Proceedings :: International Society of Precision Agriculture

Proceedings

Find matching any: Reset

Folle, S

Colbert, J

» Add more authors

Add filter to result:

Authors

Miao, Y

Kechchour, A

Folle, S

Mizuta, K

Waltz, L

Khanal, S

Katari, S

Hong, C

Anup, A

Colbert, J

Potlapally, A

Dill, T

Porter, C

Engle, J

Stewart, C

Subramoni, H

Machiraju, R

Ortez, O

Lindsey, L

Nandi, A

Topics

Site-Specific Nutrient, Lime and Seed Management

Artificial Intelligence (AI) in Agriculture

Type

Oral

Year

2024

Home » Authors » Results

Authors

Filter results2 paper(s) found.
1. On-farm Evaluation of the Potential Benefits of Variable Rate Seeding for Corn in Minnesota Many farmers in Minnesota are interested in adopting variable rate seeding technology for corn, however, little has been reported about their potential benefits. The objectives of this study were to 1) determine within-field variability of optimal seeding rates, and 2) evaluate the potential benefits of variable rate seeding in commercial corn fields in Minnesota. Four on-farm variable rate seeding trials were conducted in Minnesota in 2022 and 2023, with seeding rates ranging from 31,000 to 41,000... Y. Miao, A. Kechchour, S. Folle, K. Mizuta
2. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and Vision Advancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi Download paper

Filter results2 paper(s) found.

1. On-farm Evaluation of the Potential Benefits of Variable Rate Seeding for Corn in Minnesota

Many farmers in Minnesota are interested in adopting variable rate seeding technology for corn, however, little has been reported about their potential benefits. The objectives of this study were to 1) determine within-field variability of optimal seeding rates, and 2) evaluate the potential benefits of variable rate seeding in commercial corn fields in Minnesota. Four on-farm variable rate seeding trials were conducted in Minnesota in 2022 and 2023, with seeding rates ranging from 31,000 to 41,000... Y. Miao, A. Kechchour, S. Folle, K. Mizuta

2. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and Vision

Advancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi

Download paper