Individual lactation curves in Siboney dairy cows of Cuba

Espinosa, Alejandro; Fundora, Dianelys González Peña; Iglesias, Danilo Guerra; Villavicencio, José Luis Espinoza; Pérez, Ricardo Ortega; Trujillo, Ariel Guillén; Serrano, Narciso Ávila

doi:10.22319/rmcp.v7i1.4147

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…According to Palacios Espinosa et al [ 63 ], the parameters related to the fitting performance reported by the Legendre polynomials were lower than those obtained for the Ali and Schaeffer (ALISCH) function. This behavior was referred to by Ali and Schaeffer [ 57 ], who found it difficult to find biological reasons why the functions of the Ali-Schaeffer and Legendre polynomials can detect dissimilar types of curves; however, this behavior is particularly useful for random regression analyses, where individual deviations from a curve are sought.…”

Section: Discussionmentioning

confidence: 99%

“…According to Palacios Espinosa et al [ 63 ] and Buttchereit et al [ 49 ], the Ali and Schaeffer (ALISCH) and Legendre models presented better-fitting properties than Wilmink’s exponential (WILMINK) model for fat, protein, and dry matter. These better-fitting properties may base on the better adjustment to the distribution patterns, indicating that the models with fewer parameters find more difficulty to model the variation occurring along the entire curve.…”

Section: Discussionmentioning

confidence: 99%

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Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison

Inostroza

González

Landi

et al. 2020

Animals

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SPSS syntax was described to evaluate the individual performance of 49 linear and non-linear models to fit the milk component evolution curve of 159 Murciano-Granadina does selected for genotyping analyses. Peak and persistence for protein, fat, dry matter, lactose, and somatic cell counts were evaluated using 3107 controls (3.91 ± 2.01 average lactations/goat). Best-fit (adjusted R2) values (0.548, 0.374, 0.429, and 0.624 for protein, fat, dry matter, and lactose content, respectively) were reached by the five-parameter logarithmic model of Ali and Schaeffer (ALISCH), and for the three-parameter model of parabolic yield-density (PARYLDENS) for somatic cell counts (0.481). Cross-validation was performed using the Minimum Mean-Square Error (MMSE). Model comparison was performed using Residual Sum of Squares (RSS), Mean-Squared Prediction Error (MSPE), adjusted R2 and its standard deviation (SD), Akaike (AIC), corrected Akaike (AICc), and Bayesian information criteria (BIC). The adjusted R2 SD across individuals was around 0.2 for all models. Thirty-nine models successfully fitted the individual lactation curve for all components. Parametric and computational complexity promote variability-capturing properties, while model flexibility does not significantly (p > 0.05) improve the predictive and explanatory potential. Conclusively, ALISCH and PARYLDENS can be used to study goat milk composition genetic variability as trustable evaluation models to face future challenges of the goat dairy industry.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison

Inostroza

González

Landi

et al. 2020

Animals

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“…Lactation curve can be defined as a biological process explained by a mathematical equation. It is useful for forecasting total production, for planning herd management using a reliable prediction tool, and for selecting animals considering the relationships among the different parts of the curve (Espinosa et al, 2016;Vinay-Vadillo et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Selection of dairy goats using milk recording and multivariate analysis in a family farming system

Frau,

Salinas,

Leguizamón Carate

et al. 2023

revagro

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Although dairy control is a widely used tool in herds with numerous animals (mainly cows), it is often neglected in small farms. The aim of the present work was to select the most suitable animals for milk production using dairy control and multivariate statistics. Results indicate a great dispersion of the data as a consequence of milk production variation from each goat. These results demonstrate the need to identify and select the most productive animals in order to have a selected and controlled flock. The analysis of hierarchical conglomerates showed that the herd can be divided into three groups: Cluster 1 is integrated by 31 goats with the highest productive parameters, above the herd average and together produce 59.1% of the accumulative milk yield; Cluster 2 consists of 24 animals whose production parameters are close to the current average of the herd and accumulates 27.7% of milk production and Cluster 3 groups animals with the lowest production. From the results obtained, it was possible to make the selection of the 55 most productive animals for milk production. This represents 64.70% of the herd and they are responsible for 86.8% of the total milk production.

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Physicochemical characterization of milk in 5/8 Holstein × 3/8 Zebu crossbred cows in tropical Mexico

Domínguez-Peregrino,

González-Garduño,

Ortiz-Pérez

2024

Rev. colomb. cienc. pecu.

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Background: Milk price depends on the concentration of milk components, which are influenced by several factors. Objective: To determine the effect of cow intrinsic variables on the physicochemical composition of raw milk in a dual-purpose production system. Methods: Twenty-five 5/8 Holstein-Friesian × 3/8 Zebu (5/8H3/8Z) lactating cows aged 5-10 years and 1-6 births were selected. Body condition score (BCS) and milk production were recorded. Milk samples were taken throughout lactation from each cow at mid-milking every eight days. Milk composition analysis was carried out using an automatic Lacticheck equipment. Results: Average daily milk production per cow was 4.10 L, with 1.03 g/cm3 density, 32.70 g/L fat, 34.50 g/L protein, 50.20 g/L lactose, 91.30 g/L non-fat solids, and 127.00 g/L total solids. The BCS influenced milk composition (p<0.01). Cows with higher BCS (>3.25) showed greater density, protein and lactose, while BCS between 2.00 to 2.50 positively affected fat content (39.20 g/L). Elder cows had increased milk production. In early lactation, milk production was the highest with less fat percentage. Conclusion: Although cow production per day is low, milk composition from 5/8H3/8Z cows complies with the standards established in the Mexican norm and is considered to be of good quality.

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Individual lactation curves in Siboney dairy cows of Cuba

Cited by 4 publications

References 24 publications

Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison

Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison

Selection of dairy goats using milk recording and multivariate analysis in a family farming system

Physicochemical characterization of milk in 5/8 Holstein × 3/8 Zebu crossbred cows in tropical Mexico

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