**5. Conclusions**

In this study, we focused on the development and optimization of dorsiventral leaf structure adjusted indices to minimize the impact of spectral differences between adaxial and abaxial leaf surfaces when retrieving peanut LCC. The wavelengths used by the MDATT were optimized for peanut, while a new dorsiventral leaf adjusted index was proposed to improve the LCC retrieval accuracy. The optimal MDATT index for retrieving LCC from bifacial reflectance measurements was (R723 <sup>−</sup> R738)/(R723 <sup>−</sup> R722) with an *R*<sup>2</sup> cv of 0.91 (RMSEcv = 3.53). The DLARI incorporated an additional wavelength in the NIR and exhibited the best retrieval accuracy when compared to the MDATT and other previously published indices. The DLARIs of (R735 − R753)/(R715 − R819) and (R732 − R754)/(R724 − R773) are recommended for retrieval of LCC using adaxial and bifacial reflectance, respectively. These two DLARIs delivered excellent cross-validation accuracies (*R*<sup>2</sup> cv = 0.96, RMSEcv = 2.37; R2 cv = 0.94, RMSEcv = 2.81). The effective wavelength regions for DLARI were from the red edge to the NIR. Compared to the MDATT, the DLARI showed stronger correlation to LCC and less sensitivity to abaxial surface structure. This research provided new insights into the impact of spectral differences between adaxial and abaxial leaf surfaces on LCC estimation and proposed DLARI to improve LCC retrieval accuracy. The spectral differences between adaxial and abaxial leaf surfaces should be considered when estimating peanut canopy parameters. Further studies should be carried out to verify the applicability of DLARI to other plant species which have similar physiological response to solar radiation and drought stress as peanut.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2072-4292/11/18/2148/s1, Figure S1: Photographs of peanut canopies in the field.

**Author Contributions:** Conceptualization, Y.D., M.X. and Z.W.; methodology, Y.D. and M.X.; formal analysis, M.X. and Y.D.; data curation, H.W.; writing—original draft preparation, M.X. and Y.D.; writing—review and editing, A.H., L.A.B., Q.X. and X.X.; funding acquisition, Z.W.

**Funding:** This research was funded by the National Key Research and Development Program of China, grant number 2016YFD0200102, the Technology Development Program of Jilin Province, China, grant number 20180201012GX and "The 13th Five-Year plan" Science and Technology Project of the Department of Education, Jilin Province, grant number JJKH20170915KJ.

**Acknowledgments:** The support provided by the China Scholarship Council (CSC) during a visit by Yanling Ding (No.201806625001) to the University of Technology Sydney is acknowledged. The authors would like to thank the editors and reviewers who handled our paper.

**Conflicts of Interest:** The authors declare no conflict of interest.
