Proceedings :: International Society of Precision Agriculture

Proceedings

Find matching any: Reset

Freitas, A.A

Rehman, T

Dabbelt, D

» Add more authors

Add filter to result:

Authors

Bortolon, L

Borghi, E

Luchiari Junior, A

Bortolon, E.S

Freitas, A.A

Inamasu, R.Y

Avanzi, J.C

Borchert, A

Recke, G

Dabbelt, D

Trautz, D

Olfs, H

Syed, H.H

Rehman, T

Rahman, M

Busby, S

Sanz-Saez, A

Ru, S

Rehman, T

Rahman, M

Ayipio, E

Lukwesa, D

Zheng, J

Wells, D

Syed, H.H

Topics

Profitability, Sustainability and Adoption

Precision Nutrient Management

Robotics and Automation with Row and Horticultural Crops

Artificial Intelligence (AI) in Agriculture

Type

Poster

Oral

Year

2012

2024

Home » Authors » Results

Authors

Filter results5 paper(s) found.
1. Adoption and Tendencies of Precision Agriculture Technologies in the Tocantins State, Brazil Although precision agriculture is widely used throughout Brazilian crop production, it has not been used to increase the efficiency use of agricultural inputs. Besides, technologies available have not been... L. Bortolon, E. Borghi, A. Luchiari junior, E.S. Bortolon, A.A. Freitas, R.Y. Inamasu, J.C. Avanzi Download paper
2. Economic Evaluation of a Variable Lime Application Strategy Based on Soil pH Maps Derived from On-The-Go pH-Measurements under German Conditions ... A. Borchert, G. Recke, D. Dabbelt, D. Trautz, H. Olfs Download paper
3. Automated In-field Ornamental Nursery Plant Counting and Quality Assessment with End-to-end Deep Learning for Inventory Management Efficient inventory management and rigorous quality evaluation play crucial roles for monitoring sales, yield, space utilization, production schedules, and quality enhancements in the ornamental nursery sector. The current method for conducting inventory and quality assessments is through manual plant counting, even when dealing with thousands of plants. The prevailing approach is inefficient, time consuming, labor intensive, potential inaccuracies, and high expenses. Given the continuous decrease... H.H. Syed, T. Rehman
4. Drought Tolerance Assessment with Statistical and Deep Learning Models on Hyperspectral Images for High-throughput Plant Phenotyping Drought is an important factor that severely restricts blueberry growth, output and adversely impacts the desirable physiologic quality. Considering the challenges posed by climate change and erratic weather patterns, evaluating the drought tolerance of blueberry plants is not only vital for the agricultural industry but also for ensuring a consistent supply of these nutritious berries to consumers. Blueberry plants have a relatively ineffective water regulation mechanism due to their shallow... M. Rahman, S. Busby, A. Sanz-saez, S. Ru, T. Rehman
5. 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

Filter results5 paper(s) found.

1. Adoption and Tendencies of Precision Agriculture Technologies in the Tocantins State, Brazil

Although precision agriculture is widely used throughout Brazilian crop production, it has not been used to increase the efficiency use of agricultural inputs. Besides, technologies available have not been... L. Bortolon, E. Borghi, A. Luchiari junior, E.S. Bortolon, A.A. Freitas, R.Y. Inamasu, J.C. Avanzi

Download paper

2. Economic Evaluation of a Variable Lime Application Strategy Based on Soil pH Maps Derived from On-The-Go pH-Measurements under German Conditions

... A. Borchert, G. Recke, D. Dabbelt, D. Trautz, H. Olfs

Download paper

3. Automated In-field Ornamental Nursery Plant Counting and Quality Assessment with End-to-end Deep Learning for Inventory Management

Efficient inventory management and rigorous quality evaluation play crucial roles for monitoring sales, yield, space utilization, production schedules, and quality enhancements in the ornamental nursery sector. The current method for conducting inventory and quality assessments is through manual plant counting, even when dealing with thousands of plants. The prevailing approach is inefficient, time consuming, labor intensive, potential inaccuracies, and high expenses. Given the continuous decrease... H.H. Syed, T. Rehman

4. Drought Tolerance Assessment with Statistical and Deep Learning Models on Hyperspectral Images for High-throughput Plant Phenotyping

Drought is an important factor that severely restricts blueberry growth, output and adversely impacts the desirable physiologic quality. Considering the challenges posed by climate change and erratic weather patterns, evaluating the drought tolerance of blueberry plants is not only vital for the agricultural industry but also for ensuring a consistent supply of these nutritious berries to consumers. Blueberry plants have a relatively ineffective water regulation mechanism due to their shallow... M. Rahman, S. Busby, A. Sanz-saez, S. Ru, T. Rehman

5. 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