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Lopez-Granados, F
Dhoubhadel, S
Roach, J
Luns Hatum de Almeida , S
Xu, X
Xu, K
Rahman, M.M
Lebeau, F
Dong, T
Deng, L
Bodson, B
Bromfield, C
Brown, P
Barnes, W
Ferguson, R.B
Raju, N
Boyer, W
Delalieux, S
Barroso, L
Belsky, C
Lepoivre, B
Bussher, W.J
Rodrigues Júnior, F.H
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Authors
Vancutsem, F
Leemans, V
Ferrandis Vallterra, S
Bodson, B
Destain, J
Destain, M
Dumont, B
Garcia, A.H
Rodrigues Júnior, F.H
Bastos, A.H
Magalhaes, P.S
Silva, M.J
Shiratsuchi, L
Lutz, C.C
Ferguson, R.B
Adamchuk, V.I
Adamchuk, V.I
Pan, L
Ferguson, R.B
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
Garcia-Torres, L
Gomez-Candon, D
Caballero-Novella, J.J
Gomez-Casero, M
Pe, J.M
Jurado-Exp, M
Lopez-Granados, F
Castillejo-Gonz, I
Garc, A
Adamchuk, V.I
Ferguson, R.B
Dumont, B
Vancutsem, F
Destain, J
Bodson, B
Lebeau, F
Destain, M
Shiratsuchi, L
Ferguson, R.B
Shanahan, J.F
Adamchuk, V.I
Slater, G
Garcia-Torres, L
Gomez-Candon, D
Caballero-Novella, J.J
Pe, J.M
Jurado-Exp, M
Castillejo-Gonz, I
Garc, A
Lopez-Granados, F
Prassack, L
Amakor, X
Jacobson, A.R
Cardon, G.E
Hawks, A
Barnes, W
YI, S
Deng, L
Rojo, F
Roach, J
Coates, R
Upadhyaya, S
Delwiche, M
Han, C
Dhillon, R
Dong, T
Shang, J
Meng, J
Liu, J
Peña, J.M
Torres-Sanchez, J
de Castro, A.I
Dorado, J
Lopez-Granados, F
Basso, B
Destain, J
Bodson, B
Destain, M
Dumont, B
Lai, C
Belsky, C
Stevens, L.J
Ferguson, R.B
Franzen, D.W
Kitchen, N.R
Dhillon, R
Upadhyaya, S
Roach, J
Crawford, K
Lampinen, B
Metcalf, S
Rojo, F
Jacquin, A
Sigel, G
Hagolle, O
Lepoivre, B
Roumiguié, A
Poilvé, H
Xu, X
Zhang, X
Li, Y
Xu, K
Sun, X
Giriyappa, M
Sheshadri, T
Hanumanthappa, D
Shankar, M
Salimath, S.B
Rudramuni, T
Raju, N
Devakumar, N
Mallikaarjuna, G
Malagi, M.T
Jangandi, S
Destain, M
Leemans, V
Marlier, G
Goffart, J
Bodson, B
Mercatoris, B
Gritten, F
Bean, G
Kitchen, N.R
Franzen, D.W
Miles, R.J
Ransom, C
Scharf, P
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Ransom, C.J
Bean, M
Kitchen, N
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Delauré, B
Baeck, P
Blommaert, J
Delalieux, S
Livens, S
Sima, A
Boonen, M
Goffart, J
Jacquemin, G
Nuyttens, D
Bastos, L
Ferguson, R.B
Luck, J
Parrish, J
Thompson, L
Krienke, B
Glewen, K
Ferguson, R.B
Bauer, P.J
Stone, K.C
Bussher, W.J
Millen, J.A
Evans, D.E
Strickland, E.E
Dallago, G.M
Figueiredo, D
Santos, R
Santos, D
Barroso, L
Alves, G
Vieira, J
Guimarães, L
Santos , C
Maciel, L
Bastos, L
Ferguson, R.B
Dhoubhadel, S
Griffin, T.W
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
TORGBOR, B.A
Rahman, M.M
Robson, A
Brinkhoff, J
Chakraborty, M
Pourreza, A
Brown, P
Zhou, J
Xu, Z
Safranski, T.J
Bromfield, C
Boyer, W
Oliveira, M.F
Ortiz, B.V
Hanyabui, E
Costa Souza, J.B
Sanz-Saez, A
Luns Hatum de Almeida , S
Pilcon, C
Vellidis, G
Boyer, W
Topics
Modeling and Geo-statistics
Sensor Application in Managing In-season Crop Variability
Proximal Sensing in Precision Agriculture
Precision A to Z for Practitioners
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Education and Training in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Precision Horticulture
Proximal Sensing in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Precision Nutrient Management
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Sensor Application in Managing In-season CropVariability
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Sensor Application in Managing In-season Crop Variability
Unmanned Aerial Systems
Precision Dairy and Livestock Management
In-Season Nitrogen Management
Profitability and Success Stories in Precision Agriculture
ISPA Community: Nitrogen
Precision Horticulture
In-Season Nitrogen Management
Precision Dairy and Livestock Management
Digital Agriculture Solutions for Soil Health and Water Quality
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Demonstration
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results40 paper(s) found.

1. Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea Crop

  The software SARI® has been developed to implement precision agriculture strategies through remote sensing imagery. It is written in IDL® and works as an add-on of ENVI®. It has been designed to divide remotely sensed imagery into “micro-images”, each corresponding to a small area (“micro-plot”), and to determine the quantitative agronomic and/or environmental biotic (i.e. weeds, pathogens) and/or non-biotic (i.e. nutrient levels) indicator/s... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, M. Gomez-casero, J.M. Pe, M. Jurado-exp, F. Lopez-granados, I. Castillejo-gonz, A. Garc

2. Precision Agriculture Education Program In Nebraska

With the cost of agricultural inputs and the instability of commodity prices increasing, demand is growing for training in the essential skills needed to successfully implement site-specific crop management. This set of skills is uniquely interdisciplinary in nature. Thus, it is essential for potential users of precision agriculture to understand the basics of geodetic and electronic control equipment, principles of geographic information systems, fundamentals... V.I. Adamchuk, R.B. Ferguson

3. A Model For Wheat Yield Prediction Based On Real-time Monitoring Of Environmental Factors

... B. Dumont, F. Vancutsem, J. Destain, B. Bodson, F. Lebeau, M. Destain

4. Comparison Of Spectral Indices Derived From Active Crop Canopy Sensors For Assessing Nitrogen And Water Status

... L. Shiratsuchi, R.B. Ferguson, J.F. Shanahan, V.I. Adamchuk, G. Slater

5. Management Of Remote Imagery For Precision Agriculture

Satellite and airborne remotely sensed images cover large areas, which normally include dozens of agricultural plots. Agricultural operations such as sowing, fertilization, and pesticide applications are designed for the whole plot area, i.e. 5 to 20 ha, or through precision agriculture. This takes into account the spatial variability of biotic and of abiotic factors and uses diverse technologies to apply inputs at variable rates, fitted to the needs of each small defined area, i.e. 25 to 200... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, J.M. Pe, M. Jurado-exp, I. Castillejo-gonz, A. Garc, F. Lopez-granados, L. Prassack

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. Research On Nutrition Detection Technology Of Soil And Leaf Of Citrus Based On Spectroscopic Techniques

The diagnosis technique of real-time lossless crop nutrition is the foundation and conditions for the precise and effective fertilization. Currently, the diagnosis of crop nutrition mainly relies on the routine chemical analysis of laboratory. Due to the complicated procedure, time-consuming, high cost and high professional technique requirement, it can hardly meet the need of precise variable fertilization technology. Spectrum technology is the technology of real-time and non-destructive testing,... S. Yi, L. Deng

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

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

9. Assembly of an Ultrasound Sensors System for Mapping of Sugar Cane Height

In Precision Agriculture, the use of sensors provides faster data collection on plant, soil, and climate, allowing collecting larger sample sets with better information quality. The objective of this study was the development of a system for plant height measurement in order to mapping of sugar cane crop, so that regions with plant growth variation and grow failures could be identified... A.H. Garcia, F.H. Rodrigues júnior, A.H. Bastos, P.S. Magalhaes, M.J. Silva

10. Integrated Crop Canopy Sensing System for Spatial Analysis of In-Season Crop Performance

Over the past decade, the relationships between leaf color, chlorophyll content, nitrogen supply, biomass and grain yield of agronomic crops have been studied widely.... L. Shiratsuchi, C.C. Lutz, R.B. Ferguson, V.I. Adamchuk

11. An Approach to Selection of Soil Water Content Monitoring Locations within Fields

Increased input efficiency is one of the main challenges for a modern agricultural enterprise. One way to optimize production cycles is to rationalize crop residue utilization. In conditions where there is limited use of mineral fertilizers and without applying manure, plant residues may be used as an organic fertilizer as... V.I. Adamchuk, L. Pan, R.B. Ferguson

12. 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

13. Development And Evaluation Of A Leaf Monitoring System For Continuous Measurement Of Plant Water Status In Almond And Walnut Crops

Abstract: Leaf temperature measurements using handheld infrared thermometers have been used to predict plant water stress by calculating crop water stress index (CWSI). However, for CWSI calculations it is recommended to measure canopy temperature of trees under saturated, stressed and current conditions simultaneously, which is not very practical while using handheld units. An inexpensive, easy to use sensing system was developed to predict plant water status for tree crops by measuring... F. Rojo, J. Roach, R. Coates, S. Upadhyaya, M. Delwiche, C. Han, R. Dhillon

14. An Evaluation Of HJ-CCD Broadband Vegtation Indices For Leaf Chlorophyll Content Estimation

Leaf chlorophyll content is one of the most important biochemical variables for crop physiological status assessment, crop biomass estimation and crop yield prediction in precision agriculture. Vegetation indices were considered effective for chlorophyll content estimation. Although hyperspectral reflectance is proven to be better than multispectral reflectance for leaf chlorophyll content retrieval, the scarcity of available data from satellite hyperspectral... T. Dong, J. Shang, J. Meng, J. Liu

15. The TOAS Project: UAV Technology For Optimizing Herbicide Applications In Weed-Crop Systems

Site-specific weed management refers to the application of customised control treatments, mainly herbicide, only where weeds are located within the crop-field. In this context, the TOAS project is being developed under the financial support of the European Commission with the main objective of generating georeferenced weed infestation maps of certain herbaceous (corn and sunflower) and permanent woody crops (poplar and olive orchards) by using aerial images collected by an unmanned aerial... J.M. Peña, J. Torres-sanchez, A.I. De castro, J. Dorado, F. Lopez-granados

16. Nitrogen Fertilisation Recommendations : Could They Be Improved Using Stochastically Generated Climates In Conjunction With Crop Models ?

In the context of precision nitrogen (N) management, to ensure that the yield potential could be reached each year, farmers have too often applied quantities of fertilizers much larger than what was strictly required. However, since 2002, the Belgian Government transposed the European Nitrate Directive 91/676/EEC in the Belgian law, with the aim to maintain the productivity and the revenue of Belgian's farmers while reducing the environmental impact of excessive N management... B. Basso, J. Destain, B. Bodson, M. Destain, B. Dumont

17. Building Proactive Predictive Models With Big Data Technology For Precision Agriculture

In a world with ever increasing shortages of food production due to increasing populations and depletion of resources, the need for new technologies and techniques for sustainable and efficient agriculture with long term financial, environmental and cultural benefits are critical.  An area of scientific study concerning crop-production management called Precision Agriculture (PA) is a concept based on integrating modern information technologies such as Big Data Analytics, GPS... C. Lai, C. Belsky

18. In-Season Nitrogen Requirement For Maize Using Model And Sensor-Based Recommendation Approaches

Nitrogen (N), an essential element, is often limiting to plant growth.  There is great value in determining the optimum quantity and timing of N application to meet crop needs while minimizing losses.  Low nitrogen use efficiency (NUE) has been attributed to several factors including poor synchrony between N fertilizer and crop demand, unaccounted for spatial variability resulting in varying crop N needs, and temporal variances in crop N needs.  Applying a portion... L.J. Stevens, R.B. Ferguson, D.W. Franzen, N.R. Kitchen

19. Modeling Canopy Light Interception For Estimating Yield In Almond And Walnut Trees

A knowledge of spatio-temporal variability in potential yield is essential for site-specific nutrient management in crop production. The objectives of this project were to develop a model for photosynthetically active radiation (PAR) intercepted by almond and walnut trees based on data obtained from respective tree(s) and estimate potential crop yield in individual trees or in blocks of five trees. This project uses proximally sensed PAR interception data measured using a lightbar... R. Dhillon, S. Upadhyaya, J. Roach, K. Crawford, B. lampinen, S. Metcalf, F. Rojo

20. Development Of An Index-Based Insurance Product: Validation Of A Forage Production Index Derived From Medium Spatial Resolution fCover Time Series

An index-based insurance solution is developed by Pacifica Crédit Agricole Assurances and Astrium GEO-Information to estimate and monitor the near real-time forage production in France. In this system, payouts are indexed on an indicator, called Forage Production Index (FPI), calculated using a biophysical characterization of the grassland from medium spatial resolution remote sensing time series. We used the Fraction of green Vegetation Cover (fCover) integral as... A. Jacquin, G. Sigel, O. Hagolle, B. Lepoivre, A. Roumiguié, H. Poilvé

21. Monitoring Ratio Of Leaf Carbon To Nitrogen In Winter Wheat Based On Hyperspectral Measurements

The metabolic status of carbon (C) and nitrogen (N) as two essential elements of crop plants has significant influence on the ultimate formation of yield and quality in crop production. Leaf is the major organ of plant photosynthesis and physiological activity, and in leaf tissues the ratio of carbon to nitrogen (C/N), defined as the ratio of LCC (leaf carbon concentration) to LNC (leaf nitrogen concentration), can... X. Xu

22. Research On Measurement Device For NO3- Ion Concentration Of Nutrient Solution

The management of water and ion concentration in nutrient solution is crucial in precision agriculture. Poor management may leads to the increasing of energy consumption and cost as well as low efficiency. The measurement of ion concentration in nutrient solution is prerequisite for optimal control and management of nutrient solution. Real-time detection of NO3-, as an important component of nitrogenous fertilizer, is always a big problem over the world. The... X. Zhang, Y. Li, K. Xu, X. Sun

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

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

24. 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

25. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather Information

Corn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

26. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor Algorithm

Nitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

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

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

28. Active and Passive Crop Canopy Sensors As Tools for Nitrogen Management in Corn

The objectives of this research were to (i) assess the correlation between active and passive crop canopy sensors’ vegetation indices at different corn growth stages and (ii) assess sidedress variable rate nitrogen (N) recommendation accuracy of active and passive sensors compared to the agronomic optimum N rate (AONR). The experiment was conducted near Central City, Nebraska on a Novina sandy loam planted to corn on 15 April 2015. The experiment was a randomized complete-block design with... L. Bastos, R. Ferguson

29. Liquid Flow Control Requirements for Crop Canopy Sensor-Based N Management in Corn: A Project SENSE Case Study

While on-farm adoption of crop canopy sensors for directing in-season nitrogen (N) application has been slow, research focused on these systems has been significant for decades. Much emphasis has been placed on developing and testing algorithms based on sensor output to predict N needs, but little information has been published regarding liquid flow control requirements on equipment used in conjunction with these sensing systems. Addition of a sensor-based system to a standard spray rate controller... J. Luck, J. Parrish, L. Thompson, B. Krienke, K. Glewen, R.B. Ferguson

30. Site-specific Irrigation of Peanuts on a Coastal Plain Field

Irrigator-Pro is an expert system that prescribes irrigation for corn (Zea mays L.), cotton (Gossypium hirsutum L.) and peanut (Arachis hypogaea). We conducted an experiment in 2007 to evaluate Irrigator-Pro as a tool for variable rate irrigation of peanut using a site-specific center pivot irrigation system. Treatments were irrigation of whole plots based on the expert system, irrigation of individual soils within plots based on the expert system, irrigation of individual...

31. The Influence of Calf’s Sex on Total Milk Yield and Its Constituents of Dairy Cows

The objective of the present work was to evaluate the influence of the sex of the calf on total milk yield and its constituents of Holstein-Friesian dairy cows. The Holstein Livestock Breeders Association of Minas Gerais provided data collected over the years from 2000 to 2016 from 127 dairy farms located in the state of Minas Gerais – Brazil. The data set analyzed contained 61747 observations of Holstein-Friesian animals that calved female (n = 28903) or male (n = 32844) calf. Fat, protein,... G.M. Dallago, D. Figueiredo, R. Santos, D. Santos, L. Barroso, G. Alves, J. Vieira, L. Guimarães, C. Santos , L. Maciel

32. Active and Passive Sensor Comparison for Variable Rate Nitrogen Determination and Accuracy in Irrigated Corn

The objectives of this research were to (i) compare active and passive crop canopy sensors’ sidedress variable rate nitrogen (VRN) derived from different vegetation indices (VI) and (ii) assess VRN recommendation accuracy of active and passive sensors as compared to the agronomic optimum N rate (AONR) in irrigated corn. This study is comprised of six site-years (SY), conducted in 2015, 2016 and 2017 on different soil types (silt loam, loam and sandy loam) and with a range of preplant-applied... L. Bastos, R.B. Ferguson

33. The Impact of Precision Agriculture Technologies on Farm Profitability in Kansas

Even with more than a decade long adoption of the precision agriculture (PA) technologies in the United States, its impact on farm profitability is still not clear. This paper uses farm level data from Kansas Farm Management Association (KFMA) to conduct the ex-post evaluation of PA technologies on farm profitability in Kansas. The analysis of the data using propensity score matching method indicates that there is on an average $60,000 difference in net returns of the farm with at least one PA... S. Dhoubhadel, T.W. Griffin

34. 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

35. Assessing the Potential of Sentinel-1 in Retrieving Mango Phenology and Investigating Its Relation to Weather in Southern Ghana

The rise in global production of horticultural tree crops over the past few decades is driving technology-based innovation and research to promote productivity and efficiency. Although mango production is on the rise, application of the remote sensing technology is generally limited and the available study on retrieving mango phenology stages specifically, was focused on the application of optical data. We therefore sought to answer the questions; (1) can key phenology stages of mango be retrieved... B.A. Torgbor, M.M. Rahman, A. Robson, J. Brinkhoff

36. Retrieving Nitrogen Levels in Almond Trees Using Hyperspectral Data at Leaf and Canopy Level

Almonds are a crucial specialty crop in California, dominating approximately 80 percent of the global almond supply. To enhance nitrogen usage efficiency, reduce groundwater contamination, and optimize resource allocation, ongoing research has been dedicated to improving nitrogen management practices in almond cultivation. This study specifically focused on the retrieval of nitrogen levels with uncertainty estimation at both the leaf and canopy levels of almond trees. Hyperspectral data was collected... M. Chakraborty, A. Pourreza

37. Automated Sow Estrus Detection Using Machine Vision Technology

Successful artificial insemination for gilts and sows relies on accurate timing that is determined by estrus check. Estrus checks in current farms are manually conducted by skilled breeding technicians using the back pressure test (BPT) method that is labor-intensive and inefficient due to the large animal-to-staff ratio. This study aimed to develop a robotic imaging system powered by artificial intelligence technology to automatically detect estrus status for gilts and sows in a stall-housing... J. Zhou, Z. Xu, T.J. Safranski, C. Bromfield

38. Extension Program Prioritization Guides Web-mapping Application Delivery to Ranchers

Cooperative Extension has a long history of helping agricultural producers address their current needs and emerging public issues; often through training in the use of technologies that are not yet widely adopted. The quality of geospatial data and tools to visualize and analyze that data continues to improve. However, barriers exist to rancher adoption of geospatial decision support tools. These barriers can include costs, ease of use, and privacy concerns. The sustainability of beef cattle... W. Boyer

39. Use of Crop and Drought Spectral Indices to Support Harvest Decisions of Peanut Fields in Alabama

Harvest efficiency expressed in quantity and quality of peanut fields could increase if farmers are provided with tools to support harvest decisions. Peanut farmers still rely on a visual and empiric method to assess the right time of peanut maturity but this method does not account for within-field variability of crop growth and maturity. The integration of spectral vegetation indices to assess drought, soil moisture, and crop growth to predict peanut maturity can help farmers strengthen decisions... M.F. Oliveira, B.V. Ortiz, E. Hanyabui, J.B. Costa souza, A. Sanz-saez, S. Luns hatum de almeida , C. Pilcon, G. Vellidis

40. Drone Use Extension and Demonstrations Support Management of Riparian Areas, Grazing Land, and Water Quality

Agricultural and natural resource managers have explored a variety of ways in which drones might be used to aid in decision-making. One of the most useful ways may be the production of orthorectified aerial photography which can have very high spatial and temporal resolution. Such photography offers new opportunities for visualizing and measuring features on the landscape. Not just measuring the two-dimensional characteristics of landscape features, but also measuring three-dimensional characteristics.... W. Boyer