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Vántus, A
Taylor, D
Tabile, R
Theurer, F.D
Tempesta, M
Torino, M.S
Viator, R.P
Tian, L
Tyler, D.D
Vuolo, F
Taubinger, L
Veum, K.S
Videla, H
Tulasigeri, V
Vollmar, J
Voicu, A
Valencia-Correa, J.M
Trotter, M.G
Tanny, J
Thompson, N.M
Taylor, J.A
Venkateswarlu, B
Vilanova Jr., N.
Thurmond, M
Van Donk, S
Vitali, G.-
Tola, E
Tarapues, H.B
Vieri, M.P
Thompson, A
Tateishi, R
Tasissa, A
Tedesco, D
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Authors
Srinivasa Rao, C
Rao, K
Magen, H
Venkateswarlu, B
Subba Rao, A
Amaral, L.R
Molin, J.P
Taubinger, L
Thompson, N.M
Larson, J.A
English, B.C
Lambert, D.M
Roberts, R.K
Velandia, M
Wang, C
Nino, P
Vanino, S
Lupia, F
Altobelli, F
Vuolo, F
Namdarian, I
De Michele, C
Torino, M.S
Ortiz, B.V
Fulton, J.P
Balkcom, K
Shaver, T
Schmer, M
Irmak, S
Van Donk, S
Wienhold, B
Jin, V
Bereuter, A
Francis, D
Rudnick, D
Ward, N
Hendrickson, L
Ferguson, R.B
Adamchuk, V.I
Tremblay, N
Vigneault, P
Bouroubi, M.Y
Dorais, M
Gianquinto, G.P
Tempesta, M
Ahamed, T
Tian, L
Zhang, Y
Xiong, Y
Zhao, B
Jiang, Y
Ting, K
Allphin, E
Kitchen, N.R
Suddeth, K.A
Thompson, A
Bingner, R.L
Wells, R.R
Theurer, F.D
Reusch, S
Jasper, J
Link, A
Vollmar, J
Erdenee, B
Batbayar, B
Tateishi, R
Pagni, P
Ghinassi, G.P
Vieri, M.P
Taylor, D
Stanley, J.S
Lamb, D.W
Trotter, M.G
Rahman, M.M
Thompson, A
Boardman, D.L
Kitchen, N
Allphin, E
Vilanova Jr., N.
Molin, J.P
Portz, C
Posada, L.V
Portz, G
Trevisan, R.G
Tabile, R
Porto, A
Inamasu, R
Sousa, R
Patil, V
Madugundu, R
Tola, E
Marey, S
Mulla, D.J
Upadhyaya, S.K
Al-Gaadi, K.A
Larson, J.A
Stefanini, M
Lambert, D.M
Yin, X
Boyer, C.N
Varco, J.J
Scharf , P.C
Tubaña, B.S
Dunn, D
Savoy, H.J
Buschermohle, M.J
Tyler, D.D
Rozenstein, O
Haymann, N
Kaplan , G
Tanny, J
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
Rátonyi, T
Ragán, P
Sulyok, D
Nagy, J
Harsányi, E
Vántus, A
Csatári, N
Ragán, P
Harsányi, E
Nagy, J
Ágnes, T
Rátonyi, T
Vántus, A
Csatári, N
Nándor, C
Rátonyi, T
Harsányi, E
Ragán, P
Hagymássy, Z
Nagy, J
Vántus, A
Price, R.R
Johnson, R.M
Viator, R.P
Cammarano, D
Drexler, D
Hinsinger, P
Martre, P
Draye, X
Sessitsch, A
Pecchioni, N
Cooper, J
Helga, W
Voicu, A
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
Pasquel, D
Roux, S
Tisseyre, B
Taylor, J.A
Oliveira, M.F
Carneiro, F.M
Thurmond, M
del Val, M.D
Oliveira, L.P
Ortiz, B
Sanz-Saez, A
Tedesco, D
Ransom, C.J
Vong, C
Veum, K.S
Sudduth, K.A
Kitchen, N.R
Zhou, J
Balboa, G
Degioanni, A
Bongiovanni, R
Melchiori, R
Cerliani, C
Scaramuzza, F
Bongiovanni, M
Gonzalez, J
Balzarini, M
Videla, H
Amin, S
Esposito, G
Aliloo, J
Abbasi, E
Karamidehkordi , E
Ghanbari Parmehr, E
Canavari, M
Vitali, G.-
Ome Narvaez, J.D
Sandoval, D.F
Galeano, S.A
Tarapues, H.B
Estrada, A
Zuñiga, J.P
Valencia-Correa, J.M
Tasissa, A
Lichtenberg,, S
Vitali, G.-
Ferraz, C
Tasissa, A
Li, L
Murphy, J.M
Topics
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Profitability, Sustainability and Adoption
Remote Sensing Applications in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Spatial Variability in Crop, Soil and Natural Resources
Precision Horticulture
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Conservation
Precision A-Z for Practitioners
Global Proliferation of Precision Agriculture and its Applications
Sensor Application in Managing In-season Crop Variability
Precision Livestock Management
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Sensor Application in Managing In-season CropVariability
Engineering Technologies and Advances
Precision Nutrient Management
Profitability, Sustainability and Adoption
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Applications of Unmanned Aerial Systems
On Farm Experimentation with Site-Specific Technologies
Precision Dairy and Livestock Management
Geospatial Data
Big Data, Data Mining and Deep Learning
Geospatial Data
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Education and Outreach in Precision Agriculture
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Geospatial Data
Wireless Sensor Networks and Farm Connectivity
Decision Support Systems
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Filter results37 paper(s) found.

1. Site-specific Management For Biomass Feedstock Production: Development Of Remote Sensing Data Acquisition Systems

Efficient biomass feedstock production supply chain spans from site-specific management of crops on field to the gate of biorefinery. Remote sensing data acquisition systems have been introduced for site-specific management, which is a part of the engineering solutions for biomass feedstock production. A stand alone tower remote sensing platform was developed to monitor energy crops using multispectral imagery. The sensing system was capable of collecting RGB and CIR images during the crop growing... T. Ahamed, L. Tian, Y. Zhang, Y. Xiong, B. Zhao, Y. Jiang, K. Ting

2. Nitrogen Loss In Corn Production Varies As A Function Of Topsoil Depth

  Understanding availability and loss potential of nitrogen for varying topsoil depths of poorly-drained claypan soil landscapes could help producers make improve decisions when managing crops for feed grain or bio-fuels.  While it has been well documented that topsoil depth on these soils plays an important role in storing water for crop growth, it is not well known how this same soil... E. Allphin, N.R. Kitchen, K.A. Suddeth, A. Thompson

3. Development And Application Of Gully Erosion Components Within The USDA Annagnps Watershed Model For Precision Conservation

A watershed scale assessment of the effect of conservation practices on the environment is critical when recommending conservation management practices to agricultural producers. The identification of all sources of sediment and subsequent tracking of the movement of sediment downstream is a necessary part of this assessment including the often overlooked contributions from gully erosion sources. Pollutant loading allocations established with comprehensive studies of all sediment sources... R.L. Bingner, R.R. Wells, F.D. Theurer

4. Estimating Crop Biomass And Nitrogen Uptake Using Cropspectm, A Newly Developed Active Crop-canopy Reflectance Sensor

  In-season variable rate nitrogen fertilizer application needs efficient determination of the nitrogen nutrition status of crops with high spatial and temporal resolution. A suitable approach to get this information fast and at low cost is proximal sensing of the light that is reflected from the crop canopy. CropSpecTM is an active vehicle mounted crop canopy sensor. Using pulsed laser diodes as light source, the sensor is designed to look at the crop at an oblique... S. Reusch, J. Jasper, A. Link, J. Vollmar

5. Land Information System Of Precision Farming In Mongolia Using Remote Sensing And Geographical Information System

    Remote sensing (RS) and geographic information system (GIS) technologies have been of great use to planners in planning for efficient use of natural resources at national, sub region and rural levels.   RS can be used for precision farming in a number of ways for providing input supplies and variability management through decision support system.   GIS is the principal technology used to integrate spatial data... B. Erdenee, B. Batbayar, R. Tateishi

6. Optimizing Vineyard Irrigation Through The Automatic Resistivity Profiling (arp) Technology. The Proposal Of A Methodological Approach

 In Tuscany, central Italy, grape cultivation and wine production (i.e., Chianti DOCG, Brunello di Montalcino) are farming activities appreciated worldwide. Differently from the past, irrigation is allowed to meet the intense physiological stress that may occur during seasons affected by the increasing climate variability, in order to guarantee quality product and hence high market profitability in many vines areas. Most vineyards... P. Pagni, G.P. Ghinassi, M.P. Vieri

7. Gps Tracking Of Sheep To Investigate Shelter And Shade Use In Relation To Climatic Conditions

In Australia inclement weather contributes to losses of new-born lambs and recently-shorn sheep. Provision of forced shelter has been observed to reduce lamb losses by up to 10 percent and when given a choice, ewes preferentially seek shelter on offer for a period of approximately two weeks post shearing (Alexander et al. 1980). Given significant sheep losses can occur during adverse weather conditions a better understanding of sheep use of shelter and/or alternative ways of attracting sheep to... D. Taylor, , , , , ,

8. Categorization of Districts Based on Nonexchangeable Potassium: Generation GIS Maps and Implications in Efficient K Fertility Management in Indian Agriculture

Recommendations of K fertilizer are made based on available (exchangeable + water soluble) K status only  in India and other despite of  substantial contribution of nonexchangeable fraction of soil K to crop K uptake. Present paper examines the information generated in the last 30 years on the status of nonexchangeable K in Indian soils, categorization of Indian soils based on exchangeable and nonexchangeable K fractions and making K recommendations. Data for both K fractions of different... C. Srinivasa rao, K. Rao, H. Magen, B. Venkateswarlu, A. Subba rao

9. Vegetation Indices from Active Crop Canopy Sensor and Their Potential Interference Factors on Sugarcane

Among the inputs usually used in the sugarcane production the nitrogen (N) is the most significant. With the use of ground-based canopy sensors to obtain vegetation indexes (VI), it is possible to obtain recommendations of nutrient supply in... L.R. Amaral, J.P. Molin, L. Taubinger

10. The Adoption of Information Technologies and Subsequent Changes in Input Use in Cotton Production

The use of precision farming has become increasingly important in cotton production. It allows farmers to take advantage of knowledge about infield variability by applying expensive inputs at levels appropriate to crop needs. Essential to the success of the precision... N.M. Thompson, J.A. Larson, B.C. English, D.M. Lambert, R.K. Roberts, M. Velandia, C. Wang

11. 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

12. Evaluation of Differences in Corn Biomass and Nitrogen Uptake at Various Growth Stages Using Spectral Vegetation Indices

Application of canopy sensors for nitrogen (N) fertilizer management for corn grain production in the Southeast US requires... M.S. Torino, B.V. Ortiz, J. Fulton, K. Balkcom

13. Landscape Influences on Soil Nitrogen Supply and Water Holding Capacity for Irrigated Corn

... T. Shaver, M. Schmer, S. Irmak, S. Van donk, B. Wienhold, V. Jin, A. Bereuter, D. Francis, D. Rudnick, N. Ward, L. Hendrickson, R. Ferguson, V.I. Adamchuk

14. Remote Sensing of Nitrogen and Water Status on Boston Lettuce Transplants in a Greenhouse Environment

Remote sensing is the stand-off collection through the use of a variety of devices for gathering information on a given object or area. Applied as a warning tool in plant stock production, it is expected to help in the achievement of better, more uniform and more productive organic cropping systems. Remote sensing of vegetation targets can be achieved from the... N. Tremblay, P. Vigneault, M.Y. Bouroubi, M. Dorais, G.P. Gianquinto, M. Tempesta

15. NDVI 'Depression' In Pastures Following Grazing

Pasture biomass estimation from normalized difference vegetation index (NDVI) using ground, air or space borne sensors is becoming more widely used in precision agriculture. Proximal active optical sensors (AOS) have the potential to eliminate the confounding effects of path radiance and target illumination conditions typically encountered using passive sensors. Any algorithm that infers the green fraction of pasture from NDVI must factor in plant morphology and live/dead plant ratio, irrespective... J.S. Stanley, D.W. Lamb, M.G. Trotter, M.M. Rahman

16. Water And Nitrogen Use Efficiency Of Corn And Switchgrass On Claypan Soil Landscapes

Claypan soils cover a significant portion of Missouri and Illinois crop land, approximately 4 million ha. Claypan soils, characterized with a pronounced argilic horizon at or below the soil surface, can restrict nutrient availability and uptake, plant water storage, and water infiltration. These soil characteristics affect plant growth, with increasing depth of the topsoil above the claypan horizon having a strong positive correlation to grain crop production. In the case of low... A. Thompson, D.L. Boardman, N. Kitchen, E. Allphin

17. Cotton Field Relations Of Plant Height To Biomass Accumulation And N-Uptake On Conventional And Narrow Row Systems

Although studied for decades, cotton field management remains a challenge for growers, especially due to spatial variability of soil conditions and crop growth, which demands the use of variable rate application technology (VRT) for nitrogen and growth regulators to improve yields and quality and/or save inputs. Canopy optical reflectance sensors are being studied as an option to detect infield variability but may have some limitations due to the known effect of signal saturation when used... N. . Vilanova jr., J.P. Molin, C. Portz, L.V. Posada, G. Portz, R.G. Trevisan

18. Agribot: Development Of A Mobile Robotic Platform To Support Agricultural Data Collection

Precision Agriculture and agricultural practices that take into account environment protection, leads to several research challenges. Sampling scale and the precision required by these new agricultural practices are often greater than those required by traditional agriculture, raising the costs of production. This whole process requests an expressive number of researches in developing automation instruments. Amongst them, the use of remote sensing techniques based on On-the-Go sensors... R. Tabile, A. Porto, R. Inamasu, R. Sousa

19. Response Of Rhodes Grass (Chloris Gayana Kunth) To Variable Rate Application Of Irrigation Water And Fertilizer Nitrogen

Rhodes grass is cultivated extensively in Saudi Arabia under center pivot sprinkler irrigation system. The research work was carried out to optimize irrigation water and fertilizer nitrogen levels for the crop. The objectives of the study were: 1. To delineate the field in to management zones, 2. To study the effects of variable rate application (VRA) of irrigation water and fertilizer nitrogen on the yield of Rhodes grass. A field experiment was carried out from... V. Patil, R. Madugundu, E. Tola, S. Marey, D.J. Mulla, S.K. Upadhyaya, K.A. Al-gaadi

20. Net Returns and Production Use Efficiency for Optical Sensing and Variable Rate Nitrogen Technologies in Cotton Production

This research evaluated the profitability and N use efficiency of real time on-the-go optical sensing measurements (OPM) and variable-rate technologies (VRT) to manage spatial variability in cotton production in the Mississippi River Basin states of Louisiana, Mississippi, Missouri, and Tennessee. Two forms of OPM and VRT and the existing farmer practice (FP) were used to determine N fertilizer rates applied to cotton on farm fields in the four states. Changes in yields and N rates due to OPM... J.A. Larson, M. Stefanini, D.M. Lambert, X. Yin, C.N. Boyer, J.J. Varco, P.C. Scharf , B.S. Tubaña, D. Dunn, H.J. Savoy, M.J. Buschermohle, D.D. Tyler

21. Estimating Cotton Water Requirements Using Sentinel-2

Crop coefficient (Kc)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management.  Spectral modeling of Kc is possible due to the high correlations between Kc and the crop phenologic development and spectral reflectance.  In this study, cotton evapotranspiration was measured in the field using several methods, including eddy covariance, surface renewal, and heat pulse.  Kc was estimated as the ratio between reference evapotranspiration... O. Rozenstein, N. Haymann, G. Kaplan , J. Tanny

22. 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

23. Evaluation of Strip Tillage Systems in Maize Production in Hungary

Strip tillage is a form of conservation tillage system. It combines the benefits of conventional tillage systems with the soil-protecting advantages of no-tillage. The tillage zone is typically 0.25 to 0.3 m wide and 0.25 to 0.30 m deep. The soil surface between these strips is left undisturbed and the residue from the previous crop remain on the soil surface. The residue-covered area reaches 60-70%. Keeping residue on the surface helps prevent soil structure and reduce water loss from the soil.... T. Rátonyi, P. Ragán, D. Sulyok, J. Nagy, E. Harsányi, A. Vántus, N. Csatári

24. Examining the Relationship Between SPAD, LAI and NDVI Values in a Maize Long-Term Experiment

In Hungary, the preconditions for the use of precision crop production have undergone enormous development over the last five years. RTK coverage is complete in crop production areas. Consultants are increasingly using the vegetation index maps from Landsat and Sentinel satellite data, but measurements with on-site proximal plant sensors are also needed to exclude the influence of the atmosphere. The aim of our studies was to compare the values measured by proximal plant sensors in the... P. Ragán, E. Harsányi, J. Nagy, T. Ágnes, T. Rátonyi, A. Vántus, N. Csatári

25. The Spread of Precision Livestock Farming Technology at Dairy Farms in East Hungary

During the survey, 25 dairy farms were examined in East Hungary in Hajdú-Bihar (H-B) County between 2017 and 2018 by methodical observation and oral interviews with the farm managers, about the spread of Precision Livestock Farming (PLF) technologies. Among Holstein Friesian dairy farms in the County 60% were questioned, and the representativity was above 47 percent ins each size category. Nine precision farming equipment were examined on the farms: milking robot or robotic carousel milking... C. Nándor, T. Rátonyi, E. Harsányi, P. Ragán, Z. Hagymássy, J. Nagy, A. Vántus

26. Development of an Overhead Optical Yield Monitor for a Sugarcane Harvester in Louisiana

A yield monitor is a device used to measure harvested crop weight per unit area for a specific location within a field.  The device documents yield variability in harvested fields and ultimately can be used to create a geographical-referenced yield map. Yield maps can be used to identify low yielding areas where poor soil fertility, disease, or pests may adversely affect yield.  Management practices can then be adjusted to correct these issues, resulting in an increase in yields and... R.R. Price, R.M. Johnson, R.P. Viator

27. Shared Protocols and Data Template in Agronomic Trials

Due to the overlap of many disciplines and the availability of novel technologies, modern agriculture has become a wide, interdisciplinary endeavor, especially in Precision Agriculture. The adoption of a standard format for reporting field experiments can help researchers to focus on the data rather than on re-formatting and understanding the structure of the data. This paper describes how a European consortium plans to: i) create a “handbook” of protocols for reporting definitions,... D. Cammarano, D. Drexler, P. Hinsinger, P. Martre, X. Draye, A. Sessitsch, N. Pecchioni, J. Cooper, W. Helga, A. Voicu

28. 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

29. Comparison of Different Aspatial and Spatial Indicators to Assess Performance of Spatialized Crop Models at Different Within-field Scales

Most current crop models are point-based models, i.e. they simulate agronomic variables on a spatial footprint on which they were initially designed (e.g. plant, field, region scale). To assess their performances, many indicators based on the comparison of estimated vs observed data, can be used such as root mean square error (RMSE) or Willmott index of agreement (D-index) among others. However, shifting model use from a strategic objective to tactical in-season management is becoming a significant... D. Pasquel, S. Roux, B. Tisseyre, J.A. Taylor

30. Predicting Below and Above Ground Peanut Biomass and Maturity Using Multi-target Regression

Peanut growth and maturity prediction can help farmers and breeding programs improving crop management. Remote sensing images collected by satellites and drones make possible and accurate crop monitoring. Today, empirical relations between crop biomass and spectral reflectance could be used for prediction of single variables such as aboveground crop biomass, pod weight (PW), or peanut maturity. Robust algorithms such as multioutput regression (MTR) implemented through multioutput random forest... M.F. Oliveira, F.M. Carneiro, M. Thurmond, M.D. Del val, L.P. Oliveira, B. Ortiz, A. Sanz-saez, D. Tedesco

31. Estimating Soil Carbon Stocks with In-field Visible and Near-infrared Spectroscopy

Agricultural lands can be a sink for carbon and play an important role in offsetting carbon emissions. Current methods of measuring carbon sequestration—through repeated temporal soil samples—are costly and laborious. A promising alternative is using visible, near-infrared (VNIR) diffuse reflectance spectroscopy. However, VNIR data are complex, which requires several data processing steps and often yields inconsistent results, especially when using in situ VNIR measurements. Using... C.J. Ransom, C. Vong, K.S. Veum, K.A. Sudduth, N.R. Kitchen, J. Zhou

32. Overcoming Educational Barriers for Precision Agriculture Adoption: a University Diploma in Precision Agriculture in Argentina

The lack of educational programs in Precision Agriculture (PA) has been reported as one of the barriers for adoption. Our goal was to improve professional competence in PA through education in crop variability, management, and effective practices of PA in real cases. In the last 20 years different efforts has been made in Argentina to increase adoption of PA. The Universidad Nacional de Rio Cuarto (UNRC) launched in 2021 the first University Diploma in PA, a 9-month program to train agronomist... G. Balboa, A. Degioanni, R. Bongiovanni, R. Melchiori, C. Cerliani, F. Scaramuzza, M. Bongiovanni, J. Gonzalez, M. Balzarini, H. Videla, S. Amin, G. Esposito

33. 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

34. Developing Geospatial Method for Autopilot Harvester Trampling Evaluation in Colombian Sugarcane Fields

Sugarcane is a crop of great importance for the geographical valley of the Cauca River in Colombia, where it covers approximately 241,000 hectares and is cultivated by 13 sugar mills and about 4,200 cultivators. This region is characterized by its favorable climate, which enables year-round sugarcane harvesting and its high productivity, making it a global leader in this sector. This achievement is largely attributed to the technological advances developed by Colombia Sugarcane Research Center... J.D. Ome narvaez, D.F. Sandoval, S.A. Galeano, H.B. Tarapues, A. Estrada, J.P. Zuñiga, J.M. Valencia-correa

35. Nystrom-based Localization in Precision Agriculture Sensors

Wireless sensor networks play a pivotal role in a myriad of applications, ranging from agriculture and health monitoring and to tracking and structural health monitoring. One crucial aspect of these applications involves accurately determining the positions of the sensors. In this study, we study a novel Nystrom-based sampling protocol in which a selected group of anchor nodes, with known locations, establish communication with only a subset of the remaining sensor nodes. Leveraging partial distance... A. Tasissa, S. Lichtenberg,

36. AI Tools in Agri DSS Pipeline - the Case of Irrigated Sugarbeet

A general pipeline that can be associated to a DSS includes several steps. Data Collectionn includes Acquisition, extraction, and aggregation of data from previously identified and selected sources. Data Cleaning and preparation make data available for exploratory analysis that make them usable. Data Analysis is then applied to extract meaningful information e.g. by statistical and/or simulation models. Data are successively synthesized and visualized to make them clear to the decision-maker to... G.-. Vitali, C. Ferraz

37. Sparse Coding for Classification Via a Locality Regularizer: with Applications to Agriculture

High-dimensional data is commonly encountered in various applications, including genomics, as well as image and video processing. Analyzing, computing, and visualizing such data pose significant challenges. Feature extraction methods become crucial in addressing these challenges by obtaining compressed representations that are suitable for analysis and downstream tasks. One effective technique along these lines is sparse coding, which involves representing data as a sparse linear combination of... A. Tasissa, L. Li, J.M. Murphy