Abstract

Simple SummarySome studies have confirmed the variation in milk profiles when dairy cows show estrus. However, only a few milk components, such as fat, protein, and lactose, have been investigated so far, and thus any changes in the many other parts of milk’s composition due to estrus are unknown. Milk mid-infrared (MIR) spectra consist of wavenumbers, which provide insight into the chemical composition of milk. The MIR spectrum reflects the global composition of milk, but this information is currently underused. In this study, we considered MIR wavenumbers as traits, and directly studied the spectral information as a way to study the estrus of dairy cows linked to milk composition. This research provides a deeper understanding of the milk MIR spectrum and may lead to new approaches for estrus detection in dairy cows from routine milk analysis, thereby guiding an opportune insemination time.Milk produced by dairy cows is a complex combination of many components. However, at present, changes in only a few milk components (e.g., fat, protein, and lactose) during the estrus cycle in dairy cows have been documented. Mid-infrared (MIR) spectroscopy is a worldwide method routinely used for milk analysis, as MIR spectra reflect the global composition of milk. Therefore, this study aimed to investigate the changes in milk MIR spectra and milk production traits (fat, protein, lactose, urea, total solids (TS), and solid not fat (SnF)) due to estrus. Cows that were successfully inseminated, leading to conception, were included. Cows confirmed to be pregnant were considered to be in estrus at the day of insemination (day 0). A general linear mixed model, which included the random effect of cows, the fixed classification effects of parity number, days in relation to estrus, as well as the interaction between parity number and days in relation to estrus, was applied to investigate the changes in milk production traits and 1060 milk infrared wavenumbers, ranging from 925 to 5011 cm−1, of 371 records from 162 Holstein cows on the days before (day −3, day −2, and day −1) and on the day of estrus (day 0). The days in relation to estrus had a significant effect on fat, protein, urea, TS, and SnF, whose contents increased from day −3 to day 0. Lactose did not seem to be significantly influenced by the occurrence of estrus. The days in relation to estrus had significant effects on the majority of the wavenumbers. Besides, we found that some of the wavenumbers in the water absorption regions were significantly changed on the days before and on the day of estrus. This suggests that these wavenumbers may contain useful information. In conclusion, the changes in the milk composition due to estrus can be observed through the analysis of the milk MIR spectrum. Further analyses are warranted to more deeply explore the potential use of milk MIR spectra in the detection of estrus.

Highlights

  • Good reproductive management has an immediate effect on milk production and the economic success in dairy cattle farms

  • Akdag et al [20] compared the difference of lactose between the estrus period and 3 days after estrus, and found that estrus had no significant effect on lactose, which is in agreement with the present study

  • This study showed that the composition of fat, protein, urea, total solid (TS), and solid not fat (SnF) in milk significantly changed on the days before and on the day of estrus, whereas lactose showed no significant difference

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Summary

Introduction

Good reproductive management has an immediate effect on milk production and the economic success in dairy cattle farms. Efficient estrus detection and subsequently an opportune insemination time are fundamental components of a successful reproductive management program [1]. The traditional methods of visual estrus detection are time-consuming, ineffective, and increase the workload of farm staff. Several innovative and automated tools have been developed to detect estrus, such as pressure-sensing devices [3], body temperature detectors [4], neck-mounted collars to detect physical activity [5], and pedometers [6]. These technologies may require potentially burdensome investments in equipment and management

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