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The Assessment of Leaf Nitrogen in Corn from Digital Images
Author(s) -
Rorie Robert L.,
Purcell Larry C.,
Karcher Douglas E.,
King C. Andy
Publication year - 2011
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2010.12.0699
Subject(s) - biology , hue , digital image analysis , greenhouse , zea mays , agronomy , chlorophyll , horticulture , botany , artificial intelligence , computer science , computer vision
Environmental concerns of nitrate pollution coupled with the cost of N fertilizers have led to increased interest in assessing plant N status. Our objective was to use a digital camera and image‐analysis software to assess leaf N concentration in corn ( Zea mays L.) leaves from the association between leaf N and green color of chlorophyll. In greenhouse experiments conducted at Fayetteville, AR, in 2008 and 2009, digital photographs of the uppermost collared leaf of 3‐ to 5‐leaf corn plants grown over a range of soil N treatments were processed into a dark green color index (DGCI), which combines the hue, saturation, and brightness into one composite number. Soil plant analysis development (SPAD) and DGCI values agreed closely across both years with r 2 ≥ 0.91. There was a close relationship ( r 2 ranged from 0.80 to 0.89) between DGCI and leaf N concentration. Yellow and green disks of known DGCI values were successfully used as internal standards to correct for differences in color sensitivity among cameras. Similarly, DGCI standard disks were able to correct for differences in lighting conditions for corn grown in the field. Determination of leaf N concentration in corn by digital image analysis offers a potential new tool for assessing corn N status.