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Niwa, K
Sudduth, K.A
Nysten, S
Swanson, G
Sylvester-Bradley, R
Manon, M
McEntee, P
McVeagh, P.J
Maréchal, P
Santos, R.T
Stafford, K.J
Midtiby, H.S
Nargund, V.B
Sheppard, J
Stephens, P
Moeller, K
Sampson, T
Singh, M
Salzer, Y
Nagata, O
Nafziger, E.D
Sulastri, N
Shafii, M.S
Namdarian, I
Modi, R.U
Sarwar, M
Jasper, J
Jacobson, A.R
Mistele, B
Mercatoris, B
Scudiero, E
Junior, C.S
Sawyer, J.E
Sunohara, M
Jacobsen, N.J
Mitsuoka, M
Schwalbert, R.A
Salokhe, D.M
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Authors
Shinde, G.U
Salokhe, D.M
Badgujar, P.D
Sharma, D.B
Stephens, P
Mackin, S
Holmes, G
Mistele, B
Schmidhalter, U
Kipp, S
Mistele, B
Schmidhalter, U
Erdle, K
Nisa, M.U
Babar, I
Sarwar, M
Tauqir, N.A
Shahzad, M.A
Junior, C.S
Hirakawa, A.R
Baresel, P
Mistele, B
Yuncai, H
Schmidhalter, U
Hackl, H
Nino, P
Vanino, S
Lupia, F
Altobelli, F
Vuolo, F
Namdarian, I
De Michele, C
Marine, L
Manon, M
Claire, G
Laurent, P
Mostafa, F
Zoran, C
Naima, B
Sébastien, D
Olivier, G
Lebeau, F
Massinon, M
Maréchal, P
Boukhalfa, H
Saraiva, A.M
Santos, R.T
Molin, J.P
J�??�?�¸rgensen, R.N
Midtiby, H.S
Giselsson, T.M
Bøgild, A
Nielsen, S.H
Jacobsen, N.J
Jager-Hansen, C
Jørgensen, R.N
Jensen, K
Jørgensen, O.J
El-Sayed, S
Schmidhalter, U
Mistele, B
Hongo, C
Niwa, K
Sulastri, N
Shibusawa, S
Kodaira, M
Draganova, I
Yule, I.J
Betteridge, K
Hedley, M.J
Stafford, K.J
Mistele, B
Schmidhalter, U
Singh, M
Sharma, A
Singh, G
Fixen, P
Amakor, X
Jacobson, A.R
Cardon, G.E
Hawks, A
Barnes, W
Ruckelshausen, A
Alheit, K.V
Busemeyer, L
Klose, R
Linz, A
Moeller, K
Rahe, F
Thiel, M
Trautz, D
Weiss, U
Myers, D.B
Kitchen, N.R
Sudduth, K.A
Leonard, B.J
Tamura, E
Aijima, K
Niwa, K
Nagata, O
Wakabayashi, K
Hongo, C
Schepers, J.S
Mclure, B
Swanson, G
Destain, M
Leemans, V
Marlier, G
Goffart, J
Bodson, B
Mercatoris, B
Gritten, F
McEntee, P
Bennett, S
Trotter, M
Belford, R
Harper, J
Rudolph, S
Marchant, B.P
Gillingham, V
Kindred, D
Sylvester-Bradley, R
Gnyp, M.L
Panitzki, M
Reusch, S
Jasper, J
Bolten, A
Bareth, G
Yule, I.J
Grafton, M.C
Willis, L.A
McVeagh, P.J
Hirai, Y
Yamakawa, T
Inoue, E
Okayasu, T
Mitsuoka, M
Kempenaar, C
van Evert, F
Been, T
Kocks, C
Westerdijk, K
Nysten, S
Yule, I.J
Pullanagari, R.R
Kereszturi, G
Irwin, M.E
McVeagh, P.J
Cushnahan, T
White, M
Seepersad, G
Sampson, T
Seepersad, S
Goorahoo, D
Upadhayaya, S.K
Udompetaikul, V
Shafii, M.S
Browne, G.T
Sylvester-Bradley, R
Kindred, D
Berry, P
Reddy, S
Biradar, D.P
Patil, V.C
Desai, B.L
Nargund, V.B
Patil, P
Desai, V
Tulasigeri, V
Channangi, S.M
John, W
Kumar, S
Singh, M
Mirzakhaninafchi, H
Modi, R.U
Ali, M
Bhardwaj, M
Soni, R
Bean, G.M
Kitchen, N.R
Camberato, J.J
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Sawyer, J.E
Scharf, P.C
Kindred, D
Sylvester-Bradley, R
Clarke, S
Roques, S
Hatley, D
Marchant, B
Ransom, C.J
Kitchen, N.R
Camberato, J.J
Carter, P.R
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J
Sawyer, J.E
Maxwell, B.D
Bekkerman, A
Silverman, N
Payn, R
Sheppard, J
Izurieta, C
Davis, P
Hegedus, P.B
Sheppard, J
Peerlinck, A
Maxwell, B
Kross, A
Kaur, G
Callegari, D
Lapen, D
Sunohara, M
McNairn, H
Rudy, H
van Vliet, L
Kross, A
Kaur, G
Znoj, E
Callegari, D
Sunohara, M
McNairn, H
Lapen, D
Rudy, H
van Vliet, L
G, S
Biradar, D.P
Desai, B.L
Patil, V.C
Patil, P
Nargund, V.B
Desai, V
John, W
Channangi, S.M
Tulasigeri, V
Dandrifosse, S
Ennadifi, E
Carlier, A
Gosselin, B
Dumont, B
Mercatoris, B
El-Mejjaouy, Y
Dumont, B
Oukarroum, A
Mercatoris , B
Vermeulen , P
Peerlinck, A
Sheppard, J
Morales Luna, G.L
Hegedus, P
Maxwell, B
Li, D
Miao, Y
Fernández, .G
Kitchen, N.R
Ransom, C.
Bean, G.M
Sawyer, .E
Camberato, J.J
Carter, .R
Ferguson, R.B
Franzen, D.W
Franzen, D.W
Franzen, D.W
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J.F
Brorsen, W
Poursina, D
Patterson, C
Mieno, T
Edge, B
Nafziger, E.D
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
Scudiero, E
Nugent, C.I
Ng, C
Jones, N
Azzam, T
Salunga, N.G
Lemus, S
Carcedo, A
Antunes de Almeida, L.F
Horbe, T
Corassa, G
Pott, L.P
Ciampitti, I
Hintz, G.D
Hefley, T
Schwalbert, R.A
Prasad, V
Topics
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Precision Dairy and Livestock Management
Information Management and Traceability
Precision Crop Protection
Food Security and Precision Agriculture
Proximal Sensing in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Livestock Management
Pros and Cons of Reflectance and Fluorescence-based Remote Sensing of Crop
Sensor Application in Managing In-season Crop Variability
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Big Data Mining & Statistical Issues in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Decision Support Systems in Precision Agriculture
Engineering Technologies
Precision Agriculture and Global Food Security
Applications of Unmanned Aerial Systems
Small Holders and Precision Agriculture
In-Season Nitrogen Management
On Farm Experimentation with Site-Specific Technologies
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Decision Support Systems
ISPA Community: Nitrogen
On Farm Experimentation with Site-Specific Technologies
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Education of Precision Agriculture Topics and Practices
Weather and Models for Precision Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results53 paper(s) found.

1. Estimation Of Sugar Beet Yield Brfore Harvesting Using Meteorological Data And Spot Satellite Data

    In Japan, sugar beet is only cultivated in Hokkaido, the northernmost island. The area of sugar beet cultivation in Tokachi District is 30,000ha, which is equal to about 45% of the total national production area. Because sugar beet is suited to cool weather conditions, it is an important rotation crop in Hokkaido. The production of beet sugar in Hokkaido is about 640,000 tons, which is 75... C. Hongo, K. Niwa

2. On The Go Soil Sensor For Soil Ec Mapping

This paper describes spatial variation maps of soil electrical conductivity (EC) obtained by both spectroscopic and capacitance methods using on the go soil sensor ( a real-time soil sensor -RTSS) SAS 1000, commercialized by Shibuya Kogyo Co. The experiments were conducted over a 2 year period on an experimental Hokkaido farm with an alluvial soil type. The comparison in soil EC records between the spectroscopy and the capacitance were also discussed. The spectroscopic approach used the soil... N. Sulastri, S. Shibusawa, M. Kodaira

3. Monitoring Dairy Cow Activity With GPS-tracking And Supporting Technologies

  Nutrient loss from dairy farms is an issue of serious concern to most dairy farmers around the world. On grazed systems such as those practiced in New Zealand animal excreta has been identified as a major source of nutrient loss, which for nitrogen (N) relates to cattle urine in particular.  A study was commissioned to examine nutrient transfer around dairy farms associated with the cows with a view to developing improved precision nutrient application... I. Draganova, I.J. Yule, K. Betteridge, M.J. Hedley, K.J. Stafford

4. A Comparison Of Spectral Reflectance And Laser-induced Cholorphyll Fluorescence Measurements To Detect Differences In Aerial Dry Weight And Nitrogen Update Of Wheat

       Chlorophyll fluorescence and spectral reflectance analysis are both powerful tools to study the spatial and temporal heterogeneity of plants` biomass and nitrogen status. Whereas reflectance techniques have intensively been tested for their use in precision fertilizer application, laser-induced chlorophyll fluorescence has been tested to a lesser degree, and there are hardly any... B. Mistele, U. Schmidhalter

5. Development Of Batch Type Yield Monitor For Small Fields

 Abstract The yield monitor is intended to give the user an accurate assessment of yield variations y within a field. A yield monitor can assist grain producers in many aspects of crop management. A yield monitor by itself can provide useful information and enhance on-farm research. Yield data can... M. Singh, A. Sharma, G. Singh, P. Fixen

6. Apparent Electrical Conductivity Calibration In Semiarid Soils: Ion-pair Correction

The electromagnetic induction sensor (EM38DD) is a field proven portable sensor for rapid measurement of the apparent electrical conductivity (ECa) of soils. Calibration with the electrical conductivity of saturation paste extracts is the most widely used method to correlate ECa with the effective electrical conductivity (ECe). A drawback of this method is the formation of ion pairs in the high ionic strength saturated paste extracts, which effectively decreases the measured ECe, leading to the... X. Amakor, A.R. Jacobson, G.E. Cardon, A. Hawks, W. Barnes

7. 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

8. Computer Aided Engineering Analysis and Design Optimization for Precision Manufacturing of Tillage Tool: Sweep Cultivator

The process optimization in advance tillage tool system conceptually designed and fabricated by computer aided engineering analysis techniques. The Software testing a field performance is taken in the soil bed preparation as well as in the various crop patterns. It was found most use full in obtaining high weed removal efficiency. The precision geometry, optimum energy utilization, multi-operational design, easy transport and flexible attachments are some of the features which results in achieving... G.U. Shinde, D.M. Salokhe, P.D. Badgujar, D.B. Sharma

9. Exploiting the Dmc Satellite Constellation for Applications in Precision Agriculture

This paper presents the unique capabilities of the DMC constellation of optical sensors, and examples of how a number of organisations around the world are exploiting this powerful data source for applications in precision farming. The DMC consists of five satellites built in the UK by Surrey Satellite Technology Ltd, each carrying a wide swath (650km) optical sensor. It is an international programme of satellite ownership and groundstations, with joint campaigns being coordinated centrally... P. Stephens, S. Mackin, G. Holmes

10. Active Sensor Performance – Dependence to Measuring Height, Light Intensity and Device Temperature

For land use management, agriculture, and crop management spectral remote sensing is widely used. Ground-based sensing is particularly advantageous allowing to directly link on-site spectral information with agronomic algorithms. Sensors are nowadays most frequently used in site-specific oriented applications of fertilizers, but similarly site-specific applications of growth regulators, herbicides and pesticides become more often adopted. Generally little is known about the effects of... B. Mistele, U. Schmidhalter, S. Kipp

11. Comparison of Active and Passive Spectral Sensors in Discriminating Biomass Parameters and Nitrogen Status in Wheat Cultivars

Several sensor systems are available for ground-based remote sensing in crops. Vegetation indices of multiple active and passive sensors have seldom been compared in determining plant health. This study was aimed to compare active and passive sensing systems in terms of their ability to recognize agronomic parameters. One bi-directional passive radiometer (BDR) and three active sensors (Crop Circle, GreenSeeker, and an active flash sensor (AFS)) were tested for their ability to assess six destructively... B. Mistele, U. Schmidhalter, K. Erdle

12. Influence Of Phosphorus Application With Or Without Nitrogen On Oat (Avena Sativa) Grass Nutritive Value And In Situ Digestion Kinetics In Buffalo Bulls

Fodder is the mainstay of ruminant production in majority of developing countries. However, its low yield and poor quality are considered considerable constrains which impede ruminant productivity. Fodder production and its nutritive value can be enhanced by ensuring adequate supply and utilization of nutrients... M.U. Nisa, I. Babar, M. Sarwar, N.A. Tauqir, M.A. Shahzad

13. Ontology for Data Representation in the Production of Cotton Fiber in Brazil

... C.S. Junior, A.R. Hirakawa

14. A Comparison of Plant Temperatures as Measured By Thermal Imaging and Infrared Thermometry

... P. Baresel, B. Mistele, H. Yuncai, U. Schmidhalter, H. Hackl

15. Applications for Precision Agriculture: the Italian Experience of SIRIUS Project

    This paper reports the results of the project SIRIUS (Sustainable Irrigation water management and River-basin... P. Nino, S. Vanino, F. Lupia, F. Altobelli, F. Vuolo, I. Namdarian, C. De michele

16. Using Multiplex® to Manage Nitrogen Variability in Champagne Vineyard

... L. Marine, M. Manon, G. Claire, P. Laurent, F. Mostafa, C. Zoran, B. Naima, D. Sébastien, G. Olivier

17. The Effect of Leaf Orientation on Spray Retention on Blackgrass

Spray application efficiency depends on the pesticide application method as well as target properties. A wide range of drop impact angles exists during the spray application process because of drop trajectory and the variability of the leaf orientation. As the effect of impact angle on retention is still poorly documented, laboratory studies were conducted... F. Lebeau, M. Massinon, P. Maréchal, H. Boukhalfa

18. Comparison of Algorithms for Delineating Management Zones

... A.M. Saraiva, R.T. Santos, J.P. Molin

19. BrainWeed - Teach-In System for Adaptive High Speed Crop / Weed Classification and Targeting

Conducting inter row mechanical weeding requires the precise location of each individual crop plant is known. One technique is to record the global position of each seed when sown using  RTK-GPS systems. Another... R.N. JÃ???Ã??Ã?¸rgensen, H.S. Midtiby, T.M. Giselsson

20. 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

21. Assessing Water Status in Wheat under Field Conditions Using Laser-Induced Chlorophyll Fluorescence and Hyperspectral Measurements

Classical measurements for estimating water status in plants using oven drying or pressure chambers are tedious and time-consuming. In the field, changes in radiation conditions may further influence the measurements and thus require... S. El-sayed, U. Schmidhalter, B. Mistele

22. Physiological Repsonses Of Corn To Variable Seeding Rates In Landscape-Scale Strip Trials

Many producers now have the capability to vary seeding rates on-the-go. Methods are needed to develop variable rate seeding approaches in corn but require an understanding of the physiological response of corn to soil-landscape and weather conditions. Interplant competition fundamentally differs at varied seeding rate and may affect corn leaf area, transpiration, plant morphology, and assimilate partitioning. Optimizing these physiological effects with optimal seeding rates in a site-specific... D.B. Myers, N.R. Kitchen, K.A. Sudduth, B.J. Leonard

23. Creation Of Prescription For Optimal Nitrogen Fertilization Through Evaluation Of Soil Carbon Amount Using Remotely Sensed Data

    In these years, drastic increase of agricultural production costs has been induced, which was triggered by the sharp rise of costs relating to agricultural production materials such as fertilizers and oil. In Japan, the substantial negative influence is anticipated to spread over to management of the farmers particularly  in Hokkaido, the northern part of Japan. As one of the measures against this influence, a plan of effective fertilizer application and also... E. Tamura, K. Aijima, K. Niwa, O. Nagata, K. Wakabayashi, C. Hongo

24. Beyond The 4-Rs Of Nutrient Management In Conjunction With A Major Reduction In Tillage

Agribusiness and government agencies have embraced the 4-R concept (right form, rate, time, and place) to improve nutrient management and environmental quality. No-tillage... J.S. Schepers, B. Mclure, G. Swanson

25. 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

26. Mapping Spatial Production Stability in Integrated Crop and Pasture Systems: Towards Zonal Management That Accounts for Both Yield and Livestock-landscape Interactions.

Precision farming technologies are now widely applied within Australian cropping systems. However, the use of spatial monitoring technologies to investigate livestock and pasture interactions in mixed farming systems remains largely unexplored. Spatio-temporal patterns of grain yield and pasture biomass production were monitored over a four-year period on two Australian mixed farms, one in the south-west of Western Australia and the other in south-east Australia. A production stability index was... P. Mcentee, S. Bennett, M. Trotter, R. Belford, J. Harper

27. 'Spatial Discontinuity Analysis' a Novel Geostatistical Algorithm for On-farm Experimentation

Traditional agronomic experimentation is restricted to small plots. Under appropriate experimental designs the effects of uncontrolled environmental variables are minimized and the measured responses (e.g. in yields) are compared to controllable inputs (seed, tillage, fertilizer, pesticides) using well-trusted design-based statistical methods. However, the implementation of such experiments can be complex and the application, management, and harvesting of treated areas might have to... S. Rudolph, B.P. Marchant, V. Gillingham, D. Kindred, R. Sylvester-bradley

28. Comparison Between Tractor-based and UAV-based Spectrometer Measurements in Winter Wheat

In-season variable rate nitrogen fertilizer application needs a fast and efficient determination of nitrogen status in crops. Common sensor-based monitoring of nitrogen status mainly relies on tractor mounted active or passive sensors. Over the last few years, researchers tested different sensors and indicated the potential of in-season monitoring of nitrogen status by unmanned aerial vehicles (UAVs) in various crops. However, the UAV-platforms and the available sensors are not yet accepted to... M. Gnyp, M. Panitzki, S. Reusch, J. Jasper, A. Bolten, G. Bareth

29. Measuring Pasture Mass and Quality Indices Over Time Using Proximal and Remote Sensors

Traditionally pasture has been measured or evaluated in terms of a dry matter yield estimate, which has no reference to other important quality factors. The work in this paper measures pasture growth rates on different slopes and aspects and pasture quality through nitrogen N% and metabolizable energy and ME concentration. It is known that permanent pasture species vary greatly in terms of quality and nutritional value through different stages of maturity. Pasture quality decreases as grass tillers... I.J. Yule, M.C. Grafton, L.A. Willis, P.J. Mcveagh

30. Analysis of High Yield Condition Using a Rice Yield Predictive Model

Rice production in Japan is facing problems of yield and quality instability owing to recent climate changes and a decline in rice prices, and possible competition with foreign inexpensive rice. Thus, it is becoming more important to stably achieve high yield and quality, while reducing production costs. Various data, including crop growth, farmer’s management styles, yield and quality, has recently become accessible in actual fields using advanced information and communication technologies.... Y. Hirai, T. Yamakawa, E. Inoue, T. Okayasu, M. Mitsuoka

31. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the Netherlands

Precision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traffic... C. Kempenaar, F. Van evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten

32. 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

33. Precision Agriculture Techniques for Crop Management in Trinidad and Tobago: Methodology & Field Layout

Agriculture in Trinidad and Tobago has not advanced at the same rate at which new agricultural technology has been released. This has led to large-scale abandonment of crop lands as challenges posed by labor availability and their agronomic capability could not meet the technological demands for agricultural production, competitiveness and sustainability. There is an urgent need to develop technology-based agriculture models to meet the demands of a modern agricultural sector and to maintain its... G. Seepersad, T. Sampson, S. Seepersad, D. Goorahoo

34. A Tree Planting Site-Specific Fumigant Applicator for Orchard Crops

The goal of this research was to use recent advances in the global positioning system and computer technology to apply just the right amount of fumigant where it is most needed (i.e., in the neighborhood of each tree planting site or tree- planting-site-specific application) to decrease the incidence of replant disease, and achieve the environmental and economical benefits of reducing the application of these toxic chemicals. In the first year of this study we retrofitted a chemical applicator... S.K. Upadhayaya, V. Udompetaikul, M.S. Shafii, G.T. Browne

35. Agronōmics: Eliciting Food Security from Big Data, Big Ideas and Small Farms

Most farmers globally could make their farms more productive; few are limited by ambient availabilities of light energy and water. Similarly the sustainability of farming practices offers large scope for innovation and improvement. However, conventional ‘top-down’ Agricultural Knowledge and Innovation Systems (AKISs) are commonly failing to maintain significant progress in either productivity or sustainability because multifarious and complex agronomic interactions thwart accurate... R. Sylvester-bradley, D. Kindred, P. Berry

36. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural Crops

Aerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. Reddy, D.P. Biradar, V.C. Patil, B.L. Desai, V.B. Nargund, P. Patil, V. Desai, V. Tulasigeri, S.M. Channangi, W. John

37. Practical and Affordable Technologies for Precision Agriculture in Small Fields: Present Status and Scope in India

The objective of this review paper is to find out practical and affordable precision agriculture(PA) technologies present status and scope in India that are suitable for small fields. The judicious use of inputs like water, fertilizers, herbicides, pesticides and better management of farm equipments will increase the net profit for farmers. The important components of PA in India which are being used for small lands are Geographic Information System(GIS), laser land leveler, leaf color chart,... S. Kumar, M. Singh, H. Mirzakhaninafchi, R.U. Modi, M. Ali, M. Bhardwaj, R. Soni

38. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen Rates

Nitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf

39. Supporting and Analysing On-Farm Nitrogen Tramline Trials So Farmers, Industry, Agronomists and Scientists Can LearN Together

Nitrogen fertilizer decisions are considered important for the agronomic, economic and environmental performance of cereal crop production. Despite good recommendation systems large unpredicted variation exists in measured N requirements. There may be fields and farms that are consistently receiving too much or too little N fertilizer, therefore losing substantial profit from wasted fertilizer or lost yield. Precision farming technologies can enable farmers (& researchers) to test appropriate... D. Kindred, R. Sylvester-bradley, S. Clarke, S. Roques, D. Hatley, B. Marchant

40. Improving Corn Nitrogen Rate Recommendations Through Tool Fusion

 Improving corn (Zea maysL,) nitrogen (N) fertilizer rate recommendation tools can improve farmer’s profits and help mitigate N pollution. One way to improve N recommendation methods is to not rely on a single tool, but to employ two or more tools. Thiscould be thoughtof as “tool fusion”.The objective of this analysis was to improve N management by combining N recommendation tools used for guiding rates for an in-seasonN application. This evaluation was... C.J. Ransom, N.R. Kitchen, J.J. Camberato, P.R. Carter, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J. Shanahan, J.E. Sawyer

41. Can Optimization Associated with On-Farm Experimentation Using Site-Specific Technologies Improve Producer Management Decisions?

Crop production input decisions have become increasingly difficult due to uncertainty in global markets, input costs, commodity prices, and price premiums. We hypothesize that if producers had better knowledge of market prices, spatial variability in crop response, and weather conditions that drive crop response to inputs, they could more cost-effectively make profit-maximizing input decisions. Understanding the drivers of variability in crop response and designing accompanying management strategies... B.D. Maxwell, A. Bekkerman, N. Silverman, R. Payn, J. Sheppard, C. Izurieta, P. Davis, P.B. Hegedus

42. Using Deep Learning in Yield and Protein Prediction of Winter Wheat Based on Fertilization Prescriptions in Precision Agriculture

Precision Agriculture has been gaining interest due to the significant growth in the fields of engineering and computer science, hence leading to more sophisticated methods and tools to improve agricultural techniques. One approach to Precision Agriculture involves the application of mathematical models and machine learning to fertilization optimization and yield prediction, which is what this research focuses on. Specifically, in this work we report the results of predicting yield and protein... J. Sheppard, A. Peerlinck, B. Maxwell

43. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your Benefits

Climate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water from... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet

44. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean Yield

The ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-based... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van vliet

45. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural Crops

Aerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. G, D.P. Biradar, B.L. Desai, V.C. Patil, P. Patil, V.B. Nargund, V. Desai, W. John, S.M. Channangi, V. Tulasigeri

46. Sun Effect on the Estimation of Wheat Ear Density by Deep Learning

Ear density is one of the yield components of wheat and therefore a variable of high agronomic interest. Its traditional measurement necessitates laborious human observations in the field or destructive sampling. In the recent years, deep learning based on RGB images has been identified as a low-cost, robust and high-throughput alternative to measure this variable. However, most of the studies were limited to the computer challenge of counting the ears in the images, without aiming to convert... S. Dandrifosse, E. Ennadifi, A. Carlier, B. Gosselin, B. Dumont, B. Mercatoris

47. Investigating the Potential of Visible and Near-infrared Spectroscopy (VNIR) for Detecting Phosphorus Status of Winter Wheat Leaves Grown in Long-term Trial

The determination of plant nutrient content is crucial for evaluating crop nutrient removal, enhancing nutrient use efficiency, and optimizing yields. Nutrient conventional monitoring involves colorimetric analyses in the laboratory; however, this approach is labor-intensive, costly, and time-consuming. The visible and near-infrared spectroscopy (VNIR) or hyperspectral non-imaging sensors have been an emerging technology that has been proved its potential for rapid detection of plant nutrient... Y. El-mejjaouy, B. Dumont, A. Oukarroum, B. Mercatoris , P. Vermeulen

48. Optimizing Nitrogen Application to Maximize Yield and Reduce Environmental Impact in Winter Wheat Production

Field-specific fertilizer rate optimization is known to be beneficial for improving farming profit, and profits can be further improved by dividing the field into smaller plots and applying site-specific rates across the field. Finding optimal rates for these plots is often based on data gathered from said plots, which is used to determine a yield response curve, telling us how much fertilizer needs to be applied to maximize yield. In related work, we use a Convolutional Neural Network, known... A. Peerlinck, J. Sheppard, G.L. Morales luna, P. Hegedus, B. Maxwell

49. Developing a Machine Learning and Proximal Sensing-based In-season Site-specific Nitrogen Management Strategy for Corn in the US Midwest

Effective in-season site-specific nitrogen (N) management strategies are urgently needed to ensure both food security and sustainable agricultural development. Different active canopy sensor-based precision N management strategies have been developed and evaluated in different parts of the world. Recent studies evaluating several sensor-based N recommendation algorithms across the US Midwest indicated that these locally developed algorithms generally did not perform well when used broadly across... D. Li, Y. Miao, .G. Fernández, N.R. Kitchen, C. . Ransom, G.M. Bean, .E. Sawyer, J.J. Camberato, .R. Carter, R.B. Ferguson, D.W. Franzen, D.W. Franzen, D.W. Franzen, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.F. Shanahan

50. Using Informative Bayesian Priors and On-farm Experimentation to Predict Optimal Site-specific Nitrogen Rates

Most U.S. Corn Belt states now recommend the Maximum Return to Nitrogen (MRTN) method for determining optimal nitrogen rates, which is based on 15 years of on-farm yield response to nitrogen trials. The MRTN method recommends a uniform rate for a region of a state. This study combines Illinois MRTN data, Bayesian methods, and on-farm experimentation from the Data Intensive Farm Management (DIFM) project to provide site-specific nitrogen recommendations. On-farm trials are now being used to provide... W. Brorsen, D. Poursina, C. Patterson, T. Mieno, B. Edge, E.D. Nafziger

51. 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

52. Cultivating Future Leaders in Sustainable Agriculture: Insights from the Digital Agriculture Fellowship Program at the University of California, Riverside

Funded by USDA's National Institute of Food and Agriculture’s Sustainable Agricultural Systems Program and housed at the University of California, Riverside (UCR), the Digital Agriculture Fellowship (DAF) aims at equipping undergraduate students with the knowledge and experience necessary to meet the agricultural challenges posed by climate change and sustainability concerns. The program was established in 2020 and will be funded through 2026. Activities span over fifteen months for... E. Scudiero, C.I. Nugent, C. Ng, N. Jones, T. Azzam, N.G. Salunga, S. Lemus

53. Assessing Soybean Water Stress Patterns and ENSO Occurrence in Southern Brazil: an in Silico Approach

Water stress (WS) is one of the most important abiotic stresses worldwide, responsible for crop yield penalties and impacting food supply. The frequency and intensity of weather stresses are relevant to delimitating agricultural regions. In addition, El Nino Southern Oscillation (ENSO) has been employed to forecast the occurrence of seasonal WS. Lastly, planting date and cultivar maturity selection are key management strategies for boosting soybean (Glycine max (L.) Merr.) yield... A. Carcedo, L.F. Antunes de almeida, T. Horbe, G. Corassa, L.P. Pott, I. Ciampitti, G.D. Hintz, T. Hefley, R.A. Schwalbert, V. Prasad