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Kabir, M.S
Pitla, S
Rew, L.J
Walsh, K
Fisher, D.K
Do, D
Li, S
Reddy, K
Jiménez Castaño, V
Glewen, K
Williams, E
Bhattarai, A
Kocks, C
Anderson Guerrero, S
Acquah, H.D
Hassan, M
Gadler, D.J
Bonfil, D.J
Langrock, M
Fassana, N
Duhachek, G
CAMPOS, J
Codjia, C
Wang, N
Custer, S
Gill, N
Cloutier, G
Lidauer, L
Jensen, K
Griffin, T.W
Cendrero Mateo, M.P
R, P
Figueiredo, G.K
Lebeau, F
Andersen, P
Flores, P.J
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Authors
Wagner, P
Langrock, M
Shanwad, U.K
Patil, M.B
H, V
B.G , M
R, P
N.L. , R
S, S
Khosla, R
Patil, V.C
Bøgild, A
Nielsen, S.H
Jacobsen, N.J
Jager-Hansen, C
Jørgensen, R.N
Jensen, K
Jørgensen, O.J
Ortiz, B
Thomson, S.J
Huang, Y
Reddy, K
Gonzalez-Mora, J
Vallespi Gonzalez, C
Ehsani, R
Dima, C.S
Duhachek, G
Feher, T
Kocks, C
Kempenaar, C
Westerdijk, K
Linker, R
Payne, A
Walsh, K
Cohen, O
Rew, L.J
Maxwell, B.D
Lawrence, P.G
Horneck, D.A
Gadler, D.J
Bruce, A.E
Turner, R.W
Spinelli, C.B
Brungardt, J.J
Hamm, P.B
Hunt, E
Andriamandroso, A
Dumont, B
Lebeau, F
Bindelle, J
Bosompem, M
Kwarteng, J.A
Acquah, H.D
Muller, O
Cendrero Mateo, M.P
Albrecht, H
Pinto, F
Mueller-Linow, M
Pieruschka, R
Schurr, U
Rascher, U
Schickling, A
Keller, B
Huang, Y
Brand, H
Pennington, D
Reddy, K
Thomson, S.J
Rund, Q
Murrell, S
Erbe, A
Williams, R
Williams, E
Williams, E
Tremblay, N
Khun, K
Vigneault, P
Bouroubi, M.Y
Cavayas, F
Codjia, C
Luck, J
Parrish, J
Thompson, L
Krienke, B
Glewen, K
Ferguson, R.B
Griffin, T.W
Lambert, D.M
Lowenberg-DeBoer, J
Griffin, T.W
G.M. Florax, R.J
Lowenberg-DeBoer, J
Bonfil, D.J
Mufradi, I
Asido, S
Long, D.S
Bonfil, D.J
Mufradi, I
Asido, S
Long, D.S
Taylor, R.K
Bennur, P
Solie, J.B
Wang, N
Weckler, P
Raun, W.R
Thomson, S.J
DeFauw, S.L
English, P.J
Hanks, J.E
Fisher, D.K
Foster, P.N
Zimba, P.V
Yang, L
Huang, L
Meng, L
Wang, J
Wu, D
Fu, X
Li, S
Roland, L
Lidauer, L
Sattlecker, G
Kickinger, F
Auer, W
Sturm, V
Efrosinin, D
Drillich, M
Iwersen, M
Berger, A
Iwersen, M
Reiter, S
Schweinzer, V
Kickinger, F
Öhlschuster, M
Lidauer, L
Auer, W
Drillich, M
Berger, A
Krieger, S
Oczak, M
Lidauer, L
Kickinger, F
Öhlschuster, M
Auer, W
Drillich, M
Iwersen, M
Berger, A
Schweinzer, V
Lidauer, L
Kickinger, F
Öhlschuster, M
Auer, W
Drillich, M
Iwersen, M
Berger, A
Berger, A.G
Hoffman, E
Fassana, N
Alfonso, F
Swe, K.M
Kim, Y
Jeong, D
Lee, S
Chung, S
Kabir, M.S
Rydahl, P
Jorgensen, R.N
Dyrmann, M
Jensen, N
Sorensen, M.D
Bojer, O.M
Andersen, P
Khun, K
Vigneault, P
Fallon, E
Tremblay, N
Codjia, C
Cavayas, F
Bhandari, S
Raheja, A
Chaichi, M.R
Green, R.L
Do, D
Ansari, M
Wolf, J.G
Espinas, A
Pham, F.H
Sherman, T.M
Boatswain Jacques, A.A
Adamchuk, V.I
Cloutier, G
Clark, J.J
Miller, C
Rydahl, P
Boejer, O
Jensen, N
Hartmann, B
Jorgensen, R
Soerensen, M
Andersen, P
Paz, L
Nielsen, M.B
Lin, Z
Guo, W
Gill, N
Pereira, F.R
Dos Reis, A.A
Freitas, R.G
Oliveira, S.R
Amaral, L.R
Figueiredo, G.K
Antunes, J.F
Lamparelli, R.A
Moro, E
Pereira, N.D
Magalhães, P.S
Pereira, F.R
Lima, J.P
Freitas, R.G
Dos Reis, A.A
Amaral, L.R
Figueiredo, G.K
Lamparelli, R.A
Pereira, J.C
Magalhães, P.S
Mathew, J.J
Flores, P.J
Stenger, J
Miranda, C
Zhang, Z
Das, A.K
Fulton, J.P
Hawkins, E
Shearer, S
Klopfenstein, A
Hartschuh, J
Custer, S
Gil, E
Garcia-Ruíz, F
BISCAMPS, J
SALCEDO, R
CAMPOS, J
Munar-Vivas, O.J
Anderson Guerrero, S
Angrino Chiran, D.F
Mateus-Rodriguez, J.F
Shi, Y
Islam, M
Steele, K
Luck, J.D
Pitla, S
Ge, Y
Jhala, A
Knezevic, S
Joseph, K
Pitla, S
Muvva, V
Sánchez Virosta, Ã
Gómez-Candón, D
Montoya Sevilla, F
Pérez García, Y
Jiménez Castaño, V
González Piqueras, J
López-Urrea, R
Sánchez Tomás, J
Balabantaray, A
Pitla, S
Behera, S
Pitla, S
Muvva, V
Mwunguzi, H
Pitla, S
Joseph, K
Liew, C
Pitla, S
Kalra, A
Pitla, S
Luck, J.D
Hassan, M
Jakhar, A
Bhattarai, A
Bastos, L
Scarpin, G
Topics
Modeling and Geo-statistics
Food Security and Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Precision Horticulture
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Profitability, Sustainability and Adoption
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Precision Dairy and Livestock Management
Profitability, Sustainability and Adoption
Precision Agriculture and Climate Change
Remote Sensing Applications in Precision Agriculture
Big Data Mining & Statistical Issues in Precision Agriculture
Unmanned Aerial Systems
Sensor Application in Managing In-season Crop Variability
Profitability, Adoption and Performance Evaluation
Modelling and Geo-Statistics
Precision Management / Precision Conservation
Remote Sensing for Nitrogen Management
Remote Sensing Application / Sensor Technology
Precision Crop Protection
Precision Dairy and Livestock Management
In-Season Nitrogen Management
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Applications of Unmanned Aerial Systems
Robotics, Guidance and Automation
Precision Crop Protection
Applications of Unmanned Aerial Systems
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Precision Agriculture and Global Food Security
Precision Crop Protection
Geospatial Data
Drone Spraying
Artificial Intelligence (AI) in Agriculture
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Robotics and Automation with Row and Horticultural Crops
Big Data, Data Mining and Deep Learning
Precision Agriculture and Global Food Security
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results52 paper(s) found.

1. Determination Of Crop Injury From Aerial Application Of Glyphosate Using Vegetation Indices And Geostatistics

Injury to crops caused by off-target drift of glyphosate can seriously reduce growth and yield, and is of great concern to farmers and aerial applicators. Determining an indirect method for assessing the levels and extent of crop injury could support management decisions. The objectives of this study were to evaluate multiple vegetation indices (VIs) as surrogate variables for glyphosate injury identification and to evaluate the combined use of Geostatistical methods and the VIs to assess... B. Ortiz, S.J. Thomson, Y. Huang, K. Reddy

2. HLB Detection Using Hyperspectral Radiometry

The need for sustainable agriculture requires the adoption of low input, long-term and cost-effective strategies to overcome the adverse impact of disease and nutritional deficiencies on citrus groves. In this context, early detection of diseased trees has become an important topic in the citrus industry. Multiple factors make field assessment of disease conditions a challenging task: the non-specific nature of many symptoms, the possibility of having localized affections in only certain areas... J. Gonzalez-mora, C. Vallespi gonzalez, R. Ehsani, C.S. Dima, G. Duhachek

3. Statistical Procedure to Compare Farming Procedures with the Observation of Spatial Trends and Correlations in On-Farm Research

Modern management and machines have been introduced on a demonstration farm in Ganhe (China). This has led to new methods of cultivation with effects on yields, cost structure and thus also on the economic success of the farm. These effects should be tested with the help of an on-farm trial. The cultivation methods differed in the equipment used, plant protection and fertilisation strategies. In contrast to classical field trials, normal working practice farm machinery and fields are used in on-farm... P. Wagner, M. Langrock

4. Precision Agriculture Initiative for Karnataka – A New Direction for Strengthening Farming Community

Strengthening agriculture is crucial to meet the myriad challenges of rural poverty, food security, unemployment, and sustainability of natural resources and it also needs strengthening at technical, financial and management levels. In this context... U.K. Shanwad, M.B. Patil, V. H, M. B.g , P. R, R. N.l. , S. S, R. Khosla, V.C. Patil

5. A Low Cost, Modular Robotics Tool Carrier for Precision Agriculture Research

Current research within agricultural crop production focus on using autonomous robot technology to optimize the production efficiency, enhance sustainability and minimize tedious, monotonous and wearing tasks. But progress is slow partly... A. Bøgild, S.H. Nielsen, N.J. Jacobsen, C.L. Jaeger-hansen, R.N. Jørgensen, K. Jensen, O.J. Jørgensen

6. First Results Of Development Of A Smart Farm In The Netherlands

GNSS technology has been introduced on about 20 % of the Dutch arable farms in The Netherlands today. Use of sensor technology is also slowly but gradually being adopted by farmers, providing them large amounts of digital data on soil, crop and climate conditions. Typical data are spatial variation in soil organic matter, crop biomass, crop yield, and presence of pests and diseases. We still have to make major steps to use all this data in a way that agriculture becomes more sustainable. We... T. Feher, C. Kocks, C. Kempenaar, K. Westerdijk

7. Detection Of Fruit In Canopy Night-Time Images: Two Case Studies With Apple And Mango

Reliable estimation of the expected yield remains a major challenge in orchards. In a recent work we reported the development of an algorithm for estimating the number of fruits in images of apple trees acquired in natural daylight conditions. In the present work we tested this approach with night-time images of similar apple trees and further adapted this approach to night-time images of mango trees. Working with the apple images required only... R. Linker, A. Payne, K. Walsh, O. Cohen

8. Optimizing Site-Specific Adaptive Management Using A Probabilistic Framework: Evaluating Model Performance Using Historic Data

     Agricultural producers are tasked with managing crop yield responses to nitrogen (N) within systems that have high levels of spatial (biophysical), climatic, and price uncertainty. To date, the outcome of most variable rate application (VRA) research has focused on the spatial dimension, proposing optimal fertilizer prescription maps that can be applied year after year. However, temporally static prescriptions can result in suboptimal outcomes, particularly if they do... L.J. Rew, B.D. Maxwell, P.G. Lawrence

9. Detection Of Nitrogen Deficiency In Potatoes Using Small Unmanned Aircraft Systems

  Small Unmanned Aircraft Systems (sUAS) are recognized as potentially important remote-sensing platforms for precision agriculture. A nitrogen rate experiment was established in 2013 with ‘Ranger Russet’ potatoes by applying four rates of nitrogen fertilizer (112, 224, 337, and 449 kg N/ha) in a randomized block design with 3 replicates. A Tetracam Hawkeye sUAS and Agricultural Digital Camera Lite sensor were used to collect imagery with near-infrared... D.A. Horneck, D.J. Gadler, A.E. Bruce, R.W. Turner, C.B. Spinelli, J.J. Brungardt, P.B. Hamm, E. Hunt

10. The Performance Of Mobile Devices' Inertial Measurement Unit For The Detection Of Cattle's Behaviors On Pasture

Over the past decade, the Precision Livestock Farming (PLF) concept has taken a considerable place in the development of accurate methods for a better management of farm animals. The recent technological improvements allow the raising of numerous motion sensors such as accelerometers and GPS tracking. Several studies have shown the relevancy of these sensors to distinguish the animals’ behavior using various classification techniques such as neuronal networks or multivariate... A. Andriamandroso, B. Dumont, F. Lebeau, J. Bindelle

11. Determinants of Ex-ante Adoption of Precision Agriculture Technologies by Cocoa Farmers in Ghana

The study was to identify the best predictors of cocoa Farmers willingness to adopt future Precision Agriculture Technology (PAT) Development in Ghana. Correlational research design was used. The target population was all cocoa farmers who benefited from Cocoa High Technology Programme (an initiative of distributing free fertilizer by government to cocoa farmers) in Ghana. Multistage sampling technique was used to select 422 out of 400,000 cocoa farmers in the six (6) out of the seven (7) cocoa... M. Bosompem, J.A. Kwarteng, H.D. Acquah

12. Field Phenotyping Infrastructure in a Future World - Quantifying Information on Plant Structure and Function for Precision Agriculture and Climate Change

Phenotyping in the field is an essential step in the phenotyping chain. Phenotyping begins in the well-defined, controlled conditions in laboratories and greenhouses and extends to heterogeneous, fluctuating environments in the field. Field measurements represent a significant reference point for the relevance of the laboratory and greenhouse approaches and an important source of information on potential mechanisms and constraints for plant performance tested at controlled conditions. In this... O. Muller, M.P. Cendrero mateo, H. Albrecht, F. Pinto, M. Mueller-linow, R. Pieruschka, U. Schurr, U. Rascher, A. Schickling, B. Keller

13. Assessing Soybean Injury from Dicamba Using RGB and CIR Images Acquired on Small UAVs

Dicamba is an herbicide used for postemegence control of several broadleaf weeds in corn, grain sorghum, small grains, and non-cropland. Currently, dicamba-tolerant (DT) soybean and cotton are under development, which provide new options to combat weeds resistant to glyphosate, the most widely used herbicide.  With the use of DT-trait cotton and soybean, off-target dicamba drift onto susceptible crops will become a concern. To relate soybean injury to different rates of dicamba applications,... Y. Huang, H. Brand, D. Pennington, K. Reddy, S.J. Thomson

14. North American Soil Test Summary

With the assistance and cooperation of numerous private and public soil testing laboratories, the International Plant Nutrition Institute (IPNI) periodically summarizes soil test levels in North America (NA). Soil tests indicate the relative capacity of soil to provide nutrients to plants. Therefore, this summary can be viewed as an indicator of the nutrient supplying capacity or fertility of soils in NA. This is the eleventh summary completed by IPNI or its predecessor, the Potash &... Q. Rund, S. Murrell, A. Erbe, R. Williams, E. Williams

15. Time Series Analysis of Vegetation Dynamics and Burn Scar Mapping at Smoky Hill Air National Guard Range, Kansas Using Moderate Resolution Satellite Imagery

Military installments are import assets for the proper training of armed forces. To ensure the continued viability of the training grounds, management practices need to be implemented to sustain the necessary environmental conditions for safe and effective training. This analysis uses satellite imagery over time to gain insight into vegetation conditions over a large military installment. MODIS imagery was collected multiple times a year for 11 years at Smoky Hill Air National Guard Range (Smoky... E. Williams

16. Comparative Benefits of Drone Imagery for Nitrogen Status Determination in Corn

Remotely 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

17. Liquid Flow Control Requirements for Crop Canopy Sensor-Based N Management in Corn: A Project SENSE Case Study

While on-farm adoption of crop canopy sensors for directing in-season nitrogen (N) application has been slow, research focused on these systems has been significant for decades. Much emphasis has been placed on developing and testing algorithms based on sensor output to predict N needs, but little information has been published regarding liquid flow control requirements on equipment used in conjunction with these sensing systems. Addition of a sensor-based system to a standard spray rate controller... J. Luck, J. Parrish, L. Thompson, B. Krienke, K. Glewen, R.B. Ferguson

18. Economics of Gps-enabled Navigation Technologies

To address the economic feasibility of global positioning system (GPS) enabled navigation technologies including automated guidance and lightbar, a linear programming model was formulated using data from Midwestern U.S. Corn Belt farms. Five scenarios were compared: (i) a baseline scenario with foam, disk or other visual marker reference, (ii) lightbar navigation with basic GPS availability (+/-3 dm accuracy), (iii) lightbar with satellite subscription correction GPS (+/-1 dm), (iv) automated... T.W. Griffin, D.M. Lambert, J. Lowenberg-deboer

19. Evaluating Spatial Effects Induced by Alternative On- Farm Trial Experimental Designs with Cross-regressive Variables Using Monte Carlo Methods

The goal of this research was to adapt spatial regression methods to on-farm trials in a farm management context. Different experimental designs and statistical analysis methods are tested with site-specific data under a range of spatial autocorrelation levels using Monte Carlo simulation techniques. Simulations indicated that data usable for farm management decision making could be gathered from limited replication experimental designs if that data were analyzed with the appropriate spatial statistical... T.W. Griffin, R.J. G.m. florax, J. Lowenberg-deboer

20. Precision Nitrogen Management Based on Nitrogen Removal in Rainfed Wheat

Growers of hard red spring wheat may capture price premiums for maximizing the protein concentration of their grain. Nitrogen (N) nutrition adequacy is crucial to achieving high grain protein concentration. The objective of this study was to determine the usefulness of N removal maps by comparing grain protein, yields, and dollar returns obtained from this precision N management approach with that from conventional uniform N management. Strip plot experiments were designed to compare spatially... D.J. Bonfil, I. Mufradi, S. Asido, D.S. Long

21. On-combine Near Infrared Spectroscopy Applied to Prediction of Grain Test Weight

Whole grain near infrared (NIR) spectroscopy is a widely accepted method for analysis of the protein and moisture contents of grain, but is seldom applied to predict test weight. Test weight is a widely used specification for grading of wheat and predictor of flour yield. The objective of this study was to determine whether NIR spectroscopy could be used for measuring the test weight of grain. Reference grain samples of hard red spring wheat were obtained from dryland fields in the semiarid Negev... D.J. Bonfil, I. Mufradi, S. Asido, D.S. Long

22. Controller Performance Criteria for Sensor Based Variable Rate Application

Sensor based variable rate application of crop inputs provides unique challenges for traditional rate controllers when compared to map based applications. The controller set point is typically changing every second whereas with a map based systems the set point changes much less frequently. As applied data files for a sensor based variable rate nitrogen applicator were obtained from a wheat field in north central Oklahoma. These data were analyzed to determine the magnitude and frequency of rate... R.K. Taylor, P. Bennur, J.B. Solie, N. Wang, P. Weckler, W.R. Raun

23. Thermal Characterization and Spatial Analysis of Water Stress in Cotton (Gossypium Hirsutum L.) and Phytochemical Composition Related to Water Stress in Soybean (Glycine Max)

Studies were designed to explore spatial relationships of water and/or heat stress in cotton and soybeans and to assess factors that may influence yield potential. Investigations focused on detecting the onset of water/heat stress in row crops using thermal and multispectral imagery with ancillary physicochemical data such as soil moisture status and photosynthetic pigment concentrations. One cotton field with gradations in soil texture showed distinct patterns in thermal imagery, matching patterns... S.J. Thomson, S.L. Defauw, P.J. English, J.E. Hanks, D.K. Fisher, P.N. Foster, P.V. Zimba

24. Rapid Identification of Mulberry Leaf Pests Based on Near Infrared Hyperspectral Imaging

As one of the most common mulberry pests, Diaphania pyloalis Walker (Lepidoptera: Pyralididae) has occurred and damaged in the main sericulture areas of China. Naked eye observation, the most dominating method identifying the damage of Diaphania pyloalis, is time-wasting and labor consuming. In order to improve the identification and diagnosis efficiency and avoid the massive outbreak of Diaphania pyloalis, near infrared (NIR) hyperspectral imaging technology combined with partial least discriminant... L. Yang, L. Huang, L. Meng, J. Wang, D. Wu, X. Fu, S. Li

25. A Pilot Study on Monitoring Drinking Behavior in Bucket Fed Dairy Calves Using an Ear-Attached Tri-Axial Accelerometer

Accelerometers support the farmer with collecting information about animal behavior and thus allow a reduction in visual observation time. The milk intake of calves fed by teat-buckets has not been monitored automatically on commercial farms so far, although it is crucial for the calves’ development. This pilot study was based on bucket-fed dairy calves and intended (1) to evaluate the technical feasibility of using an ear-attached accelerometer (SMARTBOW, Smartbow GmbH, Weibern, Austria)... L. Roland, L. Lidauer, G. Sattlecker, F. Kickinger, W. Auer, V. Sturm, D. Efrosinin, M. Drillich, M. Iwersen, A. Berger

26. Evaluation of an Ear Tag Based Accelerometer for Monitoring Rumination Time, Chewing Cycles and Rumination Bouts in Dairy Cows

The objective of this study was to evaluate the ear tag based accelerometer SMARTBOW (Smartbow, Weibern, Austria) for detecting rumination time, chewing cycles and rumination bouts in dairy cows. For this, the parameters were determined by analyses of video recordings as reference and compared with the results of the accelerometer system. Additionally, the intra- and inter-observer reliability as well as the agreement of direct cow observations and video recordings was tested. Ten Simmental cows... M. Iwersen, S. Reiter, V. Schweinzer, F. Kickinger, M. Öhlschuster, L. Lidauer, W. Auer, M. Drillich, A. Berger

27. Ear-Attached Accelerometer as an On-Farm Device to Predict the Onset of Calving in Dairy Cows

The objective of this study on an ear-attached accelerometer in dairy cows was (1) to determine activity, rumination and lying time of the dams prior to calving, and include group level of measured variables (2) use the data to develop an algorithm to predict calving and (3) to test the performance of this algorithm. Video observations (24h/d) were used as reference for these events. Four weeks before expected calving, an ear-tag integrated tri-axial accelerometer (SMARTBOW system) was attached... S. Krieger, M. Oczak, L. Lidauer, F. Kickinger, M. Öhlschuster, W. Auer, M. Drillich, M. Iwersen, A. Berger

28. Evaluation of the Ear-Tag Sensor System SMARTBOW for Detecting Estrus Events in Indoor Housed Dairy Cows

Livestock farming technologies have a tremendous potential to improve and support farmers in herd management decisions, in particular in reproductive management. Nowadays, estrus detection in cows is challenging and many detection tools are available. The company Smartbow (Weibern, Austria) developed a novel ear-tag sensor, which consists of a 3D-accelerometer that records head and ear movements of cows as basis for algorithm development and further analyses. Estrus detection by the SMARTBOW system... V. Schweinzer, L. Lidauer, F. Kickinger, M. Öhlschuster, W. Auer, M. Drillich, M. Iwersen, A. Berger

29. Active Canopy Sensors for the Detection of Non-Responsive Areas to Nitrogen Application in Wheat

Active canopy sensors offer accurate measurements of crop growth status that have been used in real time to estimate nitrogen (N) requirements. NDVI can be used to determine the absolute amount of fertilizer requirement, or simply to distribute within the field an average rate defined by decision models using other diagnostics. The objective of this work was to evaluate the capacity of active canopy sensors to determine yield and N application requirements within a site at jointing stage (Feeks... A.G. Berger, E. Hoffman, N. Fassana, F. Alfonso

30. Sensor Comparison for Yield Monitoring Systems of Small-Sized Potato Harvesters

Yield monitoring of potato in real time during harvesting would be useful for farmers, providing instant yield and income information. In the study, potentials of candidate sensors were evaluated with different yield measurement techniques for yield monitoring system of small-sized potato harvesters. Mass-based (i.e., load cell) and volume-based (i.e., CCD camera) sensors were selected and tested under laboratory conditions. For mass-based sensing, an impact plate instrumented with load cells... K.M. Swe, Y. Kim, D. Jeong, S. Lee, S. Chung, M.S. Kabir

31. Spatial Variability of Optimized Herbicide Mixtures and Dosages

Driven by 25 years of Danish, political 'pesticide action plans', aiming at reducing the use of pesticides, a Danish Decision Support System (DSS) for Integrated Weed Management (IWM) has been constructed. This online tool, called ‘IPMwise’ is now in its 4th generation. It integrates the 8 general IPM-principles as defined by the EU. In Denmark, this DSS includes 30 crops, 105 weeds and full assortments of herbicides. Due to generic qualities in both the integrated... P. Rydahl, R.N. Jorgensen, M. Dyrmann, N. Jensen, M.D. Sorensen, O.M. Bojer, P. Andersen

32. Estimating Corn Biomass from RGB Images Acquired with an Unmanned Aerial Vehicle

Above-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

33. Effectiveness of UAV-Based Remote Sensing Techniques in Determining Lettuce Nitrogen and Water Stresses

This 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

34. Development of a Machine Vision Yield Monitor for Shallot Onion Harvesters

Crop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer vision have improved the detection, quality assessment and yield estimation processes for crops, including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have not yet been fully developed.... A.A. Boatswain jacques, V.I. Adamchuk, G. Cloutier, J.J. Clark, C. Miller

35. Economic Potential of RoboWeedMaps - Use of Deep Learning for Production of Weed Maps and Herbicide Application Maps

In Denmark, a new IPM ‘product chain’ has been constructed, which starts with systematic photographing of fields and ends up with field- or site-specific herbicide application. A special high-speed camera, mounted on an ATV took sufficiently good pictures of small weed plants, while driving up to 50 km/h. Pictures were uploaded to the RoboWeedMaps online platform, where appointed internal- and external persons with agro-botanical experience executed ‘virtual field inspection’... P. Rydahl, O. Boejer, N. Jensen, B. Hartmann, R. Jorgensen, M. Soerensen, P. Andersen, L. Paz, M.B. Nielsen

36. Cotton Boll Detection and Yield Estimation Using UAS Lidar Data and RGB Image

Cotton boll distribution is a critical phenotypic trait that represents the plant's response to its environment. Accurate quantification of boll distribution provides valuable information for breeding cultivars with high yield and fiber quality. Manual methods for boll mapping are time-consuming and labor-intensive. We evaluated the application of Lidar point cloud and RGB image data in boll detection and distribution and yield estimation. Lidar data was acquired at 15 m using a DJI Matrice... Z. Lin, W. Guo, N. Gill

37. A Framework for Imputation of Missing Parts in UAV Orthomosaics Using Planetscope and Sentinel-2 Data

In recent years, the emergence of Unmanned Aerial Vehicles (UAV), also known as drones, with high spatial resolution, has broadened the application of remote sensing in agriculture. However, UAV images commonly have specific problems with missing areas due to drone flight restrictions. Data mining techniques for imputing missing data is an activity often demanded in several fields of science. In this context, this research used the same approach to predict missing parts on orthomosaics obtained... F.R. Pereira, A.A. Dos reis, R.G. Freitas, S.R. Oliveira, L.R. Amaral, G.K. Figueiredo, J.F. Antunes, R.A. Lamparelli, E. Moro, N.D. Pereira, P.S. Magalhães

38. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 Imagery

Pasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of the... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães

39. Comparative Analysis of Light-weight Deep Learning Architectures for Soybean Yield Estimation Based on Pod Count from Proximal Sensing Data for Mobile and Embedded Vision Applications

Crop yield prediction is an important aspect of farming and food-production. Therefore, estimating yield is important for crop breeders, seed-companies, and farmers to make informed real-time financial decisions. In-field soybean (Glycine max L.(Merr.)) yield estimation can be of great value to plant breeders as they screen thousands of plots to identify better yielding genotypes that ultimately will strengthen national food security. Existing soybean yield estimation tools,... J.J. Mathew, P.J. Flores, J. Stenger, C. Miranda, Z. Zhang, A.K. Das

40. Nitrogen Placement Considerations for Maize Production in the Eastern US Cornbelt

Proper fertilizer placement is essential to optimize crop performance and amount of applied nitrogen (N) along with crop yield potential. There exists several practices currently used in both research within farming operations on how and when to apply N to maize (Zea mays L). Split applications of N in Ohio is popular with farmers and provides an economic benefit but more recently some farmers have been using mid- and late-season N fertilizer applications for their maize production. ... J.P. Fulton, E. Hawkins, S. Shearer, A. Klopfenstein, J. Hartschuh, S. Custer

41. Variable Rate Application to Improve Cro Protection in Orchards and Vineyards. Prescription Maps and Satellites to Accomplish EU Farm to Fork Strategy

Accurate canopy characterization is crucial for a targeted application of plant protection products following variable rate application (VRA) concept. Remote sensing offers a robust and rapid monitoring tool that allows determining the characteristics of the vegetation from aerial platforms at different spatial resolutions. Previous work have demonstrated that drone-based imagery can be used to estimate canopy height, width, and canopy volume accurately enough to allow a full automation of VRA... E. Gil, F. Garcia-ruíz, J. Biscamps, R. Salcedo, J. Campos

42. Use of Radar SAR Images to Assess Soil Moisture in Cane Crops: Practical Implications in Agricultural Operation

Sugar cane cultivation in the geographical region of the Cauca River Valley is a key industry for the local economy. However, this crop faces constant challenges related to the management of agricultural machinery for soil cultivation in conditions of high soil moisture. In this context, the synthetic aperture radar (SAR Radar) of the Sentinel 1 satellite emerges as a promising technology. The purpose of this work is to explore the use of the Sentinel 1 satellite SAR radar sensor in sugarcane... O.J. Munar-vivas, S. Anderson guerrero, D.F. Angrino chiran, J.F. Mateus-rodriguez

43. Onboard Weed Identification and Application Test with Spraying Drone Systems

Commercial spraying drone systems nowadays have the ability to implement variable rate applications according to pre-loaded prescription maps. Efforts are needed to integrate sensing and computing technologies to realize on-the-go decision making such as those on the ground based spraying systems. Besides the understudied subject of drone spraying pattern and efficacy, challenges also exist in the decision making, control, and system integration with the limits on payload and flight endurance... Y. Shi, M. Islam, K. Steele, J.D. Luck, S. Pitla, Y. Ge, A. Jhala, S. Knezevic

44. Obstacle-aware UAV Flight Planning for Agricultural Applications

The use of unmanned aerial vehicles (UAVs) has emerged as one of the most important transformational tools in modern agriculture, offering unprecedented opportunities for crop monitoring, management, and optimization. To ensure effective and safe navigation in agricultural environments, robust obstacle avoidance capabilities are required to mitigate collision risks and to ensure efficient operations. Mission planners for UAVs are typically responsible for verifying that the vehicle is following... K. Joseph, S. Pitla, V. Muvva

45. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming Context

The increasing expansion of irrigated almond orchards in regions of southeast Spain, facing water scarcity, underscores the need for a more effective and precise monitoring of the crop water status to optimize irrigation scheduling and improve crop water use efficiency. Remote and proximal sensing, combining visible, multispectral and thermal capabilities at different scales allows to estimate water needs, detect and quantify crop water stress, or identify different productivity zones within an...

46. AI Enabled Targeted Robotic Weed Management

In contemporary agriculture, effective weed management presents a considerable challenge necessitating innovative solutions. Traditional weed control methods often rely on the indiscriminate application of broad-spectrum herbicides, giving rise to environmental concerns and unintended crop damage. Our research addresses this challenge by introducing an innovative AI-enabled robotic system designed to identify and selectively target weeds in real-time. Utilizing the advanced Machine Learning technique... A. Balabantaray, S. Pitla

47. Advancements in Agrivoltaics: Autonomous Robotic Mowing for Enhanced Management in Solar Farms

Agrivoltaics – the co-location of solar energy installations and agriculture beneath or between rows of photovoltaic panels – has gained prominence as a sustainable and efficient approach to land use. The US has over 2.8 GW in Agrivoltaics, integrating crop cultivation with solar energy. However, effective vegetation management is critical for solar panel efficiency. Flat, sunny agricultural land accommodates solar panels and crops efficiently. The challenge lies in managing grass... S. Behera, S. Pitla

48. Implementation of Autonomous Material Re-filling Using Customized UAV for Autonomous Planting Operations

This project introduces a groundbreaking use case for customized Unmanned Aerial Vehicles (UAVs) in precision agriculture, focused on achieving holistic autonomy in agricultural operations through multi-robot collaboration.  Currently, commercially available drones for agriculture are restrictive in achieving collaborative autonomy with the growing number of unmanned ground robots, limiting their use to narrow and specific tasks.  The advanced payload capacities of multi-rotor UAVs,... V. Muvva, H. Mwunguzi, S. Pitla, K. Joseph

49. Wheat Spikes Counting Using Density Prediction Convolution Neural Network

Vision-based wheat spikes counting can be valuable for pre-harvest yield estimation for growers and researchers. In this study, wheat spike counting convolutions neural networks were implemented to solve the problem of vision-based wheat yield prediction problem. Encoder-decoder style convolutional neural networks (CNN) were developed with a Global Sum Pooling (GSP) layer as its output layer and trained to produce a density map which predicts the pixelwise wheat spikes density.  This... C. Liew, S. Pitla

50. AIR-N: AI-Enabled Robotic Precision Nitrogen Management Platform

The AI-Enabled Robotic Nitrogen Management (AIR-N) system is a versatile, cloud-based platform designed for precision nitrogen management in agriculture, targeting the reduction of nitrous oxide emissions as emphasized by the EPA. This end-to-end integrated system is adaptable to various cloud services, enhancing its applicability across different farming environments. AIR-N's framework consists of three primary components: a sensing layer for gathering data, a cloud layer where AI and machine... A. Kalra, S. Pitla, J.D. Luck

51. Biochar Synthesis, Its Impact on Different Soils and Canola Growth

Biochar has been demonstrated as a soil amendment to improve soil health and plant yield. The present study aimed at investigating the potential of wheat straw on canola morphology and yield grown in different soils. The influence of biochar on soil physical and chemical properties was also assessed..Biochar was prepared by pyrolysis of wheat straw in a fixed-bed reactor.  Crushed wheat straw was loaded into the reactor in an N2 environment, and the heating was continued up to... M. Hassan

52. Proximal, Drone, and Satellite Sensors for In-season Variable Nitrogen Rate Application in Corn: a Comparative Study of Fixed-rate and Sensor-based Approaches

Effective nitrogen (N) management is essential for optimizing corn yield and enhancing agricultural sustainability. Traditional N application methods, typically uniform split pre-plant and in-season applications, often neglect the spatial and temporal variability of N requirements across different fields and years, potentially leading to N overuse. With the rise of precision agriculture technologies, it is crucial to reassess these conventional practices. This study had two main objectives: first,... A. Jakhar, A. Bhattarai, L. Bastos, G. Scarpin