Comparison of standard lactation curve models using fortnightly milk records in Frieswal cattle

Dohare, Amit Kumar; Verma, Med Ram; Perme, Bangkeng; Sharma, Varun; Gupta, Neha; Kshandakar, Shashank

doi:10.14202/vetworld.2014.831-834

Cited by 5 publications

(4 citation statements)

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“…The best fit due to gamma-type function model was reported by Boujenane [ 14 ] in Moroccan Holstein-Friesian dairy cows and Jingar et al [ 12 ] in Karan Fries (crossbred) cows. The superiority in variability explained by gamma-type function in multiparous (second or more lactations) cows was in agreement with findings of previous studies [ 18 , 19 ] but contrast with reports of Koçak and Ekiz [ 20 ] in Holstein cows and Dohare et al [ 21 ] in Frieswal cows (62% Friesian and 38% Sahiwal inheritance). However, lowest adjusted R 2 value and highest values of RMSE, AIC and BIC were observed for quadratic model fitting, which in accordance with reports of Cilek and Keskin [ 22 ] who fitted gamma-type function, mixed log, quadratic model, cubic and exponential and polynomial regression model to lactation curve of Simmental cows.…”

Section: Resultssupporting

confidence: 92%

Non-linear modelling to describe lactation curve in Gir crossbred cows

Bangar

Verma

2017

J Anim Sci Technol

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BackgroundThe modelling of lactation curve provides guidelines in formulating farm managerial practices in dairy cows. The aim of the present study was to determine the suitable non-linear model which most accurately fitted to lactation curves of five lactations in 134 Gir crossbred cows reared in Research-Cum-Development Project (RCDP) on Cattle farm, MPKV (Maharashtra). Four models viz. gamma-type function, quadratic model, mixed log function and Wilmink model were fitted to each lactation separately and then compared on the basis of goodness of fit measures viz. adjusted R2, root mean square error (RMSE), Akaike’s Informaion Criteria (AIC) and Bayesian Information Criteria (BIC).ResultsIn general, highest milk yield was observed in fourth lactation whereas it was lowest in first lactation. Among the models investigated, mixed log function and gamma-type function provided best fit of the lactation curve of first and remaining lactations, respectively. Quadratic model gave least fit to lactation curve in almost all lactations. Peak yield was observed as highest and lowest in fourth and first lactation, respectively. Further, first lactation showed highest persistency but relatively higher time to achieve peak yield than other lactations.ConclusionLactation curve modelling using gamma-type function may be helpful to setting the management strategies at farm level, however, modelling must be optimized regularly before implementing them to enhance productivity in Gir crossbred cows.

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Section: Resultssupporting

confidence: 92%

Non-linear modelling to describe lactation curve in Gir crossbred cows

Bangar

Verma

2017

J Anim Sci Technol

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“…The Wood model provided a physiological basis for the lactation curve, and the fit of the model was satisfactory (Cunha et al 2010). However, the Wood model has been shown to slightly underestimate the daily milk yield (Tozer and Huffaker 1999;Cilek and Keskin 2008;Banu et al 2012;Dohare et al 2014). The Wood model serves as a guide for further modelling and provides novel insights.…”

Section: Incomplete Lactationsmentioning

confidence: 97%

Estimation of 305-day milk yield from test-day records of Chinese Holstein cattle

Kong

et al. 2017

Journal of Applied Animal Research

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This study compared six models, namely the Gaines, Sikka, Nelder, Wood, Dhanoa and Hayashi models, for the estimation of 305 days milk yield in Chinese Holstein cattle. We compared their ability to reliably predict 305-day lactation yield from incomplete (3 or 6 test-day (TD)) records. Our findings revealed that the accuracies (ACC) were 0.6655-0.9948, 0.8652-0.9977 and 0.9169-0.9968, whereas the mean square errors (MSE) were 0.0121-2.4807, 0.0139-1.0716 and 0.0170-0.5528 when 3 TD records were used in the first, second and higher lactations, respectively; when 6 TD records were used, the ACC were 0.8800-0.9992, 0.8742-0.9998 and 0.7950-0.9996, whereas the MSE values were 0.0017-0.3348, 0.0011-0.8605 and 0.0021-1.4869 in the first, second and higher lactations, respectively. All the models were fitted more accurately with 6 TD than 3 TD records. Further analysis revealed that the curves made by the Nelder, Wood and Dhanoa models were close to the actual curves. These three models can be used to predict the 305-day yield for management decisions in farms and for the genetic evaluation of Chinese Holstein cattle.

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“…For instance, in countries like India, metabolic disorders such as ketosis and milk fever are prevalent among dairy cattle, particularly in intensive production systems. According to a study by Sharma et al (2017), the incidence of ketosis in dairy cattle in India ranges from 20% to 40%, leading to significant milk yield losses and increased risk of culling. Additionally, in countries like China, metabolic disorders in pigs, such as obesity and fatty liver syndrome, are becoming more common due to changes in feeding practices and genetic selection for leaner breeds.…”

Section: Introductionmentioning

confidence: 99%

Impact of Dietary Factors on Metabolic Disorders in Animals: A Case of Uganda

Achen

2024

JAH

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Purpose: The aim of the study was to investigate impact of dietary factors on metabolic disorders in Animals in Uganda Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that metabolic disorders such as obesity, insulin resistance, and fatty liver syndrome are prevalent among various livestock species in Uganda. The role of dietary components, including energy content, nutrient composition, and the presence of anti-nutritional factors, in contributing to the development and severity of these disorders cannot be understated. Moreover, socio-economic and environmental factors such as limited access to quality forage and the effects of climate change exacerbate the situation, posing additional challenges to maintaining optimal metabolic health in Ugandan livestock Unique Contribution to Theory, Practice and Policy: Nutritional Balancing Theory & Homeorhetic Regulation Theory may be used to anchor future studies on Impact of dietary factors on metabolic disorders in Animals in Uganda. Implement evidence-based dietary interventions tailored to the specific needs of different livestock species in Uganda. These interventions should aim to optimize nutrient composition, balance energy intake, and minimize the presence of anti-nutritional factors in animal feed. Promote the adoption of sustainable agricultural practices that enhance access to quality forage and mitigate the impact of climate change on animal nutrition. This may include strategies such as agroforestry, rotational grazing, and the cultivation of drought-resistant forage crops. Develop and enforce regulations governing the composition and labeling of animal feed in Uganda to ensure the quality and safety of feed ingredients. These regulations should include guidelines for the appropriate use of supplements, additives, and feed additives to minimize the risk of metabolic disorders in animals.

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Comparison of standard lactation curve models using fortnightly milk records in Frieswal cattle

Cited by 5 publications

References 12 publications

Non-linear modelling to describe lactation curve in Gir crossbred cows

Non-linear modelling to describe lactation curve in Gir crossbred cows

Estimation of 305-day milk yield from test-day records of Chinese Holstein cattle

Impact of Dietary Factors on Metabolic Disorders in Animals: A Case of Uganda

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