Developing a procedure to measure grinding energy of forages as a predictor of forage fragility

Abstract

The structural organization of plant organs and tissues determine the intake potential through the ease of forage particle breakdown, the nature of the particles produced as well as the rate of passage from the rumen. The cell wall content of forages influences the amount of energy required for chewing, and accounts for a considerable proportion of the total energy requirement. In the past, neutral detergent fibre (NDF) has been used as the only feed characteristic to predict the filling effects of forages, but there is substantial evidence that NDF alone is inadequate to make these predictions. Forage fragility is defined as the relative rate at which the particle size of forages are reduced during processes such as chewing or milling, and forage fragility might be related to lignin concentration and digestibility, as well as to anatomical differences among plant species. The physical characteristics of feedstuffs are not measured regularly, and these physical characteristics in relation to their nutritional properties should be taken into account for more precise feed formulation. Through the measurement of grinding energy, the possibility exists to predict forage fragility as related to the chemical composition of forages, which could lead to improved predictions of animal chewing activity and energy usage during the process of chewing. In order to investigate the possibility of developing a model for the prediction of forage fragility, twenty eight different forage samples were collected from 11 different locations. Samples included legumes, C3- and C4- grasses. Dried samples were analysed for various chemical components, as well as 24-hour in vitro NDF digestibility (ivNDFd) and rate of NDF degradation (NDFkd). Dried samples were pre-cut with a knife mill, fitted with a 2 cm screen, after which particle size distribution for each sample was determined using a Retsch Sieve shaker. Ten g duplicate samples were milled with a laboratory hammer mill and an ultra-centrifugal mill, both fitted with a 1 mm screen, for the measurement of grinding energy. During the grinding process, energy usage of the specific mill was measured using a data logger with corresponding computer software and energy transducer. Energy measurements were reported as J/g sample on dry matter (DM) basis. The 2 cm samples were milled with the knife mill again, fitted with a 1 mm screen, after which particle size distribution was determined again to analyse change in particle distribution for each forage sample. The results of this study indicated that dry matter, nitrogen, ivNDFd, NDFkd and initial particle size (IPS) can all be associated with increased forage fragility, as there was a decrease in energy usage during grinding with an increase in any of the aforementioned components. The acid detergent fibre (ADF), NDF, total phenols (TP), non-tannic phenols (NTP), as well as the % change in particle size can all be associated with decreased forage fragility, as there was an increase in energy usage during grinding with an increase in any one of these components. It would be expected that acid detergent lignin (ADL) is also associated with decreased forage fragility; however, this can only be assumed as the results for the effect of lignin on forage fragility are inconclusive in this study. Literature on energy requirement for milling operations of forages is inadequate. Grinding energy is related to the stem mechanical properties (such as maximum cutting force and stem shear strength), and physical properties (such as stem diameter, DM density and moisture content). The use of grinding energy has the potential be a practical and useful measure to predict forage fragility, however, the relative contribution of factors such as original particle size, shape, surface area, morphology and many other factors toward the fragility of forages is difficult to predict. More research is needed on the prediction of forage fragility before it can be incorporated as a meaningful input into nutritional models such as NRC, CNCPS and AMTS.