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2024
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Authors
Abban-Baidoo, E
Antunes de Almeida, L.F
Archontoulis, S
Arnold, S
Balboa, G
Basran, P.S
Bathke, K.J
Bedwell, E
Behrendt, K
Boersma, S
Boote, K
Boyer, W
Buckmaster, D
Cambouris, A
Capper, J
Carcedo, A
Cesario Pinto, J
Choudhury, S.D
Ciampitti, I
Corassa, G
Duarte, P.R
Duchemin, M
Enger, B.D
Fenech, A
Feng, G
Fernández, F
Folle, S
Ford, L
Fountain, J
Francisco, E
Fulton, J.P
Gan, H
Ge, Y
Grassini, P
Harris, E.W
Hartschuh, J.M
Hefley, T
Hintz, G.D
Hoogenboom, G
Horbe, T
Huang, Y
Islam, M
Javed, B
Karam, A
Kopanja, M
Kukal, S
Lacerda, L
Longchamps, L
Lu, J
Luck, J.D
Maestrini, B
Maktabi, S
McAvoy, T
Miao, Y
Mieno, T
Mimić, G
Mizuta, K
Mueller, N
Negrini, R.P
Ortiz, B.V
Paccioretti, P
Pathak, H
Pilcon, C
Pott, L.P
Prasad, V
Pronk, A
Puntel, L
Ransom, C.J
Schuenemann, G.M
Schwalbert, R.A
Shearer, S.A
Snider, J
Sysskind, M
Thompson, L
Van Oort, P
Vellidis, G
Wang, D.R
Warren, C.J
Yoder, J
Yu, Z
Zhen, X
de Oliveira, M.F
van Evert, F
Topics
Digital Agriculture Solutions for Soil Health and Water Quality
Farm Animals Health and Welfare Monitoring
On Farm Experimentation with Site-Specific Technologies
Precision Agriculture and Global Food Security
In-Season Nitrogen Management
Precision Dairy and Livestock Management
Weather and Models for Precision Agriculture
Decision Support Systems
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Demonstration
Type
Oral
Year
2024
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Year

Filter results17 paper(s) found.

1. A Digital Twin for Arable Crops and for Grass

There is an opportunity to use process-based cropping systems models (CSMs) to support tactical farm management decisions, by monitoring the status of the farm, by predicting what will happen in the next few weeks, and by exploring scenarios. In practice, the responses of a CSM will deviate more and more from reality as time progresses because the model is an abstraction of the real system and only approximates the responses of the real system. This limitation may be overcome by using the CSM... F. Van evert, P. Van oort, B. Maestrini, A. Pronk, S. Boersma, M. Kopanja, G. Mimić

2. Advancing Adaptive Agricultural Strategies: Unraveling Impacts of Climate Change and Soils on Corn Productivity Using APSIM

With unprecedented challenges to achieve sustainable crop productivity under climate change and dynamic soil conditions, adaptive management strategies are required for optimizing cropping systems. Using sensors, cropping systems can be continuously monitored and the data collected by them can be analyzed for making informed adaptive management decisions to enhance productivity and environmental sustainability. But sensors can only tell the past and decisions bring implications into the ... H. Pathak, C.J. Warren, D. Buckmaster, D.R. Wang

3. Assessing Soybean Water Stress Patterns and ENSO Occurrence in Southern Brazil: an in Silico Approach

Water stress (WS) is one of the most important abiotic stresses worldwide, responsible for crop yield penalties and impacting food supply. The frequency and intensity of weather stresses are relevant to delimitating agricultural regions. In addition, El Nino Southern Oscillation (ENSO) has been employed to forecast the occurrence of seasonal WS. Lastly, planting date and cultivar maturity selection are key management strategies for boosting soybean (Glycine max (L.) Merr.) y... A. Carcedo, L.F. Antunes de almeida, T. Horbe, G. Corassa, L.P. Pott, I. Ciampitti, G.D. Hintz, T. Hefley, R.A. Schwalbert, V. Prasad

4. 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

5. Crop Modeling-based Framework to Explore Region-specific Impact of Nitrogen Fertilizer Management on Productivity and Environmental Footprint

To maintain current crop production while reducing negative environmental impacts, improved understanding of the relative impact of the 4Rs for nitrogen (N) management (rate, time, place, and source) for a given geo-agroecosystem are needed and can play a critical role in driving policy, recommendations, and local practices. However, the timeframe and cost required to assess and characterize the impact of N rate and timing over years and weather conditions through field experiments is prohibi... L. Thompson, S. Archontoulis, P. Grassini, L. Puntel, T. Mieno

6. Drone Use Extension and Demonstrations Support Management of Riparian Areas, Grazing Land, and Water Quality

Agricultural and natural resource managers have explored a variety of ways in which drones might be used to aid in decision-making. One of the most useful ways may be the production of orthorectified aerial photography which can have very high spatial and temporal resolution. Such photography offers new opportunities for visualizing and measuring features on the landscape. Not just measuring the two-dimensional characteristics of landscape features, but also measuring three-dimensional charac... W. Boyer

7. Effect of Terrain and Soil Properties on the Effectiveness of Crop-model Based Variable Rate Nitrogen in Corn

Growers may be reluctant to adopt variable rate nitrogen (VRN) management because of potential loss in profit and yield. This study assessed the influence of terrain attributes and soil characteristics on the effectiveness of crop-model-based variable rate nitrogen (N) for corn. To evaluate the effectiveness of the VRN methods, yield, total N rate, and N use efficiency (NUE) were compared with the grower’s management. As a crop-model-based recommendation tool, Adapt-N was used. Producti... L. Puntel, L. Thompson, G. Balboa, T. Mieno, P. Paccioretti

8. Enhancing Nutrient-related Stress Detection: High Throughput Phenotyping and Image Analysis for Improved Precision

In the 21-century agriculture has the unique responsibility to provide food, fuel, fiber and feed for the growing population under the stress of climate change and diminishing natural resources. A feat that will take considerable change to the sustainability of such practices. One of which is the idea of assessing phenotypic expression of complex traits in response to environmental factors. This idea elevates the use of phenotyping to quantitatively monitor stress manifestation.  ... K.J. Bathke, Y. Ge, S.D. Choudhury, J.D. Luck

9. Evaluating the Potential of In-season Spatial Prediction of Corn Yield and Responses to Nitrogen by Combining Crop Growth Modeling, Satellite Remote Sensing and Machine Learning

Nitrogen (N) is a critical yield-limiting factor for corn (Zea mays L.). However, over-application of N fertilizers is a common problem in the US Midwest, leading to many environmental problems. It is crucial to develop efficient precision N management (PNM) strategies to improve corn N management. Different PNM strategies have been developed using proximal and remote sensing, crop growth modeling and machine learning. These strategies have both advantages and disadvantages. There is... X. Zhen, Y. Miao, K. Mizuta, S. Folle, J. Lu, R.P. Negrini, G. Feng, Y. Huang

10. Exploring the Use of a Model-based Nitrogen Recommendation Tool and Vegetation Indices for In-season Corn Nitrogen Management in Alabama

Efficient nitrogen (N) management is critical for sustainable agriculture. Crop N needs and uptake changes within a field and it is annually influenced by weather conditions. Hence, site-specific in-season N application strategies are important to achieve optimum corn yield while minimizing negative impacts on the environment. This study evaluates the Adapt-N tool for in-season variable rate N application at two farmers’ fields in Alabama. The Adapt-N tool integrates soil and crop-based... P.R. Duarte, B.V. Ortiz, E. Abban-baidoo, E. Francisco, M.F. De oliveira

11. Have Your Steak and Eat It Too: Precision Beef Management to Simultaneously Reduce Ech4 and Increase Profit

Achieving carbon net zero is a clear priority, with beef farmers under significant scrutiny from food system stakeholders. Tools are available to assess greenhouse gas emissions (GHGe), yet adoption is low, and producers are not currently financially incentivised to change management practices. This study used cattle performance data from a commercial beef operation to model the optimal age and weight at slaughter to maximise profit and reduce enteric methane (eCH4) emissions at th... K. Behrendt, J. Capper, L. Ford, E.W. Harris

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

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

13. On-farm Evaluation of a Satellite Remote Sensing-based Precision Nitrogen Management Strategy

Improper management of nitrogen (N) fertilizers in the cropping systems of the U.S. Midwest has resulted in significant N leaching into the Mississippi River Basin that flows to the Gulf of Mexico. The majority of the U.S. Midwest states need to develop a plan for a nutrient loss reduction strategy to decrease N and phosphorous loadings into waters and the Gulf of Mexico by 45% by 2050. In Minnesota, high nitrate concentration and loads have not been significantly reduced in surface and groun... J. Lu, Y. Miao, C.J. Ransom, F. Fernández

14. Predicting the Spatial Distribution of Aflatoxin Hotspots in Peanut Fields Using DSSAT CSM-CROPGRO-PEANUT-AFLATOXIN

Aflatoxin contamination in peanuts (Arachis hypogaea L.) is a persistent concern due to its detrimental effects on both profitability and public health. Several plant stress-inducing factors, including high soil temperatures and low soil moisture, have been associated with aflatoxin contamination levels. Understanding the correlation between stress-inducing factors and contamination levels is essential for implementing effective management strategies. This study uses the DSSAT CSM-CR... S. Maktabi, G. Vellidis, G. Hoogenboom, K. Boote, C. Pilcon, J. Fountain, M. Sysskind, S. Kukal

15. Relationship of Activity and Temperature of Dairy Calves As Measured by Indwelling Rumen Boluses

Circadian rhythm of body temperature is naturally occurring in animals with a lower temperature at dawn and higher at dusk. In the past, this work was manually completed by a person using rectal temperature with temperature recorded every 2 or 3 hours. Rumen indwelling boluses allow for continuous temperature monitoring without human intervention. Human intervention can increase animal stress which can elevate temperature. Current literature indicates that the animal’s body temperature ... J.M. Hartschuh, J.P. Fulton, S.A. Shearer, B.D. Enger, G.M. Schuenemann

16. Site-specific Evaluation of Sensor-based Winter Wheat Nitrogen Tools Via On-farm Research

Crop producers face the challenge of optimizing high yields and nitrogen use efficiency (NUE) in their agricultural practices. Enhancing NUE has been demonstrated by adopting digital agricultural technologies for site-specific nitrogen (N) management, such as remote-sensing based N recommendations for winter wheat. However, winter wheat fields are often uniformly fertilized, disregarding the inherent variability within the fields. Thus, an on-farm evaluation of sensor-based N tools is needed ... J. Cesario pinto, L. Thompson, N. Mueller, T. Mieno, L. Puntel, P. Paccioretti, G. Balboa

17. Using Remote Sensing to Benchmark Crop Coefficient Curves of Sweet Corn Grown in the Southeastern United States

Irrigation is responsible for over 75% of global freshwater use, making it the largest consumer of the world’s freshwater resources. With freshwater scarcity increasing worldwide, increased efficient irrigation water use is necessary. Smart irrigation is described as ‘the linking of technology and fundamental knowledge of crop physiology to significantly increase irrigation water use efficiency'. Irrigation scheduling tools such as smartphone applications have become... E. Bedwell, L. Lacerda, T. Mcavoy, B.V. Ortiz, J. Snider, G. Vellidis, Z. Yu