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Chen, X
Balmos, A
Luns Hatum de Almeida , S
Peets, S
Gerken, A.R
Kulhandjian, M
Andrade, J
Abu Seman, I
Kieffer, D
Huggins, D.R
Karam, A
Pastore, C
Wang, X
Kitchen, N
Garc, A
Wetterich, C
Krishna, D
Fang, H
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Authors
Krishna, D
Wetterich, C
Belasque Jr., J
Marcassa, L
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
Kieffer, D
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
Kemanian, A.R
Huggins, D.R
Uberuaga, D.P
Huggins, D.R
Huggins, D.R
Ma, W
Wang, X
Deng, W
Wang, X
Zhao, C
Huang, Y
Baffaut, C
Sudduth, K
Sadler, J
Kremer, R
Lerch, R
Kitchen, N
Veum, K
Thompson, A
Boardman, D.L
Kitchen, N
Allphin, E
Veum, K
Sudduth, K
Kitchen, N
Yost, M.A
Kitchen, N
Sudduth, K
Drummond, S
Sadler, J
Conway, L
Yost, M
Kitchen, N
Sudduth, K
Myers, B
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
Bobryk, C.W
Yost, M
Kitchen, N
Scharf, P
Shannon, K
Sudduth, K
Kitchen, N
Meng, J
Fang, H
Cheng, Z
Dallago, G.M
Figueiredo, D
Santos, R
Santos, D
Guimarães, L
Santos, C
Castro, T
Santos, A
Otoni, L
Andrade, J
Bejo, S
Abdol Lajis, G
Abd Aziz, S
Abu Seman, I
Ahamed, T
Wang, Y
Balmos, A
Krogmeier, J
Buckmaster, D
Krogmeier, J
Buckmaster, D
Ault, A
Wang, Y
Zhang, Y
Layton, A
Noel, S
Balmos, A
Allegro, G
Martelli, R
Valentini, G
Pastore, C
Mazzoleni, R
Pezzi, F
Filippetti, I
Ali, A
Nze Memiaghe, J
Cambouris, A.N
Ziadi, N
Duchemin, M
Karam, A
Chen, X
Miao, Y
Yu, K
chang, Q
li, F
Kulhandjian, H
Kulhandjian, M
Rocha, D
Bennett, B
Kulhandjian, H
Kulhandjian, M
Rocha, D
Bennett , B
Kulhandjian, H
Amely, N
Kulhandjian, M
Javed, B
Cambouris, A
Duchemin, M
Longchamps, L
Basran, P.S
Arnold, S
Fenech, A
Karam, A
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
Nze Memiaghe, J
Cambouris, A
Duchemin, M
Ziadi, N
Karam, A
Castiblanco Rubio, F.A
Arun, A
Lee, B
Balmos, A
Jha, S
Krogmeier, J
Love, D.J
Buckmaster, D
Castiblanco Rubio, F.A
Basir, M
Balmos, A
Krogmeier, J
Buckmaster, D
Oliveira, M.F
Ortiz, B.V
Hanyabui, E
Costa Souza, J.B
Sanz-Saez, A
Luns Hatum de Almeida , S
Pilcon, C
Vellidis, G
Jha, S
Krogmeier, J
Buckmaster, D
Love, D.J
Grant, R.H
Crawford, M
Brinton, C
Wang, C
Cappelleri, D
Balmos, A
Zhang, Y
Bailey, J
Balmos, A
Castiblanco Rubio, F.A
Krogmeier, J
Buckmaster, D
Love, D
Zhang, J
Allen, M
Armstrong, P.R
Pordesimo, L.O
Siliveru, K
Gerken, A.R
Serfa Juan, R.O
Topics
Precision Nutrient Management
Precision Horticulture
Remote Sensing Applications in Precision Agriculture
Precision A-Z for Practitioners
Precision Carbon Management
Precision Conservation
Precision Crop Protection
Precision Conservation Management
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Precision Conservation Management
Spatial Variability in Crop, Soil and Natural Resources
Sensor Application in Managing In-season Crop Variability
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Dairy and Livestock Management
Precision Crop Protection
Big Data, Data Mining and Deep Learning
Profitability and Success Stories in Precision Agriculture
Precision Horticulture
Decision Support Systems
In-Season Nitrogen Management
Robotics and Automation with Row and Horticultural Crops
Artificial Intelligence (AI) in Agriculture
Precision Agriculture and Global Food Security
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Land Improvement and Conservation Practices
Wireless Sensor Networks and Farm Connectivity
Edge Computing and Cloud Solutions
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Filter results38 paper(s) found.

1. Fluorescence Imaging Spectroscopy Applied To Citrus Diseases

Diseases are one of the most serious threats for citrus production worldwide. Sao Paulo, Brazil and Florida, USA, are the most important citrus producers and, both, are making efforts for citrus diseases control. Citrus canker is one of the serious diseases, caused by the Xanthomonas citri subsp. citri bacteria, that infects citrus trees and relatives, causing a large economic loss in the citrus juice production. Another important disease affecting the citrus production worldwide is the Huanglongbing... C. Wetterich, J. Belasque jr., L. Marcassa

2. 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

3. Effect Of Sub-surface Drip Irrigation And Shade On Soil Moisture Uniformity In Residential Turf

Sub-surface irrigation in turf has advantages over traditional sprinkler systems. Evapotranspiration is reduced and water applied below the root zone promotes deeper root growth. Auditing such applications requires measurement of root-zone soil moisture. Data was taken in 2008 and 2009 on a private lawn in northern California that had just been rebuilt to include both sub-surface drip and overhead spray irrigation systems. A portable wave reflectometer was used to take geo-referenced soil moisture... D. Kieffer

4. 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

5. Modeling Soil Carbon Spatial Variation: Case Study In The Palouse Region

Soil organic carbon (Cs) levels in the soil profile reflect the transient state or equilibrium conditions determined by organic carbon inputs and outputs. In areas with strong topography, erosion, transport and deposition control de soil carbon balance and determine strong within-field differences in soil carbon. Carbon gains or losses are therefore difficult to predict for the average field. Total Cs ranged from 54 to 272 Mg C ha-1, with 42% (range 25 to 78%) of Cs in the top 0.3-m of the soil... A.R. Kemanian, D.R. Huggins, D.P. Uberuaga

6. Investigating Profile And Landscape Scale Variability In Soil Organic Carbon: Implications For Process-oriented Precision Management

Mitigation of rising greenhouse gases concentrations in the atmosphere has focused attention on agricultural soil organic C (SOC) sequestration. However, field scale knowledge of the processes and factors regulating SOC dynamics, distribution and variability is lacking. The objectives of this study are to characterize the profile... D.R. Huggins,

7. Precision Conservation: Site-specific Trade-offs Of Harvesting Wheat Residues For Biofuel Feedstocks

Crop residues are considered to be an important lignocellulosic feedstock for future biofuel production. Harvesting crop residues, however, could lead to serious soil degradation and loss of productivity. Our objective was to evaluate trade-offs associated with harvesting residues including impacts on soil quality, soil organic C and nutrient removal. We used cropping systems data collected at 369 geo-referenced points on the 37-ha Washington State... D.R. Huggins,

8. The Effect of Scheduling Irrigation on Yield, Concentration and Uptake of Nutrient in Zero Tilled Wheat (Triticum Aestivum L.)

Abstract: The rice–wheat rotation... D. Krishna

9. Development Of Variable Rate System For Soil Disinfection Based On Injection Technique

Abstract:  A variable rate system injection of soil pesticide was developed for control of soil pesticide amount by PWM. The paper analyzes the input and output conditions of control system, and designed hardware, algorithm and control of soil pesticide, mainly software flow and a feedback control way. In the paper, the variable-rate control system consisted of time delay, interface module, micro controller, speed sensor, PWM valve, and hydraulic... W. Ma, X. Wang

10. Weed Identification From Seedling Cabbages Using Visible And Near-Infrared Spectrum Analysis

Target identification is one of the main research content and also a key point in precision crop protection. The main purpose of the study is to choose the characteristic wavelengths (CW for short) to classify the cabbages and the weeds at their seedling stage using different data analysis methods. Using a handheld full-spectrum FieldSpec-FR, the canopies of the seedling plants, cabbage ‘8398, cabbage ‘zhonggan’, Barnyard grass, green foxtail, goosegrass,... W. Deng, X. Wang, C. Zhao, Y. Huang

11. Production And Conservation Results From A Decade-Long Field-Scale Precision Agriculture System

Research is needed that simultaneously evaluates production and conservation outcomes of precision agriculture practices.  From over a decade (1993-2003) of yield and soil mapping and water quality assessment, a multi-faceted, “precision agriculture system” (PAS) was developed and initiated in 2004 on a 36-ha field in Central Missouri. The PAS assessment was accomplished by comparing it to the previous decade of conventional corn-soybean... C. Baffaut, K. Sudduth, J. Sadler, R. Kremer, R. Lerch, N. Kitchen, K. Veum

12. 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

13. Sensor Based Soil Health Assessment

Quantification and assessment of soil health involves determining how well a soil is performing its biological, chemical, and physical functions relative to its inherent potential. Due to high cost, labor requirements, and soil disturbance, traditional laboratory analyses cannot provide high resolution soil health data. Therefore, sensor-based approaches are important to facilitate cost-effective, site-specific management for soil health. In the Central Claypan Region, visible, near-infrared (VNIR)... K. Veum, K. Sudduth, N. Kitchen

14. A Decade of Precision Agriculture Impacts on Grain Yield and Yield Variation

Targeting management practices and inputs with precision agriculture has high potential to meet some of the grand challenges of sustainability in the coming century, including simultaneously improving crop yields and reducing environmental impacts. Although the potential is high, few studies have documented long-term effects of precision agriculture on crop production and environmental quality. More specifically, long-term impacts of precision conservation practices such as cover crops, no-tillage,... M.A. Yost, N. Kitchen, K. Sudduth, S. Drummond, J. Sadler

15. Claypan Depth Effect on Soil Phosphorus and Potassium Dynamics

Understanding the effects of fertilizer addition and crop removal on long-term change in spatially-variable soil test P (STP) and soil test K (STK) is crucial for maximizing the use of grower inputs on claypan soils. Using apparent electrical conductivity (ECa) to estimate topsoil depth (or depth to claypan, DTC) within fields could help capture the variability and guide site-specific applications of P and K. The objective of this study was to determine if DTC derived from ECa... L. Conway, M. Yost, N. Kitchen, K. Sudduth, B. Myers

16. 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

17. Field Potential Soil Variability Index to Identify Precision Agriculture Opportunity

Precision agriculture (PA) technologies used for identifying and managing within-field variability are not widely used despite decades of advancement. Technological innovations in agronomic tools, such as canopy reflectance or electrical conductivity sensors, have created opportunities to achieve a greater understanding of within-field variability. However, many are hesitant to adopt PA because uncertainty exists about field-specific performance or the potential return on investment. These concerns... C.W. Bobryk, M. Yost, N. Kitchen

18. Sensor-based Nitrogen Applications Out-performed Producer-chosen Rates for Corn in On-farm Demonstrations

Optimal nitrogen fertilizer rate for corn can vary substantially within and among fields.  Current N management practices do not address this variability.  Crop reflectance sensors offer the potential to diagnose crop N need and control N application rates at a fine spatial scale.  Our objective was to evaluate the performance of sensor-based variable-rate N applications to corn, relative to constant N rates chosen by the producer.  Fifty-five replicated on-farm demonstrations... P. Scharf, K. Shannon, K. Sudduth, N. Kitchen

19. Understanding Temporal and Spatial Variation of Soil Available Nutrients with Satellite Remote Sensing

Soil available nutrients are the key determinants in crop growth, field stable output and ecological balance. The soil nutrients loss and surplus can strongly influence the stability of field ecological environment and cause unnecessary pollution. Hence, optimizing the status of soil available nutrients status has significant ecological and economic significance. With the advancement of mechanized farming and control technologies, soil available nutrients can be optimize by variable rate fertilization.... J. Meng, H. Fang, Z. Cheng

20. Time Series Analysis of Somatic Cell Count from Dairy Herds in Minas Gerais - Brazil

The objective of this study was to analyze the temporal variation of somatic cell count (SCC) in milk of dairy cows from the state of Minas Gerais, Brazil. The Holstein Livestock Breeders Association of Minas Gerais provided data collected from 128 dairy farms located in the state of Minas Gerais between the years of 2000 and 2016. The database contains the SCC average of a total of 91,851 305-day lactations of Holstein animals. The annual SCC average was calculated as well as the percentage of... G.M. Dallago, D. Figueiredo, R. Santos, D. Santos, L. Guimarães, C. Santos, T. Castro, A. Santos, L. Otoni, J. Andrade

21. Detecting Basal Stem Rot (BSR) Disease at Oil Palm Tree Using Thermal Imaging Technique

Basal stem rot (BSR), caused by Ganoderma boninense is known as the most damaging disease in oil palm plantations in Southeast Asia. Ganoderma could reduce the productivity of oil palm plantations and potentially reduce the market value of palm oil in Malaysia. Early disease management of Ganoderma could prevent production losses and reduce the cost of plantation management. This study focuses on identifying the thermal properties of healthy and BSR-infected tree using a thermal imaging... S. Bejo, G. Abdol lajis, S. Abd aziz, I. Abu seman, T. Ahamed

22. Data-Driven Agricultural Machinery Activity Anomaly Detection and Classification

In modern agriculture, machinery has become the one of the necessities in providing safe, effective and economical farming operations and logistics. In a typical farming operation, different machines perform different tasks, and sometimes are used together for collaborative work. In such cases, different machines are associated with representative activity patterns, for example, in a harvest scenario, combines move through a field following regular swaths while grain carts follow irregular paths... Y. Wang, A. Balmos, J. Krogmeier, D. Buckmaster

23. Use Cases for Real Time Data in Agriculture

Agricultural data of many types (yield, weather, soil moisture, field operations, topography, etc.) comes in varied geospatial aggregation levels and time increments. For much of this data, consumption and utilization is not time sensitive. For other data elements, time is of the essence. We hypothesize that better quality data (for those later analyses) will also follow from real-time presentation and application of data for it is during the time that data is being collected that errors can be... J. Krogmeier, D. Buckmaster, A. Ault, Y. Wang, Y. Zhang, A. Layton, S. Noel, A. Balmos

24. Variable Rate Fertilization in a High-yielding Vineyard of Cv. Trebbiano Romagnolo May Reduce Nitrogen Application and Vigour Variability Without Loss of Crop Load

The site-specific management of vineyard cultural practices may reduce the spatial variability of vine vigor, contributing to achieve the desired yield and grape composition. In this framework, variable rate fertilization may effectively contribute to reduce the different availability of mineral nutrients between different areas of the vineyard, and so achieving the vine’s aforementioned performances. The present study was aimed to apply a variable rate fertilization in a high-yielding... G. Allegro, R. Martelli, G. Valentini, C. Pastore, R. Mazzoleni, F. Pezzi, I. Filippetti, A. Ali

25. Impacts of Interpolating Methods on Soil Agri-environmental Phosphorus Maps Under Corn Production

Phosphorus (P) is an essential nutrient for crops production including corn. However, the excessive P application, tends to P accumulation at the soil surface under crops systems. This may contribute to increase water and groundwater pollution by surface runoff. To prevent this, an agri-environmental P index, (P/Al)M3, was developed in Eastern Canada and USA. This index aims to estimate soil P saturation for accurate P fertilizer recommendations, while integrating agronomical aspects... J. Nze memiaghe, A.N. Cambouris, N. Ziadi, M. Duchemin, A. Karam

26. Improving Winter Wheat Nitrogen Status Monitoring Using Proximal Canopy Sensing and Agrometeorological Information with Machine Learning

Timely and accurate diagnosis of winter wheat nitrogen (N) status plays an important role in guiding precision N management. This study aims to combine proximal canopy sensing and agrometeorological information to establish a reliable winter wheat plant N concentration (PNC) monitoring model with seven machine learning (ML) algorithms (Random Forest Regression (RFR), Support Vector Regression (SVR), K-Nearest Neighbors Regression (KNNR), Partial Least Squares Regression (PLSR), Gradient Boosting... X. Chen, Y. Miao, K. Yu, Q. Chang, F. Li

27. AI-based Pollinator Using CoreXY Robot

The declining populations of natural pollinators pose a significant ecological challenge, often attributed to the adverse effects of pesticides and intensive farming practices. To address the critical issue of pollination in the face of diminishing natural pollinators, we are pioneering an AI-based pollinator that utilizes a CoreXY pollination system. This solution aims to augment pollination efforts in agriculture, increasing yields and crop quality while mitigating the adverse impacts of pesticide... H. Kulhandjian, M. Kulhandjian, D. Rocha, B. Bennett

28. AI-based Precision Weed Detection and Elimination

Weeds are a significant challenge in agriculture, competing with crops for resources and reducing yields. Addressing this issue requires efficient and sustainable weed elimination systems. This paper presents a comprehensive overview of recent advancements in weed elimination system development, focusing on innovative technologies and methodologies. Specifically, it details the development and integration of a weed detection and elimination system based on the CoreXY architecture, implemented... H. Kulhandjian, M. Kulhandjian, D. Rocha, B. Bennett

29. AI-based Fruit Harvesting Using a Robotic Arm

Fruit harvesting stands as a pivotal and delicate process within the agricultural industry, demanding precision and efficiency to ensure both crop quality and overall productivity. Historically reliant on manual labor, this labor-intensive endeavor has taken a significant leap forward with the advent of autonomous jointed robots and Artificial Intelligence (AI). Our project aims to usher in a new era in fruit harvesting, leveraging advanced technology to perform this essential task autonomously... H. Kulhandjian, N. Amely, M. Kulhandjian

30. In-season Nitrogen Prediction Evaluation Using Airborne Imagery with AI Techniques in Commercial Potato Production

In modern agriculture, timely and precise nitrogen (N) monitoring is essential to optimize resource management and improve trade benefits. Potato (Solanum tuberosum L.) is a staple food in many regions of the world, and improving its production is inevitable to ensure food security and promote related industries. Traditional methods of assessing nitrogen are labour-intensive, time-consuming, and require subjective observations. To address these limitations, a combination of multispectral... B. Javed, A. Cambouris, M. Duchemin, L. Longchamps, P.S. Basran, S. Arnold, A. Fenech, A. Karam

31. 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

32. Delineating Management Zones for Optimizing Soil Phosphorus Recommendations Under a No Till Field in Eastern Canada

Corn (Zea mays L.) and soybean (Glycine max L.) represent the most common crop rotation in Eastern Canada. These crops are cultivated using no-tillage (NT) practice to enhance agroecosystem sustainability. However, NT practice can cause several agri-environmental issues related to phosphorus (P) stratification, movement and runoff leading to P eutrophication in waters. Another major challenge is the expensive costs of extensive soil sampling and laboratory tests needed for accurate... J. Nze memiaghe, A. Cambouris, M. Duchemin, N. Ziadi, A. Karam

33. OATSmobile: a Data Hub for Underground Sensor Communications and Rural IoT

Wireless Underground Sensor Networks (WUSNs) play a crucial role in precision agriculture by providing information about moisture levels, temperature, nutrient availability, and other relevant factors. However, the use of radio-frequency identification (RFID) devices for WUSNs has been relatively unexplored despite their benefits such as low power consumption. In this work, we develop a hardware platform, called OATSMobile, that enables radio-frequency identification (RFID) communications in WUSNs.... F.A. Castiblanco rubio, A. Arun, B. Lee, A. Balmos, S. Jha, J. Krogmeier, D.J. Love, D. Buckmaster

34. Avena: an Event-driven Software Framework for Informed Decisions and Actions in Cropping Systems

Interoperability is one of the enabling factors of real-time communications and data exchange between asynchronous data actors. Interoperability can be attained by introducing events to systems that extract data from consumed ground-truth event streams that utilize application-specific structures. Events are specific occurrences happening at a particular time and place. Event-data are observations of phenomena, or actions, as seen by different systems in Internet of Things (IoT) deployments, independent... F.A. Castiblanco rubio, M. Basir, A. Balmos, J. Krogmeier, D. Buckmaster

35. 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

36. Design of an Autonomous Ag Platform Capable of Field Scale Data Collection in Support of Artificial Intelligence

The Pivot+ Array is intended to serve as an innovative, multi-user research platform dedicated to the autonomous monitoring, analysis, and manipulation of crops and inputs at the plant scale, covering extensive areas. It will effectively address many constraints that have historically limited large-scale agricultural sensor and robotic research. This achievement will be made possible by augmenting the well-established center pivot technology, known for its autonomy, with robust power infrastructure,... S. Jha, J. Krogmeier, D. Buckmaster, D.J. Love, R.H. Grant, M. Crawford, C. Brinton, C. Wang, D. Cappelleri, A. Balmos

37. Enabling Field-level Connectivity in Rural Digital Agriculture with Cloud-based LoRaWAN

The widespread adoption of next-generation digital agriculture technologies in rural areas faces a critical challenge in the form of inadequate field-level connectivity. Traditional approaches to connecting people fall short in providing cost-effective solutions for many remote agricultural locations, exacerbating the digital divide. Current cellular networks, including 5G with millimeter wave technology, are urban-centric and struggle to meet the evolving digital agricultural needs, presenting... Y. Zhang, J. Bailey, A. Balmos, F.A. Castiblanco rubio, J. Krogmeier, D. Buckmaster, D. Love, J. Zhang, M. Allen

38. Advanced Classification of Beetle Doppelgängers Using Siamese Neural Networks and Imaging Techniques

The precise identification of beetle species, especially those that have similar macrostructure and physical characteristics, is a challenging task in the field of entomology. The term "Beetle Doppelgängers" refers to species that exhibit almost indistinguishable macrostructural characteristics, which can complicate tasks in ecological studies, conservation efforts, and pest management. The core issue resides in their striking similarity, frequently confusing both experts and automated... P.R. Armstrong, L.O. Pordesimo, K. Siliveru, A.R. Gerken, R.O. Serfa juan