Effect of lactation trimester and parity on eating behavior, milk production and efficiency traits of dairy cows

Abstract

There is absence knowledge about the effects of lactation trimester and parity on eating behavior, production and efficiency of dairy cows. Objective of this study was to identify and characterize in 340 dairy cows, the 20% high efficient (HE), 20% low efficient (LE) and 60% mid efficient (ME) cows according to their individual residual feed intake (RFI) values, within and between lactation trimesters and between 1st and 2nd parities. Efficiency effect within each lactation trimester, was exhibited in daily dry matter intake (DMI), eating rate and meal size, that were the highest in LE cows, moderate in the ME cows and lowest in the HE group. Daily eating time, meal frequency, yields of milk and energy-corrected milk (ECM) and BW were similar in the three efficiency groups within each trimester. The lower efficiency of the LE cows in each trimester attributes to their larger metabolic energy intake, heat production and energy losses. In subgroup of 52 multiparous cows examined along their 1st and 2nd trimesters, milk and ECM production, DMI, eating behavior and efficiency traits were similar with high Pearson’s correlation (r=0.78 to 0.89) between trimesters. In another subgroup of 42 multiparous cows measured at their 2nd and 3rd trimesters, milk and ECM yield, DMI and eating time were reduced (P<0.01) at the 3rd trimester, but eating rate, meal frequency and meal size remained similar with high Pearson’s correlation (r=0.74 to 0.88) between trimesters. In subgroup of 26 cows measured in 1st and 2nd parities, DMI, BW, milk and ECM yield, and ECM/DMI increased in the 2nd lactation, but eating behavior and RFI traits were similar in both parities. These findings encourage accurate prediction of DMI based on a model that includes eating behavior parameters, together with individual measurement of ECM production. This can be further used to identify HE cows in commercial herd, a step necessary for potential genetic selection program aimed to improve herd efficiency.

Individual dairy cow management: achievements, obstacles and prospects

“…The performance parameters used for the calculation are: average food consumption, average milk production, average milk composition, average BW, average body condition. One can argue that there is no such thing as an ‘average cow’ because of individual variations in production efficiency (Ben Meir et al ., 2018, 2019). In terms of ration density, under this feeding regime, around half of the cows are overfed and half of them are underfed.…”

“…3, daily running averages over 5 d of milk energy correlates significantly with the running daily average of food intake over 5 d. Hence, milk energy measured on line, which makes rationing concentrates according to energy balance possible (Maltz et al ., 2013), can also improve modeling individual food intake. However, even the best modeling results cannot predict food intake of the marginal cows on both sides of production efficiency scale (Ben Meir et al ., 2018, 2019). Therefore, a feedback system has to be incorporated into the concentrates rationing process, which would evaluate the actual results of the rationing decisions compared to those expected.…”

Cytological endometritis diagnosis in primiparous versus multiparous dairy cows

“…Cow parity is another factor that may potentially affect the defined PMN percent threshold. Primiparous and multiparous cows differ in many aspects, such as postpartum uterine involution (Bastidas et al, 1984;Melendez et al, 2004;Zhang et al, 2010), metabolism and energy balance (Morales Piñeyrúa et al, 2018;Gärtner et al, 2019;Yehia et al, 2020), milk production (Morales Piñeyrúa et al, 2018;Ben Meir et al, 2019;O'Sullivan et al, 2019), ovarian function (Tanaka et al, 2008;López-Helguera et al, 2016;Morales Piñeyrúa et al, 2018), reproductive performance (Fodor et al, 2019;Rojas Canadas et al, 2020), andmanagement (McDougall et al, 2014). Therefore, several of the studies cited above accounted for the cows' parity in their statistical models (whether it was primiparous or multiparous) while establishing a %PMN threshold for the diagnosis of CEM in all cows together (Kasimanickam et al, 2004;Barlund et al, 2008;Madoz et al, 2013).…”

Postpartum Fatigue and Inhibited Lactation

“…Lactation and milk release have been extensively investigated. Parity (Ben Meir et al, 2019), maternal age, body mass index (Fernandes et al, 2012), food intake (Johansen et al, 2018), mother-infant separation (Klemming et al, 2021), and infant sucking were reported to interact with lactation in humans and other mammals. Physiological status (Tallo-Parra et al, 2018) including postpartum depression (Mohamad Yusuff et al, 2016) and fear and anxiety (Janczak et al, 2003) have a significant influence on milk synthesis.…”