Simple Summary Digestibility is a crucial factor for assessing feed costs for dairy cattle. Rapid analysis of fecal composition is necessary to obtain accurate data on digestive efficiency. Traditional wet chemical analysis methods are time-consuming; therefore, the potential of near-infrared reflectance spectroscopy technique was explored for assessing fecal chemical components in dairy cattle. The technique has been widely used to predict the nutritional contents of raw materials and complete feeds. In the present study, near-infrared reflectance spectroscopy could successfully predict the chemical composition of dairy cattle feces, thereby reducing analysis time and workload. Abstract Traditional methods for determining the chemical composition of cattle feces are uneconomical. In contrast, near-infrared reflectance spectroscopy (NIRS) has emerged as a successful technique for assessing chemical compositions. Therefore, in this study, the feasibility of NIRS in terms of predicting fecal chemical composition was explored. Cattle fecal samples were subjected to chemical analysis using conventional wet chemistry techniques and a NIRS spectrometer. The resulting fecal spectra were used to construct predictive equations to estimate the chemical composition of the feces in both cows and calves. The coefficients of determination for calibration (RSQ) were employed to evaluate the calibration of the predictive equations. Calibration results for cows (dry matter [DM], RSQ = 0.98; crude protein [CP], RSQ = 0.93; ether extract [EE], RSQ = 0.91; neutral detergent fiber [NDF], RSQ = 0.82; acid detergent fiber [ADF], RSQ = 0.89; ash, RSQ = 0.84) and calves (DM, RSQ = 0.92; CP, RSQ = 0.89; EE, RSQ = 0.77; NDF, RSQ = 0.76; ADF, RSQ = 0.92; ash, RSQ = 0.97) demonstrated that NIRS is a cost-effective and efficient alternative for assessing the chemical composition of dairy cattle feces. This provides a new method for rapidly predicting fecal chemical content in cows and calves.
Application of Near-Infrared Reflectance Spectroscopy for Predicting Chemical Composition of Feces in Holstein Dairy Cows and Calves
Yiming Xu,Tianyu Chen,Hongxing Zhang,Yiliyaer Nuermaimaiti,Siyuan Zhang,Fei Wang,Jianxin Xiao,Shuai Liu,Wei Shao,Z. Cao,Jingjun Wang,Yong Chen
Published 2023 in Animals
ABSTRACT
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- Publication year
2023
- Venue
Animals
- Publication date
2023-12-22
- Fields of study
Agricultural and Food Sciences, Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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