Energy partitioning for maintenance and egg production under heat stress

• Grant number: 22/11402-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: November 01, 2022
• End date: October 31, 2023
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Animal Nutrition and Feeding
• Principal Investigator: Edney Pereira da Silva
• Grantee: Giulia Cancian Vieira
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil

Abstract

The objective of this research is to analyze the coefficients that represent the partition of energy ingested by Japanese quails for maintenance and egg production. An assay will be carried out to evaluate the responses of egg mass (EM) and body weight (BW) of Japanese quails submitted to different intakes of metabolizable energy (MEI). 70 Japanese quails will be used, receiving levels of metabolizable energy sufficient to modify the responses in the BW and EM of the birds. The design used will be completely randomized, with seven treatments and ten replications, consisting of one bird each, for individual control. The trial will begin at 16 weeks of age and data will be collected for eight weeks. Two diets will be formulated, one with high energy content (3,600 kcal/kg - L7) and the other with low energy content (2,100 kcal/kg - L1). Intermediate levels will be obtained by dilution. The variables analyzed will be MEI, BW and EM. The models available in the literature that predict MEI based on nutritional constants that represent energy requirement kcal per g of EM and kcal per kg of BW will be evaluated through the linear decomposition of the error (observed - predicted), in scalar error and bias. prediction, obtained by linear regression between the errors and predicted values. The decision rule will be based on the impartiality of the model, obtained when the R² approaches 0. If necessary, adjustments in the parameters can be made to recommend a model that allows the user to predict metabolizable energy intake according to the mass production of eggs and body weight from each farm.