Prediction of dry matter intake by meat sheep on tropical pastures

Gurgel, Antônio Leandro Chaves; Difante, Gelson dos Santos; Neto, João Virgínio Emerenciano; Santana, Juliana Caroline Santos; Fernandes, Patrick Bezerra; Santos, Geraldo Tadeu dos; Dias, Alexandre Menezes; Ítavo, Luís Carlos Vinhas; Ítavo, Camila Celeste Brandão Ferreira; Medeiros, Henrique Rocha de

doi:10.1007/s11250-021-02916-8

Cited by 10 publications

(5 citation statements)

References 22 publications

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“…The relationship between animal weight and DMI is well documented, as an animal's requirements increase in response to an increase in BW [43]. This relationship has been reported in various species, such as sheep [18,44,45], beef cattle [20,41,46], and dairy cattle [40]. Previous studies have used BW and/or BW 0.75 or empty body weight to predict DMI, and these variables have been shown to be significant predictors of nutrient intake.…”

Section: Discussionmentioning

confidence: 92%

“…In Brazil, most scientific studies on dairy cows use equations developed by international research committees, particularly the prediction equations reported by the National Research Council. However, research on beef cattle and sheep has shown that these equations may lead to underestimation or overestimation of results when used under conditions different from those in which they were developed [18,19]. Therefore, while these equations can be useful tools for predicting nutrient intake and milk characteristics, caution must be exercised when applying them to different conditions, as they may not accurately reflect the actual situation.…”

Section: Introductionmentioning

confidence: 99%

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Mathematical Models to Predict Dry Matter Intake and Milk Production by Dairy Cows Managed under Tropical Conditions

et al. 2023

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This study aimed to create an equation to predict dry matter intake (DMI) and milk production and N-ureic in the milk of dairy cows managed in tropical conditions in Brazil. We used 113 observations from three experiments using lactating Jersey, Girolando, and Holstein cows. The goodness of fit of the developed equations was evaluated using the coefficients of determination (r2) and root mean square error (RMSE). There was a positive correlation between body weight and milk yield (MY) of r = 0.73. The equation considered DMI to be the most important variable to estimate the MY (r2 = 0.65). Four equations were adjusted to estimate the DMI, where, by a stepwise procedure, the first variable included in the equation was the neutral detergent fibre intake, which explained 92% of the DMI of the cows. However, when the variables BW, MY, and milk fat were included in the equation, there was a reduction of 0.06 in RMSE and an increase in precision (r2 = 0.94). The nutrient intake, milk production, and characteristics prediction equations present satisfactory precision and accuracy for dairy cows managed in tropical conditions in Brazil.

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Section: Discussionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Mathematical Models to Predict Dry Matter Intake and Milk Production by Dairy Cows Managed under Tropical Conditions

et al. 2023

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“…Similarly, Gurgel et al (9) evaluated different models predicting DMI in tropical pastures using the adjustment factor proposed by McCall (61) and concluded that the equations do not accurately predict the DMI of meat sheep and generate overestimated values in tropical climate pastures. The authors proposed that the DMI estimate for lambs on tropical pasture should consider the following model (equation 6):…”

Section: Prediction Of Dry Matter Intake By Grazing Sheepmentioning

confidence: 99%

“…The main biometric measurements (Figure 3) evaluated in sheep are as follows (70) : withers height (WH)from the highest point of the withers to the ground (1); rump height (RH) the vertical distance from the highest point of the rump to the ground (2); body length (BL)from the scapulohumeral joint to the caudal part of the ischium (3); chest width (CW)the measurement between the tips of the scapulae (4); rump width (RW)the distance between the ischial tuberosities (5); heart girth (HG)taken around the chest cavity (6); abdominal circumference (AC)taken around the abdominal cavity (7); leg length (LL)taken from the ischial tuberosity to the ground (8); and leg circumference (LC)taken around the middle portion of the thigh (9). Some studies were conducted to develop linear and multiple equations to estimate the bodyweight of sheep from biometric measurements (65,66,71,72,73) .…”

Section: Prediction Of Body Weight and Carcass Traits Of Sheep Throug...mentioning

confidence: 99%

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Aspectos relacionados con la importancia del uso de modelos predictivos en la producción ovina. Revisión

Gurgel

Difante

Ítavo

et al. 2022

Rev. Mex. Cienc. Pecu.

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Sheep production systems face numerous challenges, which make decision-making a process fraught with risks and uncertainties. Modelling is a helpful tool in this respect, as it allows decision-makers to evaluate the behaviour of variables and their interrelationships, in addition to using previous or related information to predict results and simulate different scenarios. The advent of prediction models has made it possible to monitor the weight of an animal and determine the best time for its sale. Additionally, it allows producers to estimate the weights of the carcass and major marketable cuts before slaughter. All this information is directly associated with the profitability and success of the production activity. Therefore, in view of the different applications of mathematical models in production systems, this literature review examines concepts in modelling studies and the importance of using prediction models in meat sheep production. Furthermore, it addresses the practical application of modelling studies in predicting dry matter intake and carcass traits of meat sheep through correlated variables.

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