Review: Prediction of variation in energetic value of wheat for poultry

2012 ◽  
Vol 92 (3) ◽  
pp. 261-273 ◽  
Author(s):  
M. Yegani ◽  
D. R. Korver

Yegani, M. and Korver, D. R. 2012. Review: Prediction of variation in energetic value of wheat for poultry. Can. J. Anim. Sci. 92: 261–273. Variations in physical and chemical characteristics of wheat can significantly influence the energy availability of this feed ingredient for poultry. These variations can result in inefficiencies in the form of over- or under-formulation of the diets at commercial feed mills or on poultry farms. Therefore, having a clear understanding of the variations is of paramount importance in the formulation of poultry diets as they can have negative consequences for production performance of birds. There are a large number of factors that can contribute to variations in energy availability of wheat for poultry. This review is intended to briefly discuss these factors and also practical approaches that can be used to predict these variations. These approaches include measuring physico-chemical characteristics, in vivo digestibility trials, in vitro digestibility techniques, and near infrared reflectance spectroscopy (NIRS). There are limitations associated with physico-chemical and in vivo measurements. However, in vitro digestibility techniques are simple and fast and can provide data for database development and ongoing calibrations of NIRS systems. Near infrared reflectance spectroscopy has enormous potential to predict variations in wheat apparent metabolizable energy, leading to more accurate diet formulation.

1989 ◽  
Vol 69 (3) ◽  
pp. 833-839 ◽  
Author(s):  
S. S. BUGHRARA ◽  
D. A. SLEPER ◽  
R. L. BELYEA ◽  
G. C. MARTEN

Little information is available on estimating in vitro dry matter digestibility (IVDMD) of alfalfa (Medicago sativa L.) herbage by a prepared cellulase solution (PCS) and then using these IVDMD estimates to calibrate near infrared reflectance spectroscopy (NIRS) equations. Objectives were to compare PCS digestion to that by two rumen fermentation procedures, including true in vitro digestibility (TIVD), and develop NIRS equations to estimate TIVD, neutral detergent fiber, and acid detergent fiber of alfalfa hay. Seventy-eight alfalfa samples, having a wide range in herbage quality, were analyzed for IVDMD using five different PCS procedures and two rumen fermentation procedures (true and apparent in vitro digestibility). The best NIRS calibration equation for TIVD had R2 of 0.92 and a standard error of selection of 20.7 g kg−1. Correlations between IVDMD and TIVD obtained by the various PCS assays ranged from 0.91 to 0.96 (P < 0.01), with regression coefficients ranging from 0.94 to 0.98. We concluded that PCS gave rapid and accurate estimates of TIVD and that NIRS could accurately estimate TIVD of a wide range of alfalfa herbage quality.Key words: Acid detergent solubles, fungal cellulase solubles, in vitro digestible dry matter, Medicago sativa L., neutral detergent solubles, alfalfa


2022 ◽  
Vol 951 (1) ◽  
pp. 012100
Author(s):  
R. Zahera ◽  
L.A. Sari ◽  
I.G. Permana ◽  
Despal

Abstract Information on dairy fibre feed digestibility is important in ration formulation to better predict dairy cattle performance. However, its measurement takes time. Near-infrared reflectance spectroscopy (NIRS) is a rapid, precise, and cost-effective method to predict nutrient value, such as chemical content and digestibility of feedstuffs. This study aims to develop a database for an in vitro digestibility prediction model using NIRS, including dry matter digestibility (DMD), neutral and acid detergent fibre digestibility (NDFD and ADFD), and hemicellulose digestibility (HSD). Eighty dietary fibre feeds consisting of Napier grass, natural grass, rice straw, corn stover, and corn-husk were collected from four dairy farming areas in West Java (Cibungbulang District of Bogor Regency, Parung Kuda District of Sukabumi Regency, Pangalengan District of Bandung Regency, and Lembang District of West Bandung Regency). The spectrum for each sample was collected thrice using NIRSflex 500, which was automatically separated by 2/3 for calibration and 1/3 for validation. External validation was conducted by measuring 20 independent samples. Calibration and validation models were carried out by NIRCal V5.6 using the partial least squares (PLS) regression. The results showed that all parameters produce r2 > 0.5 except for ADFD. Relative prediction deviation (RPD) > 1.5 was only found in hemicellulose digestibility prediction. RPL (SEP/SEL) <1.0 were found in DMD and hemicellulose digestibility. It is concluded that hemicellulose digestibility can be predicted using NIRS accurately while other parameters need improvement.


Sensors ◽  
2017 ◽  
Vol 17 (11) ◽  
pp. 2642 ◽  
Author(s):  
Ana Garrido-Varo ◽  
María-Teresa Sánchez ◽  
María-José De la Haba ◽  
Irina Torres ◽  
Dolores Pérez-Marín

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