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Badenhorst, P.E
George, D
Velasquez, A.E
Keller, B
Jamei, M
Ayipio, E
Irwin, M.E
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Authors
Becker, M
Velasquez, A.E
Guerrero, H.B
HIguti, V.A
Milori, D.M
Magalhães, D.V
Yule, I.J
Pullanagari, R.R
Kereszturi, G
Irwin, M.E
McVeagh, P.J
Cushnahan, T
White, M
Muller, O
Cendrero Mateo, M.P
Albrecht, H
Pinto, F
Mueller-Linow, M
Pieruschka, R
Schurr, U
Rascher, U
Schickling, A
Keller, B
Nawar, S.M
Mouazen, A.M
George, D
Manfield , A
Badenhorst, P.E
Phelan, A
Muller, O
Keller, B
Zimmermanm, L
Jedmowski, C
Pingle, V
Acebron, K
Zendonadi, N
Steier, A
Pieruschka, R
Schurr, U
Rascher, U
Kraska, T
Rehman, T
Rahman, M
Ayipio, E
Lukwesa, D
Zheng, J
Wells, D
Syed, H.H
Zaman, Q.U
Farooque, A
Jamei, M
Esau, T.J
Topics
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Precision Agriculture and Climate Change
Proximal Sensing in Precision Agriculture
Applications of Unmanned Aerial Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Artificial Intelligence (AI) in Agriculture
Big Data, Data Mining and Deep Learning
Type
Oral
Poster
Year
2016
2018
2024
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Filter results8 paper(s) found.

1. Helvis - a Small-scale Agricultural Mobile Robot Prototype for Precision Agriculture

The use of agricultural robots is emerging in a complex scenario where it is necessary to produce more food to feed a crescent population, decrease production costs, fight plagues and diseases, and preserve nature. Around the world, there are many research institutes and companies trying to apply mobile robotics techniques in agricultural fields. Mostly, large prototypes are being used and their shapes and dimensions are very similar to tractors and trucks. In the present study, a small-scale... M. Becker, A.E. Velasquez, H.B. Guerrero, V.A. Higuti, D.M. Milori, D.V. Magalhães

2. Hyperspectral Imaging to Measure Pasture Nutrient Concentration and Other Quality Parameters

Managing pasture nutrient requirements on large hill country sheep and beef properties based on information from soil sampling is expensive because of the time and labor involved. High levels of error are also expected as these properties are often greatly variable and it is therefore extremely difficult to sample intensively enough to capture this variation. Extensive sampling was also not considered viable as there was no effective means of spreading fertilizer with a variable rate capability... I.J. Yule, R.R. Pullanagari, G. Kereszturi, M.E. Irwin, P.J. Mcveagh, T. Cushnahan, M. White

3. Field Phenotyping Infrastructure in a Future World - Quantifying Information on Plant Structure and Function for Precision Agriculture and Climate Change

Phenotyping in the field is an essential step in the phenotyping chain. Phenotyping begins in the well-defined, controlled conditions in laboratories and greenhouses and extends to heterogeneous, fluctuating environments in the field. Field measurements represent a significant reference point for the relevance of the laboratory and greenhouse approaches and an important source of information on potential mechanisms and constraints for plant performance tested at controlled conditions. In this... O. Muller, M.P. Cendrero mateo, H. Albrecht, F. Pinto, M. Mueller-linow, R. Pieruschka, U. Schurr, U. Rascher, A. Schickling, B. Keller

4. Comparing Predictive Performance of Near Infrared Spectroscopy at a Field, Regional, National and Continental Scales by Using Spiking and Data Mining Techniques

The development of accurate visible and near infrared (vis-NIR) spectroscopy calibration models for selected soil properties is a crucial step for variable rate application in precision agriculture. The objective of the present study was to compare the prediction performance of vis-NIR spectroscopy at local, regional, national and continental scales using data mining techniques including spiking. Fresh soil samples collected from farms in the UK, Czech Republic, Germany, Denmark and the Netherlands... S.M. Nawar, A.M. Mouazen, D. George, A. Manfield

5. Yield Assessment of a 270 000 Plant Perennial Ryegrass Field Trial Using a Multispectral Aerial Imaging Platform

Current assessment of non-destructive yield in forage breeding programs relies largely on the visual assessment by experts, who would categorize biomass to a discrete scale. Visual assessment of biomass yield has inherent pitfalls as it can generate bias between experimental repeats and between different experts. Visual assessment is also time-consuming and would be impractical on large-scale field trials. A method has been established to allow for a rapid, non-destructive assessment of biomass... P.E. Badenhorst, A. Phelan

6. Field Phenotyping and an Example of Proximal Sensing of Photosynthesis

Field phenotyping conceptually can be divided in five pillars 1) traits of interest 2) sensors to measure these traits 3) positioning systems to allow high throughput measurements by the sensors 4) experimental sites and 5) environmental monitoring. In this paper we will focus on photosynthesis as trait of interest, measured by remote active fluorescence. The sensor presented is the Light Induced Fluorescence Transient (LIFT) instrument. The LIFT instrument is integrated in three positioning systems.... O. Muller, B. Keller, L. Zimmermanm, C. Jedmowski, V. Pingle, K. Acebron, N. Zendonadi, A. Steier, R. Pieruschka, U. Schurr, U. Rascher, T. Kraska

7. A High-throughput Phenotyping System Evaluating Salt Stress Tolerance in Kale Plants Cultivated in Aquaponics Environments

Monitoring plant growth in a controlled environment is crucial to make informed decisions for various management practices such as fertilization, weed control, and harvesting. Agronomic, physiological, and architectural traits in kale plants (Brassica oleracea) are important to producers, breeders, and researchers for assessing the performance of the plants under biotic and abiotic stresses.  Traditionally, architectural, and morphological traits have been used to monitor plant growth. However,... T. Rehman, M. Rahman, E. Ayipio, D. Lukwesa, J. Zheng, D. Wells, H.H. Syed

8. Application of Advanced Soft Computing to Estimate Potato Tuber Yield: a Case Study from Atlantic Canada

The potato crop plays a crucial role in the economy of Atlantic Canada, particularly in Prince Edward Island and New Brunswick, where it contributes significantly to potato production. To help farmers make informed decisions for sustainable and profitable farming, this study was conducted to examine the variations in potato tuber yield based on thirty soil properties collected over four growing seasons through experimental trials. The study employed an advanced and explainable ensemble model called... Q.U. Zaman, A. Farooque, M. Jamei, T.J. Esau