Predicting forage indigestible NDF from lignin concentration

Area of Science:

• Animal Science
• Nutrient Analysis
• Forage Quality

Background:

• Accurate prediction of forage indigestible neutral detergent fiber (NDF) is crucial for estimating animal performance.
• Existing models for lignification and indigestible NDF may have limitations in predicting animal growth.

Purpose of the Study:

• To develop and validate new equations relating forage lignification to indigestible NDF.
• To compare the predictive accuracy of new equations with existing models, including the Cornell Net Carbohydrate and Protein System (CNCPS).

Main Methods:

• Utilized in vitro digestibility and chemical composition data from temperate and tropical forages.
• Developed nonlinear log-log models based on lignin concentration in NDF.
• Compared predictions from new equations and CNCPS with animal growth data.

Main Results:

• Indigestible NDF increased nonlinearly with lignin concentration.
• Log-log models using permanganate or sulfuric acid lignin provided the best fit and lowest prediction errors.
• CNCPS consistently underpredicted average daily gain (ADG) in steers, regardless of the indigestible NDF equation used.

Conclusions:

• New log-log equations offer improved prediction of indigestible NDF and forage energy value.
• Current CNCPS model may require adjustments for more accurate prediction of steer ADG, especially with varying forage quality.
• More accurate indigestible NDF prediction leads to revised estimates of forage energy and potential animal performance.