Prediction of Potential Mushroom Yield by Visible and Near-Infrared Spectroscopy Using Fresh Phase II Compost

Abstract

Potential mushroom (Agaricus bisporus) yield of phase II compost is determined by interactions of key quality parameters including dry matter, nitrogen dry matter, ammonia, pH, conductivity, thermophilic microorganisms, C : N ratio, fiber fractions, ash, and certain minerals. This study was aimed at generating robust visible and near-infrared (Vis-NIR) calibrations for predicting potential yield, using spectra from fresh phase II compost. Four compost comparative trials were carried out during the winter and summer months of 2001-2003, under controlled experimental conditions employing six commercially prepared composts, with eight replicate (8 bag) plots per treatment (48 x 8 = 384). The substrates were prepared by windrow or bunker phase I, followed by phase II production. The fresh samples were scanned for Vis-NIR (400-2498 nm) spectra, averaged, transformed, and regressed against the recorded yield by employing a modified partial least squares algorithm. The best calibration model generated from the database explained 84% of yield variation within the data set with a standard error of calibration of 13.75 kg/tonne of fresh compost. The model was successfully tested for robustness with yield results obtained from a validation trial, carried out under similar experimental conditions in early 2004, and the standard error of prediction was 18.21 kg/tonne, which was slightly higher than the mean experimental error (17.94 kg/tonne) of the trial. The accuracy of the model is acceptable for estimating potential yield by classifying phase II substrate as poor (180-220 kg), medium (220-260 kg), and high (260-300 kg) yielding compost. The yield prediction model is being transferred to a new instrument based at Loughgall for routine evaluation of commercial phase II samples.