*3.2. Relationships Between Optimal MDATT Indices and Peanut LCC*

The relationship between LCC and the MDATT using band combinations ranging from 400 nm to 1000 nm was assessed for each dataset. The maximum *R*<sup>2</sup> was determined by fixing λ<sup>2</sup> and λ<sup>3</sup> as single values and changing λ<sup>1</sup> from 400 nm to 1000 nm. For the sake of concise display, only *R*<sup>2</sup> values greater than 0.8 were considered and they are shown in Figure 5, where the *x*-axis represents λ<sup>3</sup> and the *y*-axis λ2. From this figure, robust wavelength regions for each band of the MDATT can be identified. For the adaxial dataset, the most sensitive region (red color in Figure 5a) ranged from 700 nm to 800 nm for λ2, 400 nm to 800 nm for λ3, and 650 nm to 750 nm for λ<sup>1</sup> (Figure 5d). The robust regions for the abaxial dataset were similar to those for the adaxial dataset (Figure 5b,e), but the most sensitive area (red color in Figure 5b) was reduced, and covered approximately 750 nm for λ2, 730 nm for λ3, and 690–750 nm for λ1. For the bifacial dataset (Figure 5c,e), the sensitive wavelength regions were further reduced. The *R*<sup>2</sup> values greater than 0.88 were demonstrated when λ<sup>2</sup> and λ<sup>3</sup> were between 700 nm to 750 nm and λ<sup>1</sup> was between 660 nm and 710 nm.

**Figure 5.** The maximum *R*<sup>2</sup> values associated with the MDATT band combinations ranging from 400 nm to 1000 nm (**a**–**c**) and its corresponding λ<sup>1</sup> (**d**–**f**). The left column is for the adaxial dataset, the middle column is for the abaxial dataset, and the right column is for the bifacial dataset. For the sake of concise display, only *R*<sup>2</sup> values greater than 0.8 were considered.

According to the principle of selecting indices demonstrating the highest *R*<sup>2</sup> values, three optimal MDATT indices for each dataset were determined and are presented in Table 2. The wavelengths λ1, λ2, and λ<sup>3</sup> of the best performing MDATT index for all three datasets were concentrated in the region of 701 to 747 nm. For the adaxial surface, the index incorporating reflectance values at 701 nm, 742 nm, and 740 nm demonstrated an *R*<sup>2</sup> of 0.95, whilst for the abaxial dataset, the best index incorporated reflectance values at 718 nm, 747 nm, and 720 nm (*R*<sup>2</sup> = 0.94). In the case of the bifacial dataset, the best index incorporated reflectance values at 723 nm, 738 nm, and 722 nm, reaching an *R*<sup>2</sup> of 0.91. The optimal indices for the adaxial and abaxial surfaces employed at least one wavelength that was highly correlated to LCC (*r* < −0.60), i.e., 701 nm, 718 nm, and 720 nm (Figure 4). The reflectance values at 722 nm and 723 nm, which were used by the optimal index for the bifacial dataset, demonstrated the minimum differences between adaxial and abaxial surfaces (Figure 2b).


**Table 2.** Cross-validation results for the MDATT indices in the case of the adaxial, abaxial, and bifacial datasets.

The linear models established using the MDATT indices are shown in Figure 6. They were randomly selected from one of the 50 training datasets used in the repeated 10 fold cross-validation. The results indicated that for the adaxial surface, the index (R701 − R742)/(R701 − R740) achieved the highest retrieval accuracy (*R*<sup>2</sup> cv = 0.95, RMSEcv = 2.52) (Figure 6a,d), followed by the index (R718 <sup>−</sup> R747)/(R718 <sup>−</sup> R720) for the abaxial surface (*R*<sup>2</sup> cv = 0.94, RMSEcv = 2.69) (Figure 6b,e). Both performed better than the index (R723 <sup>−</sup> R738)/(R723 <sup>−</sup> R722) for the bifacial dataset (*R*<sup>2</sup> cv = 0.91, RMSEcv = 3.53) (Figure 5c,f). The observed and predicted values fell close to the 1:1 line, indicating that the optimized MDATT indices were stable predictors of LCC. The optimal index for the bifacial dataset demonstrated a lower correlation with LCC and was not as accurate an LCC predicator as the other two indices.

**Figure 6.** Relationships between MDATTs and LCC (**a**–**c**) and scatter plots between observed LCC and LCC predicted by the associated linear models (**d**–**f**). The different colors indicate the 10 fold cross-validation subsets. The left column is for the adaxial dataset, the middle column is for the abaxial dataset, and the right column is for the bifacial dataset.

Differences in adaxial and abaxial reflectance properties resulted in different MDATT indices and associated retrieval accuracies. The reliability of applying the optimal index for the adaxial surface to estimate LCC from bifacial reflectance measurements was investigated (Table 3). It showed that compared to the bifacial MDATT, applying the adaxial MDATT to estimate LCC from bifacial reflectance produced considerable errors (*R*<sup>2</sup> cv = 0.87, RMSEcv = 4.14). In light of the errors, it was necessary to consider the influence of spectral differences between adaxial and abaxial sides when estimating LCC from reflectance mixed by the two sides.

**Table 3.** LCC retrieval accuracy of the adaxial and bifacial MDATT indices when applied to bifacial dataset.

