《土壤学》课程教学资源（参考资料）A Leaf Layer Spectral Model for Estimating Protein.pdf

D. Li, Y. Liu, and Y. Chen (Eds.): CCTA 2010, Part IV, IFIP AICT 347, pp. 16–29, 2011. © IFIP International Federation for Information Processing 2011 A Leaf Layer Spectral Model for Estimating Protein Content of Wheat Grains Chun-Hua Xiao1,2, Shao-Kun Li1,2,3,*, Ke-Ru Wang1,2, Yan-Li Lu2 , Jun-Hua Bai2 , Rui-Zhi Xie2 , Shi-Ju Gao2 , Qiong Wang2 , and Fang-Yong Wang1 1 Key Laboratory of Oasis Ecology Agriculture of Xinjiang Construction Crop/ Center of Crop High-Yield Research, Shihezi 832003, Xinjiang, China 2 Institute of Crop Science, Chinese Academy of Agricultural Sciences / National Key Facility for Crop Gene Resources and Genetic Improvement, NFCRI, Beijing 100081, China 3 Department of Crop Culture, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R. China Tel.: +86-010-68918891 lishk@mail.caas.net.cn Abstract. The spectral signatures of crop canopies in the field provide much information relating morphological or quality characteristics of crops to their optical properties. This experiment was conducted using two winter-wheat (Triticum aestivum) cultivars, Jingdong8 (with erect leaves) and Zhongyou9507 (with horizontal leaves). We analysiced the relation between the direction spectral characteristics and the laeves nitrogen content(LNC). The result showed that the spectral information observed at the 0° angle mainly provided information on the upper canopy and the lower layer had little impact on their spectra. However, the spectral information observed at 30° and 60° angles reflected the whole canopy information and the status of the lower layer of the canopy had great effects on their spectra. Variance analysis indicated that the ear layer of canopy and the topmost leaf blade made greater contributions to CDS. The predicted grain protein content (GPC) model by leaf layers spectra using 0° view angle was the best with root mean squares (RMSE) of 0.7500 for Jingdong8 and 0.6461 for Zhongyou9507. The coefficients of determination, R2 between measured and estimated grain protein contents were 0.7467 and 0.7599. Thus, grain protein may be reliably predicted from the leaf layer spectral model. Keywords: wheat canopy, leaf distribution, direction spectra, view angle, model. 1 Introduction The spectral characteristics of a crop canopy are determined not only by biophysical and biochemical features and also plant structural attributes. Leaf optical properties are a main factor for canopy spectral. * Corresponding author

A Leaf Layer Spectral Model for Estimating Protein Content of Wheat Grains 17 Crop canopy spectral characteristics represent important info rmation needed to guide crop management.Crop composition and structure are difficult to assess by traditional spectral measurement with vertical canopy direction.The direction spectrum includes a great deal of crop canopy information.Multiangle data significantly improved the accuracy of recovering forest parameters when inverting 3-D optical models (Kimes et al.,2002)but forest vertical structure can not be accurately using angles with the 4 spect nde in the nadi vie all viev a singl band (Kimes ).Directi nal radiances in o near the principal plane of the sun provides informati on that leads to more accurate prediction of canopy structure parameters than from other azimuth planes(Gobron et al.,2000).Canopy emissivity increased with increasing view angle due to the greater proportion of vegetation observed at off-nadir view angles;when the proportion of leaves was lower than that of soil,canopy emissivity grew with increasing view angle (Sobrino et al 2005). It should be noted these models assume a Lambertian behaviour for soil and vegetation st Although vegetation surfaces show a near Lambertian behaviour bare soil surfaces do not and the angular variation on emissivity can not be neglected Lidars,multiangle radiometers,radars and imaging spectrometers have been identified as systems that can capture information in the vertical dimension.This requires a capability to remotely measure the vertical and spatial distribution of forest structural parameters that are needed for more accurate models of energy,carbon.and water flux ntal,and lobal scales.Thus. the utility of vertical w ea t structure note ser ing systems provided age o f the honzonta Iscope,but could not provide the vertical information on biochemical distribution in a crop canopy. thereby reducing the accuracy of measurement.Multi-angle data can increase the precision of forest parameters(Kimes,et al.,2006). The distribution of tissues in a crop canopy has certain characteristics-biochemical distribution is different because of transfer of matter during the growth stage.Leaves in a whe nopy are nder middle,upper layer nd layers(Wan et al.2004).The spectral characteristic differed among canopy leaves because of th different reflection and scatter,so their effect on canopy spectra was different (Wang etal.2004)】 Various biochemical (foliar lignin and nitrogen)and biophysical factors influencing canopy reflectance signatures have been studied in previous works.Information on biochemical paramete ers is important and the multi-angle spectra which provide informationo d directi ons can faci act pre parameters. there are n studies on the relative importar of vertica stribution of wheat leaves that determines canopy reflectance across the shortwave (350-2500nm)spectrum.The contribution of each leaf layer relative to all other factors has also not been adequately determined.Yet,it is the interaction of these factors. including their potential covariance or unique behavior,that must be understood if advances in remote sensing are to be achieved

A Leaf Layer Spectral Model for Estimating Protein Content of Wheat Grains 17 Crop canopy spectral characteristics represent important information needed to guide crop management. Crop composition and structure are difficult to assess by traditional spectral measurement with vertical canopy direction. The direction spectrum includes a great deal of crop canopy information. Multiangle data significantly improved the accuracy of recovering forest parameters when inverting 3-D optical models (Kimes et al., 2002) but forest vertical structure can not be captured accurately using only the 4 spectral bands in the nadir view or all view angles with a single spectral band (Kimes et al.,2006). Directional radiances in or near the principal plane of the sun provides information that leads to more accurate prediction of canopy structure parameters than from other azimuth planes (Gobron et al., 2000). Canopy emissivity increased with increasing view angle due to the greater proportion of vegetation observed at off-nadir view angles; when the proportion of leaves was lower than that of soil, canopy emissivity grew with increasing view angle (Sobrino et al., 2005). It should be noted that these models assume a Lambertian behaviour for soil and vegetation surfaces. Although vegetation surfaces show a near Lambertian behaviour, bare soil surfaces do not and the angular variation on emissivity can not be neglected. Lidars, multiangle radiometers, radars and imaging spectrometers have been identified as systems that can capture information in the vertical dimension. This requires a capability to remotely measure the vertical and spatial distribution of forest structural parameters that are needed for more accurate models of energy, carbon, and water flux over regional, continental, and global scales. Thus, we examined the utility of hyperspectral data for the quantitative characterization of vertical wheat structure. Most remote sensing systems provided an image of the horizontal scope, but could not provide the vertical information on biochemical distribution in a crop canopy, thereby reducing the accuracy of measurement. Multi-angle data can increase the precision of forest parameters (Kimes,et al., 2006). The distribution of tissues in a crop canopy has certain characteristics - biochemical distribution is different because of transfer of matter during the growth stage. Leaves in a wheat canopy are composed of under, middle, upper layer and ear layers (Wang et al.,2004). The spectral characteristic differed among canopy leaves because of the different reflection and scatter, so their effect on canopy spectra was different (Wang et al., 2004). Various biochemical (foliar lignin and nitrogen) and biophysical factors influencing canopy reflectance signatures have been studied in previous works. Information on biochemical parameters is important and the multi-angle spectra which provide information on different directions can facilitate a more exact prediction of biochemical parameters. To date, there are no studies on the relative importance of vertical distribution of wheat leaves that determines canopy reflectance across the shortwave (350–2500nm) spectrum. The contribution of each leaf layer relative to all other factors has also not been adequately determined. Yet, it is the interaction of these factors, including their potential covariance or unique behavior, that must be understood if advances in remote sensing are to be achieved

18 C.-H.Xiao et al In this study,the leaf slice method was used to characterize a wheat canopy,evaluate the spectral response of leaf vertical distribution in the canopy,determine the characteristics of spectral curve for different leaf layers and develop a methodology for predicting the biochemistry of the canopy. 2 Materials and Methods 2.1 Preliminary Experiment A field experiment was conducted in the Experimental Station of the Institute of Crop Science of the Chinese Academy of Agricultural Sciences,Beijing (3957'55"N. 11619'46"E)in the 2005-2006 growing season.The soil was a silt clay loam containing 1.16%organic matter,42.6 mg kg-lalkali-hydrolysable N.26.5 mg kg-1 available ph rus and 139.4 mg kg-1 a rail able pota Two winte at cultivars were used:Jingdong8,an erect leaf plant-type and Zhongyou9507,a lax leaf plant-type.Four N fertilizer (urea,46%N,)treatments were set up with four randomized replications of each cultivar:NO,no N fertilization,N1. 150 kg hm-2 pure N fertilization,N2,300 kg hm-2(rationally fertilized).N3,450 kg hm-2 (excessively fertilized).The N rates were applied in three splits at pre-sowing (50%of the total amount).reviving stage(25%of the total amount)and jointing stag (25%of the total an )All the tr tilized with the same PP205 144kghm-2) K (K20,75 kg h m-2)at pre-sowing The leaf slice method of wheat canopy:whole (plant)wheat samples 0.5m long and 0.8m wide were chosen;based on the vertical distribution of wheat canopy,the samples were measured off the whole wheat canopy (WWC).ear layer of canopy (ELC). inverse first leaves layer of canopy (ILLC-1).inverse second leaves layer of canopy(ILLC-2),inverse third leaves layers of canopy (ILLC-3)and inverse fourth leave s layer of canopy (ILLC-4).Canopy layers were s vered with a sciss ors from the ear layert lowe r layer (Fig.3). 2.2 Measured Traits and Methods All canopy spectral measurements were taken from a height of 1.3 m above ground (the height of the wheat was 90 cm at maturity),under clear sky conditions between 10:00 and 14:00(Beijing local time),usir 258ie0e r(Analytical Spectral Devic r.CO.USA optic operating in spectral region with a sampling interval of 14m between 350 and 1050 nm and 2 nm between 1050 and 2500 nm and with spectral resolutions of 3 nm at 700 nm and1o nm at 1400 nm.A 40 cm x40 cm BaSo4 calibration panel was used for calculation of reflectance.The spectra were measured with view angles of 0.30.60.90.120.150.and 180 to the line vertical to the wheat row using the Sim ple multi-angle sp ctral measurement e quipment(Fig.1)after eve was removed(N2 treatment).The model spectra were measured vith a view angle of

18 C.-H. Xiao et al. In this study, the leaf slice method was used to characterize a wheat canopy, evaluate the spectral response of leaf vertical distribution in the canopy, determine the characteristics of spectral curve for different leaf layers and develop a methodology for predicting the biochemistry of the canopy. 2 Materials and Methods 2.1 Preliminary Experiment A field experiment was conducted in the Experimental Station of the Institute of Crop Science of the Chinese Academy of Agricultural Sciences, Beijing (39º57'55" N, 116º19'46" E) in the 2005-2006 growing season. The soil was a silt clay loam containing 1.16% organic matter, 42.6 mg kg-1alkali-hydrolysable N, 26.5 mg kg-1 available phosphorus and 139.4 mg kg-1 available potassium. Two winter wheat cultivars were used: Jingdong8, an erect leaf plant-type and Zhongyou9507, a lax leaf plant-type. Four N fertilizer (urea, 46%N，) treatments were set up with four randomized replications of each cultivar: N0, no N fertilization, N1, 150 kg hm-2 pure N fertilization, N2, 300 kg hm-2 (rationally fertilized), N3, 450 kg hm-2 (excessively fertilized). The N rates were applied in three splits at pre-sowing (50% of the total amount), reviving stage (25% of the total amount) and jointing stage (25% of the total amount). All the treatments were fertilized with the same amounts of P (P2O5, 144 kg hm-2) and K (K2O, 75 kg hm-2) at pre-sowing. The leaf slice method of wheat canopy: whole (plant) wheat samples 0.5m long and 0.8m wide were chosen; based on the vertical distribution of wheat canopy, the samples were measured off the whole wheat canopy (WWC), ear layer of canopy (ELC), inverse first leaves layer of canopy (ILLC-1), inverse second leaves layer of canopy(ILLC-2), inverse third leaves layers of canopy (ILLC-3) and inverse fourth leaves layer of canopy (ILLC-4). Canopy layers were severed with a scissors from the ear layer to lower layer (Fig. 3). 2.2 Measured Traits and Methods All canopy spectral measurements were taken from a height of 1.3 m above ground (the height of the wheat was 90 cm at maturity), under clear sky conditions between 10:00 and 14:00 (Beijing local time), using an ASD FieldSpec Pro spectrometer (Analytical Spectral Devices, Boulder, CO,USA) fitted with a 258 field of view fiber optics, operating in the 350–2500 nm spectral region with a sampling interval of 1.4 nm between 350 and 1050 nm and 2 nm between 1050 and 2500 nm and with spectral resolutions of 3 nm at 700 nm and10 nm at 1400 nm. A 40 cm ×40 cm BaSO4 calibration panel was used for calculation of reflectance. The spectra were measured with view angles of 0, 30,60,90,120, 150, and 180° to the line vertical to the wheat row using the Simple multi-angle spectral measurement equipment (Fig.1) after every layer was removed (N2 treatment). The model spectra were measured with a view angle of 0°