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| Filter results16 paper(s) found. |
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1. Beyond the Mean: A Quantile Count Regression Analysis of Precision Farming Technology Adoption Intensity by German FarmersThis study examines the factors influencing precision agriculture technology adoption intensity among German farmers using an innovative quantile count regression approach that reveals heterogeneous relationships across different segments of the adoption distribution. While previous research has primarily relied on mean-based regression models that may mask important variation in adoption determinants, this analysis provides new insights into how factors affect low, moderate, and high technol... M. Michels, O. Musshoff |
2. Worldwide Crop Precision Agriculture Adoption: 2026 UpdateRobotics, machine vision, and drone spraying have attracted much attention in recent years. But the technologies introduced in the 2000s and earlier, such as yield monitors, guidance, variable rate technology (VRT), and digital imagery continue to advance worldwide, more on large mechanized grain and oilseed farms. This update summarizes census estimates and adoption surveys with statistically reliable random sampling from 24 countries. Within-country and farm size breakdowns are reported whe... B. Erickson, J. Mcfadden, E. Morimoto, J. Lowenberg-deboer |
3. Expanding Access to High-Resolution Soil pH Measurement: From Smallholder Farms to 200-Hectare FieldsSoil pH is one of the most influential and correctable soil properties affecting crop productivity. It governs nutrient availability, toxicity risk, microbial activity, and overall soil function. Yet timely and spatially representative pH measurement remains inconsistent across agricultural systems due to laboratory turnaround times, sampling costs, limited field access, and sub-field variability not captured by conventional sampling density. This study evaluated multiple strategies... T. Lund, C. Maxton, E. Lund |
4. Benchmarking Precision Agriculture Adoption in the United States and BrazilThe United States has long been regarded as a global leader in agricultural technology and productivity. However, rapid advancements in other major producing countries are challenging this position. Brazil, in particular, has paired large-scale crop expansion with accelerated digital transformation, raising important questions about where the United States continues to lead and where it risks losing its competitive edge. Understanding how precision agriculture technologies are being adopted a... J. Colussi, B. Erickson, T. Malone, M. Langemeier, C. Fiechter |
5. Understanding Adoption and Post-Adoption Impacts of Smart Farming Technologies in ItalySmart farming technologies (SFTs) are increasingly promoted as key enablers of agricultural efficiency, resource optimization, and environmental sustainability. However, despite rapid technological advancement, empirical evidence on realized economic and resource-use impacts under real farming conditions remains limited, creating uncertainty about the magnitude and distribution of impacts. Existing evidence remains largely focused on perceived drivers, barriers, and intentions to adopt, rathe... |
6. Accuracy Analysis of C/A Code-based GNSS Receivers in Kinematic ConditionPrecision agriculture has emerged as a strategic approach to optimize input use and maximize crop productivity. One of the key pillars of this practice is the collection of georeferenced data, essential for the monitoring and efficient management of cultivated areas. This report aims to compare the performance of different positioning signal reception technologies under dynamic conditions. Three C/A code navigation receivers integrated into smartphones, one conventional navigation GPS receive... S. Ribeiro, G. Sanches, C.N. Ricci, J. Regazzo, J.P. Molin |
7. Digital Agriculture in Dairy Farming: Connectivity Diagnosis and Barriers to Technology Adoption in an Agrotechnological DistrictThe integration of digital tools and communication systems has underpinned a profound transformation in global production chains, aiming to optimize farm operations through technological innovation. Within this context, the present study forms part of the Semear Digital project, coordinated by Embrapa, and is grounded in the premise that digital inclusion constitutes an indispensable strategy for the sustainability and competitiveness of contemporary dairy farming. The primary object... M.D. Melo, C.M. Paiva, A.L. Oliveira, F.N. Maciel, G.C. Siqueira , M.R. Borges , G.S. Furtado, P.M. Leme |
8. Impact of Sampling Density on the Spatial Prediction of Soil Chemical Attributes Using Geostatistics and Machine LearningSoil sampling at high grid densities represents a significant economic barrier to the adoption of Precision Agriculture (PA) in Brazil. This study evaluates the trade-off between sampling density and interpolation quality by comparing geostatistical methods and machine learning algorithms. Three distinct approaches were statistically assessed: Ordinary Kriging (OK), Random Forest (RF), and the hybrid Random Forest Regression Kriging (RFRK). The analysis was conducted across six fields totalin... S. Ribeiro, H. Fantin gebler, J.P. Molin, R.F. Da silva |
9. Determinants of the Intensity of Digital Precision Technology Adoption in Brazilian FeedlotsPrecision livestock farming has gained prominence as a tool to enhance managerial control and reduce risk in intensive production systems. In the case of Brazilian beef cattle feedlots, characterized by high price volatility, tight margins, and increasing pressure for environmental performance, the adoption of digital technologies represents a relevant strategy to improve decision-making processes. Unlike studies that focus solely on binary adoption (adopt/non-adopt), understanding adoption i... G. , M.J. Carrer, M. , L.C. David, H.M. Souza filho, E. Bonjour |
10. Unveiling Research Patterns in Precision Agriculture: A Comprehensive Network Analysis of ICPA ProceedingsThe International Conference on Precision Agriculture (ICPA) is one of the most influential global forums dedicated to advancing technologies, methodologies, and scientific understanding in the domain of precision agriculture. Since its inception, the conference has served as a central platform for disseminating innovations in data-driven crop management, sensor technologies, spatial analysis, automation, and decision-support systems. Now in its 17th edition, the ICPA has accumulated more tha... S. Camargo, J. Valiati |
11. Detection of Aggressive Group Behavior of Laying Hens in Free HenhousesHarmful social behaviors among laying hens, such as feather pecking and aggressive chasing, pose a significant challenge to animal welfare and productivity in cage-free poultry systems. While cage-free housing allows hens to express natural behaviors, it also increases the risk of injurious interactions that can lead to stress, injury, and economic losses. Existing mitigation strategies, including environmental enrichment and housing design improvements, reduce but do not eliminate harmful be... Y. Heller, S. Druyan, A. Godo, V. Bloch |
12. Digital Livestock Management Solution for Cattle Identification, Traceability, and Real-time MonitoringBrazil is a global player in the beef industry with the world's largest commercial bovine herd, exceeding 230 million head, and leads the international market, accounting for approximately 25% of the global beef trade, reaching over 150 international markets. The combination of edaphoclimatic diversity, high-performance genetics, rigorous sanitary protocols, and the adoption of technological framework for tropical livestock accounts for decoupling of Brazilian ranching from extensive, low... A. Bernardi, A.R. Garcia, E.S. Guimarães, F. Tonato, S.R. Medeiros, W. Barioni jr., J.B. Portugal, T.C. Alves, W.P. Cavalcante, M. Serão filho, C. Gaioli jr |
13. Estimation of Broiler Chicken Mass using Computer Vision with Convolutional Neural NetworkIn poultry farming, monitoring bird mass during rearing is crucial, as it enables farmers to adjust parameters such as feed supply and lighting to better control weight gain. However, the methods currently used in poultry houses, i.e. manual weighing or poultry scales, present drawbacks, including the inability to weigh a representative number of birds or the frequent maintenance required to keep the equipment clean. The present work aims to validate an alternative method for estimating the m... I.D. Azevedo, A.T. Salton, R.D. Castro, L.V. Erthal |
14. Digital Transformation and Efficiency Gains in Intensive Livestock Systems: Evidence from Brazilian FeedlotsPrecision livestock farming has emerged as central strategies to enhance productive efficiency, reduce waste, and improve the sustainability of agricultural systems. In beef cattle feedlots, digital technologies such feeding automation sensors is particularly relevant. The technology reduces feed waste, improves the planning of input purchases and cost control, and reduces the need for manual labor for weighing and distributing feed, allowing the team to focus on strategic activities. In the ... L.C. David, M.J. Carrer, M. , H.M. Souza filho |
15. Automatic Detection of White Shrimp (Litopenaeus Vannamei) Feeding Activity Using Acoustic SignalsIn the cultivation of white shrimp (Litopenaeus vannamei), feeding management is one of the main challenges, accounting for approximately 40% to 60% of operational costs. Inaccurate feed management not only increases production costs but also compromises water quality, leading to environmental impacts. Shrimp produce acoustic events known as clicks, which makes it possible to use these signals as indicators of feeding activity. This study analyzes acoustic data collected ov... F. Costa filho, L. Affonso guedes, S. Peixoto, I. Sánchez-gendriz |
16. Comparative Evaluation of Ground Point Classifiers in LiDAR Point Clouds for DEM Generation in Pasture AreasThe classification of ground points in LiDAR point clouds is an essential step for generating reliable Digital Terrain Models (DTMs), particularly in livestock production systems based on pastures. Despite methodological advances in forested and urban environments, studies specifically addressing ground classification in pasture areas remain limited, where the proximity between the forage canopy and the ground surface makes altimetric distinction between classes challenging. The heterogeneous... |