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Precision Nutrient Management
Robotics and Automation with Row and Horticultural Crops
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
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Authors
Abdollahi, J.M
Adamchuk, V.I
Adamchuk, V.I
Ahmad, H.N
Al Darwish, F.H
Al-Gaadi, K.A
Al-Gaadi, K.A
Alahe, M
Alomran, A.M
Alsheri, S.A
Alwabel, M.I
Amely, N
Ampatzidis, Y
Arzani, H.P
Azimi, M.S
Balakrishnan, P
Balakrishnan, P
Banerjee, M
Barbosa, M
Basso, B
Batuman, O
Bazzi, C.L
Bazzi, C.L
Beaudoin, N
Behera, S
Benites, V.D
Bennett, B
Bereuter, A
Bernardi, A.C
Bhuiya, G
Blackmer, T.M
Blackmer, T.M
Blackmer, T.M
Bodson, B
Borchert, A
Borchert, A
Borhani, M.M
Boyko, Y.I
Braunbeck, O
Braunbeck, O.A
Cao, Q
Castrignanò, A
Castro, S.G
Castro, S.G
Chang, Y
Chang, Y.K
Chen, L
Christiaens, R
Corá, J
Cui, B
Dabbelt, D
Daroub, S.H
Denton, A.M
Destain, J
Destain, M
Devakumar, N
Diaz, O.A
Downing, B
Drury, C
Dumont, B
Dutta, S
Esau, T.J
Farahpour, M.D
Farooque, A.A
Farooque, A.A
Farooque, A.A
Feng, G
Ferguson, R.B
Francis, D
Franco, H.C
Franco, H.C
Gao, X
Gianello, E
Gilson, A
Giriyappa, M
Goswami, S
Gowda, H.H
Graziano Magalhães, P.S
Green, O
Griffin, T
Grocholski, P
Groulx, D
Guan, H
Guangwei, W
Gummi, S
Gupta, M
H, V
Hansen, J
Hanumanthappa, D
Harsha Chepally, R
Hendrickson, L
Henties, T
Huang, W
Inamassu, R.Y
Inamasu, R
Irmak, S
Jangandi, S
Jego, G
Jianjun, D
Jin, V
Johnson, R.M
Johnson, R.M
Joseph, K
Jørgensen, R.N
Kaboli, S.D
Kanannavar, P
Kanannavar, P
Kanannnavar, P.S
Karkee, M
Kaul, A
Khan, F
Khan, F.S
Khan, F.S
Khosla, R
Khosla, R
Khosla, R
Kirkpatrick, T
Kolln, O.T
Kolln, O.T
Krishna, D
Kulczycki, G
Kulhandjian, H
Kulhandjian, H
Kulhandjian, M
Kulhandjian, M
Kumar, R
Kunwar, S
Kyveryga, P.M
Kyveryga, P.M
Kyveryga, P.M
L, R.N
Lamb, D.W
Li, F
Li, F
Li, Y
Liping, C
Liu, B
Liu, W
Liu, Y
Liu, Z
Longchamps, L
Lu, Y
Ma, B
Madani, A
Madani, A
Madugundu, R
Magalhães, P.S
Magen, H
Maiti, D
Majumdar, K
Makarov, J
Makkar, M.S
Malagi, M.T
Malik, G
Mallikaarjuna, G
Marey, S
Mariano, E
Mclure, B
Melnitchouck, A
Melnitchouck, A
Meyer, T
Miao, Y
Miao, Y
Michalski, A
Mijatovic, B
Mirdavodi, H.M
Monfort, S
Mosmen, E.W
Mueller, T
Mueller, T
Mulla, D.J
Muvva, V
Mwunguzi, H
N.L., R
Nakao, H.S
Nobrega, L.H
Olfs, H
Olfs, H
Oliveira, L
Otto, R
Pack, C
Pampolino, M
Pandey, A
Pannu, C.S
Pantoja, J.L
Patil, M
Patil, M
Patil, M.B
Patil, M.B
Patil, V
Patil, V.C
Pattey, E
Percival, D
Percival, D.C
Pgowda, C.C
Phillips, S
Pitla, S
Pitla, S
Piya, N.K
Preiner, M
Pujari, B
Pujari, B
Rabello, L.M
Rahman, M.M
Raitz Persch, J
Raju, N
Rao, K
Recke, G
Reddy, K.A
Reeg, P.R
Rehman, T
Reich, R.M
Rienzi, E
Rienzi, E
Rocha, D
Rocha, D.M
Rodrigues, M
Rodrigues, M
Rossi Neto, J
Rudnick, D
Rudramuni, T
Söderström, M
Saha, S
Saleem, S.R
Sales, L
Salimath, S.B
Sanches, G.M
Sanches, G.M
Sansoulet, J
Santos, R
Sapkota, R
Schepers, J.S
Schmer, M
Schneider, D.A
Scholz, O
Schumann, A
Schumann, A.W
Schumann, A.W
Sekhon, B.S
Shankar, M
Shanwad, U
Shanwad, U
Sharma, A
Shaver, T
Sheshadri, T
Skovsen, S
Slaeem, S
Sleichter, R
Soaud, A.A
Song, X
Souza, E.G
Souza, E.G
Srinivasa Rao, C
Stanley, J.N
Stepien, P
Subba Rao, A
Sun, X
Swamy, S
Swanson, G
Syed, H.H
Sørensen, C.G
Tola, E
Trautz, D
Trautz, D
Tremblay, N
Uhrmann, F
Upadhyaya, S
Upadhyaya, S
Upadhyaya, S.K
Uribe-Opazo, M.A
V.M., A.H
Van Donk, S
Venkateswarlu, B
Viator, B.J
Viator, R.P
Walsh, O.S
Ward, N
Weiqiang, F
Westfall, D.G
Weule, M
Wienhold, B
Xu, J
Xu, J.X
Xu, K
Zaman, Q.U
Zaman, Q.U
Zaman, Q.U
Zhang, X
Zhao, C
Zhijun, M
Zhou, C
de Oliveira Costa Neto, A
de Oliveira, R.P
kaboodi, S
nabizadeh, E
Topics
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Precision Nutrient Management
Robotics and Automation with Row and Horticultural Crops
Type
Poster
Oral
Year
2012
2014
2024
Home » Topics » Results

Topics

Filter results73 paper(s) found.

1. Local And Regional Soil Clay Mapping Using Gamma Ray Spectrometry

... M. Söderström

2. Impact Of Precision Leveling On Spatial Variability Of Moisture Conservation In Arid Zones Of Karnataka

... S. Upadhyaya, P. Balakrishnan, B. Pujari, M. Patil, P. Kanannavar

3. Laser Leveling Holds a Lot Of Promise in Water Conservation and Saving in Dry Zones (Drought Prone Areas) of Karnataka

... S. Upadhyaya, P. Balakrishnan, B. Pujari, M. Patil, P. Kanannavar

4. Long Term Effects of Irrigation with Sewage Effluent on Some Soil Properties

In the arid and semiarid regions, the use of treated sewage water increases as an alternative for non-renewable resources in irrigation. The objective of this research is to identify the effect of irrigation with sewage effluent and well water for lo... M.I. Alwabel, S.A. Alsheri, A.M. Alomran

5. Application of RS, GPS & GIS in a National Monitoring System for Accurate Range Assessment

Sustainable use of rangelands requires information on vegetation cover and its changes through time, condition trend and the effect of climate as well as management practices. The main objective of this research was showing variation of vegetation para... H.P. Arzani, M.S. Azimi, S.D. kaboli, H.M. mirdavodi, M.M. Borhani, J.M. Abdollahi, M.D. farahpour

6. Natural Resources Management through Frontier Technologies - A Case Study from India

The social and economic development of the state is interlaced with our natural resources, and the manner in which they are managed and exploited.  The unplanned development and overexploitation of resources are exerting various... H.H. Gowda, K.A. Reddy, M.B. Patil, R.N. L, U. Shanwad

7. Spatial Variability Index Based On Soil Properties for Notill and Pasture Site-Specific Management in Brazil.

 Quantitative characterization of soil properties spatial variation has first been appl... R.P. De oliveira, A.C. Bernardi, V.D. Benites, L.M. Rabello, R.Y. Inamassu

8. Evaluation of Application Effect of the Laser Land Leveling Technology in Typical Areas of China

The technology of laser land leveling can improve the accuracy of land leveling and it is the important measure of improving irrigation efficiency and facilitating more uniform distribution of irrigation water. The technology is more widely used in China ... W. Guangwei, M. Zhijun, C. Liping, F. Weiqiang, D. Jianjun

9. Winter Wheat Growth Uniformity Monitoring Through Remote Sensed Images

  ... X. Song, C. Zhao, L. Chen, W. Huang, B. Cui

10. Soil Spatial Variability in the Everglades Agricultural Area in South Florida

The Everglades agricultural area is composed by histosols laying on hard limestone bedrock in south Florida. Despite the common assumption of homogeneity of these soils, agricultural practices could result in the increase of soil variability. Therefore, soil spatial variability was studied on three fields (5.5 ha each) at the Everglades Research and Education Center to compare the c... J.L. Pantoja, S.H. Daroub, O.A. Diaz

11. Spatial Econometric Approaches to Develop Site-Specific Nematode Management Strategies in Cotton Production

Root-knot nematode infestations tend to be spatially clustered within agricultural... Z. Liu, T. Griffin, T. Kirkpatrick, S. Monfort

12. Precision Tools to Evaluate Benefits of Tile Drainage in a Corn and Soybean Rotation in Iowa

... P.R. Reeg, T.M. Blackmer, P.M. Kyveryga

13. Analysis of Spatial Variability of Key Soil Attributes In North-Central Ukraine

As Ukrainian agricultural production undergoes major changes, a better understanding of the diversity of land resources is needed to optimize management.  Dealing with large fields (over 100 ha in size) with non-uniform growing conditions presents an opportunity for site-specific management of agricultural inputs. This publication describes our 2010 pilot study on the implementation of integrated mapping of apparent soil electrical conductivity and field topography to guide soil sampling... Y.I. Boyko, V.I. Adamchuk

14. Relationship of Soil Properties to Apparent Ground Conductivity in Wild Blueberry Fields

  One of the fundamental deficiencies in high value crops is the lack of detailed, up-to-date and pertinent geo-referenced soil information for site-specific crop management to improve productivity. This experiment was designed to estimate and map soil properties rapidly and reliably using an electromagnetic induction (EMI) method. Two wild bl... F.S. Khan, Q.U. Zaman, A.W. Schumann, A. Madani, D.C. Percival, A.A. Farooque, S.R. Saleem, F.S. Khan

15. Spatial Variability of Sugarcane Yields in Relation to Soil Salinity in Louisiana

High soil salinity levels have been documented to negatively impact sugarcane yields.  Tests were conducted in commercial sugarcane fields in South Louisiana in 2009-2010 to determine if elevated soil salinity ... R.P. Viator, R.M. Johnson

16. Landscape Influences on Soil Nitrogen Supply and Water Holding Capacity for Irrigated Corn

... T. Shaver, M. Schmer, S. Irmak, S. Van donk, B. Wienhold, V. Jin, A. Bereuter, D. Francis, D. Rudnick, N. Ward, L. Hendrickson, R. Ferguson, V.I. Adamchuk

17. Impact of Variable Rate Fertilization on Nutrients Losses in Surface Runoff for Wild Blueberry Fields

Wild blueberry producers apply agrochemicals uniformly without considering substantial variation in soil properties, topographic features that may affect fruit yield within field. A wild blueberry field was selected to evaluate the impact of variable rate (VR) fertilization on nutrient losses in surface runoff from steep slope to low lying areas to improve cr... S. Slaeem, Q.U. Zaman, A. Madani, A. Schumann, D. Percival, H.N. Ahmad, A.A. Farooque, F. Khan

18. Sensor Fusion on a Wild Blueberry Harvester for Fruit Yield, Plant Height and Topographic Features Mapping to Improve Crop Productivity

  Site-specific crop management can improve profitability and environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics, topographic features which may affect fruit yield. An integrated automated sensor fusion system including an ultrasonic sensor, a digital color camera, a slope sens... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang

19. Spatial Apparent Electrical Conductivity (ECa), Soil Moisture and Water Use Efficiency in Vertosol Soils

Producing high resolution maps of water use efficiency (crop yield per unit of water consumption; WUE) for precision crop management is limited by our ability to readily produce maps of soil moi... J.N. Stanley, D.A. Schneider, D.W. Lamb

20. Spatial and Temporal Variability of Corn Grain Yield as a Function of Soil Parameters, and Climate Factors

Effective site-specific management requires an understanding the influence of soil and weather on yield variability. Our objective was to examine the influence of soil, precipitation, and temperature on spatial and temporal corn grain yield variability.  The study site (10 by 250 -m in size) was located in Jaboticabal, São Paulo State, on a Rhodic Hapludox. Corn yield (planted with 0.9-m spacing) was measure... T. Mueller, J. Corá, A. Castrignanò, M. Rodrigues, E. Rienzi

21. On-The-Go pH Sensor: An Evaluation in a Kentucky Field

A commercially available on-the-go soil pH sensor measures and maps subsurface soil pH at high spatial intensities across managed landscapes.  The overall purpose of this project was to evaluate the potential for this sensor to be used in agricultural fields. The specific goals were to determine and evaluate 1) the accuracy with which this instrument can be calibrated, 2) the geospatial structure of soil pH measure... T. Mueller, E. Gianello, B. Mijatovic, E. Rienzi, M. Rodrigues

22. Measurement of Systematic Errors in Crop Prediction

Precision agriculture typically attempts to answer grower questions using an increasingly more fine-grained analysis.  However, some entities, such as cooperatives, can have an interest in answers that are spatially course-grained, such as obtaining an estimate of the overall crop production within a season.  Errors in factors that most influence fine-grained predictions, such as soil quality, may have a smaller impact on overall yield forecasts since their effect is likely to ... A.M. Denton, E.W. Mosmen, J.X. Xu

23. 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

24. 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

25. 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

26. 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

27. 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

28. 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

29. 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

30. 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

31. 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

32. 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

33. 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

34. 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

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

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

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

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

37. 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

38. Determination of Optimal Number of Management Zones

... A. Melnitchouck

39. 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

40. 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

41. 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

42. 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

43. 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

44. 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

45. 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

46. 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

47. 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

48. 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

49. 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

50. 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

51. 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

52. 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.

53. 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

54. 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

55. 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

56. 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

57. 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

58. 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

59. 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

60. 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

61. 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

62. 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

63. 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

64. 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

65. 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

66. 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

67. 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

68. 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

69. 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

70. 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

71. 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

72. 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

73. SurePoint Ag Systems - Sponsor Presentation

... B. Downing