Thermogravimetric evaluation of perennial ryegrass (Lolium perenne) for the prediction of in vitro dry matter digestibility

• Published in: Annals of applied biology Vol. 152; no. 3; pp. 277 - 288
• Main Authors: Sharma, H.S.S, Mellon, R.M, Johnston, D, Fletcher, H
• Format: Journal Article
• Language: English
• Published: Oxford, UK Oxford, UK : Blackwell Publishing Ltd 01-06-2008; Blackwell Publishing Ltd; Blackwell
• Subjects: Biological and medical sciences; Dry matter digestibility; Fundamental and applied biological sciences. Psychology; Lolium; pepsin-cellulase assay; ryegrass; thermogravimetry; Monocotyledones; Thermal method; Dry matter; Dry matter digestibility; Assay; pepsin-cellulase assay; Gramineae; Angiospermae; Chemical composition; Lolium perenne; C3-Type; Quantitative analysis; Digestibility; Plant production; Evaluation; Vegetals; Enzyme; Nutritive value; Prediction; Thermogravimetry; ryegrass; Experimental study; In vitro; Glycosylases; Applied biology; Cellulolytic enzyme; Cellulase; Glycosidases; Hydrolases; Herbaceous plant; Spermatophyta; Physical method
• ISSN: 0003-4746; 1744-7348
• DOI: 10.1111/j.1744-7348.2008.00218.x

Thermogravimetry (TG) can be used for assessing the compositional differences in grasses that relate to dry matter digestibility (DMD) determined by pepsin-cellulase assay. This investigation developed regression models for predicting DMD of herbage grass during one growing season using TG results. The calibration samples were obtained from a field trial of eight cultivars and two breeding lines. The harvested materials from five cuts were analysed by TG to identify differences in the combustion patterns within the range of 30-600°C. The discrete results including weight loss, peak height, area, temperature, widths and residue of three decomposition peaks were regressed against the measured DMD values of the calibration samples. Similarly, continuous weight loss results of the same samples were also utilised to generate DMD models. The r² for validation of the discrete and the best continuous models were 0.90 and 0.95, respectively, and the two calibrations were validated using independent samples from 24 plots from a trial carried out in 2004. The standard error for prediction of the 24 samples by the discrete model (4.14%) was higher than that by the continuous model (2.98%). This study has shown that DMD of grass could be predicted from the TG results. The benefit of thermal analysis is the ability to detect and show changes in composition of cell wall fractions of grasses during different cuts in a year.