"A number of derivatives and alternatives to NDVI have been proposed in the scientific literature to address these limitations, including the Perpendicular Vegetation Index,[13] the Soil-Adjusted Vegetation Index,[14] the Atmospherically Resistant Vegetation Index[15] and the Global Environment Monitoring Index.[16] Each of these attempted to include intrinsic correction(s) for one or more perturbing factors. It is not until the mid-1990s, however, that a new generation of algorithms were proposed to estimate directly the biogeophysical variables of interest (e.g., the Fraction of Absorbed Photosynthetically Active Radiation or FAPAR), taking advantage of the enhanced performance and characteristics of modern sensors (in particular their multispectral and multiangular capabilities) to take all the perturbing factors into account. "

Source: https://en.wikipedia.org/wiki/Normalized_difference_vegetation_index

I like the NDRE (Normalized Difference Red-Edge) vegetation index, used in-field for active proximal terrestrial reflectometry sampling that supports canopy level plant phenotyping. The Red-edge portion of the optical spectrum (centered at perhaps 720 or 730 nm) appears more sensitive and saturates less than does the traditional Red color (perhaps centered around 670 nm) in the normalized difference ratio.

In addition to Matthew M. Conley comment,

the REIP has shown linear sensitivity to leaf area index of wheat based on ground level spectral data (paper attached).

Article LAI assessment of wheat and potato crops by VENμS and Sentinel-2 bands

For the accuracy to which NDVI correlates with chlorophyll content, it may also play a role what sensors you use in what kind of setup. Also, whether you use proximal or remote sensing methods. And ultimately, what knd of resolution your setup has and how you realize the measurement (time series or point measurements? Plots, single plants or plant parts?).

Besides these, have you validated chlorophyll contents based on wet-chemistry analysis with your image/sensor data to check for biological variations?

A very simple VI that sometimes yields good correlations is the greenness index. Can be obtained with simple ccd cameras.

Pigments of leaves and plant tissues involved in the oxygen type of photosynthesis: chlorophyll-a, chlorophyll-b, carotenoids

NDVI is a linear index, so it exhibits a saturation effect. NDVI takes into account changes in the spectrum of only part of chlorophyll - a, - в. Changes in carotenoids are not taken into account, therefore. NDVI cannot be an indicator of plant stress. NDVI sees only severe damage to the plant biomass.

Dear Vjacheslav Fisenko,

In our region (drylands), we found that the results of the MSAVI2 and GDVI indices are working better than the NDVI.

Good luck and best regards.

Under heat stress, we have good sensitivity with the content of chlorophyll (-a, -b) in C-3 plants showed MTVI2.

I like the direction of research: .. Article Exploring the potential of leaf reflectance spectra for retr...

find the relationship of reflection from chlorophyll concentration and key photosynthetic parameter -The maximum carboxylation rate (Vcmax).

But the range of crop variation in Figure 1 of the article is very small in the range of 800-1000 nm: 0.1 reflectance. Look at our data on wheat growth in the range of 800-1000 nm: 0.7 change in reflectance.

https://www.researchgate.net/project/Remote-Sensing-of-plant-communities-agricultural-crops/update/5d7e1c30cfe4a7968dcb7e2a