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1. Assessment Of Physiological Effects Of Fungicides In WheatThe use of fungicides is one of the most widespread methods implemented in intensive crop production focused in solving phytosanitary problems. The use of fungicides belonging to groups such as strobilurins has been associated with positive physiological effects such as increased tolerance against abiotic stresses, changes in plant growth regulator activities and delayed leaf senescence. The use of thermography is a non- destructive method which permits to distinguish physiological changes caused... C. Berdugo, U. Steiner, E. Oerke, H. Dehne |
2. Use of Non-Invasive Sensors to Detect Beneficial Effects of Fungicides on Wheat PhysiologyDelay of leaf senescence is a beneficial side effect of fungicides several times studied on cereal crops. Strobilurins have been shown to extend the green leaf area duration (GLAD) for more than one week compared to untreated plants. The use of non-invasive sensors which allow to detect early changes in canopy pigmentation is an excellent method to assess the effect of fungicides on plant senescence. The objective of this study was to evaluate the effect of fungicides on wheat physiology by using... C.A. Berdugo, U. Steiner, E. Oerke, H. Dehne, A. Mahlein |
3. Remote Control System for Greenhouse Environment Using Mobile DevicesProtected crop production facilities such as greenhouse and plant factory have drawn interest and the area is increasing in Korea as well as in other countries in the world. Remote... S. Chung, K. Kim, H. Kim, J. Choi, Y. Zhang, S. Kang, K. han, S. Hur |
4. Thermography as Sensor for Downy Mildew on RosesDowny mildew caused by Peronospora sparsa is considered one of the most important diseases affecting cut roses under glass in the tropic. Under favorable... E. Oerke, H. Dehne, U. Steiner, S. Gómez |
5. Evaluation of Photovoltaic Modules at Different Installation Angles and Times of the DaySeveral electricity-consuming components for cooling and heating, illumination, ventilation, and irrigation are used to maintain proper environments of protected crop cultivation facilities. Photovoltaic system is considered as one of the most promising alternative power source for protected cultivation. Effects of environment,... S. Chung, J. Kong, Y. Huh, K. Bae, S. Hur, D. Lee, Y. Chae |
6. Determination of Sensor Locations for Monitoring of Greenhouse Ambient EnvironmentIn protected crop production facilities such as greenhouse and plant factory, f... S. Chung, K. Kim, Y. Huh, S. Hur, S. Ha, M. Ryu, H. kim, K. han |
7. Remote Sensing of Nitrogen and Water Status on Boston Lettuce Transplants in a Greenhouse EnvironmentRemote sensing is the stand-off collection through the use of a variety of devices for gathering information on a given object or area. Applied as a warning tool in plant stock production, it is expected to help in the achievement of better, more uniform and more productive organic cropping systems. Remote sensing of vegetation targets can be achieved from the... N. Tremblay, P. Vigneault, M.Y. Bouroubi, M. Dorais, G.P. Gianquinto, M. Tempesta |
8. A New Sensing System for Immediate and Direct Measurements of Soil NitrateIn-season management of nitrogen is a critical component in the drive to increase the nitrogen use efficiency of commercial crop production. Increasing nitrogen use efficiency itself has become a prominent issue due to both economic and environmental/regulatory drivers over the last decade. Solum, Inc (Mountain View, CA) has developed a new sensing technology to enable the immediate and direct measurement of soil nitrate. This allows rapid and economical soil... M. Preiner |
9. Field Moist Processing for Soil Analysis: Precision Measurement is Required for Precision ManagementIt has been well established over the last 50 years that many of the typical processes used by conventional soil analysis (such as drying and grinding the soil during preparation) can affect measured soil nutrient values. However, these processes have become conventional practice due to a lack of commercially viable methods of processing soil in its native field moist state. Solum, Inc (Mountain View, CA) has developed a process that allows routine, high throughput measurement... M. Preiner |
10. Thermal Sensing Of Roses Affected By Downy MildewDowny mildew caused by the oomycete Peronospora sparsa affects roses and is a serious problem in nurseries and cut roses in commercial greenhouses, especially in those without heating systems. The disease, which affects the quality and the yield of roses, develops fast under suitable environmental conditions. Currently it is controlled mainly by the application of foliar fungicides and removal of symptomatic plant material due to the limited availability of resistant cultivars... E. Oerke , H. Dehne, S. Gómez, U. Steiner |
11. Field-Based High-Throughput Phenotyping Approach For Soybean Plant ImprovementThe continued development of new, high yielding cultivars needed to meet the world’s growing food demands will be aided by improving the technology to rapidly phenotype potential cultivars. High-throughput phenotyping (HTP) is essential to maximize the greatest value of genetics analysis and to better understand the plant biology and physiology in view of a “Feed the World in 2050” theme. Field-based high-throughput phenotyping platform... L. Li, D. Jiang, R.P. Campos, Z. Lu, L.F. Tian |
12. Evaluating Leaf Fluorescence Sensor Dualex 4 For Estimating Rice Nitrogen Status In Northeast ChinaReal-time non-destructive diagnosis of crop nitrogen (N) status is crucially important for the success of in-season site-specific N management. Chlorophyll meter (CM) has been commonly used to non-destructively estimate crop leaf chlorophyll concentration, and indirectly estimate crop N status. Dualex 4 is a newly developed leaf fluorescence sensor that can estimate both leaf chlorophyll concentration and polyphenolics, especially flavonoids. When N is deficient, N stress can induce... W. Yu, Y. Miao, S. Hu, J. Shen, H. Wang |
13. A Comparison Of Performance Between UAV And Satellite Imagery For N Status Assessment In CornA number of platforms are available for the sensing of crop conditions. They vary from proximal (tractor-mounted) to satellites orbiting the Earth. A lot of interest has recently emerged from the access to unmanned aerial vehicles (UAVs) or drones that are able to carry sensors payloads providing data at very high spatial resolution. This study aims at comparing the performance of a UAV and satellite imagery acquired over a corn nitrogen response trial set-up. The nitrogen (N) response... P. Vigneault, N. Tremblay, M.Y. Bouroubi, C. Bélec, E. Fallon |
14. In-season Diagnosis of Rice Nitrogen Status Using Crop Circle Active Canopy Sensor and UAV Remote SensingActive crop canopy sensors have been used to non-destructively estimate nitrogen (N) nutrition index (NNI) for in-season site-specific N management. However, it is time-consuming and challenging to carry the hand-held active crop sensors and walk across large paddy fields. Unmanned aerial vehicle (UAV)-based remote sensing is a promising approach to overcoming the limitations of proximal sensing. The objective of this study was to combine unmanned aerial vehicle (UAV)-based remote sensing system... J. Lu, Y. Miao, Y. Huang, W. Shi |
15. Adjustment of Corn Population and Nitrogen Fertilization Based on Management ZonesThe main objective of this study was to adjust the corn population and nitrogen fertilization according to management zones, based on past grain yield maps (seven of soybean and three of corn) and soil electrical conductivity. The study was carried out in Não-Me-Toque, Rio Grande do Sul, Brazil, and it was conducted in a factorial strip blocks with 3 repetitions in each management zone, being the treatments: corn populations (56000, 64000, 72000, 80000 and 88000 plants ha-1),... R. Schwalbert, T.J. Carneiro amado, T. Horbe, G.M. Corassa, F.H. Gebert |
16. Within-field Profitability Assessment: Impact of Weather, Field Management and SoilsProfitability in crop production is largely driven by crop yield, production costs and commodity prices. The objective of this study was to quantify the often substantial yet somewhat illusive impact of weather, management, and soil spatial variability on within-field profitability in corn and soybean crop production using profitability indices for profit (net return) and return-on-investment (ROI) to produce estimates. We analyzed yield and cropping system data provided by 42 farmers within Central... P.M. Kyveryga, S. Fey, J. Connor, A. Kiel, D. Muth |
17. Comparative Benefits of Drone Imagery for Nitrogen Status Determination in CornRemotely sensed vegetation data provide an effective means of measuring the spatial variability of nitrogen and therefore of managing applications by taking intrafield variations into account. Satellites, drones and sensors mounted on agricultural machinery are all technologies that can be used for this purpose. Although a drone (or unmanned aerial vehicle [UAV]) can produce very high-resolution images, the comparative advantages of this type of imagery have not been demonstrated. The goal of... N. Tremblay, K. Khun, P. Vigneault, M.Y. Bouroubi, F. Cavayas, C. Codjia |
18. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPTAgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy |
19. Real-Time Control of Spray Drop ApplicationElectrostatic application of spray drops provides unique opportunities to precisely control the application of pesticides due to the additional electrostatic force on the spray drops, in addition to the normally seen forces of aerodynamic drag, gravity, and inertia. In this work, we develop a computational model to predict the spray drop trajectories. The model is validated through experiments with high speed photography of spray drop trajectories, and quantification of which trajectories lead... S. Post, M. Jermy, P. Gaynor, N. Kabaliuk, A. Werner |
20. An On-farm Experimental Philosophy for Farmer-centric Digital InnovationIn this paper, we review learnings gained from early On-Farm Experiments (OFE) conducted in the broadacre Australian grain industry from the 1990s to the present day. Although the initiative was originally centered around the possibilities of new data and analytics in precision agriculture, we discovered that OFEs could represent a platform for engaging farmers around digital technologies and innovation. Insight from interacting closely with farmers and advisors leads us to argue for a change... S. Cook, M. Lacoste, F. Evans, M. Ridout, M. Gibberd, T. Oberthur |
21. Prediction of Corn Economic Optimum Nitrogen Rate in ArgentinaStatic (i.e. texture and soil depth) and dynamic (i.e. soil water, temperature) factors play a role in determining field or subfield economically optimal N rates (EONR). We used 50 nitrogen (N) trials from Argentina at contrasting landscape positions and soil types, various soil-crop measurements from 2012 to 2017, and statistical techniques to address the following objectives: a) characterize corn yield and EONR variability across a multi-landscape-year study in central west Buenos Aires,... L. Puntel, A. Pagani, S. Archontoulis |
22. Site-Specific Management Zones Delineation Using Drone-Based Hyperspectral ImageryConventional techniques (e.g., intensive soil sampling) for site-specific management zones (MZ) delineation are often laborious and time-consuming. Using drones equipped with hyperspectral system can overcome some of the disadvantages of these techniques. The present work aimed to develop a drone-based hyperspectral imagery method to characterize the spatial variability of soil physical properties in order to delineate site-specific MZ. Canonical correlation analysis (CCA) was used to extract... H. Agili, K. Chokmani, A. Cambouris, I. Perron, J. Poulin |
23. Pest Detection on UAV Imagery Using a Deep Convolutional Neural NetworkPresently, precision agriculture uses remote sensing for the mapping of crop biophysical parameters with vegetation indices in order to detect problematic areas, and then send a human specialist for a targeted field investigation. The same principle is applied for the use of UAVs in precision agriculture, but with finer spatial resolutions. Vegetation mapping with UAVs requires the mosaicking of several images, which results in significant geometric and radiometric problems. Furthermore, even... Y. Bouroubi, P. Bugnet, T. Nguyen-xuan, C. Bélec, L. Longchamps, P. Vigneault, C. Gosselin |
24. Using an Unmanned Aerial Vehicle with Multispectral with RGB Sensors to Analyze Canola Yield in the Canadian PrairiesIn 2017 canola was planted on 9 million hectares in Canada surpassing wheat as the most widely planted crop in Canada. Saskatchewan is the dominant producer with nearly 5 million hectares planted in 2017. This crop, seen both as one of the highest-yielding and most profitable, is also one of most expensive and input-intensive for producers on the Canadian Prairies. In this study, the effect of natural and planted shelterbelts on canola yield was compared with canola yield... K. Hodge, L. Bainard, A. Smith, F. Akhter |
25. Snap Bean Flowering Detection from UAS Imaging SpectroscopySclerotinia sclerotiorum (white mold) is a fungus that infects the flowers of snap beans and causes a reduction in the number of pods, and subsequent yields, due to premature pod abscission. Snap bean fields typically are treated with prophylactic fungicide applications to control white mold, once 10% of the plants have at least one flower. The holistic goal of this research is to develop spatially-explicit white mold risk models, based on inputs from remote sensing systems aboard unmanned... E.W. Hughes, S.J. Pethybridge, C. Salvaggio, J. Van aardt, J.R. Kikkert |
26. Active Canopy Sensor-Based Precision Rice Management Strategy for Improving Grain Yield, Nitrogen and Water UseThe objective of this research was to develop an active crop sensor-based precision rice (Oryza sativa L.) management (PRM) strategy to improve rice yield, N and water use efficiencies and evaluate it against farmer’s rice management in Northeast China. Two field experiments were conducted from 2011 to 2013 in Jiansanjiang, Heilongjiang Province, China, involving four treatments and two varieties (Kongyu 131 and Longjing 21). The results indicated that PRM system significantly increased... J. Lu, H. Wang, Y. Miao |
27. Mapping Leaf Area Index of Maize in Tasseling Stage Based on Beer-Lambert Law and Landsat-8 ImageLeaf area index (LAI) is one of the important structural parameters of crop population, which could be used to monitor the variety of crop canopy structure and analyze photosynthesis rate. Mapping leaf area index of maize in a large scale by using remote sensing technology is very important for management of fertilizer and water, monitoring growth change and predicting yield. The Beer-Lambert law has been preliminarily applied to develop inversion model of crop LAI, and has achieved good application... X. Gu, S. Wang, G. Yang, X. Xu |
28. Estimating Corn Biomass from RGB Images Acquired with an Unmanned Aerial VehicleAbove-ground biomass, along with chlorophyll content and leaf area index (LAI), is a key biophysical parameter for crop monitoring. Being able to estimate biomass variations within a field is critical to the deployment of precision farming approaches such as variable nitrogen applications. With unprecedented flexibility, Unmanned Aerial Vehicles (UAVs) allow image acquisition at very high spatial resolution and short revisit time. Accordingly, there has been an increasing interest in... K. Khun, P. Vigneault, E. Fallon, N. Tremblay, C. Codjia, F. Cavayas |
29. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water StressesThis paper presents the results of the investigation on the effectiveness of UAV-based remote sensing data in determining lettuce nitrogen and water stresses. Multispectral images of the experimental lettuce plot at Cal Poly Pomona’s Spadra farm were collected from a UAV. Different rows of the lettuce plot were subject to different level of water and nitrogen applications. The UAV data were used in the determination of various vegetation indices. Proximal sensors used for ground-truthing... S. Bhandari, A. Raheja, M.R. Chaichi, R.L. Green, D. Do, M. Ansari, J.G. Wolf, A. Espinas, F.H. Pham, T.M. Sherman |
30. Precision Fall Urea Fertilizer Applications: Timing Impact on Carbon Dioxide, Ammonia Volatilization and Nitrous Oxide EmissionsTo minimize ammonia (NH3) volatilization and nitrous oxide (N2O) emissions from fall applied fertilizer, it is generally recommended to not apply the fertilizer until the soil temperature decreases below 10 C. However, this recommendation is not based on detailed measurements of NH3and N2O emissions. The objective of this study was to determine the influence of fertilizer application timing on nitrous oxide, carbon dioxide, and ammonia volatilization emissions. Nitrogen fertilizer was... S. Thies, D.E. Clay, S. Bruggeman, D. Joshi, S. Clay, J. Miller |
31. Survey Shows Specialty and Commodity Crop Retailers Use Precision Agriculture DifferentlyThe 2021 CropLife-Purdue Survey of precision agricultural practices by US agricultural input dealers serving the American grain and oilseed sector shows that most of them use GPS guidance and related technologies like sprayer boom control, most provide variable rate fertilizer services, and the majority say that fertilizer decisions are influenced by grower data. In contrast, dealers serving horticultural and specialty crop farms indicate comparatively modest adoption of many precision agriculture... B.J. Erickson, J. Lowenberg-deboer |
32. The ISO Strategic Advisory Group for Smart Farming: a Multi-pronged Opportunity for Greater Global InteroperabilityAgriculture is becoming increasingly complex and producers must secure their profitability, sustainability, and freedom to operate under a progressively more challenging set of constraints such as climate change, regulatory pressure, changes in consumer preferences, increasing cost of inputs, and commodity price volatility. We have not, however, yet reached the level of data interoperability required for a truly "smart" farming that can tackle the aforementioned problems... R. Ferreyra, J. Lehmann |
33. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather DataNitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by combining... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia |
34. Profitability of Regenerative Cropping with Autonomous Machines: an Ex-ante Assessment of a British Crop-livestock FarmFarmers, agroecological innovators and research have suggested mixed cropping as a way to promote soil health. Mixing areas of different crops in the same field is another form of precision agriculture's spatial and temporal management. The simplest form of mixed cropping is strip cropping. In conventional mechanized farming use of mixed cropping practices (i.e., strip cropping, pixel cropping) is limited by labour availability, rising wage rates, and management complexity. Regenerative agriculture... A. Al amin, J. Lowenberg-deboer, K.F. Franklin, E. Dickin, J. Monaghan, K. Behrendt |
35. Global Adoption of Precision Agriculture: an Update on Trends and Emerging TechnologiesThe adoption of precision agriculture (PA) has been mixed. Some technologies (e.g., Global Navigation Satellite System (GNSS) guidance) have been adopted rapidly worldwide wherever there is mechanized agriculture. Adoption of some of the original PA technologies introduced in the 1990s has been modest almost everywhere (e.g., variable rate fertilizer). New and more advanced technologies based on robotics, uncrewed aerial vehicles (UAVs), machine vision, co-robotic automation, and artificial intelligence... J. Mcfadden, B. Erickson, J. Lowenberg-deboer, G. Milics |
36. A Multi-objective Optimisation Analysis of Virtual Fencing in Precision GrazingVirtual fencing is a precision livestock farming tool consisting of invisible boundaries created via Global Navigation Satellite Systems (GNSS) and managed remotely and in real time by app-based technology. Grazing livestock are equipped with battery-powered collars capable of delivering audio or vibration cues and possibly electric shocks when approaching or crossing an invisible boundary. Virtual fencing makes precision grazing possible without the need for physical fences. This technology originated... E. Maritan, K. Behrendt, J. Lowenberg-deboer, S. Morgan, M.S. Rutter |
37. In-season Nitrogen Prediction Evaluation Using Airborne Imagery with AI Techniques in Commercial Potato ProductionIn modern agriculture, timely and precise nitrogen (N) monitoring is essential to optimize resource management and improve trade benefits. Potato (Solanum tuberosum L.) is a staple food in many regions of the world, and improving its production is inevitable to ensure food security and promote related industries. Traditional methods of assessing nitrogen are labour-intensive, time-consuming, and require subjective observations. To address these limitations, a combination of multispectral... B. Javed, A. Cambouris, M. Duchemin, L. Longchamps, P.S. Basran, S. Arnold, A. Fenech, A. Karam |
38. Data-driven Agriculture and Sustainable Farming: Friends or Foes?Sustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience. Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about synergies... O. Rozenstein, Y. Cohen, V. Alchanatis , K. Behrendt, D.J. Bonfil, G. Eshel, A. Harari, W.E. Harris, I. Klapp, Y. Laor, R. Linker, T. Paz-kagan, S. Peets, M.S. Rutter, Y. Salzer, J. Lowenberg-deboer |
39. Deposition Characteristics of Different Style Spray Tips at Varying Speeds and Altitudes from an Unmanned Aerial SystemThe application of pesticides with a UAS has become a popular practice over the past few years within crop production. The ability to carry larger volumes of liquid i onboard, reduced costs, and simple operation has attributed to the increased popularity. Additionally, the increased number of fungicide applications in corn due to the tar spot disease has shown that the demand for aerial applications of all types has increased with UAS pesticide application technology providing the opportunity... A. Leininger, K. Verhoff, K. Lovejoy, A. Thomas, G. Davis, A. Emmons, J.P. Fulton |
40. Estimating Water and Nitrogen Deficiency in Corn Using a Multi-parameter Proximal SensorThe Crop Circle Phenom (CCP) is an innovative integrated proximal sensor that can be potentially used to perform in-season diagnosis of nitrogen and water status. In addition to measuring spectral reflectance in several bands including the red, red edge, and near-infrared wavelengths, the CCP can also measure canopy and air temperatures and provides several parameters that can be associated with chlorophyll content, crop vigor, and water status. These capabilities differentiate the CCP from other... L. Lacerda, Y. Miao, V. Sharma, A. E. flores, A. Kechchour, J. Lu |
41. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote SensingFor irrigated corn fields, how to optimize nitrogen (N) and irrigation simultaneously is a great challenge. A promising strategy is to use remote sensing to diagnose corn N and water status during the growing season, which can then be used to guide in-season variable rate N application and irrigation management. The objective of this study was to evaluate the effectiveness of UAV multispectral and thermal remote sensing in simultaneous diagnosis of corn N and water status. Two field experiments... Y. Miao, A. Kechchour, V. Sharma, A. Flores, L. Lacerda, K. Mizuta, J. Lu, Y. Huang |
42. Creating Value from On-farm Research: Efields Data Workflow and Management Successes and ChallengesFarm operations today generate a large amount of data that can be difficult to properly manage. This challenge is further compounded when conducting on-farm research. The Ohio State University eFields program partners with farmers to conduct on-farm research and share results in a timely manner. Since 2017, the team has conducted and shared 987 trials across Ohio with the annual number of trials increasing from 45 to 292. This rapid increase has required development of a data workflow that streamlines... J.P. Fulton, D. Wilson, R. Tietje, E. Hawkins |
43. Evaluating Different Strategies to Analyze On-farm Precision Nitrogen Trial DataOn-farm trials are being conducted by more and more researchers and farmers. On-farm trials are very different to traditional small plot experiments due to the existence of significant within-field variability in soil-landscape conditions. Traditional statistical techniques like analysis of variance (ANOVA) are commonly adopted for on-farm trial analysis to evaluate overall performance of different treatments, assuming uniform environmental and management factors within a field. As a result, the... K. Mizuta, Y. Miao, J. Lu, R.P. Negrini |
44. Assessing the Variability in Cover Crop Growth Due to Management Practices and Biophysical Conditions Using a Mixed Modeling ApproachPlanting winter cover crops provides numerous agronomic and environmental benefits. Cereal rye, which is a commonly planted cover crop in Ohio, when established, offers advantages such as recycling residual nitrogen in the soil, enhancing soil organic matter, and reducing nutrient loss. However, understanding cover crop growth is challenging due to field management and weather conditions, and insights using traditional methods are limited. Remote sensing offers a cost-effective and timely alternative... K. Kc, S. Khanal, N. Bello, S. Culman |
45. On-farm Evaluation of a Satellite Remote Sensing-based Precision Nitrogen Management StrategyImproper management of nitrogen (N) fertilizers in the cropping systems of the U.S. Midwest has resulted in significant N leaching into the Mississippi River Basin that flows to the Gulf of Mexico. The majority of the U.S. Midwest states need to develop a plan for a nutrient loss reduction strategy to decrease N and phosphorous loadings into waters and the Gulf of Mexico by 45% by 2050. In Minnesota, high nitrate concentration and loads have not been significantly reduced in surface and ground... J. Lu, Y. Miao, C.J. Ransom, F. Fernández |
46. Lameness Detection in Dairy Cattle Using GPS and Accelerometers Wearable SensorsLameness significantly impacts cow health and welfare on dairy farms, yet identifying lamecows remains challenging. Wearable sensors like GPS and accelerometers show promise for automated lameness detection, but their effectiveness outdoors is still unclear. Therefore, there are gaps in understanding their applicability and the necessary features for outdoor settings. Additionally, it is uncertain whether environmental factors, such as temperature and time of day, influence their the model performance,... N. Mhlongo, H. De knegt, W.F. De boer, F. Van langevelde |