**2.2. Field measurements**

#### *2.2.1. Reflectance spectrum measurements*

On each sampling date, a 1 × 1 m area of winter wheat was first selected for canopy reflectance measurements, with an Analytical Spectral Devices (ASD) FieldSpec spectrometer (Analytical Spectral Devices, Inc., Boulder, CO, USA) under clear, blue-sky conditions between 10:00 and 14:00 h (Beijing Local Time). Measurements were obtained from a nadir position at approximately 1.3 m above the wheat canopy and taken by averaging 10 scans. Reflectance spectra were derived relative to a 0.4 × 0.4 m white reference panel, which was placed horizontally just above the wheat canopy.

Crop aboveground biomass from the 1 m2 area was collected immediately after canopy spectral measurements, kept in a portable refrigerator and then transferred to a laboratory for leaf reflectance measurement and biochemical analysis. Leaf spectra were obtained using the ASD spectrometer coupled with a Li-Cor 1800-12 integration sphere (Li-Cor, Inc., Lincoln, NE, USA). For each leaf sample, measurements were made on five different areas (avoiding leaf veins). The sample was illuminated by a focused beam, which was produced by a Li-Cor 787 halogen lamp light source (6 V, 10 W, 3100 K), and the radiation that was captured by the spectrometer was the average reflected radiation within the Li-Cor 1800-12 integration sphere [28].

#### *2.2.2. Plant measurements*

Laboratory analyses were made on the 1 m<sup>2</sup> quadrat wheat samples just after leaf spectral measurement. LCar, leaf dry mass and LAI were measured according to standard procedures. Leaf dry mass was determined drying the samples in an oven at 70°C for 48 h, leaf Car content was determined using an L6 ultraviolet-visible spectrophotometer (INESA, China). Chlorophyll a (Chl a), chlorophyll b (Chl b) and total carotenoids' (Car) concentrations were calculated with Eqs. (1) to (3) [29]; the unit of total carotenoids could then be converted into content unit, that is, mass per unit leaf dry weight (mg/g), and concentration unit, that is, mass per unit leaf area (μg/cm2 ), using data on the volume of leaf pigment extract, the leaf dry weight and the leaf disc area, with Eqs. (4) and (5):

$$\text{Chla (mg/L)} = 12.21 \times \text{A}\_{66} - 2.81 \times \text{A}\_{646} \tag{1}$$

$$\text{Child (mg/L)} = 20.13 \times \text{A}\_{\text{e46}} - 5.03 \times \text{A}\_{\text{e63}} \tag{2}$$

$$\text{Car (mg/L)} = \{1000 \times \text{A}\_{470} - 3.27 \times \text{C} \& a - 104 \times \text{C} \& b\} / 229 \tag{3}$$

$$\text{Car (mg/g)} = \left[ \text{Cor(mg/L)} \times V\_T \text{(ml)} \right] / \left[ \text{DW} \left( \text{\%} \right) \times 1000 \right] \tag{4}$$

$$\text{Car}\left(\mu\text{g/cm}^2\right) = \left[\text{Cor}(\text{mg/g}) \times \text{DW}(\text{g})\right] / \text{leaf}\,\text{area}(\text{cm}^2) \tag{5}$$

where A*X* is the absorbance of the extract solution at wavelength x, VT (ml) is the volume of leaf pigment extract solution and DW (g) is the leaf dry weight.

LAI was determined using a dry weight method [30]. Leaf segments of approximate area 0.06 m<sup>2</sup> were cut from the central part of about 30 leaves selected from all the green leaves in the 1 m2 quadrat as standard leaves for LAI calculation. Both the standard leaves and the remaining leaves were oven dried at 70°C to constant weight and weighed. LAI was calculated as Eq. (6):

$$\text{LAI} = \langle \mathcal{S}\_r \times \mathcal{W}\_i \rangle / \langle \mathcal{S}\_i \times \mathcal{W}\_i \rangle \tag{6}$$

where *Sr* (m2 ) is the area of the standard leaves, *Wt* (g) is the total dry weight of the 1 m2 quadrat sampled leaves, *Sl* is the sampled land area (m2 ) and *Wr* (g) is the dry weight of the standard leaves.

#### **2.3. ANGERS dataset**

**2. Materials and methods**

A field experiment was designed and conducted in 2004 to collect measured data at both the leaf and canopy level for foliar Car content assessment. The experiment site was located at the National Experimental Station for Precision Agriculture (40°10.6′ N, 116°26.3′ E), Beijing, China. Winter wheat (*Triticum aestivum* L.) was used in this experiment, and 21 cultivars of winter wheat were grown in plots of 30 × 5.4 m size in the experiment site. Fertilization and irrigation were applied according to local standard practice so as to provide nonlimiting conditions. During the whole growing season, field measurements were conducted on specific growth stages including booting (April 28), head emergence (May 11), pollination (May 28) and milk development (June 08). For each growth period, different cultivars were used for sampling at both the canopy and leaf levels.

On each sampling date, a 1 × 1 m area of winter wheat was first selected for canopy reflectance measurements, with an Analytical Spectral Devices (ASD) FieldSpec spectrometer (Analytical Spectral Devices, Inc., Boulder, CO, USA) under clear, blue-sky conditions between 10:00 and 14:00 h (Beijing Local Time). Measurements were obtained from a nadir position at approximately 1.3 m above the wheat canopy and taken by averaging 10 scans. Reflectance spectra were derived relative to a 0.4 × 0.4 m white reference panel, which was placed horizontally

tral measurements, kept in a portable refrigerator and then transferred to a laboratory for leaf reflectance measurement and biochemical analysis. Leaf spectra were obtained using the ASD spectrometer coupled with a Li-Cor 1800-12 integration sphere (Li-Cor, Inc., Lincoln, NE, USA). For each leaf sample, measurements were made on five different areas (avoiding leaf veins). The sample was illuminated by a focused beam, which was produced by a Li-Cor 787 halogen lamp light source (6 V, 10 W, 3100 K), and the radiation that was captured by the spectrometer

measurement. LCar, leaf dry mass and LAI were measured according to standard procedures. Leaf dry mass was determined drying the samples in an oven at 70°C for 48 h, leaf Car content was determined using an L6 ultraviolet-visible spectrophotometer (INESA, China). Chlorophyll a (Chl a), chlorophyll b (Chl b) and total carotenoids' (Car) concentrations were calculated with Eqs. (1) to (3) [29]; the unit of total carotenoids could then be converted into content unit, that is, mass per unit leaf dry weight (mg/g), and concentration unit, that is,

was the average reflected radiation within the Li-Cor 1800-12 integration sphere [28].

area was collected immediately after canopy spec-

quadrat wheat samples just after leaf spectral

), using data on the volume of leaf pigment extract, the leaf dry

**2.1. Field experiment**

200 Progress in Carotenoid Research

**2.2. Field measurements**

just above the wheat canopy.

*2.2.2. Plant measurements*

mass per unit leaf area (μg/cm2

*2.2.1. Reflectance spectrum measurements*

Crop aboveground biomass from the 1 m2

Laboratory analyses were made on the 1 m<sup>2</sup>

weight and the leaf disc area, with Eqs. (4) and (5):

Besides the winter wheat measured data, the ANGERS dataset, which contains various plant species and different growth conditions, was also used. The dataset was collected in 2003 on temperate plants at the National Institute for Agricultural Research (INRA), ANGERS, France. It contains leaf directional-hemispherical reflectance and transmittance spectra measured at 1 nm resolution from 400 to 2400 nm using ASD FieldSpec instruments equipped with integrating spheres. Chlorophyll *a* and *b* (Chl), total carotenoids (Car), water (also named equivalent water thickness (EWT)) and dry matter (also named leaf mass per area (LMA)) content are available for each sample [18].

#### **2.4. Simulated datasets**

PROSPECT-5 simulates leaf directional-hemispherical reflectance and transmittance from 400 to 2500 nm with six input variables: LChl, LCar, LMA, EWT, leaf structure parameter (N) and brown pigments (Cbrown). Generally, pigments absorb light in the visible range (400– 760 nm), whereas water has a high absorbance in the near-infrared band (1000–2500 nm). Dry matter and refractive index variations extend through the whole wave range (400–2500 nm) [18]. Since the goal was to estimate leaf Car content mainly from visible wavebands, and the


**Table 1.** Input parameters for PROSPECT-5 and 4SAIL models used for leaf and canopy reflectance modeling.

visible range was unaffected by EWT, the EWT value was kept fixed at the average EWT value of ANGERS dataset. The range of variation of LChl, LCar, N and LMA obtained from ANGERS dataset was used in simulations. Detailed values for the input parameters used in PROSPECT-5 simulations are shown in **Table 1**.

500–540 nm for Car, and band 521 nm showed the maximum correlation, suggesting that reflectance in this range is very sensitive to Car content [11]. Besides, the range of its maximum sensitivity overlapped with Chl absorption features (**Figure 1a**). For Chl, the correlation extended from 400 to 760 nm and two strong correlation peaks were observed in green and red-edge regions. To establish a new spectral index for LCar estimation, Band 521 nm was chosen on the consideration that it had the highest correlation with LCar (R<sup>2</sup> = 0.607, RMSE = 3.144 μg/cm<sup>2</sup>

**Spectral index Equation Reference** Ratio analysis of reflectance spectra (RARS*c*) R760/R500 [12] Pigment specific simple ratio (PSSR*c*) R800/R470 [14] Pigment specific normalized difference (PSND*c*) (R800 − R470)/(R800 + R470) [14] Reflectance band ratio index (RBRI) R672/(R550 × R708) [13] Plant senescence reflectance index (PSRI) (R678 − R500)/R750 [8]

Red-edge carotenoid index (CARred edge) [(R510)−1 − (R700)−1] × R770 [15] Green carotenoid index (CARgreen) [(R510)−1 − (R550)−1] × R770 [15] Photochemical reflectance index (PRI) (R570 − R531)/(R570 + R531) [31] Modified photochemical reflectance index (PRIm1) (R512 − R531)/(R512 + R531) [32] Simple ratio (SRcar) R515/R570 [16] Carotenoid index (CARI) R720/R521 − 1 [33]

Carotenoid reflectance index (CRI550) (R510)−1 − (R550)

Carotenoid reflectance index (CRI700) (R510)−1 − (R700)

**Figure 1b**), although a strong correlation with LChl also existed. Band 720 nm was selected to reduce the influence of Chl on LCar estimation since it showed the highest relationship with

R720/R521–1) was then established, based on the formula of chlorophyll indices (i.e., CIred-edge and CIgreen). Simulated and measured datasets were then used to investigate its capability and

Linear regression models between leaf carotenoids content and spectral indices derived from simulated and measured datasets were obtained using the SPSS 18.0 software (SPSS Inc., Chicago, IL). A k-fold (k = 6) cross-validation procedure was used to evaluate the performance of spectral index methods using ANGERS and experimental data, and all the selected spectral indices were tested using the same k-fold partitions. The overall performances of these mod-

els were evaluated by statistics including a coefficient of determination (R<sup>2</sup>

error (RMSE), relative RMSE (RRMSE) and mean absolute error (MAE).

, **Figure 1c**). The proposed new carotenoid index (CARI,

−1 [11]

Monitoring Crop Carotenoids Concentration by Remote Sensing

http://dx.doi.org/10.5772/intechopen.78239

203

−1 [11]

LChl (R<sup>2</sup> = 0.906, RMSE = 7.981 μg/cm<sup>2</sup>

R*λ* is the reflectance value at wavelength *λ*.

**Table 2.** Spectral indices selected for LCar assessment.

robustness for LCar assessment.

**2.6. Statistics analysis**

,

), root mean square

With PROSPECT-5 model, 2500 leaf reflectance simulations could be obtained by random combination of the parameters values. To avoid unrealistic combinations, we made use of the content ratio of Car to Chl to restrain the combinations. Statistics of the content ratio of Car to Chl in the ANGERS data show that the ratio values ranging from 0.1 to 0.6 account for 97% of the samples. This criterion was then used to eliminate invalid combinations and finally 1700 leaf reflectance were kept. To investigate the effect of LAI and soil background on LCar assessment, LAI values were set to change from 1 to 8 with a step of 1; soil moisture parameter values were set to vary from 0 to 1 with a step of 0.5. Other input variables were fixed and defined based on [26]. Input values used for 4SAIL are shown in **Table 1**. Then, 40,800 canopy reflectance were obtained using the PROSAIL model.

#### **2.5. Spectral indices**

Published spectral indices for Car content assessment were summarized in **Table 2**. In addition to these existing spectral indices, a new spectral index for foliar Car content estimation was proposed based on the spectral absorption features of Car and Chl observed with the leaf level simulated dataset. The correlation between Car and Chl with reflectance ranging from 400 to 800 nm was first investigated. **Figure 1a** shows that the correlation peak region is located in the range


**Table 2.** Spectral indices selected for LCar assessment.

500–540 nm for Car, and band 521 nm showed the maximum correlation, suggesting that reflectance in this range is very sensitive to Car content [11]. Besides, the range of its maximum sensitivity overlapped with Chl absorption features (**Figure 1a**). For Chl, the correlation extended from 400 to 760 nm and two strong correlation peaks were observed in green and red-edge regions.

To establish a new spectral index for LCar estimation, Band 521 nm was chosen on the consideration that it had the highest correlation with LCar (R<sup>2</sup> = 0.607, RMSE = 3.144 μg/cm<sup>2</sup> , **Figure 1b**), although a strong correlation with LChl also existed. Band 720 nm was selected to reduce the influence of Chl on LCar estimation since it showed the highest relationship with LChl (R<sup>2</sup> = 0.906, RMSE = 7.981 μg/cm<sup>2</sup> , **Figure 1c**). The proposed new carotenoid index (CARI, R720/R521–1) was then established, based on the formula of chlorophyll indices (i.e., CIred-edge and CIgreen). Simulated and measured datasets were then used to investigate its capability and robustness for LCar assessment.

#### **2.6. Statistics analysis**

visible range was unaffected by EWT, the EWT value was kept fixed at the average EWT value of ANGERS dataset. The range of variation of LChl, LCar, N and LMA obtained from ANGERS dataset was used in simulations. Detailed values for the input parameters used in

**Table 1.** Input parameters for PROSPECT-5 and 4SAIL models used for leaf and canopy reflectance modeling.

) 10/20/30/40/50/60/70/80/90/100

) 2/4/6/8/10/12/14/16/18/20

) 0.002/0.003/0.004/0.005/0.006

With PROSPECT-5 model, 2500 leaf reflectance simulations could be obtained by random combination of the parameters values. To avoid unrealistic combinations, we made use of the content ratio of Car to Chl to restrain the combinations. Statistics of the content ratio of Car to Chl in the ANGERS data show that the ratio values ranging from 0.1 to 0.6 account for 97% of the samples. This criterion was then used to eliminate invalid combinations and finally 1700 leaf reflectance were kept. To investigate the effect of LAI and soil background on LCar assessment, LAI values were set to change from 1 to 8 with a step of 1; soil moisture parameter values were set to vary from 0 to 1 with a step of 0.5. Other input variables were fixed and defined based on [26]. Input values used for 4SAIL are shown in **Table 1**. Then, 40,800 canopy

Published spectral indices for Car content assessment were summarized in **Table 2**. In addition to these existing spectral indices, a new spectral index for foliar Car content estimation was proposed based on the spectral absorption features of Car and Chl observed with the leaf level simulated dataset. The correlation between Car and Chl with reflectance ranging from 400 to 800 nm was first investigated. **Figure 1a** shows that the correlation peak region is located in the range

PROSPECT-5 simulations are shown in **Table 1**.

**Models Parameters Values**

Leaf carotenoid content (LCar, μg/cm<sup>2</sup>

4SAIL Leaf area index (LAI) 1/2/3/4/5/6/7/8

Leaf mass per area (LMA, g/cm<sup>2</sup>

Leaf structure parameter (N) 1.6/1.7/1.8/1.9/2.0

Equivalent water thickness (EWT, cm) 0.012 Brown pigments (Cbrown) 0

Leaf angle distribution (LAD) Spherical Soil moisture parameter (Psoil) 0/0.5/1 Solar zenith angle (SZA, °) 30 View zenith angle (VZA, °) 0 View azimuth angle (VAA, °) 0 Fraction of diffuse incident radiation 0.23 Hot spot effect 0.15

PROSPECT-5 Leaf chlorophyll content (LChl, μg/cm<sup>2</sup>

202 Progress in Carotenoid Research

reflectance were obtained using the PROSAIL model.

**2.5. Spectral indices**

Linear regression models between leaf carotenoids content and spectral indices derived from simulated and measured datasets were obtained using the SPSS 18.0 software (SPSS Inc., Chicago, IL). A k-fold (k = 6) cross-validation procedure was used to evaluate the performance of spectral index methods using ANGERS and experimental data, and all the selected spectral indices were tested using the same k-fold partitions. The overall performances of these models were evaluated by statistics including a coefficient of determination (R<sup>2</sup> ), root mean square error (RMSE), relative RMSE (RRMSE) and mean absolute error (MAE).

**Figure 1.** (a) R2 curves for LCar (LChl) versus leaf reflectance within the wavelength range from 400 to 800 nm (b) Correlation between band 521 nm and LCar (c) Correlation between band 720 nm and LChl and (d) linear relationship between CARI and LCar.
