Using a Simple Leaf Color Chart to Estimate Leaf and Canopy Chlorophyll a Content in Maize (Zea mays)

被引:20
作者
Nguy-Robertson, Anthony [1 ]
Peng, Yi [1 ,2 ]
Arkebauer, Timothy [3 ]
Scoby, David [3 ]
Schepers, James [3 ]
Gitelson, Anatoly [1 ,4 ]
机构
[1] Univ Nebraska, Sch Nat Resources, Ctr Adv Land Management Informat Technol, Lincoln, NE USA
[2] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430072, Peoples R China
[3] Univ Nebraska, Dept Agron & Hort, Lincoln, NE USA
[4] Technion Israel Inst Technol, Fac Civil & Environm Engn, Haifa, Israel
关键词
Leaf area index; MERIS; remote sensing; SPAD; stalk nitrate test; vegetation indices; GROSS PRIMARY PRODUCTION; NONDESTRUCTIVE DETERMINATION; NITROGEN MANAGEMENT; REMOTE ESTIMATION; STALK NITRATE; YIELD; METER; RICE; EFFICIENCY; WHEAT;
D O I
10.1080/00103624.2015.1093639
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
This study utilized a leaf color chart (LCC) to characterize the variation in leaf chlorophyll and estimate canopy chlorophyll in maize (Zea mays). The LCC consisted of four levels of greenness and was used to sort maize leaves in 2011 for three fields near Mead, Nebraska, USA. Leaf chlorophyll content for each color chart class was determined using two leaf-level sensors. The variation within each LCC class was reasonable (CV < 56%). The darkest color class predominated and indicated adequate fertilization rates using a Minolta SPAD-502 meter. Canopy chlorophyll content was estimated using destructively measured leaf area index (LAI) and the LCC. This approach was verified with a method utilizing canopy reflectance collected by both satellite imagery and a four-band radiometer. The error between the two methods was reasonable (RMSE=0.55-0.88gm(-2); CV=25.6-50.4%), indicating that both leaf and canopy chlorophyll can be estimated cheaply without a wet lab or field-based sensors.
引用
收藏
页码:2734 / 2745
页数:12
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