Chemical Composition, Fermentation Parameters and Losses of Silages From Different Hybrids of Biomass Sorghum

Due to their high productivity, biomass sorghum ( Sorghum bicolor (L.) Moench) hybrids may be promising to maximise roughage production for ruminants. However, the variation in chemical composition among hybrids may impact the nutritional value and the fermentation process of the silages produced. Thus, the present study assessed the fermentation quality and chemical composition of silages from five hybrids of biomass sorghum. The experiment adopted a 5 × 2 factorial randomised block design with five biomass sorghum hybrids (CMSXS5039, CMSXS5044, CMSXS7102, CMSXS7103 and BRS 716) sowed in two municipalities of the state of Mato Grosso do Sul, Brazil (Dourados and Jateí). The parameters assessed were chemical composition, in vitro dry matter digestibility, profile of short‐chain organic acids, pH, ammonia, fermentation losses and aerobic stability. The silages produced from CMSXS7102, CMSXS7103 and BRS 716 in Dourados had higher fibre content and lower digestibility coefficients. In contrast, hybrids with higher non‐fibrous carbohydrate content and lower lignin levels, such as CMSXS5044 and CMSXS5039, exhibited the best digestibility values. Silages produced in Jateí had higher moisture content, which resulted in increased effluent losses, particularly for the CMSXS5044 (450 kg ton −1 DM) and CMSXS5039 (320 kg ton −1 DM) hybrids. This higher effluent production in Jateí led to lower soluble protein (SP) and degradable protein (DP) concentrations compared to the silages from Dourados. Additionally, the higher moisture content in Jateí promoted the production of butyric acid in the silages. Silages from the CMSXS5039 hybrid (70.5 g kg −1 DM) had the highest lactic acid content; however, no significant difference was observed in acetic acid levels between the treatments. Overall, all the sorghum biomass hybrids tested produced silages with good fermentative and nutritional quality, but CMSXS5039 stood out in most of the parameters evaluated.