Use of near-infrared reflectance spectroscopy to predict the percentage of dead versus living grass roots

被引:1
作者
Catherine Picon-Cochard
Rémi Pilon
Sandrine Revaillot
Michel Jestin
Lorna Dawson
机构
[1] INRA,Grassland Ecosystem Research Team
[2] UR874,Unité de Recherche sur les Herbivores
[3] INRA,undefined
[4] UR1213,undefined
[5] Macaulay Institute,undefined
来源
Plant and Soil | 2009年 / 317卷
关键词
Grassland; NIRS; Roots; Species;
D O I
暂无
中图分类号
学科分类号
摘要
We tested the potential of near-infrared reflectance spectroscopy (NIRS) to predict the percentage of dead versus living roots of five grass species grown in monocultures under field conditions. Root death was induced after total severance of aboveground vegetation. Root samples were collected immediately after this treatment to obtain predominantly live roots (L), and then one (D1) and two months (D2) to obtain dead roots. NIRS spectra of L samples were different from D1 and D2 samples for four of the five species. The percentage of live and dead roots and root C and N were significantly predicted by NIRS. Validation of live and dead root percentage calibration was achieved with an error of prediction of 15%. These results show the potential of NIRS to predict the percentage of dead and live roots under field conditions and open up new opportunities in estimating more accurately below-ground net primary production of grasslands.
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页码:309 / 320
页数:11
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共 145 条
[1]  
Adams DE(1985)Nutrient and biomass allocation in five grass species in an Oklahoma tallgrass prairie Am Midl Nat 113 170-181
[2]  
Wallace LL(1989)Standard normal variate transformation and de-trending of near infrared diffuse reflectance spectra Appl Spectrosc 43 772-777
[3]  
Barnes RJ(1995)Near-infrared analysis as a rapid method to simultaneously evaluate several soil properties Soil Sci Soc Am J 59 364-372
[4]  
Dhanoa MS(2007)Determination of carbon and nitrogen contents in alfisols, oxisols and ultisols from Africa and Brazil using NIRS analysis :effects of sample grinding and set heterogeneity Geoderma 139 106-117
[5]  
Lister SJ(2001)Near-infrared reflectance spectroscopy-principal components regression analysis of soil properties Soil Sci Soc Am J 65 480-490
[6]  
Ben-Dor E(2007)Near-infrared spectroscopy for analysis of chemical and microbiological properties of forest soil organic horizons in a heavy-metal-polluted area Biol Fertil Soils 44 171-180
[7]  
Banin A(1990)Prediction of botanical composition using NIRS calibrations developed from botanically pure samples Crop Sci 30 202-207
[8]  
Brunet D(2000)Assessing root death and root system dynamics in a study of grape canopy pruning New Phytol 147 171-178
[9]  
Barthès BG(2003)Near infrared reflectance spectroscopy for determination of organic matter fractions including microbial biomass in coniferous forest soils Soil Biol Biochem 35 1587-1600
[10]  
Chotte JL(2006)Potential of near-infrared reflectance spectroscopy and chemometrics to predict soil organic carbon fractions Soil Tiller Res 85 78-85