Evaluation of a Hand-Held Radiometer for Field Determination of Nitrogen Status in Cotton

2015 ◽  
pp. 177-195
Author(s):  
John J. Read ◽  
Eric L. Whaley ◽  
Lee Tarpley ◽  
K. Raja Reddy
Keyword(s):  
Nitrogen Status

Discriminating Biomass and Nitrogen Status in Wheat Crop by Spectral Reflectance Using Artificial Neural Networks

2014 ◽  
Vol 5 (2) ◽  
pp. 38-49
Author(s):  
Claudio Kapp Junior ◽  
Eduardo Fávero Caires ◽  
Alaine Margarete Guimarães
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Biomass Production ◽  
Precision Agriculture ◽  
Spectral Reflectance ◽  
Wheat Crop ◽  
Nitrogen Status ◽  
Artificial Neural ◽  
N Rates

Precision Agriculture has the goal of reducing cost which is difficult when it is related to fertilizers application. Nitrogen (N) is the nutrient absorbed in greater amounts by crops and the N fertilizers application present significant costs. The use of spectral reflectance sensors has been studied to identify the nutritional status of crops and prescribe varying N rates. This study aimed to contribute to the determination of a model to discriminating biomass and nitrogen status in wheat through two sensors, GreenSeeker and Crop Circle, using the Resilient Propagation and Backpropagation Artificial Neural Networks algorithms. As a result was detected a strong correlation to the sensor readings with the aboveground biomass production and N extraction by plants. For both algorithms it was established a satisfactory model for estimating wheat dry biomass production. The best Backpropagation and Resilient Propagation models defined showed better performance for the GreenSeeker and Crop Circle sensors, respectively.

Discriminating Biomass and Nitrogen Status in Wheat Crop by Spectral Reflectance Using ANN Algorithms

2018 ◽  
pp. 156-172
Author(s):  
Claudio Kapp Jr. ◽  
Eduardo Fávero Caires ◽  
Alaine Margarete Guimarães
Keyword(s):  
Biomass Production ◽  
Precision Agriculture ◽  
Spectral Reflectance ◽  
Fertilizer Application ◽  
Wheat Crop ◽  
Nitrogen Status ◽  
Propagation Models ◽  
Dry Biomass ◽  
N Rates

Precision agriculture has the goal of reducing cost which is difficult when it is related to fertilizer application. Nitrogen (N) is the nutrient absorbed in greater amounts by crops and the N fertilizer application presents significant costs. The use of spectral reflectance sensors has been studied to identify the nutritional status of crops and prescribe varying N rates. This study aimed to contribute to the determination of a model to discriminating biomass and nitrogen status in wheat through two sensors, GreenSeeker and Crop Circle, using the resilient propagation and backpropagation artificial neural networks algorithms. As a result, a strong correlation to the sensor readings with the aboveground biomass production and N extraction by plants was detected. For both algorithms a satisfactory model for estimating wheat dry biomass production was established. The best backpropagation and resilient propagation models defined showed better performance for the GreenSeeker and Crop Circle sensors, respectively.

Determination of nitrogen status in maize senescing leaves

1997 ◽  
Vol 20 (1) ◽  
pp. 1-8 ◽  
Author(s):  
B. L. Ma ◽  
L. M. Dwyer
Keyword(s):  
Nitrogen Status
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