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Pullanagari, R
Perez-Ruiz, M
Pieger, K
He, Z
Hu, Y
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Authors
Pullanagari, R
Yule, I
Tuohy, M
Hedley, M
King, W
Dynes, R
Wang, X
Hu, Y
Yi, Z
Scholz, O
Uhrmann, F
Gerth, S
Pieger, K
Claußen, J
Perez-Ruiz, M
Apolo-Apolo, E
Egea, G
Martinez-Guanter, J
Marin-Barrero, C
He, Z
Manoj, K
Zhang, Q
Kshetri, S
Topics
Proximal Sensing in Precision Agriculture
Profitability, Sustainability and Adoption
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2014
2018
2022
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Filter results5 paper(s) found.

1. Proximal Sensing Tools to Estimate Pasture Quality Parameters.

To date systems for estimating pasture quality have relied on destructive sampling with measurement completed in a laboratory which was very time consuming and expensive. Results were often not received until after the pasture was grazed which defeated the point of the measurement, as farmers required the information to make decisions about grazing strategies to effectively... R. Pullanagari, I. Yule, M. Tuohy, M. Hedley, W. King, . Dynes

2. World Patent Map Analysis Of Mechanization Technologies Relatitng To Rice Production

Patents comprise a unique source for technological knowledge. They are considered to be a good proxy for invention skills, R&D activities and for the scope of technological innovation of countries, regions, sectors and firms. Rice is one of the main field crops. The research focuses on patent mechanization technologies of soil working, planting and harvesting of rice production. Based on DWPI patent database and TI patent analysis software. The temporal examination by publication year... X. Wang, Y. Hu, Z. Yi

3. A Comparison of Three-Dimensional Data Acquisition Methods for Phenotyping Applications

Currently Phenotyping is primarily performed using two-dimensional imaging techniques. While this yields interesting data about a plant, a lot of information is lost using regular cameras. Since a plant is three-dimensional, the use of dedicated 3D-imaging sensors provides a much more complete insight into the phenotype of the plant. Different methods for 3D-data acquisition are available, each with their inherent advantages and disadvantages. These have to be addressed depending on the particular... O. Scholz, F. Uhrmann, S. Gerth, K. Pieger, J. Claußen

4. Feasibility of Estimating the Leaf Area Index of Maize Traits with Hemispherical Images Captured from Unmanned Aerial Vehicles

Feeding a global population of 9.1 billion in 2050 will require food production to be increased by approximately 60%. In this context, plant breeders are demanding more effective and efficient field-based phenotyping methods to accelerate the development of more productive cultivars under contrasting environmental constraints. The leaf area index (LAI) is a dimensionless biophysical parameter of great interest to maize breeders since it is directly related to crop productivity. The LAI is defined... M. Perez-ruiz, E. Apolo-apolo, G. Egea, J. Martinez-guanter, C. Marin-barrero

5. Real-time Detection of Picking Region of Ridge Planted Strawberries Based on YOLOv5s with a Modified Neck

Robotic strawberry harvesting requires machine vision system to have the ability to detect the presence, maturity, and location of strawberries. Strawberries, however, can easily be bruised, injured, and even damaged during robotic harvest if not picked properly because of their soft surfaces. Therefore, it is important to cut or pick the strawberry stems instead of picking the fruit directly. Additionally, real-time detection is critical for robotic strawberry harvesting to adapt to the changing... Z. He, K. Manoj, Q. Zhang, S. Kshetri