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O'Sullivan, N
Rousseau, J
Burns, J
Godinho, R
Khakbazan, M
Jia, M
Roberts, A
Giriyappa, M
Chang, Y.K
Pearson , R
Kocsis, M
Livens, S
Pullanagari, R.R
Golla, B
Elkins, R
Griffin, T.W
Goel, R
Brase, T.A
Chen, T
Kaiser, D
Lindsey, L
Davadant, P
Hamm, P.B
Rennó, L.N
Bier, J
Van Couwenberghe, R
Carter, P.G
Rice, K
Kaho, T
Claussen, J
Karamidehkordi , E
Delgado, J.A
Han, K
Vangeyte, J
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Authors
Greer, K
Burns, J
Bremer, E
Zaman, Q
Esau, T.J
Farooque, A.A
Schumann, A.W
Percival, D.C
Chang, Y.K
Delgado, J.A
Ascough II, J.C
Farooque, A.A
Zaman, Q.U
Groulx, D
Schumann, A.W
Esau, T.J
Chang, Y.K
Douche, H
Rousseau, J
Delgado, J.A
Kyveryga, P.M
Blackmer, T.M
Pearson , R
Chen, L
Zhao, C
Huang, W
Chen, T
Wang , J
Rice, K
Carson, T
Krum, J
Flitcroft, I
Cline, V
Carrow, R
Cointault, F
Hijazi, B
Dubois, J
Vangeyte, J
Paindavoine, M
Kaho, T
Kodaira, M
Shibusawa, S
Sauer, B
Guppy, C.N
Trotter, M.G
Lamb, D.W
Delgado, J.A
Pierce, F
Perry, E.M
Young, S.L
Collins, H.P
Carter, 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
Kleinhenz, B
Röhrig, M
Scheiber, M
Feldhaus, J
Hartmann, B
Golla, B
Federle , C
Martini, D
Vougioukas, S.G
Jimenez, F.J
Khosro Anjom, F
Elkins, R
Ingels, C
Arikapudi, R
Giriyappa, M
Sheshadri, T
Hanumanthappa, D
Shankar, M
Salimath, S.B
Rudramuni, T
Raju, N
Devakumar, N
Mallikaarjuna, G
Malagi, M.T
Jangandi, S
Wang, C
Chen, T
Dong, J
Li, C
Moulin, A
Khakbazan, M
Han, K
Chung, S
Yule, I.J
Pullanagari, R.R
Kereszturi, G
Irwin, M.E
McVeagh, P.J
Cushnahan, T
White, M
Delauré, B
Baeck, P
Blommaert, J
Delalieux, S
Livens, S
Sima, A
Boonen, M
Goffart, J
Jacquemin, G
Nuyttens, D
Brase, T.A
Moulin, A
Khakbazan, M
Pradalier, C
Richard, A
Perez, V
Van Couwenberghe, R
Benbihi, A
Durand, P
Khakbazan, M
Moulin, A
Huang, J
Michiels, P
Xie, R
Dallago, G.M
Guimarães, M
Godinho, R
Carvalho, R
Lobo Júnior, A
Dallago, G.M
Guimarães, M
Godinho, R
Carvalho, R
Lobo Júnior, A
Sisák, I
Benő, A
Szabó, K
Kocsis, M
Abonyi, J
Claussen, J
Wörlein, N
Uhlmann, N
Gerth, S
de Azevedo, K.K
Figueiredo, D.M
de Sousa, M.G
Dallago, G.M
Silveira, R.R
da Silva, L.D
Rennó, L.N
Santos, R.A
de Azevedo, K.K
Figueiredo, D.M
Dallago, G.M
Vieira, J.A
Silveira, R.R
da Silva, L.D
Santos, R.A
Rennó, L.N
Pacheco, G.B
Cullop, J
Griffin, T.W
Ibendahl, G
Barnes, E
Shockley, J
Devine, J
King, W
Dynes, R
Laurenson, S
Zydenbos, S
MacAuliffe, R
Taylor, A
Manning, M
Roberts, A
White, M
Sridharan, S
Sornapudi, S
Hu, Q
Kumpatla, S
Bier, J
Kang, C
Karkee, M
Zhang, Q
Shcherbatyuk, N
Davadant, P
Keller, M
Dhal, S
Louis, J
O'Sullivan, N
Gumero, J
Soetan, M
Kalafatis, S
Lusher, J
Mahanta, S
Lu, J
Chen, Z
Miao, Y
Li, Y
Zhang, Y
Zhao, X
Jia, M
Aliloo, J
Abbasi, E
Karamidehkordi , E
Ghanbari Parmehr, E
Canavari, M
Vitali, G.-
Lord, E
Boatswain Jacques, A.A
Diallo, A.B
Khakbazan, M
Cambouris, A
Srinivasagan, S
Ketterings, Q
Marcaida, M
Shajahan, S
Ramos-Tanchez, J
Cho, J
Thompson, L
Guinness, J
Goel, R
Asgedom, H
Hehar, G
Willness, C
Anderson, W
Duddu, H
Mooleki, P
Schoenau, J
Khakbazan, M
Lemke, R
Derdall, E
Shang, J
Liu, K
Sulik, J
Karppinen, E
Mbakwe, I
Topics
Modeling and Geo-statistics
Engineering Technologies and Advances
Precision Conservation and Carbon Management
Spatial Variability in Crop, Soil and Natural Resources
Precision A-Z for Practitioners
Precision Conservation
Modeling and Geo-statistics
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Precision Nutrient Management
Precision Carbon Management
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Precision Crop Protection
Engineering Technologies and Advances
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Unmanned Aerial Systems
Education and Training in Precision Agriculture
Site-Specific Nutrient, Lime and Seed Management
Geospatial Data
Profitability and Success Stories in Precision Agriculture
Farm Animals Health and Welfare Monitoring
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
In-Season Nitrogen Management
Robotics, Guidance and Automation
Site-Specific Pasture Management
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Decision Support Systems
In-Season Nitrogen Management
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Big Data, Data Mining and Deep Learning
Site-Specific Nutrient, Lime and Seed Management
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results42 paper(s) found.

1. Oenoview : Bringing Remote Sensing To Wine Quality

  Oenoview is born in 2006 from the partnership between Infoterra, an EADS Astrium company specialised in earth observation and the Institut Cooperatif de Vin, a French company of services for the wine industry. Oenoview is an operating precision viticulture service, dedicated to vine monitoring, harvest optimisation and input management. In France, this service implemented in 2009 on a commercial scale is now used by clients as different as large... H. Douche, J. Rousseau

2. A New GIS Approach To Assess Nitrogen Management Across The USA

Nitrogen is one of the elements that are essential to maximizing agricultural productivity and economic returns for farmers. Its management is difficult because this element is very dynamic and mobile, characteristics that can contribute to significant losses via atmospheric, surface and/or leaching pathways. The magnitude of these losses can be affected by site-specific physical and chemical factors. These physical and chemical factors can vary significantly across the landscape, adding to the... J. Delgado

3. Using Late-season Uncalibrated Digital Aerial Imagery For Predicting Corn Nitrogen Status Within Fields

Using uncalibrated digital aerial imagery (DAI) for diagnosing in-season nitrogen (N) deficiencies of corn (Zea mays L.) is challenging because of the dynamic nature of corn growth and the difficulty of obtaining timely imagery. Digital aerial imagery taken later during the growing season is more accurate in identifying areas deficient in N. Even so, the quantitative use of late-season DAI across many fields is still limited because the imagery is not truly calibrated. This study... P.M. Kyveryga, T.M. Blackmer, R. Pearson

4. Application Of Algebra Hyper-curve Neural Network In Soil Nutrient Spatial Interpolation

Study on spatial variability of soil nutrient is the basis of soil nutrient management in precision agriculture. For study on application potential and characteristics of algebra hyper-curve neural network(AHNN) in delineating soil properties spatial variability and interpolation, total 956 soil samples were taken for alkaline hydrolytic nitrogen measurement from a 50 hectares field using 20m*20m grid sampling. The test data set consisted of 100 random samples extracting... L. Chen, C. Zhao, W. Huang, T. Chen, J. Wang

5. Spatial Mapping Of Penetrometer Resistance On Turfgrass Soils For Site-specific Cultivation

Site-specific management requires site-specific information.  Soil compaction at field capacity is a major stress on recreational turfgrass sites that requires frequent cultivation. Spatial mapping of penetrometer... K. Rice, T. Carson, J. Krum, I. Flitcroft, V. Cline, R. Carrow

6. New Power-leds Based Illumination System For Fertilizer Granule Motion Estimation

Environmental problems have become more and more pressing in the past twenty years particularly with the fertilization operation, one main contributor to environmental imbalance. The understanding of the global centrifugal spreading process, most commonly used in Europe, can contribute to provide essential information about fertiliser granule deposition on the soil. This last one can be predicted using a ballistic flight model and several fertilizer characteristic’s determination... F. Cointault, B. Hijazi, J. Dubois, J. Vangeyte, M. Paindavoine

7. Prediction Of Soil Moisture Content And Penetration Resistance Using Real-time Soil Meter

A real-time soil compaction meter that refers to the air injection subsoiler, is developed.  The final goal is to predict standarized soil compaction that is converted from soil moisture content, working resistance and working speed.  This experiment confirmed performance of predicting the soil moisture content and of measuring the working resistance was conducted.  The equipments of the meter are a working resistance measurement device received from the soil and a spectroscope... T. Kaho, M. Kodaira, S. Shibusawa

8. Matching Nitrogen To Plant Available Water For Malting Barley On Highly Constrained Vertosol Soil

Crop yield monitoring, high resolution aerial imagery and electromagnetic induction (EMI) soil sensing are three widely used techniques in precision agriculture (PA). Yield maps provide an indication of the crop’s response to a particular management regime in light of spatially-variable constraints. Aerial imagery provides timely and accurate information about photosynthetically-active biomass during crop growth and EMI indicates spatial variability in soil texture, salinity and/or... B. Sauer, C.N. Guppy, M.G. Trotter, D.W. Lamb, J.A. Delgado

9. Performance Of The Veris Nir Spectrophotometer For Mapping Soil C In The Palouse Soils Of Eastern Washington

Recent advances in sensing technology have made measuring and mapping the dynamics of important soil properties that regulate carbon and nutrient budgets possible. The Veris Technologies (Salinas, KS) Near Infrared (NIR) Spectrometer is one of the first sensors available for collecting geo-referenced NIR soil spectra on-the-go. Field studies were conducted to evaluate the performance of the Veris NIR in wheat grown under both conventional and no-till management in the Palouse region of eastern... F. Pierce, E.M. Perry, S.L. Young, H.P. Collins, P.G. Carter

10. Evaluation of PRS(TM) Probe Technology and Model for Variable Rate Fertilizer Application in Hummocky Fields in Saskatchewan

... K. Greer, J. Burns, E. Bremer

11. Development of Sensing System Using Digital Photography Technique for Spot-Application of Herbicide in Wild Blueberry Fields

An automated sensing system, hardware and software, was developed for spot-application of herbicide with 6.1 m boom automated prototype sprayer.... Q. Zaman, T.J. Esau, A.A. Farooque, A.W. Schumann, D.C. Percival, Y.K. Chang

12. A New Version of the Nitrogen Trading Tool (NTT) To Assess Nitrogen Management across the USA

A recent study from the USDA Economic Research Service (September 2011) reported that about one-third of U.S. cropland was found to meet the requirements for nutrient... J.A. Delgado, J.C. Ascough ii

13. Sensor Fusion on a Wild Blueberry Harvester for Fruit Yield, Plant Height and Topographic Features Mapping to Improve Crop Productivity

  Site-specific crop management can improve profitability and environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics, topographic features which may affect fruit yield. An integrated automated sensor fusion system including an ultrasonic sensor, a digital color camera, a slope sensor,... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang

14. 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

15. Pesticide Application Manager (PAM) - Decision Support In Crop Protection Based On Terrain-, Machine-, Business- And Public Data

Introduction   Pesticide Application Manager (PAM) is a project, co-financed by the German Federal Office for Agriculture and Food (BLE) that aims to develop solutions for automating important processes in crop protection.   Due to a series of rules and legal requirements for planning, implementation and documentation, crop protection is one of the most... B. Kleinhenz, M. Röhrig, M. Scheiber, J. Feldhaus, B. Hartmann, B. Golla, C. Federle , D. Martini

16. Design, Error Characterization And Testing Of A System To Measure Locations Of Fruits In Tree Canopies

Mapping the variability of fruit size and quality within tree canopies in commercial orchards is an important tool for implementing precision horticulture. To do so at a reasonably fast rate requires localization technologies that offer sufficient speed and accuracy, at a range long enough to cover entire trees – or several trees at a time. Existing approaches for measuring fruit locations include: manual (centimeter accuracy and measurement time in the order of minutes per... S.G. Vougioukas, F.J. Jimenez, F. Khosro anjom, R. Elkins, C. Ingels, R. Arikapudi

17. Precision Nutrient Management For Enhancing The Yield Of Groundnut In Peninsular India

               Groundnut is an important oil seed crop grown in an area of around 8 lakh hectares in Karnataka state of India under rainfed conditions. In these situations farmers applied inadequate fertilizer without knowing the initial nutrient status of the soil which resulted in low nutrient use efficiency that intern lead to low productivity of groundnut in these areas. Soil fertility deterioration due to... M. Giriyappa, T. Sheshadri, D. Hanumanthappa, M. Shankar, S.B. Salimath, T. Rudramuni, N. Raju, N. Devakumar, G. Mallikaarjuna, M.T. Malagi, S. Jangandi

18. Study Of Spatio-Temporal Variation Of Soil Nutrients In Paddy Rice Planting Farm

It is significant to analysis the spatial and temporal variation of soil nutrients for precision agriculture especially in large-scale farms. For the data size of soil nutrients grows once after sampling which mostly by the frequency of one year or months, to discover the changing trends of exact nutrient would be instructive for the fertilization in the future. In this study, theories of GIS and geostatistics were used to characterize the spatial and temporal variability of soil... C. Wang, T. Chen, J. Dong, C. Li

19. Statistical Variability of Crop Yield, Soil Test N and P Within and Between Producer’s Fields

Soil test N and P significantly affect crop production in the Canadian Prairies, but vary considerably within and between producer's fields.  This study describes the variability of crop yield, soil test N and P within and between producer's fields in the context of variable fertilizer rates.  Yield, terrain attribute, soil test N and P data were collected for 10 fields in Alberta, Saskatchewan and Manitoba Canada in 2014 and 2015.  The influence of fertilizer... A. Moulin, M. Khakbazan

20. Field Tests and Improvement of Sensor and Control Interface Modules with Improved Compatibility for Greenhouses

Number of greenhouses has been increased in many countries to control the cultivation conditions and improve crop yield and quality. Recently, various sensors and control devices, and also wireless communication tools have been adopted for efficient monitoring and control of the greenhouse environments. However, there have been farmers’ demands for improved compatibility among the sensors and control devices. In the study, sensor and control interface modules with improved compatibility... K. Han, S. Chung

21. Hyperspectral Imaging to Measure Pasture Nutrient Concentration and Other Quality Parameters

Managing pasture nutrient requirements on large hill country sheep and beef properties based on information from soil sampling is expensive because of the time and labor involved. High levels of error are also expected as these properties are often greatly variable and it is therefore extremely difficult to sample intensively enough to capture this variation. Extensive sampling was also not considered viable as there was no effective means of spreading fertilizer with a variable rate capability... I.J. Yule, R.R. Pullanagari, G. Kereszturi, M.E. Irwin, P.J. Mcveagh, T. Cushnahan, M. White

22. High Resolution Vegetation Mapping with a Novel Compact Hyperspectral Camera System

The COSI-system is a novel compact hyperspectral imaging solution designed for small remotely piloted aircraft systems (RPAS). It is designed to supply accurate action and information maps related to the crop status and health for precision agricultural applications. The COSI-Cam makes use of a thin film hyperspectral filter technology which is deposited onto an image sensor chip resulting in a compact and lightweight instrument design. This paper reports on the agricultural monitoring... B. Delauré, P. Baeck, J. Blommaert, S. Delalieux, S. Livens, A. Sima, M. Boonen, J. Goffart, G. Jacquemin, D. Nuyttens

23. Teaching Critical Thinking Skills Using Geospatial Technology As Instructional Tools

Techniques in data collection and analysis of data are important concepts for students of precision farming. Also needed in conjunction with these concepts are critical thinking and problem solving skills. Employers often list critical thinking skills as one of the most important characteristics for new employees. Helping students experience and acquire critical thinking skills can be difficult. Geospatial technologies are not only useful precision farming tools, they are also educational tools... T.A. Brase

24. Spatial Variability of Canola Yield Related to Terrain Attributes Within Producer's Fields

Canola production in the Canadian Prairies varies considerably within and between producer's fields.  This study describes the variability of crop yield in producer's fields in the context of terrain attributes, and in relation to fertilizer rates in management zones determined from historical yield.  Canola yield data were collected for 27 fields in Alberta, Saskatchewan and Manitoba Canada in 2014, 2015, 2016 and 2017.  Several terrain attributes accounted for a considerable... A. Moulin, M. Khakbazan

25. Automated Segmentation and Classification of Land Use from Overhead Imagery

Reliable land cover or habitat maps are an important component of any long-term landscape planning initiatives relying on current and past land use. Particularly in regions where sustainable management of natural resources is a goal, high spatial resolution habitat maps over large areas will give guidance in land-use management. We propose a computational approach to identify habitats based on the automated analysis of overhead imagery. Ultimately, this approach could be used to assist experts,... C. Pradalier, A. Richard, V. Perez, R. Van couwenberghe, A. Benbihi, P. Durand

26. Evaluation of the Potential for Precision Agriculture and Soil Conservation at Farm and Watershed Scale: A Case Study

Precision agriculture and soil conservation have the potential to increase crop yield and economic return while reducing environmental impacts. Landform, spatial variability of soil processes, and temporal trends may affect crop N response and should be considered for precision agriculture. The objective of this research was to evaluate the viability of precision agriculture in improving N use efficiency and profitability at the farm and watershed level in western Canada. Two studies are described... M. Khakbazan, A. Moulin, J. Huang, P. Michiels, R. Xie

27. The Animal Welfare of Dairy Cows Housed in Free-Stall Barn According to the Welfare Quality® Protocol: Good Feeding and Good Housing Principles

The objective of the present study was to evaluate the animal welfare of dairy cows according to good feeding and good housing principles of the Welfare Quality® protocol. The protocol was applied to animals kept confined in a free-stall barn during their lactation. The farm was located in São João Batista do Glória, Minas Gerais state - Brazil. One hundred and one animals were evaluated (47 primiparous and 54 multiparous). The welfare measures were collected mostly through... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

28. The Correlation Between Criteria from Welfare Quality® Protocol Applied to Dairy Cows Housed in Free-Stall Barn

The objective of this study was to evaluate correlations between animal welfare criteria from the Welfare Quality® protocol applied to dairy cows. The protocol was applied on 47 primiparous and 54 multiparous dairy cows housed in a free-stall barn located in São João Batista do Glória, Minas Gerais - Brazil. Twelve welfare criteria were obtained from mostly animal-based welfare measures as proposed by the protocol. Pearson correlation coefficients (r) were calculated between... G.M. Dallago, M. Guimarães, R. Godinho, R. Carvalho, A. Lobo júnior

29. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil Data

Our hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenous... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi

30. Quantification of Seed Performance: Non-Invasive Determination of Internal Traits Using Computed Tomography

The application of the 3D mean-shift filter to 3D Computed Tomography Data enables the segmentation of internal traits. Specifically in maize seeds this approach gives the opportunity to separate the internal structure, for example the volume of the embryo, the cavities and the low and high dense parts of the starch body. To evaluate the mean-shift filter, the results were compared to the usage of a median-smoothing filter. To show the relevance of the mean-shift extended image pipeline an automatic... J. Claussen, N. Wörlein, N. Uhlmann, S. Gerth

31. Levels of Inclusion of Crambe Meal (Crambe Abyssinica Hochst) in Sheep Diet on the Balance of Nitrogen and Ureic Nitrogen in the Blood Serum

Crambe meal, which is a co-product of biodiesel production, is a potential substitute for conventional protein sources in ruminant diets. The objective of this study was to evaluate the effect of the substitution of crude protein of the concentrate by crude protein of crambe meal with increasing levels (0, 25, 50, and 75%) on nitrogen balance and blood plasma urea nitrogen concentration in sheep. Four male sheep, rumen fistulated, were placed in metabolic crates and distributed in a 4 x 4 Latin... K.K. De azevedo, D.M. Figueiredo, M.G. De sousa, G.M. Dallago, R.R. Silveira, L.D. Da silva, L.N. Rennó, R.A. Santos

32. Efficiency of Microbial Synthesis and the Flow of Nitrogen Compounds in Sheep Receiving Crambe Meal (Crambe Abyssinica Hochst) Replacing the Concentrade Crude Protein

The objective of this study was to evaluate the effect of increasing levels (0, 25, 50, 75%) of crude protein substitution of the concentrate by crude protein of crambe meal on microbial protein synthesis and the flow of microbial nitrogen compounds in sheep. Four rumen fistulated sheep (18 months and initial average body weight of 50 kg) were distributed in a 4 x 4 Latin square design. Diets were balanced to meet the requirements for minimum gains, containing approximately 14% crude protein and... K.K. De azevedo, D.M. Figueiredo, G.M. Dallago, J.A. Vieira, R.R. Silveira, L.D. Da silva, R.A. Santos, L.N. Rennó, G.B. Pacheco

33. Economics of Swarm Bot Profitability for Cotton Harvest

Improved equipment management is one way which producers can increase profits. For cotton, this is especially true due to specialized equipment used for the sole purpose of harvest. Questions are raised regarding a way to either reduce or replace traditional cotton pickers. The main alternative being discussed is an investment in autonomous “swarm bots” to replace traditional equipment. Swarm bots are fully automated robots tasked with the responsibility of picking cotton one row at... J. Cullop, T.W. Griffin, G. Ibendahl, E. Barnes, J. Shockley, J. Devine

34. Through the Grass Ceiling: Using Multiple Data Sources on Intra-Field Variability to Reset Expectations of Pasture Production and Farm Profitability

Intra-field variability has received much attention in arable and horticultural contexts. It has resulted in increased profitability as well as reduced environmental footprint. However, in a pastoral context, the value of understanding intra-field variability has not been widely appreciated. In this programme, we used available technologies to develop multiple data layers on multiple fields within a dairy farm. This farm was selected as it was already performing at a high level, with well-developed... W. King, R. Dynes, S. Laurenson, S. Zydenbos, R. Macauliffe, A. Taylor, M. Manning, A. Roberts, M. White

35. A Generative Adversarial Network-based Method for High Fidelity Synthetic Data Augmentation

Digital Agriculture has led to new phenotyping methods that use artificial intelligence and machine learning solutions on image and video data collected from lab, greenhouse, and field environments. The availability of accurately annotated image and video data remains a bottleneck for developing most machine learning and deep learning models. Typically, deep learning models require thousands of unique samples to accurately learn a given task. However, manual annotation of a large dataset will... S. Sridharan, S. Sornapudi, Q. Hu, S. Kumpatla, J. Bier

36. Diagnosis of Grapevine Nutrient Content Using Proximal Hyperspectral Imaging

Nutrient deficiencies on grapevines could affect the fruit yield and quality, which is a major concern in vineyards. Nutrient deficiencies may be recognizable by foliar symptoms that vary by mineral nutrient and stress severity, but it is too late to manage when visible deficiency symptoms become apparent. The nutrient analysis in the laboratory is the way to get an accurate result, but it is time and cost-intensive. The differences in leaf nutrient levels also alter spectral characteristics outside... C. Kang, M. Karkee, Q. Zhang, N. Shcherbatyuk, P. Davadant, M. Keller

37. An IoT-based Smart Real Time Sensing and Control of Heavy Metals to Ensure Optimal Growth of Plants in an Aquaponic Set-up

The concentration of heavy metals that needs to be maintained in aquaponic environments for habitable growth of plants has been a cause of concern for many decades now as it is not possible to eliminate them completely in a commercial set-up. Our goal is to design a cost-effective real-time smart sensing and actuation system in order to control the concentration of heavy metals in aquaponic solutions. Our solution consists of sensing the nutrient concentrations in the aquaponic solution, namely... S. Dhal, J. Louis, N. O'sullivan, J. Gumero, M. Soetan, S. Kalafatis, J. Lusher, S. Mahanta

38. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather Data

Nitrogen 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

39. Content Analysis of the Challenges of Using Drones in Paddy Fields in the Haraz Plain Watershed, Iran

Drone technology has gained popularity in recent years as a sustainable solution to changing agricultural conditions. Using drones in agriculture provides many advantages in farm management. However, the use of drones in paddy fields in Iran is a new phenomenon facing numerous challenges. This study aims to explore the challenges for using drones in paddy fields and provide practical guidelines to solve the challenges facing the their application. This research was conducted with a qualitative... J. Aliloo, E. Abbasi, E. Karamidehkordi , E. Ghanbari parmehr, M. Canavari, G.-. Vitali

40. Deep Learning for Predicting Yield Temporal Stability from Short Crop Rotations

Investigating the temporal stability of yield in management zones is crucial for both producers and researchers, as it helps in mitigating the adverse impacts of unpredictable disruptions and weather events. The diversification of cropping systems is an approach which leads to reduced variability in yield while improving overall field resilience. In this six-year study spanning from 2016 to 2021, we monitored 40 distinct fields owned by 10 producers situated in Quebec, Canada. These... E. Lord, A.A. Boatswain jacques, A.B. Diallo, M. Khakbazan, A. Cambouris

41. Single-strip Spatial Evaluation Approach: a Simplified Method for Enhanced Sustainable Farm Management

On-farm experimentation (OFE) plays a pivotal role in evaluating and validating the effectiveness of agricultural practices and products. The results of OFE enable farmers to act and make changes that can enhance the farm’s economic and environmental sustainability. Experimental designs can be a barrier to the adoption of OFE. The conventional approach often involves randomized complete block designs with 3 to 5 replications in the field, which can be space-intensive and disrupt workflow... S. Srinivasagan, Q. Ketterings, M. Marcaida, S. Shajahan, J. Ramos-tanchez, J. Cho, , L. Thompson, J. Guinness, R. Goel

42. Response of Canola and Wheat to Application of Enhanced Efficiency Nitrogen Fertilizers on Contrasting Management Zones

Investment on nitrogen (N) fertilizers is a major cost of growers, and variable rate (VR) application of N fertilizers could help optimize its usage. In the growing season of 2023, field experiments were conducted at four sites (i.e., Watrous – Saskatchewan SK and two fields in the vicinity of Strathmore, Alberta AB, Canada). The main objectives were to (i) determine performance of Enhanced Efficiency N Fertilizers - EENF (i.e., Coated urea, urea with double inhibitors - DI, urea mixed with... H. Asgedom, G. Hehar, C. Willness, W. Anderson, H. Duddu, P. Mooleki, J. Schoenau, M. Khakbazan, R. Lemke, E. derdall, J. Shang, K. Liu, J. Sulik, E. Karppinen, I. Mbakwe