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Westbrook, J

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Authors

Zhang, H

Lan, Y

Westbrook, J

Suh, C

Hoffmann, C

Lacey, R

Lan, Y

Hoffmann, W.C

Westbrook, J

Zaller, M

Topics

Sensor Application in Managing In-season Crop Variability

Modeling and Geo-statistics

Type

Poster

Year

2010

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1. Investigation Of Crop Varieties At Different Growth Stages Using Optical Sensor Data Cotton, soybean and sorghum are economically important crops in Texas. Knowing the growing status of crops at different stages of growth is crucial to apply site-specific management and increase crop yield for farmers. Field experiments were initiated to measure cotton, soybean and sorghum plants growth status and spatial variability through the whole growing cycle. A ground-based active optical sensor, Greenseeker®, was used to collect the Normalized Difference Vegetation Index (NDVI) data... H. Zhang, Y. Lan, J. Westbrook, C. Suh, C. Hoffmann, R. Lacey Download paper
2. Development Of A Decision Support System For Precision Areawide Pest Management In Cotton Production Crop models simulate growth and development, and provide relevant information for the routine management of the crop. The use of crop models on large areas for diagnosing crop growing conditions or predicting crop production is hampered by the lack of sufficient spatial information about model inputs. Integrating crop models with other information technologies such as geographic information systems (GIS), variable rate technology, remote sensing, and global positioning... Y. Lan, W.C. Hoffmann, J. Westbrook, M. Zaller

Filter results2 paper(s) found.

1. Investigation Of Crop Varieties At Different Growth Stages Using Optical Sensor Data

Cotton, soybean and sorghum are economically important crops in Texas. Knowing the growing status of crops at different stages of growth is crucial to apply site-specific management and increase crop yield for farmers. Field experiments were initiated to measure cotton, soybean and sorghum plants growth status and spatial variability through the whole growing cycle. A ground-based active optical sensor, Greenseeker®, was used to collect the Normalized Difference Vegetation Index (NDVI) data... H. Zhang, Y. Lan, J. Westbrook, C. Suh, C. Hoffmann, R. Lacey

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2. Development Of A Decision Support System For Precision Areawide Pest Management In Cotton Production

Crop models simulate growth and development, and provide relevant information for the routine management of the crop. The use of crop models on large areas for diagnosing crop growing conditions or predicting crop production is hampered by the lack of sufficient spatial information about model inputs. Integrating crop models with other information technologies such as geographic information systems (GIS), variable rate technology, remote sensing, and global positioning... Y. Lan, W.C. Hoffmann, J. Westbrook, M. Zaller