Fox manure, food waste and yard waste were used as pure composts to construct a laboratory-scale designed (simplex mixture) experiment with repeated centre points that was monitored over 31 calendar days by near infrared (NIR) spectroscopy (900–1700 nm) and additionally by sampling for wet chemical and physical laboratory measurements: pH, energy, moisture content, NH₃/NH₄⁺ (simply called ammonium) concentration, and temperature. Three methods of data analysis were tested on the resulting data matrices: (1) modelling of the mixture design by Scheffé models, (2) principal component analysis (PCA) with interpretation of score and loading plots for the laboratory parameters and the NIR spectra separately and (3) partial least squares (PLS) regression modelling between NIR spectra and laboratory parameters. Significant Scheffé models were obtained and these could be used to make response surfaces of the parameters as a function of time. The PCA scores for the laboratory data reproduced the mixture triangles at the start of the experiment and showed that all the aerobic composts evolved to a common endpoint region. The PCA analysis of the NIR data indicated that score plots are a useful tool for monitoring the decomposition process of composts. Each of the composts could be followed over time by observing directions in the score space and changes in the step distances in score space. PLS models were built for each of the laboratory parameters and, additionally, composting time against NIR spectra, where spectra from the three centre points were used as an independent test set. The parameters pH, temperature, ammonium concentration and composting time all gave RER values above 10 and RPD values above 3 were obtained for temperature, pH and composting time.

Keywords: compost, simplex mixture design, Scheffé model, response surface, NIR, PCA, PLS, half-life