases

Abstract Recent climate studies forecast violent weather events with impact on the safety of maritime transportation. For example, harsh weather may result in system failures such as blackouts or loss of steering capability. Problems met when performing planned maintenance at sea may lead to adverse events if the weather cause delays or makes it impossible to complete the planned work. A drifting vessel in general is a liability for collisions with offshore structures, groundings, and total loss due to capsizing. The increasing use of ocean structures for energy production at sea (coastal and deepwater windfarms) and the transfer of fish farming structures to more exposed locations increase the probability of collisions between drifting ships and ocean structures. To mitigate risks, several incidents and their consequences have been analysed by national administrations. In some cases, these analyses have recommended the use of dedicated emergency towing resources. The willingness of the national governments to fund such resources is directly related to the time since the last major incident in their territorial waters. This paper reviews some recent cases of emergency towing operations in Norwegian waters and highlights challenges interlinked to setting up an emergency towing connection between a drifting ship and an emergency towing vessel in harsh weather.

Quantitative risk assessment for overtopping of earth-fill dams in Japan using machine learning algorithms

Earth-fill dams serve as crucial agricultural structures in Japan and act as buffers against flooding. However, their failure often tends to cause even greater downstream damage. Consequently, there is an urgent need for a quantitative assessment of the risks to earth-fill dams posed by disasters. The current detailed method of assessment is complicated, labour-intensive, and costly; hence, constructing risk surrogate models will greatly reduce the workload. This study employs two machine learning methods, GPR (Gaussian Process Regression) and XGBoost (eXtreme Gradient Boost), to develop surrogate models for assessing the damage cost and overtopping probability for 70 earth-fill dams in Okayama and Hiroshima prefectures, Japan. The predictive performance of each model was quantified by comparing the results against those of the detailed method. From the results, XGBoost demonstrates superior performance compared to GPR based on the comparison of coefficient of determination (R2) and root mean square error (RMSE). To clarify the extent to which the variables influence the XGBoost model, the SHapley Additive exPlanations (SHAP) algorithm was implemented. It offers an efficient and interpretable avenue for earth-fill dam risk assessments.

TRANSITION AND REGIONAL DIFFERENTIATION OF THE AREA STRUCTURE OF FARMS IN POLANDarea structure of farms, agrarian transformation, regional variation, panel models, succession

The aim of the study was to identify and assess the transformations and regional differentiation of the area structure of farms in Poland. The primary source of data was information collected from the Central Statistical Office (CSO) on the basis of the results of the 2002, 2010 and 2020 Agricultural Censuses and the CSO’s Local Data Bank. The research was carried out on a voivodeship basis. In the study, econometric models were constructed and subjected to detailed verification, the dependent variable being the average area of the farm in hectares of agricultural land. The dependent variable was compared with 16 independent variables, which were selected because of their information potential and discriminatory ability. To explain the reasons for this variation, it was decided to use a model for panel data with constant effects. Lagrange and Hausman tests were used to verify them. The analysis showed that in the period studied, the most important factor adversely affecting the level of the area structure of farms in Poland was the labor resources in agriculture. The factors that accelerated the changes in the area structure also included the rate of succession and the level of education of farm managers.

Integrating ecosystem services trade-off, drivers and zoning into watershed water environment management in Nansihu Lake Basin, China

A series of ecosystem services (ESs) have a significant impact on water environment. How these ESs can be integrated into water environment management in the lens of coupled human and natural system (CHANS) is still lack exploration. This study proposes an integrating framework that connects the ESs with water environment management to facilitate the watershed sustainable development. We employ the InVEST model to evaluate typical ESs in the Nansihu Lake Basin (largest freshwater lake in Shandong, China), and analyze the spatiotemporal characteristics and trade-off of multiple ESs indicators. By revealing the interaction mechanism and key drivers of ESs and conducting ecological functional zoning, we investigate how ESs can facilitate water environment management in the Nansihu Lake Basin. The results indicated that: (1) The high-value areas of agricultural supply service are mainly distributed in the western plain area of the basin, while high-value areas of water provision, water purification and soil conservation services are in the mountainous and hilly areas in the eastern part of the basin. (2) There is a significant trade-off between crop supply service and water purification services. Crop and livestock supply services have a greater effect on water purification services (TN) than other services. (3) Crop area sown, total power of agricultural machinery and fertilizer application are the main drivers of water purification services (TN). (4) The basin can be divided into three ecological function zones, the agricultural production zone, the ecological regulation zone and the ecological redline zone. These findings imply that water environment management should be integrated with ESs by strengthening intersectoral collaboration, conducting zoning management in watershed planning and applying differentiated control measures in each zone. This includes optimizing the scale and structure of agriculture, and implementing circular economy and clean production practices. This study explored a comprehensive framework of integrating ESs into water environment management to facilitate the sustainable development of watershed.

Recent Progress of Phase Change Materials and Their Applications in Facility Agriculture and Related-Buildings—A Review

Facility agriculture, which involves agricultural production in controlled environments such as greenhouses, indoor farms, and vertical farms, aims to maximize efficiency, yield, and quality while minimizing resource consumption and environmental impact. Energy-saving technologies are essential to the green and low-carbon development of facility agriculture. Recently, phase change heat storage (PCHS) systems using phase change materials (PCMs) have gained significant attention due to their high thermal storage density and excellent thermal regulation performance. These systems are particularly promising for applications in facility agriculture and related buildings, such as solar thermal utilization, greenhouse walls, and soil insulation. However, the low thermal conductivity of PCMs presents a challenge for applications requiring rapid heat transfer. This study aims to provide a comprehensive review of the types, thermophysical properties, and various forms of PCMs, including macro-encapsulated PCMs, shape-stabilized PCMs, and phase change capsules (PCCs), as well as their preparation methods. The research methodology involves an in-depth analysis of these PCMs and their applications in active and passive PCHS systems within facility agriculture and related buildings. The major conclusion of this study highlights the critical role of PCMs in advancing energy-saving technologies in facility agriculture. By enhancing PCM performance, optimizing latent heat storage systems, and integrating intelligent environmental control, this work provides essential guidelines for designing more efficient and sustainable agricultural structures. The article will serve as the fundamental guideline to design more robust structures for facility agriculture and related buildings.

The Impact of Farm Structure on Agricultural Growth in China

Farm structure has changed significantly since the land transfer policy was introduced in China. The quantity of and land area utilized by scale farmers and new agricultural entities are increasing, while the numbers of smallholders are decreasing. To analyze the impact of farm structure on agricultural growth in China, this study used provincial-level panel data from 2010 to 2021 and a fixed-effects model for empirical testing. The results show that (1) the structural change among farmers has a positive effect on agricultural growth, accounting for 16% of the contribution; (2) compared with scale farmers, new agricultural entities (NAEs) play a stronger role in improving agricultural growth, which is approximately five times higher than that of the former; and (3) unlike scale farmers, who only promote agricultural growth in central and major grain-producing areas, new agricultural entities have a positive effect on the entire area. Therefore, this study emphasizes the role of human capital in agricultural growth, especially in terms of promoting new agricultural entities, supporting land transfer, and optimizing farm structure.

Trends and drivers of land abandonment in Poland under Common Agricultural Policy

The results of existing research predict that the area of abandoned land will increase in many European regions. One of the countries that are the most prone to this process is Poland where agriculture, after many transformations, is still an important sector of the economy. It is essential to determine drivers of the abandonment of agricultural land use in order to effectively counteract this process. Through the Common Agricultural Policy, the European Union financially supports farmers who use agricultural land in accordance with the environmental protection requirements. This study investigated to what extent the land use, the characteristics of agricultural holdings, the demographics as well as economic factors impacted the process of land abandonment in Poland during the period 2002–2020. The analysis was carried out using statistical and spatial data pertaining to the period before and after Poland’s accession to the European Union. Our results demonstrate that the share of abandoned land within the country's agricultural area has decreased from 9.7 % to 1.2 %. Direct payments to farmers and the agrarian structure of farms were the most significant factors affecting this process. Spearman’s rank order correlations between the share of abandoned arable land and the two mentioned variables are close to or higher than 0.5 in each analysed year. The obtained results did not confirm the common conviction that environmental factors play a decisive role in the process of cultivation abandonment.

Analyzing individual rent price ratios in eastern German agricultural land markets: A GAMLSS approach

AbstractThis study explores the rent price ratio in agricultural land markets, crucial for evaluating market efficiency, policy needs, and farmer decision‐making. Traditionally, the analyses faced challenges due to the absence of concurrent sale and rent data for the same land, potentially leading to biased results. This research avoids this problem by utilizing a unique dataset from Eastern Germany, encompassing auction data from 2016 to 2019. This dataset is distinctive, containing both the purchase and lease price offers by individual farmers for the same agricultural land at a single point. Thus, this study overcomes the conventional limitations of using aggregated or non‐contemporaneous data. Hence, the focal point is to unravel the intricate relationship between individual rent price ratios and a myriad of influencing factors, including land characteristics and local farming structures. The use of Generalized Additive Models for Location, Shape, and Scale provides a robust framework for this analysis, offering a nuanced understanding of the distributional properties of individual rent price ratios. The study provides robust empirical evidence that highlights the need for adaptive and region‐specific policies if policy makers insist on intervening in the agricultural land market. Furthermore, promising points of departure for future research are identified. [EconLit Citation: Q15].

A new transferable deep learning approach for crop mapping

ABSTRACT Accurate crop mapping provides important information for government decision-making and agricultural management. Recent advancements in deep learning have significantly enhanced the capabilities of remote sensing-based crop mapping. In this study, we developed a new deep learning approach, DSH, which comprises three modules, DeepLabV3+ (D), channel self-attention (S), and histogram matching (H). The DeepLabV3+ module learns the spatial distribution of crops in the spatial and spectral dimensions. The channel self-attention module was used to enhance the weights of the important features. The histogram-matching module addresses the domain gap between the training and testing images and enhances the transferability of the DSH. In addition, the input data of the DSH are monthly synthesized Sentinel-2 data, thus relaxing the data collection requirements. The performance of the DSH was evaluated and benchmarked against HRNetV2, DeepLabV3+, and random forest (RF) at eight sites in the U.S. China, and France with different farming structures, climate conditions, and landscape complexities. Temporal transfer revealed that the classification performance of DSH improved as the growth season progressed, peaked in the peak growth season (August), and then declined at each study site. The DSH model trained during the peak growth season demonstrated superior temporal transferability. Spatial transfer experiments demonstrated that transferring DSH to sites with similar planting structures achieved higher precision than full spatial transfers. Spatiotemporal transfer experiments conducted at eight sites over three years (2020–2022) demonstrated an average overall accuracy (OA) of 88.1% for DSH, highlighting the importance of similar planting structures for effective spatiotemporal transfer. DSH outperformed HRNetV2, DeepLabV3+, and RF in OA, producer’s accuracy, and user’s accuracy at all eight study sites. Notably, DSH exhibited comparable performance during both the peak and full growth seasons, with an average OA of 93.9%. The classification accuracy of test images after histogram matching remained stable from 2020 to 2022, whereas the accuracy of raw test images fluctuated annually. This indicates that histogram matching is effective in improving the transferability of DSH. Embedding the channel self-attention module into the position of the high-level features had a more significant impact on improving DSH’s performance than other configurations. Visualizing features from the channel self-attention and high-level layers revealed that integrating the channel self-attention module with DeepLabV3+‘s high-level features significantly improved crop mapping by enhancing relevant semantic information. Overall, DSH exhibits robust spatiotemporal generalizability and requires minimal input data, making it suitable for large-scale crop mapping.

Structure of organic farming in the state of Paraná: analysis based on the 2017 Agricultural Census

This study examines the structure of organic farming establishments in Paraná, based on data from the 2017 Agricultural Census. An analysis of the representativeness of organic agriculture was conducted, and factors characterizing its structure in the state, as well as the distribution and concentration of these establishments among the evaluated municipalities, were interpreted. A quantitative and exploratory methodological approach was adopted, using two multivariate techniques, factor analysis and cluster analysis. The results indicate that the structure of agriculture in Paraná is predominantly familial, with nearly three times more family-owned establishments than non-family-owned ones. Although the number of establishments utilizing organic production is small compared to conventional practice, there is homogeneity in the structure of organic agriculture among the municipalities of Paraná. This can be attributed to the decentralization of the production area and the strong presence of collective management in providing technical support and coordinating local establishments. Keywords: Organic production; Family farming; Factor analysis; Cluster analysis.

Nutrient cycling on dairy farms in the Netherlands: The role of farm structure, management and trade-offs

Food production is a major driver for crossing planetary boundaries. Improving nutrient cycling may enable maintaining production while reducing environmental losses. This study assesses the current state of Dutch dairy on-farm nutrient (nitrogen- N, phosphorus - P) cycling through re-use of manure, scope for improvement and potential trade-offs. Data of 27 farms between 2006–2022 were used.Nutrient use efficiency (Output/Input) varied widely, with an average of 0.39 (0.29–0.47) for N and 0.88 (0.69–1.01) for P. Combining circularity and efficiency indicators showed that most gain in efficiency could be made by increasing cycled flow. Management related with improved cycling had lower external nutrient inputs, both from fertiliser and feed. Farm structure mattered for farm performance, as extensive farms with lower external N inputs from fertiliser or feed had higher N cycling and lower greenhouse gas emissions, but at the costs of agricultural land use and productivity.

Modelling High Resolution Agricultural Nitrogen Budgets: A Case Study for Germany

Water pollution with nitrogen (N) from agriculture constitutes a persisting environmental problem in intensive farming regions worldwide. Understanding the spatio-temporal interconnection between agricultural N emissions and N inputs to water bodies is key to evaluating and improving existing mitigation policies. Nitrogen flux models are an indispensable tool for addressing these complex research questions in the land use–water nexus, requiring adequate data on agricultural N surpluses. However, high-resolution farm management data are not readily available to the scientific community. We develop a municipality-level agricultural N budget model for Germany based on farm-level administration data from the Integrated Administration and Control System (IACS) and regional expert knowledge. We estimate a total agricultural N surplus of 58 kg N ha−1 of utilised agricultural area as the three-year average for 2014–2016. About 90% of municipalities exhibit N surpluses between 21 and 99 kg N ha−1. Evaluation with collected farm accountancy data revealed a good fit of the modelled (with observed) mineral N quantities applied. Our results highlight the potential of farm-level data for N flux models. Due to the ubiquitous reporting of land use and farming structures in the IACS, our approach can be adapted in other countries of the EU to serve as a harmonised backbone of monitoring and policy impact assessments.