064 Development and application of a model of heat production for lactating sows

Cabezón, F. A.; Schinckel, A. P.; Richert, B. T.; Peralta, W. A.; Gandarillas, Mónica

doi:10.2527/asasmw.2017.064

Cited by 6 publications

(8 citation statements)

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“…The DFI's in this trial with genetically improved crossbred sows was substantially greater than the purebred sows of Shurson and Irwin (1992) . Current genetically improved crossbred sows have greater milk production, lactation feed intakes, overall metabolic rates and heat production than past sows ( Cabezon et al, 2017a ). The mean results of Cabezon et al (2016) were taken in the summer months in Chile.…”

Section: Resultsmentioning

confidence: 99%

“…Selection for increased litter size and improved milk production has increased the heat production of modern sows ( Stinn and Xin, 2014 ). Heat production is a function of both milk production and the heat increment of feeding ( NRC, 2012 ; Cabezón et al 2017a ). A model of heat production has estimated that greater than 90% of the variation in heat production among sows in late lactation is due to variation in DFI ( Cabezón et al, 2017a ).…”

Section: Resultsmentioning

confidence: 99%

“…Heat production is a function of both milk production and the heat increment of feeding ( NRC, 2012 ; Cabezón et al 2017a ). A model of heat production has estimated that greater than 90% of the variation in heat production among sows in late lactation is due to variation in DFI ( Cabezón et al, 2017a ). The variation in DFI from 14 to 28 d of lactation indicates substantial variation in the sows’ heat production during late lactation.…”

Section: Resultsmentioning

confidence: 99%

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Analysis of lactation feed intakes for sows with extended lactation lengths

Cabezón

Schinckel

León

et al. 2017

Translational Animal Science

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The objectives of this research were to quantify and model daily feed intakes to 28 d of lactation in modern sows. A total of 4,512 daily feed intake (DFI) records were collected for 156 Hypor sows from February 2015 to March 2016. The mean lactation length was 27.9 ± 2.0 d. The data included 9 parity 1, 33 parity 2 and 114 parity 3+ sows. Data were collected using a computerized feeding system (Gestal Solo, JYGA Technologies, Quebec, Canada). The feeding system was used to set an upper limit to DFI for the first 7 d of lactation. Overall, the least-squares means of a model including the random effect of sow indicated that DFI's continued to slowly increase to 28 d of lactation. The DFI data were fitted to Generalized Michaelis-Menten (GMM) and polynomial functions of day of lactation (t). The GMM function [DFIi,t (kg/d) = DFI0 + (DFIA − DFI0)(t/K)C/[1 + (t/K)C]] was fitted with 2 random effects for DFI (dfiAi) and intercept (dfi0i) using the NLMIXED procedure in SAS®. The polynomial function DFIi,t (kg/d) = [B0 + B1 t + B2 t2 + B3 t3 + B4 t4] was fitted with three random effects for B0, B1, and B2 using the MIXED procedure in SAS®. Fixed effects models of the two functions had similar Akaike's Information Criteria (AIC) values and mean predicted DFI's. The polynomial function with 3 random effects provided a better fit to the data based on R2 30 (0.81 versus 0.79), AIC (14,709 versus 15,158) and RSD (1.204 versus 1.321) values than the GMM function with two random effects. The random effect for B2 in the polynomial function allowed for the fitting of the function to lactation records that had decreased DFI after 15 d of lactation. The random effects for the polynomial function were used to sort the lactation records into three groups based on the derivative of the function at 21 d of lactation. Lactation records of the three groups had similar DFI the first two weeks of lactation (P > 0.40). The three groups of sows had substantially different DFI's after 18 d of lactation (P < 0.028). The differences in both actual and predicted DFI's between the three groups increased with each day of lactation to day 28 (P < 0.001). Mixed model polynomial functions can be used to identify sows with different patterns of DFI after 15 d of lactation.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Analysis of lactation feed intakes for sows with extended lactation lengths

Cabezón

Schinckel

León

et al. 2017

Translational Animal Science

Self Cite

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“…High summer temperature during farrowing increased sow mortality in low parity [65]. A cooling pad has been developed that efficiently removes excess of heat from lactating sows [66]. So, advanced equipment in farrowing barns and increased care during the peri-partum and lactation period could help decrease sow mortality and increase longevity.…”

Section: Peri-farrowing and Lactation Care In Paritymentioning

confidence: 99%

Farm data analysis for lifetime performance components of sows and their predictors in breeding herds

Koketsu

Iida

2020

Porc Health Manag

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Our objectives in this review are 1) to define the four components of sow lifetime performance, 2) to organize the four components and other key measures in a lifetime performance tree, and 3) to compile information about sow and herd-level predictors for sow lifetime performance that can help producers or veterinarians improve their decision making. First, we defined the four components of sow lifetime performance: lifetime efficiency, sow longevity, fertility and prolificacy. We propose that lifetime efficiency should be measured as annualized piglets weaned or annualized piglets born alive which is an integrated measure for sow lifetime performance, whereas longevity should be measured as sow life days and herd-life days which are the number of days from birth to removal and the number of days from date of first-mating to removal, respectively. We also propose that fertility should be measured as lifetime non-productive days, whereas prolificacy should be measured as lifetime pigs born alive. Second, we propose two lifetime performance trees for annualized piglets weaned and annualized piglets born alive, respectively, and show inter-relationships between the four components of the lifetime performance in these trees. Third, we describe sow and herd-level predictors for high lifetime performance of sows. An example of a sow-level predictor is that gilts with lower age at first-mating are associated with higher lifetime performance in all four components. Other examples are that no re-service in parity 0 and shorter weaning-to-first-mating interval in parity 1 are associated with higher fertility, whereas more piglets born in parity 1 is associated with higher prolificacy. It appears that fertility and prolificacy are independent each other. Furthermore, sows with high prolificacy and high fertility are more likely to have high longevity and high efficiency. Also, an increased number of stillborn piglets indicates that sows have farrowing difficulty or a herd health problem. Regarding herd-level predictors, large herd size is associated with higher efficiency. Also, herd-level predictors can interact with sow level predictors for sow lifetime performance. For example, sow longevity decreases more in large herds than small-to-mid herds, whereas gilt age at first-mating increases. So, it appears that herd size alters the impact of delayed gilt age at first-mating on sow longevity. Increased knowledge of these four components of sow lifetime performance and their predictors should help producers and veterinarians maximize a sow’s potential and optimize her lifetime productivity in breeding herds.

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“…The modern lactating sow is especially at risk of heat stress, as it has been heavily selected for increased productivity including litter size and litter weaning weight and thus resulting in increased heat production in comparison to past sows ( 30 ). Given that sows within a farrowing room may be at different stages of lactation, have different litter sizes and be producing heat unequally, individual sow cooling has the possibility to confer more production and welfare benefits than whole room cooling.…”

Section: Introductionmentioning

confidence: 99%

Effect of Floor Cooling on Behavior and Heart Rate of Late Lactation Sows Under Acute Heat Stress

et al. 2018

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Much U.S. swine production is in Köppen climate types classified as “hot-summer humid continental” and “humid subtropical.” As a result, farrowing sows are often exposed to temperatures above their upper critical temperature. This heat stress (HS) can affect sow welfare and productivity and have a negative economic impact. The study objective was to evaluate the impact of a cooling pad on sows' behavioral and heart rate responses to acute HS. Treatments were randomly allotted to ten multiparous sows to receive a constant cool water flow of 0.00 (CONTROL, n = 4), 0.25 (LOW, n = 2), 0.55 (MEDIUM, n = 2), or 0.85 (HIGH, n = 2) L/min for 100 min and replicated eight times, switching treatments so that each sow was exposed to each treatment. The cooling was initiated 1 h after the room reached 35°C for 100 min. Eating, drinking and nursing behaviors, postures, and heart rate were recorded before heating (Period 1), prior to cooling (Period 2), and during cooling (Period 3). There were no differences between LOW, MEDIUM, and HIGH flow rates for any periods on all behavioral and heart rate traits, so data were pooled (COOLED). There were no differences in any of the measures during Periods 1 and 2, except for the ratio of short term to long term heart rate variability (SD1:SD2) with higher values for CONTROL than COOLED sows in Period 2. During Period 3, CONTROL sows changed postures more frequently (11.5 ±1.6 vs. 5.1 ±1.6 changes per hour), spent more time drinker-pressing/drinking (4.4 ± 0.5 vs. 1.4 ± 0.4% of time), standing (6.6 ± 1.7 vs. 3.8 ± 1.6% of time), sitting (10.0 ± 1.2 vs. 4.0 ± 1.1), less time lying (83.0 ±1.8 vs. 92.0 ±1.7% of time), especially lying laterally (62.0 ± 5.6 vs. 75.0 ± 5.3% of time), than sows in all three cooling treatments (all P < 0.001). Heart rate during Period 3 was lower for COOLED sows compared to the CONTROL sows (100.2 ± 3.4 vs. 119.0 ± 4.0 beat per min, P < 0.001). Sows response to increased thermal load can be effectively reduced using water-cooled cooling pads, thereby improving sow comfort and welfare. The beneficial effects on behavior are noticeable from the lowest flow rate.

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064 Development and application of a model of heat production for lactating sows

Cited by 6 publications

References 0 publications

Analysis of lactation feed intakes for sows with extended lactation lengths

Analysis of lactation feed intakes for sows with extended lactation lengths

Farm data analysis for lifetime performance components of sows and their predictors in breeding herds

Effect of Floor Cooling on Behavior and Heart Rate of Late Lactation Sows Under Acute Heat Stress

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