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eXtension: Precision Agriculture on the Internet
Modeling and Geo-statistics
Precision Nutrient Management
Robotics and Automation with Row and Horticultural Crops
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Authors
Adamchuk, V.I
Al-Gaadi, K.A
Alabi, T
Alahe, M
Amely, N
Ampatzidis, Y
B, K
Baghernejad, M
Banerjee, M
Barbosa, M
Basso, B
Basso, B
Batuman, O
Bazzi, C.L
Behera, S
Bennett, B
Bhuiya, G
Bodson, B
Brase, T
Braunbeck, O
Braunbeck, O.A
Burris, E
Cao, Q
Castro, S.G
Castro, S.G
Chang, Y
Chen, L
Chen, T
Christiaens, R
Cointault, F
Destain, J
Destain, M
Devakumar, N
Downing, B
Dumont, B
Dutta, S
Emadi, M.M
Feng, G
Fergugson, R.B
Franco, H.C
Franco, H.C
Gao, X
Gilson, A
Giriyappa, M
Graziano Magalhães, P.S
Green, O
Grocholski, P
Grove, J
Guan, H
Gummi, S
Hansen, J
Hanumanthappa, D
Harsha Chepally, R
Hays, A
Henties, T
Hoffmann, W.C
Huang, W
Hunsche, M
Ikpi, A.E
Inamasu, R
Jangandi, S
Johnson, R.M
Joseph, K
Journaux, L
Jørgensen, R.N
Karkee, M
Kaul, A
Kolln, O.T
Kolln, O.T
Krueger Shvetsova, E
Kulczycki, G
Kulhandjian, H
Kulhandjian, H
Kulhandjian, M
Kulhandjian, M
Kumar, R
Kunwar, S
Kurtener, D
Kurtener, D
Lambur, M
Lan, Y
Li, F
Li, Y
Liu, B
Liu, W
Liu, Y
Lu, Y
Madugundu, R
Magalhães, P.S
Maiti, D
Majumdar, K
Makarov, J
Makkar, M.S
Malagi, M.T
Malik, G
Mallikaarjuna, G
Marey, S
Mariano, E
Marin, A
Martin, D.L
Martin, R
McCarter, K.S
Mclure, B
Melnitchouck, A
Meyer, T
Miao, Y
Michalski, A
Miteran, J
Mulla, D.J
Muvva, V
Mwunguzi, H
Nakao, H.S
Noga, G
Nowatzki, J
Okoruwa, V.O
Oksanen, T
Olayide, O.E
Oliveira, L
Omodele, T
Otto, R
Pack, C
Pampolino, M
Pan, L
Pandey, A
Pannu, C.S
Patil, V
Pena-Yewtukhiw, E.M
Pgowda, C.C
Phillips, L
Phillips, S
Pitla, S
Pitla, S
Piya, N.K
Pl, L
R, C
Ragab, R
Raitz Persch, J
Raju, N
Rehman, T
Rocha, D
Rossi Neto, J
Rudramuni, T
Rumpf, T
Sales, L
Salimath, S.B
Sanches, G.M
Sanches, G.M
Santos, R
Sapkota, R
Schepers, J.S
Scholz, O
Schroeder, M.A
Sekhon, B.S
Shankar, M
Sharma, A
Sheshadri, T
Skovsen, S
Sleichter, R
Souza, E.G
Stepien, P
Stiehl, D
Sun, X
Swanson, G
Syed, H.H
Sørensen, C.G
Tola, E
Torbert, H
Uhrmann, F
Upadhyaya, S.K
V.M., A.H
Viator, B.J
Walsh, O.S
Wang, J
Westbrook, J
Weule, M
Xu, J
Xu, K
Zaller, M
Zhang, X
Zhao, C
Zhou, C
de Oliveira Costa Neto, A
http://icons.paqinteractive.com/16x16/ac, G
http://icons.paqinteractive.com/16x16/ac, G
http://icons.paqinteractive.com/16x16/ac, G
kaboodi, S
nabizadeh, E
Topics
Modeling and Geo-statistics
Precision Nutrient Management
Robotics and Automation with Row and Horticultural Crops
eXtension: Precision Agriculture on the Internet
Type
Poster
Oral
Year
2010
2014
2024
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Filter results51 paper(s) found.

1. Saltmed Model As An Integrated Management Tool For Precision Management Of Water, Crop, Soil, And Fertilizers

                 SALTMED-2009: A modelling tool for Precision Agriculture                                                    R. Ragab Centre for Ecology and H... R. Ragab

2. Smoothness Index Of Thematic Maps

A thematic map shows the spatial distribution of one or more specific data themes for standard geographic areas. The thematic maps are generated to represent the studied variables, so interpolators are used to determine their values in places not sampled. It is usuall... C.L. Bazzi, E.G. Souza, D. Stiehl

3. Application Of Algebra Hyper-curve Neural Network In Soil Nutrient Spatial Interpolation

Study on spatial variability of soil nutrient is the basis of soil nutrient management in precision agriculture. For study on application potential and characteristics of algebra hyper-curve neural network(AHNN) in delineating soil properties spatial variability and interpolation, total 956 soil samples were taken for alkaline hydrolytic nitrogen measurement from a 50 hectares field using 20m*20m grid sampling. The test data set consisted of 100 random samples extracti... L. Chen, C. Zhao, W. Huang, T. Chen, J. Wang

4. 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 availabil... L. Pan, V.I. Adamchuk, D.L. Martin, M.A. Schroeder, R.B. Fergugson

5. Evaluation Of Yield Maps Using Fuzzy Indicators

  The ultimate goal of application of yield maps is profitable crop output in many farming systems. Yield maps are the starting point in the precision farming system, and provide the final record indicating the effectiveness of any management changes. Researches on yield mapping shown, that positions and boundaries of zones with different levels ... E. Krueger shvetsova, D. Kurtener, D. Kurtener, H. Torbert

6. Assessment Of Climate Variability On Optimal Nitrogen Fertilizer Rates For Precision Agriculture

 Yield response functions... B. Basso, G. Http://icons.paqinteractive.com/16x16/ac, G. Http://icons.paqinteractive.com/16x16/ac, G. Http://icons.paqinteractive.com/16x16/ac

7. Mapping The Effect Of Food Prices, Productivity And Poverty In The Development Domains Of Nigeria

  Poverty remains the major obstacle to economic emancipation and achievement of development agenda in Nigeria. Worse still, rising food prices pose a major threat to feeding the teeming population in Nigeria. Declining food production, high population growth, and negative food trade balance combine to worsen the food and poverty situations in Nigeria. We stand on the premise that surging and volatile food prices could have a hardest hit on those who could not afford it –... O.E. Olayide, A.E. Ikpi, V.O. Okoruwa, , T. Alabi, T. Omodele

8. Early Identification Of Leaf Rust On Wheat Leaves With Robust Fitting Of Hyperspectral Signatures

Early recognition of pathogen infection is of great relevance in precision plant protection. Disease detection before the occurrence of visual symptoms is of particular interest. By use of a laserfluoroscope, UV-light induced fluorescence data were collected from healthy and with leaf rust infected wheat leaves of the susceptible cv. Ritmo 2-4 days after inoculation under controlled conditions. In order to evaluate disease impact on spectral characteristics 215 wavelengths in the range of 370... C. R, T. Rumpf, K. B, M. Hunsche, L. Pl, G. Noga

9. Decision Making And Operational Planning

In order to automatize crop farming and its processes, a number of technological and other problems have to be solved. Agricultural field robots are in our vision to fulfill operations in fields. Robots involve number of technological challenges in order to be functional and reliable, but also systems controlling these robots are to be developed. In this paper automatic crop farming is the vision, and decision making models and operational planning is discussed. Study is carried out with simu... T. Oksanen, ,

10. Wheat Growth Stages Discrimination Using Generalized Fourier Descriptors In Pattern Recognition Context

... F. Cointault, A. Marin, L. Journaux, J. Miteran, R. Martin

11. Development Of A Decision Support System For Precision Areawide Pest Management In Cotton Production

  Crop models simulate growth and development, and provide relevant information for the routine management of the crop.  The use of crop models on large areas for diagnosing crop growing conditions or predicting crop production is hampered by the lack of sufficient spatial information about model inputs. Integrating crop models with other information technologies such as geographic information systems (GIS), variable rate technology, remote sensing, and global p... Y. Lan, W.C. Hoffmann, J. Westbrook, M. Zaller

12. Mapping Soil Salinity Using Cokriging Method In Arsanjan Plain, Southern Iran

  Salt-affected landscapes are highly sensitive to changes in climatic, edaphic and hydrological conditions in time and space in semi-arid regions such as Arsanjan plain, southern Iran. The objective of this study was to combine digital satellite data with ground based measurements of ECe by cokriging method to possibility improve the soil salinity maps of study area. Soil samples in the 85 sampling site (10187 ha)were collected from 0-30 cm depths, georefrenced using GPS recei... M.P. Baghernejad, M.M. Emadi

13. Accounting For Spatial Correlation Using Radial Smoothers In Statistical Models Used For Developing Variable-rate Treatment Prescriptions

Variable-rate treatment prescriptions for use on commercial farms can be developed from embedded field trials on those farms. Such embedded trials typically involve non-random, high-density sampling schemes that result in large datasets and response variables exhibiting spatial correlation. In order to accurately evaluate the significance of the effects of the applied treatments and the measured field characteristics on the response of interest, this spatial correlation must be accounted for ... K.S. Mccarter, E. Burris

14. Crop Rotation Impacts ‘Temporal Sampling’ Needed For Landscape-defined Management Zones

Yield and landscape position are used to delineate management zones, but this approach is confounded by yield’s weather dependence, causing yield to evidence temporal variability/lack of yield stability. Management options (e.g. crop rotation) also influence yield stability. Our objective was to build a model that would describe the influence of crop rotation on the temporal yield stability of landscape defined management zones. Corn (Zea mays L.) yield data for two rotat... E.M. Pena-yewtukhiw, J. Grove

15. Extension: Precision Ariculture On The Internet

This session will include an overall description of the new eXtension precision agriculture Web site. eXtension is an interactive learning environment delivering the best, most researched knowledge from land-grant university  across America. Session participants will learn about the Website, and how to participate in the continued site development. The precision agriculture eXtension Web site is a virtual platform for engage... J. Nowatzki, T. Brase

16. Not Possible In Real Life: Precision Agriculture’s Future In 3D Virtual Worlds

Immersive 3D virtual worlds may be several years away from mainstream adoption, but thousands of scientists, educators, and visionary thinkers are already using these environments to network with colleagues, conduct research, create engaging simulations, and develop instructional models that can reach global audiences. Virtual reality offers the potential to create dynamic content that is either not possible to build in real life, or prohibitively expensive. Travel costs can be reduced by bri... L. Phillips

17. The Scholarship Of eXtension

  eXtension (www.extension.org) is an interactive on-line learning environment delivering "best of the best," researched-based knowledge from the top minds across the land-grant university system.  It is a space where university content providers can collaborate to gather and produce new educational and information resources on wide-ranging topics while continually interacting with their customers to help solve real-life problems in real time.  The works of ... M. Lambur

18. We Want You: Contributing Your Expertise To A Community Of Practice (COP)

  eXtension Communities of Practice (CoP’s) are online collaborative networks of subject matter experts.  Community of Practice as a method are not new, almost everyone has come across one by now, but you may not have realized what you were looking at was a collaborative effort.  CoP’s exist on sites like Consumer Reports, in CNET, and many other places where groups of experts work to create the content that populates a website.  Communities are self-... A. Hays

19. Precision Sensors For Improved Nitrogen Recommendations In Wheat

Crop sensor-based systems with developed algorithms for making mid-season fertilizer nitrogen (N) recommendations are commercially available to producers in some parts of the world. Although there is growing interest in these technologies by grain producers in Montana, use is limited by the lack of local research under Montana’s semiarid conditions. A field study was carried out at two locations in 2011, three locations in 2012, and two locations in 2013 in North West Mont... O.S. Walsh, A. Pandey, R. Christiaens

20. Evaluating Different Nitrogen Management Strategies For The Intensive Wheat-Maize System In North China Plain

The sustainable agricultural development involves both environmental challenges and production goals to meet growing food demand. However, excessive nitrogen (N) applications are threatening the sustainability of intensive agriculture in the North China Plain (NCP). Improved N management should result in greater N use efficiency (NUE) and producer profit while reducing the risk of environmental contamination. Therefore, developing and disseminating feasible N management strategi... Q. Cao, Y. Miao, G. Feng, F. Li, B. Liu, X. Gao, Y. Liu

21. 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

22. Precision Nutrient Management In Cotton At Different Yield Targets In Northern Transitional Zone Of Karnataka

  Nutrient management in cotton is complex due to the simultaneous production of vegetative and reproductive structures during the active growth phase. Lot of spatial variation in soil available nutrients is observed under similar management situation. In view of this an experiment ... C.C. Pgowda

23. Variable-Rate Application Of Nitrogen And Potassium Fertilizers In Louisiana Sugarcane Production Systems.

If sugar and cane yields are to be optimized and profitability improved, it is critical that a sugarcane crop receive the proper levels of plant nutrients.  Under-fertilization can result in reduced cane yields, while over-fertilization can reduce sugar recovery.  In addition, improper fertilization may increase crop susceptibility to environmental stresses and disease and insect pests. Nitrogen (N) continues to be one of the most important and co... B.J. Viator, R.M. Johnson

24. Estimation Of Nitrogen And Chlorophyll Content In Wheat Crop Using Hand Held Sensors

A Field experiment was conducted to estimate crop nitrogen (N) status and chlorophyll content in wheat crop by using chlorophyll content meter(Apogee’s CCM-200) and N-Tester®  (Make YARA International). The experiment was conducted by sowing university recommended wheat variety viz. PBW 550 with 5 nitrogen levels i.e. 0, 30, 60, 90, 120 & 150 kg N/ha. It was found that at tillering stage when nitrogen rates were increased from 0 to 150 kg ha-1 , the... M.S. Makkar, A. Kaul, R. Kumar, A. Sharma, B.S. Sekhon, C.S. Pannu

25. Multilayer And Multiyear Data Analysis In Precision Yield Planning

This work covers two separate field experiments. In the first one, the results of 1-ha grid soil analysis for soil organic matter (OM), pH, cation exchange capacity (CEC), nitrate N, P, K, S, Ca, Mg and soluble salts were compared with the results of yield mapping, biomass index from optical on-the-go sensors, as well as multispectral imagery analysis for the last 30 years.  As a result, it was found that none of the analyzed soil characteristics was predominant for determining yiel... A. Melnitchouck

26. 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 fro... V. Patil, R. Madugundu, E. Tola, S. Marey, D.J. Mulla, S.K. Upadhyaya, K.A. Al-gaadi

27. Optical Sensors To Predict Nitrogen Demand By Sugarcane

The low effectiveness of nitrogen (N) from fertilizer is a substantial concern in worldwide which has been threatening the sustainability of sugarcane production. The increment of nitrogen use efficiency (NUE) by sugarcane genotypes associated to the best practices of fertilizer management and nutritional diagnosis methods have higher potential to reduce environment impacts of nitrogen fertilization. Due to the difficult to determine N status in soil test as well as there is not... O.T. Kolln, G.M. Sanches, J. Rossi neto, S.G. Castro, E. Mariano, R. Otto, R. Inamasu, P.S. Magalhães, O.A. Braunbeck, H.C. Franco

28. Effect Of Land Use Over Spatial Variability Of Nitrogen Mineralization And Some Of Chemical Soil Properties In Mirabad Area Of Iran

Abstract Any changes in ecosystem conditions and land management impact on ecology of soil inorganic nitrogen. Understanding of the biology soil is increasingly important for sustainable ecosystem. The aim of this study was to investigate the spatial variability and zoning of nitrogen mineralization, organic carbon and calcium carbonate influenced by the user of apple orchards, crop production and pasture, and compare the two interpola... E. Nabizadeh, S. Kaboodi

29. 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. Th... X. Zhang, Y. Li, K. Xu, X. Sun

30. Site Specific Drip Fertigation

Two test plots, one from high fertility zone and one from low fertility zone were identified and delineated with the help of GPS for raising the test crop. Soil samples were collected from the experimental sites one month before planting. The samples were analyzed for available N, P and K. Site specific nutrient recommendations were made using the Decision Support System for Integrated Fertilizer Recommendation (DSSIFER) software (Murugappan et al. 2004) for optimum yie... A.H. V.m.

31. 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

32. The Most Sensitive Growth Stage To Quantify Nitrogen Stress In Sugarcane Using Active Crop Canopy Sensor

The use of sensors that allow the application of nitrogen fertilizer at variable rate has been widely used by researchers in many agricultural crops, but without success in sugarcane, probably due to the difficulty of diagnosing the nutritional status of the crop for nitrogen (N). Active crop canopy sensors are based on the principle that the spectral reflectance curve of the leaves are modified by N level. Researchers in USA indicated that in-season N stress in corn can be dete... S.G. Castro, O.T. Kolln, H.S. Nakao, H.C. Franco, O. Braunbeck, P.S. Graziano magalhães, G.M. Sanches

33. Nutrient Expert Software For Nutrient Management In Cereal Crops

Many countries in Asia have started replacing blanket fertilizer recommendations for vast areas of rice, maize, or wheat with more site-specific guidelines adapted to local needs. This process has been accompanied with a shift from traditional on-station research to on-farm development and evaluation of novel practices. A key challenge faced by the local extension agencies remains the complex nature of factors influencing nutrient requirements.  To aid in this process, the ... M. Pampolino, K. Majumdar, S. Phillips

34. Precision Nutrient Management Through Use Of LCC And Nutrient Expert In Hybrid Maize Under Laterite Soil Of India

Nutrient management has played a crucial role in achieving self sufficiency in food grain production. Energy crisis resulted in high price index of chemical fertilizers. Coupled with their limited production, fertilizer cost, soil health, sustainability and pollution have gave rise to interest in precision nutrient management tools. Field experiment was conducted to study the effect of variety and nutrient management on the growth and productivity of maize under lateritic belt of West Be... M. Banerjee, S. Dutta, G. Bhuiya, G. Malik, D. Maiti

35. Comparison Of The Variable Potassium Fertilization On The Light And Heavy Soils

Introduction. Determination of the spatial variability of the nutrient levels in soil facilitated adaptation of the fertilizer doses to the soluble forms availability. Nowadays, an increasing use of this method of the fertilizer application is observed, with this being associated with both economical and environmental advantages, as well as, with growing assortment of the purpose-built agricultural instrumentation. An accurate determination of the spatial distri... P. Grocholski, P. Stepien, G. Kulczycki, A. Michalski

36. 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-ti... J.S. Schepers, B. Mclure, G. Swanson

37. Automated In-field Ornamental Nursery Plant Counting and Quality Assessment with End-to-end Deep Learning for Inventory Management

Efficient inventory management and rigorous quality evaluation play crucial roles for monitoring sales, yield, space utilization, production schedules, and quality enhancements in the ornamental nursery sector. The current method for conducting inventory and quality assessments is through manual plant counting, even when dealing with thousands of plants. The prevailing approach is inefficient, time consuming, labor intensive, potential inaccuracies, and high expenses. Given the continuous dec... H.H. Syed, T. Rehman

38. 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 pe... H. Kulhandjian, M. Kulhandjian, D. Rocha, B. Bennett

39. 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 autonomous... H. Kulhandjian, N. Amely, M. Kulhandjian

40. Creating a Comprehensive Software Framework for Sensor-driven Precision Agriculture

Robots and GPS-guided tractors are the backbone of smart farming and precision agriculture. Many companies and vendors contribute to the market, each offering their own customized solutions for common tasks. These developments are often based on vendor-specific, proprietary components, protocols and software. Many small companies that produce sensors, actuators or software for niche applications could contribute their expertise to the global efforts of creating smart farming solutions, if the... O. Scholz, F. Uhrmann, M. Weule, T. Meyer, A. Gilson, J. Makarov, J. Hansen, T. Henties

41. Enhancing Precision Agriculture Through Dual Weed Mapping: Delineating Inter and Intra-row Weed Populations for Optimized Crop Protection

In the field of precision agriculture, effective management of weed populations is essential for optimizing crop yield and health. This paper presents an innovative approach to weed management by employing dual weed mapping techniques that differentiate between inter-row and intra-row weed populations. Utilizing advanced imaging and data analysis of CropEye images collected by the Robotti robot from AgroIntelli (AgroIntelli A/S, Aarhus, Denmark), we have developed methods to generate distinct... R.N. Jørgensen, S. Skovsen, O. Green, C.G. Sørensen

42. Voronoi-based Ant Colony Optimization Approach: Autonomous Robotic Swarm Navigation for Crop Disease Detection

The early detection of agricultural diseases is essential for sustaining food production and economic viability over the long term. To improve disease detection in agriculture, this paper presents an innovative computational approach that utilizes the Voronoi-based Ant Colony Optimization (V-ACO) algorithm with Swarm Robotics (SR). Inspired by the social behaviors observed in insect colonies such as honeybees and ants, SR offers new opportunities for precision farming. SR utilizes the coordin... S. Gummi, M. Alahe, Y. Chang, C. Pack

43. Partial Fruitlet Cutting Approach for Robotic Apple Thinning

Early season thinning of apple fruitlets is a crucial task in commercial apple farming, traditionally accomplished through chemical sprays or labor-intensive manual operations. These methods, however, are faced with the challenges of diminishing labor availability as well as environmental and/or economic sustainability. This research examines 'partial fruitlet cutting,' a novel nature-assisted strategy, as an alternative method for automated apple thinning in orchards. The study hypot... R. Sapkota, M. Karkee

44. Real Time Application of Neural Networks and Hardware Accelerated Image Processing Pipeline for Precise Autonomous Agricultural Systems

Modern agriculture is increasingly turning to automation and precision technology to optimize crop management. In this context, our research addresses the development of an autonomous pesticide spraying rover equipped with advanced technology for precision agriculture. The primary goal is to use a neural network for real-time aphid detection in Sorghum crops, enabling targeted pesticide application only to infested plants. To accomplish this, we've integrated cutting-edge technologies and... J. Raitz persch, R. Harsha chepally, N.K. Piya

45. Advancements in Agrivoltaics: Autonomous Robotic Mowing for Enhanced Management in Solar Farms

Agrivoltaics – the co-location of solar energy installations and agriculture beneath or between rows of photovoltaic panels – has gained prominence as a sustainable and efficient approach to land use. The US has over 2.8 GW in Agrivoltaics, integrating crop cultivation with solar energy. However, effective vegetation management is critical for solar panel efficiency. Flat, sunny agricultural land accommodates solar panels and crops efficiently. The challenge lies in managing grass... S. Behera, S. Pitla

46. Implementation of Autonomous Material Re-filling Using Customized UAV for Autonomous Planting Operations

This project introduces a groundbreaking use case for customized Unmanned Aerial Vehicles (UAVs) in precision agriculture, focused on achieving holistic autonomy in agricultural operations through multi-robot collaboration.  Currently, commercially available drones for agriculture are restrictive in achieving collaborative autonomy with the growing number of unmanned ground robots, limiting their use to narrow and specific tasks.  The advanced payload capacities of multi-rotor UAVs,... V. Muvva, H. Mwunguzi, S. Pitla, K. Joseph

47. Advancements in Agricultural Robots for Specialty Crops: a Comprehensive Review of Innovations, Challenges, and Prospects

The emergence of robot technology presents a timely opportunity to revolutionize specialty crop production, offering crucial support across various activities such as planting, supporting general traits, and harvesting. These robots play a pivotal role in keeping stakeholders up-to-date of developments in their production fields, while providing them the capability to automate laborious tasks. Then, to elucidate the advancements in this domain, we present the results of a comprehensive review... M. Barbosa, R. Santos, L. Sales, L. Oliveira

48. Utilizing ArUco Markers to Define Implement Boundaries

John Deere and Blue River Technology’s autonomous tillage system combines multidisciplinary efforts and cutting-edge technology to achieve Level 5—Unsupervised Autonomy. To create this engineering marvel, countless parameters need defined to ensure safe operation of the system; some of these parameters are static, while other of these parameters are dynamic. One particular set of parameters define the tillage implement’s boundaries for the software stack to utilize, and toda... R. Sleichter

49. Automated Detection and Length Estimation of Green Asparagus Towards Selective Harvesting

Green asparagus is an important vegetable crop in the United States (U.S.). Harvesting the crop is notoriously labor-intensive, accounting for over 50% of production costs. There is an urgent need to develop harvesting automation technology for the U.S. asparagus industry to remain sustainable and competitive. Despite previous research and developments on mechanical asparagus harvesting, no practically viable products are available because of their low harvest selectivity and significant yiel... J. Xu, Y. Lu

50. Agrosense: AI-enabled Sensing for Precision Management of Tree Crops

Monitoring the tree inventory and canopy density and height frequently is critical for researchers and farm managers. However, it is very expensive and challenging to manually complete these tasks weekly. Therefore, a low-cost and artificial intelligence (AI) enhanced sensing system, Agrosense, was developed for tree inventory, canopy height measurement, and tree canopy density classification in this study. The sensing system mainly consisted of four RGB-D cameras, two Jetson Xavier NX, and o... C. Zhou, Y. Ampatzidis, H. Guan, W. Liu, A. De oliveira costa neto, S. Kunwar, O. Batuman

51. SurePoint Ag Systems - Sponsor Presentation

... B. Downing