Assessment of carotenoids (Car) content provides a valuable insight into clarifying the mechanisms of plant photoprotection and light-adaption and is critical for stress diagnoses in plants. Due to their small proportion in the overall total pigment content and to the overlapping of spectral absorption features with chlorophylls (Chl) in the blue region of the spectrum, accurate estimation of Car content in plants, from remotely sensed data, is challenging. Previous studies made progress in Car content estimation at both the leaf and canopy level with remote sensing techniques. However, established spectral indices and methods for Car estimation in most studies that generally rely on specific and limited measured data might lack predictive accuracy for Car estimation and lack sensitivity to low or high Car content in various species and at different growth stages. In this chapter, a new carotenoid index (CARI) was proposed for foliar Car assessment with abundant simulated leaf data and various measured leaf reflectances. Detailed analysis on the mechanism, formation and performance of the new spectral index on Car retrieval was presented. Analysis results suggested that accurate nondestructive estimation of foliar Car content with CARI could be achieved at the leaf scale, through remote sensing techniques.
Part of the book: Progress in Carotenoid Research
Precise estimation of leaf chlorophyll content (LCC) and leaf water content (LWC) of soybean, using remote sensing technology, provides a new avenue for the nondestructive evaluation of inoculation effects of arbuscular mycorrhizal fungi (AMF) and Bradyrhizobium japonicum (BJ) on soybean growth condition. In this study, a series of pot experiments were conducted in the greenhouse, soybean inoculated with Glomus intraradices (G.i, one of AMF species), G.i and BJ, and non-inoculation were planted under drought stress (DS) and normal irrigation (NI) conditions. Leaf spectra and LCC and LWC were measured on the 28th and 56th days after inoculation. Two new simple ratio (SR) indices, derived from the first derivative spectral reflectance at λ1 nm (Dλ1) and the raw spectral reflectance at λ2 nm (Rλ2), were developed to estimate LCC and LWC. The results indicate that under DS, plants inoculated with G.i had higher LCC and LWC than the non-inoculated plants, followed by the counterparts co-inoculated with G.i and BJ. Linear estimation models, established by the D650/Rred edge and D1680/R680, achieved great improved accuracy for quantifying LCC and LWC of soybean under inoculation and drought stress treatments, with determination of coefficient of 0.63 and 0.76, respectively.
Part of the book: Soybean for Human Consumption and Animal Feed