Este estudio tuvo como objetivo evaluar indicadores productivos del crecimiento, rasgos de la canal y la composición proximal de carne de la Gallina de Guinea (GG) criada bajo condiciones tropicales de México. Se realizó de julio 2016 a mayo 2017. Se evaluó el comportamiento productivo (CP) de 100 keets en 14 semanas y para los rasgos de la canal (RC) se analizaron muestras de 5 machos y 5 hembras. Se evaluó en CP, la Ganancia de peso (GPE), consumo de alimento (CAL) y conversión alimenticia (ECA) y en RC, rendimiento de la canal (RCA), capacidad de retención de agua (CRA), pH y color. Se realizó estadística descriptiva y para detectar diferencias entre sexo se usó un modelo lineal generalizado (GLM), usando el paquete estadístico SAS (Ver. 9.4). El peso final promedio fue de 1161.56 ± 94.82 g con una GPE de 10.98 ± 0.95 g/ave, CAL de 62.04 ± 2.48 g y una ECA de 5.65 ± 0.57 g. Los machos fueron superiores (79.3%) en la RCA, sin diferencias estadísticas (P>0.05). La CRA y el pH fueron muy similares. La producción de GG es una alternativa de suministro de carne siendo una fuente de proteína de origen animal. Palabras clave: crecimiento, calidad de la canal, calidad de carne, gallinas de Guinea.
<p><strong>Background. </strong>Guinea fowl (<em>Numida meleagris)</em> is used as an alternative for the production of meat with high nutritional value; however, there are several factors that affect their productive performance. <strong>Objective.</strong> Review the main factors that affect the productive performance of the guinea fowl described in the worldwide literature. <strong>Methodology.</strong> A bibliographic review in the databases of Scopus, NCBI, Springer, Science direct, Google Scholar, Redalyc, and other repositories was carried out. The keywords for the search were: Guinea fowl, <em>Numida meleagris</em>, productive performance and body weight gain. <strong>Results. </strong>The production system is one of the main factors that affect the productive performance of the Guinea fowl. Birds raised in semi-intensive conditions have better weight gains compared to those that are kept under an extensive system. Mortality in the extensive system increases due to poor or no disease prevention practices and natural predators. The increase in population density under intensive management conditions negatively affects the performance and welfare of Guinea fowl. Ignorance of the energy and protein requirements causes a deficient productive performance in weight gains. Genetic factors also play a role; in Africa local varieties that have not been genetically improved are bred in extensive systems obtaining low yields, compared to developing countries. Birds hatch from large eggs with shorter storage periods had better growth performance. <strong>Implications.</strong> There is limited information on the main aspects related to the raising of the Guinea fowl, including the factors that affect its productive performance. Ignorance of the productive parameters favors the displacement of Guinea fowl production by other poultry species, such as chicken.<strong> Conclusions. </strong>Breeding the Guinea fowl as an alternative for meat and egg production must be accompanied by the disclosure of productive parameters to improve their production performance.</p>
Objective: To evaluate the application of one or two doses of prostaglandin F2?(PGF2?), the application of a progestogen on different days of the estrous cycle and theusage of eCG in the estrus synchronization and fertility of Zebu × Brown Swiss cows.Design / methodology / approach: The study was based on three protocols. The firstconsisted of two treatments: PGI) 26 cows were injected with a single 25 mg dose ofPGF2? and 10 cows with two 25 mg doses of PGF2? at a 14-day interval. Protocol 2consisted of two treatments: NG14) 11 cows were implanted with 3 mg of Norgestometon day 7 of their estrous cycle and NG7) 11 animals received the same dose on day 14.In protocol 3 all cows were implanted with 3 mg of Norgestomet for 9 days, 48 h beforeremoving the implant, 25 mg of PGF2? was applied. Once the implants were removed,they were distributed into two treatments. Norgestomet (n = 11) without eCG andNorgestomet + eCG (500 IU) (n = 11). Results: The application of PGF2? at two times had no influence (p > 0.05) in theestrous percentages and conception. The NG7 achieved estrous synchronization in 81.8% of the cows, in between 24 and 36 h, compared to 45.4 % of the NG14; however, theconception rate was lower (p ? 0.05). The eCG application synchronized 90.9 % ofestrous between 24 and 36 h, compared with 36.4 % of the group with no eCGapplication.Study limitations / implications: Transrectal ultrasounds are required to assess theovarian structures present at the time of the estrus onset in a synchronization protocol.Findings / conclusions: Cows that present corpus luteum do not require more thanone injection of PGF2?, the pregnancy percentage increases when Norgestomet isimplanted on day 14 of the estrous cycle, in addition the application of eCG increasesthe synchronization percentage of the heat between 24 to 36 h after the progestogenwithdrawal.
El objetivo fue caracterizar el crecimiento de aves Criollas Mexicanas (CMX), Hy-Line Brown (HLB) y Rhode Island Red (RIR) mediante los modelos Gompertz-Laird (MNGL), Logístico (MNL), Richards (MNR) y Von Bertalanffy(MNVB). Se utilizaron 70 pollitas de cada genotipo. Cada ave fue identificada para registrar su peso de 7 a 210 d de edad. Los parámetros de los modelos se estimaron con el procedimiento NLIN (algoritmo de Marquardt) de SAS. Se calculó el coeficiente de determinación ajustado, criterio de información de Akaike y criterio de información Bayesiana, para cada caso. La tasa de crecimiento inicial (d−1) en aves CMX fue menor (0.047 15) que en aves RIR (0.071 69) y HLB (0.052 16). Con los cuatro modelos, la tasa de decaimiento en aves CMX fue menor, respecto a los otros genotipos. Asimismo, la edad al máximo crecimiento (d) en las aves CMX,RIR y HLB, varió de 49.4 a 87.9, de 60.7 a 81.6 y de 58.7 a 87.8, respectivamente. Por otro lado, el peso asintótico (g), estimado con los cuatro modelos varió de 2 068.5 a 2 644.3, de 1 902.4 a 2 250.9 y 2 096.3 a 2 464.5, en las aves CMX, RIR y HLB, respectivamente. Con el MNVB se obtuvo el mejor ajuste para los datos de las aves RIR y HLB, en contraste, el MNR fue mejor para las aves CMX, seguido del MNVB. El MNVB sería el más adecuado para el estudio simultáneo del crecimiento de aves CMX, RIR y HLB.
The study was done to predict egg weight from the external traits of the Guinea fowl egg using the statistical methods of multiple linear regression (MLR) and regression tree analysis (RTA). A total of 110 eggs from a flock of 23-week-old Guinea fowl were evaluated. Egg weight (EW) and external traits: eggshell weight (ESW), egg polar diameter (EPD), egg equatorial diameter (EED), egg shape index (ESI), and egg surface area (ESA) were measured. Descriptive statistics, Pearson correlation coefficients, and regression equations using the MLR were obtained; additionally, a RTA was done using the CHAID algorithm with the SPSS software (IBM ver. 22). EW presented positive correlations (p<0.0001) with ESA (r = 0.72), EPD (r = 0.65), and EED (r = 0.49). EW can be predicted through MLR using ESA as a predictor variable (R 2 = 72%). Predictive accuracy improves when adding EPD and EED traits to the model (R 2 = 75%). The RTA built a diagram using ESA, EED, and EPD as significant independent variables; of these, the most important variable was ESA (F = 50,295, df1 = 4, and df2 = 105; Adj. p<0.000) and the variation explained for EW was 74%. Likewise, the RTA showed that the highest egg weight (41.818 g) is obtained from eggs with a surface area > 59.03 cm 2 and a polar diameter > 5.10 cm. The proposed statistical methods can be used to reliably predict the egg weight of Guinea fowl.
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