Proceedings :: International Society of Precision Agriculture

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Liburd, O.E

Marra, M.C

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Authors

Velandia, M

Mooney, D.F

Roberts, R.K

English, B.C

Larson, J.A

Lambert, D.M

Larkin, S.L

Marra, M.C

Rejesus, R

Martin, S.W

Paxton, K.W

Mishra, A

Wang, C

Segarra, E

Reeves, J.M

Zhou, C

Lee, W

Pourreza, A

Schueller, J.K

Liburd, O.E

Ampatzidis, Y

Zuniga-Ramirez, G

Topics

Profitability, Sustainability, and Adoption

Big Data, Data Mining and Deep Learning

Type

Oral

Year

2010

2022

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Authors

Filter results2 paper(s) found.
1. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 Survey The objectives of this study were 1) to determine the status of precision farming technology adoption by cotton producers in 12 states and 2) to evaluate changes in cotton precision farming technology adoption between 2000 and 2008. A mail survey of cotton producers located in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas and Virginia was conducted in February and March of 2009 to establish the use of precision farming technologies... M. Velandia, D.F. Mooney, R.K. Roberts, B.C. English, J.A. Larson, D.M. Lambert, S.L. Larkin, M.C. Marra, R. Rejesus, S.W. Martin, K.W. Paxton, A. Mishra, C. Wang, E. Segarra, J.M. Reeves Download paper
2. 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 results2 paper(s) found.

1. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 Survey

The objectives of this study were 1) to determine the status of precision farming technology adoption by cotton producers in 12 states and 2) to evaluate changes in cotton precision farming technology adoption between 2000 and 2008. A mail survey of cotton producers located in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas and Virginia was conducted in February and March of 2009 to establish the use of precision farming technologies... M. Velandia, D.F. Mooney, R.K. Roberts, B.C. English, J.A. Larson, D.M. Lambert, S.L. Larkin, M.C. Marra, R. Rejesus, S.W. Martin, K.W. Paxton, A. Mishra, C. Wang, E. Segarra, J.M. Reeves

Download paper

2. 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