Effects of wilting duration and microbial inoculation on fermentation profile, chemical composition, aerobic stability and in situ nutrient degradability of ryegrass silage

IF 2.5 2区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
F.X. Amaro , K.G. Arriola , L. Mu , S. Farooq , C. NinoDeGuzman , C. Romeiro , L.O. Lima , H. Sultana , A.O. Oyebade , M. Wallau , D. Vyas
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Abstract

The objective was to evaluate the effects of wilting duration (WD), microbial inoculant (MI) and their interaction on fermentation parameters, chemical composition, and aerobic stability of annual ryegrass (Lolium multiflorum L.) silages ensiled at 30 and 90 d. Study design was a randomized complete block with a split-plot arrangement of treatments where block was the field plots, main plot was WD (Short vs. Long), and subplot was MI (Control vs. Inoculated). Silages were evaluated at either 30 or 90 d of ensiling. Harvested forage was allowed to wilt for 48 and 72 h, for Short and Long WD, to target 30, and 40 % DM, respectively. Wilted forage was chopped and treated with either MI (1.5 × 105 colony forming units of Lentilactobacillus buchneri LB1819 and Lactococcus lactis O224/g of wet forage, SiloSolve® FC) or the same amount of distilled water. Forages (∼ 3.5–4.1 kg) were ensiled in vacuum bags for either 30 or 90 d. Silage samples were analyzed for microbial counts, fermentation parameters, and aerobic stability. For in situ ruminal degradability assay, dried silage samples were incubated in two ruminally-cannulated cows at several incubation timepoints (0, 2, 4, 8, 16, 24, 48 and 72 h) for estimation of ruminal degradability of dry matter, crude protein, and neutral detergent fiber (DM, CP, and NDF, respectively). Data were analyzed using the GLIMMIX procedure of SAS for main effects of DM, MI, and their interaction. Long WD increased forage and silage DM, and the concentration of water-soluble carbohydrates (WSC) at 0 and 30 d, while decreasing lactic acid bacteria (LAB) counts, lactate, and total organic acids concentrations of silages. In addition, Long WD slightly increased predicted milk yield probably because of greater WSC concentration. Microbial inoculant addition improved DM recovery and aerobic stability of ryegrass silages, while increasing LAB counts and acetate concentration. In conclusion, MI can be used as a strategy to improve fermentation characteristics of ryegrass silages, while WD can affect chemical characteristics that may increase predicted milk yield of dairy cows when using NASEM formulation software.
萎蔫时间和微生物接种对黑麦草青贮发酵特征、化学组成、好氧稳定性和原位养分降解性的影响
目的是评估萎蔫时间(WD)、微生物接种剂(MI)及其相互作用对一年生黑麦草(Lolium multiflorum L.)青贮30和90 d发酵参数、化学成分和好氧稳定性的影响。研究设计为随机完整区,采用分块处理安排,区为田间区,主区为WD(短区与长区),次区为MI(对照与接种区)。分别在青贮30 d和90 d进行青贮评价。收获的草料经48和72 h,在短、长WD条件下,分别达到30%和40% % DM。将枯萎的草料切碎,用MI(1.5 × 105个布氏慢乳杆菌LB1819和乳酸乳球菌O224/g湿草料SiloSolve®FC集落形成单位)或等量蒸馏水处理。将青贮饲料(~ 3.5-4.1 kg)在真空袋中青贮30或90 d。对青贮饲料样品进行微生物计数、发酵参数和有氧稳定性分析。在原位瘤胃降解率试验中,将干燥青贮样品在2头瘤胃空心奶牛中进行孵育,分别在孵育时间点(0、2、4、8、16、24、48和72 h),以估计干物质、粗蛋白质和中性洗涤纤维(DM、CP和NDF)的瘤胃降解率。使用SAS的GLIMMIX程序对数据进行分析,以确定DM、MI的主要影响及其相互作用。长WD增加了0和30 d饲粮和青贮DM以及水溶性碳水化合物(WSC)浓度,降低了青贮乳酸菌(LAB)数量、乳酸和总有机酸浓度。此外,长WD略微提高了预测产奶量,可能是由于WSC浓度较高。微生物接种剂的添加提高了黑麦草青贮的DM回收率和好氧稳定性,同时增加了LAB计数和乙酸浓度。综上所述,在使用NASEM配方软件时,MI可以作为改善黑麦草青贮发酵特性的策略,而WD可以影响化学特性,从而提高奶牛的预测产奶量。
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来源期刊
Animal Feed Science and Technology
Animal Feed Science and Technology 农林科学-奶制品与动物科学
CiteScore
6.00
自引率
6.20%
发文量
266
审稿时长
3 months
期刊介绍: Animal Feed Science and Technology is a unique journal publishing scientific papers of international interest focusing on animal feeds and their feeding. Papers describing research on feed for ruminants and non-ruminants, including poultry, horses, companion animals and aquatic animals, are welcome. The journal covers the following areas: Nutritive value of feeds (e.g., assessment, improvement) Methods of conserving and processing feeds that affect their nutritional value Agronomic and climatic factors influencing the nutritive value of feeds Utilization of feeds and the improvement of such Metabolic, production, reproduction and health responses, as well as potential environmental impacts, of diet inputs and feed technologies (e.g., feeds, feed additives, feed components, mycotoxins) Mathematical models relating directly to animal-feed interactions Analytical and experimental methods for feed evaluation Environmental impacts of feed technologies in animal production.
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