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Jara, L.A
Maxton, C
Machiraju, R
Jin, V
Martin, D.L
March, M
McArtor, B
Jadhav, B.T
Jedmowski, C
Muharam, F
Martinez-Guanter, J
Joshi, N
Mclure, B
Mulla, D.J
Magalh, P.S
Montero Pinilla, O.G
Matocha, C
McDonald, T.P
Marchant, B.P
MASIP, J
McLaren, A
Molin, J.P
Molin, J.P
McPherson, T
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Authors
Lund, E
Maxton, C
Kweon, G
Arno, J
DEL MORAL, I
Escolà, A
Company, J
MARTÍNEZ-CASASNOVAS, J.A
MASIP, J
SANZ, R
ROSELL, J.R
maas, S
Muharam, F
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
Acosta, L.E
Jara, L.A
Ortega, R.A
Poncet, A.M
McDonald, T.P
Pate, G
TISSEYRE, B
Fulton, J.P
Mueller, T
Matocha, C
Sikora, F
Mijatovic, B
Rienzi, E
Pan, L
Adamchuk, V.I
Martin, D.L
Schroeder, M.A
Fergugson, R.B
Cerri, D.G
Magalh, P.S
Stombaugh, T
Zandonadi, R.S
Luck, J.D
McDonald, T.P
McGraw, T
Fulton, J.P
Darr, M.J
Taylor, R.K
McDonald, T.P
Sharda, A
Luck, J.D
Fulton, J.P
Shearer, S.A
McDonald, T.P
Mullenix, D
Anselmi, A.A
Molin, J.P
Khosla, R
Anselmi, A.A
Federizzi , L.C
Bredemeier, C
Molin, J.P
Vilanova Jr., N.
Molin, J.P
Portz, C
Posada, L.V
Portz, G
Trevisan, R.G
Molin, J.P
Colaço, A.F
Ruiz, M
Yida, D
Molin, J.P
Colaço, A.F
Eitelwein, M.T
Molin, J.P
Spekken, M
Trevisan, R.G
Patil, V
Madugundu, R
Tola, E
Marey, S
Mulla, D.J
Upadhyaya, S.K
Al-Gaadi, K.A
Schepers, J.S
Mclure, B
Swanson, G
Rudolph, S
Marchant, B.P
Gillingham, V
Kindred, D
Sylvester-Bradley, R
Canata, T.F
Molin, J.P
Colaço, A.F
Trevisan, R.G
Fiorio, P.R
Martello, M
Trevisan, R.G
Eitelwein, M.T
Colaço, A.F
Molin, J.P
Portz, G
Jasper, J
Molin, J.P
Poncet, A.M
Fulton, J.P
McDonald, T.P
Knappenberger, T
Bridges, R.W
Shaw, J
Balkcom, K
Lund, E
Maxton, C
Lund, T
Dongare, M.L
Jadhav, B.T
Shaligram, A.D
Trevisan, R.G
Eitelwein, M.T
Ferraz, M.N
Tavares, T.R
Molin, J.P
Neves, D.C
Laamrani, A
Berg, A
March, M
McLaren, A
Martin, R
Perez-Ruiz, M
Apolo-Apolo, E
Egea, G
Martinez-Guanter, J
Marin-Barrero, C
Muller, O
Keller, B
Zimmermanm, L
Jedmowski, C
Pingle, V
Acebron, K
Zendonadi, N
Steier, A
Pieruschka, R
Schurr, U
Rascher, U
Kraska, T
Mizuta, K
Miao, Y
Morales, A.C
Lacerda, L.N
Cammarano, D
Nielsen, R.L
Gunzenhauser, R
Kuehner, K
Wakahara, S
Coulter, J.A
Mulla, D.J
Quinn, D.
McArtor, B
Lund, E
Lund, T
Maxton, C
Da Silva, M.L
Alves de Lima, J.
Balbinot, A
Molin, J.P
Filippi, P
Bishop, T
Al-Shammari, D
McPherson, T
Neupane, J
Joshi, N
Fulton, J.P
Khanal, S
B K, A
Bhattarai, B
Rubaino Sosa, S.A
Cristancho Rojas, O.Y
Leon Rueda, W.A
Montero Pinilla, O.G
Roa Bello, J.C
Lizarazo Salcedo, I.A
Martinez Martinez, L.J
Waltz, L
Khanal, S
Katari, S
Hong, C
Anup, A
Colbert, J
Potlapally, A
Dill, T
Porter, C
Engle, J
Stewart, C
Subramoni, H
Machiraju, R
Ortez, O
Lindsey, L
Nandi, A
Balboa, G
Masnello, J.C
De Oliveira Moreira, F
Canal Filho, R
Da Silva, E.R
Molin, J.P
Topics
Proximal Sensing in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Precision Horticulture
Education and Training in Precision Agriculture
Precision Conservation and Carbon Management
Modeling and Geo-statistics
Engineering Technologies and Advances
Optimizing Farm-level use of Spatial Technologies
Spatial Variability in Crop, Soil and Natural Resources
Profitability, Sustainability and Adoption
Sensor Application in Managing In-season CropVariability
Precision Fertilization of Horticultural Crops
Precision Horticulture
Precision Nutrient Management
Big Data Mining & Statistical Issues in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Sensor Application in Managing In-season Crop Variability
Proximal Sensing in Precision Agriculture
Education and Outreach in Precision Agriculture
Precision Crop Protection
Applications of Unmanned Aerial Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
In-Season Nitrogen Management
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Data Analytics for Production Ag
Decision Support Systems
Site-Specific Nutrient, Lime and Seed Management
Scouting and Field Data collection with Unmanned Aerial Systems
Artificial Intelligence (AI) in Agriculture
Demonstration
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Filter results39 paper(s) found.

1. Analysis Of Water Use Efficiency Using On-the-go Soil Sensing And A Wireless Network

An efficient irrigation system should meet the demands of the growing crops. While limited water supply may result in yield reduction, excess irrigation is a waste of resources. To investigate water use efficiency, on-the-go sensing technology was used to reveal soil spatial variability relevant to water holding capacity (in this example, field elevation and apparent electrical conductivity). These high-density data layers were used to identify strategic sites where monitoring water availability... L. Pan, V.I. Adamchuk, D.L. Martin, M.A. Schroeder, R.B. Fergugson

2. Developing Of A Monitoring System Of Cutting, Carrying, And Transportation Of Sugar Cane In Order To Manage Fleet

In the productive process for obtaining sugar cane products, the costs associated to the activities of harvesting (cut), carrying and transport (CCT), represent great part of the final cost of the product. In order to reduce this costs new technologies should be adopted in the agricultural mechanization using precision agriculture methods. The use of the information technology combined with the use of intelligent components can help to improve the performance of machines and equipments and... D.G. Cerri, P.S. Magalh

3. Tools For Evaluating The Potential Of Automatic Section Control

One of the newest technologies in precision agriculture is automatic section control on application equipment. This technology has tremendous potential to reduce wasted inputs, especially on irregularly shaped fields. Paybacks are not necessarily as great on rectangular fields. Producers considering adoption of the technology need to decide whether they will receive sufficient payback for their field shapes. They must also decide... T. Stombaugh, R.S. Zandonadi, J.D. Luck, T.P. Mcdonald, T. Mcgraw

4. Proper Implementation Of Precision Agricultural Technologies For Conducting On-farm Research

Precision agricultural technologies provide farmers, practitioners and researchers the ability to conduct on-farm or field-scale research to refine farm management, improve long term crop production decisions, and implement site-specific management strategies. However, the limitations of these technologies must be understood to draw accurate and meaningful conclusions from such investigations. Therefore, the objective of this paper was to outline the limitations of several... J.P. Fulton, M.J. Darr, R.K. Taylor, T.P. Mcdonald

5. Tip Flow Uniformity When Using Different Automatic Section Control Technologies During Field Operations

Automatic section control (ASC) technology provides a means to reduce double-coverage and application in unwanted areas thereby leading to input savings and improved environmental stewardship.  However, the impact of ASC on spray boom dynamics and tip flow uniformity are unknown. Therefore, a study was conducted to evaluate tip flow rate uniformity and control system response in maintaining target application rates during field operation. Field experiments were conducted using two self-propelled... A. Sharda, J.D. Luck, J.P. Fulton, S.A. Shearer, T.P. Mcdonald, D. Mullenix

6. The Ultimate Soil Survey in One Pass: Soil Texture, Organic Matter, pH, Elevation, Slope, and Curvature

The goal of accurately mapping soil variability preceded GPS-aided agriculture, and has been a challenging aspect of precision agriculture since its inception.  Many studies have found the range of spatial dependence is shorter than the distances used in most grid sampling.  Other studies have examined variability within government soil surveys and concluded that they have limited utility in many precision applications.  Proximal soil sensing has long been envisioned as a method... E. Lund, C. Maxton, G. Kweon

7. Mapping the Leaf Area Index In Vineyard Using a Ground-Based LIDAR Scanner

The leaf area index (LAI) is defined as the one-sided leaf area per unit ground area and is probably the most widely used index to characterize grapevine vigour. However, direct LAI measurement requires the use of destructive leaves sampling methods which are costly and time-consuming and so are other indirect methods. Faced with these techniques, vineyard leaf area can be indirectly estimated using ground-based LIDAR sensors that scan the vines and get information about the geometry and/or structure... J. Arno, I. Del moral, A. Escolà, J. Company, J.A. MartÍnez-casasnovas, J. Masip, R. Sanz, J.R. Rosell

8. Impact of Nitrogen (N) Fertilization on the Reflectance of Cotton Plants at Different Spatial Scales

This study was conducted to examine the reflectance of cotton plants measured at three different spatial scales: individual leaf, canopy, and scene, in relation to N treatment effects, and consequently to select the best spatial scale(s) for estimating chlorophyll or N contents. At the leaf scale, N treatments effects were most apparent at 550... S. Maas, F. Muharam

9. 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

10. Use of Cluster Regression for Yield Prediction in Wine Grape

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11. Maximizing Agriculture Equipment Capacity Using Precision Agriculture Technologies

Guidance systems are one of the primary Precision Agriculture technologies adopted by US farmers. While most practitioners establish their initial AB lines for fields based on previous management patterns, a potential exists in conducting analyses to establish AB lines or traffic patterns which maximize field capacity. The objective of this study was to... A.M. Poncet, T.P. Mcdonald, G. Pate, B. Tisseyre, J.P. Fulton

12. Soil Organic Carbon Multivariate Predictions Based on Diffuse Spectral Reflectance: Impact of Soil Moisture

Spatial predictions of soil organic carbon (OC) developed with proximal and remotely sensed diffuse reflectance spectra are complicated by field soil moisture variation. Our objective was to determine how moisture impacted spectral reflectance and Walkley-Black OC predictions. Soil reflectance from the North American Proficiency Testing... T. Mueller, C. Matocha, F. Sikora, B. Mijatovic, E. Rienzi

13. Optimization Of Maize Yield: Relationship Between Management Zones, Hybrids And Plant Population

Corn is highly sensitive to variations in plant population and it is one of the most important practices influencing in grain yield. Knowledge about plant physiology and morphology allow understanding how the crop interacts with plant population variation. Considering that for each production system there is a population that optimizes the use of available resources it is necessary to manage plant population to reach maximum grain yield on each particular environment. This study... A.A. Anselmi, J.P. Molin, R. Khosla

14. Factors Related To Adoption Of Precision Agriculture Technologies In Southern Brazil

The adoption of technologies which allow the increase of food production with improving quality in addition to reduce the foot prints in the environment is important for agribusiness development. Precision Agriculture (PA) stands out as an option to aid the achievement of these goals. Brazil plays an important role to supply agricultural products and to demand technologies. However, research has focused on technical and economic implementation of PA technologies. Therefore, more information... A.A. Anselmi, L.C. Federizzi , C. Bredemeier, J.P. Molin

15. 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

16. A Five Year Study Of Variable Rate Fertilization In Citrus

Citrus is a major crops in Brazil, especially in the São Paulo state, which is the main citrus production region in the world. Yet, site specific technology is still in early stages of adoption. Variable rate application of inputs is the most important tool in a Precision Agriculture system, however its effect on citrus agronomical aspects are still unknown, especially during long periods of observation. Thus, variable rate fertilizer application has been tested in citrus... J.P. Molin, A.F. Colaço

17. Management Zones Delineation In Brazilian Citrus Orchards

Precision Agriculture (PA) is in its first steps in Brazil citrus production. Variable rate fertilization based on soil grid sampling and yield maps has been tested in São Paulo orchards. In a long term study results showed potential on increasing fertilizer use efficiency and improving soil fertility management. Despite the good results, in some cases it is noticed that systematic methods of investigation (grid sampling and yield data) and prescription (standardized prescription equations)... M. Ruiz, D. Yida, J.P. Molin, A.F. Colaço

18. Assessing Definition Of Management Zones Trough Yield Maps

Yield mapping is one of the core tools of precision agriculture, showing the result of combined growing factors. In a series of yield maps collected along seasons it is possible to observe not only the spatial distribution of the productivity but also its spatial consistency among different seasons. This work proposes the study of distinct methods to analyze yield stability in grain crops regarding its potential for defining management zones from a historical sequence of yield maps. Two methods... M.T. Eitelwein, J.P. Molin, M. Spekken, R.G. Trevisan

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. 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

21. '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

22. Measuring Height of Sugarcane Plants Through LiDAR Technology

Sugarcane (Saccharum spp.) has an important economic role in Brazilian agriculture, especially in São Paulo State. Variation in the volume of plants can be an indicative of biomass which, for sugarcane, strongly relates to the yield. Laser sensors, like LiDAR (Light Detection and Ranging), has been employed to estimate yield for corn, wheat and monitoring forests. The main advantage of using this type of sensor is the capability of real-time data acquisition in a non-destructive way, previously... T.F. Canata, J.P. Molin, A.F. Colaço, R.G. Trevisan, P.R. Fiorio, M. Martello

23. Sources of Information to Delineate Management Zones for Cotton

Cotton in Brazil is an input-intensive crop. Due to its cultivation in large fields, the spatial variability takes an important role in the management actions. Yield maps are a prime information to guide site-specific practices including delineation of management zones (MZ), but its adoption still faces big challenges. Other information such as historical satellite imagery or soil electrical conductivity might help delineating MZ as well as predicting crop performance. The objective of this work... R.G. Trevisan, M.T. Eitelwein, A.F. Colaço, J.P. Molin

24. Prediction of Sugarcane Yields in Commercial Fields by Early Measurements with an Optical Crop Canopy Sensor

As a grass (Poaceae), sugarcane needs supplemental mineral nitrogen (N) to achieve high yields on commercial production areas. In Brazil, N recommendations for sugarcane ratoons are based on expected yield and the results of N response trials, as soil N analyses are not a suitable basis for decisions on optimum N fertilizer rates under tropical conditions. Since the vegetative parts in sugarcane are harvested, yield components such as the number of stalks and stalk height are directly correlated... G. Portz, J. Jasper, J.P. Molin

25. Measurement of In-field Variability for Active Seeding Depth Applications in Southeastern US

Proper seeding depth control is essential to optimize row-crop planter performance, and adjustment of planter settings to within field spatial variability is required to maximize crop yield potential. The objectives of this study were to characterize planting depth response to varying soil conditions within fields, and to discuss implementation of active seeding depth technologies in Southeastern US. This study was conducted in 2014 and 2015 in central Alabama for non-irrigated maize (Zea mays... A.M. Poncet, J.P. Fulton, T.P. Mcdonald, T. Knappenberger, R.W. Bridges, J. Shaw, K. Balkcom

26. A Data Fusion Method for Yield and Soil Sensor Maps

Utilizing yield maps to their full potential has been one of the challenges in precision agriculture.  A key objective for understanding patterns of yield variation is to derive management zones, with the expectation that several years of quality yield data will delineate consistent productivity zones.  The anticipated outcome is a map that shows where soil productive potentials differ.  In spite of the widespread usage of yield monitors, commercial agriculture has found it difficult... E. Lund, C. Maxton, T. Lund

27. Refractive Index Based Brix Measurement System for Sugar and Allied Industries

An attempt has been made to design optimization of Refractormetric based method for the measurement of Brix.  Optimization of various constructional parameters including selection and location of source, prism and detector, position of source, angular position and height of source from prism plane, divergent angle of source, refractive index of prism, size of prism, the location of detector to pick up the optimum reflected light, refractive index of sample, critical angle, choice of suitable... M.L. Dongare, B.T. Jadhav, A.D. Shaligram

28. Optimum Spatial Resolution for Precision Weed Management

The occurrence and number of herbicide-resistant weeds in the world has increased in recent years. Controlling these weeds becomes more difficult and raises production costs. Precision spraying technologies have been developed to overcome this challenge. However, these systems still have relatively high acquisition cost, requiring studies of the relation between the spatial distribution of weeds and the economically optimum spatial resolution of the control method. In this context, the objective... R.G. Trevisan, M.T. Eitelwein, M.N. Ferraz, T.R. Tavares, J.P. Molin, D.C. Neves

29. Use of UAV Acquired Imagery As a Precision Agriculture Method for Measuring Crop Residue in Southwestern Ontario, Canada

Residue management on agriculture land is a practice of great importance in southwestern Ontario, where soil management practices have an important effect on Great Lakes water quality. The ability of tillage or planting system to maintain soil residue cover is currently measured by using one or more of the common methods, line transect (e.g. knotted rope, Meter stick) and photographic (grid, script, and image analysis) methods. Each of these techniques has various advantages and disadvantages;... A. Laamrani, A. Berg, M. March, A. Mclaren, R. Martin

30. Feasibility of Estimating the Leaf Area Index of Maize Traits with Hemispherical Images Captured from Unmanned Aerial Vehicles

Feeding a global population of 9.1 billion in 2050 will require food production to be increased by approximately 60%. In this context, plant breeders are demanding more effective and efficient field-based phenotyping methods to accelerate the development of more productive cultivars under contrasting environmental constraints. The leaf area index (LAI) is a dimensionless biophysical parameter of great interest to maize breeders since it is directly related to crop productivity. The LAI is defined... M. Perez-ruiz, E. Apolo-apolo, G. Egea, J. Martinez-guanter, C. Marin-barrero

31. Field Phenotyping and an Example of Proximal Sensing of Photosynthesis

Field phenotyping conceptually can be divided in five pillars 1) traits of interest 2) sensors to measure these traits 3) positioning systems to allow high throughput measurements by the sensors 4) experimental sites and 5) environmental monitoring. In this paper we will focus on photosynthesis as trait of interest, measured by remote active fluorescence. The sensor presented is the Light Induced Fluorescence Transient (LIFT) instrument. The LIFT instrument is integrated in three positioning systems.... O. Muller, B. Keller, L. Zimmermanm, C. Jedmowski, V. Pingle, K. Acebron, N. Zendonadi, A. Steier, R. Pieruschka, U. Schurr, U. Rascher, T. Kraska

32. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and Indiana

Precision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minnesota.... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor

33. Measuring Soil Carbon with Intensive Soil Sampling and Proximal Profile Sensing

Soils have a large carbon storage capacity and sequestering additional carbon in agricultural fields can reduce CO2 levels in the atmosphere, helping to mitigate climate change. Efforts are underway to incentivize agricultural producers to increase soil organic carbon (SOC) stocks in their fields using various conservation practices.  These practices and the increased SOC provide important additional benefits including improved soil health, water quality and – in some cases –... E. Lund, T. Lund, C. Maxton

34. Yield Analysis in Sugarcane Harvesters Using Design of Experiments (DoE) Methodology

The sugarcane crop is highlighted in national agribusiness, Brazil is the world’s largest producer of the plant, and the prospection of specialists is of strong growth for the next years. However, in order to increase productivity, technological interventions through of precision agriculture must be implemented. Among them, the management of inputs guided by yield spatial variability for otmizing production and income. This project approaches the implementation of the methodology of analysis... M.L. Da silva, J. . Alves de lima, A. Balbinot, J.P. Molin

35. Are Pulses Really More Variable Than Cereals? a Country-wide Analysis of Within-field Variability

In Australia, pulses are underutilised by growers relative to cereal crops. There is significant global interest in growing pulses to provide more plant protein, and they also provide a string of agronomic and environmental benefits, such as their ability to fix nitrogen, and provide a pest and disease break for cereal crops. Many studies attribute this underutilisation to pulses exhibiting greater within-field yield variability than cereals. However, this has never been comprehensively examined... P. Filippi, T. Bishop, D. Al-shammari, T. Mcpherson

36. Assessing Crop Yield and Profitability with Site-specific Seed Rate Management in Corn and Soybean Cropping Systems

Integrating the information about soil and topographic properties for variable rate seeding is a prerequisite for improved crop production and thus profit. However, limited studies have explored the geospatial and machine learning approaches to understand factors influencing crop yield and profit under site-specific seed rate management. The objectives of this study were to: a) observe the effect of variable seeding rate based on soil and topographic properties on soybean and corn grain yield,... J. Neupane, N. Joshi, J.P. Fulton, S. Khanal, A. B k, B. Bhattarai

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

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

38. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and Vision

Advancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor.  While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi

39. Sugarcane Yield Mapping Using an On-board Volumetric Sensor

Few alternatives are available to the sugarcane sector for monitoring crop productivity. However, in recent years, research has been dedicated to developing methods ranging from estimation based on engine parameters to using sensors and artificial intelligence. This study aims to present a new tool for monitoring productivity applied to sugarcane cultivation, which utilizes a volumetric optical sensor, in contrast to other methods already used for this measurement, and is recently being introduced... G. Balboa, J.C. Masnello, F. De oliveira moreira, R. Canal filho, E.R. Da silva, J.P. Molin