Three‐band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves

Abstract

[1] Leaf pigment content and composition provide important information about plant physiological status. Reflectance measurements offer a rapid, nondestructive technique to estimate pigment content. This paper describes a recently developed three-band conceptual model capable of remotely estimating total of chlorophylls, carotenoids and anthocyanins contents in leaves from many tree and crop species. We tuned the spectral regions used in the model in accord with pigment of interest and the optical characteristics of the leaves studied, and showed that the developed technique allowed accurate estimation of total chlorophylls, carotenoids and anthocyanins, explaining more than 91%, 70% and 93% of pigment variation, respectively. This new technique shows a great potential for noninvasive tracking of the physiological status of vegetation and the impact of environmental changes.

Efficiency of chlorophyll in gross primary productivity: A proof of concept and application in crops

“…In the soybean canopy, leaf Chl is distributed more evenly than in maize canopy. The light transmitted by the uppermost soybean leaf layer inside the canopy is only 1-2% in the blue and red ranges of the spectrum and does not exceed 3-5% in the green (Gitelson et al, 2006a). The "closed" soybean canopy structure and lower light inside the canopy (as compared to that of maize at moderate to high canopy density) may be one of the reasons for the lower chlorophyll efficiency in soybean, due to documented diminishing returns from N investment at low light conditions (Gulman and Chu, 1981).…”

“…The analysis of chlorophyll efficiency is particularly suitable because non-destructive and remote techniques are readily available to effectively and accurately assess the amount of Chl present at multiple scales, from leaves (Gitelson and Merzlyak, 1997;Gitelson et al, 2006a;Fassnacht et al, 2015;Kira et al, 2015) to entire canopies (Dash and Curran, 2004;Gitelson et al, 2005;Clevers and Gitelson, 2013). Thus, given that limitations due to scaling are reduced, the use of models based on chlorophyll efficiency may allow more direct assessments of plant optimization patterns under different environmental conditions, and in different species/plant functional types.…”

Non-destructive determination of maize leaf and canopy chlorophyll content

“…Specific objectives were (1) to calibrate and validate a reflectance-based non-destructive technique (Gitelson and Merzlyak, 1994;Gitelson et al, 2003Gitelson et al, , 2006b) to estimate leaf Chl in maize; (2) to quantify the relative contribution of each leaf Chl to the total Chl in the canopy; and (3) to establish a relationship between leaf Chl content and total Chl in a maize canopy. Once the plants were selected, the position of the collar or ear leaf was identified.…”

“…One of the models, so-called Red Edge Chlorophyll Index, Clred edge, was suggested for Chl determination in both anthocyanin-containing and anthocyanin-free Leaves (Gitelson et al, 2006b). Clred edge was tested in this study; it is based on reflectances in the red edge (Rred edge) and near infrared (RNIR) wavebands and defined as:…”

Multiple drivers of seasonal change in PRI: Implications for photosynthesis 2. Stand level

“…RMSE of Chl content prediction by CI red edge was 38 mg m -2 in the range of Chl content 22-880 mg m -2 by (details in Gitelson et al, 2003Gitelson et al, , 2006Ciganda et al, 2009). The stand reflectance measurements and ground measurements were not always concurrent and, since LAI and leaf Chl content changed gradually, spline interpolations were taken between destructive LAI sampling dates for each field in each year using Matlab (V. 7.9.0.529, The MathWorks, Massachusetts, USA) (Nguy-Robertson et al, 2012).…”