Proceedings :: International Society of Precision Agriculture

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McCornack, B

V. de Sousa, R

Gonzalez-Mora, J

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Authors

M. Rabello, L

R. D. Pereira, R

C. Lopes, W

Y. Inamasu, R

V. de Sousa, R

Gonzalez-Mora, J

Vallespi Gonzalez, C

Ehsani, R

Dima, C.S

Duhachek, G

Spiesman, B

Grijalva, I

Holthaus, D

McCornack, B

Grijalva Teran, I.A

Spiesman, B

Clark, N

McCornack, B

Topics

Engineering Technologies and Advances

Precision Horticulture

Big Data, Data Mining and Deep Learning

Artificial Intelligence (AI) in Agriculture

Type

Poster

Oral

Year

2012

2010

2024

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Filter results4 paper(s) found.
1. Implementation of a Controller Unit Based on the ISO 11783 Standard for Automatic Measurement of the Electrical Conductivity of the Soil ... L. M. rabello, R. R. d. pereira, W. C. lopes, R. Y. inamasu, R. V. de sousa Download paper
2. HLB Detection Using Hyperspectral Radiometry The need for sustainable agriculture requires the adoption of low input, long-term and cost-effective strategies to overcome the adverse impact of disease and nutritional deficiencies on citrus groves. In this context, early detection of diseased trees has become an important topic in the citrus industry. Multiple factors make field assessment of disease conditions a challenging task: the non-specific nature of many symptoms, the possibility of having localized affections in only certain areas... J. Gonzalez-mora, C. Vallespi gonzalez, R. Ehsani, C.S. Dima, G. Duhachek Download paper
3. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV Imagery Pollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness of... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack
4. Detection of Sorghum Aphids with Advanced Machine Vision Sorghum aphid, Melanaphis sorghi (Theobald), became a significant pest concern due to the significant yield losses caused in the sorghum production region. Different management practices, including monitoring and applying insecticides, have been used to manage this invasive pest in sorghum. The most common management strategy consists of visual assessments of aphids on sorghum leaves to determine an economic threshold level to spray. However, because of their rapid reproduction,... I.A. Grijalva teran, B. Spiesman, N. Clark, B. Mccornack Download paper

Filter results4 paper(s) found.

1. Implementation of a Controller Unit Based on the ISO 11783 Standard for Automatic Measurement of the Electrical Conductivity of the Soil

... L. M. rabello, R. R. d. pereira, W. C. lopes, R. Y. inamasu, R. V. de sousa

Download paper

2. HLB Detection Using Hyperspectral Radiometry

The need for sustainable agriculture requires the adoption of low input, long-term and cost-effective strategies to overcome the adverse impact of disease and nutritional deficiencies on citrus groves. In this context, early detection of diseased trees has become an important topic in the citrus industry. Multiple factors make field assessment of disease conditions a challenging task: the non-specific nature of many symptoms, the possibility of having localized affections in only certain areas... J. Gonzalez-mora, C. Vallespi gonzalez, R. Ehsani, C.S. Dima, G. Duhachek

Download paper

3. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV Imagery

Pollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness of... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack

4. Detection of Sorghum Aphids with Advanced Machine Vision

Sorghum aphid, Melanaphis sorghi (Theobald), became a significant pest concern due to the significant yield losses caused in the sorghum production region. Different management practices, including monitoring and applying insecticides, have been used to manage this invasive pest in sorghum. The most common management strategy consists of visual assessments of aphids on sorghum leaves to determine an economic threshold level to spray. However, because of their rapid reproduction,... I.A. Grijalva teran, B. Spiesman, N. Clark, B. Mccornack

Download paper