Agricultural Performance Research Articles

Time-Series Based Surrogate Model For Wind Farm Performance Prediction

Aeroelastic codes are state-of-the-art simulation tools in both industry and academia for the modelling of wind turbine loads and power output. Although these codes are widely used for the analysis of individual turbines, they are in general computationally too expensive for the calculation of all turbines within a wind farm. Engineering models that are computationally cheaper but also provide a lower fidelity are therefore typically used for wind farm power performance predictions. In this paper, an alternative approach to simulate wind farm performance is presented: the use of a data-driven surrogate model that is trained on time series that were generated by the in-house aeroelastic tool BHawC. This surrogate model provides results with potentially higher fidelity than more simplistic engineering models but is computationally much cheaper than BHawC simulations.

Recommendations on setup in simulating atmospheric gravity waves under conventionally neutral boundary layer conditions

Wind farm-induced atmospheric gravity waves have been the subject of recent research as they can impact wind farm performance. Pressure variations associated with gravity waves can contribute to the global blockage effect and wind farm wake recovery. Therefore, accurate numerical simulation of flow fields, where wind-farm-induced gravity waves may be produced, is important. Three main considerations in such simulations are the overall domain size, the use of Rayleigh damping near domain boundaries to dampen gravity waves, and advection damping at the inlet to prevent spurious oscillations. Often these considerations are treated ad hoc rather than systematically. This work aims to test and extend the systematic modelling of internal gravity waves proposed in a preliminary investigation to modelling of both internal and trapped gravity waves. The preliminary study identifies the length scales to set the domain and damping layer sizes and the time scale to configure the Rayleigh damping coefficient but under linearly stratified conditions. Large eddy simulations of flow through a wind farm canopy are performed under conventionally neutral boundary layer (CNBL) conditions to test the validity of proposed setups for CNBL conditions. Background atmospheric parameters, such as Froude number (Fr), inversion height (Hi ), and inversion layer Froude number (Fri ) control most of the atmospheric gravity wave characteristics. We validated for CBNL conditions that the effective wavelengths of the internal gravity waves are the correct length scale to configure the domain size and damping layer thickness. Likewise, the optimum damping coefficient to dampen the internal gravity waves relates to the free atmosphere’s buoyancy frequency or buoyant perturbations’ time scale. We infer that the damping coefficient in the inversion layer may relate to the inversion buoyancy frequency to effectively dampen the trapped gravity waves. Moreover, the advection damping length is linked to the horizontal wavelength of the trapped gravity waves in the inversion layer to prevent spurious waves at the inlet by retaining wave energy accumulation.

Assessing wind turbine lightning risk using data-driven methodology

This paper presents a methodology to conduct a risk assessment of lightning damage for wind farms using a data-driven methodology. Methods exist to address risks related to fire but this approach goes further to address lightning damage and related impacts to operations and maintenance comprehensively - monetizing the costs of these impacts. The process begins with lightning data analysis and strike rate calculation. Then, the lightning damage data is analyzed to gain insight into the repair cost and impact. Lastly, the process-based cost model takes lightning strike rate and impact data, resulting in risk provision. The paper presents two case studies, one for onshore wind farms and one for offshore wind farms. The relative importance of operations and maintenance costs versus lost revenues due to downtime (liquidated damages) differ between the two cases due to underlying technical drivers (turbine sizes, wind farm performance, lightning prevalence) as well as market drivers (labor costs, electricity prices). Thus, the study demonstrates both the viability of the method in providing monetary estimates of lightning damage costs over the lifteime of a wind farm as well as the importance of site-specific analysis and models to ensure accurate estimation of those costs.

Socioeconomic sustainability of agroecological farming: a quantitative analysis of cucurbit crop production in Eastern Central Tanzania

ABSTRACT Agroecological farming emerges among approaches for managing crop pests including the “True” fruit fly (Diptera, Tephritidae). We conducted baseline interviews and field experiments in Eastern Central Tanzania to determine farmers’ perception on the approach and verify its socio-economic performance in cucurbit crop production. The performance of small-scale cucurbit farming in agroecological and conventional agriculture was broadly comparable. Farmers perceived the approach as effective and beneficial over conventional farming and pesticide-based agriculture but constrained by its more elaborate/laborious implementation. Still, agroecological farming significantly lowered the production costs. Therefore small-scale agroecological cucurbit farming in Tanzania represents a viable alternative and promising tool to reduce use of synthetic pesticides that negatively impact human health and the environment.

Numerical Investigation on Mooring Line Configurations of a Semisubmersible Fish Farm for Global Performance

The growth of the aquaculture industry has led to the development of innovative fish farming technologies, such as semisubmersible fish farms which offer significant advantages in terms of scalability and environmental sustainability. The study utilizes a new workflow based on an open-source finite element solver, Code_Aster, to calculate the hydrodynamic dynamic response of a fish farm. The mooring line configuration of a semisubmersible fish farm plays a crucial role in ensuring its stability and overall performance. This study presents a comprehensive numerical investigation aimed at evaluating the influence of different mooring line configurations (i.e., 4 × 1, 4 × 2, and 4 × 3) on the global performance of a semisubmersible fish farm under regular waves and irregular waves conditions. Increasing the number of mooring lines can reduce the mean and extreme tension in individual mooring lines and suppress the horizontal motions, but bring neglectable effects on the rotational responses. The findings from this research provide valuable insights into the optimal mooring line configuration for the global performance of semisubmersible fish farms.

Changes in productive, socio-economic, and environmental performance of field crop farming in the Argentine Pampas, 2007–2018

This study fills important gaps in research by analyzing the evolution over time of productive, environmental, and socio-economic aspects of agricultural production in the Argentine Pampas, utilizing farm-level data. A longitudinal study was conducted to examine the changes that occurred in farming systems during the period 2007–2018. The study evaluated the changes in 30 farms, examining modifications in the structure and management of each farm, as well as in productive, economic, and environmental performance. Canonical correlation analysis was used to relate the changes that occurred in performance to farms' characteristics at the beginning of the study period. The results indicated that, among the farms that stayed in business, there were no significant changes in land tenure and the amount of labor employed. There was a significant increase in the average age of farmers by 7 years, along with a decrease in the percentage of farmers expecting growth, dropping from 70% to 42% over the period. Canonical correlation analysis revealed that smaller farms, with a higher number of workers at the beginning of the period, were more likely to expand their farming area during the analysis period. The findings also indicate a substantial turnover of producers, with leaving farms being succeeded by larger-scale operations. The yields of the main crops and the direct production costs increased by 16% and 48% respectively, during the period. The environmental indicators for the main crops present a mixed picture: soil organic carbon input increased by 12%, while environmental impact quotient decreased on average, by 6% for cereals but increased by 40% for soybeans, and nutrient imbalances rose. The significance of this study resides in its application of a comprehensive approach to analyze the transformation of farming systems over time.

Considering the development of organic farming in Poland at different territorial aggregation levels

The aim of this paper is to show and assess how the level of data aggregation can change the way the development of organic agriculture in Poland in 2014–2021 is perceived. A composite indicator of eco-farming at different levels of territorial aggregation and in different time horizons has been built taking into account sub-components and individual indicators. The performance of organic agriculture with the initial effects of the pandemic (for 2020–2021) was also quantified. The results showed that, in populationally larger territorial units (NUTS-1, NUTS-2, NUTS-3), organic farming characteristics are less variable, whereas the same characteristics show greater variability in smaller territorial units (LAU-1, LAU-2). This reflects the strong regional character of eco-agriculture. It can be observed especially in northern and south-eastern Poland. Moreover, although the highest performance of organic farming was observed in 2021, the effects of the pandemic crisis were highly heterogeneous by location. The results may be crucial for farmers and policymakers in planning sustainable agricultural strategies and building resilient organic regions.

Belief Reliability Modeling Method for Wind Farms Considering Two-Directional Rotor Equivalent Wind Speed

Compared to conventional energy sources, wind power is a clean energy source with high intermittence and uncertainty. As a system that converts wind energy into electricity, wind farms inevitably face severe reliability issues. In this paper, based on reliability theory, a new reliability modeling method for wind farms is proposed. Firstly, a belief reliability model for wind farms is constructed. Then, a power generation model based on two-directional rotor equivalent wind speed is established to represent the wind farm performance in the belief reliability model. Finally, several numerical studies are conducted to verify the power generation model under different wind speeds and directions, to demonstrate the belief reliability model with different levels of uncertainty, and to compare the belief reliability considering two-directional rotor equivalent wind speed with other methods.

The Effects of Digitalization on the Sustainability of Small Farms

Digitalization of agriculture is one of the priorities of the EU’s rural development strategy “From Field to Table”, which promotes the creation of more added value and climate change mitigation in agriculture. A growing body of the literature argues that digitalization enables better information management, reduces production costs, and increases the potential for farm income growth, but only a few papers provide empirical studies on how digitalization improves the performance of small farms. To fill this gap in the literature, this paper presents a case study as empirical evidence of the impact of digital innovation on smallholder performance through a sustainable development lens. This paper reports research based on a pilot digitalization project implemented on a small organic farm. It examines the identification of logical links between the digitalization processes introduced and the impact of digitalization on the economic, social, and environmental performance of the small farm. The case study data were collected through semi-structured interviews and based on the results of a pilot project. The findings of this study provide evidence that the introduction of digital technologies has improved the economic performance of the farm, including a reduction in labor costs, improved customer relations, improvements in farmers’ investment planning, and process redesign. Based on this study, recommendations are made to policymakers on how to promote the uptake of digital technologies in smallholder farming.

Land and technology requirements for economically prosperous smallholder farming in sub-Saharan Africa: Evidence from Tanzania

Making a living from a small farm is difficult in sub-Saharan Africa. In this paper, we quantify how difficult, using a simple, robust, relation between per capita daily income from farming (FPDI), land per capita and whole-farm net profitability per hectare. This relation allows the calculation of the land area required to generate various levels of household income as a function of farm performance. We use nationally representative household data for Tanzania to investigate the range of whole-farm profitability and to estimate an upper limit for it. For 6818 cases where households with land reported figures for gross crop and livestock revenues and for costs in any of the three years 2009, 2011 or 2013, actual median whole-farm net profitability was only $454/ha/y even without including the opportunity cost of family labour. When those were considered, median net profitability was negative $238/ha/y, i.e. a net loss. The maximum whole-farm profitability achieved was $4485/ha/y without family labour costs and $2742/ha/y with it. We evaluated actual and potential farm performance for their ability to generate a range of values of FPDI up to $10 per person per day. Most farms are not very profitable, particularly when household labour costs are considered, and few would be considered economically prosperous. Our analysis underscores the fact that improving their operations or adopting new technologies alone is unlikely to lift many smallholder farmers out of poverty in developing countries, given typical farm size distributions and reasonable assumptions about the realized economic returns to adoption of currently available agricultural technologies. While continued agricultural R&D investments are certainly worthwhile, such efforts alone will be insufficient to meaningfully address welfare needs of the world's rural poor. This suggests that agricultural development programs should expand their attention to incorporate off-farm and non-farm components of the rural economy.

A hybrid physics-based and data-driven model for intra-day and day-ahead wind power forecasting considering a drastically expanded predictor search space

This work presents a novel hybrid (physics- and data-driven) model for short-term (intra-day and day-ahead, 3h-24h) wind power forecasting (STWPF). Traditionally, STWPF predictors admitted very few meteorological variables only from the grid points closest to the turbines. Here, with the aim to further capture the underlying atmospheric processes ruling the wind variability in the wind farm, the approach relies on drastically expanding the predictor space, composed of numerous meteorological variables throughout a large geographical domain, retrieved from a weather forecasting model (COSMO-1). An ad-hoc genetic algorithm that optimizes the selection of predictors is designed and combined with feed-forward artificial neural networks for its cost function evaluation. The introduced model is compared to multiple benchmark models in a 16-turbine wind farm in the Swiss Jura mountains. For +12h and +24h lead times, the new approach shows a root-mean squared error normalized to the installed wind farm capacity of 11% and 11.6%, respectively. These values entail ∼16% higher forecasting skill compared to state-of-the-art predictor frameworks. Results highlight the ability of the presented approach to systematically select as predictors different variables with a well-known impact on the wind farm performance, such as the turbulent kinetic energy or the vertical wind shear. Clustering the data according to the wind direction provides substantial benefit. In addition, it provides a better understanding of the attained improvement: largest performances occur in those wind directions affected by highly complex terrain. This indicates that the proposed model can be especially suitable for wind farms in complex terrain.

The impact of repayment obligations arising as a by‐product of input use on partial inefficiency: Evidence from Western Australian farm businesses

AbstractFarm businesses often use debt to finance the purchase inputs and meet operational costs. Selected studies have investigated the impact of debt use on farm performance as measured using technical efficiency. However, no prior studies in agriculture have considered treating the debt repayment obligation created as a by‐product of production when benchmarking farm performance. This study employs nonparametric directional distance function models to quantify the impact of debt repayment as a by‐product of input use purchased on credit on farm‐level partial inefficiency using a panel data of 54 mixed enterprise broadacre farms in Western Australia from 2002 to 2011. The study finds that omitting repayment obligations created in the production process in analysis results in underestimating partial inefficiency scores. Farm size, production diversification and rainfall zone are significant drivers of partial inefficiency. The implication of the study's findings is that failure to account for repayment obligations created in the production process may result in erroneous policy suggestions that undermine the efforts of farm businesses to minimise or avoid financial stress.

Legal Repair: Domesticating European Legislation on Pig Welfare

Our daily activities rely on a proliferating number of things that are subject to decay. As stressed in a growing body of literature, repair is critical to the smooth functioning of material infrastructure. However, this scholarship has overlooked a crucial dimension: things become fragile not only due to material degradation but also as a result of regulatory change. This article introduces the notion of “legal repair” to describe how, in the face of legal change, certain actors reassemble the material world. We elaborate on this concept through an analysis of the domestication of European Union (EU) animal welfare legislation by the French pig sector. While it was feared that stricter pig housing standards would fragilize the existing farms, pig farmers complied using technical systems that failed to significantly improve animal welfare. We analyze this domestication of EU legislation as a process of legal repair. Alongside the political work of the leaders of the pig sector, agricultural advisers also played a key role. Their work reveals the relational nature of legal repair: in the production of “local specifications” matching the demands of existing farming systems, in the negotiation of the finer points of the legislation, and in the redefinition of farming performance.

A Methodological Framework for Assessing the Agroecological Performance of Farms in Portugal: Integrating TAPE and ACT Approaches

Agroecology integrates science, social movements, and agricultural practices, playing a central role in the sustainability of food systems. It addresses agroecosystems and food systems holistically; however, defining whether a farm is agroecological remains a challenge. This article proposes a methodology to measure farms’ agroecological performance, adapted to the family farming context in Portugal. The aim of the developed methodology is to compare the agroecological performance of family farms (conventional and non-conventional), providing information about anchors for agroecological transition and supporting public policies. A literature review identified existing farm evaluation methodologies, with Tool for Agroecological Performance Evaluation (TAPE) and Agroecology Criteria Tool (ACT) scoring highest in an assessment process. Questions from both were integrated into a questionnaire for family farmers. This field work provided critical insights towards the methodologies: (1) territorial adaptability; (2) transition constraints’ origin; and (3) use of non-academic language. The results were incorporated into the developed methodology, which combines the TAPE indicator matrix and Gliessman’s five levels of food system change, the latter of which provides the framework for the ACT. This study made it possible to identify the most relevant aspects for characterizing family farmers/farms and the importance of how the evaluation criteria/indicators are ordered by element/theme, as it alters the values of each farm’s agroecological performance.

Nutritional Quality and Socio-Ecological Benefits of Mare Milk Produced under Grazing Management.

This review discusses the scientific evidence that supports the nutritional value of mare milk and how its properties are essentially achieved when mares are managed under grazing conditions. Mare milk's similarity with the chemical composition of human milk makes this food and its derived products not only suitable for human consumption but also an interesting food regarding human health. The contribution of horse breeding under grazing management to other socio-ecological benefits generated by equine farms is also highlighted. Both the high added value of mare milk and the socio-ecological benefits derived from pasture-based systems could be explored to improve the performance of equine farms located in arid and semi-arid areas or in regions with moderately harsh environmental conditions as equids have a strong adaptation capacity.

Factors contributing to high performance of sows in free farrowing systems

BackgroundPressure to abolish farrowing crates is increasing, and producers are faced with decisions about which alternative system to adopt. For sow welfare, well designed free farrowing systems without close confinement are considered optimal but producers have concerns about increased piglet mortality, particularly crushing by the sow. Reporting accurate performance figures from commercial farms newly operating such systems could inform the transition process. This study investigated performance on three commercial farms operating four different zero-confinement systems, three of which were newly installed. A total of 3212 litters from 2920 sows were followed from farrowing to weaning over a three-year period with key performance indicators (KPIs) recorded. Mixed Models (LMMs, GLMMs) determined the influence of different factors (e.g. farrowing system, sow parity, management aspects) and litter characteristics on performance, including levels and causes of piglet mortality.ResultsPiglet mortality was significantly influenced by farm/system. Live-born mortality ranged from 10.3 to 20.6% with stillbirths ranging from 2.5 to 5.9%. A larger litter size and higher parity resulted in higher levels of mortality regardless of system. In all systems, crushing was the main cause of piglet mortality (59%), but 31% of sows did not crush any piglets, whilst 26% crushed only one piglet and the remaining sows (43%) crushed two or more piglets. System significantly influenced crushing as a percentage of all deaths, with the system with the smallest spatial footprint (m2) compared to the other systems, recording the highest levels of crushing. Time from the start of the study influenced mortality, with significant reductions in crushing mortality (by ~ 4%) over the course of the three-year study. There was a highly significant effect of length of time (days) between moving sows into the farrowing accommodation and sows farrowing on piglet mortality (P < 0.001). The less time between sows moving in and farrowing, the higher the levels of piglet mortality, with ~ 3% increase in total mortality every five days. System effects were highly significant after adjusting for parity, litter size, and days pre-farrowing.ConclusionThese results from commercial farms demonstrate that even sows that have not been specifically selected for free farrowing are able, in many cases, to perform well in these zero-confinement systems, but that a period of adaptation is to be expected for overall farm performance. There are performance differences between the farms/systems which can be attributed to individual farm/system characteristics (e.g. pen design and management, staff expertise, pig genotypes, etc.). Higher parity sows and those producing very large litters provide a greater challenge to piglet mortality in these free farrowing systems (just as they do in crate systems). Management significantly influences performance, and ensuring sows have plenty of time to acclimatise between moving in to farrowing accommodation and giving birth is a critical aspect of improving piglet survival.

Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments

The integration of cutting-edge precision agriculture technologies into avocado production is a promising strategy to boost productivity and profitability in this thriving industry. While previous reviews have explored the application of emerging technologies in avocado cultivation, there is a gap in the analysis of patent production. This research aims to bridge that gap by identifying trends in both scientific and technological innovations related to precision agriculture in avocado. Through a bibliometric analysis using data from Scopus and Lens.org, this study reveals that scientific production is primarily concentrated in industrialized countries, with limited research output from major avocado-producing nations. The focus of research has been on remote sensing and image processing techniques. In terms of technological development, innovations in agricultural data capture, collection, and processing, as well as components for agricultural machinery, have been the most prevalent. Market-available technologies are designed to predict crop yields and assess the impact of abiotic factors such as temperature, humidity, and precipitation. By adopting these precision agriculture tools, avocado farmers can make data-driven decisions to optimize resource use, improve crop health, and ultimately enhance overall farm performance.

Control-oriented modelling of wind direction variability

Abstract. Wind direction variability significantly affects the performance and lifetime of wind turbines and wind farms. Accurately modelling wind direction variability and understanding the effects of yaw misalignment are critical towards designing better wind turbine yaw and wind farm flow controllers. This review focuses on control-oriented modelling of wind direction variability, which is an approach that aims to capture the dynamics of wind direction variability for improving controller performance over a complete set of farm flow scenarios, performing iterative controller development and/or achieving real-time closed-loop model-based feedback control. The review covers various modelling techniques, including large eddy simulations (LESs), data-driven empirical models, and machine learning models, as well as different approaches to data collection and pre-processing. The review also discusses the different challenges in modelling wind direction variability, such as data quality and availability, model uncertainty, and the trade-off between accuracy and computational cost. The review concludes with a discussion of the critical challenges which need to be overcome in control-oriented modelling of wind direction variability, including the use of both high- and low-fidelity models.

Adopting Critical Success Factors (CSF) Methods to Achieve High Management Performance on Dairy Farms

It is known that the agribusiness sector in Brazil is made up of several companies operating in different business models in their environment. They operate in production side as no cyclical and the market side as cyclical, such as milk and dairy products. It is, however, characterized by dynamic and complex processes and competitive events, applied technologies, specialized labor problems, with risks and uncertainties inherent to the environment. Dairy farming is a relevant segment of this sector, both in terms of representativeness and wealth generation. Therefore, dairy farms need to be aware of innovations, and be effective in the pursuit of productive performance and profitability. The present study aims to evaluate the Critical Success Factors (CSF) involved in the search for high productive performance and profitability in dairy farms assisted by technical and managerial consulting of an agribusiness alpha company. The research has a qualitative approach and a descriptive conclusive character. Multiple case studies were carried out, and the units of analysis are 6 farms, their respective leaders (owners and managers), and consultants specialized in dairy farming from the company Alfa de Consultoria. The results demonstrate that the CSFs that promote high performance in dairy farms are: financial management; leadership and people management; process management; employee training and development; adequate sizing of the project; search for continuous improvement; management of indices and technical indicators; ensure animal comfort; technical assistance and consultancy.

Peningkatan Kinerja Usahatani Hortikultura Melalui Pengembangan Pola Kemitraan Agribisnis: Studi Kasus Kelompok Tani Sidoluhur, Desa Cabeyan, Kabupaten Sukoharjo

The development of horticultural farming through agribusiness partnerships can serve as a solution to farmers' limitations in managing agricultural risks. Partnerships have the potential to improve farming productivity and ensure price certainty. However, in some instances, partnership practices may give rise to issues such as dependency and weakened bargaining power for farmers. This research aims to investigate and analyze the potential for enhancing the performance of horticultural farming through the development of agribusiness partnership models in the Sidoluhur Farmers' Group, Cabeyan Village, Sukoharjo District. The research methodology employed is a descriptive case study involving five key respondents, including a lecturer from Universitas Sebelas Maret, the owner of Spesial Sambal, and farmers engaged in cultivation or responsible for the Sidoluhur Farmers' Group. The case study method allows for in-depth investigation into specific cases and facilitates the development of narratives or stories. The research findings indicate that the established partnership model is a subcontracting pattern involving three parties: the Sidoluhur Farmers' Group, PT Waroeng Spesial Sambal, and Universitas Sebelas Maret. The partnership provides market certainty for the farmers with a stable selling price. Importantly, this partnership does not create dependency on PT Waroeng Spesial Sambal, as farmers are free to market their harvests independently.