Chlorophyll estimation in field crops: an assessment of handheld leaf meters and spectral reflectance measurements

2014 ◽  
Vol 153 (5) ◽  
pp. 876-890 ◽  
Author(s):  
R. CASA ◽  
F. CASTALDI ◽  
S. PASCUCCI ◽  
S. PIGNATTI

SUMMARYThe widespread adoption by agronomists and researchers of handheld leaf chlorophyll meters stimulates enquiries on instrumental calibration issues, given the necessity, for some applications, of inferring actual chlorophyll concentrations from the readings provided. This is especially required for recently developed and more innovative devices such as the Dualex (Force-A, France), which unlike the more common SPAD-502 (Minolta, Japan) has not undergone extensive (published) calibration tests. Additionally, devices for spectral reflectance measurements are also becoming increasingly available. In the present paper, the calibration of SPAD on maize (Zea mays L.) and of Dualex on winter wheat (Triticum aestivum L.), durum wheat (Triticum durum Desf.), horse bean (Vicia faba L.) and maize, was compared to spectral reflectance indices and full spectral information (400–2500 nm) acquired by a spectroradiometer (ASD FieldSpec) equipped with a contact probe and leaf clip. Full spectral data were exploited using partial least squares regression (PLSR). The measurements were performed in the field at Maccarese (Central Italy) in 2012, gathering a specific experimental dataset. The calibration models obtained on experimental data for SPAD (on maize) and Dualex (on four crops) showed intermediate or high estimation accuracy with root-mean-square error (RMSE) values ranging between 7 and 11 μg/cm2 depending on the species. These results were slightly better than those achieved using spectral reflectance indices, which were inferior though to those provided by PLSR using full spectral resolution. A synthetic database, generated by the physically based PROSPECT model, simulating hemispherical leaf reflectance and transmittance, was used to compare the performances of the reflectance indices and the chlorophyll meters for a wider range of leaf properties. The results confirmed the substantial equivalence of reflectance-based and transmittance-based (i.e. simulated SPAD and Dualex) indices and the advantage of exploiting the full spectral information, e.g. through PLSR, if available.

Crop Science ◽  
2006 ◽  
Vol 46 (2) ◽  
pp. 578-588 ◽  
Author(s):  
M. A. Babar ◽  
M. P. Reynolds ◽  
M. van Ginkel ◽  
A. R. Klatt ◽  
W. R. Raun ◽  
...  

Euphytica ◽  
2006 ◽  
Vol 150 (1-2) ◽  
pp. 155-172 ◽  
Author(s):  
M. A. Babar ◽  
M. van Ginkel ◽  
A. R. Klatt ◽  
B. Prasad ◽  
M. P. Reynolds

2009 ◽  
Vol 89 (3) ◽  
pp. 485-496 ◽  
Author(s):  
B. Prasad ◽  
M. A. Babar ◽  
B. F. Carver ◽  
W. R. Raun ◽  
A. R. Klatt

Increased biomass production could be an important criterion for future grain yield improvement in wheat (Triticum aestivum L.). Quick assessment of genetic variations for biomass production may become a useful tool for wheat breeders. The potential of using canopy spectral reflectance indices (SRI) to assess genetic variation for biomass production in winter wheat was evaluated. Three experiments were conducted for 2 yr (2003-2004 and 2004-2005) at Oklahoma State University, Stillwater, OK. The first experiment consisted of 25 winter wheat cultivars, and the other two experiments contained two sets of 25 F4:6 and F4:7 recombinant inbred lines from two crosses developed by breeding programs in the great plains of the United States of America. Three groups of SRI (vegetation-based, pigment-based, and water-based) were tested for their ability to assess biomass production at three growth stages (booting, heading, and grainfilling). The water index and the normalized water indices gave stronger genetic correlations (P < 0.01) and linear relationship for biomass production compared with the vegetation-based and pigment-based indices. The strong association of water-based indices with biomass was related to the canopy water content of the genotypes. Canopy water content was significantly (P < 0.05) correlated with biomass production. A strong positive association (P < 0.05) of grain yield and dry biomass was observed at the heading and grainfilling stages. Our study demonstrated the potential of using water-based SRI as a breeding tool to estimate genetic variability and identify genotypes with higher biomass production, and could eventually help to achieve higher grain yield in winter wheat. Key words: Wheat; biomass; grain yield; spectral reflectance index


2016 ◽  
Vol 6 (2) ◽  
pp. 221-230 ◽  
Author(s):  
Miloš Barták ◽  
Josef Hájek ◽  
Ana Carolina Amarillo ◽  
Jana Hazdrová ◽  
Hebe Carreras

Recently, spectral characteristics of lichens are in focus because of increasing number of spectral data applications in remote sensing of treeless polar and alpine regions. Therefore, species-specific spectral reflectance indices are measured in lichen species dominating polar ecosystems. Hydration status of the lichen thalli, as well as the presence of intrathalline secondary metabolites - which are UV-B absorbing compounds - both affects the spectral reflectance curves as well as numeric values of spectral reflectance indices. In the present paper, the reflectance spectra in 380-800 nm was measured in selected lichens to assess the effects of full hydration, and to evaluate the influence of secondary metabolites, they were wash out from lichen thalli with acetone (i.e. acetone rinsing) and then the spectra were also measured. For these experiments, Antarctic (Xanthoria elegans, Leptogium puberulum, Physconia muscigena and Rhizoplaca melanophthalma) and Argentinean lichens from mountain regions (Parmotrema conferendum and Ramalina celastri) were used. Changes in several spectral reflectance indices were evaluated and discussed in relation with hydration status and the absence of secondary metabolites. For the great majority of studied lichens, MCARI (Modified Chlorophyll Absorption in Reflectance Index) was the most effective index to reflect the changes between dry and wet state of thallus.


Crop Science ◽  
2019 ◽  
Vol 59 (5) ◽  
pp. 1927-1944 ◽  
Author(s):  
Leonardo Hinojosa ◽  
Neeraj Kumar ◽  
Kulvinder S. Gill ◽  
Kevin M. Murphy

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