Literature DB >> 17033768

Near-infrared reflectance spectroscopy as a fast and non-destructive tool to predict foliar organic constituents of several woody species.

C Petisco1, B García-Criado, S Mediavilla, B R Vázquez de Aldana, I Zabalgogeazcoa, A García-Ciudad.   

Abstract

Near-infrared reflectance spectroscopy (NIRS) was used to estimate N, neutral detergent fibre (NDF), acid detergent fibre (ADF), lignin and cellulose contents in leaves of a heterogeneous group of 17 woody species from the Central Western region of the Iberian Peninsula. The sample set consisted of 182 samples of leaves of deciduous and evergreen species, showing a wide range of concentrations determined by reference methods: 6.60-35.2 g kg-1 (N), 15.5-66.0% (NDF), 10.2-57.3% (ADF), 3.45-27.4% (lignin) and 5.79-31.3% (cellulose). Reflectance spectra, obtained for samples of dried and ground leaves, were recorded as log1/R (R=reflectance) from 1,100 to 2,500 nm. NIRS calibrations were developed using multiple linear (MLR) and partial least-squares (PLSR) regressions, and tested by external validation. Spectral data were transformed to the first and second derivative (1D, 2D). The PLSR method and derivative transformations provided the best statistics and showed lower standard errors of calibration (SEC) and higher coefficients of multiple determination (R2). In the external validation the standard errors of prediction (SEP) were 0.76 g kg-1 (N), 2.11% (NDF), 1.47% (ADF), 0.85% (lignin) and 0.86% (cellulose). The results obtained show that NIRS is very effective for the estimation of these organic constituents in leaf tissue of woody species. This technique can be used in ecological or ecophysiological studies as an alternative to the more time-consuming standard methods.

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Year:  2006        PMID: 17033768     DOI: 10.1007/s00216-006-0816-4

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  8 in total

1.  Quantification of Salicylates and Flavonoids in Poplar Bark and Leaves Based on IR, NIR, and Raman Spectra.

Authors:  Sylwester Mazurek; Maciej Włodarczyk; Sonia Pielorz; Piotr Okińczyc; Piotr M Kuś; Gabriela Długosz; Diana Vidal-Yañez; Roman Szostak
Journal:  Molecules       Date:  2022-06-20       Impact factor: 4.927

2.  Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature.

Authors:  Shawn P Serbin; Dylan N Dillaway; Eric L Kruger; Philip A Townsend
Journal:  J Exp Bot       Date:  2011-10-06       Impact factor: 6.992

3.  Fine root lignin content is well predictable with near-infrared spectroscopy.

Authors:  Oliver Elle; Ronny Richter; Michael Vohland; Alexandra Weigelt
Journal:  Sci Rep       Date:  2019-04-23       Impact factor: 4.379

4.  Analysis of the Acid Detergent Fibre Content in Turnip Greens and Turnip Tops (Brassica rapa L. Subsp. rapa) by Means of Near-Infrared Reflectance.

Authors:  Sara Obregón-Cano; Rafael Moreno-Rojas; Ana María Jurado-Millán; María Elena Cartea-González; Antonio De Haro-Bailón
Journal:  Foods       Date:  2019-08-26

5.  The mechanisms and prediction of non-structural carbohydrates accretion and depletion after mechanical wounding in slash pine (Pinus elliottii) using near-infrared reflectance spectroscopy.

Authors:  Yanjie Li; Honggang Sun; Thiago de Paula Protásio; Paulo Ricardo Gherardi Hein; Baoguo Du
Journal:  Plant Methods       Date:  2022-09-01       Impact factor: 5.827

6.  Advances in the genetic dissection of plant cell walls: tools and resources available in Miscanthus.

Authors:  Gancho Slavov; Gordon Allison; Maurice Bosch
Journal:  Front Plant Sci       Date:  2013-07-04       Impact factor: 5.753

7.  Early Detection of Sage (Salvia officinalis L.) Responses to Ozone Using Reflectance Spectroscopy.

Authors:  Alessandra Marchica; Silvia Loré; Lorenzo Cotrozzi; Giacomo Lorenzini; Cristina Nali; Elisa Pellegrini; Damiano Remorini
Journal:  Plants (Basel)       Date:  2019-09-12

8.  Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models.

Authors:  Ma Luisa Buchaillot; David Soba; Tianchu Shu; Juan Liu; Iker Aranjuelo; José Luis Araus; G Brett Runion; Stephen A Prior; Shawn C Kefauver; Alvaro Sanz-Saez
Journal:  Planta       Date:  2022-03-24       Impact factor: 4.540

  8 in total

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