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Lindsey, A
Lattanzi, P
Lowenberg-DeBoer, J
Lebeau, F
Li, H
Lizarazo Salcedo, I.A
Liu, H
Linz, A
Lee, S
Lajili, A
Li, H
Lin, Z
Lee, W
Leemans, V
Lena, B.P
Love, D
Lebeau, F
Lamb, D
Le-Khac, N
Lagarrigue, M
Emamalizadeh, S
Liu, Z
Lidauer, L
Laacouri, A
Liu, J
Esau, T
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Authors
Lee, W
Wang, K
Li, H
Ehsani, R
Yang, C
Vancutsem, F
Leemans, V
Ferrandis Vallterra, S
Bodson, B
Destain, J
Destain, M
Dumont, B
Ruckelshausen, A
Alheit, K.V
Busemeyer, L
Klose, R
Linz, A
Moeller, K
Rahe, F
Thiel, M
Trautz, D
Weiss, U
Lee, W
Ehsani, R
Roka, F
Choi, D
Yang, C
Rossant, F
Bloch, I
Orensanz, J
Boisgontier, D
Verma, U
Lagarrigue, M
Rossant, F
Orensanz, J
Boisgontier, D
Bouhlel, N
Lagarrigue, M
Hertzberg, J
Ruckelshausen, A
Wunder, E
Linz, A
Andriamandroso, A
Dumont, B
Lebeau, F
Bindelle, J
Lee, W
Pourreza, A
Cosby, A.M
Falzon, G
Trotter, M
Stanley, J
Powell, K
Schneider, D
Lamb, D
Destain, M
Leemans, V
Marlier, G
Goffart, J
Bodson, B
Mercatoris, B
Gritten, F
Choi, D
Lee, W
Schueller, J.K
Ehsani, R
Roka, F.M
Ritenour, M.A
Patto Pacheco, E
Liu, J
Longchamps, L
Khosla, R
Mulla, D
Laacouri, A
Kaiser, D
Gan, H
Lee, W
Alchanatis, V
Cambouris, A
Lajili, A
Chokmani , K
Perron, I
Adamchuk, V
Biswas , A
Zebrath, B
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
Laacouri, A
Nigon, T
Mulla, D
Yang, C
Ngo, V.M
Le-Khac, N
Kechadi, M
Wilson, G.L
Mulla, D.J
Galzki, J
Laacouri, A
Vetsch, J
Mohamed, M.M
Zaman, Q
Esau, T
Farooque, A
Erickson, B.J
Lowenberg-DeBoer, J
MacEachern, C
Esau, T
Zaman, Q
Lin, Z
Guo, W
Gill, N
Plum, J
Quoitin, B
Dufrasne, I
Mahmoudi, S
Lebeau, F
Ghimire, B.P
Adedeji, O
Lin, Z
Guo, W
Adedeji, O.I
Ghimire, B.P
Gu, H
Karn, R
Lin, Z
Guo, W
Ortiz, B.V
Lena, B.P
Morlin , F
Morata, G
Duarte de Val, M
Prasad, R
Gamble, A
Cheema, S.J
Farooque, A.A
Abbas, F
Esau, T
Grewal, K
Khan, H
Esau, T
Farooque, A
Abbas, F
Zhou, C
Lee, W
Pourreza, A
Schueller, J.K
Liburd, O.E
Ampatzidis, Y
Zuniga-Ramirez, G
Fulton, J.P
Shearer, S.A
Gauci, A
Lindsey, A
Barker, D
Hawkins, E
Maja, J.J
Abenina, M
Cutulle, M
Melgar, J
Liu, H
Canavari, M
Lattanzi, P
Vitali, G
Emmi, L
Ferreyra, R
Lehmann, J
Lowenberg-DeBoer, J
Al Amin, A
Lowenberg-DeBoer, J
Franklin, K.F
Dickin, E
Monaghan, J
Behrendt, K
McFadden, J
Erickson, B
Lowenberg-DeBoer, J
Milics, G
Lee, S
Swinton, S.M
Lee, S
Swinton, S.M
Maritan, E
Behrendt, K
Lowenberg-DeBoer, J
Morgan, S
Rutter, M.S
Liu, Z
liu, X
Tian, Y
Zhu, Y
Cao, W
Cao, Q
Mazzoleni, R
Vinzio, F
Emamalizadeh, S
Allegro, G
Filippetti, I
Baroni, G
Huang, Z
Lee, W
Takkellapati, N
Rozenstein, O
Cohen, Y
Alchanatis , V
Behrendt, K
Bonfil, D.J
Eshel, G
Harari, A
Harris, W.E
Klapp, I
Laor, Y
Linker, R
Paz-Kagan, T
Peets, S
Rutter, M.S
Salzer, Y
Lowenberg-DeBoer, J
Rubaino Sosa, S.A
Cristancho Rojas, O.Y
Leon Rueda, W.A
Montero Pinilla, O.G
Roa Bello, J.C
Lizarazo Salcedo, I.A
Martinez Martinez, L.J
Ghansah, B
Khuimphukhieo, I
Scott, J.L
Bhandari, M
Foster, J
Da Silva, J
Li, H
Starek, M
Zhang, Y
Bailey, J
Balmos, A
Castiblanco Rubio, F.A
Krogmeier, J
Buckmaster, D
Love, D
Zhang, J
Allen, M
Topics
Machine Vision / Multispectral & Hyperspectral Imaging Applications to Precision Agriculture
Modeling and Geo-statistics
Sensor Application in Managing In-season Crop Variability
Engineering Technologies and Advances
Precision Horticulture
Precision Dairy and Livestock Management
Precision Crop Protection
Proximal Sensing in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Remote Sensing Applications in Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Dairy and Livestock Management
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Factors Driving Adoption
Precision Crop Protection
Applications of Unmanned Aerial Systems
Farm Animals Health and Welfare Monitoring
Decision Support Systems
Drainage Optimization and Variable Rate Irrigation
Precision Agriculture and Global Food Security
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Profitability and Success Stories in Precision Agriculture
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Data Analytics for Production Ag
Land Improvement and Conservation Practices
Site-Specific Pasture Management
Big Data, Data Mining and Deep Learning
Precision Agriculture for Sustainability and Environmental Protection
Artificial Intelligence (AI) in Agriculture
Scouting and Field Data collection with Unmanned Aerial Systems
Genomics and Precision Agriculture
Edge Computing and Cloud Solutions
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Filter results50 paper(s) found.

1. Sensor And System Technology For Individual Plant Crop Scouting

Sensor and system technologies are key components for automatic treatment of individual plants as well as for plant phenotyping in field trials. Based on experiences in research and application of sensors in agriculture the authors have developed phenotyping platforms for field applications including sensors, system and software development and application-specific mountings.   Sensor and data fusion have a high potential by compensating varying selectivities... A. Ruckelshausen, K.V. Alheit, L. Busemeyer, R. Klose, A. Linz, K. Moeller, F. Rahe, M. Thiel, D. Trautz, U. Weiss

2. Spectral Angle Mapper (SAM) Based Citrus Greening Disease Detection Using Airborne Hyperspectral Imaging

Over the past two decades, hyperspectral (HS) imaging has provided remarkable performance in ground objects classification and disease identification, due to its high spectral resolution. In this paper, a novel method named ‘extended spectral angle mapping (ESAM)’ is proposed to detect citrus greening disease (Huanglongbing or HLB), which is a destructive disease of citrus. Firstly, Savitzky-Golay smoothing filter was applied to the raw image to remove spectral noise within the data,... W. Lee, K. Wang, H. Li, R. Ehsani, C. Yang

3. Assessing the Potential of an Algorithm Based On Mean Climatic Data to Predict Wheat Yield

In crop yield prediction, the unobserved future weather remains the key point of predictions. Since weather forecasts are limited in time, a large amount of information may come from the analysis of past weather data. Mean data over the past years and stochastically generated data are two possible ways to compensate the lack of future data. This research aims to demonstrate that it is possible to predict... F. Vancutsem, V. Leemans, S. Ferrandis vallterra, B. Bodson, J. Destain, M. Destain, B. Dumont

4. Post-Harvest Quality Evaluation System On Conveyor Belt For Mechanically Harvested Citrus

Recently, a machine vision technology has shown its popularity for automating visual inspection. Many studies proved that the machine vision system can successfully estimate external qualities of fruit as good as manual inspection. However, introducing mechanical harvesters to citrus industry caused the following year’s yield loss due to the loss of immature young citrus. In this study, a machine vision system on a conveyor belt was developed to inspect mechanically... W. Lee, R. Ehsani, F. Roka, D. Choi, C. Yang

5. Tomato Development Monitoring In An Open Field, Using A Two-Camera Acquisition System

  Introduction   Optimal harvesting date and predicted yield are valuable information when farming open field tomatoes, making harvest planning and work at the processing plant much easier. Monitoring growth during tomato?s early stages is also interesting to assess plant stress or abnormal development. Yet, it is very challenging due to the colours and the high degree of occlusion... F. Rossant, I. Bloch, J. Orensanz, D. Boisgontier, U. Verma, M. Lagarrigue

6. Sound Based Detection Of Moths In Open Fields

Introduction   Open field farming of tomatoes suffers from the presence of harmful moths whose larvas are devastating. Detecting automatically the presence of moths allows regulating the use of pesticides, according to the actual population present in the field. Up to now, sex pheromone traps have been used, the number of captured insects giving some indication about the population. However, proper inspection of the traps is... F. Rossant, J. Orensanz, D. Boisgontier, N. Bouhlel, M. Lagarrigue

7. Autonomous Service Robots For Orchards And Vineyards: 3D Simulation Environment Of Multi Sensor-Based Navigation And Applications

In order to fulfill economical as well as ecological boundary conditions information technologies and sensor are increasingly gaining importance in horticulture.  In combination with the reduced availability of human workers automation technologies thus play a key role in the international competition in vinicultures and orchards and have the potential to reduce the costs as well as environmental impacts.   The authors are working in the... J. Hertzberg, A. Ruckelshausen, E. Wunder, A. Linz

8. 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

9. Effect Of Starch Accumulation In Huanglongbing Symptomatic Leaves On Reflecting Polarized Light

Huanglongbing (HLB) or citrus greening disease is an extremely dangerous infection which has severely influenced the citrus industry in Florida. It was also recently found in California and Texas. There is no effective cure for this disease reported yet. The infected trees should be identified and removed immediately to prevent the disease from being spread to other trees. The visual leaf symptoms of this disease are green islands, yellow veins, or vein corking; however,... W. Lee, A. Pourreza

10. Using A Decision Tree To Predict The Population Density Of Redheaded Cockchafer (Adoryphorus Couloni) In Dairy Fields

A native soil dwelling insect pest, the redheaded cockchafer (Adoryphorus couloni) (Burmeister) (RHC) is an important pest in the higher rainfall regions of south-eastern Australia. Due to the majority of its lifecycle spent underground feeding on the roots and soil organic matter the redheaded cockchafer is difficult to detect and control. The ability to predict the level of infestation and location of redheaded cockchafers in a field may give producers the option to use an endophyte containing... A. Cosby, G. Falzon, M. Trotter, J. Stanley, K. Powell, D. Schneider, D. Lamb

11. Detection of Nitrogen Stress on Winter Wheat by Multispectral Machine Vision

Hand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen  concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for detecting... M. Destain, V. Leemans, G. Marlier, J. Goffart, B. Bodson, B. Mercatoris, F. Gritten

12. A Precise Fruit Inspection System for Huanglongbing and Other Common Citrus Defects Using GPU and Deep Learning Technologies

World climate change and extreme weather conditions can generate uncertainties in crop production by increasing plant diseases and having significant impacts on crop yield loss. To enable precision agriculture technology in Florida’s citrus industry, a machine vision system was developed to identify common citrus production problems such as Huanglongbing (HLB), rust mite and wind scar. Objectives of this article were 1) to develop a simultaneous image acquisition system using multiple cameras... D. Choi, W. Lee, J.K. Schueller, R. Ehsani, F.M. Roka, M.A. Ritenour

13. Detecting Nitrogen Variability at Early Growth Stages of Wheat by Active Fluorescence and NDVI

Low efficiency in the use of nitrogen fertilizer, has been reported around the world which often times result in high production costs and environmental damage. Today, unmanned aerial vehicles (UAV) cameras are being used to obtain conditions of crops, and can cover large areas in a short time. The objectives of this study were (i) to investigate N-variability in wheat at early growth stages using induced fluorescence indices, NDVI measured by active sensor and NDVI obtained by digital imagery;... E. Patto pacheco, J. Liu, L. Longchamps, R. Khosla

14. Comparison Between High Resolution Spectral Indices and SPAD Meter Estimates of Nitrogen Deficiency in Corn

Low altitude remote sensing provides an ideal platform for monitoring time sensitive nitrogen status in crops. Research is needed however to understand the interaction between crop growth stage, spatial resolution and spectral indices derived from low altitude remote sensing. A TetraCam camera equipped with six bands including the red edge and near infrared (NIR) was used to investigate corn nitrogen dynamics. Remote sensing data were collected during the 2013 and 2014 growing seasons at four... D. Mulla, A. Laacouri, D. Kaiser

15. A Photogrammetry-based Image Registration Method for Multi-camera Systems

In precision agriculture, yield maps are important for farmers to make plans. Farmers will have a better management of the farm if early yield map can be created. In Florida, citrus is a very important agricultural product. To predict citrus production, fruit detection method has to be developed. Ideally, the earlier the prediction can be done the better management plan can be made. Thus, fruit detection before their mature stage is expected. This study aims to develop a thermal-visible camera... H. Gan, W. Lee, V. Alchanatis

16. Use of Proximal Soil Sensing to Delineate Management Zones in a Commercial Potato Field in Prince Edward Island, Canada

Management zones (MZs) are delineated areas within an agricultural field with relatively homogenous soil properties. Such MZs can often be used for site-specific management of crop production inputs. The purpose of this study was to determine the efficiency of two proximal soil sensors for delineating MZs in an 8.1-ha commercial potato (Solanum tuberosum L.) field in Prince Edward Island (PEI), Canada. A galvanic contact resistivity sensor (Veris-3100 [Veris]) and electromagnetic induction sensors... A. Cambouris, A. Lajili, K. Chokmani , I. Perron, V. Adamchuk, A. Biswas , B. Zebrath

17. 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

18. 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

19. 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

20. 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

21. A Case Study Comparing Machine Learning and Vegetation Indices for Assessing Corn Nitrogen Status in an Agricultural Field in Minnesota

Compact hyperspectral sensors compatible with UAV platforms are becoming more readily available. These sensors provide reflectance in narrow spectral bands while covering a wide range of the electromagnetic spectrum. However, because of the narrow spectral bands and wide spectral range, hyperspectral data analysis can benefit greatly from data mining and machine learning techniques to leverage its power. In this study, rainfed corn was grown during the 2017 growing season using four nitrogen treatments... A. Laacouri, T. Nigon, D. Mulla, C. Yang

22. An Efficient Data Warehouse for Crop Yield Prediction

Nowadays, precision agriculture combined with modern information and communications technologies, is becoming more common in agricultural activities such as automated irrigation systems, precision planting, variable rate applications of nutrients and pesticides, and agricultural decision support systems. In the latter, crop management data analysis, based on machine learning and data mining, focuses mainly on how to efficiently forecast and improve crop yield. In recent years, raw and semi-processed... V.M. Ngo, N. Le-khac, M. Kechadi

23. Predicted Nitrate-N Loads for Fall, Spring, and VRN Fertilizer Application in Southern Minnesota

Nitrate-N from agricultural fields is a source of pollution to fresh and marine waters via subsurface tile drainage.  Sensor-based technologies that allow for in-season monitoring of crop nitrogen requirements may represent a way to reduce nitrate-N loadings to surface waters by allowing for fertilizer application on a more precise spatial and temporal resolution.  However, little research has been done to determine its effectiveness in reducing nitrate-N losses.  In this study,... G.L. Wilson, D.J. Mulla, J. Galzki, A. Laacouri, J. Vetsch

24. Design of Ground Surface Sensing Using RADAR

Ground sensing is the key task in harvesting head control system. Real time sensing of field topography under vegetation canopy is very challenging task in wild blueberry cropping system. This paper presents the design of an ultra-wide band RADAR sensing, scanning device to recognize the soil surface level under the canopy structure. Requirements for software and hardware were considered to determine the usability of the ultra-wide band RADAR system.An automated head elevation... M.M. Mohamed, Q. Zaman, T. Esau, A. Farooque

25. Survey Shows Specialty and Commodity Crop Retailers Use Precision Agriculture Differently

The 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

26. Development of a Granular Herbicide Spot Applicator for Management of Hair Fescue (Festuca Filiformis) in Wild Blueberry (Vaccinium Angustifolium)

Hair fescue has quickly become the pest of greatest concern for the wild blueberry industry. This is largely due to its ability to outcompete wild blueberry for critical resources including water, nutrients and most importantly space. In Nova Scotia, between 2001 and 2019, hair fescue had increased in field frequency from 7% to 68% and in field uniformity from 1.4% to 25%. This rapidly spreading and economically destructive weed is likewise a significant challenge to manage, with only a single... C. Maceachern, T. Esau, Q. Zaman

27. 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

28. Use of Watering Hole Data As a Decision Support Tool for the Management of a Grazing Herd of Cattle

Establish grazing practices would improve the welfare of the animals, allowing them to express more natural behaviours. However, free-range reduces the ability to monitor the animals, thus increase the time needed to intervene in the event of a health problem. To ease the adoption of grazing, farmer would benefit from autonomously collected indicators at pasture that identify abnormal behaviours possibly related to a health problem in a bovine. These indicators must be individualised and collected... J. Plum, B. Quoitin, I. Dufrasne, S. Mahmoudi, F. Lebeau

29. Modeling Spatial and Temporal Variability of Cotton Yield Using DSSAT for Decision Support in Precision Agriculture

The quantification of spatial and temporal variability of cotton yield provides critical information for optimizing resources, especially water. The Southern High Plains (SHP) of Texas is a major cotton (Gossypium hirsutum L.) production region with diminishing water supply. The objective of this study was to predict cotton yield variability using soil properties and topographic attributes. The DSSAT CROPGRO-Cotton model was used to simulate cotton growth, development and yield using... B.P. Ghimire, O. Adedeji, Z. Lin, W. Guo

30. Estimation of Cotton Biomass Using Unmanned Aerial Systems and Satellite-based Remote Sensing

Satellite and unmanned aerial system (UAS) images are effective in monitoring crop growth at various spatial, temporal, and spectral scales. The objective of the study was to estimate cotton biomass at different growth stages using vegetation indices (VIs) derived from UAS and satellite images. This research was conducted in a cotton field in Hale County, Texas, in 2021. Data collected include 54 plant samples at different locations for three dates of the growing season. Multispectral images from... O.I. Adedeji, B.P. Ghimire, H. Gu, R. Karn, Z. Lin, W. Guo

31. Can Topographic Indices Be Used for Irrigation Management Zone Delineation

Soil water movement is affected by soil physical properties and field terrain changes. The identification of within-field areas prone to excess or deficit of soil moisture could support the implementation of variable rate irrigation and adoption of irrigation scheduling strategies. This study evaluated the use of the topographic wetness index (TWI) and topographic position index (TPI) to understand and explain within-field soil moisture variability. Volumetric water content (VWC) collected in... B.V. Ortiz, B.P. Lena, F. morlin , G. Morata, M. Duarte de val, R. Prasad, A. Gamble

32. Establishing the First Soil Water Characteristics Curve for the Soils of Prince Edward Island, Canada

Soil water characteristics curve (SWCC), for Prince Edward Island (PEI), is much more needed currently for the sustainable production of agriculture yields. It will not only fulfil the requirements of the province’s farmers for irrigation scheduling but also help the government to decide about permitting the use of groundwater for supplemental irrigation on the island.  A soil water characteristics curve in PEI does not exist to support precision agriculture practices. Precision irrigation... S.J. Cheema, A.A. Farooque, F. Abbas, T. Esau, K. Grewal

33. Suitability of ML Algorithms to Predict Wild Blueberry Harvesting Losses

The production of wild blueberries (Vaccinium angustifolium.) is contributing 112.2 million dollars to the Canada’s revenue which can be further increased through controlling harvest losses. A precise prediction of blueberry harvesting losses is necessary to mitigate such losses. In this study, the performance of three machine learning (ML) models was evaluated to predict the wild blueberry harvest losses on the ground. The data from four commercial fields in Atlantic Canada were... H. Khan, T. Esau, A. Farooque, F. Abbas

34. Strawberry Pest Detection Using Deep Learning and Automatic Imaging System

Strawberry growers need to monitor pests to determine the options for pest management to reduce damage to yield and quality.  However, manually counting strawberry pests using a hand lens is time-consuming and biased by the observer. Therefore, an automated rapid pest scouting method in the strawberry field can save time and improve counting consistency. This study utilized six cameras to take images of the strawberry leaf. Due to the relatively small size of the strawberry pest, six cameras... C. Zhou, W. Lee, A. Pourreza, J.K. Schueller, O.E. Liburd, Y. Ampatzidis, G. Zuniga-ramirez

35. Limitations of Yield Monitor Data to Support Field-scale Research

Precision agriculture adoption on farms continues to grow globally on farms.  Today, yield monitors have become standard technologies on grain, cotton and sugarcane harvesters.  In recent years, we have seen industry and even academics leveraging the adoption of precision agriculture technologies to conduct field-scale, on-farm research.  Industry has been a primary driver of the increase in on-farm research globally through the development of software to support on-farm research. ... J.P. Fulton, S.A. Shearer, A. Gauci, A. Lindsey, D. Barker, E. Hawkins

36. Snap-shot Hyperspectral Camera for Potassium Prediction of Peach Trees Using Multivariate Analysis

Hyperspectral imaging (HSI) is an emerging technology being utilized in agriculture. This system could be used to monitor the overall health of plants or pest disease detection. As sensing technology advances, measuring nutrient levels and disease detection also progresses. This study aimed to predict the levels of potassium (K) content in peach leaves with the new snapshot hyperspectral camera. The study was conducted at the Clemson University Musser Fruit Research Farm (Seneca, SC, USA, 34.61... J.J. Maja, M. Abenina, M. Cutulle, J. Melgar, H. Liu

37. Robot Safety Issues in Field Crops - EU Regulatory Issues and Technical Aspects

The use of robots in Precision Agriculture is becoming of great interest, but they introduce a new kind of risk in the field due to their self-acting and self-driving capability. Safety issues appear with respect to people working in the same field in human-robot collaboration (HRC) framework or to the accidental presence of humans or animals. A robot out of control may also invade other areas causing unpredictable harm and damage. Currently, the safety of highly automated agricultural... M. Canavari, P. Lattanzi, G. Vitali, L. Emmi

38. The ISO Strategic Advisory Group for Smart Farming: a Multi-pronged Opportunity for Greater Global Interoperability

Agriculture 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

39. Profitability of Regenerative Cropping with Autonomous Machines: an Ex-ante Assessment of a British Crop-livestock Farm

Farmers, 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

40. Global Adoption of Precision Agriculture: an Update on Trends and Emerging Technologies

The 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

41. Comparing Profitability of Variable Rate Nitrogen Prescription Methods

Variable rate nitrogen (VRN) prescriptions have been field-tested against uniform N application for over 25 years.  VRN prescription algorithms vary in the type and cost of information they require.  To date, few studies have compared the benefits and costs of alternative VRN prescription methods. VRN prescriptions draw on diverse information, including soil and tissue N sampling, yield history (YH), and remotely sensed spectral reflectance (such as the Normalized Difference... S. Lee, S.M. Swinton

42. Opportunity Cost of Precision Conservation

Crop production and biodiversity conservation vie for limited agricultural land resources. While biodiversity conservation benefits society as a whole, it is farmers who bear the immediate economic consequences of shifting land from agricultural to conservation use. When parts of a field are put into conservation use, farmers give up the net revenue that they earned from crop production, accepting the “opportunity cost” of losing that revenue stream.  But since crop yields are... S. Lee, S.M. Swinton

43. A Multi-objective Optimisation Analysis of Virtual Fencing in Precision Grazing

Virtual 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

44. Optimizing Nitrogen Application in Global Wheat Production by an Integrated Bayesian and Machine Learning Approach

Wheat production plays a pivotal role in global food security, with nitrogen fertilizer application serving as a critical factor. The precise application of nitrogen fertilizer is imperative to maximize wheat yield while avoiding environmental degradation and economic losses resulting from excess or inadequate usage. The integration of Bayesian and machine learning methodologies has gained prominence in the realm of agricultural research. Bayesian and machine learning based methods have great... Z. Liu, X. Liu, Y. Tian, Y. Zhu, W. Cao, Q. Cao

45. Enhancing Precision Agriculture with Cosmic-ray Neutron Sensing: Monitoring Soil Moisture Dynamics and Its Impact on Grapevine Physiology

Precision agriculture has emerged as a transformative approach in modern viticulture, seeking to optimize vineyard management. Vineyard operations rely heavily on effective water management, especially in regions where water availability can significantly affect grape quality and yield. The relationship between soil moisture and grapevine physiology is however complex. Therefore, understanding these relationships is crucial for optimizing vineyard operations. Cosmic-ray neutron sensing (CRNS)... R. Mazzoleni, F. Vinzio, S. Emamalizadeh, G. Allegro, I. Filippetti, G. Baroni

46. HOPSY: Harvesting Optimization for Production of Strawberry Using Real-time Detection with YOLOv8

Optimizing the harvesting process presents a continuous challenge within the strawberry industry, especially during peak seasons when precise labor allocation becomes critical for efficiency and cost-effectiveness. The conventional method for addressing this issue has been hindered by an absence of real-time data regarding yield distribution, resulting in less-than-ideal worker assignments and unnecessary expenditures on labor. In response, a novel, portable, real-time strawberry detection system... Z. Huang, W. Lee, N. Takkellapati

47. 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

48. Spectral Response of Six Treatments of Soil Fertilization in Potato (Solanum tuberosum L.) Var. Diacol Capiro with UAS

In Colombia, potato cultivation occupies the third place among the transient crops in the country, covering approximately 160,000 hectares. It holds the first place in terms of production value, reaching US $500 million, and ranks as the second crop with the highest demand for fertilizers, constituting 20% of production costs. The departments of Cundinamarca, Boyacá, Nariño, and Antioquia are the primary potato producers, accounting for 87.8% of the total production. Traditional... S.A. Rubaino sosa, O.Y. Cristancho rojas, W.A. Leon rueda, O.G. Montero pinilla, J.C. Roa bello, I.A. Lizarazo salcedo

49. High Throughput Phenotyping of the Energy Cane Crop UAV-based LiDAR, Multispectral and RGB Data

Energy cane is a hybrid of sugarcane cultivated for their high biomass and fiber instead of sugar. It is used for production of biofuels and as feedstock for animals. As a relatively new crop, accurate knowledge of biophysical parameters such as height and biomass of different genotypes are pertinent to cultivar development. Such knowledge is also crucial to manage crop health, understand response to environmental effects, optimize harvest schedules, and estimate bioenergy yield. Nonetheless,... B. Ghansah, I. Khuimphukhieo, J.L. Scott, M. Bhandari, J. Foster, J. Da silva, H. Li, M. Starek

50. Enabling Field-level Connectivity in Rural Digital Agriculture with Cloud-based LoRaWAN

The widespread adoption of next-generation digital agriculture technologies in rural areas faces a critical challenge in the form of inadequate field-level connectivity. Traditional approaches to connecting people fall short in providing cost-effective solutions for many remote agricultural locations, exacerbating the digital divide. Current cellular networks, including 5G with millimeter wave technology, are urban-centric and struggle to meet the evolving digital agricultural needs, presenting... Y. Zhang, J. Bailey, A. Balmos, F.A. Castiblanco rubio, J. Krogmeier, D. Buckmaster, D. Love, J. Zhang, M. Allen