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Decision Support Systems in Precision Agriculture
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
eXtension: Precision Agriculture on the Internet
Modeling and Geo-statistics
Precision Nutrient Management
Robotics and Automation with Row and Horticultural Crops
Site-Specific Pasture Management
Precision Nutrient Management
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Authors
Abbasi, E
Adamchuk, V.I
Akune, V.S
Al Darwish, F.H
Al-Gaadi, K.A
Al-Gaadi, K.A
Alabi, T
Alahe, M
Alahe, M
Alchanatis, V
Aliloo, J
Amely, N
Ampatzidis, Y
Araujo, R
Avemegah, E
B, K
Baghernejad, M
Balboa, G
Balboa, G
Banerjee, M
Barbosa, M
Basso, B
Basso, B
Batuman, O
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Beaudoin, N
Been, T
Behera, S
Behrendt, K
Beneduzzi, H.M
Benez, S.H
Bennett, B
Betzek, N.M
Betzek, N.M
Bhuiya, G
Bierman, D
Blackmer, T.M
Blackmer, T.M
Bodson, B
Bonfil, D.J
Bonke, V
Borchert, A
Borchert, A
Bradacova, K
Bradacova, K
Brase, T
Braunbeck, O
Braunbeck, O.A
Burris, E
Cambouris, A
Canavari, M
Cao, Q
Castro, S.G
Castro, S.G
Chang, Y
Chang, Y
Chang, Y
Chen, L
Chen, T
Cho, J
Christiaens, R
Ciampitti, I
Citon, L.C
Clark, J
Cohen, Y
Cointault, F
Craker, B.E
Dabbelt, D
Destain, J
Destain, M
Devakumar, N
Downing, B
Drury, C
Dumont, B
Duncan, S
Dutta, S
Emadi, M.M
Erickson, B
Eshel, G
Feng, G
Fergugson, R.B
Ferraz, M.N
Fountas, S
Franco, H.C
Franco, H.C
Gao, X
Gavioli, A
Gavioli, A
Ghanbari Parmehr, E
Gilson, A
Giriyappa, M
Goel, R
Goswami, S
Graziano Magalhães, P.S
Green, O
Grocholski, P
Grove, J
Guan, H
Guinness, J
Gummi, S
Gummi, S
Gupta, M
H, V
Haapala, H.E
Hansen, J
Hanumanthappa, D
Harari, A
Harris, W.E
Harsha Chepally, R
Hatfield, J
Hays, A
Henties, T
Hoffmann, W.C
Huang, W
Hunsche, M
Ikpi, A.E
Inamasu, R
Jangandi, S
Jego, G
Johnson, R.M
Joseph, K
Journaux, L
Jørgensen, R.N
Kanannnavar, P.S
Karamidehkordi, E
Karkee, M
Kaul, A
Kemeshi, J.O
Kemeshi, J.O
Kempenaar, C
Ketterings, Q
Khosla, R
Khosla, R
Khosla, R
Klapp, I
Kocks, C
Kolln, O.T
Kolln, O.T
Kovacs, P
Krishna, D
Krueger Shvetsova, E
Kulczycki, G
Kulhandjian, H
Kulhandjian, H
Kulhandjian, M
Kulhandjian, M
Kumar, R
Kunwar, S
Kurtener, D
Kurtener, D
Kyveryga, P.M
Kyveryga, P.M
Lambur, M
Lan, Y
Laor, Y
Li, F
Li, F
Li, Y
Liakos, V
Lindblom, J
Linker, R
Liu, B
Liu, W
Liu, Y
Longchamps, L
Lowenberg-DeBoer, J
Lowenberg-DeBoer, J
Lowrance, C
Lu, Y
Ludewig, U
Lundström, C
Ma, B
Madugundu, R
Magalhães, P.S
Magen, H
Maiti, D
Majumdar, K
Makarov, J
Makkar, M.S
Malagi, M.T
Malik, G
Mallikaarjuna, G
Marcaida, M
Marey, S
Mariano, E
Marin, A
Marjerison, R
Martin, D.L
Martin, R
Maxwell, T
McCarter, K.S
McFadden, J
Mclure, B
Melnitchouck, A
Melnitchouck, A
Meyer, T
Miao, Y
Miao, Y
Michalski, A
Michels, M
Michels, M
Milics, G
Miteran, J
Moebiu-Clune, B
Moebius-Clune, D
Molin, J.P
Morad-Talab, N
Mulla, D.J
Muvva, V
Mußhoff, O
Mußhoff, O
Mwunguzi, H
Müller, T
N.L., R
Nakao, H.S
Nakazawa, P.H
Neumann, G
Nkebiwe, M
Nobrega, L.H
Noga, G
Nowatzki, J
Nysten, S
Nze Memiaghe, J.D
Okoruwa, V.O
Oksanen, T
Olayide, O.E
Olfs, H
Olfs, H
Oliveira, L
Omodele, T
Otto, R
Paccioretti, P
Pack, C
Pampolino, M
Pan, L
Pandey, A
Pannu, C.S
Patil, M.B
Patil, V
Patil, V.C
Pattey, E
Paz-Kagan, T
Peets, S
Pena-Yewtukhiw, E.M
Pgowda, C.C
Phillips, L
Phillips, S
Pitla, S
Pitla, S
Piya, N.K
Pl, L
Preiner, M
Puntel, L
R, C
Ragab, R
Rahman, M.M
Raitz Persch, J
Raju, N
Ramos-Tanchez, J
Rao, K
Raupp, M
Recke, G
Rehman, T
Reich, R.M
Rocha, D
Rocha, D.M
Romanelli, T.L
Rossi Neto, J
Rozenstein, O
Rudramuni, T
Rumpf, T
Rutter, M.S
Saha, S
Sales, L
Salimath, S.B
Salzer, Y
Sanches, G.M
Sanches, G.M
Sansoulet, J
Santana Neto, A.J
Santos, R
Sapkota, R
Schad, J
Schenatto, K
Schenatto, K
Schepers, J.S
Schindelbeck, R
Schneider, S
Scholz, O
Schroeder, M.A
Sekhon, B.S
Sela, S
Shajahan, S
Shankar, M
Shanwad, U
Sharda, A
Sharma, A
Sheshadri, T
Shoups, D
Skovsen, S
Sleichter, R
Soaud, A.A
Souza, E.G
Souza, E.G
Souza, E.G
Souza, E.G
Souza, W.J
Spekken, M
Srinivasa Rao, C
Srinivasagan, S
Stepien, P
Stiehl, D
Subba Rao, A
Sun, X
Swamy, S
Swanson, G
Syed, H.H
Sørensen, C.G
Thompson, L
Thompson, L
Tola, E
Torbert, H
Trautz, D
Trautz, D
Tremblay, N
Uhrmann, F
Upadhyaya, S.K
Uribe-Opazo, M.A
V.M., A.H
Varela, S
Vellidis, G
Venkateswarlu, B
Viator, B.J
Vigil, M
Vitali, G.-
Walsh, O.S
Walthall, C
Wang, J
Weber, N
Weinmann, M
Westbrook, J
Westerdijk, K
Westfall, D.G
Weule, M
Wever, H
Wever, H
Xu, J
Xu, K
Yadav, P.K
Zaller, M
Zhang, X
Zhao, C
Zhou, C
de Oliveira Costa Neto, A
de Souza, E.G
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
van Es, H
van Evert, F
Topics
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Modeling and Geo-statistics
Decision Support Systems in Precision Agriculture
Precision Nutrient Management
Precision Nutrient Management
Robotics and Automation with Row and Horticultural Crops
eXtension: Precision Agriculture on the Internet
Site-Specific Pasture Management
Type
Oral
Poster
Year
2024
2010
2016
2012
2014
2022
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Filter results93 paper(s) found.

1. Precision Nitrogen Management and Global Nitrogen Use Efficiency

Traditionally, nitrogen (N) fertilizers have been applied uniformly across entire field while ignoring inherent spatial variation in crop N needs across crop fields. This results in either too little or too much application of N in various parts of the ... M. Gupta, R. Khosla

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

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

3. A Statistical and an Agronomic Approach for Definition of Management Zones in Corn and Soybean

The use of productivity level management zones (MZ) has demonstrated good potential for the site-specific management of crop inputs in traditional row crops. The objectives of this research were to analyze the process of defining MZs and develop methods to evaluate the quality of MZ maps. Two approaches were used to select the layers to be used in the MZ definition: 1) Statistical Approach (SA_MZ) and 2) Agronomic Approach (AA_MZ). The difference is that in the AA_MZ approach all non stable v... C.L. Bazzi, E.G. Souza, R. Khosla, R.M. Reich

4. Use of Chemical and Physical Attributes Of the Soil in Management Units Definition

Several equipments and methodologies have been developed to make available precision agriculture, especially the high cost of its implantation and sampling. An interesting ... C.L. Bazzi, E.G. Souza, L.H. Nobrega, M.A. Uribe-opazo, D.M. Rocha

5. Early Detection of Corn N-Deficiency by Active Fluorescence Sensing in Maize

Globally, the agricultural nitrogen use efficiency (NUE) is no more than 40 %. This low efficiency comes with an agronomic, economic and environmental cost. By better management of spatial and temporal variability of crop nitrogen need, NUE can be improved. Currently available crop canopy sensors based on reflectance are cap... R. Khosla, D.G. Westfall, L. Longchamps

6. Stable Isotope N-15 as Precision Technique to Investigate Elemental Sulfur Effects on Fertilizer Nitrogen Use Efficiency of Corn Grown in Calcareous Sandy Soils

... A.A. Soaud, .M. Rahman, F.H. Al darwish

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

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

8. Precision Fertigation in Wheat for Sustainable Agriculture in Saudi Arabia

Wheat is an important cereal crop of Saudi Arabia grown on an area of 250,000 ha with an annual production of 1,260,000 metric tons. The crop is cultivated on sandy soils using sprinkler irrigation under center pivots. The crop is sown in Nove... V.C. Patil, K.A. Al-gaadi

9. Soil pH maps Derived from On-the-Go pH-Measurements as Basis for Variable Lime Application under German Conditions: Concept Development and Evaluation in Field Trials

... A. Borchert, D. Trautz, H. Olfs

10. Economic Evaluation of a Variable Lime Application Strategy Based on Soil pH Maps Derived from On-The-Go pH-Measurements under German Conditions

... A. Borchert, G. Recke, D. Dabbelt, D. Trautz, H. Olfs

11. Deriving Nitrogen Indicators of Maize Using the Canopy Chlorophyll Content Index

Many spectral indices have been proposed to derive aerial nitrogen (N) status parameters of crops in recent decades. However, most of red light based spectral indices easily loss sensitivity at moderate-high aboveground biomass. The objective of present study is to assess the performance of red edge bas... Y. Miao, F. Li

12. Precision Nutrient Management in Cotton- A Case Study from India

Cotton is being one of the important commercial crops in India, farmers have adopted cultivating hybrid cotton to achieve higher yield. In this context, cotton is becoming input intensive crop... U. Shanwad, V. H, R. N.l., P.S. Kanannnavar, S. Swamy, M.B. Patil

13. Site-Specific Evaluations of Nitrification Inhibitor with Fall Applications of Liquid Swine Manure

... P.M. Kyveryga, T.M. Blackmer

14. Digital Aerial Imagery Guides a Statewide Nutrient Management Benchmarking Survey

... P.M. Kyveryga, T.M. Blackmer

15. Performance Evaluation of STICS Crop Model to Simulate Corn Growth Attributes in Response to N Rate and Climate Variations

Improving nitrogen use efficiency in crop plants contributes to increase the sustainability of agriculture. Crop models could be used as a tool to test the impact of climatic conditions on crop growth under several N management practices and to refine N application recommendation and strategy. STICS, a crop growth simulator developed by INRA (France), has the capability to assimilate leaf area index (LAI) from remote sensing to re-initialize input parameters, such as seeding date and see... E. Pattey, G. Jego, N. Tremblay, C. Drury, B. Ma, J. Sansoulet, N. Beaudoin

16. Determination of Optimal Number of Management Zones

... A. Melnitchouck

17. Effect of Urea Application through Drip Irrigation on Yield, Water and Nitrogen Use Efficiency of Summer Bitter Gourd

Bitter gourd (Momordica charantia L.) is one of the important vegetable crops grown during summer months in high lands of Lower Gangetic Plains.  Crop is very much responsive to water and nutrient but water is limiting in dry summer months.  Farmers generally adopt furrow irrigation and hand watering with pitcher for growing this crop.  Drip irrigation ... S. Goswami, S. Saha

18. Field Moist Processing for Soil Analysis: Precision Measurement is Required for Precision Management

It has been well established over the last 50 years that many of the typical processes used by conventional soil analysis (such as drying and grinding the soil during preparation) can affect measured soil nutrient values. However, these processes have become conventional practice due to a lack of commercially viable methods of processing soil in its native field moist state. Solum, Inc (Mountain View, CA) has developed a process that allows routine, high throughput mea... M. Preiner

19. 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

20. 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

21. 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

22. 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

23. 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

24. 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

25. 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

26. 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

27. 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, ,

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

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

29. 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

30. 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

31. 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

32. 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

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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

39. 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

40. 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

41. 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

42. 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

43. 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

44. 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

45. 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

46. 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

47. 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

48. 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.

49. 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

50. 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

51. 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

52. 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

53. 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

54. 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

55. Site Specific Costs Concerning Machine Path Orientation

Computer algorithms have been created to simulate in advance the orientation/pattern of a machine operation on a field. Undesired impacts were obtained and quantified for these simulations, like: maneuvering and overlap of inputs in headlands; servicing of secondary units; and soil loss by water erosion. While the efforts could minimize the overall costs, they disregard the fact that these costs aren’t uniformly distributed over irregular fields. The cost of a non-productive machine pro... M. Spekken, J.P. Molin, T.L. Romanelli, M.N. Ferraz

56. Considering Farmers' Situated Expertise in AgriDSS Development to Fostering Sustainable Farming Practices in Precision Agriculture

Agriculture is facing immense challenges and sustainable intensification has been presented as a way forward where precision agriculture (PA) plays an important role. More sustainable agriculture needs farmers who embrace situated expertise and can handle changing farming systems. Many agricultural decision support systems (AgriDSS) have been developed to support farm management, but the traditional approach to AgriDSS development is mostly based on knowledge transfer. This has resulted in te... C. Lundström, J. Lindblom

57. Comparing Adapt-N to Static N Recommendation Approaches for US Maize Production

Large temporal and spatial variability in soil N availability leads many farmers across the US to over apply N fertilizers in maize (Zea Mays L.) production environments, often resulting in large environmental N losses.  Static N recommendation tools are typically promoted in the US, but new dynamic model-based tools allow for more precise and adaptive N recommendations that account for specific production environments and conditions. This study compares two static N recommendation tools... H. Van es, S. Sela, R. Marjerison, B. Moebiu-clune, R. Schindelbeck, D. Moebius-clune

58. Data Normalization Methods for Definition of Management Zones

The use of management zones is considered a viable economic alternative for the management of crops due to low cost of adoption as well as economic and environmental benefits. The decision whether or not to normalize the attributes before the grouping process (independent of use) is a problem of methodology, because the attributes have different metric size units, and may influence the result of the clustering process. Thus, the aim of this study was to use a Fuzzy C-Means algorithm to evalua... K. Schenatto, E.G. De souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, H.M. Beneduzzi

59. EZZone - An Online Tool for Delineating Management Zones

Management zones are a pillar of Precision Agriculture research.  Spatial variability is apparent in all fields, and assessing this variability through measurement devices can lead to better management decisions.  The use of Geographic Information Systems for agricultural management is common, especially with management zones.  Although many algorithms have been produced in research settings, no online software for management zone delineation exists.  This research used a ... G. Vellidis, C. Lowrance, S. Fountas, V. Liakos

60. Smart Agriculture: A Futuristic Vision of Application of the Internet of Things (IoT) in Brazilian Agriculture

With the economy based on agribusiness, Brazil is an important representative on the world stage in agricultural production, either in terms of quantity or cultivated diversity due to a scenario with vast arable land and favorable climate. There are many crops that are adapteble to soils of the country. Despite the global representation, it is known that the Brazilian agricultural production does not yet have a modern agriculture by restricting the use of new technologies to farmers with bett... C.L. Bazzi, R. Araujo, E.G. Souza, K. Schenatto, A. Gavioli, N.M. Betzek

61. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the Netherlands

Precision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traff... C. Kempenaar, F. Van evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten

62. Agronomic Characteristics of Green Corn and Correlations with Productivity for the Establishment of Management Zones in Vale Do Ribeira, SP, Brazil

In Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphi... W.J. Souza, V.S. Akune, S.H. Benez, L.C. Citon, P.H. Nakazawa, A.J. Santana neto

63. On Farm Studies to Determine Seeding Rate in Corn

Seeding rate (SDR) is one of the most critical production practices impacting productivity and economic return for corn (Zea mays L.) By changing SDRs in different zones within a field, herein termed as site-specific management, better economic results can be produced as the outcome of reducing SDRs in low productivity areas and increasing SDRs under high-yielding environments, relative to the uniform SDR management performed by the producer. The aim of this study was to analyze yield respons... G. Balboa, S. Varela, I. Ciampitti, S. Duncan, T. Maxwell, D. Shoups, A. Sharda

64. Closing Yield Gaps with GxExM and Precision Agriculture

There are many challenges to be faced by agriculture if the global population of nine billion people projected for 2050 is to be fed and clothed, especially given the effects of changing climate.  A focus on the interactions of genetics x environment x management (GxExM) offers potential for meeting the yield, and environment and economic sustainability goals that are integral to these challenges.  The yield gap –defined as the difference between current farmer yields and pote... C. Walthall, J. Hatfield, S. Schneider, M. Vigil

65. Grassland System Impacts on Spatial Variability of Soil Phosphorus in Eastern Canada

Phosphorus (P) is an essential nutrient for plants, including grasslands. However, continuous applications of P fertilizer result in P accumulations in the soil, increasing the risk of P losses through runoff and erosion. Since 2008, more than 31 million tonnes of organic fertilizers, representing more than 95,000 tonnes of P2O5, were applied to agricultural fields in Eastern Canada. Thus, grassland systems were fertilized intensively using organic fertilizers with high ... J.D. Nze memiaghe, A. Cambouris

66. Content Analysis of the Challenges of Using Drones in Paddy Fields in the Haraz Plain Watershed, Iran

Drone technology has gained popularity in recent years as a sustainable solution to changing agricultural conditions. Using drones in agriculture provides many advantages in farm management. However, the use of drones in paddy fields in Iran is a new phenomenon facing numerous challenges. This study aims to explore the challenges for using drones in paddy fields and provide practical guidelines to solve the challenges facing the their application. This research was conducted with a qualitativ... J. Aliloo, E. Abbasi, E. Karamidehkordi , E. Ghanbari parmehr, M. Canavari, G.-. Vitali

67. Treetop Tech: Uplifting German Foresters' Drone Perspectives Through the Technology Acceptance Model

Forests play a key role in nature as they purify water, stabilize soil, cycle nutrients, store carbon and also provide habitats for wildlife. Economically, forest product industries provide jobs and economic wealth. Sustainable forest management and planning requires foresters’ understanding of the forests dynamics for which the collection of field data is necessary, which can be time consuming and expensive. Unmanned aerial vehicles or drones can improve the efficiency of tradition acq... M. Michels, H. Wever, O. Mußhoff

68. Farming for a Greener Future: the Behavioural Drive Behind German Farmers’ Alternative Fuel Machinery Purchase Intentions

Climate change due to greenhouse gas emissions, e.g. anthropogenic carbon dioxide (CO2), in the atmosphere will lead to damages caused by global warming, increases in heavy rainfall, flooding as well as permafrost melt. One of the main issues for reducing greenhouse gas emissions is the dependence on oil for fueling transportation and other sectors. Accordingly, policy makers aim to reduce dependency on fossil fuels with the accelerated roll-out of renewable energy. Among others, t... M. Michels, V. Bonke, H. Wever, O. Mußhoff

69. Finnish Future Farm Speeding Up the Uptake of Precision Agriculture

The Finnish Future Farm (FFF) is an innovative concept that seamlessly integrates a physical Smart Farm with a Digital Twin, complemented by educational programs and business development opportunities. This holistic approach aims to propel the evolution of Smart Agriculture in Finland. At its core, FFF is a platform for co-creation with a strong emphasis on User-Centered Design. It employs a Multi-Actor Approach, bringing together companies, experts, researchers, and end users to co... H.E. Haapala

70. Global Adoption of Precision Agriculture: an Update on Trends and Emerging Technologies

The adoption of precision agriculture (PA) has been mixed. Some technologies (e.g., Global Navigation Satellite System (GNSS) guidance) have been adopted rapidly worldwide wherever there is mechanized agriculture. Adoption of some of the original PA technologies introduced in the 1990s has been modest almost everywhere (e.g., variable rate fertilizer). New and more advanced technologies based on robotics, uncrewed aerial vehicles (UAVs), machine vision, co-robotic automation, and artificial i... J. Mcfadden, B. Erickson, J. Lowenberg-deboer, G. Milics

71. R2B2 Project: Design and Construction of a Low-cost and Efficient Autonomous UGV For Row Crop Monitoring

Driving the adoption of agricultural technological advancements like Unmanned Ground Vehicles (UGVs) by small-scale farmers (SSFs) is a major concern for researchers and agricultural organizations. They aim for the adoption of precision farming (PF) by SSFs to increase crop yield to meet the increasing demand for food due to population growth. In the United States, the cost of purchasing and maintaining rugged UGVs capable of precision agricultural operations stands as a barrier to the a... J.O. Kemeshi, S. Gummi, Y. Chang

72. Barriers and Adoption of Precision Ag Tehcnologies for Nitrogen Management Nebraska

A statewide survey of Nebraska farmers shows that they determine the N rate based on soil lab recommendations (82%),  intuition, traditional rate, and own experience (67%). The adoption of dynamic site-specific models (23%), and sensor-based algorithms (11%) remains low. The survey identified the main barriers to the adoption of these N management technologies.  ... G. Balboa, L. Puntel, L. Thompson, P. Paccioretti

73. Bio-Effectors As a Promising Tool for Precision Agriculture and Integrated Plant Nutrition

Bio-effectors, such as microorganisms and active natural compounds, are of increasing interest as promising alternatives or substitutes to precarious agrochemicals. European and global markets (valued at 14.6 billion US$ in 2023) for agricultural biologicals (bio-pesticides, bio-fertilizers, and bio-stimulants) are predicted to grow at rates of more than 13.5 % per year. Improved availability and use efficiency of mineral nutrients, tolerance to abiotic stresses, yield and quality traits, as ... M. Weinmann, M. Nkebiwe, N. Weber, K. Bradacova, N. Morad-talab, U. Ludewig, T. Müller, G. Neumann, M. Raupp, K. Bradacova

74. Who Are the Data Stewards: Moving Data Driven Agriculture Forward

Nearly a decade ago agricultural equipment manufacturers, service providers, retailers, land grant universities, and grower organizations came together to begin discussing the growing needs for producers to manage their farm data. This discussion was partly fueled by the industry shifting from moving data via physical media to cloud API connections. Several initiatives including the Agricultural Data Coalition (ADC) were subsequently launched focusing on addressing data privacy and security c... B.E. Craker, D. Bierman

75. Comparing Global Shutter and Rolling Shutter Cameras for Image Data Collection in Motion on a UGV

In a bid to drive the adoption of precision farming (PF) technology by reducing the cost of developing an Unmanned Ground Vehicle (UGV), during the Reduction-To-Below-Two grand (R2B2) project we compared Arducam’s AR0234, a global shutter camera (GSC) to their IMX462, a rolling shutter camera (RSC). Since the cost of the AR0234 is approximately three times the price of the IMX462, the comparison was done to determine the possibility of using the latter for image data collection in place... J.O. Kemeshi, Y. Chang, P.K. Yadav, M. Alahe

76. 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 syne... 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

77. Single-strip Spatial Evaluation Approach: a Simplified Method for Enhanced Sustainable Farm Management

On-farm experimentation (OFE) plays a pivotal role in evaluating and validating the effectiveness of agricultural practices and products. The results of OFE enable farmers to act and make changes that can enhance the farm’s economic and environmental sustainability. Experimental designs can be a barrier to the adoption of OFE. The conventional approach often involves randomized complete block designs with 3 to 5 replications in the field, which can be space-intensive and disrupt workflo... S. Srinivasagan, Q. Ketterings, M. Marcaida, S. Shajahan, J. Ramos-tanchez, J. Cho, , L. Thompson, J. Guinness, R. Goel

78. Decision Making Factors of Precision Agricultural Practices in South Dakota

A survey among South Dakota Farmers was conducted to document current nutrient management practices. The survey included questions regarding adoption and use of precision ag technologies in addition to information considered to create prescription maps for variable fertilizer and seeding rates. The survey collected demographic information from the producers. The presentation will also highlight how farm size, farm location, farmer/decision maker’s age and/or education level in... P. Kovacs, J. Clark, J. Schad, E. Avemegah

79. 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

80. 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

81. 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

82. 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

83. 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

84. 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

85. 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

86. 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

87. 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

88. 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

89. 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

90. 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

91. 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

92. 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

93. SurePoint Ag Systems - Sponsor Presentation

... B. Downing