title: [Monitoring of wheat leaf pigment concentration with hyper-spectral remote sensing].
abstract: In a two-year field experiment with wheat cultivars under different application rates of fertilizer N, the wheat leaf pigment concentrations were monitored with hyper-spectral remote sensing, and quantitative monitoring models were established. The results showed that the pigment concentrations in wheat leaves increased with increasing N application rate, and differed significantly among test cultivars. With the growth of wheat, the relative concentration of chlorophyll a + b varied more obviously than those of chlorophyll b and carotenoid (Car), and the sensitive bands of the pigments occurred mostly within visible light range, especially in red-edge district. The analyses on the relationships between eight existing vegetation indices and leaf pigment concentrations indicated that the concentrations of chlorophyll a, chlorophyll b, and chlorophyll a + b were highly correlated with red edge position, and the relationships to REP(LE) were better than to REP(IG), giving the determination coefficient R2 as 0.835, 0.841 and 0.840, and standard error SE as 0.264, 0.095 and 0.353, respectively. However, the R2 values between Car and different spectral indices decreased significantly, and the differences among the spectrum indices were very small. The tests of the monitoring models with independent datasets indicated that REP(LE) and REP(IG) were the best to predict leaf pigment concentrations. The R2 of chlorophyll a, chlorophyll a + b, and Car for REP(LE) were 0.805, 0.744 and 0.588, with the RE being 9.0%, 9.7% and 14.6%, respectively, and the R2 and RE of chlorophyll b for REP(IG) were 0.632 and 18.2%, respectively. It was suggested that the red-edge parameters of hyper-spectral reflectance had stable relationships with the pigment concentrations in wheat leaves, and especially, REP(LE) could be used to reliably estimate the concentrations of leaf chlorophyll a and chlorophyll a + b.
authors.affiliation: Hi-Tech Key Laboratory of Information Agriculture of Jiangsu Province, Nanjing Agricultural University, Nanjing 210095, China. Feng-wei78@126.com
authors.forename: Wei
authors.initials: W
authors.lastname: Feng
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhu
authors.forename: Xia
authors.initials: X
authors.lastname: Yao
authors.forename: Yong-Chao
authors.initials: YC
authors.lastname: Tian
authors.forename: Xin-Feng
authors.initials: XF
authors.lastname: Yao
authors.forename: Wei-Xing
authors.initials: WX
authors.lastname: Cao
mesh_terms: D002734:Chlorophyll / Q000032:analysis*; D000077194:Chlorophyll A; D008962:Models, Theoretical; D018515:Plant Leaves / Q000737:chemistry / Q000254:growth & development / Q000378:metabolism*; D015203:Reproducibility of Results; D013057:Spectrum Analysis / Q000295:instrumentation / Q000379:methods*; D014908:Triticum / Q000737:chemistry / Q000254:growth & development / Q000378:metabolism*
chemical_list: D002734:Chlorophyll; C037184:chlorophyll b; D000077194:Chlorophyll A