Estimation of Energy Value and Digestibility and Prediction Equations for Sheep Fed with Diets Containing Leymus chinensis Hay

Autor: Hewei Chen, Fengliang Xiong, Qichao Wu, Weikang Wang, Zhaoyang Cui, Fan Zhang, Yanlu Wang, Liangkang Lv, Yingyi Liu, Yukun Bo, Luotong Zhang, Hongjian Yang
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Agriculture, Vol 13, Iss 6, p 1213 (2023)
Druh dokumentu: article
ISSN: 2077-0472
DOI: 10.3390/agriculture13061213
Popis: The objective of this study was to investigate the feeding value of sheepgrass, including its chemical composition, dry matter intake, nutrient digestibility, and available energy, as well as the prediction equations of dry matter intake (DMI), neutral detergent fiber digestibility (NDFD), dry matter digestibility (DMD), digestible energy (DE), and metabolizable energy (ME). Two independent experiments based on a completely randomized experimental design were performed to evaluate the feeding value. The results showed that there were significant relationships between chemical composition and DMI, digestibility, and available energy. The best-fit equations were as follows: DMI (g/d·W0.75) = 121.75 + 0.06CP (%) − 0.24EE (%) − 0.10ADF (%) − 0.60NDF (%) − 0.15OM (%) (R2 = 0.85, p < 0.01), DMD (%) = −1.37 + 0.23CP (%) + 2.96EE (%) + 0.32ADF (%) − 0.82NDF (%) + 1.27OM (%) (R2 = 0.83, p < 0.01), NDFD (%) = 225.58 − 0.59CP (%) + 0.04EE (%) + 0.09ADF (%) − 2.46NDF (%) + 0.12OM (%) (R2 = 0.67, p < 0.01), DE (MJ/kg) = −5.19 + 0.38OM (%) − 0.26NDF (%) − 0.03ADF (%) + 0.16CP (%) (R2 = 0.91, p < 0.01), and ME (MJ/kg) = 5.55 + 0.67DE (MJ/kg) + 0.01CP (%) − 0.01ADF (%) − 0.08NDF (%) + 0.02OM (%) (R2 = 0.98, p < 0.01). This study found the energy value of sheepgrass to be 11 MJ/kg, which is similar to that of millet grass silage. The NDF was the main component that affected DMI and digestibility. Using a hay replacement ratio of 28.5% to determine the forage value of sheepgrass allowed accurate prediction equations to be established. The NDF demonstrated the strongest correlation with DMI, NDFD, OMD, DE, and ME. DE was estimated to be the best single predictor of ME.
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