Predicting digesta retention times from dietary physicochemical properties in pigs

IF 2.7 2区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Animal Feed Science and Technology Pub Date : 2025-03-01 Epub Date: 2025-01-27 DOI:10.1016/j.anifeedsci.2025.116242
Sebastian Dorado-Montenegro , Joshua A. Dijksman , Walter J.J. Gerrits , Sonja de Vries
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Abstract

Dietary physicochemical properties (PP) partially modulate digesta passage along the gastrointestinal tract (GIT). Understanding which dietary PP influence digesta passage is relevant for predicting nutrient absorption kinetics. This study assessed the potential of dietary PP for predicting mean retention time (MRT) and phase segregation of digesta, combining data from four experiments (21 diets, n = 166 pigs, and body weight = 42 ± 14.0 kg) including diets broadly ranging in PP. The MRT of digesta in various GIT segments, measured using similar methodology, was related to dietary PP: rheological parameters (extract viscosity and solid phase moduli plus linear viscoelastic range) and water-binding capacity (WBC). For each GIT segment and digesta phase, PP were selected as independent variables to include in prediction models after a correlation and multicollinearity analysis, followed by MaxR and stepwise variable selection methods. Subsequently, multiple and single regression analyses were performed, including selected PP as predictor variables. The MRT of solid (MRTsolids) and liquid (MRTliquids) digesta, and digesta phase segregation were predicted using model equations with (1) selected PP (full model), (2) WBC only, and (3) extract viscosity only; and calculated vs. observed values were compared. Coefficients of determination (R2) were used to select the best model to predict digesta MRT by GIT segment. Dietary PP were capable of predicting digesta phase segregation in the stomach (R2 = 0.56), largely explained by WBC (R2 = 0.51), and MRTliquids (R2 = 0.26), explained by WBC and rheological parameters. Dietary PP were less effective at predicting MRT in the small and large intestines (R2 = 0.07–0.17), though phase segregation in the cecum was better predicted (R2 = 0.26). Full PP-models, predicted MRTsolids and MRTliquids in all segments more accurately than dietary WBC or extract viscosity alone, whereas WBC was the most important predictor of phase segregation in the stomach. Extract viscosity explained negligible variation in digesta passage. This information can be used in feed formulation to better anticipate how dietary PP influence digestion kinetics.
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猪日粮理化特性预测食糜滞留时间
饲料理化性质(PP)部分调节胃肠道(GIT)的消化通道。了解膳食PP对消化通道的影响与预测营养吸收动力学有关。本研究结合四项试验(21种饲粮,n = 166头猪,体重= 42 ± 14.0 kg)的数据,评估了饲粮PP预测食糜平均滞留时间(MRT)和相分离的潜力,其中包括广泛的PP饲粮。采用类似方法测量的食糜不同GIT段的MRT与饲粮PP、流变参数(提取物粘度和固相模量加上线性粘弹性范围)和水结合能力(WBC)有关。通过相关分析和多重共线性分析,选择PP作为自变量纳入预测模型,然后采用MaxR和逐步变量选择方法。随后,进行多元和单一回归分析,其中选择的PP作为预测变量。采用(1)选定PP(全模型),(2)仅WBC,(3)仅提取物粘度的模型方程预测固体(MRTsolids)和液体(mrtliquid)食糜的MRT,以及食糜相分离;并将计算值与观测值进行比较。采用决定系数(R2)选择最佳模型预测消化道MRT的胃肠道段。饲粮PP能够预测胃中食糜相分离(R2 = 0.56),主要由WBC (R2 = 0.51)和mrtliquid (R2 = 0.26)解释,由WBC和流变参数解释。膳食PP对小肠和大肠MRT的预测效果较差(R2 = 0.07-0.17),但盲肠相分离的预测效果较好(R2 = 0.26)。全pp模型比单独的膳食WBC或提取物粘度更准确地预测了所有部分的mrt固体和mrt液体,而WBC是胃中相分离最重要的预测指标。萃取物粘度解释了消化过程中可忽略不计的变化。该信息可用于饲料配方,以更好地预测饲料PP如何影响消化动力学。
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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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