*3.3. Relationships Between DLARI and Peanut LCC*

3.3.1. Performance of DLARIs Incorporating Wavelengths Between 660 and 750 nm

Because the most robust wavelength region was between 660 nm and 750 nm in the case of the MDATT, all possible DLARI combinations formed by Equation (3) using wavelengths from 660 nm to 750 nm were calculated. According to the principle of selecting the index that demonstrated the highest *R*2, optimal DLARIs were established for each dataset (Table 4). The results demonstrated that the wavelengths used in the DLARIs were similar to those used in the MDATTs (Table 2). When compared with the MDATTs for the adaxial surface, the DLARI did not improve retrieval accuracy (RMSEcv = 2.53), the DLARI for the abaxial surface demonstrated a marginal advantage over the abaxial MDATT (RMSEcv = 2.62). In the case of the bifacial dataset, the DLARI achieved some improvement over the bifacial MDATT (RMSEcv = 3.34).

**Table 4.** Cross-validation results for the optimal dorsiventral leaf adjusted ratio indices (DLARIs) derived using wavelengths between 660 and 750 nm in the case of the adaxial, abaxial, and bifacial datasets.


3.3.2. Performance of DLARIs Incorporating Wavelengths Over 750 nm

In the DLARIs for the bifacial dataset, the wavelength selected for λ<sup>4</sup> was at the limit of the considered region (i.e., 750 nm), indicating that relevant information might be contained at longer wavelengths. When evaluated, DLARIs incorporating longer wavelengths (around 820 nm) achieved higher retrieval accuracies than those described in Section 3.3.1. (Table 5). It showed that for the three datasets, the optimal wavelengths of λ<sup>1</sup> and λ<sup>3</sup> moved to approximately 730 nm and 720 nm, where the differences in adaxial and abaxial reflectance were less than 5% (Figure 2). The optimal location of λ<sup>2</sup> moved to the red-edge shoulder, which means less sensitivity to leaf structure [42], while the optimal location of λ<sup>4</sup> moved to the NIR, where there is less absorption by leaf pigments [12]. The new adaxial DLARI and abaxial DLARI demonstrated advantages over the DLARIs derived from reflectance over 660 and 750 nm (RMSEcv = 2.37; RMSEcv = 2.58). The new bifacial DLARI not only substantially improved the retrieval accuracy (RMSEcv = 2.81), but also enhanced its sensitivity to LCC (*R*<sup>2</sup> cv = 0.94).


**Table 5.** Cross-validation results for the optimal DLARIs derived using wavelengths between 660 and 820 nm in the case of the adaxial, abaxial, and bifacial datasets.

Relationships between LCC and the optimal DLARIs established are shown in Figure 7, as are scatter plots of the associated retrievals and observed values. For the adaxial and the abaxial datasets (Figure 7a,b,d,e), the indices (R735 − R753)/(R715 − R819) and (R731 − R755)/(R722 − R774) attained higher retrieval accuracies (*R*<sup>2</sup> cv = 0.96, RMSEcv = 2.37; *R*<sup>2</sup> cv = 0.95, RMSEcv = 2.58) than the MDATT indices (*R*<sup>2</sup> cv = 0.95, RMSEcv = 2.52; *R*<sup>2</sup> cv = 0.94, RMSEcv = 2.69). For the bifacial dataset (Figure 7e–f), the index (R732 <sup>−</sup> R754)/(R724 <sup>−</sup> R773) achieved an *R*<sup>2</sup> cv of 0.94 and RMSEcv of 2.81, demonstrating a substantial advantage over the bifacial MDATT index (*R*<sup>2</sup> cv = 0.91, RMSEcv = 3.53) and the DLARI derived using wavelengths shorter than 750 nm. The results revealed that the DLARIs incorporating longer wavelengths efficiently improved LCC estimation accuracy, whether for the adaxial, abaxial or bifacial datasets.

**Figure 7.** Relationships between optimal DLARI indices 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.
