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Farm Animals Health and Welfare Monitoring
Drainage Optimization and Variable Rate Irrigation
Precision Nutrient Management
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Authors
Abbas, F
Bazzi, C.L
Bean, G
Beitz, T
Belmont, K
Beneduzzi, H.M
Benjamin, M
Berzins, R
Betzek, N.M
Bolton, C
Bourouah, M
Büchele, D
Camberato, J
Cardoso, G.M
Carneiro Amado, T.J
Carter, P
Castro, S.G
Charvat, K
Cheema, S.J
Cho, W
Chok, S.E
Chudy, T
Chung, S
Constas, K
Corassa, G.M
D.C, H
D.C, H
Dr., N
Dr., N
Dr., S
Drzazga, T
Duarte de Val, M
Dworak, V
Elvir Flores, A
Esau, T
Farooque, A.A
Ferguson, R.B
Fernandez, F.G
Franco, H.C
Franzen, D.W
Friell, J
Gacek, E.S
Gamble, A
Gan, H
Gavioli, A
Gebbers, R
Gebert, F.H
Gornushkin, I
Gozdowski, D
Gozdowski, D
Grafton, M.C
Grewal, K
Gunther, D
Gutiérrez, V
Hammond, K
Hansen, N
Hansen, N
Heggemann, T
Heil, K
Hejl, R
Hopkins, B
Hopkins, B
Horbe, T
Ingram, B
Islam, M
Jackson, C
Jensen, R
Jensen, R
Jiang, J
Kang, C
Kepka, M
Kerry, R
Kerry, R
Kersebaum, C
Kim, D
Kim, H
Kitchen, N.R
Kombali, G
Kumar R, M
Kumar R, M
Kumke, M
Laboski, C
Lacerda, L
Lamb, D.W
Langovskis, D
Lavagnino, M
Leenen, M
Lena, B.P
Leszczyńska, E
Lu, Y
Magalhães, P.S
Mahns, B
Mailwald, M
Maiwald, M
Marjerison, R
Marshall, J
McClintick-Chess, J
McIntyre, J
McLellan, E
Melkonian, J
Mhlongo, N
Miao, Y
Miles, R.J
Mizgirev, A
Morata, G
Morlin, F
Morris, D
Musil, M
Nadagouda, D
Nafziger, E
Noorasma, S
Ortega, R
Ortiz, B.V
Ostermann, M
PATIL, B
Prabhudeva, D
Prasad, R
Pätzold, S
Ransom, C
Riebe, D
Rühlmann, J
Rühlmann, M
Samborski, S.M
Samborski, S.M
Sanches, G.M
Sawyer, J
Scharf, P
Scheithauer, H
Schenatto, K
Schill, S
Schmid, T
Schwalbert, R
Sela, S
Shanahan, J
Sharma, V
Shumate, S
Silva, A.E
Son, J
Souza, E.G
Straw, C
Stępień, M
Stępień, M
Sumpf, B
Swoboda, K
T, S
T, S
Thimmegowda, M
Thompson, C
Turner, I
Van Langevelde, F
Wagner, P
Wallor, E
Walsh, O.S
Walsh, O.S
Walsh, O.S
Wang, Y
Watkins, E
Welp, G
Weltzien, C
White, M
Woolley, E
Yoder, J
Young, J
Yule, I.J
Yun, H
Zadrazil, F
de Boer, W.F
de knegt, H
giriyappa, M
giriyappa, M
van-Es, H
Topics
Precision Nutrient Management
Drainage Optimization and Variable Rate Irrigation
Farm Animals Health and Welfare Monitoring
Type
Poster
Oral
Year
2016
2022
2024
Home » Topics » Results

Topics

Filter results25 paper(s) found.

1. Studies on Soil Spatial Variability and Its Impact on Cane Yield Under Precision Nutrient Management System

In present investigation an attempt was made to quantify the soil variability of 30 grids of 10 m x 10 m dimension at research farm of Nandi Sahakari Sakkare Karkhane (NSSK), Krishna Nagar, District. Bijapur. Each grid (10 m x 10 m) showed variation with available nitrogen as low as 140 kg ha-1 to as high as 245 kg/ha with a range of 105 kg/ha, phosphorus as low as 53 kg P2O5 ha-1 and as high as 89.3 kg P2O5 ha-1 wit... M. Kumar R, M. Kumar R, D. Nadagouda

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

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

3. Winter Wheat Genotype Effect on Canopy Reflectance: Implications for Using NDVI for In-season Nitrogen Topdressing Recommendations

Active optical sensors (AOSs) measure crop reflectance at specific wavelengths and calculate vegetation indices (VIs) that are used to prescribe variable N fertilization. Visual observations of winter wheat (Triticum aestivum L.) plant greenness and density suggest that VI values may be genotype specific. Some sensor systems use correction coefficients to eliminate the effect of genotype on VI values. This study was conducted to assess the effects of winter wheat cultivars and growing conditi... O.S. Walsh, S.M. Samborski, M. Stępień, D. Gozdowski, D.W. Lamb, E.S. Gacek, T. Drzazga

4. On-Farm Evaluation of an Active Optical Sensor Performance for Variable Nitrogen Application in Winter Wheat

Winter wheat (Triticum aestivum L.) represents almost 50% of total cereal production in the European Union, accounting for approximately 25% of total mineral nitrogen (N) fertilizer applied to all crops. Currently, several active optical sensor (AOS) based systems for optimizing variable N fertilization are commercially available for a variety of crops, including wheat. To ensure successful adoption of these systems, definitive measurable benefits must be demonstrated. Nitrogen management str... O.S. Walsh, S.M. Samborski, D. Gozdowski, M. Stępień, E. Leszczyńska

5. UAV-based Crop Scouting for Precision Nutrient Management

Precision agriculture – is one of the most substantial markets for the Unmanned Aerial Vehicles (UAVs). Mounted on the UAVs, sensors and cameras enable rapid screening of large numbers of experimental plots to identify crop growth habits that contribute to final yield and quality in a variety of environments. Wheat is one of the Idaho’s most important cereal crops grown in 42 of 44 Idaho counties. We are working on establishing a UAV-based methodology for in-season prediction of w... O.S. Walsh, K. Belmont, J. Mcclintick-chess, J. Marshall, C. Jackson, C. Thompson, K. Swoboda

6. Accuracy of Differential Rate Application Technology for Aerial Spreading of Granular Fertiliser Within New Zealand

Aerial topdressing of granular fertilizer is common practice on New Zealand hill country farms because of the challenging topography. Ravensdown Limited is a New Zealand fertilizer manufacturer, supplier and applicator, who are funding research and development of differential rate application from aircraft. The motivation for utilising this technology is to improve the accuracy of fertilizer application and fulfil the variable nutrient requirements of hill country farms.  The capability ... I.J. Yule, S.E. Chok, M.C. Grafton, M. White

7. Delineation of Site-specific Management Zones Using Spatial Principal Components and Cluster Analysis

The delineation of site-specific management zones (MZs) can enable economic use of precision agriculture for more producers. In this process, many variables, including chemical and physical (besides yield data) variables, can be used. After selecting variables, a cluster algorithm like fuzzy c-means is usually applied to define the classes. Selection of variables comprise a difficult issue in cluster analysis because these will often influence cluster determination. The goal of this study was... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto, H. Beneduzzi

8. Using the Adapt-N Model to Inform Policies Promoting the Sustainability of US Maize Production

Maize (Zea mays L.) production accounts for the largest share of crop land area in the U.S. It is the largest consumer of nitrogen (N) fertilizers but has low N Recovery Efficiency (NRE, the proportion of applied N taken up by the crop). This has resulted in well-documented environmental problems and social costs associated with high reactive N losses associated with maize production. There is a potential to reduce these costs through precision management, i.e., better application timing, use... S. Sela, H. Van-es, E. Mclellan, J. Melkonian, R. Marjerison , K. Constas

9. Spatial Variability of Soil Nutrients and Precision Nutrient Management for Targeted Yield Levels of Groundnut (Arachis Hypogaea L.)

A field study was conducted during rabi / summer 2014-15 to know the spatial variability and precision nutrient management practices on targeted yield levels of groundnut. The experimental field has been delineated into 36 grids of 9 m x 9 m using geospatial technology. Soil samples from 0-15 cm were collected and analysed. Spatial variability exists for available nitrogen, phosphorous and potassium and they varied from 99 to 197 kg N, 12.1 to 64.0 kg P2O5 and 1... H. D.c, S. Dr., N. Dr., M. Giriyappa, S. T

10. Precision Nutrient Management System Based on Ion and Crop Growth Sensing

Automated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs)... W. Cho, D. Kim, C. Kang, H. Kim, J. Son, S. Chung, J. Jiang, H. Yun

11. Precision Nutrient Management Through Drip Irrigation in Aerobic Rice

A field experiment was conducted during kharif 2015 to asses the spatial variability and precision nutrient management through drip irrigation in aerobic rice at ZARS, GKVK, Bangalore. The experimental field has been delineated into 48 grids of 4.5 m x 4.5 m using geospatial technology. Soil samples from 0-15 cm depth were collected and analysed. There was spatial variability for available nitrogen (154 to 277 kg ha-1), phosphorous (45 to 152 kg ha-1) and potass... N. Dr., S. T, M. Giriyappa, H. D.c, B. Patil, D. Prabhudeva, G. Kombali, S. Noorasma, M. Thimmegowda

12. Integrated Approach to Site-specific Soil Fertility Management

In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a funda­mental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil f... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor

13. Use of Crop Canopy Reflectance Sensor in Management of Nitrogen Fertilization in Sugarcane in Brazil

Given the difficulty to determine N status in soil testing and lack of crop parameters to recommend N for sugarcane in Brazil raise the necessity of identify new methods to find crop requirement to improve the N use efficiency. Crop canopy sensor, such as those used to measure indirectly chlorophyll content as N status indicator, can be used to monitor crop nutritional demand. The objective of this experiment was to assess the nutritional status of the sugarcane fertilized with different nitr... S.G. Castro, G.M. Sanches, G.M. Cardoso, A.E. Silva, H.C. Franco, P.S. Magalhães

14. Adjustment of Corn Population and Nitrogen Fertilization Based on Management Zones

The main objective of this study was to adjust the corn population and nitrogen fertilization according to management zones, based on past grain yield maps (seven of soybean and three of corn) and soil electrical conductivity. The study was carried out in Não-Me-Toque, Rio Grande do Sul, Brazil, and it was conducted in a factorial strip blocks with 3 repetitions in each management zone, being the treatments: corn populations (56000, 64000, 72000, 80000 and 88000 plants ha-1)... R. Schwalbert, T.J. Carneiro Amado, T. Horbe, G.M. Corassa, F.H. Gebert

15. Towards Precision Microbiology

In the recent years, the use of organic matter (OM) and microorganisms is increasing beyond organic agriculture, into conventional horticultural systems, in order to achieve high yields and quality through a more sustainable soil management. Thus, Integrated Nutrient Management (INM), that includes the use of diagnostic tools, high quality OM, microbial inoculants, highly-efficient fertilizer, and site-specific management in gaining space in intensive production systems. Precision m... V. Gutiérrez, R. Ortega

16. SmartAgriHubs FIE20 - Groundwater and Meteo Sensors and Earth Observation for Precision Agriculture

The solution developed under the SmartAgriHubs project in the scope of the Flagship Innovation Experiment FIE20 Groundwater and meteo sensors is an expert system to support farmers in decision-making process and planning process of field interventions. This FIE20 solution integrates various data sources and different analytical processes in a complete system and provides users an easy-to-use web map application as a common user interface. The FIE20 system integrates components developed durin... K. Charvat, M. Kepka, R. Berzins, F. Zadrazil, D. Langovskis, M. Musil

17. Soil Moisture Variability on Golf Course Fairways Across the United States: an Opportunity for Water Conservation with Precision Irrigation

Fairways account for an average of 11.3 irrigated hectares on each of the 15,000+ golf courses in the US. Annual median water use per hectare on fairways is between ~2,800,000 and 14,000,000 liters, depending on the region. Conventional fairway irrigation relies on visual observation of the turfgrass, followed by secondary considerations of short-term weather forecasts, which oftentimes lead to “blanket” applications to the entire area. The concept of precision irrigation is a str... C. Straw, C. Bolton, J. Young, R. Hejl, J. Friell, E. Watkins

18. Can Topographic Indices Be Used for Irrigation Management Zone Delineation

Soil water movement is affected by soil physical properties and field terrain changes. The identification of within-field areas prone to excess or deficit of soil moisture could support the implementation of variable rate irrigation and adoption of irrigation scheduling strategies. This study evaluated the use of the topographic wetness index (TWI) and topographic position index (TPI) to understand and explain within-field soil moisture variability. Volumetric water content (VWC) collected in... B.V. Ortiz, B.P. Lena, F. Morlin , G. Morata, M. Duarte De Val, R. Prasad, A. Gamble

19. Investigation of Automated Analysis of Snowmelt from Time-series Sentinel 2 Imagery to Inform Spatial Patterns of Spring Soil Moisture in the American Mountain West

Variable rate irrigation of crops is a promising approach for saving water whilst maintaining crop yields in the semi-arid American Mountain West – much of which is currently experiencing a mega drought. The first step in determining irrigation zones involves characterizing the patterns of spatial variation in soil moisture and determining if these are relatively stable temporally in relation to topographic features and soil texture. Characterizing variable rate irrigation zones is usua... I. Turner, R. Kerry, R. Jensen, E. Woolley, N. Hansen, B. Hopkins

20. Establishing the First Soil Water Characteristics Curve for the Soils of Prince Edward Island, Canada

Soil water characteristics curve (SWCC), for Prince Edward Island (PEI), is much more needed currently for the sustainable production of agriculture yields. It will not only fulfil the requirements of the province’s farmers for irrigation scheduling but also help the government to decide about permitting the use of groundwater for supplemental irrigation on the island.  A soil water characteristics curve in PEI does not exist to support precision agriculture practices. Precision ir... S.J. Cheema, A.A. Farooque, F. Abbas, T. Esau, K. Grewal

21. Evaluating the Potential of Integrated Precision Irrigation and Nitrogen Management for Corn in Minnesota

The environmental impact of irrigated agriculture on ground and surface water resources in Minnesota is of major concern. Previous studies have focused on either precision irrigation or precision nitrogen (N) management, with very limited studies on the integrated precision management of irrigation and N fertilizers, especially in Minnesota. The Dualex Scientific sensor is a leaf fluorescence sensor that has been used to diagnose crop&nbs... A. Elvir Flores, Y. Miao, V. Sharma, L. Lacerda

22. Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management

The Western United States is currently experiencing a “Mega Drought”. This makes efficient water use more important than ever. Turfgrass is a major vegetation type in urban areas and performs many ecosystem services such as cooling through evapotranspiration, fixing carbon from the atmosphere and reducing wild-fire risk. There are now more acres of irrigated turfgrass (>40 million) in the USA than irrigated corn, wheat and fruit trees combined (Milesi et al., 2005). It has been... R. Kerry, S. Shumate, B. Ingram, K. Hammond, D. Gunther, R. Jensen, S. Schill, N. Hansen, B. Hopkins

23. Automatic Body Condition Score Classification System for Individual Beef Cattle Using Computer Vision

Body condition scoring (BCS) is a widely used parameter for assessing the utilization of energy reserves in the fat and muscle of cattle. It fulfills the needs of animal welfare and precision livestock farming by enabling effective monitoring of individual animals. It serves as a crucial parameter for optimizing nutrition, reproductive performance, overall health, and economic outcomes in beef cattle. The precise and consistent assessment of BCS relies on personal experience using visuals tha... M. Islam, J. Yoder, H. Gan

24. 3D Computer Vision with a Spatial-temporal Neural Network for Lameness Detection of Sows

The lameness of sows is one of the biggest concerns for swine producers, which can lead to considerable economic losses due to reduced productivity and welfare. There is a real need for early detection of lameness in sows to enable timely intervention and minimize loss. Currently, lame detection relies on visual observation and locomotion scoring of sows, which is subjective, labor-intensive, and difficult to conduct for large groups of animals within a short time. This study presents 3D comp... Y. Wang, Y. Lu, D. Morris, M. Benjamin, M. Lavagnino, J. Mcintyre

25. Lameness Detection in Dairy Cattle Using GPS and Accelerometers Wearable Sensors

Lameness significantly impacts cow health and welfare on dairy farms, yet identifying lamecows remains challenging. Wearable sensors like GPS and accelerometers show promise for automated lameness detection, but their effectiveness outdoors is still unclear. Therefore, there are gaps in understanding their applicability and the necessary features for outdoor settings. Additionally, it is uncertain whether environmental factors, such as temperature and time of day, influence their the model pe... N. Mhlongo, H. De Knegt, W.F. De Boer, F. Van Langevelde