Active‐Optical Reflectance Sensing Corn Algorithms Evaluated over the United States Midwest Corn Belt. (1st November 2018)
- Record Type:
- Journal Article
- Title:
- Active‐Optical Reflectance Sensing Corn Algorithms Evaluated over the United States Midwest Corn Belt. (1st November 2018)
- Main Title:
- Active‐Optical Reflectance Sensing Corn Algorithms Evaluated over the United States Midwest Corn Belt
- Authors:
- Bean, G. M.
Kitchen, N. R.
Camberato, J. J.
Ferguson, R. B.
Fernandez, F. G.
Franzen, D. W.
Laboski, C. A. M.
Nafziger, E. D.
Sawyer, J. E.
Scharf, P. C.
Schepers, J.
Shanahan, J. S. - Abstract:
- Abstract : Core Ideas: Active‐optical reflectance sensor algorithms perform poorly outside the area for which they were originally developed. The red edge waveband is more sensitive to N stress than the red waveband. Some active‐optical reflectance algorithms are dependent on the sensor for which they were developed. Uncertainty exists with corn ( Zea mays L.) N management due to year‐to‐year variation in crop N need, soil N supply, and N loss from leaching, volatilization, and denitrification. Active‐optical reflectance sensing (AORS) has proven effective in some fields for generating N fertilizer recommendations that improve N use efficiency, but locally derived (e.g., within a US state) AORS algorithms have not been tested simultaneously across a broad region. The objective of this research was to evaluate locally developed AORS algorithms across the US Midwest Corn Belt region for making in‐season corn N recommendations. Forty‐nine N response trials were conducted across eight states and three growing seasons. Reflectance measurements were collected and sidedress N rates (45–270 kg N ha −1 on 45 kg ha −1 increments) applied at approximately V9 corn development stage. Nitrogen recommendation rates from AORS algorithms were compared with the end‐of‐season calculated economic optimal N rate (EONR). No algorithm was within 34 kg N ha −1 of EONR > 50% of the time. Average recommendations differed from EONR 81 to 147 kg N ha −1 with no N applied at planting and 74 to 118 kg NAbstract : Core Ideas: Active‐optical reflectance sensor algorithms perform poorly outside the area for which they were originally developed. The red edge waveband is more sensitive to N stress than the red waveband. Some active‐optical reflectance algorithms are dependent on the sensor for which they were developed. Uncertainty exists with corn ( Zea mays L.) N management due to year‐to‐year variation in crop N need, soil N supply, and N loss from leaching, volatilization, and denitrification. Active‐optical reflectance sensing (AORS) has proven effective in some fields for generating N fertilizer recommendations that improve N use efficiency, but locally derived (e.g., within a US state) AORS algorithms have not been tested simultaneously across a broad region. The objective of this research was to evaluate locally developed AORS algorithms across the US Midwest Corn Belt region for making in‐season corn N recommendations. Forty‐nine N response trials were conducted across eight states and three growing seasons. Reflectance measurements were collected and sidedress N rates (45–270 kg N ha −1 on 45 kg ha −1 increments) applied at approximately V9 corn development stage. Nitrogen recommendation rates from AORS algorithms were compared with the end‐of‐season calculated economic optimal N rate (EONR). No algorithm was within 34 kg N ha −1 of EONR > 50% of the time. Average recommendations differed from EONR 81 to 147 kg N ha −1 with no N applied at planting and 74 to 118 kg N ha −1 with 45 kg of N ha −1 at planting, indicating algorithms performed worse with no N applied at planting. With some algorithms, utilizing red edge instead of the red reflectance improved N recommendations. Results demonstrate AORS algorithms developed under a particular set of conditions may not, at least without modification, perform very well in regions outside those within which they were developed. … (more)
- Is Part Of:
- Agronomy Journal. Volume 110:Number 6(2018)
- Journal:
- Agronomy Journal
- Issue:
- Volume 110:Number 6(2018)
- Issue Display:
- Volume 110, Issue 6 (2018)
- Year:
- 2018
- Volume:
- 110
- Issue:
- 6
- Issue Sort Value:
- 2018-0110-0006-0000
- Page Start:
- 2552
- Page End:
- 2565
- Publication Date:
- 2018-11-01
- Subjects:
- Agronomy -- Periodicals
630 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.2134/agronj2018.03.0217 ↗
- Languages:
- English
- ISSNs:
- 0002-1962
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12763.xml