An overview of silage research in Finland: from ensiling innovation to advances in dairy cow feeding

Abstract

Because of the climatic conditions, the Finnish milk production research has focused to improve the utilisation of grassland, mainly as conserved forages. The main research areas have been ensiling, evaluation of the forage feeding value, predicting nutrient supply from grass silage-based diet and the effects of forage quality and concentrate supplementation on milk production responses. Due to changes in ensiling technologies and variety of forage crops new silage additives have been adopted. A centralized system for the analysis of forage energy value is based on NIRS calibration. It was calibrated against in vitro pepsin-cellulase solubility method that was validated against in vivo digestibility. The concentration of indigestible neutral detergent fibre was found to be a useful parameter both in empirical models predicting forage digestibility and mechanistic rumen models predicting the amounts of absorbed nutrients. Models predicting relative intake potential of forages and total diet were developed, and an intake model combining animal and diet effects independently of each other was developed. Using meta-analysis approaches a nutrient response model was developed for dairy cows for milk, energy corrected milk and protein yield. Feed evaluation, intake and nutrient response models form now the basis of practical Finnish ration formulation system that can optimize diets according to maximum income over feed cost in addition to minimum feed cost.

Effects of biological and chemical additives on fermentation progress in maize silage

“…In contrast, the addition of formic acid into silage decreased the concentration of acetic acid in grass silage (Kennedy 1990). As reviewed by Huhtanen et al (2013), the inconsistent results obtained in the fermentation quality of formic acid-treated silages can be explained by the variation of crop characteristics, application rates, and evenness of additive application.…”

“…They can be used when the dry matter (DM) content of ensiled matter is low (e.g. often during rainy weather), for high-protein fodder plants, or for silage with very high DM content (Huhtanen et al 2013). Because of its high antimycotic activity, propionic acid usually constitutes the greatest percentage of those active ingredients used in commercial products today (Kung et al 1998;Mills and Kung 2002).…”

Predicting feeding value of forage maize hybrids harvested at different maturities and sites

“…However, the data was not related to in animal determined in vivo OMD values. In a recent review by Huhtanen et al (2013) it was concluded that predicting OMD from forage iNDF and NDF concentrations provided smaller prediction error compared to in vivo OMD equation that only included the concentration of iNDF. The EFOS method, which has been recommended for evaluating forage maize (Åkerlind et al, 2011), had a larger prediction error of OMD for forage maize samples in the equation developed by Søegaard et al (2001) than the general iNDF-equation (across forage types and not forage specific) developed by Huhtanen et al (2006).…”

“…The cows were fed a diet consisting of 600 and 400 g · kg -1 diet dry matter (DM) of grass silage (Huhtanen et al, 2013); OMD EFOS -predicted from EFOS (Weisbjerg and Hvelplund, 1993); OMD VOS -predicted from VOS (Lindgren, 1979); OMD NIRS-F -predicted based on the Finnish NIRS calibration; 2 SD -standard deviation and concentrate (Vida 175; Lantmännen Lantbruk AB, Stockholm, Sweden), respectively, to meet production requirements. Samples of 2 g were weighed into pre-weighed polyester bags with pore size of 12 µm and a pore area equal to 6% of the total surface (Saatifil PES 12/6; Saatitech S.P.A., Veniano, Como, Italy).…”

“…Coefficient of determination (R 2 ) and root mean square error of prediction (RMSEP, g· kg -1 are given to allow evaluation of the regression equations (Huhtanen et al, 2013) were used as observed values; 2 iNDF NIRS-S -from the Swedish NIRS calibration; iNDF NIRS-F -from the Finnish NIRS calibration; OMD EFOS -predicted from the in vitro enzyme digestible organic matter (Weisbjerg and Hvelplund, 1993); OMD VOS -predicted from rumen fluid organic matter solubility (Lindgren, 1979); OMD NIRS-F -OMD predicted based on the Finnish NIRS calibration; 3 SE -standard error …”