Optimizing dietary crude protein, branched-chain amino acids, and energy levels for broiler performance using a

Sosthene Musigwa1, Pierre Cozannet2, Mingan Choct1

  • 1Animal Science, School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia.

Related Concept Videos

Optimal Foraging00:48

Optimal Foraging

How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to subjects...
Designing Growth Media for Bioreactors01:30

Designing Growth Media for Bioreactors

Growth media provide essential nutrients that support cell growth and metabolism, thereby enhancing the yield of valuable products such as enzymes, antibiotics, and biomass. Designing an effective growth medium involves balancing all components to prevent nutrient limitations or toxic excesses, both of which can impair growth and reduce product yields.Composition of a Typical Growth MediumA typical growth medium contains carbon and nitrogen sources, salts, vitamins, trace elements, and...
Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...