Proceedings :: International Society of Precision Agriculture

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Liburd, O.E

Holmes, A.W

Swain, D

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Authors

Trotter, M

Gregory, S

Trotter, T

Acuna, T

Swain, D

Fasso, W

Roberts, J

Zikan, A

Cosby, A.M

Holmes, A.W

Jiang, G

Zhou, C

Lee, W

Pourreza, A

Schueller, J.K

Liburd, O.E

Ampatzidis, Y

Zuniga-Ramirez, G

Topics

Agricultural Education

Site-Specific Nutrient, Lime and Seed Management

Big Data, Data Mining and Deep Learning

Type

Oral

Year

2016

2018

2022

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Filter results3 paper(s) found.
1. SMARTfarm Learning Hub: Next Generation Precision Agriculture Technologies for Agricultural Education The industry demands on higher education agricultural students are rapidly changing. New precision agriculture technologies are revolutionizing the farming industry but the education sector is failing to keep pace. This paper reports on the development of a key resource, the SMARTfarm Learning Hub (www.smartfarmhub.com) that will increase the skill base of higher education students using a range of new agricultural technologies and innovations. The Hub is a world first; it links real industry... M. Trotter, S. Gregory, T. Trotter, T. Acuna, D. Swain, W. Fasso, J. Roberts, A. Zikan, A. Cosby Download paper
2. Increasing Profitability & Sustainability of Maize Using Site-Specific Crop Management in New Zealand Precision agriculture (PA) tools and techniques have been used in New Zealand (NZ) since the early 1990's. There has been wide-scale uptake of some PA tools such as autosteer; planter and sprayer section control; and variable-rate irrigation. However, there has been a limited uptake of Site-Specific Crop Management (SSCM) using variable-rate seeding, nutrient and lime applications to different Management Zones (MZ). This paper outlines examples of the use of SSCM on maize crops,... A.W. Holmes, G. Jiang Download paper
3. Strawberry Pest Detection Using Deep Learning and Automatic Imaging System Strawberry growers need to monitor pests to determine the options for pest management to reduce damage to yield and quality. However, manually counting strawberry pests using a hand lens is time-consuming and biased by the observer. Therefore, an automated rapid pest scouting method in the strawberry field can save time and improve counting consistency. This study utilized six cameras to take images of the strawberry leaf. Due to the relatively small size of the strawberry pest, six cameras... C. Zhou, W. Lee, A. Pourreza, J.K. Schueller, O.E. Liburd, Y. Ampatzidis, G. Zuniga-ramirez Download paper

Filter results3 paper(s) found.

1. SMARTfarm Learning Hub: Next Generation Precision Agriculture Technologies for Agricultural Education

The industry demands on higher education agricultural students are rapidly changing. New precision agriculture technologies are revolutionizing the farming industry but the education sector is failing to keep pace. This paper reports on the development of a key resource, the SMARTfarm Learning Hub (www.smartfarmhub.com) that will increase the skill base of higher education students using a range of new agricultural technologies and innovations. The Hub is a world first; it links real industry... M. Trotter, S. Gregory, T. Trotter, T. Acuna, D. Swain, W. Fasso, J. Roberts, A. Zikan, A. Cosby

Download paper

2. Increasing Profitability & Sustainability of Maize Using Site-Specific Crop Management in New Zealand

Precision agriculture (PA) tools and techniques have been used in New Zealand (NZ) since the early 1990's. There has been wide-scale uptake of some PA tools such as autosteer; planter and sprayer section control; and variable-rate irrigation. However, there has been a limited uptake of Site-Specific Crop Management (SSCM) using variable-rate seeding, nutrient and lime applications to different Management Zones (MZ). This paper outlines examples of the use of SSCM on maize crops,... A.W. Holmes, G. Jiang

Download paper

3. Strawberry Pest Detection Using Deep Learning and Automatic Imaging System

Strawberry growers need to monitor pests to determine the options for pest management to reduce damage to yield and quality. However, manually counting strawberry pests using a hand lens is time-consuming and biased by the observer. Therefore, an automated rapid pest scouting method in the strawberry field can save time and improve counting consistency. This study utilized six cameras to take images of the strawberry leaf. Due to the relatively small size of the strawberry pest, six cameras... C. Zhou, W. Lee, A. Pourreza, J.K. Schueller, O.E. Liburd, Y. Ampatzidis, G. Zuniga-ramirez

Download paper