TY - JOUR
T1 - Water effects on optical canopy sensing for late-season site-specific nitrogen management of maize
AU - Lo, Tsz Him
AU - Rudnick, Daran R.
AU - Krienke, Brian T.
AU - Heeren, Derek M.
AU - Ge, Yufeng
AU - Shaver, Tim M.
N1 - Funding Information:
The authors are grateful to Turner Dorr and Jacob Nickel for their involvement with data collection; to Gary Mahnken and Merle Still for their supporting roles in field management; to AirScout for their donation of aerial imagery products and services; and to Lindsay Corporation, Holzfasters Irrigation, Agri-Inject, SureFire Ag Systems, and Holland Scientific for their timely technical support. This research is based upon work that was jointly supported by the United States Department of Agriculture’s National Institute of Food and Agriculture under award number 2016-68007-25066 , “Sustaining agriculture through adaptive management to preserve the Ogallala aquifer under a changing climate”, and under Hatch project #1015698; the Nebraska Corn Board under award number 88-R-1617-06 ; the Daugherty Water for Food Global Institute ; and University of Nebraska–Lincoln Institute of Agriculture and Natural Resources .
Funding Information:
The authors are grateful to Turner Dorr and Jacob Nickel for their involvement with data collection; to Gary Mahnken and Merle Still for their supporting roles in field management; to AirScout for their donation of aerial imagery products and services; and to Lindsay Corporation, Holzfasters Irrigation, Agri-Inject, SureFire Ag Systems, and Holland Scientific for their timely technical support. This research is based upon work that was jointly supported by the United States Department of Agriculture's National Institute of Food and Agriculture under award number 2016-68007-25066, “Sustaining agriculture through adaptive management to preserve the Ogallala aquifer under a changing climate”, and under Hatch project #1015698; the Nebraska Corn Board under award number 88-R-1617-06; the Daugherty Water for Food Global Institute; and University of Nebraska–Lincoln Institute of Agriculture and Natural Resources.
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/7
Y1 - 2019/7
N2 - The interpretation of optical canopy sensor readings for determining optimal rates of late-season site-specific nitrogen application to corn (Zea mays L.) can be complicated by spatially variable water sufficiency, which can also affect canopy size and/or pigmentation. In 2017 and 2018, corn following corn and corn following soybeans were subjected to irrigation × nitrogen fertilizer treatments in west central Nebraska, USA, to induce variable water sufficiency and variable nitrogen sufficiency. The vegetation index-sensor combinations investigated were the normalized difference vegetation index (NDVI), the normalized difference red edge index (NDRE), and the reflectance ratio of near infrared minus red edge over near infrared minus red (DATT) using ACS-430 active optical sensors; NDVI using SRS-NDVI passive optical sensors; and red brightness and a proprietary index using commercial aerial visible imagery. Among these combinations, NDRE and DATT were found to be the most suitable for assessing nitrogen sufficiency within irrigation levels. While DATT was the least sensitive to variable water sufficiency, DATT still tended to decrease with decreasing water sufficiency in high nitrogen treatments, whereas the effect of water sufficiency on DATT was inconsistent in low nitrogen treatments. A new method of quantifying nitrogen sufficiency while accounting for water sufficiency was proposed and generally provided more consistent improvement over the mere averaging of water effects as compared with the canopy chlorophyll content index method. Further elucidation and better handling of water-nitrogen interactions and confounding are expected to become increasingly important as the complexity, automation, and adoption of sensor-based irrigation and nitrogen management increase.
AB - The interpretation of optical canopy sensor readings for determining optimal rates of late-season site-specific nitrogen application to corn (Zea mays L.) can be complicated by spatially variable water sufficiency, which can also affect canopy size and/or pigmentation. In 2017 and 2018, corn following corn and corn following soybeans were subjected to irrigation × nitrogen fertilizer treatments in west central Nebraska, USA, to induce variable water sufficiency and variable nitrogen sufficiency. The vegetation index-sensor combinations investigated were the normalized difference vegetation index (NDVI), the normalized difference red edge index (NDRE), and the reflectance ratio of near infrared minus red edge over near infrared minus red (DATT) using ACS-430 active optical sensors; NDVI using SRS-NDVI passive optical sensors; and red brightness and a proprietary index using commercial aerial visible imagery. Among these combinations, NDRE and DATT were found to be the most suitable for assessing nitrogen sufficiency within irrigation levels. While DATT was the least sensitive to variable water sufficiency, DATT still tended to decrease with decreasing water sufficiency in high nitrogen treatments, whereas the effect of water sufficiency on DATT was inconsistent in low nitrogen treatments. A new method of quantifying nitrogen sufficiency while accounting for water sufficiency was proposed and generally provided more consistent improvement over the mere averaging of water effects as compared with the canopy chlorophyll content index method. Further elucidation and better handling of water-nitrogen interactions and confounding are expected to become increasingly important as the complexity, automation, and adoption of sensor-based irrigation and nitrogen management increase.
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U2 - 10.1016/j.compag.2019.04.006
DO - 10.1016/j.compag.2019.04.006
M3 - Article
AN - SCOPUS:85064147974
VL - 162
SP - 154
EP - 164
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
SN - 0168-1699
ER -