Proceedings

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Harper, J
Burke, C.R
Taylor, M.J
Tsoulias, N
Boini, A
Al Amin, A
Barlage, M
Taylor, A
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Authors
Dela Rue, B.T
Kamphuis, C
Jago, J.G
Burke, C.R
Dennis, S.J
Clarke-Hill, W
Taylor, A
Dynes, R
O'Neill, K
Jowett, T
Mahoney, W
Barlage, M
Gochis, D
Chen, F
McEntee, P
Bennett, S
Trotter, M
Belford, R
Harper, J
Webber III, C.L
Taylor, M.J
Shrefler, J.W
Bresilla, K
Manfrini, L
Boini, A
Perulli, G
Morandi, B
Grappadelli, L.C
King, W
Dynes, R
Laurenson, S
Zydenbos, S
MacAuliffe, R
Taylor, A
Manning, M
Roberts, A
White, M
Tsoulias, N
Paraforos, D
Brandes, N
Fountas, S
Zude-Sasse, M
Al Amin, A
Lowenberg‑DeBoer, J
Franklin, K
Behrendt, K
Al Amin, A
Lowenberg-DeBoer, J
Franklin, K.F
Dickin, E
Monaghan, J
Behrendt, K
Topics
Precision Dairy and Livestock Management
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Site-Specific Pasture Management
Precision Horticulture
Robotics, Guidance and Automation
Profitability and Success Stories in Precision Agriculture
Type
Poster
Oral
Year
2012
2014
2016
2008
2018
2022
2024
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Filter results10 paper(s) found.

1. Field Evaluation of Automated Estrus Detection Systems - Meeting Farmers' Expectation

Automated systems for oestrus detection are commonly marketed as a suitable, or in some cases, a higher performing alternative to visual observation. Farmers, particularly those with larger herds relying on less experienced staff, view the perceived benefits of automated systems as both economic and physical, with expectations of improved oestrus detection efficiency with lower labour input. There is little evidence-based information available on the field performance of these systems to... B.T. Dela Rue, C. Kamphuis, J.G. Jago, C.R. Burke

2. Estimating Spatial Variation In Annual Pasture Yield

Yield mapping is an essential tool for precision management of arable crops. Crop yields can be measured once, at harvest, automatically by the harvesting machinery, and be used to inform a wide range of activities. However yield mapping has had minimal adoption by pastoral farmers.   Yield mapping is also a potentially valuable tool for precision management of pastures. However it is difficult to practically map yields on pastures, as they... S.J. Dennis, W. Clarke-hill, A. Taylor, R. Dynes, K. O'neill, T. Jowett

3. Developing A High-Resolution Land Data Assimilation And Forecast System For Agricultural Decision Support

Technological advances in weather and climate forecasting and land surface and hydrology modeling have led to an increased ability to predict soil temperature, and soil moisture, near-surface weather elements. These variables are critical building blocks to the development of high-level agriculture-specific models such as pest models and crop yield models. The National Center for Atmospheric Research (NCAR) has developed a high-resolution agriculture-oriented land-data assimilation... W. Mahoney, M. Barlage, D. Gochis, F. Chen

4. Mapping Spatial Production Stability in Integrated Crop and Pasture Systems: Towards Zonal Management That Accounts for Both Yield and Livestock-landscape Interactions.

Precision farming technologies are now widely applied within Australian cropping systems. However, the use of spatial monitoring technologies to investigate livestock and pasture interactions in mixed farming systems remains largely unexplored. Spatio-temporal patterns of grain yield and pasture biomass production were monitored over a four-year period on two Australian mixed farms, one in the south-west of Western Australia and the other in south-east Australia. A production stability index was... P. Mcentee, S. Bennett, M. Trotter, R. Belford, J. Harper

5. Precision Placement of Corn Gluten Meal for Weed Control in Organic Vegetable Production

Organic vegetable producers rank weeds as one of their most troublesome, time consuming, and costly production problems. As a result of the limited number of organically approved weed control herbicides, the precision placement of these materials increases their potential usefulness in organic production systems. As a non-selective preemergence or preplant-incorporated herbicide, corn gluten meal (CGM) inhibits root development; decreases shoot length, and reduces plant survival. The development... C.L. Webber Iii, M.J. Taylor, J.W. Shrefler

6. Using Deep Learning - Convolutional Naural Networks (CNNS) for Real-Time Fruit Detection in the Tree

Image/video processing for fruit detection in the tree using hard-coded feature extraction algorithms have shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for specific... K. Bresilla, L. Manfrini, A. Boini, G. Perulli, B. Morandi, L.C. Grappadelli

7. Through the Grass Ceiling: Using Multiple Data Sources on Intra-Field Variability to Reset Expectations of Pasture Production and Farm Profitability

Intra-field variability has received much attention in arable and horticultural contexts. It has resulted in increased profitability as well as reduced environmental footprint. However, in a pastoral context, the value of understanding intra-field variability has not been widely appreciated. In this programme, we used available technologies to develop multiple data layers on multiple fields within a dairy farm. This farm was selected as it was already performing at a high level, with well-developed... W. King, R. Dynes, S. Laurenson, S. Zydenbos, R. Macauliffe, A. Taylor, M. Manning, A. Roberts, M. White

8. Calculating the Water Deficit of Apple Orchard by Means of Spatially Resolved Approach

In semi-humid climate, spatially resolved analysis of water deficit was carried out in apple orchard (Malus x domestica 'Pinova'). The meteorological data were recorded daily by a weather station. The apparent soil electrical conductivity (ECa) was measured at field capacity, and twenty soil samples in 30 cm were gathered for texture, bulk density, and gravimetric soil water content analyses. Furthermore, ten trees were defoliated in different ECa regions in order to estimate the leaf... N. Tsoulias, D. Paraforos, N. Brandes, S. Fountas, M. Zude-sasse

9. Economics of Field Size for Autonomous Crop Machines

Field size constrains spatial and temporal management of agriculture with implications for farm profitability, field biodiversity and environmental performance. Large, conventional equipment struggles to farm small, irregularly shaped fields efficiently. The study hypothesized that autonomous crop machines would make it possible to farm small non-rectangular fields profitably, thereby preserving field biodiversity and other environmental benefits. Using the experience of the Hands Free Hectare... A. Al Amin, J. Lowenberg‑deboer, K. Franklin, K. Behrendt

10. Profitability of Regenerative Cropping with Autonomous Machines: an Ex-ante Assessment of a British Crop-livestock Farm

Farmers, agroecological innovators and research have suggested mixed cropping as a way to promote soil health. Mixing areas of different crops in the same field is another form of precision agriculture's spatial and temporal management. The simplest form of mixed cropping is strip cropping. In conventional mechanized farming use of mixed cropping practices (i.e., strip cropping, pixel cropping) is limited by labour availability, rising wage rates, and management complexity. Regenerative agriculture... A. Al Amin, J. Lowenberg-deboer, K.F. Franklin, E. Dickin, J. Monaghan, K. Behrendt