Determination of Chemical and Biological Properties of Composts Using near Infrared Spectroscopy

Abstract

Successful use of compost to maintain plant health and soil fertility requires consistent monitoring of compost quality. For this purpose, near infrared (NIR) spectroscopy might be a useful alternative to standard procedures which are often time-consuming and laborious. Ninety-eight yard-waste compost samples were analysed by conventional methods and NIR spectroscopy. Reference analysis included the determination of age, organic C (C org ) and total N (N t ) contents, C / N ratio, microbial biomass (C mic ), the ratio of C mic to organic C (C mic / C org ), basal respiration, metabolic quotient (qCO 2 ), hydrolysis of fl uorescein diacetate (FDA-HR), specifi c enzyme activity, i.e. FDA-HR related to C mic , and suppression of pathogens. All samples were scanned in the visible light and near infrared regions (400-2500 nm). Cross-validation equations were developed using the whole spectrum (fi rst and second derivative) and a modifi ed partial least-square regression method. NIR predicted basal respiration and age successfully [ratio of standard deviation and standard error of cross-validation (RPD) was 4.3 or 2.9, respectively]. All other properties, i.e. C org and N t contents, C / N ratio, C mic , C mic / C org , qCO 2 , FDA-HR, specifi c enzyme activity and suppression of pathogens at an inoculation level of 5‰ related to rating or fresh weight, respectively, were predicted with moderate success (1.4 ≤ RPD ≤ 2.0). However, the coeffi cients of determination for specifi c enzyme activity and suppression of pathogens related to fresh weight were rather low (r² = 0.49 and 0.47, respectively). The results presented indicate that NIR spectroscopy is able to determine important compost quality parameters. However, further research is needed concerning the basis of and limitations for the determination of specifi c enzyme activity and suppressiveness by NIR spectroscopy.

Application of Multivariate Data Analyses in Waste Management

“…Michel et al [42] defined compost quality by C and N contents, suppression of pathogens, stability/ maturity and biological parameters, especially organic carbon (Corg), total N (Nt), C:N ratio, age, microbial biomass (Cmic), Cmic:Corg, basal respiration, enzymatic activity and suppression of plant disease. Spectroscopic data from 98 composts samples as well as the mentioned conventional parameters were collected.…”

“…Fundamental relations between two matrices can be found by means of PLS1. Michel et al [42] applied a PLS1 to express conventional parameters by spectral data. They designed for each conventional parameter a PLS1.…”

“…Albrecht et al [2] developed calibration models between spectral data and C, N, C:N ratio and composting time. Michel et al [42] predicted chemical and biological properties of composts such as organic C (Corg), total N, C:N ratio, age, microbial biomass (Cmic), Cmic:Corg, basal respiration, enzymatic activity and plant suppression using near infrared spectroscopy. Ludwig et al [39] also used near infrared spectroscopy to predict pH, electric conductivity, P, K, NO3 -and NH4 + and phytotoxicity.…”

“…The second example illustrates the application of partial least squares regression (PLS-R). Michel et al [42] applied PLS-R to predict conventional parameters by spectroscopic data. Ros et al [27] applied a cluster analysis to data of polymerase chain reaction coupled with denaturing gradient gel electrophoresis (PCR-DGGE) to observe the long-term effects of compost amendment on soil microbial activity.…”

“…However this is timeconsuming and laborious. Due to the fact that NIR is a simple, accurate and fast technique used for routine analysis Michel et al [42] h y p o t h e s i s e d t h a t N I R c o u l d b e u s e d f o r parameter prediction. The objective of the study was to use NIR spectroscopy to determine chemical and biological properties.…”