Predictive models of digestible and metabolizable energy of wheat in growing pigs

TL;DR

This study determines the energy content and nutrient digestibility of 17 wheat varieties for growing pigs and develops predictive models for digestible and metabolizable energy.

Contribution

The paper introduces new regression equations to predict energy values in different wheat cultivars based on chemical composition.

Findings

Digestible energy (DE) and metabolizable energy (ME) varied significantly among 17 wheat cultivars.

Key predictors for energy values include gross energy, crude protein, starch, and bulk density.

Regression models for DE and ME were developed and validated with statistical significance.

Abstract

Wheat is progressively utilized in animal husbandry. However, the chemical properties of wheat are influenced by breed and climate, consequently impacting its economic value and application in feed formulation. This study was conducted to evaluate the digestible energy (DE) and metabolizable energy (ME), as well as apparent total tract digestibility (ATTD) of nutrients in 17 samples of wheat for growing pigs.

Fifty-one growing barrows were randomly allotted to 17 experimental diets (3 pigs in each diet). The experiment included two successive periods, and per period lasted for 12 days, including 7 days for diet adaptation, 5 days for urine and feces collection.

There was significant (p < 0.01) difference in DE content of 17 wheat cultivars. The DE and ME contents ranged from 16.06 to 16.88 MJ/kg DM and 15.65 to 16.36 MJ/kg DM, respectively. The coefficients variation (CV) of the chemical compositions were bulk density (3.14%), crude protein (CP) (9.00%), neutral detergent fiber (NDF) (34.60%), acid detergent fiber (ADF) (9.65%) and ether extract (EE) (10.16%) in the 17 wheat samples. Except for the ATTD of phosphorus (P), there were significant differences in the ATTD of gross energy (GE) (p = 0.01), organic matter (OM) (p = 0.02), CP (p < 0.01), NDF (p < 0.01), ADF (p < 0.01), EE (p = 0.04) and calcium (Ca) (p = 0.03) in 17 wheat cultivars.

DE was significantly positively correlated with ME and CP content, GE was significantly negatively correlated with starch, and CP content was positively correlated with GE, DE and ME contents. Based on statistical analysis of chemical components of wheat samples, the GE, CP, starch, and bulk density are key variables for predicting effective energy, and the most suitable regression equations of DE and ME in different wheat cultivars were DE = 26.6394 − 0.6783 GE (MJ/kg) + 0.1618 CP (%) and ME = −0.3869 + 0.7788 DE (MJ/kg) + 0.0336 starch (%) + 0.0020 bulk density (g/L).

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