tailieunhanh - Báo cáo khoa học: "The of near-infrared reflectance spectroscopy in litter decomposition studies"

Tuyển tập các báo cáo nghiên cứu về lâm nghiệp được đăng trên tạp chí lâm nghiệp quốc tế đề tài:"The of near-infrared reflectance spectroscopy in litter decomposition studies. | Ann Sci For 1992 49 481 -488 Elsevier INRA 481 Original article The use of near-infrared reflectance spectroscopy in litter decomposition studies R Joffre 1 D Gillon 1 p Dardenne 2 R Agneessens 2 R Biston 2 Centre d Ecologie Fonctionnelle et Evolutive CNRS BP 5051 34033 Montpellier Cedex France 2 CRA Gembloux station de Haute Belgique 100 rue de Serpont 6800 Libramont-Chevigny Belgium Received 12 March 1992 accepted 2 July 1992 Summary The biochemical nature of leaf litter is a key factor in regulation of its decomposition. Conventional wet chemical analysis of samples is destructive time-consuming and expensive. The objective of this study was to evaluate the potentiality of near infrared reflectance spectroscopy NIRS for determining litter chemistry during the decomposition process using a wide range of species and decomposition stages. The litter of 8 species of evergreen and deciduous broad-leaved trees conifers and shrubs were used in both laboratory and field experiments. Near-infrared reflectance measurements were made with an NIRS Systems 5000 spectrophotometer over the range 1100-2500 nm. Calibration samples were analysed for ash carbon and nitrogen. Acid-detergent fiber ADF and acid-detergent lignin ADL were determined using Van Soest procedures. Stepwise regression SR calibrations and partial least squares PLSR calibrations were developed and compared as well as the effect of scatter correction. The PLS algorithm was used to create the predictive models using all the information in the spectrum to determine the chemical concentration. Using scatter correction always gave better results. Both regression methods provided acceptable validation statistics for c N and ash. The PLSR had better prediction accuracy for ADF and ADL. For these two constituents the improvement of SECV was 34 and 25 respectively. Our results showed that NIRS is an effective tool to predict nitrogen ash and proximate carbon fractions in decomposition studies and that PSLR method .