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The description of lactation curves by mathematical models could be an effective tool for management decisions in dairy cattle production systems. In this study the comparative fit of three models: negative exponential (í = (â 0 e -â1x ), incomplete gamma (í = â 0 x â1e-â2x ) and fifth order polynomial (í = â 0 + â 1 x + ... +â 5 x 5 ) was evaluated both between and within lactations using 8,763 milk yield records from 770 lactations for the first two models, and 7,228 records from 647 lactations for the third model. Milk yield records included the period 1997-2001 and were collected from five dairy farms located in Lima. The models were compared on the basis of the adjusted multiple coefficient of determination (R 2 aj ), the residual standard errors (EER), the standard errors of the predicted yield on day 305 (EE 305 ), and the residual scatter plots. Additionally, the effect of parity, calving season and the 1998 El Niño phenomenon (FEN) on the basic and derived parameters of the models were estimated using general lineal models. In terms of fitness, the models ranked fifth order polynomial > incomplete gamma > negative exponential both between and within lactations. However, the fifth order polynomial model had several shortcomings like higher EE 305 , a tendency of overestimate late lactation yields, and a requirement of a minimum number of records. These left incomplete gamma as the model of choice, being capable to explain 72% of the yield variation within lactations and having an EE 305 of only 3.3 kg. Parity and calving season affected significantly most of the basic and derived parameters of the models, whereas the FEN only affected the β 0 parameter of the exponential negative and the peak yield predicted by the incomplete gamma model. All of the three mentioned factors had significant effect on the total yield predicted for a 305 day-lactation.

El estudio tuvo por objetivo determinar el número promedio de folículos que llegan a ovular en cuyes de las razas Andina y Perú, con el fin de saber si la diferencia en el tamaño de camada entre estas razas se debe, en parte, al número de ovulaciones. Se utilizaron 15 animales de 10 semanas de edad por raza. Se consideró como día 0 del ciclo estral el día de la ovulación, el cual se determinó mediante citología vaginal y ausencia de la membrana vaginal. En el día 8 del ciclo estral se realizó citología vaginal para comprobar que los animales estaban en diestro y se sacrificaron para obtener los ovarios. Estos fueron fijados con formol buferado, se hicieron cortes seriados y se colorearon con hematoxilina eosina. Las muestras histológicas se observaron en microscopio óptico para el conteo de los cuerpos lúteos. En la raza Andina se encontró 3.6 ± 0.9 cuerpos lúteos y en la Perú se encontró 2.8 ± 0.9 cuerpos lúteos (p<0.05). La diferencia en el tamaño de camada entre las dos razas se podría deber, en parte, a que la raza Andina tiene mayor número de ovulaciones por ciclo estral que la raza Perú.

Calving -first service (IPPS) and calving -ovulation (IPPO) intervals were determined in 128 dairy cows from 5 intensively managed farms in Lima, Peru. Progesterone levels, determined by radioinmunoassay in a total of 1450 skim milk samples taken twice weekly from 15 days post partum until first artificial insemination, were used to determine IPPO. Field data on calving number (primiparous and multiparous), calving season (Spring September-December and Summer JanuaryApril), body condition (BCS evaluated monthly starting 30 days post partum) and milk production were collected. Multiple regression analysis (GLM), with IPPO and IPPS as dependent variables, and calving season, calving number, changes in BCS, milk production, heat detection efficiency and farm as independent variables, revealed an IPPO of 45 + 19.9 days and IPPS of 99.2 + 50. l days. IPPO was influenced by calving season and farm, and IPPS by heat detection efficiency, BCS at calving and farm.