Proceedings :: International Society of Precision Agriculture

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Claupein, W

Cordova Gonzalez, C

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Authors

Graeff, S

Pfenning, J

Claupein, W

Bhandari, S

Acosta, M

Cordova Gonzalez, C

Raheja, A

Sherafat, A

Topics

Precision Horticulture

Artificial Intelligence (AI) in Agriculture

Type

Oral

Year

2010

2024

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Filter results2 paper(s) found.
1. Adoption Of N-application Rates In Different Broccoli Cultivars By Reflectance Measurements To date many sensors have been solely developed and tested for arable crops. This project aims to develop the means to rapidly map N-demand in broccoli plants on a site-specific, plant-by-plant basis using reflectance measurements. The aim of this specific study was to monitor nitrogen status in six different broccoli cultivars using reflectance measurements and to derive suitable N-fertilization strategies based on the sensor measurements.A... S. Graeff, J. Pfenning, W. Claupein Download paper
2. Leveraging UAV-based Hyperspectral Data and Machine Learning Techniques for the Detection of Powderly Mildew in Vineyards This paper presents the development and validation of machine learning models for the detection of powdery mildew in vineyards. The models are trained and validated using custom datasets obtained from unmanned aerial vehicles (UAVs) equipped with a hyperspectral sensor that can collect images in visible/near-infrared (VNIR) and shortwave infrared (SWIR) wavelengths. The dataset consists of the images of vineyards with marked regions for powdery mildew, meticulously annotated using LabelImg. ... S. Bhandari, M. Acosta, C. Cordova gonzalez, A. Raheja, A. Sherafat Download paper

Filter results2 paper(s) found.

1. Adoption Of N-application Rates In Different Broccoli Cultivars By Reflectance Measurements

To date many sensors have been solely developed and tested for arable crops. This project aims to develop the means to rapidly map N-demand in broccoli plants on a site-specific, plant-by-plant basis using reflectance measurements. The aim of this specific study was to monitor nitrogen status in six different broccoli cultivars using reflectance measurements and to derive suitable N-fertilization strategies based on the sensor measurements.A... S. Graeff, J. Pfenning, W. Claupein

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2. Leveraging UAV-based Hyperspectral Data and Machine Learning Techniques for the Detection of Powderly Mildew in Vineyards

This paper presents the development and validation of machine learning models for the detection of powdery mildew in vineyards. The models are trained and validated using custom datasets obtained from unmanned aerial vehicles (UAVs) equipped with a hyperspectral sensor that can collect images in visible/near-infrared (VNIR) and shortwave infrared (SWIR) wavelengths. The dataset consists of the images of vineyards with marked regions for powdery mildew, meticulously annotated using LabelImg. ... S. Bhandari, M. Acosta, C. Cordova gonzalez, A. Raheja, A. Sherafat

Download paper